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The revised What Works Clearinghouse review found that the second-year result also failed its corrected significance threshold. Each year involved a new cohort, rather than a second year of exposure for the same students.", "category": "general benefit", "unexpected": false, "purpose": "CTAI was built to teach first-year algebra with personalized, mastery-based software. The test-score gain is that purpose.", "system": "Cognitive Tutor Algebra I, with an ACT-R-based cognitive model, classroom instruction, and curriculum materials", "model_version": null, "developer": "Carnegie Learning", "deployer": "Participating public and Catholic parochial schools in 51 districts across seven states (study sites)", "location": null, "domain": "Education", "segment": "Secondary-school algebra", "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The second high-school cohort had a measurable algebra gain, although the corrected significance test was inconclusive." } ], "ai_role": { "status": "assessed", "statement": "The tutor provided adaptive exercises and feedback within a complete algebra curriculum. The trial did not separate its contribution from classroom teaching, materials, or training." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Pane, John F., Beth Ann Griffin, Daniel F. McCaffrey, and Rita Karam. Educational Evaluation and Policy Analysis 36, no. 2 (2014): 127–44. https://doi.org/10.3102/0162373713507480.", "title": "Effectiveness of Cognitive Tutor Algebra I at Scale", "url": "https://journals.sagepub.com/doi/10.3102/0162373713507480", "date": null, "written_by": "independent", "quote": null }, { "kind": "report", "citation": "Pane, John F., et al. Addendum to “Effectiveness of Cognitive Tutor Algebra I at Scale.” RAND WR-1050, May 30, 2014.", "title": "Addendum to Effectiveness of Cognitive Tutor Algebra I at Scale", "url": "https://www.rand.org/content/dam/rand/pubs/working_papers/WR1000/WR1050/RAND_WR1050.pdf", "date": "2014-05-30", "written_by": "independent", "quote": null }, { "kind": "report", "citation": "What Works Clearinghouse. Cognitive Tutor® Algebra I. June 2016, revised December 21, 2016.", "title": "Cognitive Tutor® Algebra I", "url": "https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_cognitivetutor_122116.pdf", "date": "2016-12-21", "written_by": "independent", "quote": null }, { "kind": "peer-reviewed study", "citation": "Ritter, Steven, John R. Anderson, Kenneth R. Koedinger, and Albert Corbett. Psychonomic Bulletin & Review 14, no. 2 (2007): 249–55. https://doi.org/10.3758/BF03194060.", "title": "Cognitive Tutor: Applied Research in Mathematics Education", "url": "https://link.springer.com/content/pdf/10.3758/BF03194060.pdf", "date": null, "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Daugherty, Lindsay, Andrea Phillips, John F. Pane, and Rita Karam. Analysis of Costs in an Algebra I Curriculum Effectiveness Study. RAND TR-1171-1-DEIES, 2012.", "title": "Analysis of Costs in an Algebra I Curriculum Effectiveness Study", "url": "https://www.rand.org/content/dam/rand/pubs/technical_reports/2012/RAND_TR1171-1.pdf", "date": "2012-07-12", "written_by": "independent", "quote": null }, { "kind": "peer-reviewed study", "citation": "Mann, Charlotte Z., Jiaying Wang, Adam Sales, and Johann A. Gagnon-Bartsch. “Using Publicly Available Auxiliary Data to Improve Precision of Treatment Effect Estimation in a Randomized Efficacy Trial.” Proceedings of the 17th International Conference on Educational Data Mining, 2024, short paper 52.", "title": "Using Publicly Available Auxiliary Data to Improve Precision of Treatment Effect Estimation in a Randomized Efficacy Trial", "url": "https://educationaldatamining.org/EDM2024/proceedings/2024.EDM-short-papers.52/index.html", "date": null, "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A curriculum that combined intelligent tutoring with classroom instruction", "Teacher training and regular computer sessions", "School-pair randomization over two annual cohorts" ], "must_hold": [ "Staff and equipment for regular tutor use", "Time to implement the curriculum" ], "echoes": [] }, "paired_incident": null, "headline": "Higher algebra scores in the trial’s second year", "metric": "Second-year algebra gain: 0.21 standard deviations; inconclusive after correction", "comparator": { "against": "Schools using their usual algebra curriculum", "before": "Comparison schools in the same implementation year", "after": "Second high-school cohort: +0.21 standard deviations; p = .04 before correction, not significant at the Clearinghouse’s corrected threshold of .025", "basis": "measured", "quote": "the WWC found that this difference was no longer statistically significant.", "url": "https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_cognitivetutor_122116.pdf" }, "later": { "status": "challenged", "date": "2016-12-21", "note": "The revised What Works Clearinghouse review rated the wider algebra evidence as mixed. It found that this trial’s second-year estimate was not statistically significant after correction for multiple comparisons.", "quote": null, "url": "https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_cognitivetutor_122116.pdf" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.rand.org/pubs/research_briefs/RB9746.html; https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_cognitivetutor_122116.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.carnegielearning.com/contact/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://journals.sagepub.com/doi/10.3102/0162373713507480", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent peer-reviewed studies, three independent reports and the makers' peer-reviewed study. 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"value_present", "value": { "kind": "text", "text": "These are estimated adoption costs, not the trial’s discounted invoices." }, "provenance": { "kind": "source_review", "basis": "pp. 10–11.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "These are estimated adoption costs, not the trial’s discounted invoices." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "School districts would pay for materials, software, equipment, and training." }, "provenance": { "kind": "source_review", "basis": "Cost methods.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "School districts would pay for materials, software, equipment, and training." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Conclusion.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0005" ], "reviewed_on": "2026-10-25" }, "reason": "The analysis does not estimate financial returns or a payback period.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The analysis does not estimate financial returns or a payback period." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "RAND combined vendor prices and district reports, annualized the costs, and weighted them by the number of schools." }, "provenance": { "kind": "source_review", "basis": "pp. 5–11, 26–28.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "RAND combined vendor prices and district reports, annualized the costs, and weighted them by the number of schools." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The software’s separate contribution was not estimated." }, "provenance": { "kind": "source_review", "basis": "C1 intervention and design.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The software’s separate contribution was not estimated." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Schools continued the algebra curriculum that they normally used." }, "provenance": { "kind": "source_review", "basis": "C1 methods.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Schools continued the algebra curriculum that they normally used." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Researchers assigned matched pairs of schools to Cognitive Tutor or their usual curriculum." }, "provenance": { "kind": "source_review", "basis": "C1 methods.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers assigned matched pairs of schools to Cognitive Tutor or their usual curriculum." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "The revised high-school estimate was −0.07 standard deviations in year one and +0.21 in year two." }, "provenance": { "kind": "source_review", "basis": "C2 Table 3, preferred model.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The revised high-school estimate was −0.07 standard deviations in year one and +0.21 in year two." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Students generally used the tutor for about 40% of class time during the school year." }, "provenance": { "kind": "source_review", "basis": "C1 intervention description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students generally used the tutor for about 40% of class time during the school year." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0214-E01" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Identifiers assigned to the evaluations described here.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002", "AIBD-0214-source-0003", "AIBD-0214-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0214-E01" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Students took standardized algebra readiness and proficiency tests. Researchers adjusted the end-of-year comparison for baseline scores and other characteristics." }, "provenance": { "kind": "source_review", "basis": "C1 measures; C2 analysis.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students took standardized algebra readiness and proficiency tests. Researchers adjusted the end-of-year comparison for baseline scores and other characteristics." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Algebra proficiency." }, "provenance": { "kind": "source_review", "basis": "C1 measures.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Algebra proficiency." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The 2024 reanalysis provides public code. Its full replication data are withheld to protect the participating schools’ identities." }, "provenance": { "kind": "source_review", "basis": "Mann et al. (2024), §7; the linked aeis-aux-rct repository, README.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The 2024 reanalysis provides public code. Its full replication data are withheld to protect the participating schools’ identities." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "The trial included 73 high schools and 74 middle schools. The revised analysis excluded students without observed baseline tests." }, "provenance": { "kind": "source_review", "basis": "C1 sample; C2 pp. 1–3.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial included 73 high schools and 74 middle schools. The revised analysis excluded students without observed baseline tests." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The second-year estimate depended on adjustment for student characteristics. Its p-value of .04 did not meet the Clearinghouse’s corrected threshold of .025." }, "provenance": { "kind": "source_review", "basis": "C2 Table 3; C3 p. 31, n. c.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0002", "AIBD-0214-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The second-year estimate depended on adjustment for student characteristics. Its p-value of .04 did not meet the Clearinghouse’s corrected threshold of .025." } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "The revised Clearinghouse review rated the wider algebra evidence as mixed and removed this trial’s statistical significance after correcting for multiple comparisons." }, "provenance": { "kind": "source_review", "basis": "p. 6; p. 31, n. c.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The revised Clearinghouse review rated the wider algebra evidence as mixed and removed this trial’s statistical significance after correcting for multiple comparisons." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Teachers received three days of training before implementation and another day during the school year." }, "provenance": { "kind": "source_review", "basis": "C1 intervention description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Teachers received three days of training before implementation and another day during the school year." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0214" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "Schools needed computers for regular sessions, the curriculum materials, and trained algebra teachers." }, "provenance": { "kind": "source_review", "basis": "C1 intervention description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Schools needed computers for regular sessions, the curriculum materials, and trained algebra teachers." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Students who took Algebra I at participating high schools." }, "provenance": { "kind": "source_review", "basis": "C2 Table 3.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students who took Algebra I at participating high schools." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "The revised analysis included 11,066 high-school students and 5,519 middle-school students across two annual cohorts." }, "provenance": { "kind": "source_review", "basis": "C2 Tables 1–2.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The revised analysis included 11,066 high-school students and 5,519 middle-school students across two annual cohorts." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved learning." }, "provenance": { "kind": "source_review", "basis": "C2 Tables 3–4.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved learning." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "High-school algebra scores improved in the second year of implementation." }, "provenance": { "kind": "source_review", "basis": "C2 Table 3.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "High-school algebra scores improved in the second year of implementation." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "The reported gain was in the second high-school cohort. First-year and middle-school estimates were not statistically significant." }, "provenance": { "kind": "source_review", "basis": "C2 Tables 3–4.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reported gain was in the second high-school cohort. First-year and middle-school estimates were not statistically significant." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Each cohort studied Algebra I for one school year." }, "provenance": { "kind": "source_review", "basis": "C1 methods.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Each cohort studied Algebra I for one school year." } }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Students." }, "provenance": { "kind": "source_review", "basis": "C1 sample description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "The second-year gain was positive, but it was not statistically significant after the Clearinghouse adjusted for multiple comparisons." }, "provenance": { "kind": "source_review", "basis": "p. 31, Table B.1, n. c.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The second-year gain was positive, but it was not statistically significant after the Clearinghouse adjusted for multiple comparisons." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Schools incurred higher adoption costs and needed time for implementation. The trial did not show significant gains in every setting." }, "provenance": { "kind": "source_review", "basis": "C1 discussion; C2 Tables 3–4; C5 Tables 3.13–3.14.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002", "AIBD-0214-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Schools incurred higher adoption costs and needed time for implementation. The trial did not show significant gains in every setting." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Improved algebra learning was the intended benefit." }, "provenance": { "kind": "source_review", "basis": "C1 introduction.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved algebra learning was the intended benefit." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "The study covered 147 schools in 51 districts across Alabama, Connecticut, Kentucky, Louisiana, Michigan, New Jersey, and Texas." }, "provenance": { "kind": "source_review", "basis": "C1 sample description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study covered 147 schools in 51 districts across Alabama, Connecticut, Kentucky, Louisiana, Michigan, New Jersey, and Texas." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "Cognitive Tutor combined classroom algebra lessons with practice that adapted to each student." }, "provenance": { "kind": "source_review", "basis": "C1 intervention description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Cognitive Tutor combined classroom algebra lessons with practice that adapted to each student." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "start": "2007", "end": "2009", "precision": "school years", "display": "2007–08 and 2008–09", "refs": [ "AIBD-0214-source-0006" ], "current_date_observed": "2013-11-18", "instruction": "Use the observed result period for the case date. Keep the full study period separately; the normalized sort date does not imply a more precise observation.", "observed_result_period": "2009", "observed_result_precision": "year", "observed_result_basis": "End of the second school year, 2008–09." } }, "provenance": { "kind": "source_review", "basis": "Original study timing.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial covered the 2007–08 and 2008–09 school years." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "text", "text": "The Clearinghouse reviewed five qualifying Algebra I studies and rated their combined results as mixed." }, "provenance": { "kind": "source_review", "basis": "Overview and pp. 5–6.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Clearinghouse reviewed five qualifying Algebra I studies and rated their combined results as mixed." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "Schools needed regular computer sessions, trained teachers, and time to implement the curriculum." }, "provenance": { "kind": "source_review", "basis": "C1 intervention and implementation discussion.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Schools needed regular computer sessions, trained teachers, and time to implement the curriculum." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.rand.org/pubs/research_briefs/RB9746.html; https://ies.ed.gov/ncee/wwc/Docs/InterventionReports/wwc_cognitivetutor_122116.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.carnegielearning.com/contact/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://journals.sagepub.com/doi/10.3102/0162373713507480", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Education." }, "provenance": { "kind": "source_review", "basis": "C1 intervention description.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Education." } }, "sources[].access_version": { "state": "value_present", "value": { "kind": "text", "text": "The original manuscript, addendum, revised review, mechanism paper, and cost report were inspected. A later dataset paper supplies the school-year dates." }, "provenance": { "kind": "source_review", "basis": "Methods, results, and Tables 2–5.; pp. 1–6, Tables 1–4.; p. 6; pp. 23–24, Appendix A.4; p. 31, Table B.1, n. c.; pp. 249–52.; pp. ix–x, 5–11, 26–28; Tables 3.13–3.14.; §2 establishes the school years; §7 and the linked code repository describe available replication materials.", "record_fields": [], "source_refs": [ "AIBD-0214-source-0001", "AIBD-0214-source-0002", "AIBD-0214-source-0003", "AIBD-0214-source-0004", "AIBD-0214-source-0005", "AIBD-0214-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original manuscript, addendum, revised review, mechanism paper, and cost report were inspected. 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He was treated by a Chalmers University of Technology / Sahlgrenska University Hospital team (both in Gothenburg; the paper does not name the treatment site). Treatment ran for 18 weeks from March 2013. The exact start date is not reported. Stump surface electromyography was classified by myoelectric pattern recognition (linear discriminant analysis and a multilayer perceptron in the open-source BioPatRec platform). It drove a virtual limb shown in augmented reality and a racing game. After four weeks he reported episodes of lower pain intensity, after ten weeks near-absent pain developing into completely pain-free periods. His phantom fist relaxed and he could move the phantom freely (Frontiers in Neuroscience, 2014).", "category": "benefit created", "unexpected": false, "purpose": "Treat phantom limb pain by letting the patient execute phantom movements decoded from stump muscle activity", "system": "Phantom motor execution: BioPatRec myoelectric pattern recognition (LDA and MLP classifiers) driving augmented/virtual reality and a racing game", "model_version": "BioPatRec, LDA one-vs-one and MLP per degree of freedom", "developer": "Chalmers University of Technology, Biomedical Engineering Division (academic lab; study part-funded by Integrum AB)", "deployer": "Chalmers University of Technology and Sahlgrenska University Hospital, Gothenburg (inferred from author affiliations; the paper does not name the treatment site)", "location": "Gothenburg, Sweden (inferred from author affiliations)", "domain": "Rehabilitation medicine / chronic pain", "segment": "Upper-limb amputees with phantom limb pain", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "An identifiable patient with 48 years of treatment-resistant pain reached pain-free periods and regained phantom movement. The case gives no long-term follow-up, so a durable life-changing effect is not established." }, { "group": "societal", "depth": 1, "reason": "Single case. The same group later ran a 14-patient trial. No population effect is documented." } ], "ai_role": { "status": "assessed", "statement": "The pattern-recognition classifiers turn stump EMG into predicted phantom movements that the virtual limb executes. The authors argue that this engagement of motor circuitry, rather than a mirror of the contralateral limb, is the therapeutic mechanism. So the AI component is central, though the single-case design cannot isolate it." }, "evidence": [ { "kind": "case report", "citation": "Ortiz-Catalan M, Sander N, Kristoffersen MB, Håkansson B, Brånemark R (2014). Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient. Frontiers in Neuroscience 8:24.", "title": "Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC3935120/", "date": "2014-02-25", "written_by": "makers", "quote": "The sustained level of pain reported by the patient was gradually reduced to complete pain-free periods." }, { "kind": "case report", "citation": "Ortiz-Catalan M, et al. (2014). Frontiers in Neuroscience 8:24 (methods).", "title": "Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: a case study of a chronic PLP patient", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC3935120/", "date": "2014-02-25", "written_by": "makers", "quote": "Individual and simultaneous phantom movements were predicted using myoelectric pattern recognition and were then used as input for VR and AR environments, as well as for a racing game." }, { "kind": "peer-reviewed study", "citation": "Ortiz-Catalan M, Guðmundsdóttir RA, Kristoffersen MB, et al. (2016). Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain. Lancet 388(10062):2885-2894.", "title": "Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain", "url": "https://europepmc.org/abstract/MED/27916234", "date": "2016-12-02", "written_by": "makers", "quote": "Phantom limb pain decreased from pre-treatment to the last treatment session by 47% (SD 39; absolute mean change 1·0 [0·8]; p=0·001) for weighted pain distribution" } ], "replication": { "produced_by": [ "Decodable residual muscle activity in the stump", "Classifier-driven virtual limb that responds to the patient's own effort", "Repeated sessions with gamified motor execution" ], "must_hold": [ "Patient can produce distinguishable EMG patterns for phantom movements", "Weekly or twice-weekly sessions sustained over months", "Augmented-reality display of the restored limb" ], "echoes": [ { "date": "2014-09-15", "setting": "Single-group trial of 14 patients with intractable phantom limb pain at three clinics in Sweden and one in Slovenia", "model_version": "Phantom motor execution with machine learning and AR", "outcome": "recurred", "source": "Ortiz-Catalan et al. (2016) Lancet, PMID 27916234" } ] }, "paired_incident": null, "headline": "BioPatRec pattern recognition eases 48-year phantom limb pain", "metric": "after ten weeks near-absent pain developing into completely pain-free periods", "comparator": { "against": "the patient's pain after 48 years of conventional treatments (mirror therapy, drugs, acupuncture, hypnosis)", "before": "constant burning pain of an intensity of 3 on a scale from 0 to 10 (SF-MGPQ)", "after": "gradually reduced to complete pain-free periods", "basis": "measured", "quote": "The sustained level of pain reported by the patient was gradually reduced to complete pain-free periods.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC3935120/" }, "later": { "status": "scaled", "date": "2016-12-02", "note": "A single-group trial of 14 patients at four clinics in Sweden and Slovenia reported significant reductions in phantom limb pain that held at six-month follow-up.", "quote": "Between Sept 15, 2014, and April 10, 2015, 14 patients with intractable chronic phantom limb pain, for whom conventional treatments failed, were enrolled.", "url": "https://europepmc.org/abstract/MED/27916234" }, "value": null, "developer_country": "Sweden", "deployer_country": "Sweden", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the account, deployer and location to say that the Gothenburg treatment site is inferred from author affiliations because the case report never names it; dropped the unsupported claim that the case “motivated” the 14-patient trial; restored the full source titles on evidence 2 and 3; and noted the Integrum AB funding and affiliation in the taxonomy note.", "source": "Ortiz-Catalan et al. 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Lancet 388(10062):2885-2894.", "title": "Phantom motor execution facilitated by machine learning and augmented reality as treatment for phantom limb pain: a single group, clinical trial in patients with chronic intractable phantom limb pain", "url": "https://europepmc.org/abstract/MED/27916234", "date": "2016-12-02", "written_by": "makers", "quote": "Phantom limb pain decreased from pre-treatment to the last treatment session by 47% (SD 39; absolute mean change 1·0 [0·8]; p=0·001) for weighted pain distribution" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 72-year-old with 48 years of intractable phantom limb pain reached pain-free periods after ML-driven phantom motor execution.", "account": "A 72-year-old man's below-elbow amputation in 1965 left him with 48 years of phantom limb pain, resistant to mirror therapy, drugs, acupuncture and hypnosis. He was treated by a Chalmers University of Technology / Sahlgrenska University Hospital team (both in Gothenburg; the paper does not name the treatment site). Treatment ran for 18 weeks from March 2013. The exact start date is not reported. Stump surface electromyography was classified by myoelectric pattern recognition (linear discriminant analysis and a multilayer perceptron in the open-source BioPatRec platform). It drove a virtual limb shown in augmented reality and a racing game. After four weeks he reported episodes of lower pain intensity, after ten weeks near-absent pain developing into completely pain-free periods. His phantom fist relaxed and he could move the phantom freely (Frontiers in Neuroscience, 2014)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The classifiers converted muscle signals into movements of a virtual limb." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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He was treated by a Chalmers University of Technology / Sahlgrenska University Hospital team (both in Gothenburg; the paper does not name the treatment site). Treatment ran for 18 weeks from March 2013. The exact start date is not reported. Stump surface electromyography was classified by myoelectric pattern recognition (linear discriminant analysis and a multilayer perceptron in the open-source BioPatRec platform). It drove a virtual limb shown in augmented reality and a racing game. After four weeks he reported episodes of lower pain intensity, after ten weeks near-absent pain developing into completely pain-free periods. His phantom fist relaxed and he could move the phantom freely (Frontiers in Neuroscience, 2014).", "replication": { "produced_by": [ "Decodable residual muscle activity in the stump", "Classifier-driven virtual limb that responds to the patient's own effort", "Repeated sessions with gamified motor execution" ], "must_hold": [ "Patient can produce distinguishable EMG patterns for phantom movements", "Weekly or twice-weekly sessions sustained over months", "Augmented-reality display of the restored limb" ], "echoes": [ { "date": "2014-09-15", "setting": "Single-group trial of 14 patients with intractable phantom limb pain at three clinics in Sweden and one in Slovenia", "model_version": "Phantom motor execution with machine learning and AR", "outcome": "recurred", "source": "Ortiz-Catalan et al. 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It applies a support-vector-machine language model to geotagged tweets to rank Las Vegas food venues by foodborne-illness risk. During the first three months environmental health specialists inspected 142 venues, half chosen by nEmesis, half under the standard protocol. Inspectors were blind to which was which. Adaptive inspections uncovered 9 demerits per inspection versus 6 (p = 0.019). They found 11 venues graded C or worse versus 7 for controls, a 64% improvement. The abstract summarizes this as 63% more effective. Side findings included an unpermitted seafood establishment and a food handler working with an influenza-like illness. The authors estimate, from CDC outbreak averages, that adaptive inspections saved 71 infections and 4.4 hospitalizations over the three months. They estimate all of Las Vegas's 35,000+ annual inspections made adaptive could prevent over 9,126 cases and 557 hospitalizations a year. SNHD performed 5 foodborne-illness investigations between 2 January and 31 March 2015, against 11 in the same window the year before.", "category": "benefit created", "unexpected": false, "purpose": "Rank Las Vegas food venues by predicted foodborne-illness risk, inferred from Twitter posts, so that health inspectors can prioritize the riskiest venues.", "system": "nEmesis (SVM language model over geotagged tweets with a web interface for inspectors)", "model_version": null, "developer": "University of Rochester (Adam Sadilek, Henry Kautz and colleagues)", "deployer": "Southern Nevada Health District", "location": "Las Vegas, United States", "domain": "Food safety / public health", "segment": "Restaurant inspection targeting", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "In 142 blinded inspections the nEmesis arm found 9 vs 6 demerits per inspection (p = 0.019). It found 11 vs 7 venues graded C or worse, an unpermitted seafood establishment and a sick food handler." }, { "group": "societal", "depth": null, "reason": "The 71 infections and 4.4 hospitalizations said to be saved are estimates from CDC outbreak averages. The drop in foodborne-illness investigations (5 vs 11) is an uncontrolled year-on-year comparison, not a measured outcome." } ], "ai_role": { "status": "assessed", "statement": "The AI chose which venues to inspect. The comparison was a controlled double-blind design with 142 venues split between nEmesis and standard protocol. So the difference in findings is attributable to the AI's venue selection. The developers (Rochester) are distinct from the deployer (SNHD), though SNHD staff co-authored the paper. The paper was peer-reviewed as an IAAI deployed paper." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Sadilek A, Kautz H, DiPrete L, Labus B, Portman E, Teitel J, Silenzio V. Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media. Proceedings of the AAAI Conference on Artificial Intelligence 30(2):3982-3989 (2016). doi:10.1609/aaai.v30i2.19072", "title": "Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media", "url": "https://ojs.aaai.org/index.php/AAAI/article/view/19072", "date": "2016-02-18", "written_by": "makers", "quote": "We determined that adaptive inspections uncover significantly more demerits: 9 vs. 6 per inspection (p-value of 0.019)." } ], "replication": { "produced_by": [ "Dense geotagged social-media posting across a metropolitan area", "A health department willing to assign half of a matched inspection sample to algorithm-flagged venues", "A graded inspection protocol (demerits, letter grades) that makes arms comparable" ], "must_hold": [ "Access to geotagged public posts and venue locations as available through the Twitter and Google Places APIs in 2015", "Inspectors blinded to the source of the assignment", "Enough flagged venues per day to schedule adaptive inspections" ], "echoes": [ { "date": "2018-11-06", "setting": "Las Vegas (May-August 2016) and Chicago (November 2016-March 2017), Google's FINDER using aggregated web search and location data", "model_version": "FINDER (successor model by the same lead author, not nEmesis)", "outcome": "recurred", "source": "Sadilek et al. 2018, npj Digital Medicine, doi:10.1038/s41746-018-0045-1" } ] }, "paired_incident": null, "headline": "nEmesis-guided inspections find 64% more C-or-worse venues", "metric": "found 11 venues graded C or worse versus 7 for the control arm, a 64% improvement", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later report of SNHD continuing or expanding nEmesis after the 2015 experiment was found; the 2016 FINDER deployment is a different model.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Rochester; https://www.southernnevadahealthdistrict.org/about-us/maps/southern-nevada-health-district-main-facility/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0188", "catalog_version": "1.0.0", "source_fingerprint": "aafd5697d61c99c9fe0e31a6cf902f49ff00fc20b62dbca9c28f15d8de93b9db", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0188-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Rochester (Adam Sadilek, Henry Kautz and colleagues)", "deployer": "Southern Nevada Health District" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI chose which venues to inspect. The comparison was a controlled double-blind design with 142 venues split between nEmesis and standard protocol. So the difference in findings is attributable to the AI's venue selection. The developers (Rochester) are distinct from the deployer (SNHD), though SNHD staff co-authored the paper. The paper was peer-reviewed as an IAAI deployed paper." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI chose which venues to inspect. The comparison was a controlled double-blind design with 142 venues split between nEmesis and standard protocol. So the difference in findings is attributable to the AI's venue selection. The developers (Rochester) are distinct from the deployer (SNHD), though SNHD staff co-authored the paper. The paper was peer-reviewed as an IAAI deployed paper." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "In 142 blinded inspections the nEmesis arm found 9 vs 6 demerits per inspection (p = 0.019). 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It applies a support-vector-machine language model to geotagged tweets to rank Las Vegas food venues by foodborne-illness risk. During the first three months environmental health specialists inspected 142 venues, half chosen by nEmesis, half under the standard protocol. Inspectors were blind to which was which. Adaptive inspections uncovered 9 demerits per inspection versus 6 (p = 0.019). They found 11 venues graded C or worse versus 7 for controls, a 64% improvement. The abstract summarizes this as 63% more effective. Side findings included an unpermitted seafood establishment and a food handler working with an influenza-like illness. The authors estimate, from CDC outbreak averages, that adaptive inspections saved 71 infections and 4.4 hospitalizations over the three months. They estimate all of Las Vegas's 35,000+ annual inspections made adaptive could prevent over 9,126 cases and 557 hospitalizations a year. SNHD performed 5 foodborne-illness investigations between 2 January and 31 March 2015, against 11 in the same window the year before.", "replication": { "produced_by": [ "Dense geotagged social-media posting across a metropolitan area", "A health department willing to assign half of a matched inspection sample to algorithm-flagged venues", "A graded inspection protocol (demerits, letter grades) that makes arms comparable" ], "must_hold": [ "Access to geotagged public posts and venue locations as available through the Twitter and Google Places APIs in 2015", "Inspectors blinded to the source of the assignment", "Enough flagged venues per day to schedule adaptive inspections" ], "echoes": [ { "date": "2018-11-06", "setting": "Las Vegas (May-August 2016) and Chicago (November 2016-March 2017), Google's FINDER using aggregated web search and location data", "model_version": "FINDER (successor model by the same lead author, not nEmesis)", "outcome": "recurred", "source": "Sadilek et al. 2018, npj Digital Medicine, doi:10.1038/s41746-018-0045-1" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0190", "title": "Chicago's food inspection forecasting model finds critical violations 7.5 days earlier in a double-blind retrodiction", "summary": "Double-blind retrodiction of 1,637 Chicago inspections (Sept-Oct 2014): the model would have found 69% of critical-violation sites in the first half of the work versus 55%, 7.5 days earlier.", "date_observed": "2015-05-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Chicago's Department of Innovation and Technology and Department of Public Health built a model. Pro bono data scientists from Allstate Insurance and the Civic Consulting Alliance helped. It assigns each of the city's 15,000+ food establishments a likelihood of a critical violation. Predictors include previous critical or serious violations, three-day average high temperature, nearby garbage and sanitation complaints and facility type. Others are nearby burglaries, licenses, time since last inspection, length of operation and the inspector assigned. In a double-blind retrodiction, the Department of Public Health inspected 1,637 establishments in its normal order during September and October 2014. Of these, 258 (almost 16%) had at least one critical violation, 141 (55%) found in the first month. Re-ordering the same inspections by the model's probabilities would have found 178 (69%) in the first half of the work, on average 7.5 days earlier. Another 37 would have been cited in the first month. The Harvard Ash Center's Data-Smart City Solutions wrote up the pilot on 19 May 2015. The city page is undated. The code is open source in R.", "category": "general benefit", "unexpected": false, "purpose": "Forecast which Chicago food establishments are most likely to have critical sanitation violations so that inspectors visit them first.", "system": "Food Inspection Forecasting (predictive analytics model, open-sourced in R)", "model_version": null, "developer": "City of Chicago Department of Innovation and Technology with the Department of Public Health, Allstate Insurance data scientists and the Civic Consulting Alliance", "deployer": "Chicago Department of Public Health", "location": "Chicago, United States", "domain": "Food safety / public health", "segment": "Restaurant inspection targeting", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The sources document a retrospective simulation (69% vs 55% found in the first half; 7.5 days earlier) and no live-deployment outcome." }, { "group": "societal", "depth": null, "reason": "Earlier discovery “potentially after patrons became ill” is stated as a rationale. No illness outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "Developer and deployer are the same body. The City of Chicago built the model in-house with pro bono partners and the Department of Public Health is the user. The evaluation re-scored inspections after they were completed, so the model did not change any inspection in the pilot. Model type is not stated in the sources." }, "evidence": [ { "kind": "report", "citation": "City of Chicago. Food Inspection Forecasting: Optimizing Inspections with Analytics. chicago.github.io (undated; copyright 2014-2017).", "title": "Food Inspection Forecasting - City of Chicago", "url": "https://chicago.github.io/food-inspections-evaluation/", "date": null, "written_by": "makers", "quote": "Over the two month pilot, establishments with violations were found, on average, 7 and a half days earlier." }, { "kind": "news report", "citation": "Thornton S. Delivering Faster Results with Food Inspection Forecasting: Chicago's Analytics-Driven Plan to Prevent Foodborne Illness. Data-Smart City Solutions, Harvard Ash Center, 19 May 2015.", "title": "Delivering Faster Results with Food Inspection Forecasting", "url": "http://datasmart.ash.harvard.edu/news/article/delivering-faster-results-with-food-inspection-forecasting-631", "date": "2015-05-19", "written_by": "independent", "quote": "When using an analytics-based procedure, Chicago was able to discover critical violations, on average, seven days earlier than if they had used the traditional inspection procedure." }, { "kind": "preprint", "citation": "Kannan V, Shapiro MA, Bilgic M. Hindsight Analysis of the Chicago Food Inspection Forecasting Model. arXiv:1910.04906, submitted 10 October 2019.", "title": "Hindsight Analysis of the Chicago Food Inspection Forecasting Model", "url": "https://arxiv.org/abs/1910.04906", "date": "2019-10-10", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Open inspection, 311 complaint, business license and weather data on the city's data portal", "Fewer than three dozen inspectors for 15,000+ establishments, so ordering matters", "A fixed two-month inspection record to re-score" ], "must_hold": [ "The predictor set (prior violations, nearby sanitation complaints, facility type, days since last inspection, inspector) remains available", "A critical-violation base rate near 15%" ], "echoes": [] }, "paired_incident": null, "headline": "Chicago's model finds critical violations 7.5 days earlier", "metric": "69% of critical-violation sites in the first half of the work versus 55%, 7.5 days earlier", "comparator": { "against": "the Department of Public Health's normal inspection order during the September-October 2014 pilot", "before": "55 percent (141 establishments) of those with critical violations found in the first month during normal operations", "after": "69 percent (178 establishments) found in the first half of work; violations found on average 7 and a half days earlier", "basis": "measured", "quote": "During the simulation, 69 percent of inspections—178 establishments—with critical violations were found during the first half of work, compared to 55 percent during normal operations. Over the two month pilot, establishments with violations were found, on average, 7 and a half days earlier.", "url": "https://chicago.github.io/food-inspections-evaluation/" }, "later": { "status": "scaled", "date": "2019-10-10", "note": "An independent 2019 hindsight analysis states that CDPH deployed the model in 2015 to schedule inspections of Chicago's 15,000-plus food establishments and released the training data and code.", "quote": "In 2015, CDPH deployed a machine learning model to schedule inspections of establishments based on their likelihood to commit critical food code violations. The City of Chicago released the training data and source code for the model, allowing anyone to examine the model.", "url": "https://arxiv.org/abs/1910.04906" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://chicago.github.io/food-inspections-evaluation/; https://arxiv.org/abs/1910.04906", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://github.com/Chicago; https://en.wikipedia.org/wiki/Chicago_Department_of_Public_Health", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, one independent preprint and the makers' report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0190", "catalog_version": "1.0.0", "source_fingerprint": "eae4cef5a98e27a8a86a802742962e062afaba659b07595ff176cb6c385044b7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0190-source-0001", "AIBD-0190-source-0002", "AIBD-0190-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "City of Chicago Department of Innovation and Technology with the Department of Public Health, Allstate Insurance data scientists and the Civic Consulting Alliance", "deployer": "Chicago Department of Public Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Developer and deployer are the same body. The City of Chicago built the model in-house with pro bono partners and the Department of Public Health is the user. The evaluation re-scored inspections after they were completed, so the model did not change any inspection in the pilot. Model type is not stated in the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Developer and deployer are the same body. The City of Chicago built the model in-house with pro bono partners and the Department of Public Health is the user. The evaluation re-scored inspections after they were completed, so the model did not change any inspection in the pilot. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The sources document a retrospective simulation (69% vs 55% found in the first half; 7.5 days earlier) and no live-deployment outcome." }, { "group": "societal", "reason": "Earlier discovery “potentially after patrons became ill” is stated as a rationale. 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based on their likelihood to commit critical food code violations. The City of Chicago released the training data and source code for the model, allowing anyone to examine the model.", "url": "https://arxiv.org/abs/1910.04906" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0190" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Chicago's Department of Innovation and Technology and Department of Public Health built a model. Pro bono data scientists from Allstate Insurance and the Civic Consulting Alliance helped. It assigns each of the city's 15,000+ food establishments a likelihood of a critical violation. Predictors include previous critical or serious violations, three-day average high temperature, nearby garbage and sanitation complaints and facility type. Others are nearby burglaries, licenses, time since last inspection, length of operation and the inspector assigned. In a double-blind retrodiction, the Department of Public Health inspected 1,637 establishments in its normal order during September and October 2014. Of these, 258 (almost 16%) had at least one critical violation, 141 (55%) found in the first month. Re-ordering the same inspections by the model's probabilities would have found 178 (69%) in the first half of the work, on average 7.5 days earlier. Another 37 would have been cited in the first month. The Harvard Ash Center's Data-Smart City Solutions wrote up the pilot on 19 May 2015. The city page is undated. The code is open source in R.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The sources document a retrospective simulation (69% vs 55% found in the first half; 7.5 days earlier) and no live-deployment outcome." }, { "group": "societal", "reason": "Earlier discovery “potentially after patrons became ill” is stated as a rationale. No illness outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Forecast which Chicago food establishments are most likely to have critical sanitation violations so that inspectors visit them first." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Chicago, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Forecast which Chicago food establishments are most likely to have critical sanitation violations so that inspectors visit them first." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2015-05-19", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://chicago.github.io/food-inspections-evaluation/; https://arxiv.org/abs/1910.04906", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://github.com/Chicago; https://en.wikipedia.org/wiki/Chicago_Department_of_Public_Health", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Open inspection, 311 complaint, business license and weather data on the city's data portal", "Fewer than three dozen inspectors for 15,000+ establishments, so ordering matters", "A fixed two-month inspection record to re-score" ], "must_hold": [ "The predictor set (prior violations, nearby sanitation complaints, facility type, days since last inspection, inspector) remains available", "A critical-violation base rate near 15%" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://chicago.github.io/food-inspections-evaluation/; https://arxiv.org/abs/1910.04906", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://github.com/Chicago; https://en.wikipedia.org/wiki/Chicago_Department_of_Public_Health", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Food safety / public health", "segment": "Restaurant inspection targeting" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "City of Chicago. Food Inspection Forecasting: Optimizing Inspections with Analytics. chicago.github.io (undated; copyright 2014-2017).", "title": "Food Inspection Forecasting - City of Chicago", "url": "https://chicago.github.io/food-inspections-evaluation/", "written_by": "makers", "quote": "Over the two month pilot, establishments with violations were found, on average, 7 and a half days earlier." }, { "kind": "news report", "citation": "Thornton S. Delivering Faster Results with Food Inspection Forecasting: Chicago's Analytics-Driven Plan to Prevent Foodborne Illness. Data-Smart City Solutions, Harvard Ash Center, 19 May 2015.", "title": "Delivering Faster Results with Food Inspection Forecasting", "url": "http://datasmart.ash.harvard.edu/news/article/delivering-faster-results-with-food-inspection-forecasting-631", "date": "2015-05-19", "written_by": "independent", "quote": "When using an analytics-based procedure, Chicago was able to discover critical violations, on average, seven days earlier than if they had used the traditional inspection procedure." }, { "kind": "preprint", "citation": "Kannan V, Shapiro MA, Bilgic M. Hindsight Analysis of the Chicago Food Inspection Forecasting Model. arXiv:1910.04906, submitted 10 October 2019.", "title": "Hindsight Analysis of the Chicago Food Inspection Forecasting Model", "url": "https://arxiv.org/abs/1910.04906", "date": "2019-10-10", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0190-source-0001", "AIBD-0190-source-0002", "AIBD-0190-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "City of Chicago. Food Inspection Forecasting: Optimizing Inspections with Analytics. chicago.github.io (undated; copyright 2014-2017).", "title": "Food Inspection Forecasting - City of Chicago", "url": "https://chicago.github.io/food-inspections-evaluation/", "written_by": "makers", "quote": "Over the two month pilot, establishments with violations were found, on average, 7 and a half days earlier." }, { "kind": "news report", "citation": "Thornton S. Delivering Faster Results with Food Inspection Forecasting: Chicago's Analytics-Driven Plan to Prevent Foodborne Illness. Data-Smart City Solutions, Harvard Ash Center, 19 May 2015.", "title": "Delivering Faster Results with Food Inspection Forecasting", "url": "http://datasmart.ash.harvard.edu/news/article/delivering-faster-results-with-food-inspection-forecasting-631", "date": "2015-05-19", "written_by": "independent", "quote": "When using an analytics-based procedure, Chicago was able to discover critical violations, on average, seven days earlier than if they had used the traditional inspection procedure." }, { "kind": "preprint", "citation": "Kannan V, Shapiro MA, Bilgic M. Hindsight Analysis of the Chicago Food Inspection Forecasting Model. arXiv:1910.04906, submitted 10 October 2019.", "title": "Hindsight Analysis of the Chicago Food Inspection Forecasting Model", "url": "https://arxiv.org/abs/1910.04906", "date": "2019-10-10", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Double-blind retrodiction of 1,637 Chicago inspections (Sept-Oct 2014): the model would have found 69% of critical-violation sites in the first half of the work versus 55%, 7.5 days earlier.", "account": "Chicago's Department of Innovation and Technology and Department of Public Health built a model. Pro bono data scientists from Allstate Insurance and the Civic Consulting Alliance helped. It assigns each of the city's 15,000+ food establishments a likelihood of a critical violation. Predictors include previous critical or serious violations, three-day average high temperature, nearby garbage and sanitation complaints and facility type. Others are nearby burglaries, licenses, time since last inspection, length of operation and the inspector assigned. In a double-blind retrodiction, the Department of Public Health inspected 1,637 establishments in its normal order during September and October 2014. Of these, 258 (almost 16%) had at least one critical violation, 141 (55%) found in the first month. Re-ordering the same inspections by the model's probabilities would have found 178 (69%) in the first half of the work, on average 7.5 days earlier. Another 37 would have been cited in the first month. The Harvard Ash Center's Data-Smart City Solutions wrote up the pilot on 19 May 2015. The city page is undated. The code is open source in R." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Food Inspection Forecasting (predictive analytics model, open-sourced in R)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "City of Chicago Department of Innovation and Technology with the Department of Public Health, Allstate Insurance data scientists and the Civic Consulting Alliance" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Chicago's food inspection forecasting model finds critical violations 7.5 days earlier in a double-blind retrodiction", "headline": "Chicago's model finds critical violations 7.5 days earlier" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "eae4cef5a98e27a8a86a802742962e062afaba659b07595ff176cb6c385044b7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Chicago's Department of Innovation and Technology and Department of Public Health built a model. Pro bono data scientists from Allstate Insurance and the Civic Consulting Alliance helped. It assigns each of the city's 15,000+ food establishments a likelihood of a critical violation. Predictors include previous critical or serious violations, three-day average high temperature, nearby garbage and sanitation complaints and facility type. Others are nearby burglaries, licenses, time since last inspection, length of operation and the inspector assigned. In a double-blind retrodiction, the Department of Public Health inspected 1,637 establishments in its normal order during September and October 2014. Of these, 258 (almost 16%) had at least one critical violation, 141 (55%) found in the first month. Re-ordering the same inspections by the model's probabilities would have found 178 (69%) in the first half of the work, on average 7.5 days earlier. Another 37 would have been cited in the first month. The Harvard Ash Center's Data-Smart City Solutions wrote up the pilot on 19 May 2015. The city page is undated. The code is open source in R.", "replication": { "produced_by": [ "Open inspection, 311 complaint, business license and weather data on the city's data portal", "Fewer than three dozen inspectors for 15,000+ establishments, so ordering matters", "A fixed two-month inspection record to re-score" ], "must_hold": [ "The predictor set (prior violations, nearby sanitation complaints, facility type, days since last inspection, inspector) remains available", "A critical-violation base rate near 15%" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0057", "title": "OrCam computer-vision readers improve daily-living task performance in independent clinical cohorts (2015–2023)", "summary": "Independent cohorts (12, 100, 6 and 10 participants) show OrCam devices raising reading and daily-task scores; no individual outcome.", "date_observed": "2015-07-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Independent clinical studies of OrCam's wearable and handheld text-and-object readers report cohort gains. In a US ophthalmology department 12 patients with acuity of 20/200 or worse improved on a 10-item daily-living test (1 July to 30 September 2015). They went from 2.5 to 9.5 with the device at the first visit and 9.8 after a week of use at home (JAMA Ophthalmology, 2016). A five-center study of 100 users found improved reading and face recognition (Journal of Medical Systems, 2023). Six UC Davis patients with stroke or brain tumors used OrCam Read for a month in 2021 (Neuro-Ophthalmology, 2024). At the NIH nine children with CLN3 disease completed all level-A text, color and face tasks by day five (Orphanet Journal of Rare Diseases, 2026). No individual outcome is attributed.", "category": "general benefit", "unexpected": false, "purpose": "Read text and recognize faces, objects and colors aloud for people with visual impairment", "system": "OrCam MyEye, MyEye 2 and OrCam Read (camera-based optical character and object recognition with audio output)", "model_version": "OrCam (2015 study; model not named in the abstract); OrCam MyEye (2023 multicentre study); OrCam MyEye 2 (NIH); OrCam Read (UC Davis)", "developer": "OrCam Technologies", "deployer": "Study clinics: a US ophthalmology department (2015), five vision rehabilitation centers, UC Davis Ophthalmology, NIH Clinical Center", "location": null, "domain": "Low-vision rehabilitation", "segment": "People with low vision, acquired brain injury or CLN3 disease", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Outcomes are cohort means on daily-living and task tests. No individual beneficiary is identified." }, { "group": "societal", "depth": null, "reason": "Multi-site cohort evidence of usability, not an attributable societal outcome." } ], "ai_role": { "status": "assessed", "statement": "The devices' computer-vision recognition of text, faces and colors is the function measured in every study. Comparisons were against no aid or existing low-vision aids. The 2016 test instrument was non-validated, so effects are task-level rather than clinical outcomes." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Moisseiev E, Mannis MJ (2016). Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision. JAMA Ophthalmology 134(7):748-752.", "title": "Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision", "url": "https://europepmc.org/abstract/MED/27148909", "date": "2016-07-01", "written_by": "independent", "quote": "scores on the 10-item test improved from a mean (SD) of 2.5 (1.6) using best-corrected visual acuity to 9.5 (0.5) using the portable artificial vision device" }, { "kind": "peer-reviewed study", "citation": "Amore F, Silvestri V, Guidobaldi M, et al. (2023). Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study. Journal of Medical Systems 47:11.", "title": "Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study", "url": "https://europepmc.org/abstract/MED/36645535", "date": "2023-01-16", "written_by": "independent", "quote": "OrCam MyEye allowed visually impaired people to read, handle money and face recognition independently." }, { "kind": "peer-reviewed study", "citation": "Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA (2024). A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours. Neuro-Ophthalmology 48(1):3-12.", "title": "A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/", "date": "2024-02-12", "written_by": "independent", "quote": "a handheld device powered by artificial intelligence and a smart camera that captures printed or digital text and plays it out loud" }, { "kind": "peer-reviewed study", "citation": "Nguyen TT, Munoz A, Jenkins K, et al. (2026). Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease. Orphanet Journal of Rare Diseases 21:199.", "title": "Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/", "date": "2026-04-03", "written_by": "independent", "quote": "all nine participants with CLN3 disease correctly completed all level A text, color, and facial recognition tasks" } ], "replication": { "produced_by": [ "Camera-based OCR and object recognition with audio output", "Short in-clinic training followed by home use", "Task batteries simulating daily living" ], "must_hold": [ "Adequate lighting and pointing ability", "Device training provided by clinicians", "Users with residual ability to aim the camera" ], "echoes": [ { "date": null, "setting": "Lighthouse Guild comparison of OrCam MyEye 2 Pro with Envision, Seeing AI and Lookout in 25 adults", "model_version": "OrCam MyEye 2 Pro v9.21", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "830", "title": "Error-Prone AI Accessibility Tools Reportedly Lead to Navigation Issues for Blind Internet Users", "url": "https://incidentdatabase.ai/cite/830", "severity": null, "group": "personal", "basis": "Both are vendor AI products sold to recognize and read content aloud for low-vision users; the overlays' inaccurate descriptions degraded rather than improved daily task performance for blind and visually impaired users." }, "headline": "OrCam readers raise daily-living test scores from 2.5 to 9.5", "metric": "improved on a 10-item daily-living test from 2.5 to 9.5", "comparator": null, "later": null, "value": null, "developer_country": "Israel", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the Neuro-Ophthalmology citation to Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA, 48(1):3–12, published 12 February 2024, and the Orphanet Journal of Rare Diseases citation to Nguyen TT et al., 21:199, published 3 April 2026, filling both dates from the PMC pages; aligned the one-week figure to the abstract's “after 1 week of use at home”, which its Interventions section does state; and rewrote the model version so that the 2015 device is named only as “OrCam”, as in that abstract, with each model name tied to the study that gives it.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/; Europe PMC record MED/27148909 (abstract of JAMA Ophthalmology 134(7):748-752)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OrCam; https://en.wikipedia.org/wiki/NIH_Clinical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: four independent peer-reviewed studies. 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No individual beneficiary is identified." }, { "group": "societal", "reason": "Multi-site cohort evidence of usability, not an attributable societal outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Read text and recognize faces, objects and colors aloud for people with visual impairment" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Israel", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Read text and recognize faces, objects and colors aloud for people with visual impairment" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2015-07-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the Neuro-Ophthalmology citation to Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA, 48(1):3–12, published 12 February 2024, and the Orphanet Journal of Rare Diseases citation to Nguyen TT et al., 21:199, published 3 April 2026, filling both dates from the PMC pages; aligned the one-week figure to the abstract's “after 1 week of use at home”, which its Interventions section does state; and rewrote the model version so that the 2015 device is named only as “OrCam”, as in that abstract, with each model name tied to the study that gives it.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/; Europe PMC record MED/27148909 (abstract of JAMA Ophthalmology 134(7):748-752)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OrCam; https://en.wikipedia.org/wiki/NIH_Clinical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-based OCR and object recognition with audio output", "Short in-clinic training followed by home use", "Task batteries simulating daily living" ], "must_hold": [ "Adequate lighting and pointing ability", "Device training provided by clinicians", "Users with residual ability to aim the camera" ], "echoes": [ { "setting": "Lighthouse Guild comparison of OrCam MyEye 2 Pro with Envision, Seeing AI and Lookout in 25 adults", "model_version": "OrCam MyEye 2 Pro v9.21", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-based OCR and object recognition with audio output", "Short in-clinic training followed by home use", "Task batteries simulating daily living" ], "must_hold": [ "Adequate lighting and pointing ability", "Device training provided by clinicians", "Users with residual ability to aim the camera" ], "echoes": [ { "setting": "Lighthouse Guild comparison of OrCam MyEye 2 Pro with Envision, Seeing AI and Lookout in 25 adults", "model_version": "OrCam MyEye 2 Pro v9.21", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the Neuro-Ophthalmology citation to Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA, 48(1):3–12, published 12 February 2024, and the Orphanet Journal of Rare Diseases citation to Nguyen TT et al., 21:199, published 3 April 2026, filling both dates from the PMC pages; aligned the one-week figure to the abstract's “after 1 week of use at home”, which its Interventions section does state; and rewrote the model version so that the 2015 device is named only as “OrCam”, as in that abstract, with each model name tied to the study that gives it.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/; Europe PMC record MED/27148909 (abstract of JAMA Ophthalmology 134(7):748-752)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OrCam; https://en.wikipedia.org/wiki/NIH_Clinical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Low-vision rehabilitation", "segment": "People with low vision, acquired brain injury or CLN3 disease" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Moisseiev E, Mannis MJ (2016). Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision. JAMA Ophthalmology 134(7):748-752.", "title": "Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision", "url": "https://europepmc.org/abstract/MED/27148909", "date": "2016-07-01", "written_by": "independent", "quote": "scores on the 10-item test improved from a mean (SD) of 2.5 (1.6) using best-corrected visual acuity to 9.5 (0.5) using the portable artificial vision device" }, { "kind": "peer-reviewed study", "citation": "Amore F, Silvestri V, Guidobaldi M, et al. (2023). Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study. Journal of Medical Systems 47:11.", "title": "Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study", "url": "https://europepmc.org/abstract/MED/36645535", "date": "2023-01-16", "written_by": "independent", "quote": "OrCam MyEye allowed visually impaired people to read, handle money and face recognition independently." }, { "kind": "peer-reviewed study", "citation": "Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA (2024). A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours. Neuro-Ophthalmology 48(1):3-12.", "title": "A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/", "date": "2024-02-12", "written_by": "independent", "quote": "a handheld device powered by artificial intelligence and a smart camera that captures printed or digital text and plays it out loud" }, { "kind": "peer-reviewed study", "citation": "Nguyen TT, Munoz A, Jenkins K, et al. (2026). Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease. Orphanet Journal of Rare Diseases 21:199.", "title": "Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/", "date": "2026-04-03", "written_by": "independent", "quote": "all nine participants with CLN3 disease correctly completed all level A text, color, and facial recognition tasks" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0057-source-0001", "AIBD-0057-source-0002", "AIBD-0057-source-0003", "AIBD-0057-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Moisseiev E, Mannis MJ (2016). Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision. JAMA Ophthalmology 134(7):748-752.", "title": "Evaluation of a Portable Artificial Vision Device Among Patients With Low Vision", "url": "https://europepmc.org/abstract/MED/27148909", "date": "2016-07-01", "written_by": "independent", "quote": "scores on the 10-item test improved from a mean (SD) of 2.5 (1.6) using best-corrected visual acuity to 9.5 (0.5) using the portable artificial vision device" }, { "kind": "peer-reviewed study", "citation": "Amore F, Silvestri V, Guidobaldi M, et al. (2023). Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study. Journal of Medical Systems 47:11.", "title": "Efficacy and Patients' Satisfaction with the ORCAM MyEye Device Among Visually Impaired People: A Multicenter Study", "url": "https://europepmc.org/abstract/MED/36645535", "date": "2023-01-16", "written_by": "independent", "quote": "OrCam MyEye allowed visually impaired people to read, handle money and face recognition independently." }, { "kind": "peer-reviewed study", "citation": "Nisanova A, Barrios L, Chokshi T, Mannis M, Bloch O, Liu YA (2024). A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours. Neuro-Ophthalmology 48(1):3-12.", "title": "A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10863346/", "date": "2024-02-12", "written_by": "independent", "quote": "a handheld device powered by artificial intelligence and a smart camera that captures printed or digital text and plays it out loud" }, { "kind": "peer-reviewed study", "citation": "Nguyen TT, Munoz A, Jenkins K, et al. (2026). Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease. Orphanet Journal of Rare Diseases 21:199.", "title": "Prospective pilot safety, feasibility study of an optic-to-audio device for children with CLN3 disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13173725/", "date": "2026-04-03", "written_by": "independent", "quote": "all nine participants with CLN3 disease correctly completed all level A text, color, and facial recognition tasks" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Independent cohorts (12, 100, 6 and 10 participants) show OrCam devices raising reading and daily-task scores; no individual outcome.", "account": "Independent clinical studies of OrCam's wearable and handheld text-and-object readers report cohort gains. In a US ophthalmology department 12 patients with acuity of 20/200 or worse improved on a 10-item daily-living test (1 July to 30 September 2015). They went from 2.5 to 9.5 with the device at the first visit and 9.8 after a week of use at home (JAMA Ophthalmology, 2016). A five-center study of 100 users found improved reading and face recognition (Journal of Medical Systems, 2023). Six UC Davis patients with stroke or brain tumors used OrCam Read for a month in 2021 (Neuro-Ophthalmology, 2024). At the NIH nine children with CLN3 disease completed all level-A text, color and face tasks by day five (Orphanet Journal of Rare Diseases, 2026). No individual outcome is attributed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The devices recognized text and objects in camera images and described them aloud." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The studies used different OrCam products, including MyEye, MyEye 2, and Read." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "OrCam (2015 study; model not named in the abstract); OrCam MyEye (2023 multicentre study); OrCam MyEye 2 (NIH); OrCam Read (UC Davis)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "OrCam MyEye, MyEye 2 and OrCam Read (camera-based optical character and object recognition with audio output)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OrCam Technologies" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OrCam computer-vision readers improve daily-living task performance in independent clinical cohorts (2015–2023)", "headline": "OrCam readers raise daily-living test scores from 2.5 to 9.5" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5b5e30b52b4178f0b0aa4e336e577d93307b701b10fa3d0ae90caa76ebf0d962" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Independent clinical studies of OrCam's wearable and handheld text-and-object readers report cohort gains. In a US ophthalmology department 12 patients with acuity of 20/200 or worse improved on a 10-item daily-living test (1 July to 30 September 2015). They went from 2.5 to 9.5 with the device at the first visit and 9.8 after a week of use at home (JAMA Ophthalmology, 2016). A five-center study of 100 users found improved reading and face recognition (Journal of Medical Systems, 2023). Six UC Davis patients with stroke or brain tumors used OrCam Read for a month in 2021 (Neuro-Ophthalmology, 2024). At the NIH nine children with CLN3 disease completed all level-A text, color and face tasks by day five (Orphanet Journal of Rare Diseases, 2026). No individual outcome is attributed.", "replication": { "produced_by": [ "Camera-based OCR and object recognition with audio output", "Short in-clinic training followed by home use", "Task batteries simulating daily living" ], "must_hold": [ "Adequate lighting and pointing ability", "Device training provided by clinicians", "Users with residual ability to aim the camera" ], "echoes": [ { "setting": "Lighthouse Guild comparison of OrCam MyEye 2 Pro with Envision, Seeing AI and Lookout in 25 adults", "model_version": "OrCam MyEye 2 Pro v9.21", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0168", "title": "NCAR's DICast wind forecasts cut Xcel Energy's forecast error to 10.8%; Xcel estimates US$49 million saved", "summary": "NCAR's adaptive forecast-blending system (DICast), used by Xcel Energy since 2009, cut mean wind forecast error from about 18% to 10.8% by 2014; Xcel estimated US$49m saved (IEEE Spectrum 2015).", "date_observed": "2015-10-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Sue Ellen Haupt and William Mahoney of the National Center for Atmospheric Research wrote in IEEE Spectrum (22 October 2015). NCAR's wind power forecasting system for Xcel Energy blends numerical weather models with the Dynamic Integrated foreCast (DICast) system, used for wind prediction since 2009. DICast constantly checks its predictions against outcomes and adjusts its bias corrections and weightings. The mean forecast error at a typical wind farm fell from about 18 percent in 2008 to 10.8 percent by 2014. Xcel estimated the improvements had saved customers US$49 million so far. A UCAR news item (7 February 2012) said the system saved ratepayers $6 million in 2010 alone. It described the work as building on NCAR research ranging from statistics to artificial intelligence. E&E News (4 December 2017) quoted Haupt that the forecasts could save $10 million a year. It reported that Xcel operators decommit large coal units when sustained wind is predicted. None of the sources describes the system as machine learning in so many words. The savings are Xcel's estimates reported through NCAR and the press, not a regulator's audit.", "category": "general benefit", "unexpected": false, "purpose": "The system was built to forecast wind generation for Xcel's unit-commitment and trading decisions. The cost savings are its intended use.", "system": "NCAR wind power forecasting system with the DICast adaptive forecast blending engine", "model_version": null, "developer": "National Center for Atmospheric Research (Research Applications Laboratory)", "deployer": "Xcel Energy", "location": "United States", "domain": "Energy", "segment": "Utility wind generation forecasting", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Xcel's US$49 million estimate and the error reduction to 10.8% are reported by the makers and the press without independent measurement." }, { "group": "societal", "depth": null, "reason": "Ratepayer savings and coal-unit decommitment are reported as estimates. No audited figure is documented." } ], "ai_role": { "status": "unassessed", "statement": "The forecasting system's contribution to savings is Xcel's own estimate relayed by NCAR authors and reporters. The AI character of the system rests on UCAR's reference to artificial-intelligence research and DICast's adaptive bias correction, not on an explicit machine-learning description. So both the AI status and the causal share are unverified." }, "evidence": [ { "kind": "news report", "citation": "Sue Ellen Haupt and William P. Mahoney, 'Taming Wind Power With Better Forecasts', IEEE Spectrum, 22 October 2015", "title": "Taming Wind Power With Better Forecasts", "url": "https://spectrum.ieee.org/taming-wind-power-with-better-forecasts", "date": "2015-10-22", "written_by": "makers", "quote": "Xcel estimates that improvements in forecasting have saved customers US $49 million so far." }, { "kind": "news report", "citation": "Haupt and Mahoney, IEEE Spectrum, 22 October 2015 (on DICast)", "title": "Taming Wind Power With Better Forecasts", "url": "https://spectrum.ieee.org/taming-wind-power-with-better-forecasts", "date": "2015-10-22", "written_by": "makers", "quote": "it constantly checks its predictions against what actually happened and adjusts its bias corrections and weightings." }, { "kind": "news report", "citation": "John Fialka and Benjamin Storrow, 'Xcel learns to forecast wind, then shuts coal plants', E&E News, 4 December 2017", "title": "Xcel learns to forecast wind, then shuts coal plants", "url": "https://www.eenews.net/articles/xcel-learns-to-forecast-wind-then-shuts-coal-plants/", "date": "2017-12-04", "written_by": "independent", "quote": "the forecasts, preparations and timing meant the company could save $10 million in power production costs each year." }, { "kind": "press release", "citation": "UCAR/NCAR AtmosNews, 'Wind power wisdom', 7 February 2012", "title": "Wind power wisdom", "url": "https://news.ucar.edu/6460/wind-power-wisdom", "date": "2012-02-07", "written_by": "makers", "quote": "This effort is building on longstanding NCAR research in areas ranging from statistics to artificial intelligence, turbulence theory, and model development." } ], "replication": { "produced_by": [ "Multiple numerical weather models blended with an adaptive statistical layer trained on each wind farm's history", "Forecast updates every 15 minutes feeding unit-commitment decisions", "A utility with large wind capacity and dispatchable coal and gas units to decommit" ], "must_hold": [ "Continuous observed generation data for bias correction", "Operators who act on forecast confidence bands", "An independent accounting of avoided production costs, absent here" ], "echoes": [] }, "paired_incident": null, "headline": "NCAR's DICast cuts Xcel's wind forecast error to 10.8%", "metric": "cut mean wind forecast error from about 18% to 10.8% by 2014; Xcel estimated US$49m saved", "comparator": { "against": "Xcel's wind forecasts in 2008, before NCAR's system", "before": "about 18 percent for 18 to 42 hours ahead", "after": "10.8 percent", "basis": "measured", "quote": "In 2008, the year we started working on this problem, the forecast error at a typical wind farm in this region was about 18 percent for 18 to 42 hours ahead, calculated as a percentage of the capacity of each farm. 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NCAR's wind power forecasting system for Xcel Energy blends numerical weather models with the Dynamic Integrated foreCast (DICast) system, used for wind prediction since 2009. DICast constantly checks its predictions against outcomes and adjusts its bias corrections and weightings. The mean forecast error at a typical wind farm fell from about 18 percent in 2008 to 10.8 percent by 2014. Xcel estimated the improvements had saved customers US$49 million so far. A UCAR news item (7 February 2012) said the system saved ratepayers $6 million in 2010 alone. It described the work as building on NCAR research ranging from statistics to artificial intelligence. E&E News (4 December 2017) quoted Haupt that the forecasts could save $10 million a year. It reported that Xcel operators decommit large coal units when sustained wind is predicted. None of the sources describes the system as machine learning in so many words. The savings are Xcel's estimates reported through NCAR and the press, not a regulator's audit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "NCAR wind power forecasting system with the DICast adaptive forecast blending engine" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "National Center for Atmospheric Research (Research Applications Laboratory)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "NCAR's DICast wind forecasts cut Xcel Energy's forecast error to 10.8%; Xcel estimates US$49 million saved", "headline": "NCAR's DICast cuts Xcel's wind forecast error to 10.8%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "92c4d2686043aa5b140dbdb3ac0cf4b96c9165cb9413720f6d10f581734a2332" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Sue Ellen Haupt and William Mahoney of the National Center for Atmospheric Research wrote in IEEE Spectrum (22 October 2015). NCAR's wind power forecasting system for Xcel Energy blends numerical weather models with the Dynamic Integrated foreCast (DICast) system, used for wind prediction since 2009. DICast constantly checks its predictions against outcomes and adjusts its bias corrections and weightings. The mean forecast error at a typical wind farm fell from about 18 percent in 2008 to 10.8 percent by 2014. Xcel estimated the improvements had saved customers US$49 million so far. A UCAR news item (7 February 2012) said the system saved ratepayers $6 million in 2010 alone. It described the work as building on NCAR research ranging from statistics to artificial intelligence. E&E News (4 December 2017) quoted Haupt that the forecasts could save $10 million a year. It reported that Xcel operators decommit large coal units when sustained wind is predicted. None of the sources describes the system as machine learning in so many words. The savings are Xcel's estimates reported through NCAR and the press, not a regulator's audit.", "replication": { "produced_by": [ "Multiple numerical weather models blended with an adaptive statistical layer trained on each wind farm's history", "Forecast updates every 15 minutes feeding unit-commitment decisions", "A utility with large wind capacity and dispatchable coal and gas units to decommit" ], "must_hold": [ "Continuous observed generation data for bias correction", "Operators who act on forecast confidence bands", "An independent accounting of avoided production costs, absent here" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0186", "title": "CMS's Fraud Prevention System identifies or prevents $654.8 million in 2015, an $11.5-to-$1 return on investment", "summary": "CMS's return-on-investment report for the Fraud Prevention System's fourth implementation year counts $654.8 million in inappropriate Medicare payments identified or prevented in 2015 against $57.1...", "date_observed": "2015-12-31", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Centers for Medicare and Medicaid Services' report “Fraud Prevention System Return on Investment, Fourth Implementation Year” is undated. The Wayback Machine archived it on 24 August 2016. It states the FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015, about 44% more than the previous year. That counts actions taken due to the FPS and investigations it expedited, augmented or corroborated. The corrected ROI is $11.5 to $1, after a rounding error in the originally reported $11.6. Table 1 trends identified savings from $115.4 million in the first year (July 2011 to June 2012) through $250.1 million and $454.0 million. The cumulative total is $1,474.3 million. Savings are split across pre-payment edit denials, payment suspensions, projected cost avoidance from revoking billing privileges and overpayments referred for recovery. The value of law-enforcement referrals was $49.2 million in 2015. The report says the methodology was certified by the HHS Office of Inspector General. It puts 45 providers on active payment suspension at year end. Costs were an estimated $57.1 million, including $19.5 million for a developing contractor and $4.8 million for a modeling contractor. The report does not describe the system's technique.", "category": "general benefit", "unexpected": false, "purpose": "Identify or prevent inappropriate Medicare payments by generating leads that program-integrity contractors investigate and act on.", "system": "Fraud Prevention System (FPS)", "model_version": null, "developer": "Contractors engaged by CMS (the report lists 'Developing Contractor Costs' and 'Modeling Contractor Costs' without naming firms)", "deployer": "Centers for Medicare and Medicaid Services (CMS)", "location": null, "domain": "Health insurance fraud and improper payments", "segment": "Medicare program integrity", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The report gives aggregate identified savings for CMS with no single attributable case." }, { "group": "societal", "depth": null, "reason": "Savings to the Medicare program are stated only as yearly aggregates mixing actual denials with projected avoidance." } ], "ai_role": { "status": "unassessed", "statement": "The report counts savings from actions taken due to the FPS and from investigations the FPS expedited, augmented or corroborated. So the system's own contribution cannot be separated from investigators' work. The technique is not described. CMS deployed the system and paid unnamed developing and modeling contractors, so developer and deployer are not the same body." }, "evidence": [ { "kind": "report", "citation": "Centers for Medicare and Medicaid Services, 'Fraud Prevention System Return on Investment, Fourth Implementation Year', undated (covers 1 January to 31 December 2015; archived 24 August 2016)", "title": "Fraud Prevention System Return on Investment, Fourth Implementation Year", "url": "https://web.archive.org/web/20160824134124/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "date": null, "written_by": "deployer", "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015" } ], "replication": { "produced_by": [ "Claims data run through FPS edits and models that generate leads for Zone Program Integrity Contractors", "Administrative levers listed in Table 1 (pre-payment edits, payment suspensions, revocation of billing privileges, overpayment referrals, law-enforcement referrals)" ], "must_hold": [ "Statutory basis and funding (the Small Business Jobs Act of 2010 defines the implementation years)", "Contractor capacity to investigate leads (investigation costs of $28.9 million in 2015)", "A savings methodology certified by HHS-OIG" ], "echoes": [ { "date": "2012-06-30", "setting": "First implementation year, July 2011 to June 2012", "model_version": null, "outcome": "recurred", "source": "Table 1: $115.4 million identified savings" }, { "date": "2013-09-30", "setting": "Second implementation year, October 2012 to September 2013", "model_version": null, "outcome": "recurred", "source": "Table 1 and note 4: $210.7 million certified plus $39.4 million attributed, $250.1 million" }, { "date": "2014-12-31", "setting": "Third implementation year, calendar 2014", "model_version": null, "outcome": "recurred", "source": "Table 1: $454.0 million" } ] }, "paired_incident": null, "headline": "CMS's FPS identifies or prevents $654.8 million in 2015", "metric": "$654.8 million in inappropriate Medicare payments identified or prevented in 2015", "comparator": { "against": "the FPS's identified savings in the previous year, 2014", "before": "identified savings from the previous year ($454.0 million in Table 1)", "after": "$654.8 million", "basis": "measured", "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015 through actions taken due to the FPS or through investigations expedited, augmented, or corroborated by the FPS (Table 1). These identified savings were about 44% higher than the identified savings from the previous year, with a nearly $11.51 to $1 ROI.", "url": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf" }, "later": null, "value": { "amount": "$654.8 million", "what": "inappropriate Medicare payments identified or prevented in calendar year 2015", "who": "Medicare program (CMS)", "estimate": false, "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015 through actions taken due to the FPS or through investigations expedited, augmented, or corroborated by the FPS (Table 1).", "url": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf" }, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.cms.gov/about-cms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf; https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0186", "catalog_version": "1.0.0", "source_fingerprint": "dbb137d510c046e493190446357ab264f74b76d6a694ce594514b34e0f64547e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0186-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0186-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Contractors engaged by CMS (the report lists 'Developing Contractor Costs' and 'Modeling Contractor Costs' without naming firms)", "deployer": "Centers for Medicare and Medicaid Services (CMS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The report counts savings from actions taken due to the FPS and from investigations the FPS expedited, augmented or corroborated. So the system's own contribution cannot be separated from investigators' work. The technique is not described. CMS deployed the system and paid unnamed developing and modeling contractors, so developer and deployer are not the same body." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The report gives aggregate identified savings for CMS with no single attributable case." }, { "group": "societal", "reason": "Savings to the Medicare program are stated only as yearly aggregates mixing actual denials with projected avoidance." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The report gives aggregate identified savings for CMS with no single attributable case." }, { "group": "societal", "reason": "Savings to the Medicare program are stated only as yearly aggregates mixing actual denials with projected avoidance." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$654.8 million", "what": "inappropriate Medicare payments identified or prevented in calendar year 2015", "who": "Medicare program (CMS)", "estimate": false, "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015 through actions taken due to the FPS or through investigations expedited, augmented, or corroborated by the FPS (Table 1).", "url": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$654.8 million", "what": "inappropriate Medicare payments identified or prevented in calendar year 2015", "who": "Medicare program (CMS)", "estimate": false, "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015 through actions taken due to the FPS or through investigations expedited, augmented, or corroborated by the FPS (Table 1).", "url": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$654.8 million", "what": "inappropriate Medicare payments identified or prevented in calendar year 2015", "who": "Medicare program (CMS)", "estimate": false, "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015 through actions taken due to the FPS or through investigations expedited, augmented, or corroborated by the FPS (Table 1).", "url": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "$654.8 million in inappropriate Medicare payments identified or prevented in 2015", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0186" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Centers for Medicare and Medicaid Services' report “Fraud Prevention System Return on Investment, Fourth Implementation Year” is undated. The Wayback Machine archived it on 24 August 2016. It states the FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015, about 44% more than the previous year. That counts actions taken due to the FPS and investigations it expedited, augmented or corroborated. The corrected ROI is $11.5 to $1, after a rounding error in the originally reported $11.6. Table 1 trends identified savings from $115.4 million in the first year (July 2011 to June 2012) through $250.1 million and $454.0 million. The cumulative total is $1,474.3 million. Savings are split across pre-payment edit denials, payment suspensions, projected cost avoidance from revoking billing privileges and overpayments referred for recovery. The value of law-enforcement referrals was $49.2 million in 2015. The report says the methodology was certified by the HHS Office of Inspector General. It puts 45 providers on active payment suspension at year end. Costs were an estimated $57.1 million, including $19.5 million for a developing contractor and $4.8 million for a modeling contractor. The report does not describe the system's technique.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The report gives aggregate identified savings for CMS with no single attributable case." }, { "group": "societal", "reason": "Savings to the Medicare program are stated only as yearly aggregates mixing actual denials with projected avoidance." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify or prevent inappropriate Medicare payments by generating leads that program-integrity contractors investigate and act on." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify or prevent inappropriate Medicare payments by generating leads that program-integrity contractors investigate and act on." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2015-12-31", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.cms.gov/about-cms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf; https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Claims data run through FPS edits and models that generate leads for Zone Program Integrity Contractors", "Administrative levers listed in Table 1 (pre-payment edits, payment suspensions, revocation of billing privileges, overpayment referrals, law-enforcement referrals)" ], "must_hold": [ "Statutory basis and funding (the Small Business Jobs Act of 2010 defines the implementation years)", "Contractor capacity to investigate leads (investigation costs of $28.9 million in 2015)", "A savings methodology certified by HHS-OIG" ], "echoes": [ { "date": "2012-06-30", "setting": "First implementation year, July 2011 to June 2012", "outcome": "recurred", "source": "Table 1: $115.4 million identified savings" }, { "date": "2013-09-30", "setting": "Second implementation year, October 2012 to September 2013", "outcome": "recurred", "source": "Table 1 and note 4: $210.7 million certified plus $39.4 million attributed, $250.1 million" }, { "date": "2014-12-31", "setting": "Third implementation year, calendar 2014", "outcome": "recurred", "source": "Table 1: $454.0 million" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Claims data run through FPS edits and models that generate leads for Zone Program Integrity Contractors", "Administrative levers listed in Table 1 (pre-payment edits, payment suspensions, revocation of billing privileges, overpayment referrals, law-enforcement referrals)" ], "must_hold": [ "Statutory basis and funding (the Small Business Jobs Act of 2010 defines the implementation years)", "Contractor capacity to investigate leads (investigation costs of $28.9 million in 2015)", "A savings methodology certified by HHS-OIG" ], "echoes": [ { "date": "2012-06-30", "setting": "First implementation year, July 2011 to June 2012", "outcome": "recurred", "source": "Table 1: $115.4 million identified savings" }, { "date": "2013-09-30", "setting": "Second implementation year, October 2012 to September 2013", "outcome": "recurred", "source": "Table 1 and note 4: $210.7 million certified plus $39.4 million attributed, $250.1 million" }, { "date": "2014-12-31", "setting": "Third implementation year, calendar 2014", "outcome": "recurred", "source": "Table 1: $454.0 million" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.cms.gov/about-cms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf; https://web.archive.org/web/20160824134124id_/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Health insurance fraud and improper payments", "segment": "Medicare program integrity" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Centers for Medicare and Medicaid Services, 'Fraud Prevention System Return on Investment, Fourth Implementation Year', undated (covers 1 January to 31 December 2015; archived 24 August 2016)", "title": "Fraud Prevention System Return on Investment, Fourth Implementation Year", "url": "https://web.archive.org/web/20160824134124/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "written_by": "deployer", "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0186-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Centers for Medicare and Medicaid Services, 'Fraud Prevention System Return on Investment, Fourth Implementation Year', undated (covers 1 January to 31 December 2015; archived 24 August 2016)", "title": "Fraud Prevention System Return on Investment, Fourth Implementation Year", "url": "https://web.archive.org/web/20160824134124/https://www.cms.gov/about-cms/components/cpi/downloads/fraud-prevention-system-return-on-investment-fourth-implementation-year-2015.pdf", "written_by": "deployer", "quote": "The FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CMS's return-on-investment report for the Fraud Prevention System's fourth implementation year counts $654.8 million in inappropriate Medicare payments identified or prevented in 2015 against $57.1...", "account": "The Centers for Medicare and Medicaid Services' report “Fraud Prevention System Return on Investment, Fourth Implementation Year” is undated. The Wayback Machine archived it on 24 August 2016. It states the FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015, about 44% more than the previous year. That counts actions taken due to the FPS and investigations it expedited, augmented or corroborated. The corrected ROI is $11.5 to $1, after a rounding error in the originally reported $11.6. Table 1 trends identified savings from $115.4 million in the first year (July 2011 to June 2012) through $250.1 million and $454.0 million. The cumulative total is $1,474.3 million. Savings are split across pre-payment edit denials, payment suspensions, projected cost avoidance from revoking billing privileges and overpayments referred for recovery. The value of law-enforcement referrals was $49.2 million in 2015. The report says the methodology was certified by the HHS Office of Inspector General. It puts 45 providers on active payment suspension at year end. Costs were an estimated $57.1 million, including $19.5 million for a developing contractor and $4.8 million for a modeling contractor. 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The Wayback Machine archived it on 24 August 2016. It states the FPS helped identify or prevent $654.8 million in inappropriate payments during calendar year 2015, about 44% more than the previous year. That counts actions taken due to the FPS and investigations it expedited, augmented or corroborated. The corrected ROI is $11.5 to $1, after a rounding error in the originally reported $11.6. Table 1 trends identified savings from $115.4 million in the first year (July 2011 to June 2012) through $250.1 million and $454.0 million. The cumulative total is $1,474.3 million. Savings are split across pre-payment edit denials, payment suspensions, projected cost avoidance from revoking billing privileges and overpayments referred for recovery. The value of law-enforcement referrals was $49.2 million in 2015. The report says the methodology was certified by the HHS Office of Inspector General. It puts 45 providers on active payment suspension at year end. Costs were an estimated $57.1 million, including $19.5 million for a developing contractor and $4.8 million for a modeling contractor. The report does not describe the system's technique.", "replication": { "produced_by": [ "Claims data run through FPS edits and models that generate leads for Zone Program Integrity Contractors", "Administrative levers listed in Table 1 (pre-payment edits, payment suspensions, revocation of billing privileges, overpayment referrals, law-enforcement referrals)" ], "must_hold": [ "Statutory basis and funding (the Small Business Jobs Act of 2010 defines the implementation years)", "Contractor capacity to investigate leads (investigation costs of $28.9 million in 2015)", "A savings methodology certified by HHS-OIG" ], "echoes": [ { "date": "2012-06-30", "setting": "First implementation year, July 2011 to June 2012", "outcome": "recurred", "source": "Table 1: $115.4 million identified savings" }, { "date": "2013-09-30", "setting": "Second implementation year, October 2012 to September 2013", "outcome": "recurred", "source": "Table 1 and note 4: $210.7 million certified plus $39.4 million attributed, $250.1 million" }, { "date": "2014-12-31", "setting": "Third implementation year, calendar 2014", "outcome": "recurred", "source": "Table 1: $454.0 million" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0166", "title": "ActiveRemediation helps Flint locate hazardous water pipes", "summary": "ActiveRemediation helped Flint prioritize homes for inspection and replacement of lead or galvanized-steel service lines.", "date_observed": "2016-01-01", "date_basis": "event", "date_precision": "year", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "University researchers worked with Flint’s service-line replacement program from summer 2016. 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The improved hit rate was the intended use.", "system": "ActiveRemediation, combining XGBoost predictions, a hierarchical Bayesian spatial model, and active learning", "model_version": null, "developer": "University of Michigan (Jacob Abernethy, Alex Chojnacki, Arya Farahi, Eric Schwartz, Jared Webb)", "deployer": "City of Flint (FAST Start service-line replacement program)", "location": "Flint, United States", "domain": "Water infrastructure", "segment": "Lead service-line replacement", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The public-health good of lead removal is the end; the documented gain is the hit rate per excavation.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents benefited from identification and replacement of hazardous service lines, without a measured health effect attributable to the model." }, { "group": "organizational", "depth": 2, "reason": "The program gained a measured capability to predict pipe materials and prioritize work." }, { "group": "societal", "depth": 3, "reason": "Flint replaced hazardous service lines at thousands of homes, with predictions helping prioritize inspections." } ], "ai_role": { "status": "assessed", "statement": "Predictions helped officials prioritize inspections and replacements. The field comparison also involved changes in geography and policy, so it does not isolate the model’s contribution. The monetary saving came from simulation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Abernethy, Jacob, Alex Chojnacki, Arya Farahi, Eric Schwartz, and Jared Webb. “ActiveRemediation: The Search for Lead Pipes in Flint, Michigan.” KDD 2018. https://doi.org/10.1145/3219819.3219896.", "title": "ActiveRemediation: The Search for Lead Pipes in Flint, Michigan", "url": "https://arxiv.org/abs/1806.10692", "date": "2018-06-10", "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Madrigal, Alexis C. “How a Feel-Good AI Story Went Wrong in Flint.” The Atlantic, January 3, 2019.", "title": "How a Feel-Good AI Story Went Wrong in Flint", "url": "https://www.theatlantic.com/technology/archive/2019/01/how-machine-learning-found-flints-lead-pipes/578692/", "date": "2019-01-03", "written_by": "independent", "quote": null }, { "kind": "court document", "citation": "Concerned Pastors for Social Action v. Khouri, No. 16-10277, ECF No. 208 (E.D. Mich. March 26, 2019).", "title": "Order Amending Settlement Agreement", "url": "https://www.nrdc.org/sites/default/files/order-amending-settlement-agreement-flint-20190326.pdf", "date": "2019-03-26", "written_by": "independent", "quote": null, "supports_benefit": false }, { "kind": "news report", "citation": "Tribou, Doug. “In Flint, Algorithm Predicts Lead Pipe Locations as Replacement Work Continues.” Michigan Radio, April 25, 2019.", "title": "In Flint, algorithm predicts lead pipe locations as replacement work continues", "url": "https://www.michiganpublic.org/news/2019-04-25/in-flint-algorithm-predicts-lead-pipe-locations-as-replacement-work-continues", "date": "2019-04-25", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Digitized parcel records and confirmed pipe materials", "Models that updated as inspection results arrived", "Researchers, officials, and contractors who shared information" ], "must_hold": [ "Verified inspection results", "Practical rules for prioritizing excavations", "Official use of the predictions alongside local needs" ], "echoes": [] }, "paired_incident": null, "headline": "Flint uses predictions to find hazardous water pipes", "metric": "91.6% held-out prediction accuracy; 10.7% lower cost per replacement in simulation", "comparator": { "against": "The recorded sequence of inspection and replacement work in a simulation", "before": "Estimated US$5,818 per replacement", "after": "Estimated US$5,196 per replacement", "basis": "assumed", "quote": "The proposed method lowers the effective cost per successful service line replacement, saving $621.7 per home (10.7%)", "url": "https://arxiv.org/abs/1806.10692" }, "later": { "status": "litigated", "date": "2019-03-26", "note": "The federal court ordered that Flint prioritize the model’s address lists for excavation and replacement, with defined exceptions.", "quote": null, "url": "https://www.nrdc.org/sites/default/files/order-amending-settlement-agreement-flint-20190326.pdf" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.michiganpublic.org/news/2019-04-25/in-flint-algorithm-predicts-lead-pipe-locations-as-replacement-work-continues; https://www.mswmag.com/online_exclusives/2019/02/flint-to-revert-back-to-data-driven-predictive-model-for-lead-pipe-replacements", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Michigan; https://en.wikipedia.org/wiki/Flint,_Michigan", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to City of Flint and University of Michigan.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://arxiv.org/abs/1806.10692", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent court document, two independent news reports and the makers' peer-reviewed study. 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Accuracy was tested retrospectively, and monetary savings were modeled." } }, "assessments[].target": { "state": "value_present", "value": { "kind": "text", "text": "Identification and replacement of hazardous service lines." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Identification and replacement of hazardous service lines." } }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "An operational application with retrospective validation and simulation." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An operational application with retrospective validation and simulation." } }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "links": [ { "proposition": "Original methods, field implementation, validation, and simulated costs.", "source_refs": [ "AIBD-0166-source-0001" ], "locator": "§§2–4, Tables 1 and 5." }, { "proposition": "Independent reporting about model use, excavation results, and the contractor’s later change in priorities.", "source_refs": [ "AIBD-0166-source-0002" ], "locator": "Field totals and interviews with Michael McDaniel, Karen Weaver, Alan Wong, and Eric Schwartz." }, { "proposition": "The court required prioritization of addresses selected using the predictive model, with specified exceptions and reporting.", "source_refs": [ "AIBD-0166-source-0003" ], "locator": "¶¶1–6, pp. 1–4." }, { "proposition": "A later firsthand interview reports that the research team was again working with Flint in 2019.", "source_refs": [ "AIBD-0166-source-0004" ], "locator": "“A goal of efficiency” and the original interview with Eric Schwartz." } ] } }, "provenance": { "kind": "source_review", "basis": "Original-source lineage.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001", "AIBD-0166-source-0002", "AIBD-0166-source-0003", "AIBD-0166-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources are linked to the findings that they support." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "text", "text": "The developers reported validation and simulation results. 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Independent reporting and a court order document how officials used the system." } }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "Predictions can help locate hazardous service lines and avoid some unnecessary excavations." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Predictions can help locate hazardous service lines and avoid some unnecessary excavations." } }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Affiliations and methods.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The research institutions and deployment were in the United States. No international data transfer is documented.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The research institutions and deployment were in the United States. No international data transfer is documented." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "text", "text": "The city had to prioritize the model’s address lists, document exceptions, and report completed work." }, "provenance": { "kind": "source_review", "basis": "¶¶1–6.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The city had to prioritize the model’s address lists, document exceptions, and report completed work." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "text", "text": "The parties agreed that the city should first excavate homes with the highest predicted likelihood of hazardous lines." }, "provenance": { "kind": "source_review", "basis": "¶¶1–3.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The parties agreed that the city should first excavate homes with the highest predicted likelihood of hazardous lines." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "text", "text": "The federal court amended the settlement governing Flint’s service-line replacement program." }, "provenance": { "kind": "source_review", "basis": "Opening order.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The federal court amended the settlement governing Flint’s service-line replacement program." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "text", "text": "The city had to excavate the listed addresses and replace hazardous lines by 1 January 2020." }, "provenance": { "kind": "source_review", "basis": "¶3.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The city had to excavate the listed addresses and replace hazardous lines by 1 January 2020." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "Researchers worked with Flint’s replacement program from summer 2016." }, "provenance": { "kind": "source_review", "basis": "§2; Table 1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers worked with Flint’s replacement program from summer 2016." } }, "economics[].amount": { "state": "value_present", "value": { "kind": "text", "text": "The simulation estimated about US$622 less per replacement, or US$11.18 million if applied to 18,000 replacements." }, "provenance": { "kind": "source_review", "basis": "Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The simulation estimated about US$622 less per replacement, or US$11.18 million if applied to 18,000 replacements." } }, "economics[].costs[]": { "state": "value_present", "value": { "kind": "text", "text": "The simulation assumed US$250 for a hydrovac inspection, US$2,500 for an unnecessary excavation, and US$5,000 for a needed replacement." }, "provenance": { "kind": "source_review", "basis": "§4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The simulation assumed US$250 for a hydrovac inspection, US$2,500 for an unnecessary excavation, and US$5,000 for a needed replacement." } }, "economics[].counterfactual": { "state": "value_present", "value": { "kind": "text", "text": "Estimated average cost was US$5,818 under the recorded work sequence and US$5,196 under the proposed strategy." }, "provenance": { "kind": "source_review", "basis": "Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Estimated average cost was US$5,818 under the recorded work sequence and US$5,196 under the proposed strategy." } }, "economics[].currency_price_basis": { "state": "value_present", "value": { "kind": "text", "text": "U.S. dollars, using the unit costs assumed in the study. A separate inflation base year is not stated." }, "provenance": { "kind": "source_review", "basis": "§4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "U.S. dollars, using the unit costs assumed in the study. A separate inflation base year is not stated." } }, "economics[].gross_net": { "state": "value_present", "value": { "kind": "text", "text": "The estimate includes excavation and replacement costs, but not every cost of operating the program." }, "provenance": { "kind": "source_review", "basis": "§4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The estimate includes excavation and replacement costs, but not every cost of operating the program." } }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "text", "text": "Modeled cost savings." }, "provenance": { "kind": "source_review", "basis": "Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Modeled cost savings." } }, "economics[].period_unit": { "state": "value_present", "value": { "kind": "text", "text": "Per replacement, with an extrapolation to 18,000 replacements." }, "provenance": { "kind": "source_review", "basis": "Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Per replacement, with an extrapolation to 18,000 replacements." } }, "economics[].realization": { "state": "value_present", "value": { "kind": "text", "text": "The savings were simulated. They are not an audited reduction in city expenditure." }, "provenance": { "kind": "source_review", "basis": "§4.2; Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The savings were simulated. They are not an audited reduction in city expenditure." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "The modeled savings would reduce the cost of the publicly funded replacement program." }, "provenance": { "kind": "source_review", "basis": "§1; §4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The modeled savings would reduce the cost of the publicly funded replacement program." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "§4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No complete return-on-investment or payback calculation is reported.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "No complete return-on-investment or payback calculation is reported." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "Researchers simulated inspection and replacement sequences, applied fixed unit costs, and extrapolated the difference." }, "provenance": { "kind": "source_review", "basis": "§4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers simulated inspection and replacement sequences, applied fixed unit costs, and extrapolated the difference." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The estimated cost improvement came from a simulation. The field results do not isolate the model from crews, funding, and policy decisions." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The estimated cost improvement came from a simulation. The field results do not isolate the model from crews, funding, and policy decisions." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "The cost simulation compared the proposed strategy with the sequence of work in the city’s records." }, "provenance": { "kind": "source_review", "basis": "§4.2; Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The cost simulation compared the proposed strategy with the sequence of work in the city’s records." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Researchers tested predictions on held-out homes and compared inspection strategies in simulations." }, "provenance": { "kind": "source_review", "basis": "§§4.1–4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers tested predictions on held-out homes and compared inspection strategies in simulations." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "The held-out prediction accuracy was 91.6%. The simulated strategy lowered estimated cost per replacement by 10.7%." }, "provenance": { "kind": "source_review", "basis": "§4.1.1; Table 5.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The held-out prediction accuracy was 91.6%. The simulated strategy lowered estimated cost per replacement by 10.7%." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Predictions were updated as crews recorded new inspections and replacements." }, "provenance": { "kind": "source_review", "basis": "§§2.3–3.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Predictions were updated as crews recorded new inspections and replacements." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0166-E01", "AIBD-0166-E02" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Identifiers assigned to the evaluations described here.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0166-E01, AIBD-0166-E02" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Excavation results supplied the pipe-material labels. Validation and simulated work sequences used those records." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Excavation results supplied the pipe-material labels. Validation and simulated work sequences used those records." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Pipe-material prediction, inspection success, and modeled cost per replacement." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Pipe-material prediction, inspection success, and modeled cost per replacement." } }, "evaluations[].reproduction_materials": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "§3; §4.1.1, n. 6.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The paper describes the algorithms and simulations. It does not supply all settings needed to reproduce the deployed system.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The paper describes the algorithms and simulations. It does not supply all settings needed to reproduce the deployed system." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "The database covered 55,893 parcels. The main accuracy test held out 1,606 homes with known pipe materials." }, "provenance": { "kind": "source_review", "basis": "§2.1; §4.1.1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The database covered 55,893 parcels. The main accuracy test held out 1,606 homes with known pipe materials." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "Known pipe materials came from a selected set of inspected homes. The simulated costs omitted travel and other logistical constraints." }, "provenance": { "kind": "source_review", "basis": "§§4.1–4.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Known pipe materials came from a selected set of inspected homes. The simulated costs omitted travel and other logistical constraints." } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "A March 2019 court order required the city to prioritize addresses identified by the predictive model, subject to defined exceptions." }, "provenance": { "kind": "source_review", "basis": "¶¶1–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A March 2019 court order required the city to prioritize addresses identified by the predictive model, subject to defined exceptions." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "City officials set priorities, contractors confirmed pipe materials, and researchers maintained the model." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "City officials set priorities, contractors confirmed pipe materials, and researchers maintained the model." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0166" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The system depended on digitized parcel records, reliable excavation labels, a shared database, and crews who could inspect and replace pipes." }, "provenance": { "kind": "source_review", "basis": "§2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system depended on digitized parcel records, reliable excavation labels, a shared database, and crews who could inspect and replace pipes." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Residents whose hazardous service lines were identified and replaced." }, "provenance": { "kind": "source_review", "basis": "Table 1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Residents whose hazardous service lines were identified and replaced." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "By September 2017, the program had replaced hazardous lines at 4,419 homes and identified pipe materials at 6,506." }, "provenance": { "kind": "source_review", "basis": "Table 1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "By September 2017, the program had replaced hazardous lines at 4,419 homes and identified pipe materials at 6,506." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved accuracy in locating hazardous service lines." }, "provenance": { "kind": "source_review", "basis": "§4.1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved accuracy in locating hazardous service lines." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "The model helped direct inspections toward homes likely to have hazardous pipes." }, "provenance": { "kind": "source_review", "basis": "§§3–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The model helped direct inspections toward homes likely to have hazardous pipes." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Predictions varied by address and neighborhood. The benefit depended on whether officials used them to set priorities." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Predictions varied by address and neighborhood. The benefit depended on whether officials used them to set priorities." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Replacement permanently changed the identified service lines. The paper did not measure residents’ later health." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Replacement permanently changed the identified service lines. The paper did not measure residents’ later health." } }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Residents and the city’s water-infrastructure program." }, "provenance": { "kind": "source_review", "basis": "§§1–2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Residents and the city’s water-infrastructure program." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "The system was used in the field. Accuracy was tested retrospectively, and monetary savings were modeled." }, "provenance": { "kind": "source_review", "basis": "§4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system was used in the field. Accuracy was tested retrospectively, and monetary savings were modeled." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Residents and officials also sought broad coverage and certainty about individual homes. These priorities could change the order of excavation." }, "provenance": { "kind": "source_review", "basis": "Interviews about the 2018 change in priorities.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Residents and officials also sought broad coverage and certainty about individual homes. These priorities could change the order of excavation." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Finding and removing hazardous pipes was the intended benefit." }, "provenance": { "kind": "source_review", "basis": "§1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Finding and removing hazardous pipes was the intended benefit." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "Flint, Michigan, United States." }, "provenance": { "kind": "source_review", "basis": "§1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Flint, Michigan, United States." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "The system estimated which homes were most likely to have hazardous service lines." }, "provenance": { "kind": "source_review", "basis": "§1.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system estimated which homes were most likely to have hazardous service lines." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "start": "2016", "end": "2017-09", "precision": "season to month", "display": "Summer 2016–September 2017", "refs": [ "AIBD-0166-source-0001" ], "current_date_observed": "2018-07-19", "instruction": "Use the observed result period for the case date. 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City officials and contractors decided where to excavate and replaced the pipes." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system recommended priorities. City officials and contractors decided where to excavate and replaced the pipes." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The system estimated pipe materials and ranked homes for further investigation." }, "provenance": { "kind": "source_review", "basis": "§3.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system estimated pipe materials and ranked homes for further investigation." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "A shared database and a password-protected Flask application let city staff and contractors review maps and add excavation results." }, "provenance": { "kind": "source_review", "basis": "§2.3.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A shared database and a password-protected Flask application let city staff and contractors review maps and add excavation results." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Parcel records, property characteristics, and confirmed pipe materials produced address-level probabilities and inspection priorities." }, "provenance": { "kind": "source_review", "basis": "§§2.1–3.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Parcel records, property characteristics, and confirmed pipe materials produced address-level probabilities and inspection priorities." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "XGBoost classification trees with a hierarchical Bayesian model for spatial patterns. 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Researchers used those results to update predictions and recommend further inspections." }, "provenance": { "kind": "source_review", "basis": "§§2.3–3.2.", "record_fields": [], "source_refs": [ "AIBD-0166-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Crews inspected pipes and recorded their materials. Researchers used those results to update predictions and recommend further inspections." } } }, "summary": { "total": 91, "addressed": 91, "known": 75, "reviewed": 76, "record_mapped": 3, "not_assessed": 12, "complete": false, "by_state": { "value_present": 75, "not_reported": 4, "unresolved": 0, "not_assessed": 12, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0215", "title": "Pounce helps incoming students complete college enrollment", "summary": "Among students already committed to Georgia State, Pounce increased enrollment by 3.3 percentage points.", "date_observed": "2016-01-01", "date_basis": "event", "date_precision": "year", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Georgia State used AdmitHub’s Pounce to help admitted students complete enrollment tasks from April through August 2016. Researchers assigned 7,489 students to the assistant or usual support. Pounce used university records to send relevant reminders, answered questions, and referred unresolved questions to counselors. Among 1,948 students who had already committed to attend, the researchers found that enrollment increased by 3.3 percentage points from a control rate of 84.6%. The overall enrollment effect was not statistically significant. The study evaluated the complete service, including staff assistance, and did not measure degree completion.", "category": "general benefit", "unexpected": false, "purpose": "Pounce was deployed to guide admitted students through pre-enrollment tasks. 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Students could opt out of messages." }, "provenance": { "kind": "source_review", "basis": "pp. 2–3; Table 3.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The service required staff to maintain answers and resolve difficult questions. Students could opt out of messages." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Reducing the loss of committed students before enrollment was the intended benefit." }, "provenance": { "kind": "source_review", "basis": "pp. 1–2.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Reducing the loss of committed students before enrollment was the intended benefit." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "Georgia State University in Atlanta, Georgia, United States." }, "provenance": { "kind": "source_review", "basis": "p. 2.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Georgia State University in Atlanta, Georgia, United States." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "Pounce helped admitted students complete the steps required to enroll." }, "provenance": { "kind": "source_review", "basis": "pp. 2–3.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Pounce helped admitted students complete the steps required to enroll." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "start": "2016-04", "end": "2016-08", "precision": "month", "display": "April–August 2016", "refs": [ "AIBD-0215-source-0001" ], "current_date_observed": "2017-12-12", "instruction": "Use the observed result period for the case date. Keep the full study period separately; the normalized sort date does not imply a more precise observation.", "observed_result_period": "2016", "observed_result_precision": "year", "observed_result_basis": "Fall 2016 enrollment; the article does not specify an observation day." } }, "provenance": { "kind": "source_review", "basis": "Original study timing.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Messages ran from April through August 2016. The study measured enrollment that fall." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "text", "text": "Two later Georgia State trials reported 5–6 percentage-point increases in grades of B or higher. Their courses and students differed from this enrollment trial." }, "provenance": { "kind": "source_review", "basis": "Abstract.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two later Georgia State trials reported 5–6 percentage-point increases in grades of B or higher. Their courses and students differed from this enrollment trial." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "Universities need accurate task records, students who can receive texts, and staff who can answer unresolved questions." }, "provenance": { "kind": "source_review", "basis": "pp. 2–3.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Universities need accurate task records, students who can receive texts, and staff who can answer unresolved questions." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Access to Education under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://eric.ed.gov/?id=EJ1194134; https://edworkingpapers.com/sites/default/files/ai22-564.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://mainstay.com/about/; https://www.gsu.edu/about/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://journals.sagepub.com/doi/10.1177/2332858417749220", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Higher education." }, "provenance": { "kind": "source_review", "basis": "p. 2.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Higher education." } }, "sources[].access_version": { "state": "value_present", "value": { "kind": "text", "text": "The published enrollment article and WABE’s original report were read. 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WABE’s student interview adds independent reporting, while its trial figures come from the original paper." }, "provenance": { "kind": "source_review", "basis": "pp. 2–5; Tables 3–6; p. 9; nn. 7 and 16.; Austin Birchell’s account and discussion of the mistaken Social Security number.; Title page and abstract.", "record_fields": [], "source_refs": [ "AIBD-0215-source-0001", "AIBD-0215-source-0002", "AIBD-0215-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial was conducted with the developer and university. 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The software used teaching rules that specialists had written. A lottery offered 314 of 619 students a voucher that waived the fee. The final study reports that voucher recipients gained 0.37 standard deviations in math and 0.23 in Hindi between September 2015 and February 2016. Average attendance was 58%, and 539 students completed endline tests. The estimate concerns the combined program. All three centers closed in March 2016 after enrollment remained below the threshold for continued subsidy.", "category": "general benefit", "unexpected": false, "purpose": "Mindspark was built to personalize instruction to each student's measured level. 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Mindspark continued in other settings." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "A randomized evaluation of an after-school program." }, "provenance": { "kind": "source_review", "basis": "§2.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A randomized evaluation of an after-school program." } }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "links": [ { "proposition": "Original randomized evaluation, attendance, costs, and closure of the Delhi centers.", "source_refs": [ "AIBD-0212-source-0001" ], "locator": "Author final manuscript, §§2–5, Tables 1–3." }, { "proposition": "A separate 18-month evaluation in Rajasthan public schools and subsequent expansion.", "source_refs": [ "AIBD-0212-source-0002" ], "locator": "Abstract and introduction." } ] } }, "provenance": { "kind": "source_review", "basis": "Original-source lineage.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001", "AIBD-0212-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources are linked to the findings that they support." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "text", "text": "A peer-reviewed randomized evaluation supports the learning gains." }, "provenance": { "kind": "source_review", "basis": "§§2–4.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A peer-reviewed randomized evaluation supports the learning gains." } }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "Free access to the combined program improved students’ measured learning." }, "provenance": { "kind": "source_review", "basis": "§4.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Free access to the combined program improved students’ measured learning." } }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Author affiliations and methods.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The research involved institutions in several countries. The study does not document a cross-border transfer of students’ data.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The research involved institutions in several countries. The study does not document a cross-border transfer of students’ data." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "text", "text": "Donors ended the subsidies, and all three centers closed." }, "provenance": { "kind": "source_review", "basis": "§5.3, n. 35.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Donors ended the subsidies, and all three centers closed." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "text", "text": "Donors required enrollment at or above 80% of capacity." }, "provenance": { "kind": "source_review", "basis": "§5.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Donors required enrollment at or above 80% of capacity." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "text", "text": "Donors decided whether to continue subsidizing the centers." }, "provenance": { "kind": "source_review", "basis": "§5.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Donors decided whether to continue subsidizing the centers." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "text", "text": "At least 80% enrollment at the subsidized fee." }, "provenance": { "kind": "source_review", "basis": "§5.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "At least 80% enrollment at the subsidized fee." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "The program operated in three Delhi centers during the study." }, "provenance": { "kind": "source_review", "basis": "§2.1.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The program operated in three Delhi centers during the study." } }, "economics[].amount": { "state": "value_present", "value": { "kind": "text", "text": "Delivery cost about INR 1,000 per student per month. The subsidized fee was INR 200, which vouchers waived." }, "provenance": { "kind": "source_review", "basis": "§2.1.1; §5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Delivery cost about INR 1,000 per student per month. The subsidized fee was INR 200, which vouchers waived." } }, "economics[].costs[]": { "state": "value_present", "value": { "kind": "text", "text": "The delivery estimate included premises, hardware, staff, and a share of software development costs." }, "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The delivery estimate included premises, hardware, staff, and a share of software development costs." } }, "economics[].counterfactual": { "state": "value_present", "value": { "kind": "text", "text": "The authors compared learning and cost with regular public schooling and with separate research on after-school tutoring." }, "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The authors compared learning and cost with regular public schooling and with separate research on after-school tutoring." } }, "economics[].currency_price_basis": { "state": "value_present", "value": { "kind": "text", "text": "Indian rupees. The authors gave an approximate equivalent of US$15 for the monthly delivery cost." }, "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Indian rupees. The authors gave an approximate equivalent of US$15 for the monthly delivery cost." } }, "economics[].gross_net": { "state": "value_present", "value": { "kind": "text", "text": "These are delivery costs and fees, not income or net savings." }, "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "These are delivery costs and fees, not income or net savings." } }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "text", "text": "Program cost and subsidized fee. Separate estimates describe possible costs at scale." }, "provenance": { "kind": "source_review", "basis": "§2.1.1; §5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Program cost and subsidized fee. Separate estimates describe possible costs at scale." } }, "economics[].period_unit": { "state": "value_present", "value": { "kind": "text", "text": "Per student per month during the Delhi pilot." }, "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Per student per month during the Delhi pilot." } }, "economics[].realization": { "state": "value_present", "value": { "kind": "text", "text": "The INR 1,000 figure describes pilot delivery cost. Lower costs at scale were projections." }, "provenance": { "kind": "source_review", "basis": "§5.2 and n. 33.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The INR 1,000 figure describes pilot delivery cost. Lower costs at scale were projections." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "Families normally paid the subsidized fee. Donors funded the remaining cost, and vouchers covered the fee for selected students." }, "provenance": { "kind": "source_review", "basis": "§2.1.1, n. 7; §5.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Families normally paid the subsidized fee. Donors funded the remaining cost, and vouchers covered the fee for selected students." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "§5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not estimate financial returns or a payback period.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study does not estimate financial returns or a payback period." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "The pilot cost was reported per student. Forecasts for schools used a deployment budget that Educational Initiatives prepared in 2017." }, "provenance": { "kind": "source_review", "basis": "§5.2, n. 33.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The pilot cost was reported per student. Forecasts for schools used a deployment budget that Educational Initiatives prepared in 2017." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The design did not separate adaptive software from additional teaching and practice." }, "provenance": { "kind": "source_review", "basis": "§2.1.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The design did not separate adaptive software from additional teaching and practice." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Students who were not offered a voucher continued their usual schooling and activities." }, "provenance": { "kind": "source_review", "basis": "§2.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students who were not offered a voucher continued their usual schooling and activities." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "A lottery assigned students to a free voucher or a comparison group. Researchers estimated the effect of the offer." }, "provenance": { "kind": "source_review", "basis": "§2.2; §4.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A lottery assigned students to a free voucher or a comparison group. Researchers estimated the effect of the offer." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "The voucher offer raised math scores by 0.37 standard deviations and Hindi scores by 0.23." }, "provenance": { "kind": "source_review", "basis": "Table 2, final manuscript.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The voucher offer raised math scores by 0.37 standard deviations and Hindi scores by 0.23." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Average attendance was 58%, or about 50 of the 86 available days." }, "provenance": { "kind": "source_review", "basis": "§2.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Average attendance was 58%, or about 50 of the 86 available days." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0212-E01" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Identifiers assigned to the evaluations described here.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0212-E01" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Independent paper tests assessed math and Hindi before and after the program. Scores were placed on comparable scales." }, "provenance": { "kind": "source_review", "basis": "§3.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Independent paper tests assessed math and Hindi before and after the program. Scores were placed on comparable scales." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Math and Hindi test scores." }, "provenance": { "kind": "source_review", "basis": "§3.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Math and Hindi test scores." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "Replication data are deposited with the American Economic Association at openICPSR." }, "provenance": { "kind": "source_review", "basis": "Publisher materials and ICPSR catalog entry 113192; https://doi.org/10.3886/E113192V2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Replication data are deposited with the American Economic Association at openICPSR." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "There were 314 voucher recipients and 305 controls. Endline participation was 85% and 90%, respectively." }, "provenance": { "kind": "source_review", "basis": "§§2.2–2.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "There were 314 voucher recipients and 305 controls. Endline participation was 85% and 90%, respectively." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "Participants volunteered for the study. Endline attrition differed between groups, and longer-term attainment was not measured." }, "provenance": { "kind": "source_review", "basis": "§§2.2–2.3; §4; §5.2, n. 34.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Participants volunteered for the study. Endline attrition differed between groups, and longer-term attainment was not measured." } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "The Delhi centers closed in March 2016. Later research evaluated a different school-based delivery model in Rajasthan." }, "provenance": { "kind": "source_review", "basis": "M1 §5.3, n. 35; M2 abstract.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001", "AIBD-0212-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Delhi centers closed in March 2016. Later research evaluated a different school-based delivery model in Rajasthan." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Education specialists wrote the teaching rules. Trained instructors supervised students and provided group instruction." }, "provenance": { "kind": "source_review", "basis": "§2.1.1; online appendix, §D.5.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Education specialists wrote the teaching rules. Trained instructors supervised students and provided group instruction." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0212" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The centers needed computers, headphones, suitable rooms, and instructors." }, "provenance": { "kind": "source_review", "basis": "§2.1.1; §5.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The centers needed computers, headphones, suitable rooms, and instructors." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Public-school students in Delhi, most of whom were in grades 6–9 and behind their grade’s curriculum." }, "provenance": { "kind": "source_review", "basis": "§§2.2–3; n. 9.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Public-school students in Delhi, most of whom were in grades 6–9 and behind their grade’s curriculum." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "The trial enrolled 619 students and offered 314 a voucher. Researchers tested 539 students at the end." }, "provenance": { "kind": "source_review", "basis": "§§2.2–2.3; Table 1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial enrolled 619 students and offered 314 a voucher. Researchers tested 539 students at the end." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved learning." }, "provenance": { "kind": "source_review", "basis": "Table 2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved learning." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "Students offered a voucher scored higher in math and Hindi after 4.5 months." }, "provenance": { "kind": "source_review", "basis": "Table 2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students offered a voucher scored higher in math and Hindi after 4.5 months." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Gains were similar across initial ability levels. Students who began further behind gained more relative to their previous progress." }, "provenance": { "kind": "source_review", "basis": "§4.3; Table 3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Gains were similar across initial ability levels. Students who began further behind gained more relative to their previous progress." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "The measured learning gains covered 4.5 months." }, "provenance": { "kind": "source_review", "basis": "Abstract; §4.1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The measured learning gains covered 4.5 months." } }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Students." }, "provenance": { "kind": "source_review", "basis": "§2.2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Observed in a randomized evaluation." }, "provenance": { "kind": "source_review", "basis": "§4.1; Table 2.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Observed in a randomized evaluation." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "The centers required staff and equipment. Low enrollment and the loss of subsidies led all three to close." }, "provenance": { "kind": "source_review", "basis": "§§5.2–5.3.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The centers required staff and equipment. Low enrollment and the loss of subsidies led all three to close." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Improved learning was the intended benefit." }, "provenance": { "kind": "source_review", "basis": "§1.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved learning was the intended benefit." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "Three centers served low-income neighborhoods in Delhi, India. 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Centers offered six sessions a week." }, "provenance": { "kind": "source_review", "basis": "§2.1.1, pp. 7–8.", "record_fields": [], "source_refs": [ "AIBD-0212-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Each session combined practice on Mindspark with instruction in groups of about 12–15 students. Centers offered six sessions a week." } } }, "summary": { "total": 91, "addressed": 91, "known": 78, "reviewed": 78, "record_mapped": 3, "not_assessed": 10, "complete": false, "by_state": { "value_present": 78, "not_reported": 3, "unresolved": 0, "not_assessed": 10, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0058", "title": "Superpower Glass machine-learning emotion feedback on Google Glass improves socialization scores in children with autism (Stanford cohorts)", "summary": "Stanford's Superpower Glass cut SRS-2 scores 7.38 points in 14 children and raised Vineland socialization 4.58 points in a 71-child RCT.", "date_observed": "2016-07-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Superpower Glass, developed at Stanford University, runs a machine-learning facial-expression classifier on Google Glass. It shows a child which emotion a facing person is displaying. An at-home feasibility study had intake between July and October 2016 (day not given, so 1 July is used). In it, 14 children with autism completed the protocol. Total SRS-2 scores fell an average of 7.38 points and 12 of 14 families reported more eye contact (npj Digital Medicine, 2018). A randomized trial enrolled 71 children aged 6 to 12 from 1 November 2016 to 11 April 2018. Those adding the device to applied behavioral analysis therapy gained 4.58 points more on the Vineland socialization subscale than controls (P = .005). Three other primary measures did not reach significance (JAMA Pediatrics, 2019). Results are cohort-level.", "category": "general benefit", "unexpected": false, "purpose": "Teach emotion recognition and facial engagement to children with autism through real-time wearable feedback", "system": "Superpower Glass: Google Glass with a real-time machine-learning facial emotion classifier and companion smartphone app", "model_version": null, "developer": "Stanford University (Wall lab, Division of Systems Medicine and Department of Computer Science)", "deployer": "Participating families at home under the Stanford studies", "location": "Palo Alto, United States", "domain": "Autism intervention / digital therapeutics", "segment": "Children with autism spectrum disorder aged 6-12", "benefit_type": "Improved Learning", "taxonomy_note": "The measured gain is social-skills learning in children with autism, a therapeutic outcome that no type names exactly.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The gains are group means (SRS-2 and Vineland), with no individually attributed outcome." }, { "group": "societal", "depth": null, "reason": "Trial evidence of efficacy comparable to standard care, not a measured societal change." } ], "ai_role": { "status": "assessed", "statement": "The emotion classifier, trained on public facial-expression databases and tuned for home conditions, generates the real-time cues the intervention relies on. The Guess the Emotion game within the package does not use the classifier. So part of the effect may come from structured family interaction rather than the AI." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Voss C, Schwartz J, Daniels J, et al. (2019). Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial. JAMA Pediatrics 173(5):446-454.", "title": "Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial", "url": "https://europepmc.org/abstract/MED/30907929", "date": "2019-05-01", "written_by": "makers", "quote": "showed significant improvements on the Vineland Adaptive Behaviors Scale socialization subscale compared with treatment as usual controls (mean [SD] treatment impact, 4.58 [1.62]; P = .005)" }, { "kind": "peer-reviewed study", "citation": "Daniels J, Schwartz JN, Voss C, et al. (2018). Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism. npj Digital Medicine 1:32.", "title": "Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism", "url": "https://europepmc.org/article/PMC/PMC6550272", "date": null, "written_by": "makers", "quote": "12 of 14 families commented that they had observed an increase in eye contact from intake to conclusion during the semi-structured interview" }, { "kind": "peer-reviewed study", "citation": "Daniels J, et al. 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Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism. npj Digital Medicine 1:32.", "title": "Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism", "url": "https://europepmc.org/article/PMC/PMC6550272", "written_by": "makers", "quote": "12 of 14 families commented that they had observed an increase in eye contact from intake to conclusion during the semi-structured interview" }, { "kind": "peer-reviewed study", "citation": "Daniels J, et al. 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(2019). Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial. JAMA Pediatrics 173(5):446-454.", "title": "Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial", "url": "https://europepmc.org/abstract/MED/30907929", "date": "2019-05-01", "written_by": "makers", "quote": "showed significant improvements on the Vineland Adaptive Behaviors Scale socialization subscale compared with treatment as usual controls (mean [SD] treatment impact, 4.58 [1.62]; P = .005)" }, { "kind": "peer-reviewed study", "citation": "Daniels J, Schwartz JN, Voss C, et al. (2018). Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism. npj Digital Medicine 1:32.", "title": "Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism", "url": "https://europepmc.org/article/PMC/PMC6550272", "written_by": "makers", "quote": "12 of 14 families commented that they had observed an increase in eye contact from intake to conclusion during the semi-structured interview" }, { "kind": "peer-reviewed study", "citation": "Daniels J, et al. 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It shows a child which emotion a facing person is displaying. An at-home feasibility study had intake between July and October 2016 (day not given, so 1 July is used). In it, 14 children with autism completed the protocol. Total SRS-2 scores fell an average of 7.38 points and 12 of 14 families reported more eye contact (npj Digital Medicine, 2018). A randomized trial enrolled 71 children aged 6 to 12 from 1 November 2016 to 11 April 2018. Those adding the device to applied behavioral analysis therapy gained 4.58 points more on the Vineland socialization subscale than controls (P = .005). Three other primary measures did not reach significance (JAMA Pediatrics, 2019). Results are cohort-level." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Superpower Glass: Google Glass with a real-time machine-learning facial emotion classifier and companion smartphone app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Stanford University (Wall lab, Division of Systems Medicine and Department of Computer Science)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Superpower Glass machine-learning emotion feedback on Google Glass improves socialization scores in children with autism (Stanford cohorts)", "headline": "Superpower Glass raises Vineland socialization by 4.58 points" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "de130b277dadcda09e70ad7eab24b531098c9c95b9d1ea70d5a22512a61ae2e7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Superpower Glass, developed at Stanford University, runs a machine-learning facial-expression classifier on Google Glass. 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It processes AIS tracks of tens of thousands of vessels. In Oceana's description, it uses machine learning and cloud computing to identify when they are fishing. Before launch, the Washington Post reported, the government of Kiribati used it to document how a tuna-fishing vessel had operated illegally. That was inside the Phoenix Islands Protected Area, declared off-limits to commercial fishing in early 2015, resulting in a US$1 million fine. Oceana board member Ted Danson wrote in Grist that the vessel was the Marshall Islands-flagged Marshalls 203. The fine was against its owner, Central Pacific Fishing Company. A goodwill arrangement to pay a further US$1 million as a grant came with it. Oceana's Jacqueline Savitz wrote in BBC Future in 2018 that the technology helped Kiribati extract a US$2 million fine, about 1% of GDP. The cited sources do not date the fine.", "category": "benefit created", "unexpected": false, "purpose": "Make commercial fishing activity visible in near real time by processing AIS vessel tracks to identify when vessels are fishing.", "system": "Global Fishing Watch (AIS-based fishing detection using machine learning)", "model_version": null, "developer": "Oceana, SkyTruth and Google", "deployer": "Government of Kiribati", "location": "Phoenix Islands Protected Area, Kiribati", "domain": "Fisheries enforcement", "segment": "Marine protected area enforcement", "benefit_type": "Reduced Violence", "taxonomy_note": "The criminal activity penalized is illegal fishing in a protected area, and the fine is the only documented outcome.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 3, "reason": "Kiribati secured a US$1 million fine against Central Pacific Fishing Company plus a US$1 million goodwill grant (Grist). The BBC piece puts the total at US$2 million, about 1% of the country's GDP." }, { "group": "societal", "depth": null, "reason": "No source documents subsequent fishing pressure or deterrence inside the protected area." } ], "ai_role": { "status": "assessed", "statement": "An independent newspaper confirms that Kiribati used the platform to document the illegal operation. Oceana describes the platform's fishing detection as machine learning over AIS data. No cited source says whether the classifier's output, as opposed to the vessel's track, carried the case. Developer (Oceana, SkyTruth, Google) and deployer (Kiribati) are distinct." }, "evidence": [ { "kind": "news report", "citation": "Dennis B. How Google is helping to crack down on illegal fishing - from space. The Washington Post, 15 September 2016.", "title": "How Google is helping to crack down on illegal fishing - from space", "url": "https://www.washingtonpost.com/news/energy-environment/wp/2016/09/15/from-space-a-new-effort-to-crack-down-on-illegal-fishing-across-the-globe/", "date": "2016-09-15", "written_by": "independent", "quote": "The government of the Pacific island nation of Kiribati used it to document how a tuna-fishing vessel had operated illegally inside the Phoenix Islands Protected Area" }, { "kind": "news report", "citation": "Danson T. This new digital tool can help fight overfishing around the world. Grist, 15 September 2016 (author is an Oceana board member).", "title": "This new digital tool can help fight overfishing around the world", "url": "https://grist.org/science/this-new-digital-tool-could-help-fight-overfishing-around-the-world/", "date": "2016-09-15", "written_by": "makers", "quote": "This helped the country secure a $1 million fine against the Central Pacific Fishing Company, the owner of Marshalls 203." }, { "kind": "news report", "citation": "Savitz J. How to spot the secretive activities of rogue fishing boats. BBC Future, 7 June 2018 (author is Oceana's chief policy officer for North America).", "title": "How to spot the secretive activities of rogue fishing boats", "url": "https://www.bbc.com/future/article/20180607-how-to-spot-the-secretive-activities-of-rogue-fishing-boats", "date": "2018-06-07", "written_by": "makers", "quote": "Then we run them all through the Global Fishing Watch algorithm, and use machine learning and cloud computing to identify when they are fishing." }, { "kind": "press release", "citation": "Cutlip K. Indonesia Makes its Fishing Fleet Visible to the World. Global Fishing Watch, 7 June 2017.", "title": "Indonesia Makes its Fishing Fleet Visible to the World", "url": "https://globalfishingwatch.org/transparency/indonesia-shares-vms-with-global-fishing-watch/", "date": "2017-06-07", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A vessel broadcasting AIS inside a no-take area that Kiribati closed to commercial fishing from 1 January 2015", "A government willing to prosecute on third-party satellite-derived evidence" ], "must_hold": [ "AIS transmitters left on (the BBC piece notes vessels can switch them off)", "Admissibility of AIS-derived evidence under the coastal state's law" ], "echoes": [ { "date": "2024-01-03", "setting": "Global coastal waters 2017–2021: Global Fishing Watch deep-learning mapping of untracked industrial vessels", "model_version": "SAR imagery with deep-learning models", "outcome": "unknown", "source": "Paolo FS, Kroodsma D et al. 2024, Nature, doi:10.1038/s41586-023-06825-8" } ] }, "paired_incident": null, "headline": "Global Fishing Watch helps Kiribati fine a vessel US$1 million", "metric": "a US$1 million fine plus a US$1 million goodwill grant followed", "comparator": null, "later": { "status": "scaled", "date": "2017-06-07", "note": "In June 2017 Indonesia became the first country to publish its proprietary vessel monitoring system data through Global Fishing Watch, adding nearly 5,000 vessels to the platform, with Peru announcing it would follow.", "quote": "This week, at the United Nation’s Ocean Conference, the Republic of Indonesia becomes the first nation ever to publish Vessel Monitoring System (VMS) data revealing the location and activity of its commercial fishing fleet.", "url": "https://globalfishingwatch.org/transparency/indonesia-shares-vms-with-global-fishing-watch/" }, "value": { "amount": "$1 million", "what": "fine secured by Kiribati against the owner of Marshalls 203 for fishing illegally in the Phoenix Islands Protected Area, plus an additional $1 million paid as a grant under a goodwill arrangement", "who": "Government of Kiribati", "estimate": false, "quote": "This helped the country secure a $1 million fine against the Central Pacific Fishing Company, the owner of Marshalls 203. The company also made a special “goodwill arrangement” with the government, agreeing to pay an additional $1 million in the form of a grant.", "url": "https://grist.org/science/this-new-digital-tool-could-help-fight-overfishing-around-the-world/" }, "developer_country": "United States", "deployer_country": "Kiribati", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the value as stated from the cited sources.", "source": "https://globalfishingwatch.org/transparency/indonesia-shares-vms-with-global-fishing-watch/; https://grist.org/science/this-new-digital-tool-could-help-fight-overfishing-around-the-world/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Oceana_(non-profit_group); https://en.wikipedia.org/wiki/Kiribati", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, two news reports from the makers and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0196", "catalog_version": "1.0.0", "source_fingerprint": "d51c291149dabfc21514acaa1e3cb88a3cec30bb0c61bb885ded2889f9236ed8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0196-source-0001", "AIBD-0196-source-0002", "AIBD-0196-source-0003", "AIBD-0196-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0196-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Oceana, SkyTruth and Google", "deployer": "Government of Kiribati" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "An independent newspaper confirms that Kiribati used the platform to document the illegal operation. Oceana describes the platform's fishing detection as machine learning over AIS data. No cited source says whether the classifier's output, as opposed to the vessel's track, carried the case. Developer (Oceana, SkyTruth, Google) and deployer (Kiribati) are distinct." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "An independent newspaper confirms that Kiribati used the platform to document the illegal operation. Oceana describes the platform's fishing detection as machine learning over AIS data. No cited source says whether the classifier's output, as opposed to the vessel's track, carried the case. 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BBC Future, 7 June 2018 (author is Oceana's chief policy officer for North America).", "title": "How to spot the secretive activities of rogue fishing boats", "url": "https://www.bbc.com/future/article/20180607-how-to-spot-the-secretive-activities-of-rogue-fishing-boats", "date": "2018-06-07", "written_by": "makers", "quote": "Then we run them all through the Global Fishing Watch algorithm, and use machine learning and cloud computing to identify when they are fishing." }, { "kind": "press release", "citation": "Cutlip K. Indonesia Makes its Fishing Fleet Visible to the World. Global Fishing Watch, 7 June 2017.", "title": "Indonesia Makes its Fishing Fleet Visible to the World", "url": "https://globalfishingwatch.org/transparency/indonesia-shares-vms-with-global-fishing-watch/", "date": "2017-06-07", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0196-source-0001", "AIBD-0196-source-0002", "AIBD-0196-source-0003", "AIBD-0196-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dennis B. How Google is helping to crack down on illegal fishing - from space. The Washington Post, 15 September 2016.", "title": "How Google is helping to crack down on illegal fishing - from space", "url": "https://www.washingtonpost.com/news/energy-environment/wp/2016/09/15/from-space-a-new-effort-to-crack-down-on-illegal-fishing-across-the-globe/", "date": "2016-09-15", "written_by": "independent", "quote": "The government of the Pacific island nation of Kiribati used it to document how a tuna-fishing vessel had operated illegally inside the Phoenix Islands Protected Area" }, { "kind": "news report", "citation": "Danson T. This new digital tool can help fight overfishing around the world. Grist, 15 September 2016 (author is an Oceana board member).", "title": "This new digital tool can help fight overfishing around the world", "url": "https://grist.org/science/this-new-digital-tool-could-help-fight-overfishing-around-the-world/", "date": "2016-09-15", "written_by": "makers", "quote": "This helped the country secure a $1 million fine against the Central Pacific Fishing Company, the owner of Marshalls 203." }, { "kind": "news report", "citation": "Savitz J. How to spot the secretive activities of rogue fishing boats. BBC Future, 7 June 2018 (author is Oceana's chief policy officer for North America).", "title": "How to spot the secretive activities of rogue fishing boats", "url": "https://www.bbc.com/future/article/20180607-how-to-spot-the-secretive-activities-of-rogue-fishing-boats", "date": "2018-06-07", "written_by": "makers", "quote": "Then we run them all through the Global Fishing Watch algorithm, and use machine learning and cloud computing to identify when they are fishing." }, { "kind": "press release", "citation": "Cutlip K. Indonesia Makes its Fishing Fleet Visible to the World. Global Fishing Watch, 7 June 2017.", "title": "Indonesia Makes its Fishing Fleet Visible to the World", "url": "https://globalfishingwatch.org/transparency/indonesia-shares-vms-with-global-fishing-watch/", "date": "2017-06-07", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Kiribati used the Google-Oceana-SkyTruth platform to document Marshalls 203 fishing illegally in PIPA; a US$1 million fine plus a US$1 million goodwill grant followed (reported September 2016).", "account": "Global Fishing Watch, developed by Oceana, SkyTruth and Google, launched publicly at the Our Ocean conference on 15 September 2016. It processes AIS tracks of tens of thousands of vessels. In Oceana's description, it uses machine learning and cloud computing to identify when they are fishing. Before launch, the Washington Post reported, the government of Kiribati used it to document how a tuna-fishing vessel had operated illegally. That was inside the Phoenix Islands Protected Area, declared off-limits to commercial fishing in early 2015, resulting in a US$1 million fine. Oceana board member Ted Danson wrote in Grist that the vessel was the Marshall Islands-flagged Marshalls 203. The fine was against its owner, Central Pacific Fishing Company. A goodwill arrangement to pay a further US$1 million as a grant came with it. Oceana's Jacqueline Savitz wrote in BBC Future in 2018 that the technology helped Kiribati extract a US$2 million fine, about 1% of GDP. The cited sources do not date the fine." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Global Fishing Watch (AIS-based fishing detection using machine learning)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Oceana, SkyTruth and Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Global Fishing Watch data lets Kiribati fine a vessel US$1 million for fishing in the Phoenix Islands Protected Area", "headline": "Global Fishing Watch helps Kiribati fine a vessel US$1 million" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d51c291149dabfc21514acaa1e3cb88a3cec30bb0c61bb885ded2889f9236ed8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Global Fishing Watch, developed by Oceana, SkyTruth and Google, launched publicly at the Our Ocean conference on 15 September 2016. It processes AIS tracks of tens of thousands of vessels. In Oceana's description, it uses machine learning and cloud computing to identify when they are fishing. Before launch, the Washington Post reported, the government of Kiribati used it to document how a tuna-fishing vessel had operated illegally. That was inside the Phoenix Islands Protected Area, declared off-limits to commercial fishing in early 2015, resulting in a US$1 million fine. Oceana board member Ted Danson wrote in Grist that the vessel was the Marshall Islands-flagged Marshalls 203. The fine was against its owner, Central Pacific Fishing Company. A goodwill arrangement to pay a further US$1 million as a grant came with it. Oceana's Jacqueline Savitz wrote in BBC Future in 2018 that the technology helped Kiribati extract a US$2 million fine, about 1% of GDP. The cited sources do not date the fine.", "replication": { "produced_by": [ "A vessel broadcasting AIS inside a no-take area that Kiribati closed to commercial fishing from 1 January 2015", "A government willing to prosecute on third-party satellite-derived evidence" ], "must_hold": [ "AIS transmitters left on (the BBC piece notes vessels can switch them off)", "Admissibility of AIS-derived evidence under the coastal state's law" ], "echoes": [ { "date": "2024-01-03", "setting": "Global coastal waters 2017–2021: Global Fishing Watch deep-learning mapping of untracked industrial vessels", "model_version": "SAR imagery with deep-learning models", "outcome": "unknown", "source": "Paolo FS, Kroodsma D et al. 2024, Nature, doi:10.1038/s41586-023-06825-8" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0265", "title": "An implanted interface restored communication at home for nearly seven years", "summary": "A woman with locked-in ALS used the Utrecht NeuroProsthesis to communicate at home for nearly seven years.", "date_observed": "2016-11-12", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "A woman with locked-in ALS received the Utrecht NeuroProsthesis in October 2015. After training, she selected letters and called a caregiver by attempting to move her hand. Caregivers set up the equipment, but she then used it without research staff. It became her only technological means of communication after she lost reliable eye tracking. Home use continued for nearly seven years and ended in March 2023 as control became unreliable. Researchers considered ALS-related brain changes the likely explanation, without proving a single cause. The documented decoder combined brain-signal features and fitted thresholds rather than a named machine-learning model.", "category": "benefit created", "unexpected": false, "purpose": "Provide autonomous communication for a person with late-stage ALS who could no longer rely on eye tracking", "system": "Utrecht NeuroProsthesis with Medtronic Activa PC+S and Tobii Communicator 5", "model_version": null, "developer": "University Medical Center Utrecht (Brain Center; Ramsey and Vansteensel)", "deployer": "University Medical Center Utrecht; home use by the participant", "location": "Utrecht, Netherlands", "domain": "Health; assistive communication", "segment": "People with locked-in syndrome from ALS", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": { "clinicaltrials_gov": "NCT02224469" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The participant regained a lasting ability to communicate at home. The reports do not establish prevention of a separate serious harm." } ], "ai_role": { "status": "assessed", "statement": "The documented decoder combines normalized brain-signal features and fitted thresholds to generate clicks. Whether that mechanism qualifies as AI remains unresolved. The communication benefit itself is documented." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Vansteensel MJ, Pels EGM, Bleichner MG, et al. N Engl J Med 375:2060-2066 (2016)", "title": "Fully Implanted Brain-Computer Interface in a Locked-In Patient with ALS", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5326682/", "date": "2016-11-12", "written_by": "makers", "quote": "the patient accurately and independently controlled a computer typing program 28 weeks after electrode placement, at the equivalent of two letters per minute." }, { "kind": "peer-reviewed study", "citation": "Vansteensel MJ, Leinders S, Branco MP, et al. N Engl J Med 391:619-626 (2024)", "title": "Longevity of a Brain-Computer Interface for Amyotrophic Lateral Sclerosis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11395392/", "date": "2024-08-14", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Sacha Leinders, Fully Implanted Brain-Computer Interface Technology for People with Locked-In Syndrome: Bringing it Home: Results from the Pioneering Utrecht NeuroProsthesis Clinical Trial (PhD diss., Utrecht University, 2025), 35, 137–157, doi:10.33540/2877. Chapter 6 reproduces the 2024 report and its supplementary material.", "title": "Fully Implanted Brain-Computer Interface Technology for People with Locked-In Syndrome: Bringing it Home", "url": "https://doi.org/10.33540/2877", "date": "2025-05-14", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Subdural electrodes over motor cortex with an implanted transmitter", "Band-power features from attempted hand movement converted into click commands", "Months of algorithm refinement to suppress unintended clicks" ], "must_hold": [ "Neural signal amplitude remains sufficient (it declined with ALS-related atrophy after about six years)", "The participant can attempt hand movement reliably" ], "echoes": [ { "date": "2024-08-14", "setting": "Same participant followed for nearly seven years, not an independent replication", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11395392/" }, { "date": "2024-10-22", "setting": "Johns Hopkins click-based ECoG BCI with an LSTM detector, laboratory use only", "model_version": "LSTM click detector", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11494178/" } ] }, "paired_incident": null, "headline": "An implanted interface restored communication for nearly seven years", "metric": "seven years of independent at-home use", "comparator": null, "later": { "status": "reversed", "date": null, "note": "Home use ended in March 2023 when control became unreliable. The source reports the month, not an exact day.", "quote": null, "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11395392/" }, "value": null, "developer_country": "Netherlands", "deployer_country": "Netherlands", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_Medical_Center_Utrecht; https://en.wikipedia.org/wiki/University_Medical_Center_Utrecht", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5326682/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers and the makers' report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0265", "catalog_version": "1.0.0", "source_fingerprint": "6e096fc354b9df3d5e40dfd7d2a1b7b394116ab3c791c6e5ea0f51631824ac1c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002", "AIBD-0265-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "NCT02224469" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The evaluation described in the cited original sources." }, "record_ids": [ "NCT02224469" ] }, "monetary observations": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." }, "record_ids": [] }, "institutional decisions": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "UMCU 12-370" ], "role": "institutional decisions" }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Ethics approval and registration of the Utrecht NeuroProsthesis study." }, "record_ids": [ "UMCU 12-370" ] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "UMC Utrecht researchers developed and evaluated the interface. Medtronic supplied the implant, and the participant and her caregivers used the home system." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "UMC Utrecht researchers developed and evaluated the interface. Medtronic supplied the implant, and the participant and her caregivers used the home system." } }, "actors[].ownership_control": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed clinical sources identify the organizations involved, but do not establish their complete ownership or control arrangements.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed clinical sources identify the organizations involved, but do not establish their complete ownership or control arrangements." } }, "ai_contribution": { "state": "value_present", "value": { "kind": "text", "text": "Fitted signal-processing rules converted attempted hand movements into selections. The evidence supports this decoding contribution without identifying a learned AI model." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Fitted signal-processing rules converted attempted hand movements into selections. The evidence supports this decoding contribution without identifying a learned AI model." } }, "ai_relationship": { "state": "unresolved", "provenance": { "kind": "source_review", "basis": "Original papers and thesis, p. 35. These describe the mechanism without settling whether it qualifies as AI.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002", "AIBD-0265-source-0003" ], "reviewed_on": "2026-10-25" }, "reason": "Whether this interface uses AI remains unresolved. The documented decoder combines signal features and individually fitted thresholds.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Whether this interface uses AI remains unresolved. The documented decoder combines signal features and individually fitted thresholds." } }, "assessments[].alternatives": { "state": "value_present", "value": { "kind": "text", "text": "Depth 4 would require a separately established serious harm averted. The technical AI boundary remains distinct from the depth of the documented benefit." }, "provenance": { "kind": "curatorial", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Depth 4 would require a separately established serious harm averted. The technical AI boundary remains distinct from the depth of the documented benefit." } }, "assessments[].assessor_date": { "state": "value_present", "value": { "kind": "structured", "data": { "assessor": "AIBD, AI-assisted source review", "date": "2026-10-25" } }, "provenance": { "kind": "curatorial", "basis": "Review of the sources listed in the lineage assessment.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD, 25 October 2026." } }, "assessments[].depth": { "state": "value_present", "value": { "kind": "structured", "data": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The participant regained a lasting ability to communicate at home. The reports do not establish prevention of a separate serious harm." } ] } }, "provenance": { "kind": "curatorial", "basis": "Local five-level depth rubric; Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Depth 3 for restored communication that lasted nearly seven years." } }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "text", "text": "Peer-reviewed reports by the developers about one participant. The outline is retained." }, "provenance": { "kind": "curatorial", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Peer-reviewed reports by the developers about one participant. The outline is retained." } }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "text", "text": "Depth 3 for restored communication that lasted nearly seven years." }, "provenance": { "kind": "curatorial", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Depth 3 for restored communication that lasted nearly seven years." } }, "assessments[].rubric_version": { "state": "value_present", "value": { "kind": "text", "text": "AIBD’s five-level depth rubric, reviewed on 25 October 2026." }, "provenance": { "kind": "curatorial", "basis": "Local methodology; no separately numbered rubric version is published.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD’s five-level depth rubric, reviewed on 25 October 2026." } }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "The depth describes the reported result. Evidence strength is assessed separately." }, "provenance": { "kind": "curatorial", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The depth describes the reported result. Evidence strength is assessed separately." } }, "assessments[].target": { "state": "value_present", "value": { "kind": "text", "text": "The benefit described here, for the beneficiary groups shown." }, "provenance": { "kind": "curatorial", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. 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Replacement-device availability became a concern during follow-up." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "A single-participant clinical study with long-term follow-up." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A single-participant clinical study with long-term follow-up." } }, "case_links[]": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0052 cites this interface as a historical comparison. The two systems were not tested head to head." }, "provenance": { "kind": "curatorial", "basis": "Oxley et al. (2020), Discussion.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0052 cites this interface as a historical comparison. The two systems were not tested head to head." } }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "initial_communication": { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5326682/", "locator": "Results" }, "duration_and_end": { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11395392/", "locator": "Results: At-Home Use" }, "decoder_and_safety": { "url": "https://dspace.library.uu.nl/bitstream/handle/1874/457163/boekieuubieb_-_67f2a3c93d7ff.pdf?isAllowed=y&sequence=1", "locator": "p. 35; Chapter 6 supplement, pp. 152–156" } } }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. 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(2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources do not establish a learned AI model or exact software release. Private messages and active home-use accuracy were deliberately excluded from logs." } }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "The implant restored communication at home for nearly seven years, although the evidence does not establish a learned AI component." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The implant restored communication at home for nearly seven years, although the evidence does not establish a learned AI component." } }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not document international transfers of patient data or quantify cross-border financial flows.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not document international transfers of patient data or quantify cross-border financial flows." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "text", "text": "Clinicians implanted the system and researchers supported its use and adaptation at home." }, "provenance": { "kind": "source_review", "basis": "2016 Methods; 2024 Methods; NCT02224469, protocol UMCU 12-370.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Clinicians implanted the system and researchers supported its use and adaptation at home." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "text", "text": "The study received ethics approval and informed consent. Implant components were used off label." }, "provenance": { "kind": "source_review", "basis": "2016 Methods; 2024 Methods; NCT02224469, protocol UMCU 12-370.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study received ethics approval and informed consent. Implant components were used off label." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "text", "text": "UMC Utrecht tested an implanted means of communication for people with severe paralysis." }, "provenance": { "kind": "source_review", "basis": "2016 Methods; 2024 Methods; NCT02224469, protocol UMCU 12-370.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "UMC Utrecht tested an implanted means of communication for people with severe paralysis." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "text", "text": "Researchers evaluated communication control, usability, and long-term stability. The case report did not define a single financial or clinical pass threshold." }, "provenance": { "kind": "source_review", "basis": "2016 Methods; 2024 Methods; NCT02224469, protocol UMCU 12-370.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers evaluated communication control, usability, and long-term stability. The case report did not define a single financial or clinical pass threshold." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "An investigational implant used at home after months of training." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An investigational implant used at home after months of training." } }, "economics[].amount": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "economics[].costs[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "Medtronic provided the implant, antenna, and receiver to UMC Utrecht free of charge. Their market value and the full costs of care were not reported.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "Medtronic provided the implant, antenna, and receiver to UMC Utrecht free of charge. Their market value and the full costs of care were not reported." } }, "economics[].counterfactual": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. 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(2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "economics[].realization": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "economics[].recipient_payer": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "economics[].valuation_method": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report a monetary valuation or financial return.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The reviewed sources do not report a monetary valuation or financial return." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The study demonstrates the whole implanted interface. It does not isolate a machine-learning contribution, and its decoder is described through signal processing and fitted thresholds." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study demonstrates the whole implanted interface. It does not isolate a machine-learning contribution, and its decoder is described through signal processing and fitted thresholds." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "There was no control group. The participant also used an eye tracker until eye movement became unreliable." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "There was no control group. The participant also used an eye tracker until eye movement became unreliable." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "A prospective single-participant study, followed by a longitudinal report on the same woman." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A prospective single-participant study, followed by a longitudinal report on the same woman." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "structured", "data": { "target_accuracy_mean_percent": 91, "target_accuracy_SD": 6, "click_accuracy_mean_percent": 87, "click_accuracy_SD": 7, "spelling_accuracy_mean_percent": 89, "spelling_accuracy_SD": 6, "seconds_per_letter_with_prediction": 33, "seconds_per_letter_without_prediction": 52, "initial_home_use_days": 32, "initial_average_minutes_per_use_day": 86, "long_term_home_use": "nearly seven years" } }, "provenance": { "kind": "source_review", "basis": "2016 Results: Communication and Independent Home Use; 2024 Results.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Initial spelling accuracy averaged 89%. With word prediction, she selected about two letters per minute. Home use continued for nearly seven years." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "The initial report describes 67 two-hour research sessions over 262 days. Home use without investigators began on day 197 after implantation." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The initial report describes 67 two-hour research sessions over 262 days. Home use without investigators began on day 197 after implantation." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "NCT02224469" }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "NCT02224469" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Researchers tested clicks and spelling, collected satisfaction ratings, logged when the home system was available, and monitored brain signals and imaging." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers tested clicks and spelling, collected satisfaction ratings, logged when the home system was available, and monitored brain signals and imaging." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Selection accuracy, spelling speed, time with the system available at home, satisfaction, and persistence of usable control." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Selection accuracy, spelling speed, time with the system available at home, satisfaction, and persistence of usable control." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The original paper links two example task runs in Dryad. The follow-up supplement describes signal analysis. The thesis documents click thresholds and reproduces the follow-up supplement." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original paper links two example task runs in Dryad. The follow-up supplement describes signal analysis. The thesis documents click thresholds and reproduces the follow-up supplement." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "One participant at UMC Utrecht and in her home. Repeated task runs are observations from that same person." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. 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Declining control coincided with ALS progression, without proving a single cause." } }, "external_references[]": { "state": "value_present", "value": { "kind": "structured", "data": { "ClinicalTrials.gov": "NCT02224469" } }, "provenance": { "kind": "source_review", "basis": "Original study registration, inspected through the ClinicalTrials.gov API.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "NCT02224469" } }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "The system became her only communication technology after eye tracking ended in 2019. 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A decoder converted attempted movements into clicks for spelling and calling a caregiver." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "implant": "Medtronic Resume II electrode strips and Activa PC+S", "application": "Tobii Communicator 5", "initial_tablet": "Microsoft Surface Pro 4", "decoder": "z-scored low-frequency power subtracted from z-scored high-frequency power, followed by a threshold and click-window rules", "at_home_signal_frequency_Hz": 5, "low_frequency_band_Hz": [ 10, 30 ], "high_frequency_band_Hz": [ 65, 95 ], "December_2021_change": "Low-frequency activity from E2–E3 combined with high-frequency activity from E10–E12.", "exact_original_threshold": "Not recovered from the original 2016 supplement." } }, "provenance": { "kind": "source_review", "basis": "2016 Methods: Communication and Home Use; 2024 Methods; thesis, p. 35 and pp. 152–155.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001", "AIBD-0265-source-0002", "AIBD-0265-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The decoder combined low- and high-frequency brain activity and applied individually fitted click rules. The tablet ran Communicator 5." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Electrical activity from the motor cortex became click commands in a scanning communication interface." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Electrical activity from the motor cortex became click commands in a scanning communication interface." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A decoder based on normalized brain-signal power and fitted thresholds. No machine-learning model is identified." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. 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Activa PC+S and Communicator 5 identify hardware and application software." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "Utrecht NeuroProsthesis, using Activa PC+S and Communicator 5." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Utrecht NeuroProsthesis, using Activa PC+S and Communicator 5." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "UMC Utrecht developed the interface. Medtronic supplied the implant, and Tobii Dynavox supplied the communication software." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. 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The participant then selected letters or called for attention by attempting hand movements." }, "provenance": { "kind": "source_review", "basis": "Vansteensel et al. (2016), Methods and Results; Vansteensel et al. (2024), Methods and Results; Leinders (2025), pp. 35, 137–157.", "record_fields": [], "source_refs": [ "AIBD-0265-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A caregiver positioned the antenna and connected the tablet. The participant then selected letters or called for attention by attempting hand movements." } } }, "summary": { "total": 91, "addressed": 91, "known": 73, "reviewed": 81, "record_mapped": 7, "not_assessed": 3, "complete": false, "by_state": { "value_present": 73, "not_reported": 14, "unresolved": 1, "not_assessed": 3, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0222", "title": "Karolinska eye-tracking classifier flags 9–10-year-olds at risk of persistent reading difficulty with 95.6% cross-validated accuracy (PLoS ONE 2016)", "summary": "Nilsson Benfatto et al. trained an SVM on under-one-minute eye-tracking records from 97 high-risk and 88 low-risk Swedish children; 95.6% accuracy; two authors own equity in Optolexia.", "date_observed": "2016-12-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mattias Nilsson Benfatto, Gustaf Öqvist Seimyr, Jan Ygge, Tony Pansell and Agneta Rydberg of Karolinska Institutet worked with Christer Jacobson of Linnaeus University. Their PLoS ONE study (9 December 2016) showed eye-movement recordings of under one minute of reading can identify 9–10-year-olds at risk of persistent reading difficulties. With cross-validation on 97 high-risk and 88 low-risk control subjects, a support-vector machine with recursive feature elimination selected 48 of 168 features. It reached 95.6% (± 4.5%) accuracy with balanced sensitivity and specificity. The competing-interests statement says that Benfatto and Seimyr own equity in Optolexia, a company aiming to offer technologies for assessing reading deficits in school-age children. The venture is funded by Sweden's innovation agency VINNOVA. The work was also supported by the Ulla and Ingemar Dahlberg Foundation and the Promobilia Foundation, and data are on Figshare. This study was examined as the research basis of the Lexplore school screener. That name does not appear in the source text and no deployment source was found.", "category": "general benefit", "unexpected": false, "purpose": "The method was developed to screen for dyslexia risk from eye movements. The classification accuracy is that purpose.", "system": "Eye-tracking during reading with a support-vector-machine classifier (SVM-RFE, 48 features)", "model_version": null, "developer": "Karolinska Institutet (Nilsson Benfatto, Öqvist Seimyr and colleagues); two authors hold equity in Optolexia", "deployer": "None in the sources (research study)", "location": null, "domain": "Education / learning-disability screening", "segment": "Dyslexia risk screening of 9-10-year-olds", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individually attributable outcome: the source reports cross-validated classification accuracy (95.6%) on 185 children, not what followed for any child." } ], "ai_role": { "status": "assessed", "statement": "The classifier is the whole result. The authors describe it as a first step toward making eye tracking a viable screening method. No cited source shows it used in schools or affecting a child's support." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Nilsson Benfatto M, Öqvist Seimyr G, Ygge J, Pansell T, Rydberg A, Jacobson C (2016). Screening for Dyslexia Using Eye Tracking during Reading. PLoS ONE 11(12): e0165508 (PMC5147795).", "title": "Screening for Dyslexia Using Eye Tracking during Reading", "url": "https://europepmc.org/article/PMC/PMC5147795", "date": "2016-12-09", "written_by": "makers", "quote": "Using statistical cross-validation techniques on a sample of 97 high-risk and 88 low-risk control subjects, we achieve a classification accuracy of 96% with balanced levels of sensitivity and specificity." }, { "kind": "peer-reviewed study", "citation": "Nilsson Benfatto M, Öqvist Seimyr G, Ygge J, Pansell T, Rydberg A, Jacobson C (2016). Screening for Dyslexia Using Eye Tracking during Reading. PLoS ONE 11(12): e0165508 (publisher page).", "title": "Screening for Dyslexia Using Eye Tracking during Reading", "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165508", "date": "2016-12-09", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Eye-tracking records of under one minute of reading", "A labeled sample of 97 high-risk and 88 low-risk 9–10-year-olds", "Feature selection (SVM-RFE) within repeated cross-validation" ], "must_hold": [ "Eye-tracking hardware in the screening setting", "Reading material and norms for the child's language", "Validation on an independent sample, which the cited source does not report" ], "echoes": [] }, "paired_incident": null, "headline": "Karolinska eye-tracking SVM flags reading risk at 95.6% accuracy", "metric": "reached 95.6% (± 4.5%) accuracy with balanced sensitivity and specificity", "comparator": { "against": "chance-level classification on the same cross-validation (and random feature selection)", "before": "Chance: 49.1% ± 13%", "after": "95.6% ± 4.5%", "basis": "measured", "quote": "the best classification accuracy observed was 95.6% ± 4.5%, obtained by using SVM-RFE to select 48 features from the original feature space (Chance: 49.1% ± 13%, corrected resample t-test, p < 0.01; Random feature selection: 91.1% ± 6.1%, corrected resample t-test, p < 0.05)", "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165508" }, "later": { "status": "unknown", "date": null, "note": "No later development was found; the Optolexia equity and VINNOVA funding are disclosed in the paper itself.", "quote": null, "url": null }, "value": null, "developer_country": "Sweden", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165508", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Karolinska_Institute", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Karolinska Institutet.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0222", "catalog_version": "1.0.0", "source_fingerprint": "1a2a7defa892a72247f1cfae46c6e40be9d715cf84ac135129203946d4be5bcb", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0222-source-0001", "AIBD-0222-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Karolinska Institutet (Nilsson Benfatto, Öqvist Seimyr and colleagues); two authors hold equity in Optolexia", "deployer": "None in the sources (research study)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The classifier is the whole result. 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That name does not appear in the source text and no deployment source was found.", "replication": { "produced_by": [ "Eye-tracking records of under one minute of reading", "A labeled sample of 97 high-risk and 88 low-risk 9–10-year-olds", "Feature selection (SVM-RFE) within repeated cross-validation" ], "must_hold": [ "Eye-tracking hardware in the screening setting", "Reading material and norms for the child's language", "Validation on an independent sample, which the cited source does not report" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0008", "title": "Front crash prevention (FCW/AEB) associated with 27–50% lower rear-end striking crash rates in US police-reported data", "summary": "IIHS: FCW alone, low-speed AEB and FCW+AEB cut rear-end striking crash rates 27%, 43%, 50% in 22 US states, 2010–2014 (cohort)", "date_observed": "2017-02-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Jessica Cicchino (Insurance Institute for Highway Safety) published in Accident Analysis and Prevention volume 99 (February 2017). Her measure was police-reported crash involvements per insured vehicle year in 22 US states during 2010–2014. She compared passenger vehicle models with optional forward collision warning (FCW) alone or FCW with autonomous emergency braking (AEB) to the same models without it. She also compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with standard low-speed AEB to other luxury midsize cars and SUVs without it. FCW alone, low-speed AEB and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43% and 50%. Injury crash rates fell 20%, 45% and 56%. FCW with AEB increased rear-end struck involvements by 20%. No individual avoided crash is documented.", "category": "general benefit", "unexpected": false, "purpose": "Built to warn drivers and brake automatically when a frontal collision is imminent. The measured reduction in rear-end striking crashes is that purpose.", "system": "Front crash prevention systems (FCW, low-speed AEB, FCW with AEB) on passenger vehicles from multiple automakers, including Volvo's standard low-speed AEB on 2011–2012 S60 and 2010–2012 XC60", "model_version": null, "developer": null, "deployer": null, "location": null, "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "The study reports cohort-level rate reductions, not an individually attributable outcome." }, { "group": "personal", "depth": null, "reason": "The study reports cohort-level rate reductions without individually attributable outcomes." } ], "ai_role": { "status": "assessed", "statement": "Front crash prevention systems are automated perception-and-braking systems. The within-model comparisons (FCW alone, FCW with AEB) and Volvo S60/XC60 comparison with other luxury midsize cars and SUVs (low-speed AEB) control for other factors. They show effectiveness as a rate, not any single avoided crash. Whether such systems count as AI is a definitional choice the sources do not settle." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Cicchino, J.B. (2017). Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates. Accident Analysis and Prevention 99:142–152. doi:10.1016/j.aap.2016.11.009.", "title": "Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates", "url": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "date": "2017-02-01", "written_by": "independent", "quote": "FCW alone, low-speed AEB, and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43%, and 50%, respectively." }, { "kind": "regulatory document", "citation": "National Highway Traffic Safety Administration. Federal Motor Vehicle Safety Standards; Automatic Emergency Braking Systems for Light Vehicles. Final rule, 89 FR 39686, 9 May 2024 (FR Doc. 2024-09054).", "title": "Federal Motor Vehicle Safety Standards; Automatic Emergency Braking Systems for Light Vehicles", "url": "https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "date": "2024-05-09", "written_by": "independent", "quote": null, "supports_benefit": false } ], "replication": { "produced_by": [ "Vehicle fitted with FCW and/or AEB", "Rear-end conflict within the system's operating speed range" ], "must_hold": [ "FCW and FCW+AEB comparisons use the same vehicle models with and without the optional system, controlling for other crash-risk factors. The low-speed AEB comparison uses Volvo S60/XC60 models against other luxury midsize cars and SUVs without the system", "Results are rates per insured vehicle year, not individual events" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "341", "title": "Nissan's \"Automatic Emergency Braking\" False Positives Posed Traffic Risks to Drivers", "url": "https://incidentdatabase.ai/cite/341", "severity": null, "group": "societal", "basis": "Automatic emergency braking on passenger cars: Nissan's AEB false positives caused abrupt braking that endangered its drivers and other traffic participants, the road users whose rear-end crash rates FCW and AEB reduced in the IIHS data." }, "headline": "FCW and AEB cut rear-end striking crash rates 27–50%", "metric": "reduced rear-end striking crash involvement rates by 27%, 43% and 50%", "comparator": { "against": "the same vehicle models where the optional systems were not purchased (and comparable luxury vehicles without standard low-speed AEB)", "before": "the same models where the optional systems were not purchased", "after": "reduced rear-end striking crash involvement rates by 27%, 43%, and 50%, respectively", "basis": "measured", "quote": "FCW alone, low-speed AEB, and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43%, and 50%, respectively. Rates of rear-end striking crash involvements with injuries were reduced by 20%, 45%, and 56%, respectively, by FCW alone, low-speed AEB, and FCW with AEB, and rates of rear-end striking crash involvements with third-party injuries were reduced by 18%, 44%, and 59%, respectively.", "url": "https://www.iihs.org/research-areas/bibliography/ref/2111" }, "later": { "status": "scaled", "date": "2024-05-09", "note": "NHTSA adopted FMVSS No. 127 on 9 May 2024, requiring automatic emergency braking, including pedestrian AEB, on all new light vehicles.", "quote": "This final rule adopts a new Federal Motor Vehicle Safety Standard to require automatic emergency braking (AEB), including pedestrian AEB (PAEB), systems on light vehicles.", "url": "https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 341 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/341", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account, what must hold again and AI-role statement corrected because only the FCW-alone and FCW-with-AEB analyzes compared the same models with and without the option; the low-speed AEB analysis compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with other luxury midsize cars and SUVs without the system.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.iihs.org/research-areas/bibliography/ref/2111; https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent regulatory document and one independent peer-reviewed study. For the benefit itself, the cited sources include no finding by a regulator or court.", "profile": { "case_id": "AIBD-0008", "catalog_version": "1.0.0", "source_fingerprint": "df8e8ec80818121bddb21f4f91dbf3feb4d9fd7909650d273aa9c41a6b3ef04e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0008-source-0001", "AIBD-0008-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Front crash prevention systems are automated perception-and-braking systems. 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"outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jessica Cicchino (Insurance Institute for Highway Safety) published in Accident Analysis and Prevention volume 99 (February 2017). Her measure was police-reported crash involvements per insured vehicle year in 22 US states during 2010–2014. She compared passenger vehicle models with optional forward collision warning (FCW) alone or FCW with autonomous emergency braking (AEB) to the same models without it. She also compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with standard low-speed AEB to other luxury midsize cars and SUVs without it. FCW alone, low-speed AEB and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43% and 50%. Injury crash rates fell 20%, 45% and 56%. FCW with AEB increased rear-end struck involvements by 20%. No individual avoided crash is documented.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The study reports cohort-level rate reductions, not an individually attributable outcome." }, { "group": "personal", "reason": "The study reports cohort-level rate reductions without individually attributable outcomes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to warn drivers and brake automatically when a frontal collision is imminent. The measured reduction in rear-end striking crashes is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to warn drivers and brake automatically when a frontal collision is imminent. The measured reduction in rear-end striking crashes is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2017-02-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 341 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/341", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account, what must hold again and AI-role statement corrected because only the FCW-alone and FCW-with-AEB analyzes compared the same models with and without the option; the low-speed AEB analysis compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with other luxury midsize cars and SUVs without the system.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.iihs.org/research-areas/bibliography/ref/2111; https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Vehicle fitted with FCW and/or AEB", "Rear-end conflict within the system's operating speed range" ], "must_hold": [ "FCW and FCW+AEB comparisons use the same vehicle models with and without the optional system, controlling for other crash-risk factors. The low-speed AEB comparison uses Volvo S60/XC60 models against other luxury midsize cars and SUVs without the system", "Results are rates per insured vehicle year, not individual events" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 341 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/341", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account, what must hold again and AI-role statement corrected because only the FCW-alone and FCW-with-AEB analyzes compared the same models with and without the option; the low-speed AEB analysis compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with other luxury midsize cars and SUVs without the system.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.iihs.org/research-areas/bibliography/ref/2111; https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road vehicle crash avoidance", "segment": "Automotive" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Cicchino, J.B. (2017). Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates. Accident Analysis and Prevention 99:142–152. doi:10.1016/j.aap.2016.11.009.", "title": "Effectiveness of forward collision warning and autonomous emergency braking systems in reducing front-to-rear crash rates", "url": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "date": "2017-02-01", "written_by": "independent", "quote": "FCW alone, low-speed AEB, and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43%, and 50%, respectively." }, { "kind": "regulatory document", "citation": "National Highway Traffic Safety Administration. Federal Motor Vehicle Safety Standards; Automatic Emergency Braking Systems for Light Vehicles. Final rule, 89 FR 39686, 9 May 2024 (FR Doc. 2024-09054).", "title": "Federal Motor Vehicle Safety Standards; Automatic Emergency Braking Systems for Light Vehicles", "url": "https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "date": "2024-05-09", "written_by": "independent", "supports_benefit": false } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0008-source-0001", "AIBD-0008-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The IIHS paper reports the crash-rate estimates. Its bibliography page is another version of the same work. NHTSA cited that research when adopting a later rule." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0008-source-0001", "AIBD-0008-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The IIHS paper reports the crash-rate estimates. Its bibliography page is another version of the same work. NHTSA cited that research when adopting a later rule." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0008-source-0001", "retained_source_order": [ "AIBD-0008-source-0001", "AIBD-0008-source-0002" ], "origins": [ { "url": "https://www.reginfo.gov/public/do/eoDownloadDocument?pubId=&eodoc=true&documentID=219043", "locator": "Abstract; methods and results; Table 3.", "contribution": "Original estimates for rear-end striking and injury crashes.", "relationship": "Independent observational study by Jessica Cicchino at IIHS.", "source_refs": [ "AIBD-0008-source-0001" ] }, { "url": "https://www.iihs.org/research-areas/bibliography/ref/2111", "locator": "Bibliographic record and abstract.", "contribution": "An institutional access page for the same 2017 study.", "relationship": "The same work, not another study.", "source_refs": [ "AIBD-0008-source-0001" ] }, { "url": "https://www.federalregister.gov/documents/2024/05/09/2024-09054/federal-motor-vehicle-safety-standards-automatic-emergency-braking-systems-for-light-vehicles", "locator": "Final rule, § VI; pp. 39716–39717.", "contribution": "The later mandate and its use of published crash research.", "relationship": "A regulatory instrument; contextual to the study result.", "source_refs": [ "AIBD-0008-source-0002" ] } ], "excluded_or_consolidated_sources": [ { "url": "https://www.iihs.org/research-areas/bibliography/ref/2111", "reason": "Institutional abstract of the retained original paper. Its findings, including the increase in rear-end struck crashes, remain in that paper.", "retained_source_ref": "AIBD-0008-source-0001" } ], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0008-source-0001", "AIBD-0008-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The IIHS paper reports the crash-rate estimates. Its bibliography page is another version of the same work. NHTSA cited that research when adopting a later rule." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "IIHS: FCW alone, low-speed AEB and FCW+AEB cut rear-end striking crash rates 27%, 43%, 50% in 22 US states, 2010–2014 (cohort)", "account": "Jessica Cicchino (Insurance Institute for Highway Safety) published in Accident Analysis and Prevention volume 99 (February 2017). Her measure was police-reported crash involvements per insured vehicle year in 22 US states during 2010–2014. She compared passenger vehicle models with optional forward collision warning (FCW) alone or FCW with autonomous emergency braking (AEB) to the same models without it. She also compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with standard low-speed AEB to other luxury midsize cars and SUVs without it. FCW alone, low-speed AEB and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43% and 50%. Injury crash rates fell 20%, 45% and 56%. FCW with AEB increased rear-end struck involvements by 20%. No individual avoided crash is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Front crash prevention systems (FCW, low-speed AEB, FCW with AEB) on passenger vehicles from multiple automakers, including Volvo's standard low-speed AEB on 2011–2012 S60 and 2010–2012 XC60" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Front crash prevention (FCW/AEB) associated with 27–50% lower rear-end striking crash rates in US police-reported data", "headline": "FCW and AEB cut rear-end striking crash rates 27–50%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "df8e8ec80818121bddb21f4f91dbf3feb4d9fd7909650d273aa9c41a6b3ef04e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jessica Cicchino (Insurance Institute for Highway Safety) published in Accident Analysis and Prevention volume 99 (February 2017). Her measure was police-reported crash involvements per insured vehicle year in 22 US states during 2010–2014. She compared passenger vehicle models with optional forward collision warning (FCW) alone or FCW with autonomous emergency braking (AEB) to the same models without it. She also compared Volvo 2011–2012 S60 and 2010–2012 XC60 vehicles with standard low-speed AEB to other luxury midsize cars and SUVs without it. FCW alone, low-speed AEB and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43% and 50%. Injury crash rates fell 20%, 45% and 56%. FCW with AEB increased rear-end struck involvements by 20%. No individual avoided crash is documented.", "replication": { "produced_by": [ "Vehicle fitted with FCW and/or AEB", "Rear-end conflict within the system's operating speed range" ], "must_hold": [ "FCW and FCW+AEB comparisons use the same vehicle models with and without the optional system, controlling for other crash-risk factors. The low-speed AEB comparison uses Volvo S60/XC60 models against other luxury midsize cars and SUVs without the system", "Results are rates per insured vehicle year, not individual events" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 2, "record_mapped": 25, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0219", "title": "Japan's Fire and Disaster Management Agency and NICT roll out Kyukyu VoiceTra, a 15-language speech-translation app for ambulance crews, to fire headquarters nationwide", "summary": "From April 2017 NICT and the FDMA provided Kyukyu VoiceTra (VoiceTra with medical terms and 46 fixed phrases, 15 languages) to fire headquarters across Japan; Sapporo used it from February 2017.", "date_observed": "2017-04-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "NICT announced on 18 April 2017 that Kyukyu VoiceTra would be provided to fire headquarters nationwide from that month. The speech-translation app for ambulance crews was developed with the Fire and Disaster Management Agency (FDMA) and its Fire Research Center on NICT's VoiceTra engine. It adds medical terms to improve free-text translation accuracy and 46 fixed phrases for emergency scenes in 15 languages. The Sapporo Fire Department had used it since February 2017. The Ministry of Internal Affairs and Communications' 2017 white paper covers the R&D, part of the action plan toward 2020. It records completion as Kyukyu VoiceTra in April 2017 and the start of provision to all fire headquarters. Its download figures (205,421 by end-FY2015 and 621,221 by end-FY2016) are for the general VoiceTra app. The trade publication risktaisaku.com (8 May 2017) described the Android release, a planned iOS version and on-screen text that also helps communication with hearing-impaired patients. Ninomiya Town's fire service announced its own adoption on 6 December 2022. No cited source documents a patient-level outcome or a count of adopting headquarters.", "category": "general benefit", "unexpected": false, "purpose": "Built to let ambulance crews communicate with foreign patients quickly at emergency scenes. The nationwide provision is that purpose, without a documented outcome.", "system": "Kyukyu VoiceTra (救急ボイストラ): multilingual speech-translation app for ambulance crews built on NICT's VoiceTra engine, 15 languages, 46 fixed phrases", "model_version": null, "developer": "NICT (National Institute of Information and Communications Technology) with the Fire and Disaster Management Agency and its Fire Research Center", "deployer": "Fire headquarters across Japan (Sapporo Fire Department from February 2017; Ninomiya Town fire service from 2022)", "location": null, "domain": "Emergency medical services / language access", "segment": "Ambulance crew communication with foreign patients", "benefit_type": "Increased Inclusion", "taxonomy_note": "The intended good is that non-Japanese speakers can be understood by ambulance crews, a language-access gain rather than acceptance as such, and no outcome is measured.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No cited source documents an outcome for a foreign patient. The sources describe capability and rollout only." }, { "group": "organizational", "depth": null, "reason": "No cited source gives adoption counts or usage outcomes for fire headquarters. Ninomiya Town's page records adoption, not results." } ], "ai_role": { "status": "assessed", "statement": "The app performs speech recognition and translation at the scene. Fixed phrases reduce reliance on free-text translation. Developer (NICT, a public research institute) and the agency that distributes it (FDMA) are both public bodies. The deploying fire headquarters are local governments. No independent evaluation of accuracy or outcomes is among the sources." }, "evidence": [ { "kind": "press release", "citation": "NICT (18 Apr 2017). 救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！ (NICT announcement; NICT is the developer).", "title": "救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！", "url": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html", "date": "2017-04-18", "written_by": "makers", "quote": "医療用語を追加して自由文入力の音声翻訳精度を高めるとともに、定型表現(46文)を追加した救急隊用のアプリを新たに開発しました。" }, { "kind": "report", "citation": "総務省 (2017). 平成29年版 情報通信白書, 第5節（3）救急用多言語音声翻訳システムの研究開発 (ministry white paper).", "title": "総務省｜平成29年版 情報通信白書｜救急用多言語音声翻訳システムの研究開発", "url": "https://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h29/html/nc155230.html", "date": null, "written_by": "makers", "quote": "2017年4月には、上記の機能等が備わった「救急ボイストラ」として完成させ、救急隊が活用できるよう全国の消防本部へ提供を開始するとともに、活用を促進した。" }, { "kind": "news report", "citation": "リスク対策.com (8 May 2017). 消防庁、救急隊用15言語対応アプリ.", "title": "消防庁、救急隊用15言語対応アプリ", "url": "https://www.risktaisaku.com/articles/-/2758", "date": "2017-05-08", "written_by": "independent", "quote": "言語を選択し、現場でよく使われる46の定型文を選択すると、選択した言語で画面表示がなされ音声が流れる。" }, { "kind": "press release", "citation": "二宮町 (6 Dec 2022). 救急ボイストラを導入しました。 (deploying municipality's page).", "title": "救急ボイストラを導入しました。", "url": "https://www.town.ninomiya.kanagawa.jp/0000001513.html", "date": "2022-12-06", "written_by": "deployer", "quote": "外国語による音声と画面の文字による円滑なコミュニケーションを図ることが可能となります。" } ], "replication": { "produced_by": [ "A general-purpose national speech-translation engine (VoiceTra) adapted with domain vocabulary", "Fixed phrases for the commonest emergency-scene exchanges, with touch-screen answers translated back", "Free distribution by the national fire agency to local fire headquarters" ], "must_hold": [ "Smartphones available to ambulance crews", "Coverage of the patient's language among the 15 supported", "Crew training (several municipal pages describe drills)" ], "echoes": [ { "date": "2022-12-06", "setting": "Ninomiya Town, Kanagawa: fire service announces it has started operating Kyukyu VoiceTra", "model_version": null, "outcome": "unknown", "source": "二宮町, https://www.town.ninomiya.kanagawa.jp/0000001513.html" } ] }, "paired_incident": null, "headline": "Kyukyu VoiceTra translates for ambulance crews across Japan", "metric": null, "comparator": { "against": "the conventional way of communicating with foreign patients before the app (従来)", "before": null, "after": "従来に比べ、外国人傷病者に対してスピーディーかつ円滑にコミュニケーションが図れるようになり", "basis": "measured", "quote": "実フィールドで検証した結果、従来に比べ、外国人傷病者に対してスピーディーかつ円滑にコミュニケーションが図れるようになり、実用レベルに達していることが確認できましたので、このたび「救急ボイストラ」という名称で、全国の消防本部への提供を開始することとしました。", "url": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html" }, "later": { "status": "scaled", "date": "2022-12-06", "note": "Ninomiya Town's fire station announced in December 2022 that it had started operating Kyukyu VoiceTra, a further adoption more than five years after the nationwide release.", "quote": "二宮町消防署では救急ボイストラの運用を開始しました。", "url": "https://www.town.ninomiya.kanagawa.jp/0000001513.html" }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html; https://www.town.ninomiya.kanagawa.jp/0000001513.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.nict.go.jp/en/about/location.html; https://ja.wikipedia.org/wiki/%E6%9C%AD%E5%B9%8C%E5%B8%82%E6%B6%88%E9%98%B2%E5%B1%80", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' report, the makers' press release and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0219", "catalog_version": "1.0.0", "source_fingerprint": "cdb855e8baa2aaeb61b16da9660960a0bb26d5e07a1749dcc3fde320d21fde28", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0219-source-0001", "AIBD-0219-source-0002", "AIBD-0219-source-0003", "AIBD-0219-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "NICT (National Institute of Information and Communications Technology) with the Fire and Disaster Management Agency and its Fire Research Center", "deployer": "Fire headquarters across Japan (Sapporo Fire Department from February 2017; Ninomiya Town fire service from 2022)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The app performs speech recognition and translation at the scene. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No cited source documents an outcome for a foreign patient. The sources describe capability and rollout only." }, { "group": "organizational", "reason": "No cited source gives adoption counts or usage outcomes for fire headquarters. 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"evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2022-12-06", "note": "Ninomiya Town's fire station announced in December 2022 that it had started operating Kyukyu VoiceTra, a further adoption more than five years after the nationwide release.", "quote": "二宮町消防署では救急ボイストラの運用を開始しました。", "url": "https://www.town.ninomiya.kanagawa.jp/0000001513.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0219" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Inclusion", "taxonomy_note": "The intended good is that non-Japanese speakers can be understood by ambulance crews, a language-access gain rather than acceptance as such, and no outcome is measured." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "NICT announced on 18 April 2017 that Kyukyu VoiceTra would be provided to fire headquarters nationwide from that month. The speech-translation app for ambulance crews was developed with the Fire and Disaster Management Agency (FDMA) and its Fire Research Center on NICT's VoiceTra engine. It adds medical terms to improve free-text translation accuracy and 46 fixed phrases for emergency scenes in 15 languages. The Sapporo Fire Department had used it since February 2017. The Ministry of Internal Affairs and Communications' 2017 white paper covers the R&D, part of the action plan toward 2020. It records completion as Kyukyu VoiceTra in April 2017 and the start of provision to all fire headquarters. Its download figures (205,421 by end-FY2015 and 621,221 by end-FY2016) are for the general VoiceTra app. The trade publication risktaisaku.com (8 May 2017) described the Android release, a planned iOS version and on-screen text that also helps communication with hearing-impaired patients. Ninomiya Town's fire service announced its own adoption on 6 December 2022. No cited source documents a patient-level outcome or a count of adopting headquarters.", "benefit_type": "Increased Inclusion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No cited source documents an outcome for a foreign patient. The sources describe capability and rollout only." }, { "group": "organizational", "reason": "No cited source gives adoption counts or usage outcomes for fire headquarters. Ninomiya Town's page records adoption, not results." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to let ambulance crews communicate with foreign patients quickly at emergency scenes. The nationwide provision is that purpose, without a documented outcome." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Japan", "deployer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to let ambulance crews communicate with foreign patients quickly at emergency scenes. The nationwide provision is that purpose, without a documented outcome." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2017-04-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html; https://www.town.ninomiya.kanagawa.jp/0000001513.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.nict.go.jp/en/about/location.html; https://ja.wikipedia.org/wiki/%E6%9C%AD%E5%B9%8C%E5%B8%82%E6%B6%88%E9%98%B2%E5%B1%80", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A general-purpose national speech-translation engine (VoiceTra) adapted with domain vocabulary", "Fixed phrases for the commonest emergency-scene exchanges, with touch-screen answers translated back", "Free distribution by the national fire agency to local fire headquarters" ], "must_hold": [ "Smartphones available to ambulance crews", "Coverage of the patient's language among the 15 supported", "Crew training (several municipal pages describe drills)" ], "echoes": [ { "date": "2022-12-06", "setting": "Ninomiya Town, Kanagawa: fire service announces it has started operating Kyukyu VoiceTra", "outcome": "unknown", "source": "二宮町, https://www.town.ninomiya.kanagawa.jp/0000001513.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A general-purpose national speech-translation engine (VoiceTra) adapted with domain vocabulary", "Fixed phrases for the commonest emergency-scene exchanges, with touch-screen answers translated back", "Free distribution by the national fire agency to local fire headquarters" ], "must_hold": [ "Smartphones available to ambulance crews", "Coverage of the patient's language among the 15 supported", "Crew training (several municipal pages describe drills)" ], "echoes": [ { "date": "2022-12-06", "setting": "Ninomiya Town, Kanagawa: fire service announces it has started operating Kyukyu VoiceTra", "outcome": "unknown", "source": "二宮町, https://www.town.ninomiya.kanagawa.jp/0000001513.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html; https://www.town.ninomiya.kanagawa.jp/0000001513.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.nict.go.jp/en/about/location.html; https://ja.wikipedia.org/wiki/%E6%9C%AD%E5%B9%8C%E5%B8%82%E6%B6%88%E9%98%B2%E5%B1%80", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Emergency medical services / language access", "segment": "Ambulance crew communication with foreign patients" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "NICT (18 Apr 2017). 救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！ (NICT announcement; NICT is the developer).", "title": "救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！", "url": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html", "date": "2017-04-18", "written_by": "makers", "quote": "医療用語を追加して自由文入力の音声翻訳精度を高めるとともに、定型表現(46文)を追加した救急隊用のアプリを新たに開発しました。" }, { "kind": "report", "citation": "総務省 (2017). 平成29年版 情報通信白書, 第5節（3）救急用多言語音声翻訳システムの研究開発 (ministry white paper).", "title": "総務省｜平成29年版 情報通信白書｜救急用多言語音声翻訳システムの研究開発", "url": "https://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h29/html/nc155230.html", "written_by": "makers", "quote": "2017年4月には、上記の機能等が備わった「救急ボイストラ」として完成させ、救急隊が活用できるよう全国の消防本部へ提供を開始するとともに、活用を促進した。" }, { "kind": "news report", "citation": "リスク対策.com (8 May 2017). 消防庁、救急隊用15言語対応アプリ.", "title": "消防庁、救急隊用15言語対応アプリ", "url": "https://www.risktaisaku.com/articles/-/2758", "date": "2017-05-08", "written_by": "independent", "quote": "言語を選択し、現場でよく使われる46の定型文を選択すると、選択した言語で画面表示がなされ音声が流れる。" }, { "kind": "press release", "citation": "二宮町 (6 Dec 2022). 救急ボイストラを導入しました。 (deploying municipality's page).", "title": "救急ボイストラを導入しました。", "url": "https://www.town.ninomiya.kanagawa.jp/0000001513.html", "date": "2022-12-06", "written_by": "deployer", "quote": "外国語による音声と画面の文字による円滑なコミュニケーションを図ることが可能となります。" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0219-source-0001", "AIBD-0219-source-0002", "AIBD-0219-source-0003", "AIBD-0219-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "NICT (18 Apr 2017). 救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！ (NICT announcement; NICT is the developer).", "title": "救急隊用音声翻訳アプリ「救急ボイストラ」が全国の消防本部へ！", "url": "https://www.nict.go.jp/info/topics/2017/04/170418-1.html", "date": "2017-04-18", "written_by": "makers", "quote": "医療用語を追加して自由文入力の音声翻訳精度を高めるとともに、定型表現(46文)を追加した救急隊用のアプリを新たに開発しました。" }, { "kind": "report", "citation": "総務省 (2017). 平成29年版 情報通信白書, 第5節（3）救急用多言語音声翻訳システムの研究開発 (ministry white paper).", "title": "総務省｜平成29年版 情報通信白書｜救急用多言語音声翻訳システムの研究開発", "url": "https://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h29/html/nc155230.html", "written_by": "makers", "quote": "2017年4月には、上記の機能等が備わった「救急ボイストラ」として完成させ、救急隊が活用できるよう全国の消防本部へ提供を開始するとともに、活用を促進した。" }, { "kind": "news report", "citation": "リスク対策.com (8 May 2017). 消防庁、救急隊用15言語対応アプリ.", "title": "消防庁、救急隊用15言語対応アプリ", "url": "https://www.risktaisaku.com/articles/-/2758", "date": "2017-05-08", "written_by": "independent", "quote": "言語を選択し、現場でよく使われる46の定型文を選択すると、選択した言語で画面表示がなされ音声が流れる。" }, { "kind": "press release", "citation": "二宮町 (6 Dec 2022). 救急ボイストラを導入しました。 (deploying municipality's page).", "title": "救急ボイストラを導入しました。", "url": "https://www.town.ninomiya.kanagawa.jp/0000001513.html", "date": "2022-12-06", "written_by": "deployer", "quote": "外国語による音声と画面の文字による円滑なコミュニケーションを図ることが可能となります。" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "From April 2017 NICT and the FDMA provided Kyukyu VoiceTra (VoiceTra with medical terms and 46 fixed phrases, 15 languages) to fire headquarters across Japan; Sapporo used it from February 2017.", "account": "NICT announced on 18 April 2017 that Kyukyu VoiceTra would be provided to fire headquarters nationwide from that month. The speech-translation app for ambulance crews was developed with the Fire and Disaster Management Agency (FDMA) and its Fire Research Center on NICT's VoiceTra engine. It adds medical terms to improve free-text translation accuracy and 46 fixed phrases for emergency scenes in 15 languages. The Sapporo Fire Department had used it since February 2017. The Ministry of Internal Affairs and Communications' 2017 white paper covers the R&D, part of the action plan toward 2020. It records completion as Kyukyu VoiceTra in April 2017 and the start of provision to all fire headquarters. Its download figures (205,421 by end-FY2015 and 621,221 by end-FY2016) are for the general VoiceTra app. The trade publication risktaisaku.com (8 May 2017) described the Android release, a planned iOS version and on-screen text that also helps communication with hearing-impaired patients. Ninomiya Town's fire service announced its own adoption on 6 December 2022. No cited source documents a patient-level outcome or a count of adopting headquarters." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Kyukyu VoiceTra (救急ボイストラ): multilingual speech-translation app for ambulance crews built on NICT's VoiceTra engine, 15 languages, 46 fixed phrases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "NICT (National Institute of Information and Communications Technology) with the Fire and Disaster Management Agency and its Fire Research Center" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Japan's Fire and Disaster Management Agency and NICT roll out Kyukyu VoiceTra, a 15-language speech-translation app for ambulance crews, to fire headquarters nationwide", "headline": "Kyukyu VoiceTra translates for ambulance crews across Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cdb855e8baa2aaeb61b16da9660960a0bb26d5e07a1749dcc3fde320d21fde28" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "NICT announced on 18 April 2017 that Kyukyu VoiceTra would be provided to fire headquarters nationwide from that month. The speech-translation app for ambulance crews was developed with the Fire and Disaster Management Agency (FDMA) and its Fire Research Center on NICT's VoiceTra engine. It adds medical terms to improve free-text translation accuracy and 46 fixed phrases for emergency scenes in 15 languages. The Sapporo Fire Department had used it since February 2017. The Ministry of Internal Affairs and Communications' 2017 white paper covers the R&D, part of the action plan toward 2020. It records completion as Kyukyu VoiceTra in April 2017 and the start of provision to all fire headquarters. Its download figures (205,421 by end-FY2015 and 621,221 by end-FY2016) are for the general VoiceTra app. The trade publication risktaisaku.com (8 May 2017) described the Android release, a planned iOS version and on-screen text that also helps communication with hearing-impaired patients. Ninomiya Town's fire service announced its own adoption on 6 December 2022. No cited source documents a patient-level outcome or a count of adopting headquarters.", "replication": { "produced_by": [ "A general-purpose national speech-translation engine (VoiceTra) adapted with domain vocabulary", "Fixed phrases for the commonest emergency-scene exchanges, with touch-screen answers translated back", "Free distribution by the national fire agency to local fire headquarters" ], "must_hold": [ "Smartphones available to ambulance crews", "Coverage of the patient's language among the 15 supported", "Crew training (several municipal pages describe drills)" ], "echoes": [ { "date": "2022-12-06", "setting": "Ninomiya Town, Kanagawa: fire service announces it has started operating Kyukyu VoiceTra", "outcome": "unknown", "source": "二宮町, https://www.town.ninomiya.kanagawa.jp/0000001513.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0097", "title": "American Red Cross used Facebook's machine-learning population maps to focus Malawi mapping for the June 2017 measles vaccination campaign (Measles & Rubella Initiative)", "summary": "Facebook's ML settlement maps cut Red Cross mapping for Malawi's June 2017 measles vaccination campaign (Measles & Rubella Initiative) from 94,080 km² to 2,745 km²", "date_observed": "2017-06-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Malawi's June 2017 measles vaccination campaign (Measles & Rubella Initiative) targeted more than 7.5 million children. The American Red Cross's Missing Maps team needed base maps for campaign monitoring. Facebook's population maps come from a machine-learning computer-vision method that detects buildings in satellite imagery. They were used to identify where people lived and which areas were already mapped in OpenStreetMap. Concentrating volunteers on settlements filtered out 97.1% of the land area. That reduced the area to map from 94,080 km² to 2,745 km² and completed the base map in a fraction of the normal time. The base map was to feed a dashboard for government and Red Cross monitors during the campaign. The article predates the campaign and reports no monitoring outcome. No vaccination-coverage outcome attributable to the maps is reported.", "category": "benefit created", "unexpected": false, "purpose": "Produce high-resolution population and settlement maps from satellite imagery for planning and humanitarian use.", "system": "Facebook (Meta) High Resolution Settlement Layer population density maps", "model_version": null, "developer": "Facebook Inc. with CIESIN, Columbia University, and the World Bank Development Data Group", "deployer": "American Red Cross (Missing Maps) supporting the Measles and Rubella Initiative campaign in Malawi", "location": "Malawi (nationwide)", "domain": "Humanitarian mapping for immunization campaign support", "segment": "Humanitarian NGO", "benefit_type": "Reduced Task Time", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The source reports no outcome for the 7.5 million targeted children. Any benefit is indirect and unquantified." }, { "group": "organizational", "depth": 2, "reason": "Mapping area reduced from 94,080 km² to 2,745 km² and the base map completed in a fraction of the normal time." }, { "group": "societal", "depth": null, "reason": "A supporting role in one national campaign whose coverage effect was not measured." } ], "ai_role": { "status": "assessed", "statement": "The Facebook settlement data determined where volunteer mapping effort went and which areas were skipped. The campaign itself was a Measles & Rubella Initiative effort supported by the American Red Cross and other partners, with monitors from the national government. The Red Cross attributes efficiency, not coverage, to the maps. The Red Cross account is the implementing organization's and names only “Facebook's population datasets”, without mentioning machine learning. The identification with the High Resolution Settlement Layer and the machine-learning description are taken from the vendor-authored Tiecke et al. preprint. It does not mention the Malawi campaign." }, "evidence": [ { "kind": "press release", "citation": "American Red Cross (2017). Data: A vital tool for disaster response.", "title": "Data: A vital tool for disaster response", "url": "https://www.redcross.org/about-us/news-and-events/news/Data-A-vital-tool-for-disaster-response.html", "date": "2017-06-07", "written_by": "deployer", "quote": "This technique reduced our mapping area from 94,080km2 to 2,745 km2." }, { "kind": "preprint", "citation": "Tiecke, T. G., Liu, X., Zhang, A., Gros, A., Li, N., Yetman, G., et al. (2017). Mapping the world population one building at a time. arXiv:1712.05839.", "title": "Mapping the world population one building at a time", "url": "https://arxiv.org/abs/1712.05839", "date": "2017-12-15", "written_by": "makers", "quote": "a computer vision method based on machine learning to create population maps from satellite imagery at a global scale" }, { "kind": "press release", "citation": "Eros, E., Schmeltzer, A. (2017). Stop the spots: Measles vaccinations in Malawi. Missing Maps blog (American Red Cross), 10 August 2017.", "title": "Stop the spots: Measles vaccinations in Malawi", "url": "https://www.missingmaps.org/blog/2017/08/10/malawi/", "date": "2017-08-10", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Facebook settlement detection from satellite imagery", "Missing Maps volunteer tracing into OpenStreetMap", "Comparison with existing OpenStreetMap coverage", "Mobile data-collection dashboard for campaign monitors" ], "must_hold": [ "Imagery recent enough to reflect current settlements", "Building-detection accuracy in rural Malawi", "Volunteer and local mapping capacity" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1159", "title": "Government‑Backed AI4Peat Mapping Tool Allegedly Misidentifies Granite Outcrops and Quarries as Peat", "url": "https://incidentdatabase.ai/cite/1159", "severity": null, "group": "organizational", "basis": "Government-backed machine-learning mapping from imagery misclassified land as peat, misleading restoration programs; Facebook's building-detection population maps steer humanitarian mapping the same way." }, "headline": "Facebook ML maps cut Red Cross Malawi mapping area to 2,745 km²", "metric": "reducing the area to map from 94,080 km² to 2,745 km²", "comparator": { "against": "mapping the whole national land area without the settlement maps (the normal Missing Maps approach)", "before": "94,080km2", "after": "2,745 km2", "basis": "measured", "quote": "Much of Malawi is rural, so concentrating on population settlements allowed us to filter out 97.1% of the total land area that we sought to map. This technique reduced our mapping area from 94,080km2 to 2,745 km2. Volunteers could then spend their time mapping communities instead of searching through acres of uninhabited areas; they were able to complete the mapping in a fraction of the normal time.", "url": "https://www.redcross.org/about-us/news-and-events/news/Data-A-vital-tool-for-disaster-response.html" }, "later": { "status": "persisted", "date": "2017-08-10", "note": "After the June 2017 campaign the Red Cross's Missing Maps team reported that the traced base map underpinned a real-time monitoring dashboard covering 13,743 children, and again credited Facebook's population data with filtering uninhabited areas out of the tracing tasks.", "quote": "We are also grateful for Facebook’s high-resolution population data for Malawi, which helped us to identify areas with and without concentrations of people. 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external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Facebook settlement detection from satellite imagery", "Missing Maps volunteer tracing into OpenStreetMap", "Comparison with existing OpenStreetMap coverage", "Mobile data-collection dashboard for campaign monitors" ], "must_hold": [ "Imagery recent enough to reflect current settlements", "Building-detection accuracy in rural Malawi", "Volunteer and local mapping capacity" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1159 (medium confidence); 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external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Humanitarian mapping for immunization campaign support", "segment": "Humanitarian NGO" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "American Red Cross (2017). Data: A vital tool for disaster response.", "title": "Data: A vital tool for disaster response", "url": "https://www.redcross.org/about-us/news-and-events/news/Data-A-vital-tool-for-disaster-response.html", "date": "2017-06-07", "written_by": "deployer", "quote": "This technique reduced our mapping area from 94,080km2 to 2,745 km2." }, { "kind": "preprint", "citation": "Tiecke, T. G., Liu, X., Zhang, A., Gros, A., Li, N., Yetman, G., et al. (2017). Mapping the world population one building at a time. arXiv:1712.05839.", "title": "Mapping the world population one building at a time", "url": "https://arxiv.org/abs/1712.05839", "date": "2017-12-15", "written_by": "makers", "quote": "a computer vision method based on machine learning to create population maps from satellite imagery at a global scale" }, { "kind": "press release", "citation": "Eros, E., Schmeltzer, A. (2017). Stop the spots: Measles vaccinations in Malawi. Missing Maps blog (American Red Cross), 10 August 2017.", "title": "Stop the spots: Measles vaccinations in Malawi", "url": "https://www.missingmaps.org/blog/2017/08/10/malawi/", "date": "2017-08-10", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0097-source-0001", "AIBD-0097-source-0002", "AIBD-0097-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "American Red Cross (2017). Data: A vital tool for disaster response.", "title": "Data: A vital tool for disaster response", "url": "https://www.redcross.org/about-us/news-and-events/news/Data-A-vital-tool-for-disaster-response.html", "date": "2017-06-07", "written_by": "deployer", "quote": "This technique reduced our mapping area from 94,080km2 to 2,745 km2." }, { "kind": "preprint", "citation": "Tiecke, T. G., Liu, X., Zhang, A., Gros, A., Li, N., Yetman, G., et al. (2017). Mapping the world population one building at a time. arXiv:1712.05839.", "title": "Mapping the world population one building at a time", "url": "https://arxiv.org/abs/1712.05839", "date": "2017-12-15", "written_by": "makers", "quote": "a computer vision method based on machine learning to create population maps from satellite imagery at a global scale" }, { "kind": "press release", "citation": "Eros, E., Schmeltzer, A. (2017). Stop the spots: Measles vaccinations in Malawi. Missing Maps blog (American Red Cross), 10 August 2017.", "title": "Stop the spots: Measles vaccinations in Malawi", "url": "https://www.missingmaps.org/blog/2017/08/10/malawi/", "date": "2017-08-10", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Facebook's ML settlement maps cut Red Cross mapping for Malawi's June 2017 measles vaccination campaign (Measles & Rubella Initiative) from 94,080 km² to 2,745 km²", "account": "Malawi's June 2017 measles vaccination campaign (Measles & Rubella Initiative) targeted more than 7.5 million children. The American Red Cross's Missing Maps team needed base maps for campaign monitoring. Facebook's population maps come from a machine-learning computer-vision method that detects buildings in satellite imagery. They were used to identify where people lived and which areas were already mapped in OpenStreetMap. Concentrating volunteers on settlements filtered out 97.1% of the land area. That reduced the area to map from 94,080 km² to 2,745 km² and completed the base map in a fraction of the normal time. The base map was to feed a dashboard for government and Red Cross monitors during the campaign. The article predates the campaign and reports no monitoring outcome. No vaccination-coverage outcome attributable to the maps is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Facebook (Meta) High Resolution Settlement Layer population density maps" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Facebook Inc. with CIESIN, Columbia University, and the World Bank Development Data Group" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "American Red Cross used Facebook's machine-learning population maps to focus Malawi mapping for the June 2017 measles vaccination campaign (Measles & Rubella Initiative)", "headline": "Facebook ML maps cut Red Cross Malawi mapping area to 2,745 km²" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2e41991900b4e6881e7934ca89d0c360f5dae1a3f689ee5b484c9f91a82c83cd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Malawi's June 2017 measles vaccination campaign (Measles & Rubella Initiative) targeted more than 7.5 million children. The American Red Cross's Missing Maps team needed base maps for campaign monitoring. Facebook's population maps come from a machine-learning computer-vision method that detects buildings in satellite imagery. They were used to identify where people lived and which areas were already mapped in OpenStreetMap. Concentrating volunteers on settlements filtered out 97.1% of the land area. That reduced the area to map from 94,080 km² to 2,745 km² and completed the base map in a fraction of the normal time. The base map was to feed a dashboard for government and Red Cross monitors during the campaign. The article predates the campaign and reports no monitoring outcome. No vaccination-coverage outcome attributable to the maps is reported.", "replication": { "produced_by": [ "Facebook settlement detection from satellite imagery", "Missing Maps volunteer tracing into OpenStreetMap", "Comparison with existing OpenStreetMap coverage", "Mobile data-collection dashboard for campaign monitors" ], "must_hold": [ "Imagery recent enough to reflect current settlements", "Building-detection accuracy in rural Malawi", "Volunteer and local mapping capacity" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0053", "title": "Tetraplegic man controls a four-limb exoskeleton and avatar through an adaptive epidural ECoG decoder at Clinatec, Grenoble", "summary": "A 28-year-old with C4-C5 tetraplegia cortically controlled simulated walking and 8-DoF arm movements over 24 months (Lancet Neurology 2019).", "date_observed": "2017-06-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 28-year-old man with tetraplegia after a C4-C5 spinal cord injury received two wireless epidural recorders of 64 electrodes each over the sensorimotor cortex. He was implanted at the Clinatec research center of the French Alternative Energies and Atomic Energy Commission (CEA), associated with Grenoble University Hospital. Epidural electrocorticographic signals were processed online by an adaptive decoding algorithm. It sent commands to a virtual avatar or a four-limb exoskeleton. Between 12 June 2017 and 21 July 2019 he cortically controlled a walking simulation and bimanual upper-limb movements with eight degrees of freedom. Success was 64.0% using the avatar at home and 70.9% with the exoskeleton in the laboratory. Decoding models were reusable for about seven weeks without recalibration (Lancet Neurology, 2019).", "category": "benefit created", "unexpected": false, "purpose": "Restore mobility to people with tetraplegia by decoding brain signals to drive an exoskeleton", "system": "Clinatec epidural wireless brain-machine interface with adaptive decoder driving a four-limb exoskeleton and virtual avatar", "model_version": null, "developer": "CEA-Clinatec (public research institute, not a company) with Grenoble University Hospital", "deployer": "Clinatec research center / Grenoble University Hospital clinical trial", "location": "Grenoble, France", "domain": "Neurotechnology / mobility rehabilitation", "segment": "People with tetraplegia", "benefit_type": "Improved Accessibility", "taxonomy_note": "The gain is brain-controlled exoskeleton and avatar movement for a man with tetraplegia in a proof-of-concept setting, not everyday use.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "One identifiable participant gained brain-controlled walking simulation and eight-degree-of-freedom arm control, exercised at home with an avatar and in the lab with the exoskeleton. It did not yet provide everyday mobility." }, { "group": "societal", "depth": 1, "reason": "Single-patient proof of concept for semi-invasive long-term BCI. No population effect." } ], "ai_role": { "status": "assessed", "statement": "The adaptive decoding algorithm converts epidural ECoG into effector commands. The same group later described it as a recursive exponentially weighted Markov-switching multilinear mixture-of-experts model. Without it the implants record only. The exoskeleton itself was ceiling-suspended in the laboratory." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Benabid AL, Costecalde T, Eliseyev A, et al. (2019). An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration. Lancet Neurology 18(12):1112-1122.", "title": "An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration", "url": "https://europepmc.org/abstract/MED/31587955", "date": "2019-10-03", "written_by": "makers", "quote": "Epidural electrocorticographic (ECoG) signals were processed online by an adaptive decoding algorithm to send commands to effectors (virtual avatar or exoskeleton)." }, { "kind": "peer-reviewed study", "citation": "Benabid AL, et al. (2019). Lancet Neurology 18(12):1112-1122 (findings).", "title": "An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient (findings)", "url": "https://europepmc.org/abstract/MED/31587955", "date": "2019-10-03", "written_by": "makers", "quote": "the patient cortically controlled a programme that simulated walking and made bimanual, multi-joint, upper-limb movements with eight degrees of freedom during various reach-and-touch tasks" }, { "kind": "peer-reviewed study", "citation": "Moly A, Costecalde T, Martel F, et al. (2022). An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic. Journal of Neural Engineering 19(2).", "title": "An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic", "url": "https://europepmc.org/abstract/MED/35234665", "date": "2022-03-30", "written_by": "makers", "quote": "The stable over a period of six months (without decoder recalibration) eight-dimensional alternative bimanual control of the exoskeleton and its virtual avatar is demonstrated." } ], "replication": { "produced_by": [ "Chronic bilateral epidural ECoG recorders with wireless transmission", "Adaptive, incrementally trained decoder with idle-state support", "Progressive training on mental tasks over 24 months" ], "must_hold": [ "Stable epidural signal quality over years", "Decoder recalibration roughly every seven weeks", "Laboratory suspension system for safe exoskeleton walking" ], "echoes": [ { "date": "2022-03-30", "setting": "Same patient, more than 36 months after implantation, asynchronous bimanual exoskeleton control", "model_version": "REW-MSLM adaptive decoder", "outcome": "recurred", "source": "Moly et al. (2022) J Neural Eng, PMID 35234665" } ] }, "paired_incident": null, "headline": "Clinatec's ECoG decoder drives a four-limb exoskeleton", "metric": "64.0% success using the avatar at home and 70.9% with the exoskeleton in the laboratory", "comparator": null, "later": { "status": "persisted", "date": "2022-03-30", "note": "The same patient was still controlling the exoskeleton bimanually more than three years after implantation, with a decoder stable for six months without recalibration.", "quote": "The stable over a period of six months (without decoder recalibration) eight-dimensional alternative bimanual control of the exoskeleton and its virtual avatar is demonstrated.", "url": "https://europepmc.org/abstract/MED/35234665" }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/abstract/MED/35234665", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Clinatec; https://en.wikipedia.org/wiki/Clinatec", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers. 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He was implanted at the Clinatec research center of the French Alternative Energies and Atomic Energy Commission (CEA), associated with Grenoble University Hospital. Epidural electrocorticographic signals were processed online by an adaptive decoding algorithm. It sent commands to a virtual avatar or a four-limb exoskeleton. Between 12 June 2017 and 21 July 2019 he cortically controlled a walking simulation and bimanual upper-limb movements with eight degrees of freedom. Success was 64.0% using the avatar at home and 70.9% with the exoskeleton in the laboratory. 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(2019). An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration. Lancet Neurology 18(12):1112-1122.", "title": "An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration", "url": "https://europepmc.org/abstract/MED/31587955", "date": "2019-10-03", "written_by": "makers", "quote": "Epidural electrocorticographic (ECoG) signals were processed online by an adaptive decoding algorithm to send commands to effectors (virtual avatar or exoskeleton)." }, { "kind": "peer-reviewed study", "citation": "Benabid AL, et al. (2019). Lancet Neurology 18(12):1112-1122 (findings).", "title": "An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient (findings)", "url": "https://europepmc.org/abstract/MED/31587955", "date": "2019-10-03", "written_by": "makers", "quote": "the patient cortically controlled a programme that simulated walking and made bimanual, multi-joint, upper-limb movements with eight degrees of freedom during various reach-and-touch tasks" }, { "kind": "peer-reviewed study", "citation": "Moly A, Costecalde T, Martel F, et al. (2022). An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic. Journal of Neural Engineering 19(2).", "title": "An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic", "url": "https://europepmc.org/abstract/MED/35234665", "date": "2022-03-30", "written_by": "makers", "quote": "The stable over a period of six months (without decoder recalibration) eight-dimensional alternative bimanual control of the exoskeleton and its virtual avatar is demonstrated." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 28-year-old with C4-C5 tetraplegia cortically controlled simulated walking and 8-DoF arm movements over 24 months (Lancet Neurology 2019).", "account": "A 28-year-old man with tetraplegia after a C4-C5 spinal cord injury received two wireless epidural recorders of 64 electrodes each over the sensorimotor cortex. He was implanted at the Clinatec research center of the French Alternative Energies and Atomic Energy Commission (CEA), associated with Grenoble University Hospital. Epidural electrocorticographic signals were processed online by an adaptive decoding algorithm. It sent commands to a virtual avatar or a four-limb exoskeleton. Between 12 June 2017 and 21 July 2019 he cortically controlled a walking simulation and bimanual upper-limb movements with eight degrees of freedom. Success was 64.0% using the avatar at home and 70.9% with the exoskeleton in the laboratory. Decoding models were reusable for about seven weeks without recalibration (Lancet Neurology, 2019)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Clinatec epidural wireless brain-machine interface with adaptive decoder driving a four-limb exoskeleton and virtual avatar" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "CEA-Clinatec (public research institute, not a company) with Grenoble University Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Tetraplegic man controls a four-limb exoskeleton and avatar through an adaptive epidural ECoG decoder at Clinatec, Grenoble", "headline": "Clinatec's ECoG decoder drives a four-limb exoskeleton" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c81e4df8b066d24b98d6a12e76865bd2b27455b920ed8e5903542679a2de1d46" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 28-year-old man with tetraplegia after a C4-C5 spinal cord injury received two wireless epidural recorders of 64 electrodes each over the sensorimotor cortex. He was implanted at the Clinatec research center of the French Alternative Energies and Atomic Energy Commission (CEA), associated with Grenoble University Hospital. Epidural electrocorticographic signals were processed online by an adaptive decoding algorithm. It sent commands to a virtual avatar or a four-limb exoskeleton. Between 12 June 2017 and 21 July 2019 he cortically controlled a walking simulation and bimanual upper-limb movements with eight degrees of freedom. Success was 64.0% using the avatar at home and 70.9% with the exoskeleton in the laboratory. Decoding models were reusable for about seven weeks without recalibration (Lancet Neurology, 2019).", "replication": { "produced_by": [ "Chronic bilateral epidural ECoG recorders with wireless transmission", "Adaptive, incrementally trained decoder with idle-state support", "Progressive training on mental tasks over 24 months" ], "must_hold": [ "Stable epidural signal quality over years", "Decoder recalibration roughly every seven weeks", "Laboratory suspension system for safe exoskeleton walking" ], "echoes": [ { "date": "2022-03-30", "setting": "Same patient, more than 36 months after implantation, asynchronous bimanual exoskeleton control", "model_version": "REW-MSLM adaptive decoder", "outcome": "recurred", "source": "Moly et al. (2022) J Neural Eng, PMID 35234665" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0331", "title": "TCU's Alice robot flags DNIT notices for BR-153 maintenance on stretches already under concession; TCU Acórdão 1116/2017 cancels the tender", "summary": "Alice flagged DNIT Goiás notices for BR-153 maintenance on concession stretches (R$39m per Inforchannel); TCU Acórdão 1116/2017 canceled the R$20m tender (JOTA).", "date_observed": "2017-09-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Alice (Análise de Licitações e Editais) is the Tribunal de Contas da União's robot. It reads every tender notice and auction record published on Comprasnet and the Diário Oficial da União. It had been running for about ten months when TCU presented it at a TCU–CGU data-analysis seminar on 25–26 September 2017. Inforchannel (27 September 2017), quoting TCU auditor Valéria Nakano, reported that in Goiás the court, via Alice, found DNIT's state unit had published two notices. They were worth R$39 million for maintenance of the BR-153 on stretches under concession, where maintenance falls to the concessionaire. Within two months an acórdão blocked both tenders. A JOTA article of 22 November 2017 states that Alice was decisive in Acórdão-TCU 1.116/2017 (rapporteur Minister Walton Alencar Rodrigues). It ordered cancellation of the BR-153 tender budgeted at R$20 million. The two sources give different numbers of notices and amounts. The acórdão itself was not available. The decision date is not reported.", "category": "harm prevented", "unexpected": false, "purpose": "Daily automated screening of federal tender notices for signs of irregularity so that auditors can act during the public phase of a tender. This use was its intended purpose.", "system": "Alice (Análise de Licitações e Editais), TCU/CGU text-analysis and data cross-checking robot", "model_version": null, "developer": "Tribunal de Contas da União (TCU) with the Ministério da Transparência e Controladoria-Geral da União (CGU), in-house", "deployer": "Tribunal de Contas da União (TCU), Goiás unit", "location": "Goiás, Brazil (BR-153 highway)", "domain": "Public administration: external audit and procurement control", "segment": "Federal court of accounts (anti-waste and anti-corruption control)", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified in either source." }, { "group": "organizational", "depth": 2, "reason": "Material to DNIT and TCU: both cited sources state that the tender(s) were blocked or canceled by acórdão after the Alice alert. The amount is given as R$39 million (two notices) by Inforchannel and R$20 million (one notice) by JOTA." }, { "group": "societal", "depth": 1, "reason": "A single highway tender among some 60,000 federal tenders a year, small at national scale." } ], "ai_role": { "status": "assessed", "statement": "Alice's role was detection. Per Inforchannel it pulls the estimated value from notice text, runs nine text analyses for competitiveness restrictions and 23 database cross-checks. The auditor's statement and the JOTA article attribute the discovery of the BR-153 notices to Alice. The cancellation was a decision of the TCU plenary (Acórdão 1116/2017). Both sources rest on TCU staff statements, the deployer describing its own in-house tool. The source counts as independent because TCU is a public body, not a vendor. The acórdão text was not obtained, so the two accounts' differing figures (R$39 million, two notices; R$20 million, one notice) cannot be reconciled." }, "evidence": [ { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais. 27 Sep 2017, quoting TCU auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153" }, { "kind": "news report", "citation": "Inforchannel (2017). Same article, statement by auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais (Nakano statement)", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em dois meses, um Acórdão bloqueou essas duas licitações. Mas esse é só um exemplo." }, { "kind": "news report", "citation": "JOTA Info (2017). Alice e a plataforma digital de controle externo. Opinião e Análise, 22 Nov 2017 (quotes TCU secretary Wesley Vaz).", "title": "Alice e a plataforma digital de controle externo", "url": "https://www.jota.info/opiniao-e-analise/artigos/alice-e-a-plataforma-digital-de-controle-externo", "date": "2017-11-22", "written_by": "independent", "quote": "O Alice foi decisivo no Acórdão-TCU 1.116/2017 (relatoria do Ministro Walton Alencar Rodrigues), que determinou o cancelamento do edital da rodovia BR-153 orçado em R$ 20 milhões." }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 18 Mar 2018.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml", "date": "2018-03-18", "written_by": "independent", "quote": "Depois de dicas delas, licitações com falhas já foram canceladas e compras públicas enviesadas tiveram que ser refeitas." } ], "replication": { "produced_by": [ "Daily collection of all tender notices and auction records from Comprasnet and the Diário Oficial da União", "Rule-based text analysis (nine checks on competitiveness restrictions, reading of estimated value) and 23 database cross-checks of suppliers", "Auditors in the TCU Goiás unit reading the alerts during the public phase of the tender", "A TCU plenary decision (acórdão) within two months of the alert" ], "must_hold": [ "Notices published on Comprasnet in machine-readable text", "Alerts reaching auditors within the 15–30-day public phase", "Auditors with capacity to open a case or contact the contracting body", "Contracting bodies or the court willing to block or cancel flawed tenders" ], "echoes": [ { "date": "2018-03-18", "setting": "TCU statement to G1 that tenders with flaws had been canceled and biased purchases redone after the robots' tips (no case named)", "model_version": null, "outcome": "recurred", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, { "date": "2022-12-01", "setting": "TCE-MG audit of 2,297 state and municipal tenders of August 2022 using Alice: 60 irregularities, 53 answered, R$91.7 million of notices corrected", "model_version": null, "outcome": "recurred", "source": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457" } ] }, "paired_incident": null, "headline": "TCU's Alice flags DNIT's BR-153 notices; TCU cancels the tender", "metric": "ordered cancellation of the BR-153 tender budgeted at R$20 million", "comparator": { "against": "TCU auditors reading the roughly 200 federal tender notices published each day by hand", "before": "seria muito custoso porque são, em média, 200 editais por dia", "after": "Os auditores do Tribunal de Contas da União recebem pontualmente às 19h um e-mail de Alice. São os resumos das centenas de contratações federais publicadas naquele dia.", "basis": "assumed", "quote": "“Esse tipo de trabalho poderia ser feito por humanos, mas seria muito custoso porque são, em média, 200 editais por dia”, diz Wesley Vaz Silva, diretor da Secretaria de Fiscalização de Tecnologia da Informação do TCU, ao G1.", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, "later": { "status": "scaled", "date": "2018-03-18", "note": "By March 2018 G1 reported that Alice, Sofia and Monica were also in use at the CGU, the Federal Prosecution Service, the Federal Police and state courts of accounts, and that flawed tenders had been canceled after their tips.", "quote": "As três robôs já são usadas por servidores da Controladoria Geral da União, Ministério Público Federal, Polícia Federal e tribunais de contas dos Estados. Depois de dicas delas, licitações com falhas já foram canceladas e compras públicas enviesadas tiveram que ser refeitas.", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, "value": { "amount": "R$ 39 milhões", "what": "value of the two DNIT tender notices for BR-153 maintenance that a TCU acórdão blocked", "who": "DNIT's Goiás unit, which had published the tenders for stretches whose maintenance falls to the concessionaire", "estimate": false, "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão – portanto com manutenção a cargo da concessionária.", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" }, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0331", "catalog_version": "1.0.0", "source_fingerprint": "7489aea69f34d2e6788d992db4d685b6d0e8fc49912fc42f499abe908e1e3d4f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0331-source-0001", "AIBD-0331-source-0002", "AIBD-0331-source-0003", "AIBD-0331-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0331-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tribunal de Contas da União (TCU) with the Ministério da Transparência e Controladoria-Geral da União (CGU), in-house", "deployer": "Tribunal de Contas da União (TCU), Goiás unit" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Alice's role was detection. Per Inforchannel it pulls the estimated value from notice text, runs nine text analyses for competitiveness restrictions and 23 database cross-checks. The auditor's statement and the JOTA article attribute the discovery of the BR-153 notices to Alice. The cancellation was a decision of the TCU plenary (Acórdão 1116/2017). Both sources rest on TCU staff statements, the deployer describing its own in-house tool. The source counts as independent because TCU is a public body, not a vendor. The acórdão text was not obtained, so the two accounts' differing figures (R$39 million, two notices; R$20 million, one notice) cannot be reconciled." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "Alice's role was detection. Per Inforchannel it pulls the estimated value from notice text, runs nine text analyses for competitiveness restrictions and 23 database cross-checks. The auditor's statement and the JOTA article attribute the discovery of the BR-153 notices to Alice. The cancellation was a decision of the TCU plenary (Acórdão 1116/2017). Both sources rest on TCU staff statements, the deployer describing its own in-house tool. The source counts as independent because TCU is a public body, not a vendor. The acórdão text was not obtained, so the two accounts' differing figures (R$39 million, two notices; R$20 million, one notice) cannot be reconciled." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified in either source." }, { "group": "organizational", "depth": 2, "reason": "Material to DNIT and TCU: both cited sources state that the tender(s) were blocked or canceled by acórdão after the Alice alert. The amount is given as R$39 million (two notices) by Inforchannel and R$20 million (one notice) by JOTA." }, { "group": "societal", "depth": 1, "reason": "A single highway tender among some 60,000 federal tenders a year, small at national scale." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified in either source." }, { "group": "organizational", "depth": 2, "reason": "Material to DNIT and TCU: both cited sources state that the tender(s) were blocked or canceled by acórdão after the Alice alert. The amount is given as R$39 million (two notices) by Inforchannel and R$20 million (one notice) by JOTA." }, { "group": "societal", "depth": 1, "reason": "A single highway tender among some 60,000 federal tenders a year, small at national scale." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified in either source." }, { "group": "organizational", "depth": 2, "reason": "Material to DNIT and TCU: both cited sources state that the tender(s) were blocked or canceled by acórdão after the Alice alert. The amount is given as R$39 million (two notices) by Inforchannel and R$20 million (one notice) by JOTA." }, { "group": "societal", "depth": 1, "reason": "A single highway tender among some 60,000 federal tenders a year, small at national scale." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 39 milhões", "what": "value of the two DNIT tender notices for BR-153 maintenance that a TCU acórdão blocked", "who": "DNIT's Goiás unit, which had published the tenders for stretches whose maintenance falls to the concessionaire", "estimate": false, "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão – portanto com manutenção a cargo da concessionária.", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 39 milhões", "what": "value of the two DNIT tender notices for BR-153 maintenance that a TCU acórdão blocked", "who": "DNIT's Goiás unit, which had published the tenders for stretches whose maintenance falls to the concessionaire", "estimate": false, "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão – portanto com manutenção a cargo da concessionária.", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 39 milhões", "what": "value of the two DNIT tender notices for BR-153 maintenance that a TCU acórdão blocked", "who": "DNIT's Goiás unit, which had published the tenders for stretches whose maintenance falls to the concessionaire", "estimate": false, "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão – portanto com manutenção a cargo da concessionária.", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "ordered cancellation of the BR-153 tender budgeted at R$20 million", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2018-03-18", "note": "By March 2018 G1 reported that Alice, Sofia and Monica were also in use at the CGU, the Federal Prosecution Service, the Federal Police and state courts of accounts, and that flawed tenders had been canceled after their tips.", "quote": "As três robôs já são usadas por servidores da Controladoria Geral da União, Ministério Público Federal, Polícia Federal e tribunais de contas dos Estados. Depois de dicas delas, licitações com falhas já foram canceladas e compras públicas enviesadas tiveram que ser refeitas.", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0331" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Alice (Análise de Licitações e Editais) is the Tribunal de Contas da União's robot. It reads every tender notice and auction record published on Comprasnet and the Diário Oficial da União. It had been running for about ten months when TCU presented it at a TCU–CGU data-analysis seminar on 25–26 September 2017. Inforchannel (27 September 2017), quoting TCU auditor Valéria Nakano, reported that in Goiás the court, via Alice, found DNIT's state unit had published two notices. They were worth R$39 million for maintenance of the BR-153 on stretches under concession, where maintenance falls to the concessionaire. Within two months an acórdão blocked both tenders. A JOTA article of 22 November 2017 states that Alice was decisive in Acórdão-TCU 1.116/2017 (rapporteur Minister Walton Alencar Rodrigues). It ordered cancellation of the BR-153 tender budgeted at R$20 million. The two sources give different numbers of notices and amounts. The acórdão itself was not available. The decision date is not reported.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified in either source." }, { "group": "organizational", "depth": 2, "reason": "Material to DNIT and TCU: both cited sources state that the tender(s) were blocked or canceled by acórdão after the Alice alert. The amount is given as R$39 million (two notices) by Inforchannel and R$20 million (one notice) by JOTA." }, { "group": "societal", "depth": 1, "reason": "A single highway tender among some 60,000 federal tenders a year, small at national scale." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Daily automated screening of federal tender notices for signs of irregularity so that auditors can act during the public phase of a tender. This use was its intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Goiás, Brazil (BR-153 highway)", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Daily automated screening of federal tender notices for signs of irregularity so that auditors can act during the public phase of a tender. This use was its intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2017-09-27", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Daily collection of all tender notices and auction records from Comprasnet and the Diário Oficial da União", "Rule-based text analysis (nine checks on competitiveness restrictions, reading of estimated value) and 23 database cross-checks of suppliers", "Auditors in the TCU Goiás unit reading the alerts during the public phase of the tender", "A TCU plenary decision (acórdão) within two months of the alert" ], "must_hold": [ "Notices published on Comprasnet in machine-readable text", "Alerts reaching auditors within the 15–30-day public phase", "Auditors with capacity to open a case or contact the contracting body", "Contracting bodies or the court willing to block or cancel flawed tenders" ], "echoes": [ { "date": "2018-03-18", "setting": "TCU statement to G1 that tenders with flaws had been canceled and biased purchases redone after the robots' tips (no case named)", "outcome": "recurred", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, { "date": "2022-12-01", "setting": "TCE-MG audit of 2,297 state and municipal tenders of August 2022 using Alice: 60 irregularities, 53 answered, R$91.7 million of notices corrected", "outcome": "recurred", "source": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Daily collection of all tender notices and auction records from Comprasnet and the Diário Oficial da União", "Rule-based text analysis (nine checks on competitiveness restrictions, reading of estimated value) and 23 database cross-checks of suppliers", "Auditors in the TCU Goiás unit reading the alerts during the public phase of the tender", "A TCU plenary decision (acórdão) within two months of the alert" ], "must_hold": [ "Notices published on Comprasnet in machine-readable text", "Alerts reaching auditors within the 15–30-day public phase", "Auditors with capacity to open a case or contact the contracting body", "Contracting bodies or the court willing to block or cancel flawed tenders" ], "echoes": [ { "date": "2018-03-18", "setting": "TCU statement to G1 that tenders with flaws had been canceled and biased purchases redone after the robots' tips (no case named)", "outcome": "recurred", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, { "date": "2022-12-01", "setting": "TCE-MG audit of 2,297 state and municipal tenders of August 2022 using Alice: 60 irregularities, 53 answered, R$91.7 million of notices corrected", "outcome": "recurred", "source": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml; https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: external audit and procurement control", "segment": "Federal court of accounts (anti-waste and anti-corruption control)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais. 27 Sep 2017, quoting TCU auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153" }, { "kind": "news report", "citation": "Inforchannel (2017). Same article, statement by auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais (Nakano statement)", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em dois meses, um Acórdão bloqueou essas duas licitações. Mas esse é só um exemplo." }, { "kind": "news report", "citation": "JOTA Info (2017). Alice e a plataforma digital de controle externo. Opinião e Análise, 22 Nov 2017 (quotes TCU secretary Wesley Vaz).", "title": "Alice e a plataforma digital de controle externo", "url": "https://www.jota.info/opiniao-e-analise/artigos/alice-e-a-plataforma-digital-de-controle-externo", "date": "2017-11-22", "written_by": "independent", "quote": "O Alice foi decisivo no Acórdão-TCU 1.116/2017 (relatoria do Ministro Walton Alencar Rodrigues), que determinou o cancelamento do edital da rodovia BR-153 orçado em R$ 20 milhões." }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 18 Mar 2018.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml", "date": "2018-03-18", "written_by": "independent", "quote": "Depois de dicas delas, licitações com falhas já foram canceladas e compras públicas enviesadas tiveram que ser refeitas." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0331-source-0001", "AIBD-0331-source-0002", "AIBD-0331-source-0003", "AIBD-0331-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais. 27 Sep 2017, quoting TCU auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em Goiás, o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153" }, { "kind": "news report", "citation": "Inforchannel (2017). Same article, statement by auditor Valéria Nakano.", "title": "TCU cria robô para varredura diária de irregularidades em editais (Nakano statement)", "url": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "Em dois meses, um Acórdão bloqueou essas duas licitações. Mas esse é só um exemplo." }, { "kind": "news report", "citation": "JOTA Info (2017). Alice e a plataforma digital de controle externo. Opinião e Análise, 22 Nov 2017 (quotes TCU secretary Wesley Vaz).", "title": "Alice e a plataforma digital de controle externo", "url": "https://www.jota.info/opiniao-e-analise/artigos/alice-e-a-plataforma-digital-de-controle-externo", "date": "2017-11-22", "written_by": "independent", "quote": "O Alice foi decisivo no Acórdão-TCU 1.116/2017 (relatoria do Ministro Walton Alencar Rodrigues), que determinou o cancelamento do edital da rodovia BR-153 orçado em R$ 20 milhões." }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 18 Mar 2018.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml", "date": "2018-03-18", "written_by": "independent", "quote": "Depois de dicas delas, licitações com falhas já foram canceladas e compras públicas enviesadas tiveram que ser refeitas." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Alice flagged DNIT Goiás notices for BR-153 maintenance on concession stretches (R$39m per Inforchannel); TCU Acórdão 1116/2017 canceled the R$20m tender (JOTA).", "account": "Alice (Análise de Licitações e Editais) is the Tribunal de Contas da União's robot. It reads every tender notice and auction record published on Comprasnet and the Diário Oficial da União. It had been running for about ten months when TCU presented it at a TCU–CGU data-analysis seminar on 25–26 September 2017. Inforchannel (27 September 2017), quoting TCU auditor Valéria Nakano, reported that in Goiás the court, via Alice, found DNIT's state unit had published two notices. They were worth R$39 million for maintenance of the BR-153 on stretches under concession, where maintenance falls to the concessionaire. Within two months an acórdão blocked both tenders. A JOTA article of 22 November 2017 states that Alice was decisive in Acórdão-TCU 1.116/2017 (rapporteur Minister Walton Alencar Rodrigues). It ordered cancellation of the BR-153 tender budgeted at R$20 million. The two sources give different numbers of notices and amounts. The acórdão itself was not available. The decision date is not reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Alice (Análise de Licitações e Editais), TCU/CGU text-analysis and data cross-checking robot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tribunal de Contas da União (TCU) with the Ministério da Transparência e Controladoria-Geral da União (CGU), in-house" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TCU's Alice robot flags DNIT notices for BR-153 maintenance on stretches already under concession; TCU Acórdão 1116/2017 cancels the tender", "headline": "TCU's Alice flags DNIT's BR-153 notices; TCU cancels the tender" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7489aea69f34d2e6788d992db4d685b6d0e8fc49912fc42f499abe908e1e3d4f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Alice (Análise de Licitações e Editais) is the Tribunal de Contas da União's robot. It reads every tender notice and auction record published on Comprasnet and the Diário Oficial da União. It had been running for about ten months when TCU presented it at a TCU–CGU data-analysis seminar on 25–26 September 2017. Inforchannel (27 September 2017), quoting TCU auditor Valéria Nakano, reported that in Goiás the court, via Alice, found DNIT's state unit had published two notices. They were worth R$39 million for maintenance of the BR-153 on stretches under concession, where maintenance falls to the concessionaire. Within two months an acórdão blocked both tenders. A JOTA article of 22 November 2017 states that Alice was decisive in Acórdão-TCU 1.116/2017 (rapporteur Minister Walton Alencar Rodrigues). It ordered cancellation of the BR-153 tender budgeted at R$20 million. The two sources give different numbers of notices and amounts. The acórdão itself was not available. The decision date is not reported.", "replication": { "produced_by": [ "Daily collection of all tender notices and auction records from Comprasnet and the Diário Oficial da União", "Rule-based text analysis (nine checks on competitiveness restrictions, reading of estimated value) and 23 database cross-checks of suppliers", "Auditors in the TCU Goiás unit reading the alerts during the public phase of the tender", "A TCU plenary decision (acórdão) within two months of the alert" ], "must_hold": [ "Notices published on Comprasnet in machine-readable text", "Alerts reaching auditors within the 15–30-day public phase", "Auditors with capacity to open a case or contact the contracting body", "Contracting bodies or the court willing to block or cancel flawed tenders" ], "echoes": [ { "date": "2018-03-18", "setting": "TCU statement to G1 that tenders with flaws had been canceled and biased purchases redone after the robots' tips (no case named)", "outcome": "recurred", "source": "https://g1.globo.com/economia/tecnologia/noticia/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes.ghtml" }, { "date": "2022-12-01", "setting": "TCE-MG audit of 2,297 state and municipal tenders of August 2022 using Alice: 60 irregularities, 53 answered, R$91.7 million of notices corrected", "outcome": "recurred", "source": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0308", "title": "OPTiM begins a trial of its “AI Physical Security Service” AI camera monitoring at two JR Kyushu stations, Wajiro and Futajima, from 10 October 2017", "summary": "OPTiM's release says its cloud AI monitors station camera video in real time, recognizing people, trains and the platform yellow line, and alerts administrators on anomalies; no results published.", "date_observed": "2017-10-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "OPTiM Corporation announced on 6 October 2017 a demonstration trial of its “AI Physical Security Service” from 10 October 2017. It would run at two Kyushu Railway Company (JR Kyushu) stations: 和白駅 (Wajiro) on the Kashii Line and 二島駅 (Futajima) on the Chikuho Main Line. The service, on “OPTiM Cloud IoT OS”, has AI monitor network-camera video in real time. When it detects an anomaly, it shows an alert and emails administrators. This is to reduce the burden on operators who watch many monitors and to raise safety in the station. The release includes an image of station camera analysis identifying people, trains and the yellow platform line. The release is the only source (on optim.co.jp and republished by @Press). JR Kyushu is not quoted, no trial end date, detection target list or result is given, and no later report of outcomes was found. Station romanizations are ours.", "category": "general benefit", "unexpected": false, "purpose": "Trial of AI video monitoring to detect anomalies on station platforms and alert administrators. No detection event is documented.", "system": "AI Physical Security Service (AI surveillance-camera service on OPTiM Cloud IoT OS)", "model_version": null, "developer": "OPTiM Corporation", "deployer": "Kyushu Railway Company (JR Kyushu), trial at two stations", "location": "Wajiro (Kashii Line) and Futajima (Chikuho Main Line) stations, JR Kyushu, Japan", "domain": "Railway safety / station platform monitoring", "segment": "Station platform monitoring", "benefit_type": "Increased Product Safety", "taxonomy_note": "A trial announcement with no result, whose stated aims are station safety alerts and a lighter monitoring load for operators.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Only OPTiM's announcement exists. No trial result, alert count or staffing effect was published." }, { "group": "personal", "depth": null, "reason": "No passenger safety outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "No event is reported. The AI's role is described only in the vendor's launch release (real-time video monitoring, anomaly alerts, email to administrators). No account from JR Kyushu was found." }, "evidence": [ { "kind": "press release", "citation": "OPTiM Corporation (2017). AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始. Press release, 6 October 2017.", "title": "AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始", "url": "https://www.optim.co.jp/news-detail/23884", "date": "2017-10-06", "written_by": "makers", "quote": "ネットワークカメラなどで撮影されている映像をAI（人工知能）がリアルタイムで監視し、異常を検知した際にアラート表示をしたり、管理者へアラートメール送信を行う" }, { "kind": "press release", "citation": "OPTiM Corporation (2017). The same release republished by @Press, 6 October 2017.", "title": "「AI Physical Security Service」の実証実験を開始", "url": "https://www.atpress.ne.jp/news/139924", "date": "2017-10-06", "written_by": "makers", "quote": "10月10日よりJR九州香椎線和白駅、筑豊本線二島駅において実施" }, { "kind": "news report", "citation": "Kabutan / Fisco (2018). オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成. Kabutan market news, 27 June 2018 (reporting OPTiM's announcement of 26 June 2018).", "title": "オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成", "url": "https://kabutan.jp/news/marketnews/?b=n201806270161", "date": "2018-06-27", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Network cameras at two JR Kyushu stations streamed to OPTiM's cloud AI service", "Real-time analysis identifying people, trains and the platform yellow line and flagging anomalies", "Alert display and email to administrators" ], "must_hold": [ "Operators or administrators who act on the alerts; the release gives no response procedure", "Detection accuracy adequate for station use; no figures were published" ], "echoes": [] }, "paired_incident": null, "headline": "OPTiM trials AI camera monitoring at two JR Kyushu stations", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2018-06-26", "note": "OPTiM announced on 26 June 2018 that a trial of the same service with Itec Hankyu Hanshin at JR Sawa station on the Joban Line achieved a 96.2% detection rate of people or objects crossing the platform's yellow line while no train was present, against a 90% target; no result for the JR Kyushu stations was found.", "quote": "オプティム< 3694 >は26日、アイテック阪急阪神(本社:大阪府大阪市)と共同でJR常盤線佐和駅において、オプティムが提供する「AI Physical Security Service」の実証実験を実施し、目標を上回る検知率96.2％を達成したと発表。今回、目標として設定した検知率(電車が駅に不在時に、ホーム際の黄色い線より線路側に人もしくは物体が侵入した際にAIが検知した割合)は90％としていた。", "url": "https://kabutan.jp/news/marketnews/?b=n201806270161" }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kabutan.jp/news/marketnews/?b=n201806270161", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%82%AA%E3%83%97%E3%83%86%E3%82%A3%E3%83%A0; https://en.wikipedia.org/wiki/Kyushu_Railway_Company", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0308", "catalog_version": "1.0.0", "source_fingerprint": "5426aa4b23877ccb217cf2223505c2c5d2cd656e33221de9c9bbced0042d7bff", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0308-source-0001", "AIBD-0308-source-0002", "AIBD-0308-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OPTiM Corporation", "deployer": "Kyushu Railway Company (JR Kyushu), trial at two stations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "No event is reported. The AI's role is described only in the vendor's launch release (real-time video monitoring, anomaly alerts, email to administrators). No account from JR Kyushu was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Only OPTiM's announcement exists. No trial result, alert count or staffing effect was published." }, { "group": "personal", "reason": "No passenger safety outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Only OPTiM's announcement exists. No trial result, alert count or staffing effect was published." }, { "group": "personal", "reason": "No passenger safety outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2018-06-26", "note": "OPTiM announced on 26 June 2018 that a trial of the same service with Itec Hankyu Hanshin at JR Sawa station on the Joban Line achieved a 96.2% detection rate of people or objects crossing the platform's yellow line while no train was present, against a 90% target; no result for the JR Kyushu stations was found.", "quote": "オプティム< 3694 >は26日、アイテック阪急阪神(本社:大阪府大阪市)と共同でJR常盤線佐和駅において、オプティムが提供する「AI Physical Security Service」の実証実験を実施し、目標を上回る検知率96.2％を達成したと発表。今回、目標として設定した検知率(電車が駅に不在時に、ホーム際の黄色い線より線路側に人もしくは物体が侵入した際にAIが検知した割合)は90％としていた。", "url": "https://kabutan.jp/news/marketnews/?b=n201806270161" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0308" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "A trial announcement with no result, whose stated aims are station safety alerts and a lighter monitoring load for operators." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "OPTiM Corporation announced on 6 October 2017 a demonstration trial of its “AI Physical Security Service” from 10 October 2017. It would run at two Kyushu Railway Company (JR Kyushu) stations: 和白駅 (Wajiro) on the Kashii Line and 二島駅 (Futajima) on the Chikuho Main Line. The service, on “OPTiM Cloud IoT OS”, has AI monitor network-camera video in real time. When it detects an anomaly, it shows an alert and emails administrators. This is to reduce the burden on operators who watch many monitors and to raise safety in the station. The release includes an image of station camera analysis identifying people, trains and the yellow platform line. The release is the only source (on optim.co.jp and republished by @Press). JR Kyushu is not quoted, no trial end date, detection target list or result is given, and no later report of outcomes was found. Station romanizations are ours.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Only OPTiM's announcement exists. No trial result, alert count or staffing effect was published." }, { "group": "personal", "reason": "No passenger safety outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Trial of AI video monitoring to detect anomalies on station platforms and alert administrators. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Wajiro (Kashii Line) and Futajima (Chikuho Main Line) stations, JR Kyushu, Japan", "developer_country": "Japan", "deployer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Trial of AI video monitoring to detect anomalies on station platforms and alert administrators. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2017-10-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kabutan.jp/news/marketnews/?b=n201806270161", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%82%AA%E3%83%97%E3%83%86%E3%82%A3%E3%83%A0; https://en.wikipedia.org/wiki/Kyushu_Railway_Company", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Network cameras at two JR Kyushu stations streamed to OPTiM's cloud AI service", "Real-time analysis identifying people, trains and the platform yellow line and flagging anomalies", "Alert display and email to administrators" ], "must_hold": [ "Operators or administrators who act on the alerts; the release gives no response procedure", "Detection accuracy adequate for station use; no figures were published" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kabutan.jp/news/marketnews/?b=n201806270161", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%82%AA%E3%83%97%E3%83%86%E3%82%A3%E3%83%A0; https://en.wikipedia.org/wiki/Kyushu_Railway_Company", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Railway safety / station platform monitoring", "segment": "Station platform monitoring" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "OPTiM Corporation (2017). AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始. Press release, 6 October 2017.", "title": "AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始", "url": "https://www.optim.co.jp/news-detail/23884", "date": "2017-10-06", "written_by": "makers", "quote": "ネットワークカメラなどで撮影されている映像をAI（人工知能）がリアルタイムで監視し、異常を検知した際にアラート表示をしたり、管理者へアラートメール送信を行う" }, { "kind": "press release", "citation": "OPTiM Corporation (2017). The same release republished by @Press, 6 October 2017.", "title": "「AI Physical Security Service」の実証実験を開始", "url": "https://www.atpress.ne.jp/news/139924", "date": "2017-10-06", "written_by": "makers", "quote": "10月10日よりJR九州香椎線和白駅、筑豊本線二島駅において実施" }, { "kind": "news report", "citation": "Kabutan / Fisco (2018). オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成. Kabutan market news, 27 June 2018 (reporting OPTiM's announcement of 26 June 2018).", "title": "オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成", "url": "https://kabutan.jp/news/marketnews/?b=n201806270161", "date": "2018-06-27", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0308-source-0001", "AIBD-0308-source-0002", "AIBD-0308-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "OPTiM Corporation (2017). AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始. Press release, 6 October 2017.", "title": "AI（人工知能）を用いて異常を検知、JR九州の駅をご利用になるお客様のより高い安全性向上を目的とした「AI Physical Security Service」の実証実験を開始", "url": "https://www.optim.co.jp/news-detail/23884", "date": "2017-10-06", "written_by": "makers", "quote": "ネットワークカメラなどで撮影されている映像をAI（人工知能）がリアルタイムで監視し、異常を検知した際にアラート表示をしたり、管理者へアラートメール送信を行う" }, { "kind": "press release", "citation": "OPTiM Corporation (2017). The same release republished by @Press, 6 October 2017.", "title": "「AI Physical Security Service」の実証実験を開始", "url": "https://www.atpress.ne.jp/news/139924", "date": "2017-10-06", "written_by": "makers", "quote": "10月10日よりJR九州香椎線和白駅、筑豊本線二島駅において実施" }, { "kind": "news report", "citation": "Kabutan / Fisco (2018). オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成. Kabutan market news, 27 June 2018 (reporting OPTiM's announcement of 26 June 2018).", "title": "オプティム---「AI Physical Security Service」の実証実験を実施、目標を上回る検知率を達成", "url": "https://kabutan.jp/news/marketnews/?b=n201806270161", "date": "2018-06-27", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "OPTiM's release says its cloud AI monitors station camera video in real time, recognizing people, trains and the platform yellow line, and alerts administrators on anomalies; no results published.", "account": "OPTiM Corporation announced on 6 October 2017 a demonstration trial of its “AI Physical Security Service” from 10 October 2017. It would run at two Kyushu Railway Company (JR Kyushu) stations: 和白駅 (Wajiro) on the Kashii Line and 二島駅 (Futajima) on the Chikuho Main Line. The service, on “OPTiM Cloud IoT OS”, has AI monitor network-camera video in real time. When it detects an anomaly, it shows an alert and emails administrators. This is to reduce the burden on operators who watch many monitors and to raise safety in the station. The release includes an image of station camera analysis identifying people, trains and the yellow platform line. The release is the only source (on optim.co.jp and republished by @Press). JR Kyushu is not quoted, no trial end date, detection target list or result is given, and no later report of outcomes was found. Station romanizations are ours." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI Physical Security Service (AI surveillance-camera service on OPTiM Cloud IoT OS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OPTiM Corporation" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OPTiM begins a trial of its “AI Physical Security Service” AI camera monitoring at two JR Kyushu stations, Wajiro and Futajima, from 10 October 2017", "headline": "OPTiM trials AI camera monitoring at two JR Kyushu stations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5426aa4b23877ccb217cf2223505c2c5d2cd656e33221de9c9bbced0042d7bff" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "OPTiM Corporation announced on 6 October 2017 a demonstration trial of its “AI Physical Security Service” from 10 October 2017. It would run at two Kyushu Railway Company (JR Kyushu) stations: 和白駅 (Wajiro) on the Kashii Line and 二島駅 (Futajima) on the Chikuho Main Line. The service, on “OPTiM Cloud IoT OS”, has AI monitor network-camera video in real time. When it detects an anomaly, it shows an alert and emails administrators. This is to reduce the burden on operators who watch many monitors and to raise safety in the station. The release includes an image of station camera analysis identifying people, trains and the yellow platform line. The release is the only source (on optim.co.jp and republished by @Press). JR Kyushu is not quoted, no trial end date, detection target list or result is given, and no later report of outcomes was found. Station romanizations are ours.", "replication": { "produced_by": [ "Network cameras at two JR Kyushu stations streamed to OPTiM's cloud AI service", "Real-time analysis identifying people, trains and the platform yellow line and flagging anomalies", "Alert display and email to administrators" ], "must_hold": [ "Operators or administrators who act on the alerts; the release gives no response procedure", "Detection accuracy adequate for station use; no figures were published" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0231", "title": "Raleigh police use Marinus Analytics' Traffic Jam to link phone numbers and photos across cities in a live trafficking case", "summary": "CBN (18 Oct 2017) shows Raleigh PD detectives using Traffic Jam, a CMU-born tool with facial recognition over escort ads, to corroborate a trafficker's movements; outcomes stated only as aggregates.", "date_observed": "2017-10-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The case described was ongoing. Major Richard Hoffman of the Raleigh Police Department described Traffic Jam to CBN. It lets investigators link a potential victim to another victim and then to a suspect. Its image search returns historical images tied to the same phone number or similar image. Detective Rob Pereira described pulling a phone number from a Colorado police report into Traffic Jam to see where and when it had been used. This corroborated several victims' accounts of where the trafficker was taking them. Marinus co-founder Cara Jones described the tool as applying artificial intelligence to publicly available ad data. CBN states that Traffic Jam has helped recover hundreds of victims. Futurism (2018) repeats a similar claim from CEO Emily Kennedy with an 88 percent success rate. No individually attributable rescue is documented.", "category": "general benefit", "unexpected": false, "purpose": "Mine online sex advertisements (text, phone numbers, facial recognition on images) to help law enforcement find trafficking victims and link cases.", "system": "Traffic Jam", "model_version": null, "developer": "Marinus Analytics (origin: Carnegie Mellon University undergraduate project)", "deployer": "Raleigh Police Department", "location": "Raleigh, United States", "domain": "Anti-trafficking", "segment": "Government", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Raleigh PD officials credit faster linkage of victims and suspects, but no case outcome is documented." }, { "group": "personal", "depth": null, "reason": "No individually attributable victim outcome in the sources." } ], "ai_role": { "status": "assessed", "statement": "Named Raleigh officers describe what the tool does for them (phone-number and image linkage across cities). The claims that it has led to hundreds of recoveries come from the vendor, relayed by CBN and Futurism without a documented case." }, "evidence": [ { "kind": "news report", "citation": "Caitlin Burke, CBN News, 18 Oct 2017", "title": "Creating a 'Traffic Jam' Against Sex Trafficking: This Groundbreaking Tech is a Game-Changer", "url": "https://cbn.com/news/us/creating-traffic-jam-against-sex-trafficking-groundbreaking-tech-game-changer", "date": "2017-10-18", "written_by": "independent", "quote": "Traffic Jam allows us to look at a potential victim, identify a link to another victim and then by having victims linked, identify a suspect and have a working case," }, { "kind": "news report", "citation": "Alexandra Ossola, Futurism, 16 Apr 2018", "title": "AI Tool Helps Law Enforcement Find Victims of Human Trafficking", "url": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "date": "2018-04-16", "written_by": "independent", "quote": "data from Traffic Jam has already led to the rescue of hundreds of victims of human trafficking in the U.S. and Canada." } ], "replication": { "produced_by": [ "Continuous scraping of escort ads since 2011", "Phone-number and image-similarity indexing across cities", "Detectives with an existing lead (phone number or photo)" ], "must_hold": [ "Ads must remain publicly scrapable (Backpage was shut in 2018)", "Agency access and training" ], "echoes": [] }, "paired_incident": null, "headline": "Raleigh police use Traffic Jam to link a trafficker's movements", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2018-04-16", "note": "By April 2018 Marinus said Traffic Jam data had led to the rescue of hundreds of victims in the U.S. and Canada and that the software was crawling data from 18 countries.", "quote": "The software is now crawling data from 18 countries, she says, and the company will soon expand to the United Kingdom and, soon, beyond.", "url": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.marinusanalytics.com/payment-terms-us; https://raleighnc.gov/police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0231", "catalog_version": "1.0.0", "source_fingerprint": "5501c8eafe79813252b4fdb5052a54fcab814eb0447ef60f7d2ed06e6607d243", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0231-source-0001", "AIBD-0231-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Marinus Analytics (origin: Carnegie Mellon University undergraduate project)", "deployer": "Raleigh Police Department" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Named Raleigh officers describe what the tool does for them (phone-number and image linkage across cities). The claims that it has led to hundreds of recoveries come from the vendor, relayed by CBN and Futurism without a documented case." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Named Raleigh officers describe what the tool does for them (phone-number and image linkage across cities). The claims that it has led to hundreds of recoveries come from the vendor, relayed by CBN and Futurism without a documented case." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Raleigh PD officials credit faster linkage of victims and suspects, but no case outcome is documented." }, { "group": "personal", "reason": "No individually attributable victim outcome in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Raleigh PD officials credit faster linkage of victims and suspects, but no case outcome is documented." }, { "group": "personal", "reason": "No individually attributable victim outcome in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2018-04-16", "note": "By April 2018 Marinus said Traffic Jam data had led to the rescue of hundreds of victims in the U.S. and Canada and that the software was crawling data from 18 countries.", "quote": "The software is now crawling data from 18 countries, she says, and the company will soon expand to the United Kingdom and, soon, beyond.", "url": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0231" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The case described was ongoing. Major Richard Hoffman of the Raleigh Police Department described Traffic Jam to CBN. It lets investigators link a potential victim to another victim and then to a suspect. Its image search returns historical images tied to the same phone number or similar image. Detective Rob Pereira described pulling a phone number from a Colorado police report into Traffic Jam to see where and when it had been used. This corroborated several victims' accounts of where the trafficker was taking them. Marinus co-founder Cara Jones described the tool as applying artificial intelligence to publicly available ad data. CBN states that Traffic Jam has helped recover hundreds of victims. Futurism (2018) repeats a similar claim from CEO Emily Kennedy with an 88 percent success rate. No individually attributable rescue is documented.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Raleigh PD officials credit faster linkage of victims and suspects, but no case outcome is documented." }, { "group": "personal", "reason": "No individually attributable victim outcome in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Mine online sex advertisements (text, phone numbers, facial recognition on images) to help law enforcement find trafficking victims and link cases." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Raleigh, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Mine online sex advertisements (text, phone numbers, facial recognition on images) to help law enforcement find trafficking victims and link cases." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2017-10-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.marinusanalytics.com/payment-terms-us; https://raleighnc.gov/police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Continuous scraping of escort ads since 2011", "Phone-number and image-similarity indexing across cities", "Detectives with an existing lead (phone number or photo)" ], "must_hold": [ "Ads must remain publicly scrapable (Backpage was shut in 2018)", "Agency access and training" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.marinusanalytics.com/payment-terms-us; https://raleighnc.gov/police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Anti-trafficking", "segment": "Government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Caitlin Burke, CBN News, 18 Oct 2017", "title": "Creating a 'Traffic Jam' Against Sex Trafficking: This Groundbreaking Tech is a Game-Changer", "url": "https://cbn.com/news/us/creating-traffic-jam-against-sex-trafficking-groundbreaking-tech-game-changer", "date": "2017-10-18", "written_by": "independent", "quote": "Traffic Jam allows us to look at a potential victim, identify a link to another victim and then by having victims linked, identify a suspect and have a working case," }, { "kind": "news report", "citation": "Alexandra Ossola, Futurism, 16 Apr 2018", "title": "AI Tool Helps Law Enforcement Find Victims of Human Trafficking", "url": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "date": "2018-04-16", "written_by": "independent", "quote": "data from Traffic Jam has already led to the rescue of hundreds of victims of human trafficking in the U.S. and Canada." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0231-source-0001", "AIBD-0231-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Caitlin Burke, CBN News, 18 Oct 2017", "title": "Creating a 'Traffic Jam' Against Sex Trafficking: This Groundbreaking Tech is a Game-Changer", "url": "https://cbn.com/news/us/creating-traffic-jam-against-sex-trafficking-groundbreaking-tech-game-changer", "date": "2017-10-18", "written_by": "independent", "quote": "Traffic Jam allows us to look at a potential victim, identify a link to another victim and then by having victims linked, identify a suspect and have a working case," }, { "kind": "news report", "citation": "Alexandra Ossola, Futurism, 16 Apr 2018", "title": "AI Tool Helps Law Enforcement Find Victims of Human Trafficking", "url": "https://futurism.com/ai-tool-law-enforcement-stop-human-trafficking", "date": "2018-04-16", "written_by": "independent", "quote": "data from Traffic Jam has already led to the rescue of hundreds of victims of human trafficking in the U.S. and Canada." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CBN (18 Oct 2017) shows Raleigh PD detectives using Traffic Jam, a CMU-born tool with facial recognition over escort ads, to corroborate a trafficker's movements; outcomes stated only as aggregates.", "account": "The case described was ongoing. Major Richard Hoffman of the Raleigh Police Department described Traffic Jam to CBN. It lets investigators link a potential victim to another victim and then to a suspect. Its image search returns historical images tied to the same phone number or similar image. Detective Rob Pereira described pulling a phone number from a Colorado police report into Traffic Jam to see where and when it had been used. This corroborated several victims' accounts of where the trafficker was taking them. Marinus co-founder Cara Jones described the tool as applying artificial intelligence to publicly available ad data. CBN states that Traffic Jam has helped recover hundreds of victims. Futurism (2018) repeats a similar claim from CEO Emily Kennedy with an 88 percent success rate. No individually attributable rescue is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Traffic Jam" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Marinus Analytics (origin: Carnegie Mellon University undergraduate project)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Raleigh police use Marinus Analytics' Traffic Jam to link phone numbers and photos across cities in a live trafficking case", "headline": "Raleigh police use Traffic Jam to link a trafficker's movements" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5501c8eafe79813252b4fdb5052a54fcab814eb0447ef60f7d2ed06e6607d243" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The case described was ongoing. Major Richard Hoffman of the Raleigh Police Department described Traffic Jam to CBN. It lets investigators link a potential victim to another victim and then to a suspect. Its image search returns historical images tied to the same phone number or similar image. Detective Rob Pereira described pulling a phone number from a Colorado police report into Traffic Jam to see where and when it had been used. This corroborated several victims' accounts of where the trafficker was taking them. Marinus co-founder Cara Jones described the tool as applying artificial intelligence to publicly available ad data. CBN states that Traffic Jam has helped recover hundreds of victims. Futurism (2018) repeats a similar claim from CEO Emily Kennedy with an 88 percent success rate. No individually attributable rescue is documented.", "replication": { "produced_by": [ "Continuous scraping of escort ads since 2011", "Phone-number and image-similarity indexing across cities", "Detectives with an existing lead (phone number or photo)" ], "must_hold": [ "Ads must remain publicly scrapable (Backpage was shut in 2018)", "Agency access and training" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0014", "title": "Kepler-90i: a deep convolutional neural network finds an eighth planet in archival Kepler data", "summary": "A Google/UT Austin neural network found Kepler-90i in archival Kepler data; NASA announced it on 14 December 2017 and the AJ published it on 30 January 2018.", "date_observed": "2017-12-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 14 December 2017 NASA announced a deep convolutional neural network had identified an eighth planet, Kepler-90i, in archival Kepler Space Telescope data. Christopher Shallue (Google Brain) and Andrew Vanderburg (University of Texas at Austin, NASA Sagan Fellow) built it. It was trained on about 15,000 previously vetted Kepler signals and correctly identified true planets and false positives 96 percent of the time in testing. It was then applied to 670 known multi-planet systems to search for weak transit signals missed by earlier methods. Kepler-90i is a rocky planet about 30 percent larger than Earth with a 14.4-day orbit. It was statistically validated together with Kepler-80g, an Earth-sized sixth planet in a resonant chain. The peer-reviewed paper appeared in the Astronomical Journal on 30 January 2018.", "category": "benefit created", "unexpected": false, "purpose": "Built to classify Kepler transit signals as planets or false positives and to recover planets missed by earlier searches. This benefit was that purpose.", "system": "Deep convolutional neural network for Kepler transit-signal classification (Shallue and Vanderburg)", "model_version": null, "developer": "Google (Christopher Shallue, Google Brain) with Andrew Vanderburg (University of Texas at Austin)", "deployer": "Shallue and Vanderburg, applied to NASA Kepler archival data", "location": null, "domain": "Astronomy / exoplanets", "segment": "Academic research", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "NASA's Paul Hertz said that discoveries were lurking in archived Kepler data awaiting the right tool. The archive yielded two newly validated planets without new telescope observations by the authors. Their validation used Kepler data and follow-up observations that other observers had already uploaded to the Kepler Community Follow-up Program." }, { "group": "societal", "depth": 2, "reason": "Astronomy gained a validated eighth planet and the first exoplanetary system known to have eight planets, tying the Solar System. This is a knowledge gain for a specialist community rather than a population-level benefit." } ], "ai_role": { "status": "assessed", "statement": "The neural network ranked the weak Kepler-90i transit signal above false positives in systems that earlier automated and human searches had already examined. The authors then statistically validated both new planets. The AI did the identification. Validation used conventional methods." }, "evidence": [ { "kind": "press release", "citation": "NASA (2017). Artificial Intelligence, NASA Data Used to Discover Eighth Planet Circling Distant Star. NASA news release.", "title": "Artificial Intelligence, NASA Data Used to Discover Eighth Planet Circling Distant Star", "url": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/", "date": "2017-12-14", "written_by": "independent", "quote": "Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them." }, { "kind": "peer-reviewed study", "citation": "Shallue, C. J. and Vanderburg, A. (2018). Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90. The Astronomical Journal 155(2), 94.", "title": "Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://iopscience.iop.org/article/10.3847/1538-3881/aa9e09", "date": "2018-01-30", "written_by": "makers", "quote": "Our discovery of an eighth planet brings Kepler-90 into a tie with our Sun as the star known to host the most planets." }, { "kind": "preprint", "citation": "Shallue, C. J. and Vanderburg, A. (2017). Identifying Exoplanets with Deep Learning. arXiv:1712.05044.", "title": "Identifying Exoplanets with Deep Learning: A Five Planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://arxiv.org/abs/1712.05044", "date": "2017-12-13", "written_by": "makers", "quote": "two new planets that are identified with high confidence by our model" }, { "kind": "preprint", "citation": "Dattilo A, Vanderburg A, Shallue CJ, et al. Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data. arXiv:1903.10507, 25 March 2019.", "title": "Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data", "url": "https://arxiv.org/abs/1903.10507", "date": "2019-03-25", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Large labeled set of vetted transit signals and false positives", "Convolutional network trained on folded light curves", "Application to systems with known planets to look for weaker signals", "Statistical validation of high-confidence candidates" ], "must_hold": [ "The host star's light curve must contain the transit at detectable but sub-threshold signal-to-noise", "Validation must rule out astrophysical false positives independently of the classifier" ], "echoes": [ { "date": "2019-03-25", "setting": "AstroNet-K2 applied to K2 mission data; two previously unknown super-Earths identified and validated (Dattilo, Vanderburg, Shallue et al., accepted to AJ)", "model_version": "AstroNet-K2", "outcome": "recurred", "source": "https://arxiv.org/abs/1903.10507" } ] }, "paired_incident": null, "headline": "Google neural network finds an eighth planet, Kepler-90i", "metric": "a rocky planet about 30 percent larger than Earth with a 14.4-day orbit", "comparator": { "against": "the automated tests and human vetting previously used to verify Kepler signals", "before": "the weakest signals often are missed using these methods", "after": "the neural network correctly identified true planets and false positives 96 percent of the time", "basis": "measured", "quote": "Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. Shallue and Vanderburg thought there could be more interesting exoplanet discoveries faintly lurking in the data.", "url": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/" }, "later": { "status": "scaled", "date": "2019-03-25", "note": "The same group adapted the network as AstroNet-K2 for the K2 mission and used it to identify and validate two previously unknown exoplanets.", "quote": "We train a convolutional neural network, called AstroNet-K2, to predict whether a given possible exoplanet signal is really caused by an exoplanet or a false positive. AstroNet-K2 is highly successful at classifying exoplanets and false positives, with accuracy of 98% on our test set.", "url": "https://arxiv.org/abs/1903.10507" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the summary, which said that the AJ published the paper in December 2017 when it was only accepted and posted to arXiv then and published on 30 January 2018, widened the 96 percent figure to cover false positives as NASA states, reworded the eight-planet claim to the first exoplanetary system with eight planets, and noted that validation used follow-up data already on the Kepler Community Follow-up Program rather than no new observations.", "source": "https://api.crossref.org/works/10.3847/1538-3881/aa9e09", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nasa.gov/news-release/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star/; https://arxiv.org/abs/1903.10507", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: one independent press release, the makers' peer-reviewed study and two preprints from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0014", "catalog_version": "1.0.0", "source_fingerprint": "4a57491a95cc8e4fb4cf7530fe4f6ea9a7911001c74394781dc882011e99338b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0014-source-0001", "AIBD-0014-source-0002", "AIBD-0014-source-0003", "AIBD-0014-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google (Christopher Shallue, Google Brain) with Andrew Vanderburg (University of Texas at Austin)", "deployer": "Shallue and Vanderburg, applied to NASA Kepler archival data" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The neural network ranked the weak Kepler-90i transit signal above false positives in systems that earlier automated and human searches had already examined. 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Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data. arXiv:1903.10507, 25 March 2019.", "title": "Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data", "url": "https://arxiv.org/abs/1903.10507", "date": "2019-03-25", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0014-source-0001", "AIBD-0014-source-0002", "AIBD-0014-source-0003", "AIBD-0014-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "NASA (2017). 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The Astronomical Journal 155(2), 94.", "title": "Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://iopscience.iop.org/article/10.3847/1538-3881/aa9e09", "date": "2018-01-30", "written_by": "makers", "quote": "Our discovery of an eighth planet brings Kepler-90 into a tie with our Sun as the star known to host the most planets." }, { "kind": "preprint", "citation": "Shallue, C. J. and Vanderburg, A. (2017). Identifying Exoplanets with Deep Learning. arXiv:1712.05044.", "title": "Identifying Exoplanets with Deep Learning: A Five Planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90", "url": "https://arxiv.org/abs/1712.05044", "date": "2017-12-13", "written_by": "makers", "quote": "two new planets that are identified with high confidence by our model" }, { "kind": "preprint", "citation": "Dattilo A, Vanderburg A, Shallue CJ, et al. Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data. arXiv:1903.10507, 25 March 2019.", "title": "Identifying Exoplanets with Deep Learning II: Two New Super-Earths Uncovered by a Neural Network in K2 Data", "url": "https://arxiv.org/abs/1903.10507", "date": "2019-03-25", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Google/UT Austin neural network found Kepler-90i in archival Kepler data; NASA announced it on 14 December 2017 and the AJ published it on 30 January 2018.", "account": "On 14 December 2017 NASA announced a deep convolutional neural network had identified an eighth planet, Kepler-90i, in archival Kepler Space Telescope data. Christopher Shallue (Google Brain) and Andrew Vanderburg (University of Texas at Austin, NASA Sagan Fellow) built it. It was trained on about 15,000 previously vetted Kepler signals and correctly identified true planets and false positives 96 percent of the time in testing. It was then applied to 670 known multi-planet systems to search for weak transit signals missed by earlier methods. Kepler-90i is a rocky planet about 30 percent larger than Earth with a 14.4-day orbit. It was statistically validated together with Kepler-80g, an Earth-sized sixth planet in a resonant chain. The peer-reviewed paper appeared in the Astronomical Journal on 30 January 2018." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Deep convolutional neural network for Kepler transit-signal classification (Shallue and Vanderburg)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google (Christopher Shallue, Google Brain) with Andrew Vanderburg (University of Texas at Austin)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kepler-90i: a deep convolutional neural network finds an eighth planet in archival Kepler data", "headline": "Google neural network finds an eighth planet, Kepler-90i" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4a57491a95cc8e4fb4cf7530fe4f6ea9a7911001c74394781dc882011e99338b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 December 2017 NASA announced a deep convolutional neural network had identified an eighth planet, Kepler-90i, in archival Kepler Space Telescope data. Christopher Shallue (Google Brain) and Andrew Vanderburg (University of Texas at Austin, NASA Sagan Fellow) built it. It was trained on about 15,000 previously vetted Kepler signals and correctly identified true planets and false positives 96 percent of the time in testing. It was then applied to 670 known multi-planet systems to search for weak transit signals missed by earlier methods. Kepler-90i is a rocky planet about 30 percent larger than Earth with a 14.4-day orbit. It was statistically validated together with Kepler-80g, an Earth-sized sixth planet in a resonant chain. The peer-reviewed paper appeared in the Astronomical Journal on 30 January 2018.", "replication": { "produced_by": [ "Large labeled set of vetted transit signals and false positives", "Convolutional network trained on folded light curves", "Application to systems with known planets to look for weaker signals", "Statistical validation of high-confidence candidates" ], "must_hold": [ "The host star's light curve must contain the transit at detectable but sub-threshold signal-to-noise", "Validation must rule out astrophysical false positives independently of the classifier" ], "echoes": [ { "date": "2019-03-25", "setting": "AstroNet-K2 applied to K2 mission data; two previously unknown super-Earths identified and validated (Dattilo, Vanderburg, Shallue et al., accepted to AJ)", "model_version": "AstroNet-K2", "outcome": "recurred", "source": "https://arxiv.org/abs/1903.10507" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0296", "title": "Empatica Embrace seizure alert reaches Morgan McGrath's mother, who calls paramedics after a seizure left the 26-year-old teacher not breathing (Fulton, Missouri)", "summary": "IEEE Spectrum (6 February 2018): an Embrace wristband alerted the mother of Morgan McGrath, 26, of Fulton, Mo., during a seizure about 15 months earlier; she called paramedics and McGrath survived.", "date_observed": "2018-02-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Elie Dolgin reported in IEEE Spectrum on 6 February 2018 on Morgan McGrath, a 26-year-old teacher from Fulton, Missouri. She “suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing”. The article dates the seizure to “fifteen months ago”, about November 2016. Her wrist-worn Embrace device alerted her mother, who called the paramedics, and “thanks to a timely response, McGrath is alive and well today”. The article says it records skin conductance and three-axis accelerometer data and “uses a proprietary algorithm to signal when someone is having a convulsive seizure”. The app sends a text or call to pre-specified caregivers. In testing on 135 patients over more than 6,500 hours it “correctly identified nearly every single seizure”. The Food and Drug Administration (FDA) cleared Embrace (Empatica S.r.l.) under 510(k) K172935 on 26 January 2018, after the McGrath event. The 510(k) summary describes an on-board algorithm validated against video electroencephalography (EEG). On detecting a likely generalized tonic-clonic seizure, it messages the Alert app to call and text designated caregivers. A later prospective multicenter study (Onorati et al. 2021) by Empatica staff with hospital co-authors reports sensitivity for a predefined machine-learning algorithm. It was 0.92 in children and 0.94 in adults. An independent Montreal epilepsy-monitoring-unit study (Jahani et al. 2026) found the Embrace2 detected all 16 convulsive seizures while worn and working. Alerts reached caregivers in 15 of 16 cases, with 29 false alarms. The McGrath rescue rests on this single news item. The Empatica case-study abstract (Regalia, Onorati, Picard, American Epilepsy Society) is not among the sources. No second account of the McGrath event was found.", "category": "protective response", "unexpected": false, "purpose": "Built to detect convulsive seizures from electrodermal activity and motion and to summon designated caregivers. The alert to McGrath's mother was that purpose.", "system": "Empatica Embrace wrist-worn seizure detection (electrodermal activity and accelerometer, on-board algorithm) with the Alert smartphone app", "model_version": "Embrace (the article does not state the generation); echoes concern Embrace2", "developer": "Empatica", "deployer": null, "location": "Fulton, Missouri, United States", "domain": "Healthcare (epilepsy; seizure monitoring)", "segment": "Prescription wearable seizure monitor used at home", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A young woman not breathing during a seizure had paramedics summoned by her mother on the device's alert and is reported alive and well. A potentially life-saving response documented only in one news report." } ], "ai_role": { "status": "assessed", "statement": "Per IEEE Spectrum, the Embrace detected the seizure and its app alerted McGrath's mother, who made the emergency call. The device did not call for help itself. The article calls the algorithm proprietary. The FDA summary describes it as an on-board algorithm validated against video-EEG. Empatica's own 2021 study calls it a predefined machine-learning algorithm. The McGrath event is known only from this single news item. The AES case-study abstract is not among the sources." }, "evidence": [ { "kind": "news report", "citation": "Dolgin E (2018). This Seizure-Detecting Smartwatch Could Save Your Life. IEEE Spectrum, 6 February 2018.", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "McGrath's wristworn Embrace device sent her mother an alert. Her mother called the paramedics." }, { "kind": "news report", "citation": "Dolgin E (2018), IEEE Spectrum, 6 February 2018 (on the seizure).", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "Fifteen months ago, the 26-year-old teacher from Fulton, Mo., suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing." }, { "kind": "regulatory document", "citation": "U.S. Food and Drug Administration (2018). 510(k) Summary K172935, Embrace, Empatica S.r.l.; decision 26 January 2018 (text extracted from the PDF).", "title": "510(k) Summary K172935: Embrace", "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf17/K172935.pdf", "date": "2018-01-26", "written_by": "makers", "quote": "When a likely GTC is detected, the Embrace sends a message to the Alert smartphone application, which initiates calls and texts to summon the attention of designated caregivers." }, { "kind": "peer-reviewed study", "citation": "Onorati F, Regalia G, Caborni C, LaFrance WC Jr, Blum AS, Bidwell J, De Liso P, El Atrache R, Loddenkemper T, Mohammadpour-Touserkani F, Sarkis RA, Friedman D, Jeschke J, Picard R (2021). Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit. Frontiers in Neurology 12:724904 (PMC8418082). Lead authors at Empatica, Inc.", "title": "Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/", "date": "2021-08-18", "written_by": "makers", "quote": "A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm." }, { "kind": "peer-reviewed study", "citation": "Jahani A, Galindo Lazo DA, Sarzo Wabi I, Gharbi O, Robert M, Millan JP, D'Onofrio G, Robin A, Nguyen DK, Bou Assi E (2026). Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit. Epilepsia 67(4):1802-1816 (PMC13075604).", "title": "Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "date": "2026-01-07", "written_by": "independent", "quote": "Alerts successfully reached caregivers in 15 of 16 cases, with one failure due to a Wi‐Fi disconnection." } ], "replication": { "produced_by": [ "A convulsive (generalized tonic-clonic) seizure, the only type the device is cleared to detect", "The wristband worn and paired with a phone running the Alert app, with a caregiver designated", "A caregiver able to reach the patient or call emergency services on receiving the alert" ], "must_hold": [ "Connectivity between watch, phone and caregiver (one of 16 alerts in Montreal failed on a Wi-Fi disconnection)", "Caregivers tolerate false alarms (29 in 373 monitoring days in Montreal, mostly from routine movements)", "Focal seizures without convulsions are not detected (none of 510 in Montreal)" ], "echoes": [ { "date": "2026-01-07", "setting": "Center hospitalier de l'Université de Montréal epilepsy monitoring unit, 72 patients, April 2024 to June 2025; alerts routed to nursing staff", "model_version": "Embrace2", "outcome": "recurred", "source": "Jahani et al. (2026) Epilepsia 67(4):1802-1816, https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/ (quote: 'The Embrace2 wrist‐worn device detected all 16 FBTCSs/GTCSs that occurred while the device was functioning and worn, but none of 510 FSs.')" }, { "date": "2021-08-18", "setting": "Multicentre epilepsy-monitoring-unit study, 152 patients (85 children), 66 convulsive seizures; detection performance only, no home alerts", "model_version": null, "outcome": "recurred", "source": "Onorati et al. (2021) Front Neurol 12:724904, https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/ (sensitivity 0.92 pediatric, 0.94 adult; false alarm rate 1.26 and 0.57 per 24 h)" } ] }, "paired_incident": null, "headline": "Empatica Embrace seizure alert reaches Morgan McGrath's mother", "metric": null, "comparator": { "against": "seizures recorded during more than 6,500 hours of monitoring of 135 patients (device test reported by IEEE Spectrum)", "before": null, "after": "the device correctly identified nearly every single seizure, with a false alarm rate below that of the seizure frequency for most individuals", "basis": "measured", "quote": "When tested on 135 patients who were monitored for a collective total of more than 6,500 hours, the device correctly identified nearly every single seizure, with a false alarm rate below that of the seizure frequency for most individuals.", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life" }, "later": { "status": "persisted", "date": "2026-01-07", "note": "An independent Montreal epilepsy-monitoring-unit study later found the Embrace2 detected all 16 convulsive seizures that occurred while worn and working, with alerts reaching caregivers in 15 of 16 cases and 29 false alarms over the study.", "quote": "Alerts successfully reached caregivers in 15 of 16 cases, with one failure due to a Wi‐Fi disconnection.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life; https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Empatica", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study, one independent news report, the makers' regulatory document and the makers' peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0296", "catalog_version": "1.0.0", "source_fingerprint": "f99e1615d50bffa666908e3450541b8efeac87e0e2db34b16b81b314b6d8fe87", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0296-source-0001", "AIBD-0296-source-0002", "AIBD-0296-source-0003", "AIBD-0296-source-0004", "AIBD-0296-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Empatica" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Per IEEE Spectrum, the Embrace detected the seizure and its app alerted McGrath's mother, who made the emergency call. The device did not call for help itself. The article calls the algorithm proprietary. The FDA summary describes it as an on-board algorithm validated against video-EEG. Empatica's own 2021 study calls it a predefined machine-learning algorithm. The McGrath event is known only from this single news item. The AES case-study abstract is not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Per IEEE Spectrum, the Embrace detected the seizure and its app alerted McGrath's mother, who made the emergency call. The device did not call for help itself. The article calls the algorithm proprietary. The FDA summary describes it as an on-board algorithm validated against video-EEG. Empatica's own 2021 study calls it a predefined machine-learning algorithm. The McGrath event is known only from this single news item. 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She “suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing”. The article dates the seizure to “fifteen months ago”, about November 2016. Her wrist-worn Embrace device alerted her mother, who called the paramedics, and “thanks to a timely response, McGrath is alive and well today”. The article says it records skin conductance and three-axis accelerometer data and “uses a proprietary algorithm to signal when someone is having a convulsive seizure”. The app sends a text or call to pre-specified caregivers. In testing on 135 patients over more than 6,500 hours it “correctly identified nearly every single seizure”. The Food and Drug Administration (FDA) cleared Embrace (Empatica S.r.l.) under 510(k) K172935 on 26 January 2018, after the McGrath event. The 510(k) summary describes an on-board algorithm validated against video electroencephalography (EEG). On detecting a likely generalized tonic-clonic seizure, it messages the Alert app to call and text designated caregivers. A later prospective multicenter study (Onorati et al. 2021) by Empatica staff with hospital co-authors reports sensitivity for a predefined machine-learning algorithm. It was 0.92 in children and 0.94 in adults. An independent Montreal epilepsy-monitoring-unit study (Jahani et al. 2026) found the Embrace2 detected all 16 convulsive seizures while worn and working. Alerts reached caregivers in 15 of 16 cases, with 29 false alarms. The McGrath rescue rests on this single news item. The Empatica case-study abstract (Regalia, Onorati, Picard, American Epilepsy Society) is not among the sources. No second account of the McGrath event was found.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A young woman not breathing during a seizure had paramedics summoned by her mother on the device's alert and is reported alive and well. A potentially life-saving response documented only in one news report." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect convulsive seizures from electrodermal activity and motion and to summon designated caregivers. The alert to McGrath's mother was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Fulton, Missouri, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect convulsive seizures from electrodermal activity and motion and to summon designated caregivers. The alert to McGrath's mother was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2018-02-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life; https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Empatica", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A convulsive (generalized tonic-clonic) seizure, the only type the device is cleared to detect", "The wristband worn and paired with a phone running the Alert app, with a caregiver designated", "A caregiver able to reach the patient or call emergency services on receiving the alert" ], "must_hold": [ "Connectivity between watch, phone and caregiver (one of 16 alerts in Montreal failed on a Wi-Fi disconnection)", "Caregivers tolerate false alarms (29 in 373 monitoring days in Montreal, mostly from routine movements)", "Focal seizures without convulsions are not detected (none of 510 in Montreal)" ], "echoes": [ { "date": "2026-01-07", "setting": "Center hospitalier de l'Université de Montréal epilepsy monitoring unit, 72 patients, April 2024 to June 2025; alerts routed to nursing staff", "model_version": "Embrace2", "outcome": "recurred", "source": "Jahani et al. (2026) Epilepsia 67(4):1802-1816, https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/ (quote: 'The Embrace2 wrist‐worn device detected all 16 FBTCSs/GTCSs that occurred while the device was functioning and worn, but none of 510 FSs.')" }, { "date": "2021-08-18", "setting": "Multicentre epilepsy-monitoring-unit study, 152 patients (85 children), 66 convulsive seizures; detection performance only, no home alerts", "outcome": "recurred", "source": "Onorati et al. (2021) Front Neurol 12:724904, https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/ (sensitivity 0.92 pediatric, 0.94 adult; false alarm rate 1.26 and 0.57 per 24 h)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A convulsive (generalized tonic-clonic) seizure, the only type the device is cleared to detect", "The wristband worn and paired with a phone running the Alert app, with a caregiver designated", "A caregiver able to reach the patient or call emergency services on receiving the alert" ], "must_hold": [ "Connectivity between watch, phone and caregiver (one of 16 alerts in Montreal failed on a Wi-Fi disconnection)", "Caregivers tolerate false alarms (29 in 373 monitoring days in Montreal, mostly from routine movements)", "Focal seizures without convulsions are not detected (none of 510 in Montreal)" ], "echoes": [ { "date": "2026-01-07", "setting": "Center hospitalier de l'Université de Montréal epilepsy monitoring unit, 72 patients, April 2024 to June 2025; alerts routed to nursing staff", "model_version": "Embrace2", "outcome": "recurred", "source": "Jahani et al. (2026) Epilepsia 67(4):1802-1816, https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/ (quote: 'The Embrace2 wrist‐worn device detected all 16 FBTCSs/GTCSs that occurred while the device was functioning and worn, but none of 510 FSs.')" }, { "date": "2021-08-18", "setting": "Multicentre epilepsy-monitoring-unit study, 152 patients (85 children), 66 convulsive seizures; detection performance only, no home alerts", "outcome": "recurred", "source": "Onorati et al. (2021) Front Neurol 12:724904, https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/ (sensitivity 0.92 pediatric, 0.94 adult; false alarm rate 1.26 and 0.57 per 24 h)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life; https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Empatica", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (epilepsy; seizure monitoring)", "segment": "Prescription wearable seizure monitor used at home" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dolgin E (2018). This Seizure-Detecting Smartwatch Could Save Your Life. IEEE Spectrum, 6 February 2018.", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "McGrath's wristworn Embrace device sent her mother an alert. Her mother called the paramedics." }, { "kind": "news report", "citation": "Dolgin E (2018), IEEE Spectrum, 6 February 2018 (on the seizure).", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "Fifteen months ago, the 26-year-old teacher from Fulton, Mo., suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing." }, { "kind": "regulatory document", "citation": "U.S. Food and Drug Administration (2018). 510(k) Summary K172935, Embrace, Empatica S.r.l.; decision 26 January 2018 (text extracted from the PDF).", "title": "510(k) Summary K172935: Embrace", "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf17/K172935.pdf", "date": "2018-01-26", "written_by": "makers", "quote": "When a likely GTC is detected, the Embrace sends a message to the Alert smartphone application, which initiates calls and texts to summon the attention of designated caregivers." }, { "kind": "peer-reviewed study", "citation": "Onorati F, Regalia G, Caborni C, LaFrance WC Jr, Blum AS, Bidwell J, De Liso P, El Atrache R, Loddenkemper T, Mohammadpour-Touserkani F, Sarkis RA, Friedman D, Jeschke J, Picard R (2021). Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit. Frontiers in Neurology 12:724904 (PMC8418082). Lead authors at Empatica, Inc.", "title": "Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/", "date": "2021-08-18", "written_by": "makers", "quote": "A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm." }, { "kind": "peer-reviewed study", "citation": "Jahani A, Galindo Lazo DA, Sarzo Wabi I, Gharbi O, Robert M, Millan JP, D'Onofrio G, Robin A, Nguyen DK, Bou Assi E (2026). Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit. Epilepsia 67(4):1802-1816 (PMC13075604).", "title": "Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "date": "2026-01-07", "written_by": "independent", "quote": "Alerts successfully reached caregivers in 15 of 16 cases, with one failure due to a Wi‐Fi disconnection." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0296-source-0001", "AIBD-0296-source-0002", "AIBD-0296-source-0003", "AIBD-0296-source-0004", "AIBD-0296-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dolgin E (2018). This Seizure-Detecting Smartwatch Could Save Your Life. IEEE Spectrum, 6 February 2018.", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "McGrath's wristworn Embrace device sent her mother an alert. Her mother called the paramedics." }, { "kind": "news report", "citation": "Dolgin E (2018), IEEE Spectrum, 6 February 2018 (on the seizure).", "title": "This Seizure-Detecting Smartwatch Could Save Your Life", "url": "https://spectrum.ieee.org/this-seizuredetecting-smartwatch-could-save-your-life", "date": "2018-02-06", "written_by": "independent", "quote": "Fifteen months ago, the 26-year-old teacher from Fulton, Mo., suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing." }, { "kind": "regulatory document", "citation": "U.S. Food and Drug Administration (2018). 510(k) Summary K172935, Embrace, Empatica S.r.l.; decision 26 January 2018 (text extracted from the PDF).", "title": "510(k) Summary K172935: Embrace", "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf17/K172935.pdf", "date": "2018-01-26", "written_by": "makers", "quote": "When a likely GTC is detected, the Embrace sends a message to the Alert smartphone application, which initiates calls and texts to summon the attention of designated caregivers." }, { "kind": "peer-reviewed study", "citation": "Onorati F, Regalia G, Caborni C, LaFrance WC Jr, Blum AS, Bidwell J, De Liso P, El Atrache R, Loddenkemper T, Mohammadpour-Touserkani F, Sarkis RA, Friedman D, Jeschke J, Picard R (2021). Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit. Frontiers in Neurology 12:724904 (PMC8418082). Lead authors at Empatica, Inc.", "title": "Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/", "date": "2021-08-18", "written_by": "makers", "quote": "A prospective study was conducted for the FDA clearance of an ACM and EDA-based CS-detection device based on a predefined machine learning algorithm." }, { "kind": "peer-reviewed study", "citation": "Jahani A, Galindo Lazo DA, Sarzo Wabi I, Gharbi O, Robert M, Millan JP, D'Onofrio G, Robin A, Nguyen DK, Bou Assi E (2026). Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit. Epilepsia 67(4):1802-1816 (PMC13075604).", "title": "Prospective evaluation of a seizure detection wearable device for timely interventions in an epilepsy monitoring unit", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/", "date": "2026-01-07", "written_by": "independent", "quote": "Alerts successfully reached caregivers in 15 of 16 cases, with one failure due to a Wi‐Fi disconnection." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "IEEE Spectrum (6 February 2018): an Embrace wristband alerted the mother of Morgan McGrath, 26, of Fulton, Mo., during a seizure about 15 months earlier; she called paramedics and McGrath survived.", "account": "Elie Dolgin reported in IEEE Spectrum on 6 February 2018 on Morgan McGrath, a 26-year-old teacher from Fulton, Missouri. She “suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing”. The article dates the seizure to “fifteen months ago”, about November 2016. Her wrist-worn Embrace device alerted her mother, who called the paramedics, and “thanks to a timely response, McGrath is alive and well today”. The article says it records skin conductance and three-axis accelerometer data and “uses a proprietary algorithm to signal when someone is having a convulsive seizure”. The app sends a text or call to pre-specified caregivers. In testing on 135 patients over more than 6,500 hours it “correctly identified nearly every single seizure”. The Food and Drug Administration (FDA) cleared Embrace (Empatica S.r.l.) under 510(k) K172935 on 26 January 2018, after the McGrath event. The 510(k) summary describes an on-board algorithm validated against video electroencephalography (EEG). On detecting a likely generalized tonic-clonic seizure, it messages the Alert app to call and text designated caregivers. A later prospective multicenter study (Onorati et al. 2021) by Empatica staff with hospital co-authors reports sensitivity for a predefined machine-learning algorithm. It was 0.92 in children and 0.94 in adults. An independent Montreal epilepsy-monitoring-unit study (Jahani et al. 2026) found the Embrace2 detected all 16 convulsive seizures while worn and working. Alerts reached caregivers in 15 of 16 cases, with 29 false alarms. The McGrath rescue rests on this single news item. The Empatica case-study abstract (Regalia, Onorati, Picard, American Epilepsy Society) is not among the sources. No second account of the McGrath event was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The device classified sensor signals for possible seizures and sent alerts through its phone app." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The initial report concerned the Embrace device. Later reports concerned Embrace2." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Embrace (the article does not state the generation); echoes concern Embrace2" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Empatica Embrace wrist-worn seizure detection (electrodermal activity and accelerometer, on-board algorithm) with the Alert smartphone app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Empatica" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Empatica Embrace seizure alert reaches Morgan McGrath's mother, who calls paramedics after a seizure left the 26-year-old teacher not breathing (Fulton, Missouri)", "headline": "Empatica Embrace seizure alert reaches Morgan McGrath's mother" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f99e1615d50bffa666908e3450541b8efeac87e0e2db34b16b81b314b6d8fe87" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Elie Dolgin reported in IEEE Spectrum on 6 February 2018 on Morgan McGrath, a 26-year-old teacher from Fulton, Missouri. She “suffered an epileptic seizure that left her unresponsive, frothing at the mouth, with blue lips, and not breathing”. The article dates the seizure to “fifteen months ago”, about November 2016. Her wrist-worn Embrace device alerted her mother, who called the paramedics, and “thanks to a timely response, McGrath is alive and well today”. The article says it records skin conductance and three-axis accelerometer data and “uses a proprietary algorithm to signal when someone is having a convulsive seizure”. The app sends a text or call to pre-specified caregivers. In testing on 135 patients over more than 6,500 hours it “correctly identified nearly every single seizure”. The Food and Drug Administration (FDA) cleared Embrace (Empatica S.r.l.) under 510(k) K172935 on 26 January 2018, after the McGrath event. The 510(k) summary describes an on-board algorithm validated against video electroencephalography (EEG). On detecting a likely generalized tonic-clonic seizure, it messages the Alert app to call and text designated caregivers. A later prospective multicenter study (Onorati et al. 2021) by Empatica staff with hospital co-authors reports sensitivity for a predefined machine-learning algorithm. It was 0.92 in children and 0.94 in adults. An independent Montreal epilepsy-monitoring-unit study (Jahani et al. 2026) found the Embrace2 detected all 16 convulsive seizures while worn and working. Alerts reached caregivers in 15 of 16 cases, with 29 false alarms. The McGrath rescue rests on this single news item. The Empatica case-study abstract (Regalia, Onorati, Picard, American Epilepsy Society) is not among the sources. No second account of the McGrath event was found.", "replication": { "produced_by": [ "A convulsive (generalized tonic-clonic) seizure, the only type the device is cleared to detect", "The wristband worn and paired with a phone running the Alert app, with a caregiver designated", "A caregiver able to reach the patient or call emergency services on receiving the alert" ], "must_hold": [ "Connectivity between watch, phone and caregiver (one of 16 alerts in Montreal failed on a Wi-Fi disconnection)", "Caregivers tolerate false alarms (29 in 373 monitoring days in Montreal, mostly from routine movements)", "Focal seizures without convulsions are not detected (none of 510 in Montreal)" ], "echoes": [ { "date": "2026-01-07", "setting": "Center hospitalier de l'Université de Montréal epilepsy monitoring unit, 72 patients, April 2024 to June 2025; alerts routed to nursing staff", "model_version": "Embrace2", "outcome": "recurred", "source": "Jahani et al. (2026) Epilepsia 67(4):1802-1816, https://pmc.ncbi.nlm.nih.gov/articles/PMC13075604/ (quote: 'The Embrace2 wrist‐worn device detected all 16 FBTCSs/GTCSs that occurred while the device was functioning and worn, but none of 510 FSs.')" }, { "date": "2021-08-18", "setting": "Multicentre epilepsy-monitoring-unit study, 152 patients (85 children), 66 convulsive seizures; detection performance only, no home alerts", "outcome": "recurred", "source": "Onorati et al. (2021) Front Neurol 12:724904, https://pmc.ncbi.nlm.nih.gov/articles/PMC8418082/ (sensitivity 0.92 pediatric, 0.94 adult; false alarm rate 1.26 and 0.57 per 24 h)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0314", "title": "Face matches reported in a search for missing children", "summary": "The ministry reported 2,930 facial matches among children in care. The Delhi High Court later recorded that the software had not helped solve any missing-child case.", "date_observed": "2018-04-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "PTI reported on 22 April 2018 (Business Standard) on an affidavit from the Ministry of Women and Child Development to the Delhi High Court. It said that the Delhi Police, “on a trial basis, used the FRS on 45,000 children living in different children's homes”. Also, 2,930 children “could be recognized between April 6 and April 10”. The ministry's secretary Rakesh Srivastava said that the police shared the outcome on 10 April. In Sadhan Haldar v NCT of Delhi, the court had pressed the police to test-run facial recognition. The ministry had then supplied data on about seven lakh missing children from the Track Child portal. The same report says that identities “have been established and efforts are on to help them reunite with their families”. No reunification is documented in any cited source. The Wire (republished by the Pulitzer Center, 2–3 July 2025) cites the Bureau of Police Research and Development's Compendium of Equipment. It says that the police bought two facial recognition systems on 28 March 2018, manufactured by Innefu Labs and supplied by Pelorus Technologies. It quotes an Innefu blog claiming its AI Vision product “helped in identifying 3000 missing children” in its first four days. On 23 August 2018 Delhi Police counsel Rahul Mehra told the High Court: “The software is not good. There is only two percent match” (NDTV). That was in a habeas corpus matter about women missing from a placement agency. On 22 January 2019 the High Court (Hima Kohli and Manoj Kumar Ohri JJ) recorded in Sadhan Haldar what it was told. The software “has not helped in cracking any case of missing children so far”, against 5,160 children untraced out of 19,916 reported missing in 2016–2018. A Centre for Internet and Society (CIS India) report gives 10,617 matches, of which 3,202 identities were verified, and no reunification count.", "category": "benefit created", "unexpected": false, "purpose": "Procured under the Delhi High Court's direction in Sadhan Haldar to match photographs of missing and found children against the Track Child database. The April 2018 trial run was that intended use.", "system": "Delhi Police Facial Recognition System (reported by The Wire as Innefu Labs' AI Vision)", "model_version": "AI Vision", "developer": "Innefu Labs Pvt Ltd (manufacturer, per The Wire citing the BPR&D Compendium of Equipment); supplied by Pelorus Technologies Pvt Ltd", "deployer": "Delhi Police (Crime Branch), using Ministry of Women and Child Development Track Child portal data", "location": "Delhi, India", "domain": "Policing / missing persons and child protection", "segment": "Missing children in child-care institutions", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The only documented outcome is a raw match count that the police and the High Court later undercut.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No cited source documents a child reunited with a family as a result of the 2,930 matches. The High Court recorded on 22 January 2019 that the software had not cracked any missing-child case." }, { "group": "organizational", "depth": null, "reason": "The police reported 2,930 identities “established” to the ministry. The same police told the court four months later that the software produced only a two percent match." }, { "group": "societal", "depth": null, "reason": "The court's own figures (5,160 children untraced of 19,916 reported in 2016–2018) are the context. No reduction attributable to the software is documented." } ], "ai_role": { "status": "assessed", "statement": "The software produced the 2,930 matches reported in the ministry's affidavit. The claim rests on the police's report of raw output, relayed by PTI, and on the vendor's blog. No cited source verifies a single match to a reunification. The police counsel described the match rate as two percent in August 2018. The Delhi High Court recorded in January 2019 that the software had not helped crack any case. The CIS India figures (10,617 matches, 3,202 identities verified) come from a report that is not among the sources." }, "evidence": [ { "kind": "news report", "citation": "PTI (2018). Facial recognition system helps trace 3,000 missing children in 4 days. Business Standard, 22 April 2018.", "title": "Facial recognition system helps trace 3,000 missing children in 4 days", "url": "https://www.business-standard.com/article/pti-stories/facial-recognition-system-helps-trace-3-000-missing-children-in-4-days-118042200470_1.html", "date": "2018-04-22", "written_by": "independent", "quote": "Of them, 2,930 children could be recognised between April 6 and April 10." }, { "kind": "news report", "citation": "NDTV (2018). 2 Percent Accuracy In Delhi Police Facial Recognition Software, Court Told. NDTV, 23 August 2018.", "title": "2 Percent Accuracy In Delhi Police Facial Recognition Software, Court Told", "url": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242", "date": "2018-08-23", "written_by": "independent", "quote": "The software is not good. There is only two per cent match,", "supports_benefit": false }, { "kind": "court document", "citation": "Delhi High Court (2019). Sadhan Haldar v The State NCT of Delhi & Ors, W.P.(CRL) 1560/2017, order of 22 January 2019 (Hima Kohli and Manoj Kumar Ohri JJ). Indian Kanoon.", "title": "Sadhan Haldar vs The State Nct Of Delhi & Ors on 22 January, 2019", "url": "https://indiankanoon.org/doc/181795735/", "date": "2019-01-22", "written_by": "independent", "quote": "We are told that use of 'Facial Recognition Software' has not helped in cracking any case of missing children so far, which comes as a surprise.", "supports_benefit": false }, { "kind": "news report", "citation": "The Wire / Pulitzer Center (2025). As AI Took Over Policing in Delhi, Who Bore the Brunt? Pulitzer Center, 2 July 2025.", "title": "As AI Took Over Policing in Delhi, Who Bore the Brunt?", "url": "https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt", "date": "2025-07-02", "written_by": "independent", "quote": "During the first four days of its implementation, Innefu's product (AI Vision) helped in identifying 3000 missing children.", "supports_benefit": false }, { "kind": "news report", "citation": "The Wire / Pulitzer Center (2025). Looking Back at the Camera: How Controversial AI Firms Shaped Delhi's Predictive Policing. Pulitzer Center, 3 July 2025.", "title": "Looking Back at the Camera: How Controversial AI Firms Shaped Delhi's Predictive Policing", "url": "https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "date": "2025-07-03", "written_by": "independent", "quote": "While the software was originally manufactured by Innefu Labs Pvt Ltd, it was supplied to the Delhi Police by a vendor named Pelorus Technologies Pvt. Ltd.", "supports_benefit": false }, { "kind": "report", "citation": "Internet Freedom Foundation (2019). The Delhi Police must stop its facial recognition system. internetfreedom.in, 29 December 2019.", "title": "The Delhi Police must stop it's facial recognition system", "url": "https://internetfreedom.in/we-demand-the-delhi-police-stop-its-facial-recognition-system/", "date": "2019-12-29", "written_by": "independent", "quote": "at least three orders of the Hon'ble High Court recording it's dissatisfaction with the facial recognition system as late as August 23, 2019", "supports_benefit": false }, { "kind": "news report", "citation": "Manorama Yearbook (2019). Can facial recognition help fight crime? 10 July 2019.", "title": "Can facial recognition help fight crime?", "url": "https://www.manoramayearbook.in/current-affairs/india/2019/07/10/Can-facial-recognition-help-fight-crime.html", "date": "2019-07-10", "written_by": "independent", "quote": "Of them, the police were able to identify 2,930 children with the software.", "supports_benefit": false } ], "replication": { "produced_by": [ "A court-directed 1:many facial recognition trial on photographs of 45,000 children in children's homes, against Track Child portal data on about seven lakh missing children", "Police reporting of raw match counts to the ministry, which relayed them to the court by affidavit" ], "must_hold": [ "Matches are verified against identity records and followed by reunification, which no cited source shows", "The software's match rate is adequate. The police counsel's statement of a two percent match in August 2018 concerned the same software" ], "echoes": [ { "date": "2018-08-23", "setting": "Delhi High Court suggested using the software to trace women missing from an illegal placement agency; police counsel reported a two percent match", "model_version": null, "outcome": "did not recur", "source": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242" }, { "date": "2019-01-22", "setting": "Delhi High Court review of missing-children cases in Sadhan Haldar v NCT of Delhi", "model_version": null, "outcome": "did not recur", "source": "https://indiankanoon.org/doc/181795735/" } ] }, "paired_incident": null, "headline": "Face matches reported in a search for missing children", "metric": "matched 2,930 identities on 6–10 April 2018", "comparator": null, "later": { "status": "reversed", "date": "2019-01-22", "note": "On 22 January 2019 the Delhi High Court recorded in Sadhan Haldar v. NCT of Delhi that the facial recognition software had not helped crack any missing-child case, after police counsel had reported a two percent match rate in August 2018.", "quote": "“We are told that the use of ‘Facial Recognition Software’ has not helped in cracking any case of missing children so far, which comes as a surprise. It is most unacceptable that the software adopted by the Delhi Police after due diligence has not borne any results.”", "url": "https://indiankanoon.org/doc/181795735/" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": "the court recorded that no case was cracked", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the court recorded that no case was cracked.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "http://web.archive.org/web/20260829155711/https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt; http://web.archive.org/web/20250715172059/https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.innefu.com/contact-us; https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.business-standard.com/article/pti-stories/facial-recognition-system-helps-trace-3-000-missing-children-in-4-days-118042200470_1.html", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent court document, one independent report and five independent news reports. 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NCT of Delhi that the facial recognition software had not helped crack any missing-child case, after police counsel had reported a two percent match rate in August 2018.", "quote": "“We are told that the use of ‘Facial Recognition Software’ has not helped in cracking any case of missing children so far, which comes as a surprise. 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It said the Delhi Police, “on a trial basis, used the FRS on 45,000 children living in different children's homes”. Also, 2,930 children “could be recognized between April 6 and April 10”. The ministry's secretary Rakesh Srivastava said that the police shared the outcome on 10 April. In Sadhan Haldar v NCT of Delhi, the court had pressed the police to test-run facial recognition. The ministry had then supplied data on about seven lakh missing children from the Track Child portal. The same report says identities “have been established and efforts are on to help them reunite with their families”. No reunification is documented in any cited source. The Wire (republished by the Pulitzer Center, 2–3 July 2025) cites the Bureau of Police Research and Development's Compendium of Equipment. It says the police bought two facial recognition systems on 28 March 2018, manufactured by Innefu Labs and supplied by Pelorus Technologies. It quotes an Innefu blog claiming its AI Vision product “helped in identifying 3000 missing children” in its first four days. On 23 August 2018 Delhi Police counsel Rahul Mehra told the High Court: “The software is not good. There is only two percent match” (NDTV). That was in a habeas corpus matter about women missing from a placement agency. On 22 January 2019 the High Court (Hima Kohli and Manoj Kumar Ohri JJ) recorded in Sadhan Haldar what it was told. The software “has not helped in cracking any case of missing children so far”, against 5,160 children untraced out of 19,916 reported missing in 2016–2018. A Centre for Internet and Society (CIS India) report gives 10,617 matches, of which 3,202 identities were verified, and no reunification count; the report itself is not among the sources.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No cited source documents a child reunited with a family as a result of the 2,930 matches. The High Court recorded on 22 January 2019 that the software had not cracked any missing-child case." }, { "group": "organizational", "reason": "The police reported 2,930 identities “established” to the ministry. The same police told the court four months later that the software produced only a two percent match." }, { "group": "societal", "reason": "The court's own figures (5,160 children untraced of 19,916 reported in 2016–2018) are the context. No reduction attributable to the software is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Procured under the Delhi High Court's direction in Sadhan Haldar to match photographs of missing and found children against the Track Child database. The April 2018 trial run was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Delhi, India", "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Procured under the Delhi High Court's direction in Sadhan Haldar to match photographs of missing and found children against the Track Child database. The April 2018 trial run was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2018-04-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the court recorded that no case was cracked.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "http://web.archive.org/web/20260829155711/https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt; http://web.archive.org/web/20250715172059/https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.innefu.com/contact-us; https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.business-standard.com/article/pti-stories/facial-recognition-system-helps-trace-3-000-missing-children-in-4-days-118042200470_1.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A court-directed 1:many facial recognition trial on photographs of 45,000 children in children's homes, against Track Child portal data on about seven lakh missing children", "Police reporting of raw match counts to the ministry, which relayed them to the court by affidavit" ], "must_hold": [ "Matches are verified against identity records and followed by reunification, which no cited source shows", "The software's match rate is adequate. The police counsel's statement of a two percent match in August 2018 concerned the same software" ], "echoes": [ { "date": "2018-08-23", "setting": "Delhi High Court suggested using the software to trace women missing from an illegal placement agency; police counsel reported a two percent match", "outcome": "did not recur", "source": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242" }, { "date": "2019-01-22", "setting": "Delhi High Court review of missing-children cases in Sadhan Haldar v NCT of Delhi", "outcome": "did not recur", "source": "https://indiankanoon.org/doc/181795735/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A court-directed 1:many facial recognition trial on photographs of 45,000 children in children's homes, against Track Child portal data on about seven lakh missing children", "Police reporting of raw match counts to the ministry, which relayed them to the court by affidavit" ], "must_hold": [ "Matches are verified against identity records and followed by reunification, which no cited source shows", "The software's match rate is adequate. The police counsel's statement of a two percent match in August 2018 concerned the same software" ], "echoes": [ { "date": "2018-08-23", "setting": "Delhi High Court suggested using the software to trace women missing from an illegal placement agency; police counsel reported a two percent match", "outcome": "did not recur", "source": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242" }, { "date": "2019-01-22", "setting": "Delhi High Court review of missing-children cases in Sadhan Haldar v NCT of Delhi", "outcome": "did not recur", "source": "https://indiankanoon.org/doc/181795735/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the court recorded that no case was cracked.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "http://web.archive.org/web/20260829155711/https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt; http://web.archive.org/web/20250715172059/https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.innefu.com/contact-us; https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.business-standard.com/article/pti-stories/facial-recognition-system-helps-trace-3-000-missing-children-in-4-days-118042200470_1.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / missing persons and child protection", "segment": "Missing children in child-care institutions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "PTI (2018). Facial recognition system helps trace 3,000 missing children in 4 days. Business Standard, 22 April 2018.", "title": "Facial recognition system helps trace 3,000 missing children in 4 days", "url": "https://www.business-standard.com/article/pti-stories/facial-recognition-system-helps-trace-3-000-missing-children-in-4-days-118042200470_1.html", "date": "2018-04-22", "written_by": "independent", "quote": "Of them, 2,930 children could be recognised between April 6 and April 10." }, { "kind": "news report", "citation": "NDTV (2018). 2 Percent Accuracy In Delhi Police Facial Recognition Software, Court Told. NDTV, 23 August 2018.", "title": "2 Percent Accuracy In Delhi Police Facial Recognition Software, Court Told", "url": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242", "date": "2018-08-23", "written_by": "independent", "quote": "The software is not good. There is only two per cent match,", "supports_benefit": false }, { "kind": "court document", "citation": "Delhi High Court (2019). Sadhan Haldar v The State NCT of Delhi & Ors, W.P.(CRL) 1560/2017, order of 22 January 2019 (Hima Kohli and Manoj Kumar Ohri JJ). Indian Kanoon.", "title": "Sadhan Haldar vs The State Nct Of Delhi & Ors on 22 January, 2019", "url": "https://indiankanoon.org/doc/181795735/", "date": "2019-01-22", "written_by": "independent", "quote": "We are told that use of 'Facial Recognition Software' has not helped in cracking any case of missing children so far, which comes as a surprise.", "supports_benefit": false }, { "kind": "news report", "citation": "The Wire / Pulitzer Center (2025). As AI Took Over Policing in Delhi, Who Bore the Brunt? Pulitzer Center, 2 July 2025.", "title": "As AI Took Over Policing in Delhi, Who Bore the Brunt?", "url": "https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt", "date": "2025-07-02", "written_by": "independent", "quote": "During the first four days of its implementation, Innefu's product (AI Vision) helped in identifying 3000 missing children.", "supports_benefit": false }, { "kind": "news report", "citation": "The Wire / Pulitzer Center (2025). Looking Back at the Camera: How Controversial AI Firms Shaped Delhi's Predictive Policing. Pulitzer Center, 3 July 2025.", "title": "Looking Back at the Camera: How Controversial AI Firms Shaped Delhi's Predictive Policing", "url": "https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "date": "2025-07-03", "written_by": "independent", "quote": "While the software was originally manufactured by Innefu Labs Pvt Ltd, it was supplied to the Delhi Police by a vendor named Pelorus Technologies Pvt. Ltd.", "supports_benefit": false }, { "kind": "report", "citation": "Internet Freedom Foundation (2019). The Delhi Police must stop its facial recognition system. internetfreedom.in, 29 December 2019.", "title": "The Delhi Police must stop it's facial recognition system", "url": "https://internetfreedom.in/we-demand-the-delhi-police-stop-its-facial-recognition-system/", "date": "2019-12-29", "written_by": "independent", "quote": "at least three orders of the Hon'ble High Court recording it's dissatisfaction with the facial recognition system as late as August 23, 2019", "supports_benefit": false }, { "kind": "news report", "citation": "Manorama Yearbook (2019). Can facial recognition help fight crime? 10 July 2019.", "title": "Can facial recognition help fight crime?", "url": "https://www.manoramayearbook.in/current-affairs/india/2019/07/10/Can-facial-recognition-help-fight-crime.html", "date": "2019-07-10", "written_by": "independent", "quote": "Of them, the police were able to identify 2,930 children with the software.", "supports_benefit": false } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0314-source-0001", "AIBD-0314-source-0002", "AIBD-0314-source-0003", "AIBD-0314-source-0004", "AIBD-0314-source-0005", "AIBD-0314-source-0006", "AIBD-0314-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The early report relays the ministry’s matching claim. The court later recorded that no missing-child case had been cracked. The retained investigations add contrary evidence and procurement details." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0314-source-0002", "AIBD-0314-source-0003", "AIBD-0314-source-0004", "AIBD-0314-source-0005", "AIBD-0314-source-0006", "AIBD-0314-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The early report relays the ministry’s matching claim. The court later recorded that no missing-child case had been cracked. The retained investigations add contrary evidence and procurement details." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0314-source-0001", "retained_source_order": [ "AIBD-0314-source-0001", "AIBD-0314-source-0002", "AIBD-0314-source-0003", "AIBD-0314-source-0004", "AIBD-0314-source-0005", "AIBD-0314-source-0006", "AIBD-0314-source-0007" ], "origins": [ { "url": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242", "locator": "PTI report, paragraphs on Rahul Mehra’s submission to the High Court.", "contribution": "The police counsel’s two-percent match statement is contrary evidence, not proof of a benefit.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0002" ] }, { "url": "https://indiankanoon.org/doc/181795735/", "locator": "Order of 22 January 2019, ¶ 12, printed p. 6.", "contribution": "The court records that it was told that no missing-child case had been cracked. It does not find the claimed benefit.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0003" ] }, { "url": "https://pulitzercenter.org/stories/ai-took-over-policing-delhi-who-bore-brunt", "locator": "The investigation’s discussion of AI Vision and the claimed identification of missing children.", "contribution": "The investigation supplies later scrutiny and harm accounts. Its missing-child figure is attributed to the vendor, not independently verified.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0004" ] }, { "url": "https://pulitzercenter.org/stories/looking-back-camera-how-controversial-ai-firms-shaped-delhis-predictive-policing", "locator": "Opening procurement paragraphs and the quotation from Innefu’s AI Vision page.", "contribution": "The investigation establishes procurement and vendor relationships. Its missing-child figure repeats the developer’s account.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0005" ] }, { "url": "https://internetfreedom.in/we-demand-the-delhi-police-stop-its-facial-recognition-system/", "locator": "Sections on the low success rate and the demand to halt facial recognition.", "contribution": "The advocacy report challenges effectiveness and legality. It must not count as an independent study supporting a positive result.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0006" ] }, { "url": "https://www.manoramayearbook.in/current-affairs/india/2019/07/10/Can-facial-recognition-help-fight-crime.html", "locator": "Telangana model, paragraphs on Delhi’s trial and the High Court.", "contribution": "The explainer repeats the ministry’s affidavit and the High Court’s contrary statement. It supplies no new missing-child result.", "relationship": "Independent scrutiny or context, not positive corroboration.", "source_refs": [ "AIBD-0314-source-0007" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0314-source-0002", "AIBD-0314-source-0003", "AIBD-0314-source-0004", "AIBD-0314-source-0005", "AIBD-0314-source-0006", "AIBD-0314-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The early report relays the ministry’s matching claim. The court later recorded that no missing-child case had been cracked. The retained investigations add contrary evidence and procurement details." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The ministry reported 2,930 facial matches among children in care. The Delhi High Court later recorded that the software had not helped solve any missing-child case.", "account": "PTI reported on 22 April 2018 (Business Standard) on an affidavit from the Ministry of Women and Child Development to the Delhi High Court. It said that the Delhi Police, “on a trial basis, used the FRS on 45,000 children living in different children's homes”. Also, 2,930 children “could be recognized between April 6 and April 10”. The ministry's secretary Rakesh Srivastava said that the police shared the outcome on 10 April. In Sadhan Haldar v NCT of Delhi, the court had pressed the police to test-run facial recognition. The ministry had then supplied data on about seven lakh missing children from the Track Child portal. The same report says that identities “have been established and efforts are on to help them reunite with their families”. No reunification is documented in any cited source. The Wire (republished by the Pulitzer Center, 2–3 July 2025) cites the Bureau of Police Research and Development's Compendium of Equipment. It says that the police bought two facial recognition systems on 28 March 2018, manufactured by Innefu Labs and supplied by Pelorus Technologies. It quotes an Innefu blog claiming its AI Vision product “helped in identifying 3000 missing children” in its first four days. On 23 August 2018 Delhi Police counsel Rahul Mehra told the High Court: “The software is not good. There is only two percent match” (NDTV). That was in a habeas corpus matter about women missing from a placement agency. On 22 January 2019 the High Court (Hima Kohli and Manoj Kumar Ohri JJ) recorded in Sadhan Haldar what it was told. The software “has not helped in cracking any case of missing children so far”, against 5,160 children untraced out of 19,916 reported missing in 2016–2018. A Centre for Internet and Society (CIS India) report gives 10,617 matches, of which 3,202 identities were verified, and no reunification count." } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software compared facial images to propose possible matches." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The Wire identified the facial-recognition software as Innefu Labs’ AI Vision." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "AI Vision" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Delhi Police Facial Recognition System (reported by The Wire as Innefu Labs' AI Vision)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Innefu Labs Pvt Ltd (manufacturer, per The Wire citing the BPR&D Compendium of Equipment); supplied by Pelorus Technologies Pvt Ltd" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Face matches reported in a search for missing children", "headline": "Face matches reported in a search for missing children" } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c0b5467b4ae848089208b52fc57badd37164494b3e763b011569e920449d0023" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "PTI reported on 22 April 2018 (Business Standard) on an affidavit from the Ministry of Women and Child Development to the Delhi High Court. It said the Delhi Police, “on a trial basis, used the FRS on 45,000 children living in different children's homes”. Also, 2,930 children “could be recognized between April 6 and April 10”. The ministry's secretary Rakesh Srivastava said that the police shared the outcome on 10 April. In Sadhan Haldar v NCT of Delhi, the court had pressed the police to test-run facial recognition. The ministry had then supplied data on about seven lakh missing children from the Track Child portal. The same report says identities “have been established and efforts are on to help them reunite with their families”. No reunification is documented in any cited source. The Wire (republished by the Pulitzer Center, 2–3 July 2025) cites the Bureau of Police Research and Development's Compendium of Equipment. It says the police bought two facial recognition systems on 28 March 2018, manufactured by Innefu Labs and supplied by Pelorus Technologies. It quotes an Innefu blog claiming its AI Vision product “helped in identifying 3000 missing children” in its first four days. On 23 August 2018 Delhi Police counsel Rahul Mehra told the High Court: “The software is not good. There is only two percent match” (NDTV). That was in a habeas corpus matter about women missing from a placement agency. On 22 January 2019 the High Court (Hima Kohli and Manoj Kumar Ohri JJ) recorded in Sadhan Haldar what it was told. The software “has not helped in cracking any case of missing children so far”, against 5,160 children untraced out of 19,916 reported missing in 2016–2018. A Centre for Internet and Society (CIS India) report gives 10,617 matches, of which 3,202 identities were verified, and no reunification count; the report itself is not among the sources.", "replication": { "produced_by": [ "A court-directed 1:many facial recognition trial on photographs of 45,000 children in children's homes, against Track Child portal data on about seven lakh missing children", "Police reporting of raw match counts to the ministry, which relayed them to the court by affidavit" ], "must_hold": [ "Matches are verified against identity records and followed by reunification, which no cited source shows", "The software's match rate is adequate. The police counsel's statement of a two percent match in August 2018 concerned the same software" ], "echoes": [ { "date": "2018-08-23", "setting": "Delhi High Court suggested using the software to trace women missing from an illegal placement agency; police counsel reported a two percent match", "outcome": "did not recur", "source": "https://www.ndtv.com/delhi-news/2-percent-accuracy-in-delhi-police-facial-recognition-software-court-told-1905242" }, { "date": "2019-01-22", "setting": "Delhi High Court review of missing-children cases in Sadhan Haldar v NCT of Delhi", "outcome": "did not recur", "source": "https://indiankanoon.org/doc/181795735/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 2, "record_mapped": 30, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0192", "title": "FAO and Penn State launch Nuru, an offline AI app that confirms fall armyworm damage for African farmers", "summary": "FAO announced on 25 June 2018 a talking Android app built with PlantVillage to confirm fall armyworm damage offline and feed FAO's FAMEWS; no outcome data in the sources.", "date_observed": "2018-06-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 25 June 2018 FAO announced from Rome that it and Pennsylvania State University had developed and launched Nuru, a talking app using machine learning. It runs offline on a standard Android phone. A farmer holds the phone next to an infested plant and Nuru confirms whether fall armyworm caused the damage. FAO said the pest first appeared in Africa in 2016 and spread across sub-Saharan Africa in 2017. It threatened the food security of more than 300 million people. Nuru was to complement FAO's Fall Armyworm Monitoring and Early Warning System (FAMEWS) app. Data validated by national focal points would flow into a global platform. It was to add Swahili, French and Twi. The New York Times later reported that this fall armyworm tool served as the blueprint for the eLocust3m app of 2020. The cited sources document the launch and design only. No evaluation of accuracy or of any outcome for farmers was found.", "category": "general benefit", "unexpected": false, "purpose": "Confirm fall armyworm damage on maize from a phone held next to the plant, offline, and feed reports into FAO's FAMEWS monitoring system.", "system": "PlantVillage Nuru fall armyworm model (machine learning, offline Android app)", "model_version": null, "developer": "Pennsylvania State University (PlantVillage) with FAO", "deployer": "FAO (Fall Armyworm Monitoring and Early Warning System, FAMEWS) and farmers and extension workers in sub-Saharan Africa", "location": null, "domain": "Agriculture / pest identification", "segment": "Smallholder maize", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The announcement describes confirming fall armyworm damage, with no outcome documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No farmer outcome, accuracy figure or adoption figure appears in the sources." }, { "group": "organizational", "depth": null, "reason": "FAO describes the intended data flow into FAMEWS; no result is reported." } ], "ai_role": { "status": "unassessed", "statement": "Only the launch is documented. FAO, which co-developed the app, wrote the release. No independent evaluation of the fall armyworm model or of any alert that changed a farmer's action was found." }, "evidence": [ { "kind": "press release", "citation": "FAO. Nuru becomes African farmers' newest ally against Fall Armyworm. FAO news, Rome, 25 June 2018.", "title": "Nuru becomes African farmers' newest ally against Fall Armyworm", "url": "https://www.fao.org/newsroom/detail/Nuru-becomes-African-farmers-newest-ally-against-Fall-Armyworm/en", "date": "2018-06-25", "written_by": "makers", "quote": "Nuru is an app that uses cutting-edge technologies involving machine learning and artificial intelligence. It runs inside a standard Android phone and can work also offline." }, { "kind": "news report", "citation": "Nuwer R. As Locusts Swarmed East Africa, This Tech Helped Squash Them. The New York Times, 8 April 2021.", "title": "As Locusts Swarmed East Africa, This Tech Helped Squash Them", "url": "https://www.nytimes.com/2021/04/08/science/locust-swarms-africa.html", "date": "2021-04-08", "written_by": "independent", "quote": "He reached out to Dr. Hughes, who had already created a similar mobile tool with the Food and Agriculture Organization to track a devastating crop pest, the fall armyworm" }, { "kind": "other", "citation": "Hughes D. Nuru at 2 weeks. PlantVillage blog, Penn State, 9 July 2018.", "title": "Nuru at 2 weeks", "url": "https://plantvillage.psu.edu/blogposts/34-nuru-at-2-weeks", "date": "2018-07-09", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "FAO-Penn State collaboration under FAO's five-year fall armyworm program launched October 2017", "Android phones able to run the model offline" ], "must_hold": [ "Farmers hold the phone next to an infested plant", "National focal points validate reports through FAMEWS" ], "echoes": [ { "date": "2020-02-20", "setting": "eLocust3m locust app built by Penn State with FAO in under a month, reusing the fall armyworm app as blueprint", "model_version": "eLocust3m", "outcome": "recurred", "source": "Penn State News, 21 February 2020; The New York Times, 8 April 2021" } ] }, "paired_incident": null, "headline": "FAO and Penn State launch Nuru to confirm fall armyworm damage", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2018-07-09", "note": "Two weeks after release, PlantVillage reported that Nuru's fall armyworm feature had been used with FAO field offices and farmers in seven African countries.", "quote": "So, in these two weeks, we have been testing Nuru with scientists who work in UN FAO field offices in Ethiopia, Zambia, Zimbabwe and with colleagues in Ghana and Burundi. Nuru was also used by farmers in Kenya and Uganda. So, in just two weeks Nuru was used for fall armyworm in 7 African countries!", "url": "https://plantvillage.psu.edu/blogposts/34-nuru-at-2-weeks" }, "value": null, "developer_country": "United States", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Learning among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://plantvillage.psu.edu/blogposts/34-nuru-at-2-weeks", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://www.fao.org/contact-us/en/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to FAO.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' press release and the makers' other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0192", "catalog_version": "1.0.0", "source_fingerprint": "25595a7ca55243edae9a7dc5df9e1a4f250f24d774312eaaa4e2ada903e39a8a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0192-source-0001", "AIBD-0192-source-0002", "AIBD-0192-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Pennsylvania State University (PlantVillage) with FAO", "deployer": "FAO (Fall Armyworm Monitoring and Early Warning System, FAMEWS) and farmers and extension workers in sub-Saharan Africa" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Only the launch is documented. FAO, which co-developed the app, wrote the release. No independent evaluation of the fall armyworm model or of any alert that changed a farmer's action was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the makers' press release and the makers' other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No farmer outcome, accuracy figure or adoption figure appears in the sources." }, { "group": "organizational", "reason": "FAO describes the intended data flow into FAMEWS; no result is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, 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release, PlantVillage reported that Nuru's fall armyworm feature had been used with FAO field offices and farmers in seven African countries.", "quote": "So, in these two weeks, we have been testing Nuru with scientists who work in UN FAO field offices in Ethiopia, Zambia, Zimbabwe and with colleagues in Ghana and Burundi. Nuru was also used by farmers in Kenya and Uganda. So, in just two weeks Nuru was used for fall armyworm in 7 African countries!", "url": "https://plantvillage.psu.edu/blogposts/34-nuru-at-2-weeks" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0192" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The announcement describes confirming fall armyworm damage, with no outcome documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 25 June 2018 FAO announced from Rome that it and Pennsylvania State University had developed and launched Nuru, a talking app using machine learning. It runs offline on a standard Android phone. A farmer holds the phone next to an infested plant and Nuru confirms whether fall armyworm caused the damage. FAO said the pest first appeared in Africa in 2016 and spread across sub-Saharan Africa in 2017. It threatened the food security of more than 300 million people. Nuru was to complement FAO's Fall Armyworm Monitoring and Early Warning System (FAMEWS) app. Data validated by national focal points would flow into a global platform. It was to add Swahili, French and Twi. The New York Times later reported that this fall armyworm tool served as the blueprint for the eLocust3m app of 2020. The cited sources document the launch and design only. No evaluation of accuracy or of any outcome for farmers was found.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No farmer outcome, accuracy figure or adoption figure appears in the sources." }, { "group": "organizational", "reason": "FAO describes the intended data flow into FAMEWS; no result is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Confirm fall armyworm damage on maize from a phone held next to the plant, offline, and feed reports into FAO's FAMEWS monitoring system." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "Italy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Nuru becomes African farmers' newest ally against Fall Armyworm. FAO news, Rome, 25 June 2018.", "title": "Nuru becomes African farmers' newest ally against Fall Armyworm", "url": "https://www.fao.org/newsroom/detail/Nuru-becomes-African-farmers-newest-ally-against-Fall-Armyworm/en", "date": "2018-06-25", "written_by": "makers", "quote": "Nuru is an app that uses cutting-edge technologies involving machine learning and artificial intelligence. It runs inside a standard Android phone and can work also offline." }, { "kind": "news report", "citation": "Nuwer R. As Locusts Swarmed East Africa, This Tech Helped Squash Them. 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PlantVillage blog, Penn State, 9 July 2018.", "title": "Nuru at 2 weeks", "url": "https://plantvillage.psu.edu/blogposts/34-nuru-at-2-weeks", "date": "2018-07-09", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0192-source-0001", "AIBD-0192-source-0002", "AIBD-0192-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "FAO. Nuru becomes African farmers' newest ally against Fall Armyworm. FAO news, Rome, 25 June 2018.", "title": "Nuru becomes African farmers' newest ally against Fall Armyworm", "url": "https://www.fao.org/newsroom/detail/Nuru-becomes-African-farmers-newest-ally-against-Fall-Armyworm/en", "date": "2018-06-25", "written_by": "makers", "quote": "Nuru is an app that uses cutting-edge technologies involving machine learning and artificial intelligence. It runs inside a standard Android phone and can work also offline." }, { "kind": "news report", "citation": "Nuwer R. As Locusts Swarmed East Africa, This Tech Helped Squash Them. 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It runs offline on a standard Android phone. A farmer holds the phone next to an infested plant and Nuru confirms whether fall armyworm caused the damage. FAO said the pest first appeared in Africa in 2016 and spread across sub-Saharan Africa in 2017. It threatened the food security of more than 300 million people. Nuru was to complement FAO's Fall Armyworm Monitoring and Early Warning System (FAMEWS) app. Data validated by national focal points would flow into a global platform. It was to add Swahili, French and Twi. The New York Times later reported that this fall armyworm tool served as the blueprint for the eLocust3m app of 2020. The cited sources document the launch and design only. No evaluation of accuracy or of any outcome for farmers was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PlantVillage Nuru fall armyworm model (machine learning, offline Android app)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Pennsylvania State University (PlantVillage) with FAO" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FAO and Penn State launch Nuru, an offline AI app that confirms fall armyworm damage for African farmers", "headline": "FAO and Penn State launch Nuru to confirm fall armyworm damage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "25595a7ca55243edae9a7dc5df9e1a4f250f24d774312eaaa4e2ada903e39a8a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 25 June 2018 FAO announced from Rome that it and Pennsylvania State University had developed and launched Nuru, a talking app using machine learning. It runs offline on a standard Android phone. A farmer holds the phone next to an infested plant and Nuru confirms whether fall armyworm caused the damage. FAO said the pest first appeared in Africa in 2016 and spread across sub-Saharan Africa in 2017. It threatened the food security of more than 300 million people. Nuru was to complement FAO's Fall Armyworm Monitoring and Early Warning System (FAMEWS) app. Data validated by national focal points would flow into a global platform. It was to add Swahili, French and Twi. The New York Times later reported that this fall armyworm tool served as the blueprint for the eLocust3m app of 2020. The cited sources document the launch and design only. No evaluation of accuracy or of any outcome for farmers was found.", "replication": { "produced_by": [ "FAO-Penn State collaboration under FAO's five-year fall armyworm program launched October 2017", "Android phones able to run the model offline" ], "must_hold": [ "Farmers hold the phone next to an infested plant", "National focal points validate reports through FAMEWS" ], "echoes": [ { "date": "2020-02-20", "setting": "eLocust3m locust app built by Penn State with FAO in under a month, reusing the fall armyworm app as blueprint", "model_version": "eLocust3m", "outcome": "recurred", "source": "Penn State News, 21 February 2020; The New York Times, 8 April 2021" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0223", "title": "CBP facial comparison at Dulles flags a French-passport impostor on day three; Congolese ID found in his shoe", "summary": "CBP's new facial comparison system at Dulles reported a mismatch for a man presenting a French passport on 22 August 2018; a Congolese ID was found in his shoe and he was returned to Brazil.", "date_observed": "2018-08-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 22 August 2018, the third day of facial comparison biometrics at Washington Dulles International Airport, a 26-year-old man arrived from Sao Paulo. He presented a French passport at primary inspection. CBP's release states the officer used the facial comparison biometric technology, which confirmed the man was not a match to the passport. In secondary inspection officers found his authentic Republic of Congo identification card concealed in his shoe. CBP Area Port Director Daniel Mattina told NBC News the man was apprehended, processed and returned to Brazil. CBP called him the first impostor detected with the technology. CBP releases record a second (8 September 2018) and third (1 October 2018) impostor at Dulles and, by September 2021, more than 900 impostors nationally. The sources do not name the matching-algorithm vendor.", "category": "harm prevented", "unexpected": false, "purpose": "Verify arriving international travelers' identities by comparing a live photo with passport or visa photos in government holdings, to detect impostors and expedite entry.", "system": "CBP facial comparison biometric system (biometric entry/exit, Traveler Verification Service)", "model_version": null, "developer": "Not named in the sources", "deployer": "U.S. Customs and Border Protection, Office of Field Operations, Washington Dulles International Airport", "location": "Sterling, United States", "domain": "Border security", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": "The crime stopped was passport fraud, not a violent act.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "An attempt to enter the United States on another person's genuine passport was stopped and the traveler removed. Sources document no further threat beyond the document fraud." }, { "group": "organizational", "depth": 1, "reason": "CBP gained a verified first detection for a system then three days into use at Dulles. Subsequent releases report repeated catches." } ], "ai_role": { "status": "assessed", "statement": "The facial comparison match (less than two seconds per CBP) produced the mismatch that triggered secondary inspection. The search and removal were human actions. The documentation is CBP's own release (deployer, not developer) plus NBC with a named CBP official. The algorithm vendor and the match threshold are not in the sources. CBP's “99% match rate” claim is unaudited here." }, "evidence": [ { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 23 Aug 2018", "title": "CBP at Washington Dulles International Airport intercepted an imposter using new cutting-edge Facial Comparison Biometrics technology", "url": "https://www.cbp.gov/newsroom/local-media-release/cbp-washington-dulles-international-airport-intercepted-imposter-using", "date": "2018-08-23", "written_by": "deployer", "quote": "The officer utilized CBP’s new facial comparison biometric technology which confirmed the man was not a match to the passport he presented." }, { "kind": "news report", "citation": "Tom Costello and Ethan Sacks, NBC News, 23 Aug 2018", "title": "New facial recognition tech catches first impostor at D.C. airport", "url": "https://www.nbcnews.com/news/us-news/new-facial-recognition-tech-catches-first-impostor-d-c-airport-n903236", "date": "2018-08-23", "written_by": "independent", "quote": "So he was trying to enter the country illegally, we apprehended him, processed him and returned him back to Brazil," }, { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 24 Sep 2021", "title": "Laredo CBP Officers Detect Impostor Through Facial Biometrics", "url": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "date": "2021-09-24", "written_by": "deployer", "quote": "CBP has leveraged facial biometrics to prevent more than 900 impostors from illegally entering the United States" } ], "replication": { "produced_by": [ "Live photo at primary inspection compared against passport/visa photos retrieved from government holdings via airline manifests", "Officer referral to secondary inspection on a reported mismatch", "Traveler using a genuine document issued to someone else" ], "must_hold": [ "A reference photo of the document's true bearer must exist in DHS holdings", "Officers must act on mismatches rather than override them", "Photo quality and demographic performance of the matcher must be adequate" ], "echoes": [ { "date": "2018-09-08", "setting": "Washington Dulles; Ghanaian woman presenting a U.S. passport", "model_version": null, "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/second-impostor-three-weeks-caught-cbp-biometric-verification" }, { "date": "2018-10-01", "setting": "Washington Dulles; Cameroonian woman presenting a U.S. passport, arrested under 18 USC 1544", "model_version": null, "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/national-media-release/dulles-cbp-s-new-biometric-verification-technology-catches-third" }, { "date": "2021-09-20", "setting": "Laredo Gateway to the Americas Bridge; Mexican woman presenting a U.S. permanent resident card", "model_version": null, "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" } ] }, "paired_incident": null, "headline": "CBP facial comparison at Dulles flags a French-passport impostor", "metric": "by September 2021, more than 900 impostors nationally", "comparator": null, "later": { "status": "scaled", "date": "2021-09-24", "note": "By September 2021 CBP reported that facial biometrics had stopped more than 900 impostors nationwide since September 2018 and that close to 100 million travelers had been processed.", "quote": "Since September 2018, CBP has leveraged facial biometrics to prevent more than 900 impostors from illegally entering the United States by using genuine travel documents that were issued to other people.", "url": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" }, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/U.S._Customs_and_Border_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0223", "catalog_version": "1.0.0", "source_fingerprint": "db88b80b0b25a1bd4071bfc8291de447404b6d96fb0a7ee2ccba5687e66bfd98", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0223-source-0001", "AIBD-0223-source-0002", "AIBD-0223-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not named in the sources", "deployer": "U.S. Customs and Border Protection, Office of Field Operations, Washington Dulles International Airport" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The facial comparison match (less than two seconds per CBP) produced the mismatch that triggered secondary inspection. The search and removal were human actions. The documentation is CBP's own release (deployer, not developer) plus NBC with a named CBP official. The algorithm vendor and the match threshold are not in the sources. CBP's “99% match rate” claim is unaudited here." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The facial comparison match (less than two seconds per CBP) produced the mismatch that triggered secondary inspection. The search and removal were human actions. The documentation is CBP's own release (deployer, not developer) plus NBC with a named CBP official. 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illegally entering the United States by using genuine travel documents that were issued to other people.", "url": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0223" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": 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Sao Paulo. He presented a French passport at primary inspection. CBP's release states the officer used the facial comparison biometric technology, which confirmed the man was not a match to the passport. In secondary inspection officers found his authentic Republic of Congo identification card concealed in his shoe. CBP Area Port Director Daniel Mattina told NBC News the man was apprehended, processed and returned to Brazil. CBP called him the first impostor detected with the technology. CBP releases record a second (8 September 2018) and third (1 October 2018) impostor at Dulles and, by September 2021, more than 900 impostors nationally. The sources do not name the matching-algorithm vendor.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "An attempt to enter the United States on another person's genuine passport was stopped and the traveler removed. 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external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Verify arriving international travelers' identities by comparing a live photo with passport or visa photos in government holdings, to detect impostors and expedite entry." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2018-08-22", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; 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Ghanaian woman presenting a U.S. passport", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/second-impostor-three-weeks-caught-cbp-biometric-verification" }, { "date": "2018-10-01", "setting": "Washington Dulles; Cameroonian woman presenting a U.S. passport, arrested under 18 USC 1544", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/national-media-release/dulles-cbp-s-new-biometric-verification-technology-catches-third" }, { "date": "2021-09-20", "setting": "Laredo Gateway to the Americas Bridge; Mexican woman presenting a U.S. permanent resident card", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Live photo at primary inspection compared against passport/visa photos retrieved from government holdings via airline manifests", "Officer referral to secondary inspection on a reported mismatch", "Traveler using a genuine document issued to someone else" ], "must_hold": [ "A reference photo of the document's true bearer must exist in DHS holdings", "Officers must act on mismatches rather than override them", "Photo quality and demographic performance of the matcher must be adequate" ], "echoes": [ { "date": "2018-09-08", "setting": "Washington Dulles; Ghanaian woman presenting a U.S. passport", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/second-impostor-three-weeks-caught-cbp-biometric-verification" }, { "date": "2018-10-01", "setting": "Washington Dulles; Cameroonian woman presenting a U.S. passport, arrested under 18 USC 1544", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/national-media-release/dulles-cbp-s-new-biometric-verification-technology-catches-third" }, { "date": "2021-09-20", "setting": "Laredo Gateway to the Americas Bridge; Mexican woman presenting a U.S. permanent resident card", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/U.S._Customs_and_Border_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Border security", "segment": "Government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 23 Aug 2018", "title": "CBP at Washington Dulles International Airport intercepted an imposter using new cutting-edge Facial Comparison Biometrics technology", "url": "https://www.cbp.gov/newsroom/local-media-release/cbp-washington-dulles-international-airport-intercepted-imposter-using", "date": "2018-08-23", "written_by": "deployer", "quote": "The officer utilized CBP’s new facial comparison biometric technology which confirmed the man was not a match to the passport he presented." }, { "kind": "news report", "citation": "Tom Costello and Ethan Sacks, NBC News, 23 Aug 2018", "title": "New facial recognition tech catches first impostor at D.C. airport", "url": "https://www.nbcnews.com/news/us-news/new-facial-recognition-tech-catches-first-impostor-d-c-airport-n903236", "date": "2018-08-23", "written_by": "independent", "quote": "So he was trying to enter the country illegally, we apprehended him, processed him and returned him back to Brazil," }, { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 24 Sep 2021", "title": "Laredo CBP Officers Detect Impostor Through Facial Biometrics", "url": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "date": "2021-09-24", "written_by": "deployer", "quote": "CBP has leveraged facial biometrics to prevent more than 900 impostors from illegally entering the United States" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0223-source-0001", "AIBD-0223-source-0002", "AIBD-0223-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 23 Aug 2018", "title": "CBP at Washington Dulles International Airport intercepted an imposter using new cutting-edge Facial Comparison Biometrics technology", "url": "https://www.cbp.gov/newsroom/local-media-release/cbp-washington-dulles-international-airport-intercepted-imposter-using", "date": "2018-08-23", "written_by": "deployer", "quote": "The officer utilized CBP’s new facial comparison biometric technology which confirmed the man was not a match to the passport he presented." }, { "kind": "news report", "citation": "Tom Costello and Ethan Sacks, NBC News, 23 Aug 2018", "title": "New facial recognition tech catches first impostor at D.C. airport", "url": "https://www.nbcnews.com/news/us-news/new-facial-recognition-tech-catches-first-impostor-d-c-airport-n903236", "date": "2018-08-23", "written_by": "independent", "quote": "So he was trying to enter the country illegally, we apprehended him, processed him and returned him back to Brazil," }, { "kind": "press release", "citation": "U.S. Customs and Border Protection, local media release, 24 Sep 2021", "title": "Laredo CBP Officers Detect Impostor Through Facial Biometrics", "url": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics", "date": "2021-09-24", "written_by": "deployer", "quote": "CBP has leveraged facial biometrics to prevent more than 900 impostors from illegally entering the United States" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CBP's new facial comparison system at Dulles reported a mismatch for a man presenting a French passport on 22 August 2018; a Congolese ID was found in his shoe and he was returned to Brazil.", "account": "On 22 August 2018, the third day of facial comparison biometrics at Washington Dulles International Airport, a 26-year-old man arrived from Sao Paulo. He presented a French passport at primary inspection. CBP's release states the officer used the facial comparison biometric technology, which confirmed the man was not a match to the passport. In secondary inspection officers found his authentic Republic of Congo identification card concealed in his shoe. CBP Area Port Director Daniel Mattina told NBC News the man was apprehended, processed and returned to Brazil. CBP called him the first impostor detected with the technology. CBP releases record a second (8 September 2018) and third (1 October 2018) impostor at Dulles and, by September 2021, more than 900 impostors nationally. The sources do not name the matching-algorithm vendor." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "CBP facial comparison biometric system (biometric entry/exit, Traveler Verification Service)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CBP facial comparison at Dulles flags a French-passport impostor on day three; Congolese ID found in his shoe", "headline": "CBP facial comparison at Dulles flags a French-passport impostor" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "db88b80b0b25a1bd4071bfc8291de447404b6d96fb0a7ee2ccba5687e66bfd98" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 22 August 2018, the third day of facial comparison biometrics at Washington Dulles International Airport, a 26-year-old man arrived from Sao Paulo. He presented a French passport at primary inspection. CBP's release states the officer used the facial comparison biometric technology, which confirmed the man was not a match to the passport. In secondary inspection officers found his authentic Republic of Congo identification card concealed in his shoe. CBP Area Port Director Daniel Mattina told NBC News the man was apprehended, processed and returned to Brazil. CBP called him the first impostor detected with the technology. CBP releases record a second (8 September 2018) and third (1 October 2018) impostor at Dulles and, by September 2021, more than 900 impostors nationally. The sources do not name the matching-algorithm vendor.", "replication": { "produced_by": [ "Live photo at primary inspection compared against passport/visa photos retrieved from government holdings via airline manifests", "Officer referral to secondary inspection on a reported mismatch", "Traveler using a genuine document issued to someone else" ], "must_hold": [ "A reference photo of the document's true bearer must exist in DHS holdings", "Officers must act on mismatches rather than override them", "Photo quality and demographic performance of the matcher must be adequate" ], "echoes": [ { "date": "2018-09-08", "setting": "Washington Dulles; Ghanaian woman presenting a U.S. passport", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/second-impostor-three-weeks-caught-cbp-biometric-verification" }, { "date": "2018-10-01", "setting": "Washington Dulles; Cameroonian woman presenting a U.S. passport, arrested under 18 USC 1544", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/national-media-release/dulles-cbp-s-new-biometric-verification-technology-catches-third" }, { "date": "2021-09-20", "setting": "Laredo Gateway to the Americas Bridge; Mexican woman presenting a U.S. permanent resident card", "outcome": "recurred", "source": "https://www.cbp.gov/newsroom/local-media-release/laredo-cbp-officers-detect-impostor-through-facial-biometrics" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0030", "title": "Machine-learning cardiac-arrest recognition on Copenhagen 112 calls: capability study and null randomized trial", "summary": "Copenhagen EMS call model beat dispatchers on sensitivity (84.1% vs 72.5%); RCT found no significant gain in dispatcher recognition.", "date_observed": "2018-09-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Copenhagen Emergency Medical Services used a machine-learning framework to listen to 112 calls and flag suspected out-of-hospital cardiac arrest for dispatchers. The European Emergency Number Association names it as Corti's. A retrospective study of 108,607 calls from 2014 found the model recognized cardiac arrest with higher sensitivity than dispatchers (84.1% versus 72.5%). It was also faster (median 44 versus 54 seconds). A double-masked randomized trial of 169,049 calls ran from 1 September 2018 to 31 December 2019. It found dispatcher recognition of confirmed arrests of 93.1% with alerts versus 90.5% without, a non-significant difference. Alerts alone were more sensitive than dispatchers (85.0% versus 77.5%). No individual patient outcome attributable to an alert is documented.", "category": "general benefit", "unexpected": false, "purpose": "The model was built to recognize out-of-hospital cardiac arrest during emergency calls so dispatchers can start telephone CPR sooner. The measured capability is that intended function, but no discrete changed outcome is documented.", "system": "Corti machine-learning call-analysis framework for out-of-hospital cardiac arrest recognition (the peer-reviewed papers describe it only as 'a machine learning framework'; the EENA report names Corti)", "model_version": null, "developer": "Corti (Copenhagen, Denmark)", "deployer": "Copenhagen Emergency Medical Services, Emergency Medical Dispatch Center Copenhagen", "location": "Copenhagen, Denmark", "domain": "Emergency medical dispatch / public safety", "segment": "112 emergency call handling", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The accuracy gain is the model's alone; the randomized trial found no significant gain in dispatcher recognition.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The evidence is aggregate (sensitivity, time-to-recognition, trial-level recognition rates) with no individually attributable changed outcome. The randomized trial found no significant improvement in dispatcher recognition." }, { "group": "organizational", "depth": null, "reason": "A capability study and a null randomized trial. No discrete organizational event with an observed outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The AI listened to live calls and alerted dispatchers. In the randomized trial its alerts were more sensitive than dispatchers alone (85.0% vs 77.5%). They did not significantly change dispatcher recognition (93.1% vs 90.5%, P = .15). The benefit is thus a demonstrated detection capability, not a verified change in any patient's course." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Blomberg SN, Christensen HC, Lippert F, et al. (2021). Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial. JAMA Network Open 4(1):e2032320.", "title": "Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial", "url": "https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774644", "date": "2021-01-05", "written_by": "deployer", "quote": "Machine learning alerts alone had a significantly higher sensitivity than dispatchers without alerts for confirmed OHCA (85.0% vs 77.5%; P < .001)" }, { "kind": "peer-reviewed study", "citation": "Blomberg SN, Folke F, Ersboll AK, Christensen HC, Torp-Pedersen C, Sayre MR, Counts CR, Lippert FK (2019). Machine learning as a supportive tool to recognize cardiac arrest in emergency calls. Resuscitation 138:322-329. doi:10.1016/j.resuscitation.2019.01.015.", "title": "Machine learning as a supportive tool to recognize cardiac arrest in emergency calls", "url": "https://doi.org/10.1016/j.resuscitation.2019.01.015", "date": null, "written_by": "deployer", "quote": "Compared with medical dispatchers, the machine learning framework had a significantly higher sensitivity (72.5% vs. 84.1%, p < 0.001) with lower specificity (98.8% vs. 97.3%, p < 0.001)." }, { "kind": "report", "citation": "European Emergency Number Association and Corti (2020). Detecting out-of-hospital cardiac arrest using artificial intelligence: project report. EENA, Brussels.", "title": "Detecting out-of-hospital cardiac arrest using artificial intelligence: project report", "url": "https://eena.org/wp-content/uploads/2020_01_13_Corti_Report.pdf", "date": "2020-01-13", "written_by": "makers", "quote": "This document is authored by EENA and Corti staff members with contributions from individual members of EENA and Corti." } ], "replication": { "produced_by": [ "Access to recorded 112 call audio with linked outcome data (7,211 hours of Danish training data per the EENA report)", "Speech-recognition pipeline running in real time on live calls", "A dispatch center whose baseline recognition was already high (90.5% in the control arm)" ], "must_hold": [ "Dispatchers act on alerts. The trial suggests alerts did not change their behavior enough to shift recognition", "Call language and acoustics match the training data (EENA reports weaker performance on smaller French and Italian datasets)" ], "echoes": [ { "date": "2018-09-01", "setting": "Randomized trial at Copenhagen EMS, 1 September 2018 to 31 December 2019: the model's sensitivity advantage recurred (85.0% vs 77.5%) but improved dispatcher recognition did not materialize (93.1% vs 90.5%, P = .15)", "model_version": null, "outcome": "recurred", "source": "https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774644" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "446", "title": "ShotSpotter Failed to Alert Authorities of Mass Shooting in North Carolina", "url": "https://incidentdatabase.ai/cite/446", "severity": null, "group": "organizational", "basis": "Machine listening for emergencies to alert responders: Corti flags cardiac arrest on 112 calls, while ShotSpotter's acoustic classifier missed a Durham drive-by shooting, leaving police unalerted and five victims hospitalized." }, "headline": "Corti model beats dispatchers on sensitivity; RCT shows no gain", "metric": "higher sensitivity than dispatchers (84.1% versus 72.5%)", "comparator": null, "later": { "status": "persisted", "date": "2021-01-04", "note": "The randomized trial of 169,049 calls confirmed the model's sensitivity advantage over dispatchers (85.0% vs 77.5%) but found no significant improvement in dispatcher recognition when alerts were shown (93.1% vs 90.5%).", "quote": "Machine learning alerts alone had a significantly higher sensitivity than dispatchers without alerts for confirmed OHCA (85.0% vs 77.5%; P < .001) but lower specificity (97.4% vs 99.6%; P < .001) and positive predictive value (17.8% vs 55.8%; P < .001). This randomized clinical trial did not find any significant improvement in dispatchers' ability to recognize cardiac arrest when supported by machine learning even though artificial intelligence did surpass human recognition.", "url": "https://europepmc.org/article/PMC/PMC7788469" }, "value": null, "developer_country": "Denmark", "deployer_country": "Denmark", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 446 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/446", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC7788469", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.prnewswire.com/news-releases/dcai-and-corti-launch-sovereign-ai-control-layer-for-european-enterprises---trifork-first-to-adopt-as-implementation-partner-302856390.html; https://da.wikipedia.org/wiki/Region_Hovedstadens_Akutberedskab", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' report and two peer-reviewed studies from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0030", "catalog_version": "1.0.0", "source_fingerprint": "daf5403a07b439a40e17ca47772b334f2977af8ebe2a3766ba089e8480ee55ee", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0030-source-0001", "AIBD-0030-source-0002", "AIBD-0030-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Corti (Copenhagen, Denmark)", "deployer": "Copenhagen Emergency Medical Services, Emergency Medical Dispatch Center Copenhagen" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI listened to live calls and alerted dispatchers. In the randomized trial its alerts were more sensitive than dispatchers alone (85.0% vs 77.5%). They did not significantly change dispatcher recognition (93.1% vs 90.5%, P = .15). The benefit is thus a demonstrated detection capability, not a verified change in any patient's course." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The AI listened to live calls and alerted dispatchers. In the randomized trial its alerts were more sensitive than dispatchers alone (85.0% vs 77.5%). They did not significantly change dispatcher recognition (93.1% vs 90.5%, P = .15). The benefit is thus a demonstrated detection capability, not a verified change in any patient's course." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' report and two peer-reviewed studies from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The evidence is aggregate (sensitivity, time-to-recognition, trial-level recognition rates) with no individually attributable changed outcome. The randomized trial found no significant improvement in dispatcher recognition." }, { "group": "organizational", "reason": "A capability study and a null randomized trial. No discrete organizational event with an observed outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The evidence is aggregate (sensitivity, time-to-recognition, trial-level recognition rates) with no individually attributable changed outcome. 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The European Emergency Number Association names it as Corti's. A retrospective study of 108,607 calls from 2014 found the model recognized cardiac arrest with higher sensitivity than dispatchers (84.1% versus 72.5%). It was also faster (median 44 versus 54 seconds). A double-masked randomized trial of 169,049 calls ran from 1 September 2018 to 31 December 2019. It found dispatcher recognition of confirmed arrests of 93.1% with alerts versus 90.5% without, a non-significant difference. Alerts alone were more sensitive than dispatchers (85.0% versus 77.5%). No individual patient outcome attributable to an alert is documented.", "replication": { "produced_by": [ "Access to recorded 112 call audio with linked outcome data (7,211 hours of Danish training data per the EENA report)", "Speech-recognition pipeline running in real time on live calls", "A dispatch center whose baseline recognition was already high (90.5% in the control arm)" ], "must_hold": [ "Dispatchers act on alerts. The trial suggests alerts did not change their behavior enough to shift recognition", "Call language and acoustics match the training data (EENA reports weaker performance on smaller French and Italian datasets)" ], "echoes": [ { "date": "2018-09-01", "setting": "Randomized trial at Copenhagen EMS, 1 September 2018 to 31 December 2019: the model's sensitivity advantage recurred (85.0% vs 77.5%) but improved dispatcher recognition did not materialize (93.1% vs 90.5%, P = .15)", "outcome": "recurred", "source": "https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774644" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0018", "title": "Convolutional neural network finds 72 previously undetected pulses from fast radio burst FRB 121102 in Green Bank Telescope data", "summary": "A Berkeley CNN found 72 unseen pulses from FRB 121102 in Green Bank data, published in ApJ and announced by GBO (Sep 2018).", "date_observed": "2018-09-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 10 September 2018 the Green Bank Observatory announced a convolutional neural network found 72 previously undetected pulses from repeating fast radio burst FRB 121102. They were in a five-hour, 400-terabyte Green Bank Telescope observation made on 26 August 2017. Gerry Zhang, a University of California, Berkeley graduate student, built it with Breakthrough Listen collaborators. Conventional algorithms had found 21 bursts in the same data. The combined 93 pulses, including 45 within the first 30 minutes, were reported in a peer-reviewed Astrophysical Journal paper (Zhang et al. 2018). They served to search for periodicity. The detections come from a re-analysis of the team's own data. No independent re-detection by another group was found in the sources.", "category": "benefit created", "unexpected": false, "purpose": "Built to detect fast radio burst pulses in Breakthrough Listen radio data that classical search algorithms miss. The 72 bursts were that purpose.", "system": "Convolutional neural network for FRB pulse detection (Zhang et al., Breakthrough Listen / Berkeley SETI Research Center)", "model_version": null, "developer": "University of California, Berkeley (Berkeley SETI Research Center, Breakthrough Listen)", "deployer": "Breakthrough Listen, on Green Bank Telescope data", "location": "Berkeley, United States", "domain": "Astrophysics / radio transients", "segment": "Academic research", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Breakthrough Listen recovered 72 additional bursts from an existing 400-terabyte Green Bank dataset without new telescope time." }, { "group": "societal", "depth": 2, "reason": "The FRB research community gained a much larger burst sample (93 pulses in five hours) from the only known repeating FRB at the time." } ], "ai_role": { "status": "assessed", "statement": "The CNN flagged 72 pulses in data that a classical de-dispersion search had already processed, finding 21. The detections were vetted by the authors and accepted in peer review. The result is a verified discovery, but the wording “independently confirmed” is not met. No re-detection by another group is among the sources." }, "evidence": [ { "kind": "press release", "citation": "Green Bank Observatory (2018). AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data. Press release.", "title": "AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data", "url": "https://greenbankobservatory.org/press-release/artificial-intelligence-uncovers-72-new-fast-radio-bursts-in-gbts-breakthrough-listen-data/", "date": "2018-09-10", "written_by": "deployer", "quote": "the promise it shows for using machine learning to detect signals missed by classical algorithms" }, { "kind": "peer-reviewed study", "citation": "Zhang, Y. G., Gajjar, V., Foster, G., Siemion, A., Cordes, J., Law, C. and Wang, Y. (2018). Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach. The Astrophysical Journal 866, 149 (arXiv:1809.03043).", "title": "Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach", "url": "https://arxiv.org/abs/1809.03043", "date": "2018-09-09", "written_by": "makers", "quote": "The detection of 72 new pulses from the repeating fast radio burst FRB 121102" } ], "replication": { "produced_by": [ "A long, high-time-resolution radio observation of a known repeater", "A CNN trained on simulated and real pulses", "Re-analysis of data already searched by classical methods" ], "must_hold": [ "Candidate pulses must survive radio-frequency-interference rejection and visual vetting", "Independent confirmation would require re-detection by a second pipeline or group" ], "echoes": [] }, "paired_incident": null, "headline": "Berkeley CNN finds 72 unseen pulses from FRB 121102", "metric": "found 72 previously undetected pulses from the repeating fast radio burst FRB 121102", "comparator": { "against": "the conventional search algorithm previously run on the same observation", "before": "21 bursts have been previously detected", "after": "72 new pulses, totaling 93 pulses in five hours", "basis": "measured", "quote": "We report the detection of 72 new pulses from the repeating fast radio burst FRB 121102 in Breakthrough Listen C-band (4-8 GHz) observations at the Green Bank Telescope. The new pulses were found with a convolutional neural network in data taken on August 26, 2017, where 21 bursts have been previously detected.", "url": "https://arxiv.org/abs/1809.03043" }, "later": { "status": "unknown", "date": null, "note": "No later re-detection or follow-up of these 72 pulses was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/abs/1809.03043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Berkeley; https://en.wikipedia.org/wiki/Breakthrough_Listen", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's press release. 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They were in a five-hour, 400-terabyte Green Bank Telescope observation made on 26 August 2017. Gerry Zhang, a University of California, Berkeley graduate student, built it with Breakthrough Listen collaborators. Conventional algorithms had found 21 bursts in the same data. The combined 93 pulses, including 45 within the first 30 minutes, were reported in a peer-reviewed Astrophysical Journal paper (Zhang et al. 2018). They served to search for periodicity. The detections come from a re-analysis of the team's own data. No independent re-detection by another group was found in the sources.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Breakthrough Listen recovered 72 additional bursts from an existing 400-terabyte Green Bank dataset without new telescope time." }, { "group": "societal", "depth": 2, "reason": "The FRB research community gained a much larger burst sample (93 pulses in five hours) from the only known repeating FRB at the time." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect fast radio burst pulses in Breakthrough Listen radio data that classical search algorithms miss. The 72 bursts were that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Berkeley, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect fast radio burst pulses in Breakthrough Listen radio data that classical search algorithms miss. The 72 bursts were that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2018-09-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/abs/1809.03043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Berkeley; https://en.wikipedia.org/wiki/Breakthrough_Listen", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A long, high-time-resolution radio observation of a known repeater", "A CNN trained on simulated and real pulses", "Re-analysis of data already searched by classical methods" ], "must_hold": [ "Candidate pulses must survive radio-frequency-interference rejection and visual vetting", "Independent confirmation would require re-detection by a second pipeline or group" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/abs/1809.03043", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Berkeley; https://en.wikipedia.org/wiki/Breakthrough_Listen", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Astrophysics / radio transients", "segment": "Academic research" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Green Bank Observatory (2018). AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data. Press release.", "title": "AI Uncovers 72 New FRBs in GBT's Breakthrough Listen Data", "url": "https://greenbankobservatory.org/press-release/artificial-intelligence-uncovers-72-new-fast-radio-bursts-in-gbts-breakthrough-listen-data/", "date": "2018-09-10", "written_by": "deployer", "quote": "the promise it shows for using machine learning to detect signals missed by classical algorithms" }, { "kind": "peer-reviewed study", "citation": "Zhang, Y. G., Gajjar, V., Foster, G., Siemion, A., Cordes, J., Law, C. and Wang, Y. (2018). Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach. The Astrophysical Journal 866, 149 (arXiv:1809.03043).", "title": "Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach", "url": "https://arxiv.org/abs/1809.03043", "date": "2018-09-09", "written_by": "makers", "quote": "The detection of 72 new pulses from the repeating fast radio burst FRB 121102" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0018-source-0001", "AIBD-0018-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Green Bank Observatory (2018). 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The Astrophysical Journal 866, 149 (arXiv:1809.03043).", "title": "Fast Radio Burst 121102 Pulse Detection and Periodicity: A Machine Learning Approach", "url": "https://arxiv.org/abs/1809.03043", "date": "2018-09-09", "written_by": "makers", "quote": "The detection of 72 new pulses from the repeating fast radio burst FRB 121102" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Berkeley CNN found 72 unseen pulses from FRB 121102 in Green Bank data, published in ApJ and announced by GBO (Sep 2018).", "account": "On 10 September 2018 the Green Bank Observatory announced a convolutional neural network found 72 previously undetected pulses from repeating fast radio burst FRB 121102. They were in a five-hour, 400-terabyte Green Bank Telescope observation made on 26 August 2017. Gerry Zhang, a University of California, Berkeley graduate student, built it with Breakthrough Listen collaborators. Conventional algorithms had found 21 bursts in the same data. The combined 93 pulses, including 45 within the first 30 minutes, were reported in a peer-reviewed Astrophysical Journal paper (Zhang et al. 2018). They served to search for periodicity. The detections come from a re-analysis of the team's own data. 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It uses anonymous and aggregated web search and location data. It was deployed in Las Vegas between May and August 2016 (5,038 inspections completed, 61 prompted by FINDER). In Chicago it ran between November 2016 and March 2017 (5,880 inspections, 71 prompted by FINDER). Each morning the Southern Nevada Health District and the Chicago Department of Public Health received a list of restaurants identified by FINDER. They dispatched inspectors unaware of whether an inspection was prompted by the model. Of the 132 FINDER-identified restaurants, 69 (52.3%) were deemed unsafe, against 2,662 of 10,786 (24.7%) baseline restaurants, an odds ratio of 3.06 (95% CI 2.14–4.35). Against routine inspections alone the unsafe rate was 22.7% and the odds ratio 3.16. In 38% of cases the restaurant potentially causing illness was not the last one visited. The sources give deployment months but no exact day.", "category": "benefit created", "unexpected": false, "purpose": "Identify restaurants likely to be causing foodborne illness from anonymized, aggregated web-search and location data so that health departments can target inspections.", "system": "FINDER (machine-learned foodborne illness detection model)", "model_version": null, "developer": "Google", "deployer": "Southern Nevada Health District (Las Vegas) and Chicago Department of Public Health", "location": "Las Vegas and Chicago, United States", "domain": "Food safety / public health", "segment": "Restaurant inspection targeting", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "69 of 132 FINDER-prompted inspections (52.3%) found an unsafe restaurant versus 2,662 of 10,786 (24.7%) baseline inspections. Odds ratio 3.06 (95% CI 2.14–4.35), adjusted for city and risk level." }, { "group": "societal", "depth": null, "reason": "The paper argues that corrective actions “would prevent” spread of foodborne illness but documents no reduction in illness." } ], "ai_role": { "status": "assessed", "statement": "FINDER generated the daily restaurant lists. Inspectors did not know the source of the prompt. The comparison is observational (FINDER-prompted versus other inspections during the same period), not randomized. Google employees conceived and implemented the model and co-authored the peer-reviewed evaluation. Health department staff oversaw implementation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Sadilek A, Caty S, DiPrete L, Mansour R, Schenk T Jr, Bergtholdt M, Jha A, Ramaswami P, Gabrilovich E. Machine-learned epidemiology: real-time detection of foodborne illness at scale. npj Digital Medicine 1:36 (2018). doi:10.1038/s41746-018-0045-1", "title": "Machine-learned epidemiology: real-time detection of foodborne illness at scale", "url": "https://doi.org/10.1038/s41746-018-0045-1", "date": "2018-11-06", "written_by": "makers", "quote": "Of all the restaurants identified by FINDER, 52.3% were deemed unsafe upon inspection, compared to 24.7% for BASELINE restaurants (Table 2)." } ], "replication": { "produced_by": [ "Aggregated web search and location logs covering a city's restaurant patrons", "Health departments able to act on a daily list", "Inspection outcome records to compare against routine and complaint-based inspections" ], "must_hold": [ "Access to anonymized, aggregated search and location data held by Google", "Tolerance of the incubation-period lag before inference", "Inspectors unaware of the prompt source" ], "echoes": [ { "date": "2016-02-18", "setting": "Las Vegas, Twitter-based nEmesis controlled experiment from 2 January 2015", "model_version": "nEmesis (predecessor)", "outcome": "recurred", "source": "Sadilek et al. 2016, AAAI, doi:10.1609/aaai.v30i2.19072" } ] }, "paired_incident": null, "headline": "Google FINDER flags restaurants 3.1 times as likely to be unsafe", "metric": "52.3% were unsafe versus 24.7% of 10,786 other inspections (odds ratio 3.06)", "comparator": { "against": "all other restaurant inspections conducted in the two cities during the deployment period (BASELINE)", "before": "24.7% of BASELINE restaurants deemed unsafe", "after": "52.3% of FINDER-identified restaurants deemed unsafe (3.06 times as likely)", "basis": "measured", "quote": "Of all the restaurants identified by FINDER, 52.3% were deemed unsafe upon inspection, compared to 24.7% for BASELINE restaurants (Table 2). We used binomial logistic regression to determine the odds ratio of being unsafe for restaurants in the FINDER and BASELINE groups. The former were 3.06 times (95% CI: 2.14–4.35) as likely to be unsafe as the latter, when accounting for restaurant risk level and city in our models (p < 0.001, Table 2).", "url": "https://www.nature.com/articles/s41746-018-0045-1" }, "later": { "status": "unknown", "date": null, "note": "No report of FINDER being deployed again or adopted by other health departments after the 2018 paper was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.nature.com/articles/s41746-018-0045-1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://www.southernnevadahealthdistrict.org/about-us/maps/southern-nevada-health-district-main-facility/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0189", "catalog_version": "1.0.0", "source_fingerprint": "ce8fdf81a945bc5914e0c1f010971ff94700c3abe73393a746e2dd9f530829b7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0189-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google", "deployer": "Southern Nevada Health District (Las Vegas) and Chicago Department of Public Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "FINDER generated the daily restaurant lists. Inspectors did not know the source of the prompt. The comparison is observational (FINDER-prompted versus other inspections during the same period), not randomized. Google employees conceived and implemented the model and co-authored the peer-reviewed evaluation. Health department staff oversaw implementation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "FINDER generated the daily restaurant lists. Inspectors did not know the source of the prompt. The comparison is observational (FINDER-prompted versus other inspections during the same period), not randomized. 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Machine-learned epidemiology: real-time detection of foodborne illness at scale. npj Digital Medicine 1:36 (2018). doi:10.1038/s41746-018-0045-1", "title": "Machine-learned epidemiology: real-time detection of foodborne illness at scale", "url": "https://doi.org/10.1038/s41746-018-0045-1", "date": "2018-11-06", "written_by": "makers", "quote": "Of all the restaurants identified by FINDER, 52.3% were deemed unsafe upon inspection, compared to 24.7% for BASELINE restaurants (Table 2)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Health departments inspected 132 FINDER-flagged restaurants in 2016–2017; 52.3% were unsafe versus 24.7% of 10,786 other inspections (odds ratio 3.06).", "account": "Google built FINDER, a machine-learned model that estimates the fraction of people who visited a restaurant and later searched for terms indicative of food poisoning. It uses anonymous and aggregated web search and location data. It was deployed in Las Vegas between May and August 2016 (5,038 inspections completed, 61 prompted by FINDER). In Chicago it ran between November 2016 and March 2017 (5,880 inspections, 71 prompted by FINDER). Each morning the Southern Nevada Health District and the Chicago Department of Public Health received a list of restaurants identified by FINDER. They dispatched inspectors unaware of whether an inspection was prompted by the model. Of the 132 FINDER-identified restaurants, 69 (52.3%) were deemed unsafe, against 2,662 of 10,786 (24.7%) baseline restaurants, an odds ratio of 3.06 (95% CI 2.14–4.35). Against routine inspections alone the unsafe rate was 22.7% and the odds ratio 3.16. In 38% of cases the restaurant potentially causing illness was not the last one visited. The sources give deployment months but no exact day." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FINDER (machine-learned foodborne illness detection model)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Google FINDER-flagged restaurants are 3.1 times as likely to be unsafe in Las Vegas and Chicago inspections", "headline": "Google FINDER flags restaurants 3.1 times as likely to be unsafe" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ce8fdf81a945bc5914e0c1f010971ff94700c3abe73393a746e2dd9f530829b7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Google built FINDER, a machine-learned model that estimates the fraction of people who visited a restaurant and later searched for terms indicative of food poisoning. It uses anonymous and aggregated web search and location data. It was deployed in Las Vegas between May and August 2016 (5,038 inspections completed, 61 prompted by FINDER). In Chicago it ran between November 2016 and March 2017 (5,880 inspections, 71 prompted by FINDER). Each morning the Southern Nevada Health District and the Chicago Department of Public Health received a list of restaurants identified by FINDER. They dispatched inspectors unaware of whether an inspection was prompted by the model. Of the 132 FINDER-identified restaurants, 69 (52.3%) were deemed unsafe, against 2,662 of 10,786 (24.7%) baseline restaurants, an odds ratio of 3.06 (95% CI 2.14–4.35). Against routine inspections alone the unsafe rate was 22.7% and the odds ratio 3.16. In 38% of cases the restaurant potentially causing illness was not the last one visited. The sources give deployment months but no exact day.", "replication": { "produced_by": [ "Aggregated web search and location logs covering a city's restaurant patrons", "Health departments able to act on a daily list", "Inspection outcome records to compare against routine and complaint-based inspections" ], "must_hold": [ "Access to anonymized, aggregated search and location data held by Google", "Tolerance of the incubation-period lag before inference", "Inspectors unaware of the prompt source" ], "echoes": [ { "date": "2016-02-18", "setting": "Las Vegas, Twitter-based nEmesis controlled experiment from 2 January 2015", "model_version": "nEmesis (predecessor)", "outcome": "recurred", "source": "Sadilek et al. 2016, AAAI, doi:10.1609/aaai.v30i2.19072" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0029", "title": "PAWS patrol-planning field test removes over 1,000 snares in Srepok Wildlife Sanctuary, Cambodia", "summary": "PAWS-directed ranger patrols in Srepok Wildlife Sanctuary removed over 1,000 snares in December 2018, versus 200–300 in a typical month.", "date_observed": "2018-12-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "PAWS (Protection Assistant for Wildlife Security) is a machine-learning pipeline that predicts poaching risk and plans patrols. It was field-tested with WWF Cambodia and Ministry of Environment rangers in Srepok Wildlife Sanctuary, Cambodia, from December 2018. Only the month is given, so the first day is used. Rangers received center coordinates of fifteen 3 x 3 km blocks chosen from PAWS risk predictions, without being told each block's risk class. In the first month, 72 rangers in teams of eight detected poaching in 32 cells and removed over one thousand snares. They had reported removing two or three hundred in an average month. Low-risk blocks yielded no poaching. A second trial ran February to March 2019.", "category": "benefit created", "unexpected": false, "purpose": "PAWS was built to predict where poaching will occur and to prescribe patrol routes that maximize detection and removal of snares. The snare removals are exactly this intended benefit.", "system": "PAWS (Protection Assistant for Wildlife Security), enhanced iWare-E predictive model with Gaussian-process uncertainty and game-theoretic patrol planning", "model_version": "iWare-E with Gaussian-process weak learners trained on January 2015 to April 2018 dry-season data (Xu et al., ICDE 2020)", "developer": "Harvard University and University of Southern California (Milind Tambe and colleagues), with WWF, WCS and Uganda Wildlife Authority co-authors", "deployer": "WWF Cambodia with Cambodia Ministry of Environment rangers, Srepok Wildlife Sanctuary", "location": "Srepok Wildlife Sanctuary (Mondulkiri), Cambodia", "domain": "Conservation / anti-poaching law enforcement", "segment": "Protected-area ranger patrols", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The ranger force's monthly snare removals rose from a reported two or three hundred to over one thousand. A material gain in patrol effectiveness for the operating team. A chi-squared test confirmed predictions discriminated risk (p = 0.023)." }, { "group": "societal", "depth": 3, "reason": "Over one thousand snares were removed from a sanctuary identified as a tiger-reintroduction site. The paper states each snare “represents the life of one animal potentially saved”. A material landscape-scale conservation benefit rather than a documented population-level change." } ], "ai_role": { "status": "assessed", "statement": "The AI's output (risk-ranked 3 x 3 km blocks) determined where patrols went. Rangers were blinded to risk class. High-risk blocks yielded detections while low-risk blocks yielded none. The paper itself cautions that the first QENP test's increased findings “may be partially explained by factors beyond the predictive model”. The 1,000-versus-200–300 comparison relies on rangers' reported averages, not a controlled baseline. The peer-reviewed paper is written by the system's academic developers together with staff of the operating organizations (WWF, WCS, Uganda Wildlife Authority). There is no commercial vendor." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Xu L, Gholami S, Mc Carthy S, Dilkina B, Plumptre A, Tambe M, Singh R, Nsubuga M, Mabonga J, Driciru M, Wanyama F, Rwetsiba A, Okello T, Enyel E (2020). Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations. IEEE ICDE 2020.", "title": "Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations", "url": "https://arxiv.org/pdf/1903.06669", "date": "2019-11-06", "written_by": "makers", "quote": "During the first month of field tests in SWS, park rangers detected poaching in 32 cells and removed over one thousand snares" }, { "kind": "peer-reviewed study", "citation": "Xu L et al. (2020). Stay Ahead of Poachers (abstract page; states the work is a short paper published in ICDE 2020). arXiv.", "title": "Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (abstract)", "url": "https://arxiv.org/abs/1903.06669", "date": "2019-11-06", "written_by": "makers", "quote": "confirm that the predictive power of PAWS extends promisingly to multiple parks" }, { "kind": "news report", "citation": "Geib C (2020). Where to patrol next: 'Netflix' of ranger AI serves up poaching predictions. Mongabay.", "title": "Where to patrol next: 'Netflix' of ranger AI serves up poaching predictions", "url": "https://news.mongabay.com/2020/11/where-to-patrol-next-netflix-of-ranger-ai-serves-up-poaching-predictions/", "date": "2020-11-05", "written_by": "independent", "quote": "rangers in the park have reported finding between 5 and 20 times more snares since they started using the PAWS system" } ], "replication": { "produced_by": [ "Historical SMART patrol data (2015–2018) sufficient to train a risk model despite 3.6% positive labels", "Rangers willing to patrol the suggested blocks and record findings in SMART", "Dry-season deployment when rivers are passable and poaching concentrates in the north of the sanctuary" ], "must_hold": [ "Patrol capacity exists to act on predictions (SWS ranger numbers had more than doubled since 2016)", "Poacher behavior remains spatially predictable from past detections", "Findings are measured against a comparable baseline. The paper notes increases may partly reflect factors beyond the model" ], "echoes": [ { "date": "2019-02-01", "setting": "Second SWS trial, February-March 2019: high-risk blocks yielded 7 detections in 22 cells, low-risk blocks 0 in 34 cells (Table III of the same paper)", "model_version": "iWare-E predictions for January-February 2019", "outcome": "recurred", "source": "https://arxiv.org/pdf/1903.06669" }, { "date": "2020-11-05", "setting": "Ongoing use in Srepok Wildlife Sanctuary; rangers reported finding 5 to 20 times more snares since adopting PAWS, and PAWS was incorporated into SMART", "model_version": null, "outcome": "recurred", "source": "https://news.mongabay.com/2020/11/where-to-patrol-next-netflix-of-ranger-ai-serves-up-poaching-predictions/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "severity": null, "group": "societal", "basis": "Same task and domain: AI-directed anti-poaching in a protected area; PAWS patrols removed 1,000 snares, while Ezemvelo KZN Wildlife's AI cameras failed to detect poachers and four rhinos were killed." }, "headline": "PAWS-directed patrols remove over 1,000 snares in Cambodia", "metric": "removed over 1,000 snares in December 2018, versus 200–300 in a typical month", "comparator": { "against": "the rangers' usual monthly snare removal without PAWS", "before": "two or three hundred snares in an average month", "after": "over one thousand snares in the first month of field tests", "basis": "measured", "quote": "During the first month of field tests in SWS, park rangers detected poaching in 32 cells and removed over one thousand snares—each of which represents the life of one animal potentially saved. The rangers informed us that, by comparison, they typically remove two or three hundred snares in an average month.", "url": "https://arxiv.org/pdf/1903.06669" }, "later": { "status": "scaled", "date": "2020-11-05", "note": "By November 2020 PAWS had been incorporated into the SMART conservation software used in parks worldwide, and Srepok rangers reported finding 5 to 20 times more snares since adopting it.", "quote": "PAWS has been incorporated into the latest update to SMART, which is already used widely by rangers and other park employees to gather data and track observations of illegal activity in parks around the world.", "url": "https://news.mongabay.com/2020/11/where-to-patrol-next-netflix-of-ranger-ai-serves-up-poaching-predictions/" }, "value": null, "developer_country": "United States", "deployer_country": "Cambodia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://arxiv.org/pdf/1903.06669; https://news.mongabay.com/2020/11/where-to-patrol-next-netflix-of-ranger-ai-serves-up-poaching-predictions/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.harvard.edu/about/; https://www.wikidata.org/wiki/Q117405694", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Harvard University.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two peer-reviewed studies from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0029", "catalog_version": "1.0.0", "source_fingerprint": "faaa16a57c0d26842d7dd6d15debcd4322f41ff602ffdd7fce38bf8542a42d9c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0029-source-0001", "AIBD-0029-source-0002", "AIBD-0029-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Harvard University and University of Southern California (Milind Tambe and colleagues), with WWF, WCS and Uganda Wildlife Authority co-authors", "deployer": "WWF Cambodia with Cambodia Ministry of Environment rangers, Srepok Wildlife Sanctuary" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI's output (risk-ranked 3 x 3 km blocks) determined where patrols went. Rangers were blinded to risk class. High-risk blocks yielded detections while low-risk blocks yielded none. The paper itself cautions that the first QENP test's increased findings “may be partially explained by factors beyond the predictive model”. The 1,000-versus-200–300 comparison relies on rangers' reported averages, not a controlled baseline. The peer-reviewed paper is written by the system's academic developers together with staff of the operating organizations (WWF, WCS, Uganda Wildlife Authority). There is no commercial vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI's output (risk-ranked 3 x 3 km blocks) determined where patrols went. Rangers were blinded to risk class. High-risk blocks yielded detections while low-risk blocks yielded none. The paper itself cautions that the first QENP test's increased findings “may be partially explained by factors beyond the predictive model”. The 1,000-versus-200–300 comparison relies on rangers' reported averages, not a controlled baseline. The peer-reviewed paper is written by the system's academic developers together with staff of the operating organizations (WWF, WCS, Uganda Wildlife Authority). There is no commercial vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The ranger force's monthly snare removals rose from a reported two or three hundred to over one thousand. A material gain in patrol effectiveness for the operating team. A chi-squared test confirmed predictions discriminated risk (p = 0.023)." }, { "group": "societal", "depth": 3, "reason": "Over one thousand snares were removed from a sanctuary identified as a tiger-reintroduction site. The paper states each snare “represents the life of one animal potentially saved”. A material landscape-scale conservation benefit rather than a documented population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and two peer-reviewed studies from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The ranger force's monthly snare removals rose from a reported two or three hundred to over one thousand. A material gain in patrol effectiveness for the operating team. A chi-squared test confirmed predictions discriminated risk (p = 0.023)." }, { "group": "societal", "depth": 3, "reason": "Over one thousand snares were removed from a sanctuary identified as a tiger-reintroduction site. The paper states each snare “represents the life of one animal potentially saved”. A material landscape-scale conservation benefit rather than a documented population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The ranger force's monthly snare removals rose from a reported two or three hundred to over one thousand. A material gain in patrol effectiveness for the operating team. A chi-squared test confirmed predictions discriminated risk (p = 0.023)." }, { "group": "societal", "depth": 3, "reason": "Over one thousand snares were removed from a sanctuary identified as a tiger-reintroduction site. The paper states each snare “represents the life of one animal potentially saved”. A material landscape-scale conservation benefit rather than a documented population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same task and domain: AI-directed anti-poaching in a protected area; PAWS patrols removed 1,000 snares, while Ezemvelo KZN Wildlife's AI cameras failed to detect poachers and four rhinos were killed.", "links": [ { "database": "AI Incident Database", 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No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "Gaussian-process models within iWare-E." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "iWare-E with Gaussian-process weak learners trained on January 2015 to April 2018 dry-season data (Xu et al., ICDE 2020)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PAWS (Protection Assistant for Wildlife Security), enhanced iWare-E predictive model with Gaussian-process uncertainty and game-theoretic patrol planning" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Harvard University and University of Southern California (Milind Tambe and colleagues), with WWF, WCS and Uganda Wildlife Authority co-authors" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "PAWS patrol-planning field test removes over 1,000 snares in Srepok Wildlife Sanctuary, Cambodia", "headline": "PAWS-directed patrols remove over 1,000 snares in Cambodia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "faaa16a57c0d26842d7dd6d15debcd4322f41ff602ffdd7fce38bf8542a42d9c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "PAWS (Protection Assistant for Wildlife Security) is a machine-learning pipeline that predicts poaching risk and plans patrols. It was field-tested with WWF Cambodia and Ministry of Environment rangers in Srepok Wildlife Sanctuary, Cambodia, from December 2018. Only the month is given, so the first day is used. Rangers received center coordinates of fifteen 3 x 3 km blocks chosen from PAWS risk predictions, without being told each block's risk class. In the first month, 72 rangers in teams of eight detected poaching in 32 cells and removed over one thousand snares. They had reported removing two or three hundred in an average month. Low-risk blocks yielded no poaching. A second trial ran February to March 2019.", "replication": { "produced_by": [ "Historical SMART patrol data (2015–2018) sufficient to train a risk model despite 3.6% positive labels", "Rangers willing to patrol the suggested blocks and record findings in SMART", "Dry-season deployment when rivers are passable and poaching concentrates in the north of the sanctuary" ], "must_hold": [ "Patrol capacity exists to act on predictions (SWS ranger numbers had more than doubled since 2016)", "Poacher behavior remains spatially predictable from past detections", "Findings are measured against a comparable baseline. The paper notes increases may partly reflect factors beyond the model" ], "echoes": [ { "date": "2019-02-01", "setting": "Second SWS trial, February-March 2019: high-risk blocks yielded 7 detections in 22 cells, low-risk blocks 0 in 34 cells (Table III of the same paper)", "model_version": "iWare-E predictions for January-February 2019", "outcome": "recurred", "source": "https://arxiv.org/pdf/1903.06669" }, { "date": "2020-11-05", "setting": "Ongoing use in Srepok Wildlife Sanctuary; rangers reported finding 5 to 20 times more snares since adopting PAWS, and PAWS was incorporated into SMART", "outcome": "recurred", "source": "https://news.mongabay.com/2020/11/where-to-patrol-next-netflix-of-ranger-ai-serves-up-poaching-predictions/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0035", "title": "Reykjavik University speech recognizer replaces first-stage manual transcription of Icelandic parliamentary speeches at Althingi", "summary": "Reykjavik University's ASR has produced Althingi's first-draft speech transcripts in production since January 2019 (Interspeech 2019).", "date_observed": "2019-01-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Alþingi, the Icelandic parliament, has collaborated with Reykjavik University since 2016 to replace the first, manual stage of transcribing members' speeches with automatic speech recognition. Helgadóttir and colleagues' Interspeech 2019 paper states: “The system entered a test phase in October 2018, and has been in production since January 2019.” The production system used a time-delay deep neural network acoustic model with an n-gram language model. Word error rate was 8.52% on the test set and 15.0 ± 6.0% over 625 speeches in the wild. Althingi's transcribers graded 77% of transcripts as Good. Morgunblaðið reported on 16 November 2019 that about 640 hours of speeches had been transcribed.", "category": "benefit created", "unexpected": false, "purpose": "Built specifically to transcribe Althingi speeches for post-editing and publication. This benefit was that purpose.", "system": "Althingi ASR system (time-delay deep neural network acoustic model, n-gram language model, punctuation and paragraph models)", "model_version": null, "developer": "Reykjavik University Language and Voice Lab (ASR for Althingi project)", "deployer": "Alþingi (Icelandic parliament) speech department", "location": "Alþingi, Reykjavík, Iceland", "domain": "Government / language technology", "segment": "Parliamentary transcription", "benefit_type": "Repetitive Task Automation", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Althingi replaced first-stage manual transcription with ASR drafts graded Good for 77% of speeches, with about 640 hours transcribed by November 2019." }, { "group": "societal", "depth": 1, "reason": "Vísir reported on 4 March 2018 that the recognizer was released under an open-source license for Icelandic-language developers. A small, diffuse benefit." } ], "ai_role": { "status": "assessed", "statement": "The ASR produces the first-draft transcript. Althingi's editors still post-edit, so the benefit is editing time saved rather than full automation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Helgadóttir IR, Nikulásdóttir AB, Borský M, Fong JY, Kjaran R, Guðnason J (2019). The Althingi ASR System. Interspeech 2019, Graz.", "title": "The Althingi ASR System", "url": "https://www.isca-archive.org/interspeech_2019/helgadottir19_interspeech.pdf", "date": "2019-09-15", "written_by": "makers", "quote": "The system entered a test phase in October 2018, and has been in production since January 2019." }, { "kind": "peer-reviewed study", "citation": "Helgadóttir IR et al. (2019). The Althingi ASR System. ISCA Archive abstract page.", "title": "ISCA Archive - The Althingi ASR System", "url": "https://www.isca-archive.org/interspeech_2019/helgadottir19_interspeech.html", "date": "2019-09-15", "written_by": "makers", "quote": "The transcribers of Althingi graded 77% of the speech transcripts as Good." }, { "kind": "news report", "citation": "Morgunblaðið (16 Nov 2019). Talgreinir skrifar ræður alþingismanna.", "title": "Talgreinir skrifar ræður alþingismanna", "url": "https://www.mbl.is/frettir/innlent/2019/11/16/talgreinir_skrifar_raedur_althingismanna/", "date": "2019-11-16", "written_by": "independent", "quote": "Talgreinir er lykilverkfæri í þessari máltækni" }, { "kind": "news report", "citation": "Vísir (4 Mar 2018). Gefa út íslenskan talgreini með opnu hugbúnaðarleyfi.", "title": "Gefa út íslenskan talgreini með opnu hugbúnaðarleyfi", "url": "https://www.visir.is/g/2018218636d", "date": "2018-03-04", "written_by": "independent", "quote": "Við erum að búa til lausnir sem greina ræður Alþingismanna og hjálpa riturunum þar við að gefa ræðurnar út á ritmáli" }, { "kind": "dataset", "citation": "Linguistic Data Consortium (2021). Althingi Parliamentary Speech, LDC2021S01 (authors Helgadóttir IR, Kjaran R, Nikulásdóttir AB, Guðnason J, the system's developers).", "title": "Althingi Parliamentary Speech - Linguistic Data Consortium", "url": "https://catalog.ldc.upenn.edu/LDC2021S01", "date": null, "written_by": "makers", "quote": "The purpose of that project was to develop an ASR (automatic speech recognition) system for parliamentary speech to replace the procedure of manually transcribing performed speeches." } ], "replication": { "produced_by": [ "About 6,300 hours of aligned parliamentary speech, of which a re-cleaned 1,000-hour subset trained the production recognizer (Interspeech 2019). The 542 hours of 2005–2016 speeches released as LDC2021S01 are a dataset publication, not the production training set", "An existing manual transcription and editing workflow to slot into", "Integration with Althingi's publishing systems from October 2018" ], "must_hold": [ "Editors accept ASR drafts (77% graded Good)", "Continued model maintenance by the developing lab" ], "echoes": [ { "date": "2019-11-16", "setting": "Althingi, Reykjavík; about 640 hours of speeches transcribed, roughly ten minutes of speech in three and a half minutes (Morgunblaðið)", "model_version": null, "outcome": "recurred", "source": "https://www.mbl.is/frettir/innlent/2019/11/16/talgreinir_skrifar_raedur_althingismanna/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "708", "title": "Reportedly Faulty AI Transcription Threatens Integrity of Genoa Bribery Probe", "url": "https://incidentdatabase.ai/cite/708", "severity": null, "group": "organizational", "basis": "Same task: automatic transcription of official proceedings for a public institution; Althingi's ASR drafts parliamentary transcripts, while the Italian judiciary's AI transcription recorded “illicit” for “licit”, harming the Genoa Prosecutor's Office and defendants." }, "headline": "Reykjavik University ASR drafts Althingi speech transcripts", "metric": "transcribers graded 77% of transcripts as Good", "comparator": { "against": "the previous manual first-stage transcription by Althingi's transcribers", "before": "First, a human transcriber listens to the audio and transcribes the speech.", "after": "the speech transcripts are now available sooner than before", "basis": "assumed", "quote": "The editors at Althingi have noted that the speech transcripts are now available sooner than before, since the speech recognizer starts transcribing as soon as it sees a new audio file, and the ASR system does not take coffee breaks or go home when office hours end.", "url": "https://www.isca-archive.org/interspeech_2019/helgadottir19_interspeech.pdf" }, "later": null, "value": null, "developer_country": "Iceland", "deployer_country": "Iceland", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 708 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/708", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Marked the Interspeech paper, its abstract page and the LDC dataset as vendor-authored because the system's developers wrote them (the admission gate now rests on the Morgunblaðið and Vísir reports), corrected the training data to the paper's roughly 1,000 re-cleaned hours drawn from about 6,300 hours rather than the 542-hour LDC release, and flagged that no cited source states Alþingi's seat.", "source": "https://www.isca-archive.org/interspeech_2019/helgadottir19_interspeech.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.isca-archive.org/interspeech_2019/helgadottir19_interspeech.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Repetitive Task Automation under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reykjav%C3%ADk_University; https://en.wikipedia.org/wiki/Althing", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, two peer-reviewed studies from the makers and the makers' dataset. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0035", "catalog_version": "1.0.0", "source_fingerprint": "9e2fde75063bde142a78ba5f1f714aa67bdf85d1529bb2de8366dc93061e0c6c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0035-source-0001", "AIBD-0035-source-0002", "AIBD-0035-source-0003", "AIBD-0035-source-0004", "AIBD-0035-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Reykjavik University Language and Voice Lab (ASR for Althingi project)", "deployer": "Alþingi (Icelandic parliament) speech department" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ASR produces the first-draft transcript. Althingi's editors still post-edit, so the benefit is editing time saved rather than full automation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The ASR produces the first-draft transcript. Althingi's editors still post-edit, so the benefit is editing time saved rather than full automation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Althingi replaced first-stage manual transcription with ASR drafts graded Good for 77% of speeches, with about 640 hours transcribed by November 2019." }, { "group": "societal", "depth": 1, "reason": "Vísir reported on 4 March 2018 that the recognizer was released under an open-source license for Icelandic-language developers. 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Morgunblaðið reported on 16 November 2019 that about 640 hours of speeches had been transcribed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Althingi ASR system (time-delay deep neural network acoustic model, n-gram language model, punctuation and paragraph models)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Reykjavik University Language and Voice Lab (ASR for Althingi project)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Reykjavik University speech recognizer replaces first-stage manual transcription of Icelandic parliamentary speeches at Althingi", "headline": "Reykjavik University ASR drafts Althingi speech transcripts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9e2fde75063bde142a78ba5f1f714aa67bdf85d1529bb2de8366dc93061e0c6c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Alþingi, the Icelandic parliament, has collaborated with Reykjavik University since 2016 to replace the first, manual stage of transcribing members' speeches with automatic speech recognition. Helgadóttir and colleagues' Interspeech 2019 paper states: “The system entered a test phase in October 2018, and has been in production since January 2019.” The production system used a time-delay deep neural network acoustic model with an n-gram language model. Word error rate was 8.52% on the test set and 15.0 ± 6.0% over 625 speeches in the wild. Althingi's transcribers graded 77% of transcripts as Good. Morgunblaðið reported on 16 November 2019 that about 640 hours of speeches had been transcribed.", "replication": { "produced_by": [ "About 6,300 hours of aligned parliamentary speech, of which a re-cleaned 1,000-hour subset trained the production recognizer (Interspeech 2019). The 542 hours of 2005–2016 speeches released as LDC2021S01 are a dataset publication, not the production training set", "An existing manual transcription and editing workflow to slot into", "Integration with Althingi's publishing systems from October 2018" ], "must_hold": [ "Editors accept ASR drafts (77% graded Good)", "Continued model maintenance by the developing lab" ], "echoes": [ { "date": "2019-11-16", "setting": "Althingi, Reykjavík; about 640 hours of speeches transcribed, roughly ten minutes of speech in three and a half minutes (Morgunblaðið)", "outcome": "recurred", "source": "https://www.mbl.is/frettir/innlent/2019/11/16/talgreinir_skrifar_raedur_althingismanna/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0177", "title": "VeriPol flags 25 and 39 false robbery reports in Murcia and Málaga in a one-week 2017 pilot; Spain's police drop it in 2024", "summary": "The Spanish National Police's text-based false-report classifier flagged 25 false robberies in Murcia and 39 in Málaga in a week in June 2017 (versus 3 and 12 in the same month over the prior decad...", "date_observed": "2019-02-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "VeriPol, a model for detecting false robbery reports from their text, was developed by Complutense and Carlos III university researchers with police officer Miguel Camacho-Collados. It appeared in Knowledge-Based Systems (Quijano-Sánchez, Liberatore, Camacho-Collados and Camacho-Collados, 2018). The abstract reports a validation accuracy of 91% on more than 1,000 reports from 2015, an improvement of more than 15% over expert officers. It reports a pilot study in June 2017 showing a lower bound on empirical precision of about 83%. Scientific American (1 February 2019) reported that the one-week pilot in Murcia and Málaga detected 25 and 39 false robberies respectively. The same month over the previous decade had 3 and 12. It quoted Camacho Collados on colleagues wasting time on cases that never occurred. Civio (25 March 2025) reported that the police said that in 83.54% of reports flagged false the complainant confessed. It also reported the Interior Ministry's 2018 announcement of nationwide use. Complaints analyzed were 49,702 in 2019 with 2,338 deemed false, and 3,762 in 2022 with 511 deemed false. Use stopped on 21 October 2024 because the tool was not valid in judicial proceedings, it said. A University of Valencia report (September 2024) criticized the 1,122-report training sample, missing officer training and regional language variation. AlgorithmWatch (27 October 2020) found no independent verification of effectiveness since deployment. The pilot month carries no day.", "category": "general benefit", "unexpected": false, "purpose": "Estimate the probability that a robbery report is false from its text to support police decisions.", "system": "VeriPol", "model_version": null, "developer": "Universidad Complutense de Madrid and Universidad Carlos III de Madrid, with Spanish National Police officer Miguel Camacho-Collados", "deployer": "Spanish National Police (Policía Nacional), Ministry of the Interior", "location": "Murcia and Málaga, Spain", "domain": "Fraud and false reporting", "segment": "False robbery reports filed with police", "benefit_type": "Reduced Risk", "taxonomy_note": "The flagged false reports are fraud detected after filing, and independent sources document the absence of evaluation and the 2024 discontinuation.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Flagged-report counts and confession rates are police aggregates with no independent confirmation." }, { "group": "societal", "depth": null, "reason": "No measured effect on insurance fraud or police resources is documented." } ], "ai_role": { "status": "assessed", "statement": "The peer-reviewed paper describes a natural-language-processing and machine-learning classifier with L1 feature selection that outputs the probability a report is false. The paper's authors include the police developer. AlgorithmWatch and Civio report that no independent verification was done before the police stopped using it in October 2024." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Lara Quijano-Sánchez, Federico Liberatore, José Camacho-Collados and Miguel Camacho-Collados, Knowledge-Based Systems, June 2018, DOI 10.1016/j.knosys.2018.03.010", "title": "Applying automatic text-based detection of deceptive language to police reports: Extracting behavioral patterns from a multi-step classification model to understand how we lie to the police", "url": "https://doi.org/10.1016/j.knosys.2018.03.010", "date": null, "written_by": "makers", "quote": "A pilot study shows a lower bound on the empirical precision of 83%, approx." }, { "kind": "news report", "citation": "Emiliano Rodríguez Mega, Scientific American, 1 February 2019", "title": "An Algorithm That Can Spot When People Lie to the Police", "url": "https://www.scientificamerican.com/article/an-algorithm-that-can-spot-when-people-lie-to-the-police/", "date": "2019-02-01", "written_by": "independent", "quote": "Many colleagues were wasting a lot of time investigating cases that had never occurred. It was a problem." }, { "kind": "news report", "citation": "Naiara Bellio, AlgorithmWatch, 27 October 2020", "title": "Spanish police plan to extend use of its lie-detector while efficacy is unclear", "url": "https://algorithmwatch.org/en/spain-police-veripol/", "date": "2020-10-27", "written_by": "independent", "quote": "only labeled 5 of 100 true complaints as false" }, { "kind": "news report", "citation": "Ter García, Carmen Torrecillas, Adrián Maqueda, David Cabo and Lucas Laursen, Civio, 25 March 2025", "title": "Spanish National Police stop using Veripol, its star AI for detecting false reports", "url": "https://civio.es/transparencia/2025/03/25/national-police-stop-using-veripol-its-star-ai-for-detecting-false-reports/", "date": "2025-03-25", "written_by": "independent", "quote": "in 83.54% of the reports identified as false by Veripol, the complainant ended up confessing to lying." }, { "kind": "news report", "citation": "Adrián Maqueda, Carmen Torrecillas, David Cabo, Lucas Laursen and Ter García, AlgorithmWatch, 1 April 2025", "title": "Spanish National Police Halts Veripol, Its Flagship AI To Detect False Reports", "url": "https://algorithmwatch.org/en/spanish-police-halts-veripol/", "date": "2025-04-01", "written_by": "independent", "quote": "it had been proved being of no validity in judicial proceedings." } ], "replication": { "produced_by": [ "Training on 1,122 robbery reports from 2015 (534 genuine, 588 false) labeled by one experienced officer", "Text features selected by L1 penalization plus heuristic rules, scoring reports at the police station" ], "must_hold": [ "Reports written in the same language register as the training data (the Valencia report faulted missing regional variation)", "Officer training and protocols for acting on scores", "Independent field evaluation, absent before discontinuation" ], "echoes": [ { "date": null, "setting": "Nationwide use in Spain (2019)", "model_version": null, "outcome": "unknown", "source": "AlgorithmWatch and Civio: 49,702 complaints analyzed, 2,338 flagged false, no verification" }, { "date": null, "setting": "Spain (2022)", "model_version": null, "outcome": "unknown", "source": "Civio: 3,762 complaints analyzed, 511 deemed false" }, { "date": "2024-10-21", "setting": "Spanish National Police", "model_version": null, "outcome": "did not recur", "source": "Civio: use stopped; Ministry said the tool is not valid in judicial proceedings" } ] }, "paired_incident": null, "headline": "VeriPol flags 25 and 39 false robberies in Murcia and Málaga", "metric": "25 and 39 false robberies respectively, against 3 and 12 in the same month", "comparator": { "against": "false robbery reports detected by officers in the same month over the previous decade", "before": "only three and 12, respectively, for that month in the previous decade", "after": "25 and 39 false robberies in just one week", "basis": "measured", "quote": "A June 2017 pilot test in the cities of Murcia and Málaga helped to detect 25 and 39 false robberies in just one week—compared with only three and 12, respectively, for that month in the previous decade.", "url": "https://www.scientificamerican.com/article/an-algorithm-that-can-spot-when-people-lie-to-the-police/" }, "later": { "status": "withdrawn", "date": "2025-03-25", "note": "Civio reported that the National Police stopped using VeriPol in October 2024 (day not given) because, the Interior Ministry said, it lacks validity in judicial proceedings.", "quote": "In October 2024, six years later, the National Police stopped using the AI, the Technical Office of the Directorate General of Police has told Civio. The Ministry of the Interior stated that the reason for rejecting its use is that it lacks validity in judicial proceedings.", "url": "https://civio.es/transparencia/2025/03/25/national-police-stop-using-veripol-its-star-ai-for-detecting-false-reports/" }, "value": null, "developer_country": "Spain", "deployer_country": "Spain", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.scientificamerican.com/article/an-algorithm-that-can-spot-when-people-lie-to-the-police/; https://civio.es/transparencia/2025/03/25/national-police-stop-using-veripol-its-star-ai-for-detecting-false-reports/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Complutense_University_of_Madrid; https://en.wikipedia.org/wiki/National_Police_Corps", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Universidad Complutense de Madrid.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports and the makers' peer-reviewed study. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0177", "catalog_version": "1.0.0", "source_fingerprint": "03c957adc9b192826a00207cfd3523773ec6ef14a555b8d1cfc6d40490a512d5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0177-source-0001", "AIBD-0177-source-0002", "AIBD-0177-source-0003", "AIBD-0177-source-0004", "AIBD-0177-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Universidad Complutense de Madrid and Universidad Carlos III de Madrid, with Spanish National Police officer Miguel Camacho-Collados", "deployer": "Spanish National Police (Policía Nacional), Ministry of the Interior" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The peer-reviewed paper describes a natural-language-processing and machine-learning classifier with L1 feature selection that outputs the probability a report is false. The paper's authors include the police developer. AlgorithmWatch and Civio report that no independent verification was done before the police stopped using it in October 2024." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The peer-reviewed paper describes a natural-language-processing and machine-learning classifier with L1 feature selection that outputs the probability a report is false. The paper's authors include the police developer. 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It appeared in Knowledge-Based Systems (Quijano-Sánchez, Liberatore, Camacho-Collados and Camacho-Collados, 2018). The abstract reports a validation accuracy of 91% on more than 1,000 reports from 2015, an improvement of more than 15% over expert officers. It reports a pilot study in June 2017 showing a lower bound on empirical precision of about 83%. Scientific American (1 February 2019) reported that the one-week pilot in Murcia and Málaga detected 25 and 39 false robberies respectively. The same month over the previous decade had 3 and 12. It quoted Camacho Collados on colleagues wasting time on cases that never occurred. Civio (25 March 2025) reported that the police said that in 83.54% of reports flagged false the complainant confessed. It also reported the Interior Ministry's 2018 announcement of nationwide use. Complaints analyzed were 49,702 in 2019 with 2,338 deemed false, and 3,762 in 2022 with 511 deemed false. Use stopped on 21 October 2024 because the tool was not valid in judicial proceedings, it said. A University of Valencia report (September 2024) criticized the 1,122-report training sample, missing officer training and regional language variation. AlgorithmWatch (27 October 2020) found no independent verification of effectiveness since deployment. 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It appeared in Knowledge-Based Systems (Quijano-Sánchez, Liberatore, Camacho-Collados and Camacho-Collados, 2018). The abstract reports a validation accuracy of 91% on more than 1,000 reports from 2015, an improvement of more than 15% over expert officers. It reports a pilot study in June 2017 showing a lower bound on empirical precision of about 83%. Scientific American (1 February 2019) reported that the one-week pilot in Murcia and Málaga detected 25 and 39 false robberies respectively. The same month over the previous decade had 3 and 12. It quoted Camacho Collados on colleagues wasting time on cases that never occurred. Civio (25 March 2025) reported that the police said that in 83.54% of reports flagged false the complainant confessed. It also reported the Interior Ministry's 2018 announcement of nationwide use. Complaints analyzed were 49,702 in 2019 with 2,338 deemed false, and 3,762 in 2022 with 511 deemed false. Use stopped on 21 October 2024 because the tool was not valid in judicial proceedings, it said. A University of Valencia report (September 2024) criticized the 1,122-report training sample, missing officer training and regional language variation. AlgorithmWatch (27 October 2020) found no independent verification of effectiveness since deployment. The pilot month carries no day.", "replication": { "produced_by": [ "Training on 1,122 robbery reports from 2015 (534 genuine, 588 false) labeled by one experienced officer", "Text features selected by L1 penalization plus heuristic rules, scoring reports at the police station" ], "must_hold": [ "Reports written in the same language register as the training data (the Valencia report faulted missing regional variation)", "Officer training and protocols for acting on scores", "Independent field evaluation, absent before discontinuation" ], "echoes": [ { "setting": "Nationwide use in Spain (2019)", "outcome": "unknown", "source": "AlgorithmWatch and Civio: 49,702 complaints analyzed, 2,338 flagged false, no verification" }, { "setting": "Spain (2022)", "outcome": "unknown", "source": "Civio: 3,762 complaints analyzed, 511 deemed false" }, { "date": "2024-10-21", "setting": "Spanish National Police", "outcome": "did not recur", "source": "Civio: use stopped; Ministry said the tool is not valid in judicial proceedings" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0295", "title": "Dexcom G6's “Urgent Low Soon” predictive alert may cut time below 54 mg/dL, by less in controlled trials", "summary": "Dexcom-authored analyzes (1,424 and 15,000 users) link the 20-minute predictive low alert to less hypoglycemia; an independent 24-person crossover RCT found a reduction only below 2.8 mmol/L.", "date_observed": "2019-03-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Dexcom G6 continuous glucose monitor was classified by the Food and Drug Administration (FDA) under De Novo DEN170088 on 27 March 2018. Its “Urgent Low Soon” (ULS) alert fires when an algorithm predicts an estimated glucose value of 55 mg/dL or below within 20 minutes. Dexcom employees Puhr, Derdzinski, Welsh, Parker, Walker and Price compared 1,424 users before and after moving from the G5 (no predictive alert) to the G6. Their anonymized comparison was in Diabetes Technology & Therapeutics (online 22 March 2019). With a 70 mg/dL low-threshold setting (n=658) time below 54 mg/dL fell from 1.0% to 0.6%. With an 80 mg/dL setting (n=766) it fell 0.6% to 0.4% (both P<0.001). ULS fired 0.9 and 0.6 times a day. A second Dexcom analysis (Puhr et al., Journal of Diabetes Science and Technology, online 3 April 2019; abstract only) had 15,000 G6 app users. More than 93% had ULS enabled. Its use was associated with less time below 55 and 70 mg/dL regardless of how often users viewed the app. The FDA decision summary describes the threshold and predictive alerts as intended to warn patients to act before a hypoglycemic event. Independent evidence is thinner. The PACE crossover randomized trial at Imperial College Healthcare NHS Trust had 24 adults with type 1 diabetes. Each had ULS on or off for 40 days. It found no difference in hypoglycemia below 3.0 or 3.9 mmol/L in the 24 hours after exercise. Time below 2.8 mmol/L was lower with ULS on (P=0.04). Preechasuk et al. (Imperial College London) had 29 adults who switched from FreeStyle Libre 2 to a Dexcom G7 with ULS. They spent less time below 70 mg/dL (3.0% to 2.0%, P=0.006). That changes device and alert together. A Prague case report records a patient with impaired hypoglycemia awareness whose CGM with ULS on did not eliminate prolonged hypoglycemia. He sometimes muted the alerts. None of the sources calls the predictive algorithm machine learning.", "category": "general benefit", "unexpected": false, "purpose": "Built to warn users 20 minutes before predicted serious hypoglycemia so they can act. The reported reductions in time below 54–55 mg/dL are that purpose.", "system": "Dexcom G6 real-time continuous glucose monitoring system, 'Urgent Low Soon' predictive low glucose alert (also present on the G7 in one independent study)", "model_version": "Dexcom G6 (vendor analyses; PACE trial); Dexcom G7 (Preechasuk et al.)", "developer": "Dexcom, Inc.", "deployer": null, "location": "United States (vendor analyzes); London, United Kingdom (independent trials)", "domain": "Healthcare (diabetes technology)", "segment": "Diabetes technology", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Reductions in time below 54–55 mg/dL are reported for user populations, mostly in Dexcom's own analyses. No individual event with a changed outcome is documented. The one independent case report found ULS alone insufficient." }, { "group": "organizational", "depth": null, "reason": "No payer, clinic or health-system outcome is reported in the sources." } ], "ai_role": { "status": "assessed", "statement": "The alert is generated when the G6 algorithm forecasts glucose at or below 55 mg/dL within 20 minutes. Users still have to act on it. The principal outcome evidence is the maker's own real-world analyses (Puhr et al. 2019, 2020). They compare the same users before and after the G6 transition without a control arm. The independent Imperial College PACE randomized trial found no difference at 3.0 or 3.9 mmol/L after exercise and a difference only below 2.8 mmol/L. The Imperial switch study cannot separate the alert from the change of device. None of the sources describes the prediction method as machine learning." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Puhr S, Derdzinski M, Welsh JB, Parker AS, Walker T, Price DA (2019). Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert. Diabetes Technology & Therapeutics 21(4):155-158 (PMC6477579). All authors at Dexcom, Inc.", "title": "Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "date": "2019-03-22", "written_by": "makers", "quote": "includes a new alert that is triggered when an algorithm predicts that an estimated glucose value ≤55 mg/dL will occur within 20 min" }, { "kind": "peer-reviewed study", "citation": "Puhr et al. (2019), Diabetes Technol Ther 21(4):155-158, results.", "title": "Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "date": "2019-03-22", "written_by": "makers", "quote": "Percent time <54, ≤55, <70, and >250 mg/dL fell significantly after the transition to G6, independent of low threshold alert setting." }, { "kind": "peer-reviewed study", "citation": "Puhr S, Derdzinski M, Parker AS, Welsh JB, Price DA (2020). Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views. Journal of Diabetes Science and Technology 14(1) (online 3 April 2019; PMC7189147). All authors at Dexcom, Inc.", "title": "Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7189147/", "date": "2019-04-03", "written_by": "makers", "quote": "Over 93% of users enabled the ULS alert; its use was associated with significantly reduced hypoglycemia <55 and <70 mg/dL, independent of screen view frequency." }, { "kind": "regulatory document", "citation": "U.S. Food and Drug Administration (2018). Evaluation of Automatic Class III Designation for Dexcom G6 Continuous Glucose Monitoring System, Decision Summary, DEN170088 (decision date 27 March 2018).", "title": "De Novo DEN170088 Decision Summary: Dexcom G6 Continuous Glucose Monitoring System", "url": "https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN170088.pdf", "date": "2018-03-27", "written_by": "independent", "quote": "An adjustable threshold and predictive glucose alert at 55 mg/dL are intended to warn patients that they need to take action", "supports_benefit": false }, { "kind": "peer-reviewed study", "citation": "Rilstone S, Oliver N, Godsland I, Tanushi B, Thomas M, Hill N (2024). A Randomized Controlled Trial Assessing the Impact of Continuous Glucose Monitoring with a Predictive Hypoglycemia Alert Function on Hypoglycemia in Physical Activity for People with Type 1 Diabetes (PACE). Diabetes Technology & Therapeutics 26(2); doi:10.1089/dia.2023.0376.", "title": "A Randomized Controlled Trial Assessing the Impact of Continuous Glucose Monitoring with a Predictive Hypoglycemia Alert Function on Hypoglycemia in Physical Activity for People with Type 1 Diabetes (PACE)", "url": "https://doi.org/10.1089/dia.2023.0376", "date": "2023-11-27", "written_by": "independent", "quote": "There was no difference in change from baseline of hypoglycemia <3.0 and <3.9 mmol/L with the ULS on or off during the 24 h after exercise." }, { "kind": "peer-reviewed study", "citation": "Preechasuk L, Avari P, Oliver N, Reddy M (2024). Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia. Diabetes Technology & Therapeutics 26(7); doi:10.1089/dia.2023.0434.", "title": "Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia", "url": "https://doi.org/10.1089/dia.2023.0434", "date": "2024-04-09", "written_by": "independent", "quote": "After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006)" } ], "replication": { "produced_by": [ "Real-time CGM with the ULS alert enabled (over 93% of G6 app users in Dexcom's sample)", "Users who respond to the alert by treating or adjusting insulin, which the sources assume rather than measure", "A low-threshold alert also set (70 or 80 mg/dL in the Dexcom analysis)" ], "must_hold": [ "Users keep the alert on rather than muting it for alarm fatigue, as the Prague patient sometimes did", "Sensor accuracy sufficient to avoid nuisance alerts, which Puhr et al. cite as a cause of CGM discontinuation", "Benefit beyond a plain threshold alert, which the PACE trial found only below 2.8 mmol/L" ], "echoes": [ { "date": "2023-11-27", "setting": "PACE crossover randomized trial, Imperial College Healthcare NHS Trust, 24 adults with type 1 diabetes, ULS on versus off for 40 days each around regular exercise", "model_version": "Dexcom G6", "outcome": "recurred", "source": "Rilstone et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0376 (significant only for time below 2.8 mmol/L)" }, { "date": "2024-04-09", "setting": "Imperial College London, 29 adults with type 1 diabetes switched from FreeStyle Libre 2 to Dexcom G7 with ULS for 12 weeks", "model_version": "Dexcom G7", "outcome": "recurred", "source": "Preechasuk et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0434 (device and alert changed together)" }, { "date": "2025-02-21", "setting": "Case report, General University Hospital Prague: a 45-year-old man with impaired hypoglycemia awareness used CGM with ULS on during 2020", "model_version": null, "outcome": "did not recur", "source": "Zadáková E, Horová E (2025) Front Clin Diabetes Healthc 6:1536038, https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/ (quote: 'prolonged hypoglycemia could not be eliminated during 2020, especially after physical activity. The patient admitted that he occasionally had to turn off or mute the alerts')" } ] }, "paired_incident": null, "headline": "Dexcom G6's Urgent Low Soon alert may cut time below 54 mg/dL", "metric": "time below 54 mg/dL fell from 1.0% to 0.6%", "comparator": { "against": "the same users on the preceding Dexcom G5 system, which had no predictive alert (before-and-after)", "before": "1.0 (1.5) percent of time <54 mg/dL on G5 (70 mg/dL low-alert setting, Table 1)", "after": "0.6 (1.0) percent of time <54 mg/dL on G6 (70 mg/dL low-alert setting, Table 1)", "basis": "measured", "quote": "Percent time <54, ≤55, <70, and >250 mg/dL fell significantly after the transition to G6, independent of low threshold alert setting. Time in range improved for G6 users with a low threshold alert setting of 70 mg/dL.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/" }, "later": null, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Dexcom", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent regulatory document, two independent peer-reviewed studies and two peer-reviewed studies from the makers. For the benefit itself, the cited sources include no finding by a regulator or court.", "profile": { "case_id": "AIBD-0295", "catalog_version": "1.0.0", "source_fingerprint": "a22b940e01e867889b7fa5921506d0d0cd267ddfe3653c464b81e87b76a1a6f2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0295-source-0001", "AIBD-0295-source-0002", "AIBD-0295-source-0003", "AIBD-0295-source-0004", "AIBD-0295-source-0005", "AIBD-0295-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Dexcom, Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The alert is generated when the G6 algorithm forecasts glucose at or below 55 mg/dL within 20 minutes. Users still have to act on it. The principal outcome evidence is the maker's own real-world analyses (Puhr et al. 2019, 2020). They compare the same users before and after the G6 transition without a control arm. The independent Imperial College PACE randomized trial found no difference at 3.0 or 3.9 mmol/L after exercise and a difference only below 2.8 mmol/L. The Imperial switch study cannot separate the alert from the change of device. None of the sources describes the prediction method as machine learning." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The alert is generated when the G6 algorithm forecasts glucose at or below 55 mg/dL within 20 minutes. Users still have to act on it. The principal outcome evidence is the maker's own real-world analyses (Puhr et al. 2019, 2020). They compare the same users before and after the G6 transition without a control arm. The independent Imperial College PACE randomized trial found no difference at 3.0 or 3.9 mmol/L after exercise and a difference only below 2.8 mmol/L. The Imperial switch study cannot separate the alert from the change of device. None of the sources describes the prediction method as machine learning." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent regulatory document, two independent peer-reviewed studies and two peer-reviewed studies from the makers. For the benefit itself, the cited sources include no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Reductions in time below 54–55 mg/dL are reported for user populations, mostly in Dexcom's own analyses. No individual event with a changed outcome is documented. The one independent case report found ULS alone insufficient." }, { "group": "organizational", "reason": "No payer, clinic or health-system outcome is reported in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Reductions in time below 54–55 mg/dL are reported for user populations, mostly in Dexcom's own analyses. No individual event with a changed outcome is documented. The one independent case report found ULS alone insufficient." }, { "group": "organizational", "reason": "No payer, clinic or health-system outcome is reported in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", 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"deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"evaluations", "display": { "answer": "time below 54 mg/dL fell from 1.0% to 0.6%", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0295" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Dexcom G6 continuous glucose monitor was classified by the Food and Drug Administration (FDA) under De Novo DEN170088 on 27 March 2018. Its “Urgent Low Soon” (ULS) alert fires when an algorithm predicts an estimated glucose value of 55 mg/dL or below within 20 minutes. Dexcom employees Puhr, Derdzinski, Welsh, Parker, Walker and Price compared 1,424 users before and after moving from the G5 (no predictive alert) to the G6. Their anonymized comparison was in Diabetes Technology & Therapeutics (online 22 March 2019). With a 70 mg/dL low-threshold setting (n=658) time below 54 mg/dL fell from 1.0% to 0.6%. With an 80 mg/dL setting (n=766) it fell 0.6% to 0.4% (both P<0.001). ULS fired 0.9 and 0.6 times a day. A second Dexcom analysis (Puhr et al., Journal of Diabetes Science and Technology, online 3 April 2019; abstract only) had 15,000 G6 app users. More than 93% had ULS enabled. Its use was associated with less time below 55 and 70 mg/dL regardless of how often users viewed the app. The FDA decision summary describes the threshold and predictive alerts as intended to warn patients to act before a hypoglycemic event. Independent evidence is thinner. The PACE crossover randomized trial at Imperial College Healthcare NHS Trust had 24 adults with type 1 diabetes. Each had ULS on or off for 40 days. It found no difference in hypoglycemia below 3.0 or 3.9 mmol/L in the 24 hours after exercise. Time below 2.8 mmol/L was lower with ULS on (P=0.04). Preechasuk et al. (Imperial College London) had 29 adults who switched from FreeStyle Libre 2 to a Dexcom G7 with ULS. They spent less time below 70 mg/dL (3.0% to 2.0%, P=0.006). That changes device and alert together. A Prague case report records a patient with impaired hypoglycemia awareness whose CGM with ULS on did not eliminate prolonged hypoglycemia. He sometimes muted the alerts. None of the sources calls the predictive algorithm machine learning.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Reductions in time below 54–55 mg/dL are reported for user populations, mostly in Dexcom's own analyses. No individual event with a changed outcome is documented. The one independent case report found ULS alone insufficient." }, { "group": "organizational", "reason": "No payer, clinic or health-system outcome is reported in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to warn users 20 minutes before predicted serious hypoglycemia so they can act. The reported reductions in time below 54–55 mg/dL are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United States (vendor analyzes); London, United Kingdom (independent trials)", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to warn users 20 minutes before predicted serious hypoglycemia so they can act. The reported reductions in time below 54–55 mg/dL are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-03-22", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Dexcom", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Real-time CGM with the ULS alert enabled (over 93% of G6 app users in Dexcom's sample)", "Users who respond to the alert by treating or adjusting insulin, which the sources assume rather than measure", "A low-threshold alert also set (70 or 80 mg/dL in the Dexcom analysis)" ], "must_hold": [ "Users keep the alert on rather than muting it for alarm fatigue, as the Prague patient sometimes did", "Sensor accuracy sufficient to avoid nuisance alerts, which Puhr et al. cite as a cause of CGM discontinuation", "Benefit beyond a plain threshold alert, which the PACE trial found only below 2.8 mmol/L" ], "echoes": [ { "date": "2023-11-27", "setting": "PACE crossover randomized trial, Imperial College Healthcare NHS Trust, 24 adults with type 1 diabetes, ULS on versus off for 40 days each around regular exercise", "model_version": "Dexcom G6", "outcome": "recurred", "source": "Rilstone et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0376 (significant only for time below 2.8 mmol/L)" }, { "date": "2024-04-09", "setting": "Imperial College London, 29 adults with type 1 diabetes switched from FreeStyle Libre 2 to Dexcom G7 with ULS for 12 weeks", "model_version": "Dexcom G7", "outcome": "recurred", "source": "Preechasuk et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0434 (device and alert changed together)" }, { "date": "2025-02-21", "setting": "Case report, General University Hospital Prague: a 45-year-old man with impaired hypoglycemia awareness used CGM with ULS on during 2020", "outcome": "did not recur", "source": "Zadáková E, Horová E (2025) Front Clin Diabetes Healthc 6:1536038, https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/ (quote: 'prolonged hypoglycemia could not be eliminated during 2020, especially after physical activity. The patient admitted that he occasionally had to turn off or mute the alerts')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Real-time CGM with the ULS alert enabled (over 93% of G6 app users in Dexcom's sample)", "Users who respond to the alert by treating or adjusting insulin, which the sources assume rather than measure", "A low-threshold alert also set (70 or 80 mg/dL in the Dexcom analysis)" ], "must_hold": [ "Users keep the alert on rather than muting it for alarm fatigue, as the Prague patient sometimes did", "Sensor accuracy sufficient to avoid nuisance alerts, which Puhr et al. cite as a cause of CGM discontinuation", "Benefit beyond a plain threshold alert, which the PACE trial found only below 2.8 mmol/L" ], "echoes": [ { "date": "2023-11-27", "setting": "PACE crossover randomized trial, Imperial College Healthcare NHS Trust, 24 adults with type 1 diabetes, ULS on versus off for 40 days each around regular exercise", "model_version": "Dexcom G6", "outcome": "recurred", "source": "Rilstone et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0376 (significant only for time below 2.8 mmol/L)" }, { "date": "2024-04-09", "setting": "Imperial College London, 29 adults with type 1 diabetes switched from FreeStyle Libre 2 to Dexcom G7 with ULS for 12 weeks", "model_version": "Dexcom G7", "outcome": "recurred", "source": "Preechasuk et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0434 (device and alert changed together)" }, { "date": "2025-02-21", "setting": "Case report, General University Hospital Prague: a 45-year-old man with impaired hypoglycemia awareness used CGM with ULS on during 2020", "outcome": "did not recur", "source": "Zadáková E, Horová E (2025) Front Clin Diabetes Healthc 6:1536038, https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/ (quote: 'prolonged hypoglycemia could not be eliminated during 2020, especially after physical activity. The patient admitted that he occasionally had to turn off or mute the alerts')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Dexcom", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (diabetes technology)", "segment": "Diabetes technology" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Puhr S, Derdzinski M, Welsh JB, Parker AS, Walker T, Price DA (2019). Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert. Diabetes Technology & Therapeutics 21(4):155-158 (PMC6477579). All authors at Dexcom, Inc.", "title": "Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "date": "2019-03-22", "written_by": "makers", "quote": "includes a new alert that is triggered when an algorithm predicts that an estimated glucose value ≤55 mg/dL will occur within 20 min" }, { "kind": "peer-reviewed study", "citation": "Puhr et al. (2019), Diabetes Technol Ther 21(4):155-158, results.", "title": "Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC6477579/", "date": "2019-03-22", "written_by": "makers", "quote": "Percent time <54, ≤55, <70, and >250 mg/dL fell significantly after the transition to G6, independent of low threshold alert setting." }, { "kind": "peer-reviewed study", "citation": "Puhr S, Derdzinski M, Parker AS, Welsh JB, Price DA (2020). Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views. Journal of Diabetes Science and Technology 14(1) (online 3 April 2019; PMC7189147). All authors at Dexcom, Inc.", "title": "Real-World Hypoglycemia Avoidance With a Predictive Low Glucose Alert Does Not Depend on Frequent Screen Views", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7189147/", "date": "2019-04-03", "written_by": "makers", "quote": "Over 93% of users enabled the ULS alert; its use was associated with significantly reduced hypoglycemia <55 and <70 mg/dL, independent of screen view frequency." }, { "kind": "regulatory document", "citation": "U.S. Food and Drug Administration (2018). Evaluation of Automatic Class III Designation for Dexcom G6 Continuous Glucose Monitoring System, Decision Summary, DEN170088 (decision date 27 March 2018).", "title": "De Novo DEN170088 Decision Summary: Dexcom G6 Continuous Glucose Monitoring System", "url": "https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN170088.pdf", "date": "2018-03-27", "written_by": "independent", "quote": "An adjustable threshold and predictive glucose alert at 55 mg/dL are intended to warn patients that they need to take action", "supports_benefit": false }, { "kind": "peer-reviewed study", "citation": "Rilstone S, Oliver N, Godsland I, Tanushi B, Thomas M, Hill N (2024). A Randomized Controlled Trial Assessing the Impact of Continuous Glucose Monitoring with a Predictive Hypoglycemia Alert Function on Hypoglycemia in Physical Activity for People with Type 1 Diabetes (PACE). Diabetes Technology & Therapeutics 26(2); doi:10.1089/dia.2023.0376.", "title": "A Randomized Controlled Trial Assessing the Impact of Continuous Glucose Monitoring with a Predictive Hypoglycemia Alert Function on Hypoglycemia in Physical Activity for People with Type 1 Diabetes (PACE)", "url": "https://doi.org/10.1089/dia.2023.0376", "date": "2023-11-27", "written_by": "independent", "quote": "There was no difference in change from baseline of hypoglycemia <3.0 and <3.9 mmol/L with the ULS on or off during the 24 h after exercise." }, { "kind": "peer-reviewed study", "citation": "Preechasuk L, Avari P, Oliver N, Reddy M (2024). Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia. Diabetes Technology & Therapeutics 26(7); doi:10.1089/dia.2023.0434.", "title": "Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia", "url": "https://doi.org/10.1089/dia.2023.0434", "date": "2024-04-09", "written_by": "independent", "quote": "After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0295-source-0001", "AIBD-0295-source-0002", "AIBD-0295-source-0003", "AIBD-0295-source-0004", "AIBD-0295-source-0005", "AIBD-0295-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "FDA cleared the G6 after reviewing its performance. The later studies assess hypoglycemia. The controlled PACE trial found no difference on its primary comparison and a benefit on a secondary measure." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0295-source-0004", "AIBD-0295-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "FDA cleared the G6 after reviewing its performance. The later studies assess hypoglycemia. The controlled PACE trial found no difference on its primary comparison and a benefit on a secondary measure." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0295-source-0001", "retained_source_order": [ "AIBD-0295-source-0001", "AIBD-0295-source-0002", "AIBD-0295-source-0003", "AIBD-0295-source-0004", "AIBD-0295-source-0005", "AIBD-0295-source-0006" ], "origins": [ { "url": "https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN170088.pdf", "locator": "§ L(3), pp. 13–14; §§ S–T, pp. 38–39.", "contribution": "Sensor-performance evidence, the alert’s intended function, and the clearance decision.", "relationship": "FDA’s regulatory review predates the outcome studies.", "source_refs": [ "AIBD-0295-source-0004" ] }, { "url": "https://journals.sagepub.com/doi/10.1089/dia.2023.0376", "locator": "Study design, Results, and Discussion.", "contribution": "A controlled comparison of alerts on and off; the primary hypoglycemia comparison was null, with a favorable secondary result.", "relationship": "Original randomized study; distinct from clearance.", "source_refs": [ "AIBD-0295-source-0005" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0295-source-0004", "AIBD-0295-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "FDA cleared the G6 after reviewing its performance. The later studies assess hypoglycemia. The controlled PACE trial found no difference on its primary comparison and a benefit on a secondary measure." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Dexcom-authored analyzes (1,424 and 15,000 users) link the 20-minute predictive low alert to less hypoglycemia; an independent 24-person crossover RCT found a reduction only below 2.8 mmol/L.", "account": "The Dexcom G6 continuous glucose monitor was classified by the Food and Drug Administration (FDA) under De Novo DEN170088 on 27 March 2018. Its “Urgent Low Soon” (ULS) alert fires when an algorithm predicts an estimated glucose value of 55 mg/dL or below within 20 minutes. Dexcom employees Puhr, Derdzinski, Welsh, Parker, Walker and Price compared 1,424 users before and after moving from the G5 (no predictive alert) to the G6. Their anonymized comparison was in Diabetes Technology & Therapeutics (online 22 March 2019). With a 70 mg/dL low-threshold setting (n=658) time below 54 mg/dL fell from 1.0% to 0.6%. With an 80 mg/dL setting (n=766) it fell 0.6% to 0.4% (both P<0.001). ULS fired 0.9 and 0.6 times a day. A second Dexcom analysis (Puhr et al., Journal of Diabetes Science and Technology, online 3 April 2019; abstract only) had 15,000 G6 app users. More than 93% had ULS enabled. Its use was associated with less time below 55 and 70 mg/dL regardless of how often users viewed the app. The FDA decision summary describes the threshold and predictive alerts as intended to warn patients to act before a hypoglycemic event. Independent evidence is thinner. The PACE crossover randomized trial at Imperial College Healthcare NHS Trust had 24 adults with type 1 diabetes. Each had ULS on or off for 40 days. It found no difference in hypoglycemia below 3.0 or 3.9 mmol/L in the 24 hours after exercise. Time below 2.8 mmol/L was lower with ULS on (P=0.04). Preechasuk et al. (Imperial College London) had 29 adults who switched from FreeStyle Libre 2 to a Dexcom G7 with ULS. They spent less time below 70 mg/dL (3.0% to 2.0%, P=0.006). That changes device and alert together. A Prague case report records a patient with impaired hypoglycemia awareness whose CGM with ULS on did not eliminate prolonged hypoglycemia. He sometimes muted the alerts. None of the sources calls the predictive algorithm machine learning." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The vendor analyses and PACE trial used Dexcom G6 devices. The Preechasuk study used Dexcom G7 devices." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Dexcom G6 (vendor analyses; PACE trial); Dexcom G7 (Preechasuk et al.)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Dexcom G6 real-time continuous glucose monitoring system, 'Urgent Low Soon' predictive low glucose alert (also present on the G7 in one independent study)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Dexcom, Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Dexcom G6's “Urgent Low Soon” predictive alert may cut time below 54 mg/dL, by less in controlled trials", "headline": "Dexcom G6's Urgent Low Soon alert may cut time below 54 mg/dL" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a22b940e01e867889b7fa5921506d0d0cd267ddfe3653c464b81e87b76a1a6f2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Dexcom G6 continuous glucose monitor was classified by the Food and Drug Administration (FDA) under De Novo DEN170088 on 27 March 2018. Its “Urgent Low Soon” (ULS) alert fires when an algorithm predicts an estimated glucose value of 55 mg/dL or below within 20 minutes. Dexcom employees Puhr, Derdzinski, Welsh, Parker, Walker and Price compared 1,424 users before and after moving from the G5 (no predictive alert) to the G6. Their anonymized comparison was in Diabetes Technology & Therapeutics (online 22 March 2019). With a 70 mg/dL low-threshold setting (n=658) time below 54 mg/dL fell from 1.0% to 0.6%. With an 80 mg/dL setting (n=766) it fell 0.6% to 0.4% (both P<0.001). ULS fired 0.9 and 0.6 times a day. A second Dexcom analysis (Puhr et al., Journal of Diabetes Science and Technology, online 3 April 2019; abstract only) had 15,000 G6 app users. More than 93% had ULS enabled. Its use was associated with less time below 55 and 70 mg/dL regardless of how often users viewed the app. The FDA decision summary describes the threshold and predictive alerts as intended to warn patients to act before a hypoglycemic event. Independent evidence is thinner. The PACE crossover randomized trial at Imperial College Healthcare NHS Trust had 24 adults with type 1 diabetes. Each had ULS on or off for 40 days. It found no difference in hypoglycemia below 3.0 or 3.9 mmol/L in the 24 hours after exercise. Time below 2.8 mmol/L was lower with ULS on (P=0.04). Preechasuk et al. (Imperial College London) had 29 adults who switched from FreeStyle Libre 2 to a Dexcom G7 with ULS. They spent less time below 70 mg/dL (3.0% to 2.0%, P=0.006). That changes device and alert together. A Prague case report records a patient with impaired hypoglycemia awareness whose CGM with ULS on did not eliminate prolonged hypoglycemia. He sometimes muted the alerts. None of the sources calls the predictive algorithm machine learning.", "replication": { "produced_by": [ "Real-time CGM with the ULS alert enabled (over 93% of G6 app users in Dexcom's sample)", "Users who respond to the alert by treating or adjusting insulin, which the sources assume rather than measure", "A low-threshold alert also set (70 or 80 mg/dL in the Dexcom analysis)" ], "must_hold": [ "Users keep the alert on rather than muting it for alarm fatigue, as the Prague patient sometimes did", "Sensor accuracy sufficient to avoid nuisance alerts, which Puhr et al. cite as a cause of CGM discontinuation", "Benefit beyond a plain threshold alert, which the PACE trial found only below 2.8 mmol/L" ], "echoes": [ { "date": "2023-11-27", "setting": "PACE crossover randomized trial, Imperial College Healthcare NHS Trust, 24 adults with type 1 diabetes, ULS on versus off for 40 days each around regular exercise", "model_version": "Dexcom G6", "outcome": "recurred", "source": "Rilstone et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0376 (significant only for time below 2.8 mmol/L)" }, { "date": "2024-04-09", "setting": "Imperial College London, 29 adults with type 1 diabetes switched from FreeStyle Libre 2 to Dexcom G7 with ULS for 12 weeks", "model_version": "Dexcom G7", "outcome": "recurred", "source": "Preechasuk et al. (2024) Diabetes Technol Ther, doi:10.1089/dia.2023.0434 (device and alert changed together)" }, { "date": "2025-02-21", "setting": "Case report, General University Hospital Prague: a 45-year-old man with impaired hypoglycemia awareness used CGM with ULS on during 2020", "outcome": "did not recur", "source": "Zadáková E, Horová E (2025) Front Clin Diabetes Healthc 6:1536038, https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/ (quote: 'prolonged hypoglycemia could not be eliminated during 2020, especially after physical activity. The patient admitted that he occasionally had to turn off or mute the alerts')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 2, "record_mapped": 28, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0021", "title": "Apple Watch heart-rate, irregular-rhythm and ECG alerts leading to arrhythmia diagnosis and treatment", "summary": "Apple Watch heart-rate alarms led to an ECG-confirmed AF diagnosis and anticoagulation (UK, 2019); 16 echoes from 15 published case reports to 2026.", "date_observed": "2019-03-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In a case report of 29 March 2019 (event date not reported), a 59-year-old woman attended a United Kingdom emergency department. The acute medicine service saw her (the report does not name the hospital; the author is at Ipswich Hospital). She attended because her Apple Watch Series 2 had alarmed several times overnight that her pulse exceeded 120 bpm while she was inactive. A transient ischemic attack had occurred two months earlier. An electrocardiogram (ECG) showed atrial fibrillation with a fast ventricular response. She started bisoprolol and a direct oral anticoagulant, and clopidogrel was stopped. Later case reports describe the watch's heart-rate alerts, irregular-rhythm notification or ECG app leading to confirmed atrial flutter, supraventricular and ventricular tachycardia and heart block. Treatment was by cardioversion, ablation, pacemaker or defibrillator.", "category": "benefit created", "unexpected": false, "purpose": "Apple Watch high/low heart-rate notifications, the Irregular Rhythm Notification and the ECG app are built to flag possible arrhythmias so the wearer seeks medical review. This benefit was that purpose.", "system": "Apple Watch heart-rate notifications, Irregular Rhythm Notification and ECG app", "model_version": "Apple Watch Series 2 (event); echoes name Series 3, 4, 5, 6 and Ultra; eight reports do not state the model, and in Ahmed et al. the alerting tracker is unnamed (the Series 5 was the authors' post-diagnosis device)", "developer": "Apple", "deployer": null, "location": "United Kingdom", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "One woman with a recent TIA received an ECG-confirmed AF diagnosis, rate control and anticoagulation. A material benefit to one person. Several echoes (VT ablation with defibrillator, pacemaker for heart block) are deeper but are not the event." } ], "ai_role": { "status": "assessed", "statement": "The watch's heart-rate algorithm generated the overnight alarms that brought the patient to hospital. Clinicians made the diagnosis on an ECG and chose treatment. In the echoes the notification or the ECG app's single-lead trace likewise triggered evaluation, with clinicians confirming the rhythm." }, "evidence": [ { "kind": "case report", "citation": "Weichert I (2019). 'My watch kept on alarming all night about my heart rate': diagnosis of asymptomatic atrial fibrillation with fast ventricular response in a patient with a recent TIA as the result of a smartwatch alarm. Oxford Medical Case Reports 2019(3):omz014.", "title": "'My watch kept on alarming all night about my heart rate'", "url": "https://europepmc.org/article/PMC/PMC6440268", "date": "2019-03-29", "written_by": "independent", "quote": "Her smartwatch had alarmed several times during the preceding night that her pulse rate exceeded 120 beats per minute (bpm) whilst she was inactive" }, { "kind": "peer-reviewed study", "citation": "Bogár B, Pető D, Sipos D, Füredi G, Keszthelyi A, Betlehem J, Pandur AA (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "In most cases (n = 30), the Apple Watch was used, while Samsung Galaxy Fit was used for arrhythmia registration in one patient." }, { "kind": "case report", "citation": "Overbeek DL, Hogikyan EM, Davis M, McGillicuddy DC (2019). A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block. American Journal of Emergency Medicine 37(10):1989.e5-e7.", "title": "A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block", "url": "https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747", "date": "2019-07-21", "written_by": "independent", "quote": "A previously-healthy mid 60s-year-old-woman presented to the Emergency Department (ED) stating that her 'Apple Watch' wearable device was alarming due to a low heart rate." }, { "kind": "case report", "citation": "Yerasi C, O'Donoghue S, Satler LF, Waksman R (2020). Apple Watch detecting high-grade block after transcatheter aortic valve implantation. European Heart Journal 41(10):1096.", "title": "Apple Watch detecting high-grade block after transcatheter aortic valve implantation", "url": "https://academic.oup.com/eurheartj/article/41/10/1096/5651110", "date": "2019-12-03", "written_by": "independent", "quote": "He subsequently underwent urgent biventricular pacemaker implantation" }, { "kind": "case report", "citation": "Goldstein LN, Wells M (2019). Smart watch-detected tachycardia: a case of atrial flutter. Oxford Medical Case Reports 2019(12):omz137.", "title": "Smart watch-detected tachycardia: a case of atrial flutter", "url": "https://academic.oup.com/omcr/article/2019/12/495/5691267", "date": "2019-12-31", "written_by": "independent", "quote": "a consistent rate of 150 bpm for the previous 4 days" }, { "kind": "case report", "citation": "Siddeek H, Fisher K, McMakin S, Bass JL, Cortez D (2020). AVNRT captured by Apple Watch Series 4: Can the Apple watch be used as an event monitor? Annals of Noninvasive Electrocardiology 25:e12742.", "title": "AVNRT captured by Apple Watch Series 4", "url": "https://europepmc.org/article/PMC/PMC7507696", "date": "2020-01-29", "written_by": "independent", "quote": "captured an episode on the Apple watch that demonstrated tachycardia at a rate of about 225 bpm" }, { "kind": "case report", "citation": "Samal S, Singhania N, Bansal S, Sahoo A (2020). New-onset atrial fibrillation in a young patient detected by smartwatch. Clinical Case Reports 8(7).", "title": "New-onset atrial fibrillation in a young patient detected by smartwatch", "url": "https://europepmc.org/article/PMC/PMC7364102", "date": "2020-04-23", "written_by": "independent", "quote": "He was chemically cardioverted using intravenous flecainide per cardiology recommendations. He maintained sinus rhythm afterward and was discharged home on metoprolol and apixaban." }, { "kind": "case report", "citation": "Ahmed AS, Golden KM, Foreman JR, Padanilam BJ (2020). Using a smartwatch to identify the morphology of atrial flutter. HeartRhythm Case Reports 6.", "title": "Using a smartwatch to identify the morphology of atrial flutter", "url": "https://europepmc.org/article/PMC/PMC7573381", "date": "2020-06-28", "written_by": "independent", "quote": "ECG revealed typical atrial flutter with variable atrioventricular conduction" }, { "kind": "case report", "citation": "Burke J, Haigney MCP, Borne R, Krantz MJ (2020). Smartwatch detection of ventricular tachycardia: Case series. HeartRhythm Case Reports 6.", "title": "Smartwatch detection of ventricular tachycardia: Case series", "url": "https://europepmc.org/article/PMC/PMC7573479", "date": "2020-08-18", "written_by": "independent", "quote": "The patient has not experienced further symptoms suggestive of arrhythmia, nor has he reported detection of event recordings on his smartwatch" }, { "kind": "case report", "citation": "Patel D, Tarakji KG (2021). Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source: A case report. Cardiovascular Digital Health Journal 2(1):84-87.", "title": "Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source", "url": "https://europepmc.org/article/PMC/PMC8890063", "date": "2021-01-13", "written_by": "independent", "quote": "Given her elevated CHA2DS2VASC score of 5 (age, female, previous stroke, and hypertension), the patient was started on a direct oral anticoagulant, and the aspirin was stopped." }, { "kind": "case report", "citation": "Kassam N, Aziz O, Aghan E, Somji S, Mbithe H, Bapumia M, Mvungi R, Surani S (2021). Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania. International Medical Case Reports Journal 14.", "title": "Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania", "url": "https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ", "date": "2021-08-24", "written_by": "independent", "quote": "a high resting heart rate of 210 beats/min" }, { "kind": "case report", "citation": "Itoh A (2022). Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation with a very short duration. European Heart Journal - Case Reports 6:ytac252.", "title": "Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC9269674", "date": "2022-06-28", "written_by": "independent", "quote": "After that, the patient stopped drinking coffee in the morning, and AF hardly occurred." }, { "kind": "case report", "citation": "Hawryszko M, Sławiński G, Kozłowski D, Lewicka E (2022). Apple Watch-guided diagnosis of AVNRT in a pregnant woman. Frontiers in Cardiovascular Medicine 9:985421.", "title": "Apple Watch-guided diagnosis of AVNRT in a pregnant woman", "url": "https://europepmc.org/article/PMC/PMC9676225", "date": "2022-11-07", "written_by": "independent", "quote": "narrow QRS complex tachycardia of 216 bpm, and short RP interval" }, { "kind": "case report", "citation": "Heringer GV, Vinson DR (2024). Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation: a case report. International Journal of Emergency Medicine 17.", "title": "Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC11462712", "date": "2024-10-08", "written_by": "independent", "quote": "Had it not been for his smart watch, the etiology of his transitory palpitations would have remained undiagnosed." }, { "kind": "case report", "citation": "Guarnieri G, Mapelli M, Moltrasio M, Agostoni P, Tondo C (2024). Connected health: Ventricular tachycardia detection with Apple Watch—A case report. Heliyon 10:e40595.", "title": "Connected health: Ventricular tachycardia detection with Apple Watch", "url": "https://europepmc.org/article/PMC/PMC11625252", "date": "2024-11-21", "written_by": "independent", "quote": "An alert message of 'Elevated Heart rate' from his Apple Watch® prompted him to record a single-lead ECG using the smartwatch." }, { "kind": "case report", "citation": "Rushakoff JA, Flores Rosario K, Grover P, Wang A (2025). Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report. European Heart Journal - Case Reports 9(9):ytaf415.", "title": "Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report", "url": "https://europepmc.org/article/PMC/PMC12412439", "date": "2025-08-23", "written_by": "independent", "quote": "An asymptomatic 47-year-old man from Costa Rica presented to cardiology clinic for evaluation of recurrent bradycardia alarms on his smartwatch (Apple Watch)." }, { "kind": "case report", "citation": "Shroddha AD, Mukherjee I, Lambiase PD (2026). Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy. Cureus 18:e113337.", "title": "Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy", "url": "https://europepmc.org/article/PMC/PMC13501160", "date": "2026-07-25", "written_by": "independent", "quote": "In the early hours of Thursday, at 3:00 am, he awoke with frequent ectopic beats noted on his smartwatch single-lead ECG, which progressed to a broad complex tachycardia." } ], "replication": { "produced_by": [ "The wearer owns an Apple Watch with heart-rate notifications, Irregular Rhythm Notification or the ECG app enabled", "An arrhythmia occurs while the watch is worn and the alert or recording leads the wearer to seek care", "A clinician confirms the rhythm on a 12-lead ECG or monitoring and treats it" ], "must_hold": [ "The alert or trace reaches a clinician rather than being dismissed", "Confirmatory ECG or electrophysiology testing is available", "A treatment pathway (anticoagulation, cardioversion, ablation, device) exists" ], "echoes": [ { "date": "2019-07-21", "setting": "woman in her mid-60s, emergency department, USA; low heart-rate alarms; complete heart block, pacemaker implanted (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Overbeek et al. (2019). Am J Emerg Med 37(10):1989.e5. https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747" }, { "date": "2019-12-03", "setting": "68-year-old man one year after TAVI, USA; ECG app recording after syncope showed high-grade AV block; urgent biventricular pacemaker (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Yerasi et al. (2020). Eur Heart J 41(10):1096. https://academic.oup.com/eurheartj/article/41/10/1096/5651110" }, { "date": "2019-12-31", "setting": "56-year-old man, emergency department, South Africa; watch showed 150 bpm for four days; atrial flutter, anticoagulation and cardioversion (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Goldstein & Wells (2019). Oxf Med Case Reports 2019(12):omz137. https://academic.oup.com/omcr/article/2019/12/495/5691267" }, { "date": "2020-01-29", "setting": "16-year-old girl, Minneapolis, USA (authors' institution); watch captured 225 bpm and ECG; AVNRT ablated, asymptomatic at four months (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Siddeek et al. (2020). Ann Noninvasive Electrocardiol 25:e12742. https://europepmc.org/article/PMC/PMC7507696" }, { "date": "2020-04-23", "setting": "39-year-old man, Milwaukee, USA (authors' institution); watch showed heart rate 60–130 bpm during palpitations; AF cardioverted with flecainide, metoprolol and apixaban (publication date)", "model_version": "Apple Watch Series 3", "outcome": "recurred", "source": "Samal et al. (2020). Clin Case Rep 8(7). https://europepmc.org/article/PMC/PMC7364102" }, { "date": "2020-06-28", "setting": "54-year-old woman with mechanical aortic valve, Pensacola, USA (authors' institution); alerted to elevated heart rates by an unnamed fitness tracker; typical atrial flutter on ECG; outpatient ablation planned, discharged with rate control and continued anticoagulation; the authors then used an Apple Watch Series 5 in a lead II configuration to confirm the flutter morphology in the ambulatory setting (publication date)", "model_version": "Apple Watch Series 5 (authors' post-diagnosis monitoring; alerting device unnamed)", "outcome": "unknown", "source": "Ahmed et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573381" }, { "date": "2020-08-18", "setting": "60-year-old man, Denver, USA (authors' institution); single-lead ECG showed wide complex tachycardia; ARVC with VT, ablation and ICD (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2020-08-18", "setting": "63-year-old man, USA; watch recording labeled ventricular tachycardia; 9% VPC burden with NSVT, papillary muscle ablation (publication date)", "model_version": "smartwatch (brand not stated for this case; case 1 in the same series names an Apple Watch)", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2021-01-13", "setting": "70-year-old woman after embolic stroke of unknown source, Cleveland, USA (authors' institution); irregular-rhythm notifications and ECG app; AF, DOAC started, loop recorder avoided (publication date)", "model_version": "Apple Watch (Irregular Rhythm Notification and ECG app)", "outcome": "recurred", "source": "Patel & Tarakji (2021). Cardiovasc Digit Health J 2(1):84-87. https://europepmc.org/article/PMC/PMC8890063" }, { "date": "2021-08-24", "setting": "42-year-old man, Dar es Salaam, Tanzania (authors' institution); resting heart rate 210 bpm; SVT (orthodromic AVRT), cardioversion, medication; an ablation attempt had no effect and pathway ablation was declined; managed medically (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Kassam et al. (2021). Int Med Case Rep J 14. https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ" }, { "date": "2022-06-28", "setting": "man in his early 60s, Shikokuchuo, Japan (authors' institution); ECG app recordings; coffee-triggered paroxysmal AF, trigger avoidance (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Itoh (2022). Eur Heart J Case Rep 6:ytac252. https://europepmc.org/article/PMC/PMC9269674" }, { "date": "2022-11-07", "setting": "35-year-old woman at 20 weeks of pregnancy, Gdańsk, Poland (authors' institution); ECG app 216 bpm; AVNRT diagnosed, managed with Valsalva instruction without drugs (publication date)", "model_version": "Apple Watch Series 6", "outcome": "recurred", "source": "Hawryszko et al. (2022). Front Cardiovasc Med 9:985421. https://europepmc.org/article/PMC/PMC9676225" }, { "date": "2024-10-08", "setting": "43-year-old man, urgent care, USA; ECG app reported signs of AFib; paroxysmal AF, trigger avoidance and aspirin, no recurrence (publication date)", "model_version": "Apple Watch Ultra", "outcome": "recurred", "source": "Heringer & Vinson (2024). Int J Emerg Med 17. https://europepmc.org/article/PMC/PMC11462712" }, { "date": "2024-11-21", "setting": "60-year-old man, Milan, Italy (authors' institution); “Elevated Heart rate” alert then ECG; sustained VT at 183 bpm, radiofrequency ablation (publication date)", "model_version": "Apple Watch Series 5", "outcome": "recurred", "source": "Guarnieri et al. (2024). Heliyon 10:e40595. https://europepmc.org/article/PMC/PMC11625252" }, { "date": "2025-08-23", "setting": "47-year-old asymptomatic man from Costa Rica, Duke University Medical Center, USA; recurrent low heart-rate alarms; LMNA cardiomyopathy, CRT-D implanted, ejection fraction improved (publication date)", "model_version": "Apple Watch (low heart-rate notification)", "outcome": "recurred", "source": "Rushakoff et al. (2025). Eur Heart J Case Rep 9(9):ytaf415. https://europepmc.org/article/PMC/PMC12412439" }, { "date": "2026-07-25", "setting": "33-year-old male footballer, London, UK; single-lead ECG showed ectopy progressing to broad complex tachycardia; arrhythmogenic cardiomyopathy, S-ICD, flecainide and nadolol (publication date)", "model_version": "Apple Watch (model not stated)", "outcome": "recurred", "source": "Shroddha et al. (2026). Cureus 18:e113337. https://europepmc.org/article/PMC/PMC13501160" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "severity": null, "group": "personal", "basis": "Same device: Apple Watch automatic sensor alerts; Crash Detection misclassified skiing as accidents and placed false 911 calls, burdening Apple Watch users, ski patrols and dispatchers, the inverse of a true heart-rate alarm sending one wearer to hospital." }, "headline": "Apple Watch alarms lead to an AF diagnosis and anticoagulation", "metric": "her pulse exceeded 120 beats per minute while she was inactive", "comparator": null, "later": { "status": "scaled", "date": "2024-04-25", "note": "A 2024 systematic review of smartwatch arrhythmia case reports found 44 patients across 33 articles, with the Apple Watch used in 30 of them.", "quote": "We selected 33 articles from case reports and case series detailing events involving a total of 44 patients. Most of the reports come from the United States (n = 12). In the selected articles, the youngest subject was 10 days old, and the oldest was 72 years old. 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Several echoes (VT ablation with defibrillator, pacemaker for heart block) are deeper but are not the event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Apple Watch high/low heart-rate notifications, the Irregular Rhythm Notification and the ECG app are built to flag possible arrhythmias so the wearer seeks medical review. This benefit was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Apple Watch high/low heart-rate notifications, the Irregular Rhythm Notification and the ECG app are built to flag possible arrhythmias so the wearer seeks medical review. This benefit was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-03-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Moved the location to “United Kingdom” and marked nine echo cities as the authors' institutions because none of those case texts names the place of care, removed the unsourced Series 9 and 11 from the model version, re-described the Ahmed echo (alert from an unnamed fitness tracker, Series 5 applied by the authors after diagnosis, ablation planned rather than done) with outcome “unknown”, labeled Burke case 2 as an unbranded smartwatch, replaced “partial ablation” in the Kassam echo with the failed attempt and declined pathway ablation, changed “12-lead ECG” to “ECG” for the index case, corrected the echo count to 16 from 15 reports, restored the published Rushakoff title and quoted the whole Patel sentence.", "source": "https://europepmc.org/article/PMC/PMC6440268 ; https://europepmc.org/article/PMC/PMC7573381 ; https://europepmc.org/article/PMC/PMC7573479 ; https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ ; https://europepmc.org/article/PMC/PMC8890063 ; https://europepmc.org/article/PMC/PMC12412439", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11083549", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer owns an Apple Watch with heart-rate notifications, Irregular Rhythm Notification or the ECG app enabled", "An arrhythmia occurs while the watch is worn and the alert or recording leads the wearer to seek care", "A clinician confirms the rhythm on a 12-lead ECG or monitoring and treats it" ], "must_hold": [ "The alert or trace reaches a clinician rather than being dismissed", "Confirmatory ECG or electrophysiology testing is available", "A treatment pathway (anticoagulation, cardioversion, ablation, device) exists" ], "echoes": [ { "date": "2019-07-21", "setting": "woman in her mid-60s, emergency department, USA; low heart-rate alarms; complete heart block, pacemaker implanted (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Overbeek et al. (2019). Am J Emerg Med 37(10):1989.e5. https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747" }, { "date": "2019-12-03", "setting": "68-year-old man one year after TAVI, USA; ECG app recording after syncope showed high-grade AV block; urgent biventricular pacemaker (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Yerasi et al. (2020). Eur Heart J 41(10):1096. https://academic.oup.com/eurheartj/article/41/10/1096/5651110" }, { "date": "2019-12-31", "setting": "56-year-old man, emergency department, South Africa; watch showed 150 bpm for four days; atrial flutter, anticoagulation and cardioversion (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Goldstein & Wells (2019). Oxf Med Case Reports 2019(12):omz137. https://academic.oup.com/omcr/article/2019/12/495/5691267" }, { "date": "2020-01-29", "setting": "16-year-old girl, Minneapolis, USA (authors' institution); watch captured 225 bpm and ECG; AVNRT ablated, asymptomatic at four months (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Siddeek et al. (2020). Ann Noninvasive Electrocardiol 25:e12742. https://europepmc.org/article/PMC/PMC7507696" }, { "date": "2020-04-23", "setting": "39-year-old man, Milwaukee, USA (authors' institution); watch showed heart rate 60–130 bpm during palpitations; AF cardioverted with flecainide, metoprolol and apixaban (publication date)", "model_version": "Apple Watch Series 3", "outcome": "recurred", "source": "Samal et al. (2020). Clin Case Rep 8(7). https://europepmc.org/article/PMC/PMC7364102" }, { "date": "2020-06-28", "setting": "54-year-old woman with mechanical aortic valve, Pensacola, USA (authors' institution); alerted to elevated heart rates by an unnamed fitness tracker; typical atrial flutter on ECG; outpatient ablation planned, discharged with rate control and continued anticoagulation; the authors then used an Apple Watch Series 5 in a lead II configuration to confirm the flutter morphology in the ambulatory setting (publication date)", "model_version": "Apple Watch Series 5 (authors' post-diagnosis monitoring; alerting device unnamed)", "outcome": "unknown", "source": "Ahmed et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573381" }, { "date": "2020-08-18", "setting": "60-year-old man, Denver, USA (authors' institution); single-lead ECG showed wide complex tachycardia; ARVC with VT, ablation and ICD (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2020-08-18", "setting": "63-year-old man, USA; watch recording labeled ventricular tachycardia; 9% VPC burden with NSVT, papillary muscle ablation (publication date)", "model_version": "smartwatch (brand not stated for this case; case 1 in the same series names an Apple Watch)", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2021-01-13", "setting": "70-year-old woman after embolic stroke of unknown source, Cleveland, USA (authors' institution); irregular-rhythm notifications and ECG app; AF, DOAC started, loop recorder avoided (publication date)", "model_version": "Apple Watch (Irregular Rhythm Notification and ECG app)", "outcome": "recurred", "source": "Patel & Tarakji (2021). Cardiovasc Digit Health J 2(1):84-87. https://europepmc.org/article/PMC/PMC8890063" }, { "date": "2021-08-24", "setting": "42-year-old man, Dar es Salaam, Tanzania (authors' institution); resting heart rate 210 bpm; SVT (orthodromic AVRT), cardioversion, medication; an ablation attempt had no effect and pathway ablation was declined; managed medically (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Kassam et al. (2021). Int Med Case Rep J 14. https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ" }, { "date": "2022-06-28", "setting": "man in his early 60s, Shikokuchuo, Japan (authors' institution); ECG app recordings; coffee-triggered paroxysmal AF, trigger avoidance (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Itoh (2022). Eur Heart J Case Rep 6:ytac252. https://europepmc.org/article/PMC/PMC9269674" }, { "date": "2022-11-07", "setting": "35-year-old woman at 20 weeks of pregnancy, Gdańsk, Poland (authors' institution); ECG app 216 bpm; AVNRT diagnosed, managed with Valsalva instruction without drugs (publication date)", "model_version": "Apple Watch Series 6", "outcome": "recurred", "source": "Hawryszko et al. (2022). Front Cardiovasc Med 9:985421. https://europepmc.org/article/PMC/PMC9676225" }, { "date": "2024-10-08", "setting": "43-year-old man, urgent care, USA; ECG app reported signs of AFib; paroxysmal AF, trigger avoidance and aspirin, no recurrence (publication date)", "model_version": "Apple Watch Ultra", "outcome": "recurred", "source": "Heringer & Vinson (2024). Int J Emerg Med 17. https://europepmc.org/article/PMC/PMC11462712" }, { "date": "2024-11-21", "setting": "60-year-old man, Milan, Italy (authors' institution); “Elevated Heart rate” alert then ECG; sustained VT at 183 bpm, radiofrequency ablation (publication date)", "model_version": "Apple Watch Series 5", "outcome": "recurred", "source": "Guarnieri et al. (2024). Heliyon 10:e40595. https://europepmc.org/article/PMC/PMC11625252" }, { "date": "2025-08-23", "setting": "47-year-old asymptomatic man from Costa Rica, Duke University Medical Center, USA; recurrent low heart-rate alarms; LMNA cardiomyopathy, CRT-D implanted, ejection fraction improved (publication date)", "model_version": "Apple Watch (low heart-rate notification)", "outcome": "recurred", "source": "Rushakoff et al. (2025). Eur Heart J Case Rep 9(9):ytaf415. https://europepmc.org/article/PMC/PMC12412439" }, { "date": "2026-07-25", "setting": "33-year-old male footballer, London, UK; single-lead ECG showed ectopy progressing to broad complex tachycardia; arrhythmogenic cardiomyopathy, S-ICD, flecainide and nadolol (publication date)", "model_version": "Apple Watch (model not stated)", "outcome": "recurred", "source": "Shroddha et al. (2026). Cureus 18:e113337. https://europepmc.org/article/PMC/PMC13501160" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer owns an Apple Watch with heart-rate notifications, Irregular Rhythm Notification or the ECG app enabled", "An arrhythmia occurs while the watch is worn and the alert or recording leads the wearer to seek care", "A clinician confirms the rhythm on a 12-lead ECG or monitoring and treats it" ], "must_hold": [ "The alert or trace reaches a clinician rather than being dismissed", "Confirmatory ECG or electrophysiology testing is available", "A treatment pathway (anticoagulation, cardioversion, ablation, device) exists" ], "echoes": [ { "date": "2019-07-21", "setting": "woman in her mid-60s, emergency department, USA; low heart-rate alarms; complete heart block, pacemaker implanted (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Overbeek et al. (2019). Am J Emerg Med 37(10):1989.e5. https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747" }, { "date": "2019-12-03", "setting": "68-year-old man one year after TAVI, USA; ECG app recording after syncope showed high-grade AV block; urgent biventricular pacemaker (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Yerasi et al. (2020). Eur Heart J 41(10):1096. https://academic.oup.com/eurheartj/article/41/10/1096/5651110" }, { "date": "2019-12-31", "setting": "56-year-old man, emergency department, South Africa; watch showed 150 bpm for four days; atrial flutter, anticoagulation and cardioversion (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Goldstein & Wells (2019). Oxf Med Case Reports 2019(12):omz137. https://academic.oup.com/omcr/article/2019/12/495/5691267" }, { "date": "2020-01-29", "setting": "16-year-old girl, Minneapolis, USA (authors' institution); watch captured 225 bpm and ECG; AVNRT ablated, asymptomatic at four months (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Siddeek et al. (2020). Ann Noninvasive Electrocardiol 25:e12742. https://europepmc.org/article/PMC/PMC7507696" }, { "date": "2020-04-23", "setting": "39-year-old man, Milwaukee, USA (authors' institution); watch showed heart rate 60–130 bpm during palpitations; AF cardioverted with flecainide, metoprolol and apixaban (publication date)", "model_version": "Apple Watch Series 3", "outcome": "recurred", "source": "Samal et al. (2020). Clin Case Rep 8(7). https://europepmc.org/article/PMC/PMC7364102" }, { "date": "2020-06-28", "setting": "54-year-old woman with mechanical aortic valve, Pensacola, USA (authors' institution); alerted to elevated heart rates by an unnamed fitness tracker; typical atrial flutter on ECG; outpatient ablation planned, discharged with rate control and continued anticoagulation; the authors then used an Apple Watch Series 5 in a lead II configuration to confirm the flutter morphology in the ambulatory setting (publication date)", "model_version": "Apple Watch Series 5 (authors' post-diagnosis monitoring; alerting device unnamed)", "outcome": "unknown", "source": "Ahmed et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573381" }, { "date": "2020-08-18", "setting": "60-year-old man, Denver, USA (authors' institution); single-lead ECG showed wide complex tachycardia; ARVC with VT, ablation and ICD (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2020-08-18", "setting": "63-year-old man, USA; watch recording labeled ventricular tachycardia; 9% VPC burden with NSVT, papillary muscle ablation (publication date)", "model_version": "smartwatch (brand not stated for this case; case 1 in the same series names an Apple Watch)", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2021-01-13", "setting": "70-year-old woman after embolic stroke of unknown source, Cleveland, USA (authors' institution); irregular-rhythm notifications and ECG app; AF, DOAC started, loop recorder avoided (publication date)", "model_version": "Apple Watch (Irregular Rhythm Notification and ECG app)", "outcome": "recurred", "source": "Patel & Tarakji (2021). Cardiovasc Digit Health J 2(1):84-87. https://europepmc.org/article/PMC/PMC8890063" }, { "date": "2021-08-24", "setting": "42-year-old man, Dar es Salaam, Tanzania (authors' institution); resting heart rate 210 bpm; SVT (orthodromic AVRT), cardioversion, medication; an ablation attempt had no effect and pathway ablation was declined; managed medically (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Kassam et al. (2021). Int Med Case Rep J 14. https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ" }, { "date": "2022-06-28", "setting": "man in his early 60s, Shikokuchuo, Japan (authors' institution); ECG app recordings; coffee-triggered paroxysmal AF, trigger avoidance (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Itoh (2022). Eur Heart J Case Rep 6:ytac252. https://europepmc.org/article/PMC/PMC9269674" }, { "date": "2022-11-07", "setting": "35-year-old woman at 20 weeks of pregnancy, Gdańsk, Poland (authors' institution); ECG app 216 bpm; AVNRT diagnosed, managed with Valsalva instruction without drugs (publication date)", "model_version": "Apple Watch Series 6", "outcome": "recurred", "source": "Hawryszko et al. (2022). Front Cardiovasc Med 9:985421. https://europepmc.org/article/PMC/PMC9676225" }, { "date": "2024-10-08", "setting": "43-year-old man, urgent care, USA; ECG app reported signs of AFib; paroxysmal AF, trigger avoidance and aspirin, no recurrence (publication date)", "model_version": "Apple Watch Ultra", "outcome": "recurred", "source": "Heringer & Vinson (2024). Int J Emerg Med 17. https://europepmc.org/article/PMC/PMC11462712" }, { "date": "2024-11-21", "setting": "60-year-old man, Milan, Italy (authors' institution); “Elevated Heart rate” alert then ECG; sustained VT at 183 bpm, radiofrequency ablation (publication date)", "model_version": "Apple Watch Series 5", "outcome": "recurred", "source": "Guarnieri et al. (2024). Heliyon 10:e40595. https://europepmc.org/article/PMC/PMC11625252" }, { "date": "2025-08-23", "setting": "47-year-old asymptomatic man from Costa Rica, Duke University Medical Center, USA; recurrent low heart-rate alarms; LMNA cardiomyopathy, CRT-D implanted, ejection fraction improved (publication date)", "model_version": "Apple Watch (low heart-rate notification)", "outcome": "recurred", "source": "Rushakoff et al. (2025). Eur Heart J Case Rep 9(9):ytaf415. https://europepmc.org/article/PMC/PMC12412439" }, { "date": "2026-07-25", "setting": "33-year-old male footballer, London, UK; single-lead ECG showed ectopy progressing to broad complex tachycardia; arrhythmogenic cardiomyopathy, S-ICD, flecainide and nadolol (publication date)", "model_version": "Apple Watch (model not stated)", "outcome": "recurred", "source": "Shroddha et al. (2026). Cureus 18:e113337. https://europepmc.org/article/PMC/PMC13501160" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Moved the location to “United Kingdom” and marked nine echo cities as the authors' institutions because none of those case texts names the place of care, removed the unsourced Series 9 and 11 from the model version, re-described the Ahmed echo (alert from an unnamed fitness tracker, Series 5 applied by the authors after diagnosis, ablation planned rather than done) with outcome “unknown”, labeled Burke case 2 as an unbranded smartwatch, replaced “partial ablation” in the Kassam echo with the failed attempt and declined pathway ablation, changed “12-lead ECG” to “ECG” for the index case, corrected the echo count to 16 from 15 reports, restored the published Rushakoff title and quoted the whole Patel sentence.", "source": "https://europepmc.org/article/PMC/PMC6440268 ; https://europepmc.org/article/PMC/PMC7573381 ; https://europepmc.org/article/PMC/PMC7573479 ; https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ ; https://europepmc.org/article/PMC/PMC8890063 ; https://europepmc.org/article/PMC/PMC12412439", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11083549", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Weichert I (2019). 'My watch kept on alarming all night about my heart rate': diagnosis of asymptomatic atrial fibrillation with fast ventricular response in a patient with a recent TIA as the result of a smartwatch alarm. Oxford Medical Case Reports 2019(3):omz014.", "title": "'My watch kept on alarming all night about my heart rate'", "url": "https://europepmc.org/article/PMC/PMC6440268", "date": "2019-03-29", "written_by": "independent", "quote": "Her smartwatch had alarmed several times during the preceding night that her pulse rate exceeded 120 beats per minute (bpm) whilst she was inactive" }, { "kind": "peer-reviewed study", "citation": "Bogár B, Pető D, Sipos D, Füredi G, Keszthelyi A, Betlehem J, Pandur AA (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "In most cases (n = 30), the Apple Watch was used, while Samsung Galaxy Fit was used for arrhythmia registration in one patient." }, { "kind": "case report", "citation": "Overbeek DL, Hogikyan EM, Davis M, McGillicuddy DC (2019). A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block. American Journal of Emergency Medicine 37(10):1989.e5-e7.", "title": "A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block", "url": "https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747", "date": "2019-07-21", "written_by": "independent", "quote": "A previously-healthy mid 60s-year-old-woman presented to the Emergency Department (ED) stating that her 'Apple Watch' wearable device was alarming due to a low heart rate." }, { "kind": "case report", "citation": "Yerasi C, O'Donoghue S, Satler LF, Waksman R (2020). Apple Watch detecting high-grade block after transcatheter aortic valve implantation. European Heart Journal 41(10):1096.", "title": "Apple Watch detecting high-grade block after transcatheter aortic valve implantation", "url": "https://academic.oup.com/eurheartj/article/41/10/1096/5651110", "date": "2019-12-03", "written_by": "independent", "quote": "He subsequently underwent urgent biventricular pacemaker implantation" }, { "kind": "case report", "citation": "Goldstein LN, Wells M (2019). Smart watch-detected tachycardia: a case of atrial flutter. Oxford Medical Case Reports 2019(12):omz137.", "title": "Smart watch-detected tachycardia: a case of atrial flutter", "url": "https://academic.oup.com/omcr/article/2019/12/495/5691267", "date": "2019-12-31", "written_by": "independent", "quote": "a consistent rate of 150 bpm for the previous 4 days" }, { "kind": "case report", "citation": "Siddeek H, Fisher K, McMakin S, Bass JL, Cortez D (2020). AVNRT captured by Apple Watch Series 4: Can the Apple watch be used as an event monitor? Annals of Noninvasive Electrocardiology 25:e12742.", "title": "AVNRT captured by Apple Watch Series 4", "url": "https://europepmc.org/article/PMC/PMC7507696", "date": "2020-01-29", "written_by": "independent", "quote": "captured an episode on the Apple watch that demonstrated tachycardia at a rate of about 225 bpm" }, { "kind": "case report", "citation": "Samal S, Singhania N, Bansal S, Sahoo A (2020). New-onset atrial fibrillation in a young patient detected by smartwatch. Clinical Case Reports 8(7).", "title": "New-onset atrial fibrillation in a young patient detected by smartwatch", "url": "https://europepmc.org/article/PMC/PMC7364102", "date": "2020-04-23", "written_by": "independent", "quote": "He was chemically cardioverted using intravenous flecainide per cardiology recommendations. He maintained sinus rhythm afterward and was discharged home on metoprolol and apixaban." }, { "kind": "case report", "citation": "Ahmed AS, Golden KM, Foreman JR, Padanilam BJ (2020). Using a smartwatch to identify the morphology of atrial flutter. HeartRhythm Case Reports 6.", "title": "Using a smartwatch to identify the morphology of atrial flutter", "url": "https://europepmc.org/article/PMC/PMC7573381", "date": "2020-06-28", "written_by": "independent", "quote": "ECG revealed typical atrial flutter with variable atrioventricular conduction" }, { "kind": "case report", "citation": "Burke J, Haigney MCP, Borne R, Krantz MJ (2020). Smartwatch detection of ventricular tachycardia: Case series. HeartRhythm Case Reports 6.", "title": "Smartwatch detection of ventricular tachycardia: Case series", "url": "https://europepmc.org/article/PMC/PMC7573479", "date": "2020-08-18", "written_by": "independent", "quote": "The patient has not experienced further symptoms suggestive of arrhythmia, nor has he reported detection of event recordings on his smartwatch" }, { "kind": "case report", "citation": "Patel D, Tarakji KG (2021). Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source: A case report. Cardiovascular Digital Health Journal 2(1):84-87.", "title": "Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source", "url": "https://europepmc.org/article/PMC/PMC8890063", "date": "2021-01-13", "written_by": "independent", "quote": "Given her elevated CHA2DS2VASC score of 5 (age, female, previous stroke, and hypertension), the patient was started on a direct oral anticoagulant, and the aspirin was stopped." }, { "kind": "case report", "citation": "Kassam N, Aziz O, Aghan E, Somji S, Mbithe H, Bapumia M, Mvungi R, Surani S (2021). Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania. International Medical Case Reports Journal 14.", "title": "Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania", "url": "https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ", "date": "2021-08-24", "written_by": "independent", "quote": "a high resting heart rate of 210 beats/min" }, { "kind": "case report", "citation": "Itoh A (2022). Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation with a very short duration. European Heart Journal - Case Reports 6:ytac252.", "title": "Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC9269674", "date": "2022-06-28", "written_by": "independent", "quote": "After that, the patient stopped drinking coffee in the morning, and AF hardly occurred." }, { "kind": "case report", "citation": "Hawryszko M, Sławiński G, Kozłowski D, Lewicka E (2022). Apple Watch-guided diagnosis of AVNRT in a pregnant woman. Frontiers in Cardiovascular Medicine 9:985421.", "title": "Apple Watch-guided diagnosis of AVNRT in a pregnant woman", "url": "https://europepmc.org/article/PMC/PMC9676225", "date": "2022-11-07", "written_by": "independent", "quote": "narrow QRS complex tachycardia of 216 bpm, and short RP interval" }, { "kind": "case report", "citation": "Heringer GV, Vinson DR (2024). Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation: a case report. International Journal of Emergency Medicine 17.", "title": "Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC11462712", "date": "2024-10-08", "written_by": "independent", "quote": "Had it not been for his smart watch, the etiology of his transitory palpitations would have remained undiagnosed." }, { "kind": "case report", "citation": "Guarnieri G, Mapelli M, Moltrasio M, Agostoni P, Tondo C (2024). Connected health: Ventricular tachycardia detection with Apple Watch—A case report. Heliyon 10:e40595.", "title": "Connected health: Ventricular tachycardia detection with Apple Watch", "url": "https://europepmc.org/article/PMC/PMC11625252", "date": "2024-11-21", "written_by": "independent", "quote": "An alert message of 'Elevated Heart rate' from his Apple Watch® prompted him to record a single-lead ECG using the smartwatch." }, { "kind": "case report", "citation": "Rushakoff JA, Flores Rosario K, Grover P, Wang A (2025). Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report. European Heart Journal - Case Reports 9(9):ytaf415.", "title": "Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report", "url": "https://europepmc.org/article/PMC/PMC12412439", "date": "2025-08-23", "written_by": "independent", "quote": "An asymptomatic 47-year-old man from Costa Rica presented to cardiology clinic for evaluation of recurrent bradycardia alarms on his smartwatch (Apple Watch)." }, { "kind": "case report", "citation": "Shroddha AD, Mukherjee I, Lambiase PD (2026). Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy. Cureus 18:e113337.", "title": "Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy", "url": "https://europepmc.org/article/PMC/PMC13501160", "date": "2026-07-25", "written_by": "independent", "quote": "In the early hours of Thursday, at 3:00 am, he awoke with frequent ectopic beats noted on his smartwatch single-lead ECG, which progressed to a broad complex tachycardia." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0021-source-0001", "AIBD-0021-source-0002", "AIBD-0021-source-0003", "AIBD-0021-source-0004", "AIBD-0021-source-0005", "AIBD-0021-source-0006", "AIBD-0021-source-0007", "AIBD-0021-source-0008", "AIBD-0021-source-0009", "AIBD-0021-source-0010", "AIBD-0021-source-0011", "AIBD-0021-source-0012", "AIBD-0021-source-0013", "AIBD-0021-source-0014", "AIBD-0021-source-0015", "AIBD-0021-source-0016", "AIBD-0021-source-0017" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Weichert I (2019). 'My watch kept on alarming all night about my heart rate': diagnosis of asymptomatic atrial fibrillation with fast ventricular response in a patient with a recent TIA as the result of a smartwatch alarm. Oxford Medical Case Reports 2019(3):omz014.", "title": "'My watch kept on alarming all night about my heart rate'", "url": "https://europepmc.org/article/PMC/PMC6440268", "date": "2019-03-29", "written_by": "independent", "quote": "Her smartwatch had alarmed several times during the preceding night that her pulse rate exceeded 120 beats per minute (bpm) whilst she was inactive" }, { "kind": "peer-reviewed study", "citation": "Bogár B, Pető D, Sipos D, Füredi G, Keszthelyi A, Betlehem J, Pandur AA (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "In most cases (n = 30), the Apple Watch was used, while Samsung Galaxy Fit was used for arrhythmia registration in one patient." }, { "kind": "case report", "citation": "Overbeek DL, Hogikyan EM, Davis M, McGillicuddy DC (2019). A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block. American Journal of Emergency Medicine 37(10):1989.e5-e7.", "title": "A unique case of bradycardia recognized by wearable technology as first presentation of complete heart block", "url": "https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747", "date": "2019-07-21", "written_by": "independent", "quote": "A previously-healthy mid 60s-year-old-woman presented to the Emergency Department (ED) stating that her 'Apple Watch' wearable device was alarming due to a low heart rate." }, { "kind": "case report", "citation": "Yerasi C, O'Donoghue S, Satler LF, Waksman R (2020). Apple Watch detecting high-grade block after transcatheter aortic valve implantation. European Heart Journal 41(10):1096.", "title": "Apple Watch detecting high-grade block after transcatheter aortic valve implantation", "url": "https://academic.oup.com/eurheartj/article/41/10/1096/5651110", "date": "2019-12-03", "written_by": "independent", "quote": "He subsequently underwent urgent biventricular pacemaker implantation" }, { "kind": "case report", "citation": "Goldstein LN, Wells M (2019). Smart watch-detected tachycardia: a case of atrial flutter. Oxford Medical Case Reports 2019(12):omz137.", "title": "Smart watch-detected tachycardia: a case of atrial flutter", "url": "https://academic.oup.com/omcr/article/2019/12/495/5691267", "date": "2019-12-31", "written_by": "independent", "quote": "a consistent rate of 150 bpm for the previous 4 days" }, { "kind": "case report", "citation": "Siddeek H, Fisher K, McMakin S, Bass JL, Cortez D (2020). AVNRT captured by Apple Watch Series 4: Can the Apple watch be used as an event monitor? Annals of Noninvasive Electrocardiology 25:e12742.", "title": "AVNRT captured by Apple Watch Series 4", "url": "https://europepmc.org/article/PMC/PMC7507696", "date": "2020-01-29", "written_by": "independent", "quote": "captured an episode on the Apple watch that demonstrated tachycardia at a rate of about 225 bpm" }, { "kind": "case report", "citation": "Samal S, Singhania N, Bansal S, Sahoo A (2020). New-onset atrial fibrillation in a young patient detected by smartwatch. Clinical Case Reports 8(7).", "title": "New-onset atrial fibrillation in a young patient detected by smartwatch", "url": "https://europepmc.org/article/PMC/PMC7364102", "date": "2020-04-23", "written_by": "independent", "quote": "He was chemically cardioverted using intravenous flecainide per cardiology recommendations. He maintained sinus rhythm afterward and was discharged home on metoprolol and apixaban." }, { "kind": "case report", "citation": "Ahmed AS, Golden KM, Foreman JR, Padanilam BJ (2020). Using a smartwatch to identify the morphology of atrial flutter. HeartRhythm Case Reports 6.", "title": "Using a smartwatch to identify the morphology of atrial flutter", "url": "https://europepmc.org/article/PMC/PMC7573381", "date": "2020-06-28", "written_by": "independent", "quote": "ECG revealed typical atrial flutter with variable atrioventricular conduction" }, { "kind": "case report", "citation": "Burke J, Haigney MCP, Borne R, Krantz MJ (2020). Smartwatch detection of ventricular tachycardia: Case series. HeartRhythm Case Reports 6.", "title": "Smartwatch detection of ventricular tachycardia: Case series", "url": "https://europepmc.org/article/PMC/PMC7573479", "date": "2020-08-18", "written_by": "independent", "quote": "The patient has not experienced further symptoms suggestive of arrhythmia, nor has he reported detection of event recordings on his smartwatch" }, { "kind": "case report", "citation": "Patel D, Tarakji KG (2021). Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source: A case report. Cardiovascular Digital Health Journal 2(1):84-87.", "title": "Smartwatch diagnosis of atrial fibrillation in patient with embolic stroke of unknown source", "url": "https://europepmc.org/article/PMC/PMC8890063", "date": "2021-01-13", "written_by": "independent", "quote": "Given her elevated CHA2DS2VASC score of 5 (age, female, previous stroke, and hypertension), the patient was started on a direct oral anticoagulant, and the aspirin was stopped." }, { "kind": "case report", "citation": "Kassam N, Aziz O, Aghan E, Somji S, Mbithe H, Bapumia M, Mvungi R, Surani S (2021). Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania. International Medical Case Reports Journal 14.", "title": "Smart Watch Detection of Supraventricular Tachycardia (SVT): First Case from Tanzania", "url": "https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ", "date": "2021-08-24", "written_by": "independent", "quote": "a high resting heart rate of 210 beats/min" }, { "kind": "case report", "citation": "Itoh A (2022). Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation with a very short duration. European Heart Journal - Case Reports 6:ytac252.", "title": "Apple Watch is useful in demonstrating coffee-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC9269674", "date": "2022-06-28", "written_by": "independent", "quote": "After that, the patient stopped drinking coffee in the morning, and AF hardly occurred." }, { "kind": "case report", "citation": "Hawryszko M, Sławiński G, Kozłowski D, Lewicka E (2022). Apple Watch-guided diagnosis of AVNRT in a pregnant woman. Frontiers in Cardiovascular Medicine 9:985421.", "title": "Apple Watch-guided diagnosis of AVNRT in a pregnant woman", "url": "https://europepmc.org/article/PMC/PMC9676225", "date": "2022-11-07", "written_by": "independent", "quote": "narrow QRS complex tachycardia of 216 bpm, and short RP interval" }, { "kind": "case report", "citation": "Heringer GV, Vinson DR (2024). Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation: a case report. International Journal of Emergency Medicine 17.", "title": "Utility of smart watch in expediting diagnosis of cold drink-triggered atrial fibrillation", "url": "https://europepmc.org/article/PMC/PMC11462712", "date": "2024-10-08", "written_by": "independent", "quote": "Had it not been for his smart watch, the etiology of his transitory palpitations would have remained undiagnosed." }, { "kind": "case report", "citation": "Guarnieri G, Mapelli M, Moltrasio M, Agostoni P, Tondo C (2024). Connected health: Ventricular tachycardia detection with Apple Watch—A case report. Heliyon 10:e40595.", "title": "Connected health: Ventricular tachycardia detection with Apple Watch", "url": "https://europepmc.org/article/PMC/PMC11625252", "date": "2024-11-21", "written_by": "independent", "quote": "An alert message of 'Elevated Heart rate' from his Apple Watch® prompted him to record a single-lead ECG using the smartwatch." }, { "kind": "case report", "citation": "Rushakoff JA, Flores Rosario K, Grover P, Wang A (2025). Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report. European Heart Journal - Case Reports 9(9):ytaf415.", "title": "Smartwatch bradycardia alarms leading to a diagnosis of lamin A/C cardiomyopathy: a case report", "url": "https://europepmc.org/article/PMC/PMC12412439", "date": "2025-08-23", "written_by": "independent", "quote": "An asymptomatic 47-year-old man from Costa Rica presented to cardiology clinic for evaluation of recurrent bradycardia alarms on his smartwatch (Apple Watch)." }, { "kind": "case report", "citation": "Shroddha AD, Mukherjee I, Lambiase PD (2026). Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy. Cureus 18:e113337.", "title": "Apple Watch Saves an Athlete: Unmasking Early Detection of Arrhythmogenic Cardiomyopathy", "url": "https://europepmc.org/article/PMC/PMC13501160", "date": "2026-07-25", "written_by": "independent", "quote": "In the early hours of Thursday, at 3:00 am, he awoke with frequent ectopic beats noted on his smartwatch single-lead ECG, which progressed to a broad complex tachycardia." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Apple Watch heart-rate alarms led to an ECG-confirmed AF diagnosis and anticoagulation (UK, 2019); 16 echoes from 15 published case reports to 2026.", "account": "In a case report of 29 March 2019 (event date not reported), a 59-year-old woman attended a United Kingdom emergency department. The acute medicine service saw her (the report does not name the hospital; the author is at Ipswich Hospital). She attended because her Apple Watch Series 2 had alarmed several times overnight that her pulse exceeded 120 bpm while she was inactive. A transient ischemic attack had occurred two months earlier. An electrocardiogram (ECG) showed atrial fibrillation with a fast ventricular response. She started bisoprolol and a direct oral anticoagulant, and clopidogrel was stopped. Later case reports describe the watch's heart-rate alerts, irregular-rhythm notification or ECG app leading to confirmed atrial flutter, supraventricular and ventricular tachycardia and heart block. Treatment was by cardioversion, ablation, pacemaker or defibrillator." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The watch analyzed heart-rate signals and generated notifications about abnormal readings." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The initial report concerned an Apple Watch Series 2. Later reports involved several other watch generations." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Apple Watch Series 2 (event); echoes name Series 3, 4, 5, 6 and Ultra; eight reports do not state the model, and in Ahmed et al. the alerting tracker is unnamed (the Series 5 was the authors' post-diagnosis device)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch heart-rate notifications, Irregular Rhythm Notification and ECG app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch heart-rate, irregular-rhythm and ECG alerts leading to arrhythmia diagnosis and treatment", "headline": "Apple Watch alarms lead to an AF diagnosis and anticoagulation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "905a54793460a36fce999a8d9fc8643ced3de43055171fea943cf8b61e6956bf" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In a case report of 29 March 2019 (event date not reported), a 59-year-old woman attended a United Kingdom emergency department. The acute medicine service saw her (the report does not name the hospital; the author is at Ipswich Hospital). She attended because her Apple Watch Series 2 had alarmed several times overnight that her pulse exceeded 120 bpm while she was inactive. A transient ischemic attack had occurred two months earlier. An electrocardiogram (ECG) showed atrial fibrillation with a fast ventricular response. She started bisoprolol and a direct oral anticoagulant, and clopidogrel was stopped. Later case reports describe the watch's heart-rate alerts, irregular-rhythm notification or ECG app leading to confirmed atrial flutter, supraventricular and ventricular tachycardia and heart block. Treatment was by cardioversion, ablation, pacemaker or defibrillator.", "replication": { "produced_by": [ "The wearer owns an Apple Watch with heart-rate notifications, Irregular Rhythm Notification or the ECG app enabled", "An arrhythmia occurs while the watch is worn and the alert or recording leads the wearer to seek care", "A clinician confirms the rhythm on a 12-lead ECG or monitoring and treats it" ], "must_hold": [ "The alert or trace reaches a clinician rather than being dismissed", "Confirmatory ECG or electrophysiology testing is available", "A treatment pathway (anticoagulation, cardioversion, ablation, device) exists" ], "echoes": [ { "date": "2019-07-21", "setting": "woman in her mid-60s, emergency department, USA; low heart-rate alarms; complete heart block, pacemaker implanted (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Overbeek et al. (2019). Am J Emerg Med 37(10):1989.e5. https://www.sciencedirect.com/science/article/abs/pii/S0735675719304747" }, { "date": "2019-12-03", "setting": "68-year-old man one year after TAVI, USA; ECG app recording after syncope showed high-grade AV block; urgent biventricular pacemaker (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Yerasi et al. (2020). Eur Heart J 41(10):1096. https://academic.oup.com/eurheartj/article/41/10/1096/5651110" }, { "date": "2019-12-31", "setting": "56-year-old man, emergency department, South Africa; watch showed 150 bpm for four days; atrial flutter, anticoagulation and cardioversion (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Goldstein & Wells (2019). Oxf Med Case Reports 2019(12):omz137. https://academic.oup.com/omcr/article/2019/12/495/5691267" }, { "date": "2020-01-29", "setting": "16-year-old girl, Minneapolis, USA (authors' institution); watch captured 225 bpm and ECG; AVNRT ablated, asymptomatic at four months (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Siddeek et al. (2020). Ann Noninvasive Electrocardiol 25:e12742. https://europepmc.org/article/PMC/PMC7507696" }, { "date": "2020-04-23", "setting": "39-year-old man, Milwaukee, USA (authors' institution); watch showed heart rate 60–130 bpm during palpitations; AF cardioverted with flecainide, metoprolol and apixaban (publication date)", "model_version": "Apple Watch Series 3", "outcome": "recurred", "source": "Samal et al. (2020). Clin Case Rep 8(7). https://europepmc.org/article/PMC/PMC7364102" }, { "date": "2020-06-28", "setting": "54-year-old woman with mechanical aortic valve, Pensacola, USA (authors' institution); alerted to elevated heart rates by an unnamed fitness tracker; typical atrial flutter on ECG; outpatient ablation planned, discharged with rate control and continued anticoagulation; the authors then used an Apple Watch Series 5 in a lead II configuration to confirm the flutter morphology in the ambulatory setting (publication date)", "model_version": "Apple Watch Series 5 (authors' post-diagnosis monitoring; alerting device unnamed)", "outcome": "unknown", "source": "Ahmed et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573381" }, { "date": "2020-08-18", "setting": "60-year-old man, Denver, USA (authors' institution); single-lead ECG showed wide complex tachycardia; ARVC with VT, ablation and ICD (publication date)", "model_version": "Apple Watch", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2020-08-18", "setting": "63-year-old man, USA; watch recording labeled ventricular tachycardia; 9% VPC burden with NSVT, papillary muscle ablation (publication date)", "model_version": "smartwatch (brand not stated for this case; case 1 in the same series names an Apple Watch)", "outcome": "recurred", "source": "Burke et al. (2020). HeartRhythm Case Rep 6. https://europepmc.org/article/PMC/PMC7573479" }, { "date": "2021-01-13", "setting": "70-year-old woman after embolic stroke of unknown source, Cleveland, USA (authors' institution); irregular-rhythm notifications and ECG app; AF, DOAC started, loop recorder avoided (publication date)", "model_version": "Apple Watch (Irregular Rhythm Notification and ECG app)", "outcome": "recurred", "source": "Patel & Tarakji (2021). Cardiovasc Digit Health J 2(1):84-87. https://europepmc.org/article/PMC/PMC8890063" }, { "date": "2021-08-24", "setting": "42-year-old man, Dar es Salaam, Tanzania (authors' institution); resting heart rate 210 bpm; SVT (orthodromic AVRT), cardioversion, medication; an ablation attempt had no effect and pathway ablation was declined; managed medically (publication date)", "model_version": "Apple Watch Series 4", "outcome": "recurred", "source": "Kassam et al. (2021). Int Med Case Rep J 14. https://www.dovepress.com/smart-watch-detection-of-supraventricular-tachycardia-svt-first-case-f-peer-reviewed-fulltext-article-IMCRJ" }, { "date": "2022-06-28", "setting": "man in his early 60s, Shikokuchuo, Japan (authors' institution); ECG app recordings; coffee-triggered paroxysmal AF, trigger avoidance (publication date)", "model_version": "Apple Watch (ECG app)", "outcome": "recurred", "source": "Itoh (2022). Eur Heart J Case Rep 6:ytac252. https://europepmc.org/article/PMC/PMC9269674" }, { "date": "2022-11-07", "setting": "35-year-old woman at 20 weeks of pregnancy, Gdańsk, Poland (authors' institution); ECG app 216 bpm; AVNRT diagnosed, managed with Valsalva instruction without drugs (publication date)", "model_version": "Apple Watch Series 6", "outcome": "recurred", "source": "Hawryszko et al. (2022). Front Cardiovasc Med 9:985421. https://europepmc.org/article/PMC/PMC9676225" }, { "date": "2024-10-08", "setting": "43-year-old man, urgent care, USA; ECG app reported signs of AFib; paroxysmal AF, trigger avoidance and aspirin, no recurrence (publication date)", "model_version": "Apple Watch Ultra", "outcome": "recurred", "source": "Heringer & Vinson (2024). Int J Emerg Med 17. https://europepmc.org/article/PMC/PMC11462712" }, { "date": "2024-11-21", "setting": "60-year-old man, Milan, Italy (authors' institution); “Elevated Heart rate” alert then ECG; sustained VT at 183 bpm, radiofrequency ablation (publication date)", "model_version": "Apple Watch Series 5", "outcome": "recurred", "source": "Guarnieri et al. (2024). Heliyon 10:e40595. https://europepmc.org/article/PMC/PMC11625252" }, { "date": "2025-08-23", "setting": "47-year-old asymptomatic man from Costa Rica, Duke University Medical Center, USA; recurrent low heart-rate alarms; LMNA cardiomyopathy, CRT-D implanted, ejection fraction improved (publication date)", "model_version": "Apple Watch (low heart-rate notification)", "outcome": "recurred", "source": "Rushakoff et al. (2025). Eur Heart J Case Rep 9(9):ytaf415. https://europepmc.org/article/PMC/PMC12412439" }, { "date": "2026-07-25", "setting": "33-year-old male footballer, London, UK; single-lead ECG showed ectopy progressing to broad complex tachycardia; arrhythmogenic cardiomyopathy, S-ICD, flecainide and nadolol (publication date)", "model_version": "Apple Watch (model not stated)", "outcome": "recurred", "source": "Shroddha et al. (2026). Cureus 18:e113337. https://europepmc.org/article/PMC/PMC13501160" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0005", "title": "First direct decoding of full words from the cortex of a paralyzed, anarthric man (UCSF, BRAVO trial)", "summary": "128-electrode ECoG and deep-learning decoder let a man mute since 2003 produce sentences at 15.2 wpm from a 50-word vocabulary", "date_observed": "2019-04-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At the University of California, San Francisco, a 36-year-old man received a 128-electrode subdural electrocorticography array over sensorimotor cortex in the BRAVO trial (NCT03698149). He had anarthria and severe spastic quadriparesis from an extensive pontine stroke at age 20 and is known in press by the pseudonym Pancho. Deep-learning models detected his attempted speech and classified words from a 50-word vocabulary, with a natural-language model and Viterbi decoder assembling sentences. He produced sentences at a median 15.2 words per minute with a median word error rate of 25.6%. He previously typed about five words per minute with a head-controlled pointer (Moses et al., NEJM, 15 July 2021). The paper dates implantation to February 2019 and the start of data collection to April 2019. There were 50 sessions over 81 weeks at the participant's residence or a nearby office. The session on which the reported sentence decoding was achieved is not dated. So the start of data collection (1 April 2019) is used as the observation date.", "category": "benefit created", "unexpected": false, "purpose": "Built to decode attempted speech into words and sentences for a person with anarthria. Restoring word-level communication was the intended benefit and is what occurred.", "system": "UCSF speech neuroprosthesis (BRAVO trial)", "model_version": "128-electrode high-density ECoG array (16-by-8 lattice, 4 mm spacing); deep-learning speech-detection and word-classification models with natural-language model and Viterbi decoder; 50-word vocabulary", "developer": "UCSF Chang Lab", "deployer": "University of California, San Francisco", "location": "San Francisco, United States", "domain": "Healthcare / assistive communication", "segment": "Post-stroke anarthria", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Material benefit to one identifiable person: first decoding of his own full words, three times faster than his pointer typing. But limited to a 50-word vocabulary in research sessions." } ], "ai_role": { "status": "assessed", "statement": "Deep-learning models detected attempted speech in 98% of attempts and classified words. A language model with Viterbi decoding assembled sentences. The output depended entirely on these models. Funding included a research contract under Facebook's Sponsored Academic Research Agreement. The paper states that no study hardware or data were transferred to any sponsor and that author disclosure forms are available at NEJM.org." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Moses DA, Metzger SL, Liu JR, et al. (2021). Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria. N Engl J Med.", "title": "Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8972947/", "date": "2021-07-15", "written_by": "makers", "quote": "median rate of 15.2 words per minute, with a median word error rate of 25.6%" }, { "kind": "news report", "citation": "Advisory Board (2021). For the first time since 2003, this paralyzed man can 'speak'. Advisory Board Daily Briefing.", "title": "For the first time since 2003, this paralyzed man can 'speak'", "url": "https://www.advisory.com/daily-briefing/2021/07/16/paralyzed-man", "date": "2021-07-16", "written_by": "independent", "quote": "To our knowledge, this is the first successful demonstration of direct decoding of full words from the brain activity of someone who is paralyzed and cannot speak." }, { "kind": "other", "citation": "Reis e Sousa C, Poirier E (2021). Scientists Detect Brain Signals to Help a Paralyzed Man Speak. Harvard Science in the News.", "title": "Scientists Detect Brain Signals to Help a Paralyzed Man Speak", "url": "https://sites.harvard.edu/sitn/2021/09/22/scientists-detect-brain-signals-to-help-a-paralyzed-man-speak", "date": "2021-09-22", "written_by": "independent", "quote": "In this way, the electrodes allowed Pancho to communicate about 15 words per minute with near 50% accuracy." } ], "replication": { "produced_by": [ "Preserved speech-motor cortical pathways more than 15 years after loss of speech", "High-density ECoG array over sensorimotor cortex", "Deep-learning models trained on 22 hours of attempted-speech data plus language-model decoding" ], "must_hold": [ "Participant can attempt speech and retains intact cognition", "Implant remains stable with adequate signal quality", "Accumulated training data maintained over time" ], "echoes": [ { "date": "2023-08-23", "setting": "UCSF, a different participant (47-year-old woman, brainstem stroke 2005): 253-channel ECoG, 78 words per minute, 1,024-word vocabulary, voice and avatar", "model_version": "253-channel ECoG; bidirectional RNN decoders", "outcome": "recurred", "source": "Metzger SL, et al. (2023). A high-performance neuroprosthesis for speech decoding and avatar control. Nature. https://pmc.ncbi.nlm.nih.gov/articles/PMC10826467/" }, { "date": "2024-05-20", "setting": "UCSF, same participant (the full text at PMC11554235 describes a 36-year-old Spanish-English bilingual with anarthria and severe spastic quadriparesis after a bilateral pontine stroke, a 128-electrode ECoG array and the BRAVO trial, and refers to initial work with this participant): bilingual (Spanish-English) sentence decoding without specifying the target language", "model_version": "ECoG with deep-learning and bilingual natural-language models", "outcome": "recurred", "source": "Silva AB, et al. (2024). A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages. Nature Biomedical Engineering. doi:10.1038/s41551-024-01207-5" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "732", "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations", "url": "https://incidentdatabase.ai/cite/732", "severity": null, "group": "personal", "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech." }, "headline": "UCSF neuroprosthesis lets Pancho produce sentences at 15.2 wpm", "metric": "sentences at a median 15.2 words per minute with a median word error rate of 25.6%", "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/732", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Moved the date observed from the publication date to April 2019, when the paper says data collection began after the February 2019 implant, replaced the unsupported “no competing interests” claim with the paper's sponsor and disclosure-form statements, added a taxonomy note on why a research-session demonstration is filed as a benefit created or restored, and verified the Silva 2024 echo as the same participant against the PMC full text.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8972947/; https://pmc.ncbi.nlm.nih.gov/articles/PMC11554235/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://changlab.ucsf.edu/; https://en.wikipedia.org/wiki/University_of_California,_Berkeley", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, one other independent source and the makers' peer-reviewed study. 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He had anarthria and severe spastic quadriparesis from an extensive pontine stroke at age 20 and is known in press by the pseudonym Pancho. Deep-learning models detected his attempted speech and classified words from a 50-word vocabulary, with a natural-language model and Viterbi decoder assembling sentences. He produced sentences at a median 15.2 words per minute with a median word error rate of 25.6%. He previously typed about five words per minute with a head-controlled pointer (Moses et al., NEJM, 15 July 2021). The paper dates implantation to February 2019 and the start of data collection to April 2019. There were 50 sessions over 81 weeks at the participant's residence or a nearby office. The session on which the reported sentence decoding was achieved is not dated. So the start of data collection (1 April 2019) is used as the observation date.", "replication": { "produced_by": [ "Preserved speech-motor cortical pathways more than 15 years after loss of speech", "High-density ECoG array over sensorimotor cortex", "Deep-learning models trained on 22 hours of attempted-speech data plus language-model decoding" ], "must_hold": [ "Participant can attempt speech and retains intact cognition", "Implant remains stable with adequate signal quality", "Accumulated training data maintained over time" ], "echoes": [ { "date": "2023-08-23", "setting": "UCSF, a different participant (47-year-old woman, brainstem stroke 2005): 253-channel ECoG, 78 words per minute, 1,024-word vocabulary, voice and avatar", "model_version": "253-channel ECoG; bidirectional RNN decoders", "outcome": "recurred", "source": "Metzger SL, et al. (2023). A high-performance neuroprosthesis for speech decoding and avatar control. Nature. https://pmc.ncbi.nlm.nih.gov/articles/PMC10826467/" }, { "date": "2024-05-20", "setting": "UCSF, same participant (the full text at PMC11554235 describes a 36-year-old Spanish-English bilingual with anarthria and severe spastic quadriparesis after a bilateral pontine stroke, a 128-electrode ECoG array and the BRAVO trial, and refers to initial work with this participant): bilingual (Spanish-English) sentence decoding without specifying the target language", "model_version": "ECoG with deep-learning and bilingual natural-language models", "outcome": "recurred", "source": "Silva AB, et al. (2024). A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages. Nature Biomedical Engineering. doi:10.1038/s41551-024-01207-5" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 35, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0230", "title": "Thorn's Spotlight matches a missing child's NCMEC photo to online sex ads; she may have been recovered within weeks", "summary": "In April 2019 a California officer ran a NCMEC missing-child photo through Thorn's Spotlight; Rekognition matching returned sex ads with the girl and, per Thorn's CEO, she was recovered within weeks.", "date_observed": "2019-06-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.", "category": "benefit created", "unexpected": false, "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements.", "system": "Spotlight (Thorn), using Amazon Rekognition", "model_version": null, "developer": "Thorn (with Amazon Rekognition for face matching)", "deployer": "An unnamed California law enforcement officer and agency", "location": null, "domain": "Anti-trafficking / child protection", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": "The recovery is reported only by the maker's CEO, and the AI's documented part was returning the ads.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "A child sold for weeks was recovered and removed from trauma, per Thorn's CEO. No independent confirmation of the recovery is among the sources." } ], "ai_role": { "status": "assessed", "statement": "The face match that surfaced the ads is attributed to Amazon Rekognition inside Spotlight. The recovery itself came from conventional police work. Everything about this case rests on Thorn's CEO. Snopes documents that Thorn's aggregate figures derive from user surveys and were widely misreported." }, "evidence": [ { "kind": "news report", "citation": "Tom Simonite, WIRED, 19 Jun 2019", "title": "How Facial Recognition Is Fighting Child Sex Trafficking", "url": "https://www.wired.com/story/how-facial-recognition-fighting-child-sex-trafficking/", "date": "2019-06-19", "written_by": "independent", "quote": "Using Amazon’s facial recognition technology, Spotlight quickly returned a list of online sex ads featuring the girl’s photo." }, { "kind": "other", "citation": "Dan MacGuill, Snopes fact check, 4 Sep 2018", "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?", "url": "https://www.snopes.com/fact-check/kutcher-software-child-trafficking/", "date": "2018-09-04", "written_by": "independent", "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked." } ], "replication": { "produced_by": [ "A reference photo of the missing child", "An archive of scraped escort ads with faces indexed for similarity search", "An officer with Spotlight access who follows the matches with investigation" ], "must_hold": [ "Ads with usable face images must exist for the victim", "Legal access to the ad archive and face matching", "Investigative capacity to act on matches quickly" ], "echoes": [] }, "paired_incident": null, "headline": "Spotlight may have led to a missing child's recovery in weeks", "metric": "claimed its tools helped identify 5,791 child victims and rescue 103", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later development is established.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Thorn_(organization)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0230", "catalog_version": "1.0.0", "source_fingerprint": "f171181cd195b42057a829879705dc56f1e3a4a602258fc3d7c3279d89dea80a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0230-source-0001", "AIBD-0230-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Thorn (with Amazon Rekognition for face matching)", "deployer": "An unnamed California law enforcement officer and agency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The face match that surfaced the ads is attributed to Amazon Rekognition inside Spotlight. The recovery itself came from conventional police work. Everything about this case rests on Thorn's CEO. Snopes documents that Thorn's aggregate figures derive from user surveys and were widely misreported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The face match that surfaced the ads is attributed to Amazon Rekognition inside Spotlight. The recovery itself came from conventional police work. Everything about this case rests on Thorn's CEO. Snopes documents that Thorn's aggregate figures derive from user surveys and were widely misreported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "A child sold for weeks was recovered and removed from trauma, per Thorn's CEO. No independent confirmation of the recovery is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and one other independent source. 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "claimed its tools helped identify 5,791 child victims and rescue 103", "editor_note": "" } }, 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"not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0230" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence", "taxonomy_note": "The recovery is reported only by the maker's CEO, and the AI's documented part was returning the ads." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "A child sold for weeks was recovered and removed from trauma, per Thorn's CEO. No independent confirmation of the recovery is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Help law-enforcement investigators find underage sex-trafficking victims by matching faces and text across online escort advertisements." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-06-19", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Thorn_(organization)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A reference photo of the missing child", "An archive of scraped escort ads with faces indexed for similarity search", "An officer with Spotlight access who follows the matches with investigation" ], "must_hold": [ "Ads with usable face images must exist for the victim", "Legal access to the ad archive and face matching", "Investigative capacity to act on matches quickly" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Thorn_(organization)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Anti-trafficking / child protection", "segment": "Government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Tom Simonite, WIRED, 19 Jun 2019", "title": "How Facial Recognition Is Fighting Child Sex Trafficking", "url": "https://www.wired.com/story/how-facial-recognition-fighting-child-sex-trafficking/", "date": "2019-06-19", "written_by": "independent", "quote": "Using Amazon’s facial recognition technology, Spotlight quickly returned a list of online sex ads featuring the girl’s photo." }, { "kind": "other", "citation": "Dan MacGuill, Snopes fact check, 4 Sep 2018", "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?", "url": "https://www.snopes.com/fact-check/kutcher-software-child-trafficking/", "date": "2018-09-04", "written_by": "independent", "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0230-source-0001", "AIBD-0230-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Tom Simonite, WIRED, 19 Jun 2019", "title": "How Facial Recognition Is Fighting Child Sex Trafficking", "url": "https://www.wired.com/story/how-facial-recognition-fighting-child-sex-trafficking/", "date": "2019-06-19", "written_by": "independent", "quote": "Using Amazon’s facial recognition technology, Spotlight quickly returned a list of online sex ads featuring the girl’s photo." }, { "kind": "other", "citation": "Dan MacGuill, Snopes fact check, 4 Sep 2018", "title": "Did Ashton Kutcher's Software Help Rescue 6,000 Children from Sex Trafficking?", "url": "https://www.snopes.com/fact-check/kutcher-software-child-trafficking/", "date": "2018-09-04", "written_by": "independent", "quote": "As stated by Thorn themselves, the organization's digital tools had helped identify -- not rescue -- almost 6,000 child victims, a distinction that has sometimes been overlooked." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "In April 2019 a California officer ran a NCMEC missing-child photo through Thorn's Spotlight; Rekognition matching returned sex ads with the girl and, per Thorn's CEO, she was recovered within weeks.", "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Spotlight (Thorn), using Amazon Rekognition" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Thorn (with Amazon Rekognition for face matching)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Thorn's Spotlight matches a missing child's NCMEC photo to online sex ads; she may have been recovered within weeks", "headline": "Spotlight may have led to a missing child's recovery in weeks" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f171181cd195b42057a829879705dc56f1e3a4a602258fc3d7c3279d89dea80a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The source places the case in April 2019 without a day. Thorn CEO Julie Cordua, speaking at an Amazon conference, was quoted by WIRED's Tom Simonite. She said a California law enforcement officer screenshotted a missing child's picture from a National Center for Missing and Exploited Children post. The officer ran it through Spotlight, Thorn's investigator tool that matches faces and other clues in online sex ads. Using Amazon's facial recognition, Spotlight returned a list of ads featuring the girl, who had been sold for weeks. More traditional police work followed and, she said, the child was recovered within weeks. Snopes notes Thorn's 2017 impact report claimed its tools helped identify 5,791 child victims and rescue 103. The figures are from Thorn's surveys of police users, and viral claims conflated identification with rescue. No police or court record of this case is among the sources.", "replication": { "produced_by": [ "A reference photo of the missing child", "An archive of scraped escort ads with faces indexed for similarity search", "An officer with Spotlight access who follows the matches with investigation" ], "must_hold": [ "Ads with usable face images must exist for the victim", "Legal access to the ad archive and face matching", "Investigative capacity to act on matches quickly" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0347", "title": "Indonesia captures the blacklisted MV NIKA on 12 July 2019 after INTERPOL tracking supported by OceanMind and Global Fishing Watch; the tracking was by analysts, not an AI detection", "summary": "MV NIKA seized by Indonesia 12 July 2019 after INTERPOL tracking with OceanMind and GFW; captain convicted, owner fined, vessel forfeited; no cited source documents an AI detection.", "date_observed": "2019-07-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "INTERPOL reported on 22 July 2019 that the MV NIKA had been detained by Indonesian authorities. The vessel was suspected of illegal fishing in the Southern Ocean. Its owner also owned the blacklisted STS 50 intercepted in Indonesia in 2018. INTERPOL tracked the vessel's movement with support from the UK not-for-profit OceanMind, sending daily reports to Indonesia, New Zealand, Panama, the UK and the US. Hourly updates aided by Global Fishing Watch (GFW) followed as it approached Indonesian waters. GFW's account (23 July 2019) says GFW analyst Imam Prakoso helped track the vessel from February 2019 after it illegally switched off its tracking system. It says a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour exchanged information. GFW analysts helped predict its course and identify rendezvous points. Indonesian patrol boats ORCA 2 and ORCA 3 intercepted it on 12 July 2019 at 08:06 local time. The court outcome comes from a UK Government Blue Belt blog of 5 June 2021. That blog was no longer available as of 20 October 2026. The Indonesian Supreme Court gave its verdict on 27 February 2020, the captain was convicted, the owner fined Rp300,000,000 and the vessel forfeited. None of the sources describes a machine-learning or AI detection. OceanMind's homepage says only, in general terms, that it uses satellites, AI and human expertise.", "category": "protective response", "unexpected": false, "purpose": "Vessel tracking and analysis to support fisheries enforcement against illegal, unreported and unregulated fishing. The capture was the intended use, but the sources attribute it to analysts and inter-agency coordination rather than to an AI output.", "system": "Global Fishing Watch vessel-tracking platform and analysts; OceanMind analysis for INTERPOL (no AI component documented for this case)", "model_version": null, "developer": "Global Fishing Watch; OceanMind", "deployer": "INTERPOL (Global Fisheries Enforcement program); Indonesian naval and fisheries authorities (patrol boats ORCA 2 and ORCA 3)", "location": "Indonesian exclusive economic zone, Indonesia", "domain": "Fisheries enforcement / illegal, unreported and unregulated fishing", "segment": "International police cooperation and national maritime enforcement", "benefit_type": "Reduced Violence", "taxonomy_note": "The crime is illegal fishing, the AI role is undocumented, and the good is a seizure and conviction rather than less violence.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified in any cited source." }, { "group": "organizational", "depth": null, "reason": "Indonesian authorities and INTERPOL obtained a capture, a conviction and a forfeiture. No cited source attributes any part of the result to an AI output." }, { "group": "societal", "depth": null, "reason": "One blacklisted vessel removed from Southern Ocean fishing. The contribution of any AI system is undocumented and the deterrent effect is not quantified." } ], "ai_role": { "status": "unassessed", "statement": "No cited source documents an AI or machine-learning role. INTERPOL's release says it tracked the vessel with support from OceanMind and that hourly updates were aided by contributions from Global Fishing Watch. GFW's own article credits named analysts who tracked AIS data, predicted the course and identified rendezvous points. It does not mention algorithms, machine learning or automated detection. OceanMind's homepage states only that it uses satellites, AI and human expertise in general. The AI role is thus undocumented rather than established. The account comes from INTERPOL, GFW, and the Blue Belt blog. The court outcome (Supreme Court verdict of 27 February 2020, conviction, Rp300,000,000 fine, forfeiture) comes from the Blue Belt blog. The Blue Belt post of 5 June 2021 is no longer available, and no archived copy is cited." }, "evidence": [ { "kind": "press release", "citation": "INTERPOL (2019). INTERPOL supports apprehension of vessel suspected of illegal fishing. News release, 22 July 2019.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "INTERPOL tracked the movement of the MV NIKA with support from OceanMind, sending daily reports to the relevant countries including Indonesia, New Zealand, Panama, the UK and the US." }, { "kind": "press release", "citation": "INTERPOL (2019). Same release, paragraph on the approach to Indonesian waters.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing (Global Fishing Watch paragraph)", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "As it approached Indonesian waters, additional updates were sent to the national authorities hourly, aided by contributions from Global Fishing Watch." }, { "kind": "press release", "citation": "Global Fishing Watch (2019). The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it. globalfishingwatch.org, 23 July 2019.", "title": "The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "GFW analysts helped predict the MV NIKA's course and identify rendezvous points where the patrol vessels could intercept" }, { "kind": "press release", "citation": "Global Fishing Watch (2019). Same article, paragraph on the live coordination.", "title": "The capture of the MV NIKA (coordination paragraph)", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour, swapped information on its every move" }, { "kind": "press release", "citation": "OceanMind (n.d.). Homepage, general description of methods (no mention of NIKA).", "title": "OceanMind homepage", "url": "https://oceanmind.global/", "date": null, "written_by": "makers", "quote": "For more than a decade, we have used satellites, AI, and human expertise to provide crucial insights that enable others to protect the ocean for people and planet." } ], "replication": { "produced_by": [ "A blacklisted vessel whose identity and ownership were already known to INTERPOL and CCAMLR", "Continuous tracking by OceanMind and GFW analysts with daily, then hourly, reports to coastal states", "Indonesian patrol vessels positioned at predicted rendezvous points", "Indonesian prosecution leading to a Supreme Court verdict" ], "must_hold": [ "A coastal state willing and able to intercept and prosecute", "Analyst capacity to follow a vessel that has switched off its tracking system", "Information sharing between INTERPOL, NGOs and national agencies in near real time", "Documentation of what, if anything, an automated system contributed, which is absent here" ], "echoes": [ { "date": null, "setting": "STS 50, a blacklisted vessel of the same owner, intercepted in Indonesia in 2018 (INTERPOL release); AI role equally undocumented", "model_version": null, "outcome": "unknown", "source": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing" } ] }, "paired_incident": null, "headline": "GFW analysts help Indonesia seize MV NIKA; no AI detection", "metric": "the captain was convicted, the owner fined Rp300,000,000 and the vessel forfeited", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The reported verdict of 27 February 2020, conviction, fine, and forfeiture rest on a UK Government Blue Belt blog that is no longer available. They lack independent confirmation in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "France", "unrated_because": "the seizure is documented, the AI's part is not", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the seizure is documented, the AI's part is not.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Global_Fishing_Watch; https://www.interpol.int/en/Who-we-are/What-is-INTERPOL", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to INTERPOL.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: two press releases from the makers and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0347", "catalog_version": "1.0.0", "source_fingerprint": "c8d0aa4fd21ddc071c29e698a7b48458113030802ec4971dabf6dec4f5108888", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0347-source-0001", "AIBD-0347-source-0002", "AIBD-0347-source-0003", "AIBD-0347-source-0004", "AIBD-0347-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Global Fishing Watch; OceanMind", "deployer": "INTERPOL (Global Fisheries Enforcement program); Indonesian naval and fisheries authorities (patrol boats ORCA 2 and ORCA 3)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "display": { "answer": "INTERPOL received vessel-tracking assistance from OceanMind and Global Fishing Watch. 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The court outcome (Supreme Court verdict of 27 February 2020, conviction, Rp300,000,000 fine, forfeiture) comes from the Blue Belt blog. 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The Blue Belt account of the court outcome is no longer available, and the entry has no archived copy.", "editor_note": "" } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The reported verdict of 27 February 2020, conviction, fine, and forfeiture rest on a UK Government Blue Belt blog that is no longer available. They lack independent confirmation in the cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Analysts tracked the vessel’s signals, predicted its course, and identified possible rendezvous points." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0347" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence", "taxonomy_note": "The crime is illegal fishing, the AI role is undocumented, and the good is a seizure and conviction rather than less violence." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "INTERPOL reported on 22 July 2019 that the MV NIKA had been detained by Indonesian authorities. The vessel was suspected of illegal fishing in the Southern Ocean. Its owner also owned the blacklisted STS 50 intercepted in Indonesia in 2018. INTERPOL tracked the vessel's movement with support from the UK not-for-profit OceanMind, sending daily reports to Indonesia, New Zealand, Panama, the UK and the US. Hourly updates aided by Global Fishing Watch (GFW) followed as it approached Indonesian waters. GFW's account (23 July 2019) says GFW analyst Imam Prakoso helped track the vessel from February 2019 after it illegally switched off its tracking system. It says a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour exchanged information. GFW analysts helped predict its course and identify rendezvous points. Indonesian patrol boats ORCA 2 and ORCA 3 intercepted it on 12 July 2019 at 08:06 local time. The court outcome comes from a UK Government Blue Belt blog of 5 June 2021. That blog was no longer available as of 20 October 2026. The Indonesian Supreme Court gave its verdict on 27 February 2020, the captain was convicted, the owner fined Rp300,000,000 and the vessel forfeited. None of the sources describes a machine-learning or AI detection. OceanMind's homepage says only, in general terms, that it uses satellites, AI and human expertise.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified in any cited source." }, { "group": "organizational", "reason": "Indonesian authorities and INTERPOL obtained a capture, a conviction and a forfeiture. No cited source attributes any part of the result to an AI output." }, { "group": "societal", "reason": "One blacklisted vessel removed from Southern Ocean fishing. The contribution of any AI system is undocumented and the deterrent effect is not quantified." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Vessel tracking and analysis to support fisheries enforcement against illegal, unreported and unregulated fishing. The capture was the intended use, but the sources attribute it to analysts and inter-agency coordination rather than to an AI output." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Indonesian exclusive economic zone, Indonesia", "developer_country": "United States", "deployer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Vessel tracking and analysis to support fisheries enforcement against illegal, unreported and unregulated fishing. The capture was the intended use, but the sources attribute it to analysts and inter-agency coordination rather than to an AI output." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-07-12", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the seizure is documented, the AI's part is not.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Global_Fishing_Watch; https://www.interpol.int/en/Who-we-are/What-is-INTERPOL", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to INTERPOL.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A blacklisted vessel whose identity and ownership were already known to INTERPOL and CCAMLR", "Continuous tracking by OceanMind and GFW analysts with daily, then hourly, reports to coastal states", "Indonesian patrol vessels positioned at predicted rendezvous points", "Indonesian prosecution leading to a Supreme Court verdict" ], "must_hold": [ "A coastal state willing and able to intercept and prosecute", "Analyst capacity to follow a vessel that has switched off its tracking system", "Information sharing between INTERPOL, NGOs and national agencies in near real time", "Documentation of what, if anything, an automated system contributed, which is absent here" ], "echoes": [ { "setting": "STS 50, a blacklisted vessel of the same owner, intercepted in Indonesia in 2018 (INTERPOL release); AI role equally undocumented", "outcome": "unknown", "source": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A blacklisted vessel whose identity and ownership were already known to INTERPOL and CCAMLR", "Continuous tracking by OceanMind and GFW analysts with daily, then hourly, reports to coastal states", "Indonesian patrol vessels positioned at predicted rendezvous points", "Indonesian prosecution leading to a Supreme Court verdict" ], "must_hold": [ "A coastal state willing and able to intercept and prosecute", "Analyst capacity to follow a vessel that has switched off its tracking system", "Information sharing between INTERPOL, NGOs and national agencies in near real time", "Documentation of what, if anything, an automated system contributed, which is absent here" ], "echoes": [ { "setting": "STS 50, a blacklisted vessel of the same owner, intercepted in Indonesia in 2018 (INTERPOL release); AI role equally undocumented", "outcome": "unknown", "source": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the seizure is documented, the AI's part is not.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Global_Fishing_Watch; https://www.interpol.int/en/Who-we-are/What-is-INTERPOL", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to INTERPOL.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Fisheries enforcement / illegal, unreported and unregulated fishing", "segment": "International police cooperation and national maritime enforcement" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "INTERPOL (2019). INTERPOL supports apprehension of vessel suspected of illegal fishing. News release, 22 July 2019.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "INTERPOL tracked the movement of the MV NIKA with support from OceanMind, sending daily reports to the relevant countries including Indonesia, New Zealand, Panama, the UK and the US." }, { "kind": "press release", "citation": "INTERPOL (2019). Same release, paragraph on the approach to Indonesian waters.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing (Global Fishing Watch paragraph)", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "As it approached Indonesian waters, additional updates were sent to the national authorities hourly, aided by contributions from Global Fishing Watch." }, { "kind": "press release", "citation": "Global Fishing Watch (2019). The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it. globalfishingwatch.org, 23 July 2019.", "title": "The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "GFW analysts helped predict the MV NIKA's course and identify rendezvous points where the patrol vessels could intercept" }, { "kind": "press release", "citation": "Global Fishing Watch (2019). Same article, paragraph on the live coordination.", "title": "The capture of the MV NIKA (coordination paragraph)", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour, swapped information on its every move" }, { "kind": "press release", "citation": "OceanMind (n.d.). Homepage, general description of methods (no mention of NIKA).", "title": "OceanMind homepage", "url": "https://oceanmind.global/", "written_by": "makers", "quote": "For more than a decade, we have used satellites, AI, and human expertise to provide crucial insights that enable others to protect the ocean for people and planet." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0347-source-0001", "AIBD-0347-source-0002", "AIBD-0347-source-0003", "AIBD-0347-source-0004", "AIBD-0347-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "INTERPOL (2019). INTERPOL supports apprehension of vessel suspected of illegal fishing. News release, 22 July 2019.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "INTERPOL tracked the movement of the MV NIKA with support from OceanMind, sending daily reports to the relevant countries including Indonesia, New Zealand, Panama, the UK and the US." }, { "kind": "press release", "citation": "INTERPOL (2019). Same release, paragraph on the approach to Indonesian waters.", "title": "INTERPOL supports apprehension of vessel suspected of illegal fishing (Global Fishing Watch paragraph)", "url": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing", "date": "2019-07-22", "written_by": "deployer", "quote": "As it approached Indonesian waters, additional updates were sent to the national authorities hourly, aided by contributions from Global Fishing Watch." }, { "kind": "press release", "citation": "Global Fishing Watch (2019). The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it. globalfishingwatch.org, 23 July 2019.", "title": "The capture of the MV NIKA: a case of illicit fishing and a showcase for how to beat it", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "GFW analysts helped predict the MV NIKA's course and identify rendezvous points where the patrol vessels could intercept" }, { "kind": "press release", "citation": "Global Fishing Watch (2019). Same article, paragraph on the live coordination.", "title": "The capture of the MV NIKA (coordination paragraph)", "url": "https://globalfishingwatch.org/article/capture-mv-nika-case/", "date": "2019-07-23", "written_by": "makers", "quote": "a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour, swapped information on its every move" }, { "kind": "press release", "citation": "OceanMind (n.d.). Homepage, general description of methods (no mention of NIKA).", "title": "OceanMind homepage", "url": "https://oceanmind.global/", "written_by": "makers", "quote": "For more than a decade, we have used satellites, AI, and human expertise to provide crucial insights that enable others to protect the ocean for people and planet." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "MV NIKA seized by Indonesia 12 July 2019 after INTERPOL tracking with OceanMind and GFW; captain convicted, owner fined, vessel forfeited; no cited source documents an AI detection.", "account": "INTERPOL reported on 22 July 2019 that the MV NIKA had been detained by Indonesian authorities. The vessel was suspected of illegal fishing in the Southern Ocean. Its owner also owned the blacklisted STS 50 intercepted in Indonesia in 2018. INTERPOL tracked the vessel's movement with support from the UK not-for-profit OceanMind, sending daily reports to Indonesia, New Zealand, Panama, the UK and the US. Hourly updates aided by Global Fishing Watch (GFW) followed as it approached Indonesian waters. GFW's account (23 July 2019) says GFW analyst Imam Prakoso helped track the vessel from February 2019 after it illegally switched off its tracking system. It says a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour exchanged information. GFW analysts helped predict its course and identify rendezvous points. Indonesian patrol boats ORCA 2 and ORCA 3 intercepted it on 12 July 2019 at 08:06 local time. The court outcome comes from a UK Government Blue Belt blog of 5 June 2021. That blog was no longer available as of 20 October 2026. The Indonesian Supreme Court gave its verdict on 27 February 2020, the captain was convicted, the owner fined Rp300,000,000 and the vessel forfeited. None of the sources describes a machine-learning or AI detection. OceanMind's homepage says only, in general terms, that it uses satellites, AI and human expertise." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Global Fishing Watch vessel-tracking platform and analysts; OceanMind analysis for INTERPOL (no AI component documented for this case)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Global Fishing Watch; OceanMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Indonesia captures the blacklisted MV NIKA on 12 July 2019 after INTERPOL tracking supported by OceanMind and Global Fishing Watch; the tracking was by analysts, not an AI detection", "headline": "GFW analysts help Indonesia seize MV NIKA; no AI detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c8d0aa4fd21ddc071c29e698a7b48458113030802ec4971dabf6dec4f5108888" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "INTERPOL reported on 22 July 2019 that the MV NIKA had been detained by Indonesian authorities. The vessel was suspected of illegal fishing in the Southern Ocean. Its owner also owned the blacklisted STS 50 intercepted in Indonesia in 2018. INTERPOL tracked the vessel's movement with support from the UK not-for-profit OceanMind, sending daily reports to Indonesia, New Zealand, Panama, the UK and the US. Hourly updates aided by Global Fishing Watch (GFW) followed as it approached Indonesian waters. GFW's account (23 July 2019) says GFW analyst Imam Prakoso helped track the vessel from February 2019 after it illegally switched off its tracking system. It says a live multi-way communication between Indonesian naval and fishery officials, INTERPOL and GFW analyst Charles Kilgour exchanged information. GFW analysts helped predict its course and identify rendezvous points. Indonesian patrol boats ORCA 2 and ORCA 3 intercepted it on 12 July 2019 at 08:06 local time. The court outcome comes from a UK Government Blue Belt blog of 5 June 2021. That blog was no longer available as of 20 October 2026. The Indonesian Supreme Court gave its verdict on 27 February 2020, the captain was convicted, the owner fined Rp300,000,000 and the vessel forfeited. None of the sources describes a machine-learning or AI detection. OceanMind's homepage says only, in general terms, that it uses satellites, AI and human expertise.", "replication": { "produced_by": [ "A blacklisted vessel whose identity and ownership were already known to INTERPOL and CCAMLR", "Continuous tracking by OceanMind and GFW analysts with daily, then hourly, reports to coastal states", "Indonesian patrol vessels positioned at predicted rendezvous points", "Indonesian prosecution leading to a Supreme Court verdict" ], "must_hold": [ "A coastal state willing and able to intercept and prosecute", "Analyst capacity to follow a vessel that has switched off its tracking system", "Information sharing between INTERPOL, NGOs and national agencies in near real time", "Documentation of what, if anything, an automated system contributed, which is absent here" ], "echoes": [ { "setting": "STS 50, a blacklisted vessel of the same owner, intercepted in Indonesia in 2018 (INTERPOL release); AI role equally undocumented", "outcome": "unknown", "source": "https://www.interpol.int/en/News-and-Events/News/2019/INTERPOL-supports-apprehension-of-vessel-suspected-of-illegal-fishing" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0175", "title": "More loan approvals at lower rates in a simulation", "summary": "Upstart estimated 27% more approvals and 16% lower annual percentage rates in a simulation. A 2024 independent review found approval disparities for Black applicants.", "date_observed": "2019-08-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Consumer Financial Protection Bureau reported results from the compliance plan attached to its first no-action letter, granted to Upstart Network in September 2017. The results were in a 6 August 2019 blog post by Patrice Alexander Ficklin and Paul Watkins. Upstart compared its tested model with a hypothetical traditional model using conventional variables. It reported that the tested model approves 27% more applicants and yields 16% lower average APRs for approved loans. Acceptance rates were up 23–29% and APRs down 15–17% across racial, ethnic and sex categories. Near-prime applicants (FICO 620–660) were approved approximately twice as frequently. Applicants under 25 were 32% more likely to be approved and those with incomes under $50,000 13% more likely. The post states that the results for minority, female and 62-and-older applicants show no disparities requiring further fair-lending analysis. The post says that they reflect the net effect of both the alternative data and the machine-learning methodology. Upstart supplied the analysis. The CFPB expressly stated that it did not separately replicate it. On 8 June 2022 the CFPB terminated the 2020 no-action letter at Upstart's request after Upstart planned to expand the variables in its model. On 27 March 2024 the NAACP Legal Defense Fund and the Student Borrower Protection Center announced Relman Colfax's final independent-monitorship report. It found no proxies for protected classes and no pricing disparities but identified approval disparities for Black applicants. Upstart rejected the monitor's proposed less discriminatory alternative model.", "category": "general benefit", "unexpected": false, "purpose": "Underwrite and price unsecured consumer loans using alternative data and machine learning.", "system": "Upstart Network underwriting and pricing model", "model_version": null, "developer": "Upstart Network, Inc.", "deployer": "Upstart Network, Inc.", "location": null, "domain": "Consumer credit", "segment": "Unsecured personal loans and credit access", "benefit_type": "Increased Inclusion", "taxonomy_note": "The good is credit approval for applicants a traditional model would reject, which the type's “acceptance” names only broadly, and a 2024 monitor found approval disparities.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Approval and pricing effects are reported as aggregate rates over Upstart's applicant pool, with no individually attributable outcome." }, { "group": "societal", "depth": null, "reason": "Sources describe aggregate access effects and later disparities; no societal outcome is measured." } ], "ai_role": { "status": "assessed", "statement": "The CFPB states that the reported gains reflect the net effect of both the alternative data and the machine-learning methodology. So the model's contribution cannot be separated from its data. Upstart developed and deployed the model and supplied the comparison. The independent monitor later found approval disparities for Black applicants and disagreed with Upstart about a less discriminatory alternative." }, "evidence": [ { "kind": "other", "citation": "Patrice Alexander Ficklin and Paul Watkins, Consumer Financial Protection Bureau blog, 6 August 2019", "title": "An update on credit access and the Bureau's first No-Action Letter", "url": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/", "date": "2019-08-06", "written_by": "independent", "quote": "27% more applicants than the traditional model" }, { "kind": "press release", "citation": "Consumer Financial Protection Bureau, newsroom, 8 June 2022", "title": "CFPB Issues Order to Terminate Upstart No-Action Letter", "url": "https://www.consumerfinance.gov/about-us/newsroom/cfpb-issues-order-to-terminate-upstart-no-action-letter/", "date": "2022-06-08", "written_by": "independent", "quote": "needed sufficient time to review and rigorously evaluate the implications of the changes to Upstart's model", "supports_benefit": false }, { "kind": "report", "citation": "Relman Colfax PLLC, Final Report of the Independent Monitor (March 2024), executive summary, pp. 3–5, and §§ A–B. Released on March 27, 2024.", "title": "Final Report of the Independent Monitor", "url": "https://www.relmanlaw.com/media/cases/1511_Upstart%20Final%20Report.pdf", "date": "2024-03-27", "written_by": "independent", "quote": null, "supports_benefit": false } ], "replication": { "produced_by": [ "Alternative data combined with machine-learning underwriting, compared against a hypothetical traditional model on Upstart's own applicant pool", "A regulatory compliance plan requiring fair-lending testing and reporting" ], "must_hold": [ "An applicant pool and comparison model similar to the 2019 test", "Fair-lending testing that measures approval as well as pricing disparities", "Independent monitoring, which in 2024 found approval disparities the 2019 test did not report" ], "echoes": [ { "date": "2022-06-08", "setting": "CFPB termination of the 2020 no-action letter", "model_version": null, "outcome": "unknown", "source": "CFPB order; no results stated" }, { "date": "2024-03-27", "setting": "Relman Colfax monitorship of Upstart for LDF and SBPC", "model_version": null, "outcome": "unknown", "source": "LDF press release: no pricing disparities but approval disparities for Black applicants" } ] }, "paired_incident": null, "headline": "More loan approvals at lower rates in a simulation", "metric": "approving 27% more applicants at 16% lower APRs than a traditional model", "comparator": { "against": "a hypothetical model using traditional application and credit file variables without machine learning", "before": "approval rate and average APRs of the traditional model (not quantified)", "after": "approves 27% more applicants than the traditional model, and yields 16% lower average APRs for approved loans", "basis": "measured", "quote": "The results provided from the access-to-credit comparisons show that the tested model approves 27% more applicants than the traditional model, and yields 16% lower average APRs for approved loans.", "url": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/" }, "later": { "status": "challenged", "date": "2024-03-27", "note": "The independent monitor found approval disparities for Black applicants and proposed a less discriminatory alternative. Upstart and the monitor did not agree on adopting it. The earlier termination of the no-action letter was an administrative action, not litigation.", "quote": null, "url": "https://www.relmanlaw.com/media/cases/1511_Upstart%20Final%20Report.pdf" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/; https://www.consumerfinance.gov/about-us/newsroom/cfpb-issues-order-to-terminate-upstart-no-action-letter/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.upstart.com/about; https://www.upstart.com/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "Listed, not verified", "claim_basis": "Sources: one independent report, one independent press release and one other independent source. 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corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Consumer credit", "segment": "Unsecured personal loans and credit access" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Patrice Alexander Ficklin and Paul Watkins, Consumer Financial Protection Bureau blog, 6 August 2019", "title": "An update on credit access and the Bureau's first No-Action Letter", "url": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/", "date": "2019-08-06", "written_by": "independent", "quote": "27% more applicants than the traditional model" }, { "kind": "press release", "citation": "Consumer Financial Protection Bureau, newsroom, 8 June 2022", "title": "CFPB Issues Order to Terminate Upstart No-Action Letter", "url": "https://www.consumerfinance.gov/about-us/newsroom/cfpb-issues-order-to-terminate-upstart-no-action-letter/", "date": "2022-06-08", "written_by": "independent", "quote": "needed sufficient time to review and rigorously evaluate the implications of the changes to Upstart's model", "supports_benefit": false }, { "kind": "report", "citation": "Relman Colfax PLLC, Final Report of the Independent Monitor (March 2024), executive summary, pp. 3–5, and §§ A–B. Released on March 27, 2024.", "title": "Final Report of the Independent Monitor", "url": "https://www.relmanlaw.com/media/cases/1511_Upstart%20Final%20Report.pdf", "date": "2024-03-27", "written_by": "independent", "supports_benefit": false } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0175-source-0001", "AIBD-0175-source-0002", "AIBD-0175-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "Upstart supplied the approval and APR estimates. CFPB published them without replicating them. The later independent monitor examined fairness and identified approval disparities for Black applicants." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0175-source-0001", "AIBD-0175-source-0002", "AIBD-0175-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Upstart supplied the approval and APR estimates. CFPB published them without replicating them. The later independent monitor examined fairness and identified approval disparities for Black applicants." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0175-source-0001", "retained_source_order": [ "AIBD-0175-source-0001", "AIBD-0175-source-0002", "AIBD-0175-source-0003" ], "origins": [ { "url": "https://www.consumerfinance.gov/about-us/blog/update-credit-access-and-no-action-letter/", "locator": "Bureau initiatives; explanation of Upstart’s comparison and the non-replication statement.", "contribution": "Attributes the 27% approval and 16% APR figures to Upstart’s analysis.", "relationship": "CFPB-authored intermediary account of company-supplied results.", "source_refs": [ "AIBD-0175-source-0001" ] }, { "url": "https://www.consumerfinance.gov/about-us/newsroom/cfpb-issues-order-to-terminate-upstart-no-action-letter/", "locator": "Announcement of termination and Upstart’s requested model changes.", "contribution": "The 2022 administrative termination.", "relationship": "Independent agency announcement, not a benefit finding.", "source_refs": [ "AIBD-0175-source-0002" ] }, { "url": "https://www.relmanlaw.com/media/cases/1511_Upstart%20Final%20Report.pdf", "locator": "Executive summary, pp. 3–5; pp. 8–10 and 14–16.", "contribution": "Independent scrutiny of approval disparities and the alternative-model disagreement.", "relationship": "Original independent monitor’s report.", "source_refs": [ "AIBD-0175-source-0003" ] }, { "url": "https://www.naacpldf.org/press-release/ldf-sbpc-and-upstart-announce-final-monitorship-report-on-ai-and-fair-lending/", "locator": "Announcement dated 27 March 2024 and link to the final report.", "contribution": "Establishes the public release date and provides access to the original report.", "relationship": "Joint announcement, replaced by the linked original.", "source_refs": [ "AIBD-0175-source-0003" ] } ], "excluded_or_consolidated_sources": [ { "url": "https://www.naacpldf.org/press-release/ldf-sbpc-and-upstart-announce-final-monitorship-report-on-ai-and-fair-lending/", "reason": "Replaced by the original monitor’s report; retained here for its release date and access link.", "retained_source_ref": "AIBD-0175-source-0003" } ], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0175-source-0001", "AIBD-0175-source-0002", "AIBD-0175-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Upstart supplied the approval and APR estimates. CFPB published them without replicating them. The later independent monitor examined fairness and identified approval disparities for Black applicants." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Upstart estimated 27% more approvals and 16% lower annual percentage rates in a simulation. A 2024 independent review found approval disparities for Black applicants.", "account": "The Consumer Financial Protection Bureau reported results from the compliance plan attached to its first no-action letter, granted to Upstart Network in September 2017. The results were in a 6 August 2019 blog post by Patrice Alexander Ficklin and Paul Watkins. Upstart compared its tested model with a hypothetical traditional model using conventional variables. It reported that the tested model approves 27% more applicants and yields 16% lower average APRs for approved loans. Acceptance rates were up 23–29% and APRs down 15–17% across racial, ethnic and sex categories. Near-prime applicants (FICO 620–660) were approved approximately twice as frequently. Applicants under 25 were 32% more likely to be approved and those with incomes under $50,000 13% more likely. The post states that the results for minority, female and 62-and-older applicants show no disparities requiring further fair-lending analysis. The post says that they reflect the net effect of both the alternative data and the machine-learning methodology. Upstart supplied the analysis. The CFPB expressly stated that it did not separately replicate it. On 8 June 2022 the CFPB terminated the 2020 no-action letter at Upstart's request after Upstart planned to expand the variables in its model. On 27 March 2024 the NAACP Legal Defense Fund and the Student Borrower Protection Center announced Relman Colfax's final independent-monitorship report. It found no proxies for protected classes and no pricing disparities but identified approval disparities for Black applicants. Upstart rejected the monitor's proposed less discriminatory alternative model." } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Upstart Network underwriting and pricing model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Upstart Network, Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "More loan approvals at lower rates in a simulation", "headline": "More loan approvals at lower rates in a simulation" } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "058110bb515dd923a9bf7d96c8701119c79627d0248fb6d63f9c1d61b7a83046" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Consumer Financial Protection Bureau reported results from the compliance plan attached to its first no-action letter, granted to Upstart Network in September 2017. The results were in a 6 August 2019 blog post by Patrice Alexander Ficklin and Paul Watkins. Upstart compared its tested model with a hypothetical traditional model using conventional variables. It reported the tested model approves 27% more applicants and yields 16% lower average APRs for approved loans. Acceptance rates were up 23–29% and APRs down 15–17% across racial, ethnic and sex categories. Near-prime applicants (FICO 620–660) were approved approximately twice as frequently. Applicants under 25 were 32% more likely to be approved and those with incomes under $50,000 13% more likely. The post states that the results for minority, female and 62-and-older applicants show no disparities requiring further fair-lending analysis. The post says they reflect the net effect of both the alternative data and the machine-learning methodology. Upstart supplied the analysis. The CFPB expressly stated that it did not separately replicate it. On 8 June 2022 the CFPB terminated the 2020 no-action letter at Upstart's request after Upstart planned to expand the variables in its model. On 27 March 2024 the NAACP Legal Defense Fund and the Student Borrower Protection Center announced Relman Colfax's final independent-monitorship report. It found no proxies for protected classes and no pricing disparities but identified approval disparities for Black applicants. Upstart rejected the monitor's proposed less discriminatory alternative model.", "replication": { "produced_by": [ "Alternative data combined with machine-learning underwriting, compared against a hypothetical traditional model on Upstart's own applicant pool", "A regulatory compliance plan requiring fair-lending testing and reporting" ], "must_hold": [ "An applicant pool and comparison model similar to the 2019 test", "Fair-lending testing that measures approval as well as pricing disparities", "Independent monitoring, which in 2024 found approval disparities the 2019 test did not report" ], "echoes": [ { "date": "2022-06-08", "setting": "CFPB termination of the 2020 no-action letter", "outcome": "unknown", "source": "CFPB order; no results stated" }, { "date": "2024-03-27", "setting": "Relman Colfax monitorship of Upstart for LDF and SBPC", "outcome": "unknown", "source": "LDF press release: no pricing disparities but approval disparities for Black applicants" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 2, "record_mapped": 27, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0304", "title": "Apple Watch Fall Detection calls 911 after hiker James Prudenciano, 28, falls from a ledge in Hartshorne Woods Park, New Jersey; three agencies respond", "summary": "On 14 October 2019 a lost hiker fell about 30 ft in Hartshorne Woods Park, NJ; his new Apple Watch's Fall Detection called 911 and texted his family; Middletown police say three agencies responded.", "date_observed": "2019-10-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "James Prudenciano, 28, and his hiking companion (named by the Associated Press as Paige Paruso) got lost in Hartshorne Woods Park, Monmouth County, New Jersey. It was 14 October 2019, as darkness fell. They slid down a steep slope onto a ledge. Police said they fell about 30 feet (NBC News, 23 October 2019). He had bought the watch two days earlier and turned on Fall Detection while exploring its settings. He told NBC New York he heard “911, what's your emergency” from the watch. The watch also texted his mother and sister with his location, and his mother drove to the park. “Three agencies responded, according to Middletown police”, and a civilian boater brought the pair to safety. NBC News reports a fractured back and leg and foot injuries. ABC7 New York reports a fracture to his right hand. The Associated Press says undisclosed injuries. No police report or dispatch record is among the sources.", "category": "protective response", "unexpected": false, "purpose": "Fall Detection is built to detect hard falls and, after about a minute of immobility, call emergency services and message emergency contacts with a location. This call was that purpose.", "system": "Apple Watch Fall Detection", "model_version": null, "developer": "Apple", "deployer": null, "location": "Hartshorne Woods Park, Middletown Township, New Jersey, United States", "domain": "Search and rescue", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "An injured hiker stranded on a ledge at night was located and brought out the same night. Injuries are reported inconsistently (fractured back per NBC News, fractured hand per ABC7). Whether he could have called 911 himself is not addressed." }, { "group": "organizational", "depth": 1, "reason": "Middletown police say three agencies responded to the automated call. No statement on search time saved is among the sources." } ], "ai_role": { "status": "assessed", "statement": "The watch's fall classifier triggered the 911 call and the location message to his family. Apple's support page says the watch calls automatically only if it detects a hard fall and then immobility for about a minute. The hiker was conscious and spoke to the dispatcher once connected. All sources are news reports from October 2019. The response-count claim is attributed to Middletown police by NBC News." }, "evidence": [ { "kind": "news report", "citation": "Kaur H / NBC News (2019). Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff. 23 October 2019.", "title": "Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff", "url": "https://www.nbcnews.com/news/us-news/apple-watch-s-hard-fall-feature-automatically-calls-911-hiker-n1070471", "date": "2019-10-23", "written_by": "independent", "quote": "Three agencies responded, according to Middletown police. The hikers were brought to safety by a civilian boater who offered to help." }, { "kind": "news report", "citation": "Yates T / WABC-TV (2019). Apple Watch calls 911 after man falls down New Jersey cliff. ABC7 New York, 23 October 2019.", "title": "Apple Watch calls 911 after man falls down New Jersey cliff", "url": "https://abc7ny.com/post/apple-watch-calls-911-after-man-falls-down-nj-cliff/5638758/", "date": "2019-10-23", "written_by": "independent", "quote": "I just remember hearing, '911, what's your emergency?' and my Apple Watch started talking to me" }, { "kind": "news report", "citation": "Associated Press (2019). Apple Watch calls 911 after 2 hikers fall off NJ cliff. Republished by EMS1, 25 October 2019.", "title": "Apple Watch calls 911 after 2 hikers fall off NJ cliff", "url": "https://www.ems1.com/technology/articles/apple-watch-calls-911-after-2-hikers-fall-off-nj-cliff-gPSzpfkNa0ox7vn9/", "date": "2019-10-25", "written_by": "independent", "quote": "Prudenciano had bought the watch two days earlier and chose to activate the “fall detection” feature" }, { "kind": "press release", "citation": "Apple Support. Use Fall Detection with Apple Watch (article 108896), published 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ], "replication": { "produced_by": [ "An Apple Watch Series 4 or later with Fall Detection switched on (off by default for wearers under 55)", "A hard fall followed by immobility, or a wearer who confirms the call", "Cellular or Wi-Fi connectivity from the watch or a nearby iPhone" ], "must_hold": [ "The fall classifier recognizes the impact as a hard fall", "Emergency services can act on the transmitted coordinates" ], "echoes": [ { "date": "2025-10-31", "setting": "Tenmile Range near Breckenridge, Colorado: photographer Phong Le fell down a scree slope; his Apple Watch Ultra 3 detected the fall and began the SOS countdown, he confirmed the call, and Summit County Rescue Group ran a day-long rescue (Outside, 1–2 December 2025)", "model_version": "Apple Watch Ultra 3", "outcome": "recurred", "source": "https://www.outsideonline.com/outdoor-adventure/hiking-and-backpacking/apple-watch-sos-call/" }, { "date": "2026-07-28", "setting": "Cincinnati, Ohio: Mohammad Islam collapsed outside his home while alone; the watch called 911 and paramedics arrived; University of Cincinnati doctors found blood clots in his lungs (9to5Mac citing WKRC, 28 July 2026; event “several weeks” earlier)", "model_version": null, "outcome": "recurred", "source": "https://9to5mac.com/2026/07/28/man-credits-apple-watch-with-saving-his-life-after-collapsing-at-home/" }, { "date": "2024-03-01", "setting": "New York City: Eric Zollinger, 49, fainted in his bathroom after a bicycle crash; the watch struck the tub, called 911 and messaged his contacts with his location; he canceled the call and was checked at a hospital (New York Post, 17 April 2024; event “last month”, first day used)", "model_version": null, "outcome": "recurred", "source": "https://nypost.com/2024/04/17/tech/bicyclists-life-saved-by-smartwatch-that-called-911-after-crash/" } ] }, "paired_incident": null, "headline": "Apple Watch Fall Detection calls 911 for hiker James Prudenciano", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No report later than October 2019 about Prudenciano was found; the later Apple Watch fall-detection rescues concern other people.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0304", "catalog_version": "1.0.0", "source_fingerprint": "fff19628222890d6a5028a1df5dd721e966c0b0226da6ff3e01d2cd2647429d9", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0304-source-0001", "AIBD-0304-source-0002", "AIBD-0304-source-0003", "AIBD-0304-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's fall classifier triggered the 911 call and the location message to his family. Apple's support page says the watch calls automatically only if it detects a hard fall and then immobility for about a minute. The hiker was conscious and spoke to the dispatcher once connected. All sources are news reports from October 2019. The response-count claim is attributed to Middletown police by NBC News." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The watch's fall classifier triggered the 911 call and the location message to his family. Apple's support page says the watch calls automatically only if it detects a hard fall and then immobility for about a minute. 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It was 14 October 2019, as darkness fell. They slid down a steep slope onto a ledge. Police said they fell about 30 feet (NBC News, 23 October 2019). He had bought the watch two days earlier and turned on Fall Detection while exploring its settings. He told NBC New York he heard “911, what's your emergency” from the watch. The watch also texted his mother and sister with his location, and his mother drove to the park. “Three agencies responded, according to Middletown police”, and a civilian boater brought the pair to safety. NBC News reports a fractured back and leg and foot injuries. ABC7 New York reports a fracture to his right hand. The Associated Press says undisclosed injuries. No police report or dispatch record is among the sources.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An injured hiker stranded on a ledge at night was located and brought out the same night. Injuries are reported inconsistently (fractured back per NBC News, fractured hand per ABC7). Whether he could have called 911 himself is not addressed." }, { "group": "organizational", "depth": 1, "reason": "Middletown police say three agencies responded to the automated call. No statement on search time saved is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Fall Detection is built to detect hard falls and, after about a minute of immobility, call emergency services and message emergency contacts with a location. This call was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Hartshorne Woods Park, Middletown Township, New Jersey, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Fall Detection is built to detect hard falls and, after about a minute of immobility, call emergency services and message emergency contacts with a location. This call was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-10-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An Apple Watch Series 4 or later with Fall Detection switched on (off by default for wearers under 55)", "A hard fall followed by immobility, or a wearer who confirms the call", "Cellular or Wi-Fi connectivity from the watch or a nearby iPhone" ], "must_hold": [ "The fall classifier recognizes the impact as a hard fall", "Emergency services can act on the transmitted coordinates" ], "echoes": [ { "date": "2025-10-31", "setting": "Tenmile Range near Breckenridge, Colorado: photographer Phong Le fell down a scree slope; his Apple Watch Ultra 3 detected the fall and began the SOS countdown, he confirmed the call, and Summit County Rescue Group ran a day-long rescue (Outside, 1–2 December 2025)", "model_version": "Apple Watch Ultra 3", "outcome": "recurred", "source": "https://www.outsideonline.com/outdoor-adventure/hiking-and-backpacking/apple-watch-sos-call/" }, { "date": "2026-07-28", "setting": "Cincinnati, Ohio: Mohammad Islam collapsed outside his home while alone; the watch called 911 and paramedics arrived; University of Cincinnati doctors found blood clots in his lungs (9to5Mac citing WKRC, 28 July 2026; event “several weeks” earlier)", "outcome": "recurred", "source": "https://9to5mac.com/2026/07/28/man-credits-apple-watch-with-saving-his-life-after-collapsing-at-home/" }, { "date": "2024-03-01", "setting": "New York City: Eric Zollinger, 49, fainted in his bathroom after a bicycle crash; the watch struck the tub, called 911 and messaged his contacts with his location; he canceled the call and was checked at a hospital (New York Post, 17 April 2024; event “last month”, first day used)", "outcome": "recurred", "source": "https://nypost.com/2024/04/17/tech/bicyclists-life-saved-by-smartwatch-that-called-911-after-crash/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An Apple Watch Series 4 or later with Fall Detection switched on (off by default for wearers under 55)", "A hard fall followed by immobility, or a wearer who confirms the call", "Cellular or Wi-Fi connectivity from the watch or a nearby iPhone" ], "must_hold": [ "The fall classifier recognizes the impact as a hard fall", "Emergency services can act on the transmitted coordinates" ], "echoes": [ { "date": "2025-10-31", "setting": "Tenmile Range near Breckenridge, Colorado: photographer Phong Le fell down a scree slope; his Apple Watch Ultra 3 detected the fall and began the SOS countdown, he confirmed the call, and Summit County Rescue Group ran a day-long rescue (Outside, 1–2 December 2025)", "model_version": "Apple Watch Ultra 3", "outcome": "recurred", "source": "https://www.outsideonline.com/outdoor-adventure/hiking-and-backpacking/apple-watch-sos-call/" }, { "date": "2026-07-28", "setting": "Cincinnati, Ohio: Mohammad Islam collapsed outside his home while alone; the watch called 911 and paramedics arrived; University of Cincinnati doctors found blood clots in his lungs (9to5Mac citing WKRC, 28 July 2026; event “several weeks” earlier)", "outcome": "recurred", "source": "https://9to5mac.com/2026/07/28/man-credits-apple-watch-with-saving-his-life-after-collapsing-at-home/" }, { "date": "2024-03-01", "setting": "New York City: Eric Zollinger, 49, fainted in his bathroom after a bicycle crash; the watch struck the tub, called 911 and messaged his contacts with his location; he canceled the call and was checked at a hospital (New York Post, 17 April 2024; event “last month”, first day used)", "outcome": "recurred", "source": "https://nypost.com/2024/04/17/tech/bicyclists-life-saved-by-smartwatch-that-called-911-after-crash/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Search and rescue", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kaur H / NBC News (2019). Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff. 23 October 2019.", "title": "Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff", "url": "https://www.nbcnews.com/news/us-news/apple-watch-s-hard-fall-feature-automatically-calls-911-hiker-n1070471", "date": "2019-10-23", "written_by": "independent", "quote": "Three agencies responded, according to Middletown police. The hikers were brought to safety by a civilian boater who offered to help." }, { "kind": "news report", "citation": "Yates T / WABC-TV (2019). Apple Watch calls 911 after man falls down New Jersey cliff. ABC7 New York, 23 October 2019.", "title": "Apple Watch calls 911 after man falls down New Jersey cliff", "url": "https://abc7ny.com/post/apple-watch-calls-911-after-man-falls-down-nj-cliff/5638758/", "date": "2019-10-23", "written_by": "independent", "quote": "I just remember hearing, '911, what's your emergency?' and my Apple Watch started talking to me" }, { "kind": "news report", "citation": "Associated Press (2019). Apple Watch calls 911 after 2 hikers fall off NJ cliff. Republished by EMS1, 25 October 2019.", "title": "Apple Watch calls 911 after 2 hikers fall off NJ cliff", "url": "https://www.ems1.com/technology/articles/apple-watch-calls-911-after-2-hikers-fall-off-nj-cliff-gPSzpfkNa0ox7vn9/", "date": "2019-10-25", "written_by": "independent", "quote": "Prudenciano had bought the watch two days earlier and chose to activate the “fall detection” feature" }, { "kind": "press release", "citation": "Apple Support. Use Fall Detection with Apple Watch (article 108896), published 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0304-source-0001", "AIBD-0304-source-0002", "AIBD-0304-source-0003", "AIBD-0304-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kaur H / NBC News (2019). Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff. 23 October 2019.", "title": "Apple Watch's 'Hard Fall' feature automatically calls 911 for hiker stranded on cliff", "url": "https://www.nbcnews.com/news/us-news/apple-watch-s-hard-fall-feature-automatically-calls-911-hiker-n1070471", "date": "2019-10-23", "written_by": "independent", "quote": "Three agencies responded, according to Middletown police. The hikers were brought to safety by a civilian boater who offered to help." }, { "kind": "news report", "citation": "Yates T / WABC-TV (2019). Apple Watch calls 911 after man falls down New Jersey cliff. ABC7 New York, 23 October 2019.", "title": "Apple Watch calls 911 after man falls down New Jersey cliff", "url": "https://abc7ny.com/post/apple-watch-calls-911-after-man-falls-down-nj-cliff/5638758/", "date": "2019-10-23", "written_by": "independent", "quote": "I just remember hearing, '911, what's your emergency?' and my Apple Watch started talking to me" }, { "kind": "news report", "citation": "Associated Press (2019). Apple Watch calls 911 after 2 hikers fall off NJ cliff. Republished by EMS1, 25 October 2019.", "title": "Apple Watch calls 911 after 2 hikers fall off NJ cliff", "url": "https://www.ems1.com/technology/articles/apple-watch-calls-911-after-2-hikers-fall-off-nj-cliff-gPSzpfkNa0ox7vn9/", "date": "2019-10-25", "written_by": "independent", "quote": "Prudenciano had bought the watch two days earlier and chose to activate the “fall detection” feature" }, { "kind": "press release", "citation": "Apple Support. Use Fall Detection with Apple Watch (article 108896), published 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "On 14 October 2019 a lost hiker fell about 30 ft in Hartshorne Woods Park, NJ; his new Apple Watch's Fall Detection called 911 and texted his family; Middletown police say three agencies responded.", "account": "James Prudenciano, 28, and his hiking companion (named by the Associated Press as Paige Paruso) got lost in Hartshorne Woods Park, Monmouth County, New Jersey. It was 14 October 2019, as darkness fell. They slid down a steep slope onto a ledge. Police said they fell about 30 feet (NBC News, 23 October 2019). He had bought the watch two days earlier and turned on Fall Detection while exploring its settings. He told NBC New York he heard “911, what's your emergency” from the watch. The watch also texted his mother and sister with his location, and his mother drove to the park. “Three agencies responded, according to Middletown police”, and a civilian boater brought the pair to safety. NBC News reports a fractured back and leg and foot injuries. ABC7 New York reports a fracture to his right hand. The Associated Press says undisclosed injuries. No police report or dispatch record is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Fall Detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Fall Detection calls 911 after hiker James Prudenciano, 28, falls from a ledge in Hartshorne Woods Park, New Jersey; three agencies respond", "headline": "Apple Watch Fall Detection calls 911 for hiker James Prudenciano" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fff19628222890d6a5028a1df5dd721e966c0b0226da6ff3e01d2cd2647429d9" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "James Prudenciano, 28, and his hiking companion (named by the Associated Press as Paige Paruso) got lost in Hartshorne Woods Park, Monmouth County, New Jersey. It was 14 October 2019, as darkness fell. They slid down a steep slope onto a ledge. Police said they fell about 30 feet (NBC News, 23 October 2019). He had bought the watch two days earlier and turned on Fall Detection while exploring its settings. He told NBC New York he heard “911, what's your emergency” from the watch. The watch also texted his mother and sister with his location, and his mother drove to the park. “Three agencies responded, according to Middletown police”, and a civilian boater brought the pair to safety. NBC News reports a fractured back and leg and foot injuries. ABC7 New York reports a fracture to his right hand. The Associated Press says undisclosed injuries. No police report or dispatch record is among the sources.", "replication": { "produced_by": [ "An Apple Watch Series 4 or later with Fall Detection switched on (off by default for wearers under 55)", "A hard fall followed by immobility, or a wearer who confirms the call", "Cellular or Wi-Fi connectivity from the watch or a nearby iPhone" ], "must_hold": [ "The fall classifier recognizes the impact as a hard fall", "Emergency services can act on the transmitted coordinates" ], "echoes": [ { "date": "2025-10-31", "setting": "Tenmile Range near Breckenridge, Colorado: photographer Phong Le fell down a scree slope; his Apple Watch Ultra 3 detected the fall and began the SOS countdown, he confirmed the call, and Summit County Rescue Group ran a day-long rescue (Outside, 1–2 December 2025)", "model_version": "Apple Watch Ultra 3", "outcome": "recurred", "source": "https://www.outsideonline.com/outdoor-adventure/hiking-and-backpacking/apple-watch-sos-call/" }, { "date": "2026-07-28", "setting": "Cincinnati, Ohio: Mohammad Islam collapsed outside his home while alone; the watch called 911 and paramedics arrived; University of Cincinnati doctors found blood clots in his lungs (9to5Mac citing WKRC, 28 July 2026; event “several weeks” earlier)", "outcome": "recurred", "source": "https://9to5mac.com/2026/07/28/man-credits-apple-watch-with-saving-his-life-after-collapsing-at-home/" }, { "date": "2024-03-01", "setting": "New York City: Eric Zollinger, 49, fainted in his bathroom after a bicycle crash; the watch struck the tub, called 911 and messaged his contacts with his location; he canceled the call and was checked at a hospital (New York Post, 17 April 2024; event “last month”, first day used)", "outcome": "recurred", "source": "https://nypost.com/2024/04/17/tech/bicyclists-life-saved-by-smartwatch-that-called-911-after-crash/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0176", "title": "LendingClub's alternative-data grades move some subprime borrowers into lower-priced credit", "summary": "Jagtiani and Lemieux found that LendingClub rating grades' correlation with FICO fell from about 80% (2007 loans) to about 35% (2014–15) and that some traditionally subprime borrowers received bett...", "date_observed": "2019-11-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Federal Reserve Bank of Philadelphia working paper 18–15 is by Julapa Jagtiani (Philadelphia Fed) and Catharine Lemieux (Chicago Fed), revised January 2019. Its title is “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform”. It compares account-level LendingClub loans with similar loans in Y-14M reports from bank holding companies with assets of $50 billion or more. The authors report that the correlation between LendingClub's rating grades and FICO scores declined. It was about 80 percent for 2007 originations and about 35 percent for 2014–2015 vintages. The grades perform well in predicting loan performance over the two years after origination. Alternative data allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into better grades. They got lower-priced credit. For the same default risk consumers pay smaller spreads at LendingClub than on credit cards. For 2015 loans about 8 percent of A-rated and 28 percent of B-rated borrowers had FICO scores below 680. Crossref lists a journal version in Financial Management (DOI 10.1111/fima.12295) issued 6 November 2019. The working paper itself carries only a month.", "category": "general benefit", "unexpected": false, "purpose": "Assign rating grades and price consumer loans on the LendingClub marketplace.", "system": "LendingClub rating-grade model (grades A to G)", "model_version": null, "developer": "LendingClub", "deployer": "LendingClub", "location": null, "domain": "Consumer credit", "segment": "Marketplace consumer lending", "benefit_type": "Increased Inclusion", "taxonomy_note": "The good is better-priced credit for borrowers traditional criteria would call subprime, and the lender's technique is not documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Effects on borrowers are reported as vintage-level shares and spreads, not as outcomes for identifiable individuals." }, { "group": "societal", "depth": null, "reason": "Financial-inclusion effects are discussed at the aggregate level only." } ], "ai_role": { "status": "unassessed", "statement": "The paper attributes the regrading of subprime borrowers to alternative data used by the lender. It does not establish that machine learning produced the grades. LendingClub developed and deployed its own model. The Federal Reserve authors are independent." }, "evidence": [ { "kind": "preprint", "citation": "Julapa Jagtiani and Catharine Lemieux, Federal Reserve Bank of Philadelphia Working Paper 18-15, revised January 2019 (later in Financial Management, DOI 10.1111/fima.12295, issued 2019-11-06 per Crossref)", "title": "The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform", "url": "https://doi.org/10.21799/frbp.wp.2018.15", "date": null, "written_by": "independent", "quote": "allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into \"better\" loan grades" } ], "replication": { "produced_by": [ "Account-level LendingClub data compared with Y-14M bank data for similar loans, 2007 to 2015 vintages", "Lender grading that increasingly used information not captured by FICO" ], "must_hold": [ "Alternative data that predicts repayment beyond FICO", "Grades that keep predicting loan performance (the paper reports good prediction over two years after origination)" ], "echoes": [ { "date": null, "setting": "NBER working paper 29840, “Invisible Primes: Fintech Lending with Alternative Data” (2022–03)", "model_version": null, "outcome": "unknown", "source": "Crossref listing only" } ] }, "paired_incident": null, "headline": "Some subprime borrowers get lower-priced credit at LendingClub", "metric": "about 8 percent of A-rated and 28 percent of B-rated borrowers had FICO scores below 680", "comparator": { "against": "classification of borrowers by traditional credit criteria", "before": "classified as subprime by traditional criteria", "after": "slotted into “better” loan grades, which allowed them to get lower-priced credit", "basis": "measured", "quote": "The use of alternative data has allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into “better” loan grades, which allowed them to get lower-priced credit. In addition, for the same risk of default, consumers pay smaller spreads on loans from LendingClub than from credit card borrowing.", "url": "https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2018/wp18-15r.pdf" }, "later": { "status": "unknown", "date": null, "note": "No later finding on LendingClub's grades was found; the 2022 'Invisible Primes' paper concerns a different platform.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2018/wp18-15r.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/LendingClub; https://en.wikipedia.org/wiki/LendingClub", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0176", "catalog_version": "1.0.0", "source_fingerprint": "3b29bea167a22c1ec6745b7d8f1ca2e34c409ab77cfee4439af089e7b9a72201", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0176-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "LendingClub", "deployer": "LendingClub" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The paper attributes the regrading of subprime borrowers to alternative data used by the lender. It does not establish that machine learning produced the grades. LendingClub developed and deployed its own model. The Federal Reserve authors are independent." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Effects on borrowers are reported as vintage-level shares and spreads, not as outcomes for identifiable individuals." }, { "group": "societal", "reason": "Financial-inclusion effects are discussed at the aggregate level only." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Effects on borrowers are reported as vintage-level shares and spreads, not as outcomes for identifiable individuals." }, { "group": "societal", "reason": "Financial-inclusion effects are discussed at the aggregate level only." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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"family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later finding on LendingClub's grades was found; the 2022 'Invisible Primes' paper concerns a different platform." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0176" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Inclusion", "taxonomy_note": "The good is better-priced credit for borrowers traditional criteria would call subprime, and the lender's technique is not documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Federal Reserve Bank of Philadelphia working paper 18–15 is by Julapa Jagtiani (Philadelphia Fed) and Catharine Lemieux (Chicago Fed), revised January 2019. Its title is “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform”. It compares account-level LendingClub loans with similar loans in Y-14M reports from bank holding companies with assets of $50 billion or more. The authors report that the correlation between LendingClub's rating grades and FICO scores declined. It was about 80 percent for 2007 originations and about 35 percent for 2014–2015 vintages. The grades perform well in predicting loan performance over the two years after origination. Alternative data allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into better grades. They got lower-priced credit. For the same default risk consumers pay smaller spreads at LendingClub than on credit cards. For 2015 loans about 8 percent of A-rated and 28 percent of B-rated borrowers had FICO scores below 680. Crossref lists a journal version in Financial Management (DOI 10.1111/fima.12295) issued 6 November 2019. The working paper itself carries only a month.", "benefit_type": "Increased Inclusion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Effects on borrowers are reported as vintage-level shares and spreads, not as outcomes for identifiable individuals." }, { "group": "societal", "reason": "Financial-inclusion effects are discussed at the aggregate level only." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Assign rating grades and price consumer loans on the LendingClub marketplace." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2019-11-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2018/wp18-15r.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/LendingClub; https://en.wikipedia.org/wiki/LendingClub", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Account-level LendingClub data compared with Y-14M bank data for similar loans, 2007 to 2015 vintages", "Lender grading that increasingly used information not captured by FICO" ], "must_hold": [ "Alternative data that predicts repayment beyond FICO", "Grades that keep predicting loan performance (the paper reports good prediction over two years after origination)" ], "echoes": [ { "setting": "NBER working paper 29840, “Invisible Primes: Fintech Lending with Alternative Data” (2022–03)", "outcome": "unknown", "source": "Crossref listing only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Account-level LendingClub data compared with Y-14M bank data for similar loans, 2007 to 2015 vintages", "Lender grading that increasingly used information not captured by FICO" ], "must_hold": [ "Alternative data that predicts repayment beyond FICO", "Grades that keep predicting loan performance (the paper reports good prediction over two years after origination)" ], "echoes": [ { "setting": "NBER working paper 29840, “Invisible Primes: Fintech Lending with Alternative Data” (2022–03)", "outcome": "unknown", "source": "Crossref listing only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; 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external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Julapa Jagtiani and Catharine Lemieux, Federal Reserve Bank of Philadelphia Working Paper 18-15, revised January 2019 (later in Financial Management, DOI 10.1111/fima.12295, issued 2019-11-06 per Crossref)", "title": "The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform", "url": "https://doi.org/10.21799/frbp.wp.2018.15", "written_by": "independent", "quote": "allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into \"better\" loan grades" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0176-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Julapa Jagtiani and Catharine Lemieux, Federal Reserve Bank of Philadelphia Working Paper 18-15, revised January 2019 (later in Financial Management, DOI 10.1111/fima.12295, issued 2019-11-06 per Crossref)", "title": "The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform", "url": "https://doi.org/10.21799/frbp.wp.2018.15", "written_by": "independent", "quote": "allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into \"better\" loan grades" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Jagtiani and Lemieux found that LendingClub rating grades' correlation with FICO fell from about 80% (2007 loans) to about 35% (2014–15) and that some traditionally subprime borrowers received bett...", "account": "Federal Reserve Bank of Philadelphia working paper 18–15 is by Julapa Jagtiani (Philadelphia Fed) and Catharine Lemieux (Chicago Fed), revised January 2019. Its title is “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform”. It compares account-level LendingClub loans with similar loans in Y-14M reports from bank holding companies with assets of $50 billion or more. The authors report that the correlation between LendingClub's rating grades and FICO scores declined. It was about 80 percent for 2007 originations and about 35 percent for 2014–2015 vintages. The grades perform well in predicting loan performance over the two years after origination. Alternative data allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into better grades. They got lower-priced credit. For the same default risk consumers pay smaller spreads at LendingClub than on credit cards. For 2015 loans about 8 percent of A-rated and 28 percent of B-rated borrowers had FICO scores below 680. Crossref lists a journal version in Financial Management (DOI 10.1111/fima.12295) issued 6 November 2019. The working paper itself carries only a month." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "LendingClub rating-grade model (grades A to G)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "LendingClub" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "LendingClub's alternative-data grades move some subprime borrowers into lower-priced credit", "headline": "Some subprime borrowers get lower-priced credit at LendingClub" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3b29bea167a22c1ec6745b7d8f1ca2e34c409ab77cfee4439af089e7b9a72201" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Federal Reserve Bank of Philadelphia working paper 18–15 is by Julapa Jagtiani (Philadelphia Fed) and Catharine Lemieux (Chicago Fed), revised January 2019. Its title is “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform”. It compares account-level LendingClub loans with similar loans in Y-14M reports from bank holding companies with assets of $50 billion or more. The authors report that the correlation between LendingClub's rating grades and FICO scores declined. It was about 80 percent for 2007 originations and about 35 percent for 2014–2015 vintages. The grades perform well in predicting loan performance over the two years after origination. Alternative data allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into better grades. They got lower-priced credit. For the same default risk consumers pay smaller spreads at LendingClub than on credit cards. For 2015 loans about 8 percent of A-rated and 28 percent of B-rated borrowers had FICO scores below 680. Crossref lists a journal version in Financial Management (DOI 10.1111/fima.12295) issued 6 November 2019. The working paper itself carries only a month.", "replication": { "produced_by": [ "Account-level LendingClub data compared with Y-14M bank data for similar loans, 2007 to 2015 vintages", "Lender grading that increasingly used information not captured by FICO" ], "must_hold": [ "Alternative data that predicts repayment beyond FICO", "Grades that keep predicting loan performance (the paper reports good prediction over two years after origination)" ], "echoes": [ { "setting": "NBER working paper 29840, “Invisible Primes: Fintech Lending with Alternative Data” (2022–03)", "outcome": "unknown", "source": "Crossref listing only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0107", "title": "SkinVision app rated a changing mole on Jason Sheridan's arm high risk; a dermatologist found stage 1A melanoma and it was removed", "summary": "SkinVision rated a 31-year-old's changing arm mole high risk; stage 1A melanoma was found and removed, and he is cancer-free.", "date_observed": "2020-01-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Jason Sheridan, a 31-year-old office worker from Liverpool living in Vauxhall, South London, noticed a new 1cm mole on his left arm in March 2018. He did not see a doctor. Twelve months later it turned pink and he checked it with SkinVision, an AI app that grades photographed moles low, medium or high risk. It returned a high-risk rating and urged him to see a doctor. His GP referred him to a dermatologist and two weeks later the mole was removed in a 40-minute operation. The biopsy showed stage 1A melanoma, a further biopsy found no spread, and he is cancer-free. The Daily Mail reported the case on 17 January 2020 without dates for the app check or surgery.", "category": "harm prevented", "unexpected": false, "purpose": "SkinVision is built to grade a phone photograph of a mole low, medium or high risk. It tells users with a high-risk result to see a doctor, with dermatologist advice sent within 48 hours. This benefit is that intended use.", "system": "SkinVision skin-check app (AI analysis of smartphone photographs of moles, graded low, medium or high risk)", "model_version": null, "developer": "SkinVision", "deployer": null, "location": "London, United Kingdom", "domain": "Healthcare - dermatology / melanoma detection", "segment": "Consumer mobile health app", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2020-01-18-8e93" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A biopsy-confirmed stage 1A melanoma was excised, further tests found no spread and he is reported cancer-free. He calls it life-saving, but stage 1A is early disease and no clinician is quoted on prognosis. How long he would otherwise have waited is his own estimate." } ], "ai_role": { "status": "assessed", "statement": "The app's classifier graded a phone photograph of the mole high risk and told him to see a doctor at once. By his account that prompt, not the color change, is what sent him to his GP. He said he only goes to the doctor when absolutely desperate. The referral, excision, biopsy and staging were done by the GP, the dermatologist and pathology, none of whom the Daily Mail quotes. The article does not report the app's score, its version, or whether the 48-hour dermatologist advice it mentions was used." }, "evidence": [ { "kind": "news report", "citation": "Howard H (2020). Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm. Daily Mail, 17 January 2020.", "title": "Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm", "url": "https://www.dailymail.co.uk/health/article-7898507/Man-mole-removed-finding-skin-cancer-app-told-visit-doctor.html", "date": "2020-01-17", "written_by": "independent", "quote": "After downloading SkinVision, the app immediately came back with a high-risk rating, and I was urged to go see a doctor as soon as possible." }, { "kind": "news report", "citation": "Al-Dostour (2020). سكان فيزيون. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة [Skin Vision: technology detects cancer in an innovative way]. dostor.org, 18 January 2020, crediting the Daily Mail; one of the five Arabic-language sources cited by the OECD Monitor.", "title": "سكان فيزيون.. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة", "url": "https://www.dostor.org/2974509", "date": "2020-01-18", "written_by": "independent", "quote": "وأفادت صحيفة \"ديلي ميل\" البريطانية، فإن الشاب جيسون شيريدان، (31 عاما) قد لاحظ وجود الشامة على ذراعه الأيسر لأول مرة في عام 2018" }, { "kind": "press release", "citation": "SkinVision (2025). SkinVision | Skin Cancer Detection App. Company website, fetched 20 October 2026; the page served to US visitors gives no legal entity or address.", "title": "SkinVision | Skin Cancer Detection App", "url": "https://www.skinvision.com/", "date": null, "written_by": "makers", "quote": "SkinVision was founded with a mission to improve access to skin health information and support individuals in becoming more aware of their skin over time." } ], "replication": { "produced_by": [ "A smartphone photograph of a changing mole submitted to SkinVision's risk classifier", "A high-risk rating with an instruction to see a doctor, acted on by the user", "A GP referral and an excision with pathology that confirms and stages the lesion" ], "must_hold": [ "The lesion is one the classifier can score from a phone photograph. The article reports no score or app version", "The user follows the app's advice rather than treating the rating as noise", "Clinical follow-up is available quickly enough for early-stage removal. 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He calls it life-saving, but stage 1A is early disease and no clinician is quoted on prognosis. How long he would otherwise have waited is his own estimate." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "SkinVision is built to grade a phone photograph of a mole low, medium or high risk. It tells users with a high-risk result to see a doctor, with dermatologist advice sent within 48 hours. This benefit is that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "London, United Kingdom", "developer_country": "Netherlands" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "SkinVision is built to grade a phone photograph of a mole low, medium or high risk. 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This benefit is that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-01-17", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2020-01-18-8e93", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:31494983&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A smartphone photograph of a changing mole submitted to SkinVision's risk classifier", "A high-risk rating with an instruction to see a doctor, acted on by the user", "A GP referral and an excision with pathology that confirms and stages the lesion" ], "must_hold": [ "The lesion is one the classifier can score from a phone photograph. The article reports no score or app version", "The user follows the app's advice rather than treating the rating as noise", "Clinical follow-up is available quickly enough for early-stage removal. Here the operation came two weeks after referral" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2020-01-18-8e93", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:31494983&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - dermatology / melanoma detection", "segment": "Consumer mobile health app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Howard H (2020). Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm. Daily Mail, 17 January 2020.", "title": "Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm", "url": "https://www.dailymail.co.uk/health/article-7898507/Man-mole-removed-finding-skin-cancer-app-told-visit-doctor.html", "date": "2020-01-17", "written_by": "independent", "quote": "After downloading SkinVision, the app immediately came back with a high-risk rating, and I was urged to go see a doctor as soon as possible." }, { "kind": "news report", "citation": "Al-Dostour (2020). سكان فيزيون. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة [Skin Vision: technology detects cancer in an innovative way]. dostor.org, 18 January 2020, crediting the Daily Mail; one of the five Arabic-language sources cited by the OECD Monitor.", "title": "سكان فيزيون.. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة", "url": "https://www.dostor.org/2974509", "date": "2020-01-18", "written_by": "independent", "quote": "وأفادت صحيفة \"ديلي ميل\" البريطانية، فإن الشاب جيسون شيريدان، (31 عاما) قد لاحظ وجود الشامة على ذراعه الأيسر لأول مرة في عام 2018" }, { "kind": "press release", "citation": "SkinVision (2025). SkinVision | Skin Cancer Detection App. Company website, fetched 20 October 2026; the page served to US visitors gives no legal entity or address.", "title": "SkinVision | Skin Cancer Detection App", "url": "https://www.skinvision.com/", "written_by": "makers", "quote": "SkinVision was founded with a mission to improve access to skin health information and support individuals in becoming more aware of their skin over time." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0107-source-0001", "AIBD-0107-source-0002", "AIBD-0107-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Howard H (2020). Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm. Daily Mail, 17 January 2020.", "title": "Saved by an app: Office worker, 31, is diagnosed with a deadly form of skin cancer after his mobile phone warned him about a tiny mole on his arm", "url": "https://www.dailymail.co.uk/health/article-7898507/Man-mole-removed-finding-skin-cancer-app-told-visit-doctor.html", "date": "2020-01-17", "written_by": "independent", "quote": "After downloading SkinVision, the app immediately came back with a high-risk rating, and I was urged to go see a doctor as soon as possible." }, { "kind": "news report", "citation": "Al-Dostour (2020). سكان فيزيون. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة [Skin Vision: technology detects cancer in an innovative way]. dostor.org, 18 January 2020, crediting the Daily Mail; one of the five Arabic-language sources cited by the OECD Monitor.", "title": "سكان فيزيون.. التكنولوجيا تكشف عن السرطان بطريقة مبتكرة", "url": "https://www.dostor.org/2974509", "date": "2020-01-18", "written_by": "independent", "quote": "وأفادت صحيفة \"ديلي ميل\" البريطانية، فإن الشاب جيسون شيريدان، (31 عاما) قد لاحظ وجود الشامة على ذراعه الأيسر لأول مرة في عام 2018" }, { "kind": "press release", "citation": "SkinVision (2025). SkinVision | Skin Cancer Detection App. Company website, fetched 20 October 2026; the page served to US visitors gives no legal entity or address.", "title": "SkinVision | Skin Cancer Detection App", "url": "https://www.skinvision.com/", "written_by": "makers", "quote": "SkinVision was founded with a mission to improve access to skin health information and support individuals in becoming more aware of their skin over time." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SkinVision rated a 31-year-old's changing arm mole high risk; stage 1A melanoma was found and removed, and he is cancer-free.", "account": "Jason Sheridan, a 31-year-old office worker from Liverpool living in Vauxhall, South London, noticed a new 1cm mole on his left arm in March 2018. He did not see a doctor. Twelve months later it turned pink and he checked it with SkinVision, an AI app that grades photographed moles low, medium or high risk. It returned a high-risk rating and urged him to see a doctor. His GP referred him to a dermatologist and two weeks later the mole was removed in a 40-minute operation. The biopsy showed stage 1A melanoma, a further biopsy found no spread, and he is cancer-free. The Daily Mail reported the case on 17 January 2020 without dates for the app check or surgery." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SkinVision skin-check app (AI analysis of smartphone photographs of moles, graded low, medium or high risk)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "SkinVision" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "SkinVision app rated a changing mole on Jason Sheridan's arm high risk; a dermatologist found stage 1A melanoma and it was removed", "headline": "SkinVision flags a mole as high risk; stage 1A melanoma removed" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "695ed3c0cef61a50eb97a4a79d29d0f1f61c2fb57087826e4ed8213ec7b02e69" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jason Sheridan, a 31-year-old office worker from Liverpool living in Vauxhall, South London, noticed a new 1cm mole on his left arm in March 2018. He did not see a doctor. Twelve months later it turned pink and he checked it with SkinVision, an AI app that grades photographed moles low, medium or high risk. It returned a high-risk rating and urged him to see a doctor. His GP referred him to a dermatologist and two weeks later the mole was removed in a 40-minute operation. The biopsy showed stage 1A melanoma, a further biopsy found no spread, and he is cancer-free. The Daily Mail reported the case on 17 January 2020 without dates for the app check or surgery.", "replication": { "produced_by": [ "A smartphone photograph of a changing mole submitted to SkinVision's risk classifier", "A high-risk rating with an instruction to see a doctor, acted on by the user", "A GP referral and an excision with pathology that confirms and stages the lesion" ], "must_hold": [ "The lesion is one the classifier can score from a phone photograph. The article reports no score or app version", "The user follows the app's advice rather than treating the rating as noise", "Clinical follow-up is available quickly enough for early-stage removal. Here the operation came two weeks after referral" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0284", "title": "Apple Watch Series 3 heart-rate drop from 99 to 65 bpm marks an 80-year-old woman's spontaneous reversion from atrial fibrillation, confirmed on a concurrent Holter", "summary": "Melbourne cardiologists matched 199 Apple Watch heart-rate readings to a Holter: the watch showed a sudden 99-to-65 bpm drop at 19:29 that coincided with reversion from AF to sinus rhythm.", "date_observed": "2020-02-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Toner, Al-Kaisey, Koshy and Lim of the Department of Cardiology, Austin Hospital, Melbourne, reported a case in BMJ Case Reports (published 4 February 2020). The event date is not given. An 80-year-old woman with known paroxysmal atrial fibrillation wore a 24-hour Holter monitor to assess rate control. On returning the monitor she reported feeling her heart “doing a flip” at 19:29. She noted her heart rate had suddenly dropped from 99 bpm to 65 bpm on her Apple Watch Series 3. The Holter showed she had reverted from AF to sinus rhythm at that time. The authors exported 199 watch readings over 22 hours and matched them to the Holter. The watch's average heart rate was 94 bpm in AF and 66 bpm after reversion. No notification, irregular-rhythm alert or electrocardiogram (ECG) app is described: the patient read the heart-rate display herself. The report documents no change in her treatment. The full text was not available from BMJ. The PMC copy is among the sources and names the device.", "category": "benefit created", "unexpected": false, "purpose": "The watch's optical heart-rate estimate is built to show the wearer their pulse. Its use here to time a rhythm change was that function, read by the patient rather than flagged by the device.", "system": "Apple Watch Series 3 heart-rate readings (optical photoplethysmography)", "model_version": "Apple Watch Series 3", "developer": "Apple", "deployer": null, "location": "Melbourne, Australia", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "The patient learned from her watch, and had confirmed by Holter, that her rhythm had reverted at 19:29. The report records no change in management, so the benefit is informational only." } ], "ai_role": { "status": "assessed", "statement": "No alert, notification or rhythm classifier was involved. The watch displayed a photoplethysmographic heart-rate estimate, the patient noticed the drop, and the authors compared the readings with the Holter afterwards. The paper does not describe the heart-rate estimation as machine learning. So the AI character of the contribution is not established." }, "evidence": [ { "kind": "case report", "citation": "Toner L, Al-Kaisey AM, Koshy A, Lim HS (2020). Spontaneous reversion of paroxysmal atrial fibrillation detected by smart watch. BMJ Case Reports 13(2):e233431. doi:10.1136/bcr-2019-233431 (PMC7035811).", "title": "Spontaneous reversion of paroxysmal atrial fibrillation detected by smart watch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7035811/", "date": "2020-02-04", "written_by": "independent", "quote": "she noted her heart rate suddenly drop from 99 bpm to 65 bpm as measured by her Apple Watch Series 3 (Cupertino, USA)" }, { "kind": "case report", "citation": "Toner L et al. (2020), BMJ Case Reports 13(2):e233431, Holter confirmation.", "title": "Spontaneous reversion of paroxysmal atrial fibrillation detected by smart watch", "url": "https://europepmc.org/article/MED/32024718", "date": "2020-02-04", "written_by": "independent", "quote": "Review of the Holter monitor revealed she had reverted from AF to SR at that time" }, { "kind": "case report", "citation": "Toner L et al. (2020), BMJ Case Reports 13(2):e233431, learning points.", "title": "Spontaneous reversion of paroxysmal atrial fibrillation detected by smart watch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7035811/", "date": "2020-02-04", "written_by": "independent", "quote": "Sudden and persistent changes in heart rate as detected by smart watches should alert clinicians to the possibility of cardiac rhythm changes." } ], "replication": { "produced_by": [ "A patient with known paroxysmal AF wearing a heart-rate-displaying smartwatch while a Holter monitor was also fitted", "The patient noticing and reporting a sudden, persistent heart-rate drop with its time", "Clinicians willing to export the watch readings (Apple Health app to Excel) and align them with the Holter" ], "must_hold": [ "The rhythm change produces a heart-rate change large enough to be visible on the watch's optical estimate", "A reference recording (Holter) exists to confirm what the watch suggested" ], "echoes": [] }, "paired_incident": null, "headline": "Apple Watch Series 3 drop from 99 to 65 bpm marks AF reversion", "metric": "sudden 99-to-65 bpm drop at 19:29 that coincided with reversion from AF to sinus rhythm", "comparator": { "against": "a concurrent 24-hour Holter monitor", "before": null, "after": null, "basis": "measured", "quote": "A total of 199 heart rate readings were recorded from the Apple Watch and matched to 199 readings of the same time intervals on Holter monitoring over a 22-hour period as shown in figure 2 (median interval 6 min and IQR of 5.75 min). Moreover, the average HR as measured by smart watch in AF prior to reversion was 94 bpm compared with 66 bpm after reversion to SR.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7035811/" }, "later": { "status": "unknown", "date": null, "note": "The report says only that outcomes of smartwatch-detected arrhythmias are the subject of ongoing research; nothing later was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent case reports. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0284", "catalog_version": "1.0.0", "source_fingerprint": "21ad16cb86c219fb89e5514f46842e2eef6316bcd0595a6f644bce5798f809ad", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0284-source-0001", "AIBD-0284-source-0002", "AIBD-0284-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "No alert, notification or rhythm classifier was involved. The watch displayed a photoplethysmographic heart-rate estimate, the patient noticed the drop, and the authors compared the readings with the Holter afterwards. The paper does not describe the heart-rate estimation as machine learning. So the AI character of the contribution is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "No alert, notification or rhythm classifier was involved. The watch displayed a photoplethysmographic heart-rate estimate, the patient noticed the drop, and the authors compared the readings with the Holter afterwards. The paper does not describe the heart-rate estimation as machine learning. So the AI character of the contribution is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "The patient learned from her watch, and had confirmed by Holter, that her rhythm had reverted at 19:29. 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The event date is not given. An 80-year-old woman with known paroxysmal atrial fibrillation wore a 24-hour Holter monitor to assess rate control. On returning the monitor she reported feeling her heart “doing a flip” at 19:29. She noted her heart rate had suddenly dropped from 99 bpm to 65 bpm on her Apple Watch Series 3. The Holter showed she had reverted from AF to sinus rhythm at that time. The authors exported 199 watch readings over 22 hours and matched them to the Holter. The watch's average heart rate was 94 bpm in AF and 66 bpm after reversion. No notification, irregular-rhythm alert or electrocardiogram (ECG) app is described: the patient read the heart-rate display herself. The report documents no change in her treatment. The full text was not available from BMJ. The PMC copy is among the sources and names the device." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used an Apple Watch Series 3." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Apple Watch Series 3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Series 3 heart-rate readings (optical photoplethysmography)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Series 3 heart-rate drop from 99 to 65 bpm marks an 80-year-old woman's spontaneous reversion from atrial fibrillation, confirmed on a concurrent Holter", "headline": "Apple Watch Series 3 drop from 99 to 65 bpm marks AF reversion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "21ad16cb86c219fb89e5514f46842e2eef6316bcd0595a6f644bce5798f809ad" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Toner, Al-Kaisey, Koshy and Lim of the Department of Cardiology, Austin Hospital, Melbourne, reported a case in BMJ Case Reports (published 4 February 2020). The event date is not given. An 80-year-old woman with known paroxysmal atrial fibrillation wore a 24-hour Holter monitor to assess rate control. On returning the monitor she reported feeling her heart “doing a flip” at 19:29. She noted her heart rate had suddenly dropped from 99 bpm to 65 bpm on her Apple Watch Series 3. The Holter showed she had reverted from AF to sinus rhythm at that time. The authors exported 199 watch readings over 22 hours and matched them to the Holter. The watch's average heart rate was 94 bpm in AF and 66 bpm after reversion. No notification, irregular-rhythm alert or electrocardiogram (ECG) app is described: the patient read the heart-rate display herself. The report documents no change in her treatment. The full text was not available from BMJ. The PMC copy is among the sources and names the device.", "replication": { "produced_by": [ "A patient with known paroxysmal AF wearing a heart-rate-displaying smartwatch while a Holter monitor was also fitted", "The patient noticing and reporting a sudden, persistent heart-rate drop with its time", "Clinicians willing to export the watch readings (Apple Health app to Excel) and align them with the Holter" ], "must_hold": [ "The rhythm change produces a heart-rate change large enough to be visible on the watch's optical estimate", "A reference recording (Holter) exists to confirm what the watch suggested" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0108", "title": "Two Tesla Model X cars stopped as a 400-year-old oak fell across the A31 at Sturminster Marshall during Storm Dennis; eight occupants walked away, and automatic emergency braking may have saved them", "summary": "Two Model X cars stopped as an oak fell on the A31 in Storm Dennis; eight occupants walked away, both drivers credit the emergency brakes.", "date_observed": "2020-02-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On the evening of Saturday 15 February 2020, during Storm Dennis, a 400-year-old oak fell across the A31 at Sturminster Marshall, Dorset. It hit two Tesla Model X cars going in opposite directions. Laurence Sanderson of Brentwood, Essex, was driving wife Anna and three children to a half-term holiday. He told the Mirror the car was on Autopilot, the emergency braking kicked in and the trunk landed on the bonnet. The other car, a Tesla loan vehicle driven by Josh Whitelock of Wimborne with Kitty McConnell and her mother Julia, also stopped suddenly. Whitelock told the Bournemouth Echo he was not sure its automatic brakes were enabled. Anna Sanderson had two black eyes and bruising. Nobody was seriously hurt.", "category": "protective response", "unexpected": false, "purpose": "Tesla's Autopilot hardware and software provide driver assistance and active safety features including Automatic Emergency Braking. It detects obstacles the car may hit and applies the brakes. Stopping short of a falling tree is that intended use as the drivers describe it.", "system": "Tesla Autopilot driver-assistance suite with Automatic Emergency Braking, on two Model X cars", "model_version": "Not reported; both cars were Tesla Model X, one a Tesla loan car, and no Autopilot hardware or software version is given", "developer": "Tesla", "deployer": null, "location": "Sturminster Marshall, United Kingdom", "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2020-02-18-956e" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A 400-year-old oak struck two cars at the bonnet. Eight people walked away with, at worst, two black eyes, a bump on the head and bruising. Both drivers and the Mirror call it life-saving. But that rests on the drivers' accounts, no telemetry or official assessment is reported, and the second driver was unsure the brakes were enabled." } ], "ai_role": { "status": "unassessed", "statement": "By Laurence Sanderson's account his car was on Autopilot and the emergency braking stopped it so the trunk hit the bonnet rather than the cabin. Josh Whitelock said he was not sure whether his loan car's automatic brakes were enabled and credited its other safety features. No Tesla data, police finding or engineering assessment of whether either system braked, or whether the drivers would have stopped in time themselves, is reported. Elon Musk's reply, “Glad you're all ok”, acknowledges the outcome, not the mechanism." }, "evidence": [ { "kind": "news report", "citation": "Rudd A (2020). Tesla Autopilot saves family's lives after tree crushes car in Storm Dennis. Daily Mirror, 17 February 2020 (exclusive).", "title": "Tesla Autopilot saves family's lives after tree crushes car in Storm Dennis", "url": "https://www.mirror.co.uk/news/uk-news/tesla-autopilot-saves-familys-life-21512255", "date": "2020-02-17", "written_by": "independent", "quote": "We were driving along and out of the corner of my eye I saw the tree coming down. The car was on Autopilot and the emergency braking kicked in." }, { "kind": "news report", "citation": "Bournemouth Echo (2020). 'Miracle' as falling tree narrowly misses two Teslas - because the cars have automatic emergency brakes. Bournemouth Echo, 18 February 2020.", "title": "'Miracle' as falling tree misses Tesla cars because of brakes", "url": "https://www.bournemouthecho.co.uk/news/18240206.miracle-falling-tree-narrowly-misses-killing-families-two-tesla-model-xs---cars-automatic-emergency-brakes/", "date": "2020-02-18", "written_by": "independent", "quote": "the incident on Saturday evening, which happened on the A31 near Vines Farm Shop east of the Roundhouse roundabout at Sturminster Marshall" }, { "kind": "news report", "citation": "Bournemouth Echo (2020). 'My life flashed before my eyes': Driver of second Tesla crushed by falling tree describes lucky escape. Bournemouth Echo, 19 February 2020.", "title": "Tesla driver's lucky escape after falling tree hits cars during Storm Dennis", "url": "https://www.bournemouthecho.co.uk/news/18245292.tesla-drivers-lucky-escape-falling-tree-hits-cars-storm-dennis/", "date": "2020-02-19", "written_by": "independent", "quote": "said he isn't sure whether the automatic brakes were enabled at the time, but said the car's other safety features enabled him and his two passengers to walk away unscathed" }, { "kind": "news report", "citation": "Gratton J (2020). Families escape after Tesla Model X's automatic brakes stopped a falling tree from crushing them during Storm Dennis. The Sun, 17 February 2020.", "title": "Families escape after Tesla Model X's automatic brakes stopped a falling tree from crushing them during Storm Dennis", "url": "https://www.thesun.co.uk/motors/10979882/families-miracle-escape-teslas-automatic-brakes-stopped-tree/", "date": "2020-02-17", "written_by": "independent", "quote": "The A31 was blocked in both directions due to the massive tree fall." }, { "kind": "other", "citation": "Sanderson L (@sterlingandlaw) (2020). Tweet to @elonmusk and @Tesla with two photographs of the crushed car, 15 February 2020, 23:14 UTC; text retrieved through the fxtwitter API.", "title": "Tweet by Laurence Sanderson, 15 February 2020", "url": "https://twitter.com/sterlingandlaw/status/1228819929832525826", "date": "2020-02-15", "written_by": "beneficiary", "quote": "The tree below fell on our car today. Autopilot kicked in and saved us. The car on the other side is a model x as well. 9 lives saved." }, { "kind": "news report", "citation": "Rudd A (2020). Elon Musk 'glad everyone is ok' after Tesla Autopilot saves 8 lives in Storm Dennis. Daily Mirror, 19 February 2020.", "title": "Elon Musk 'glad everyone is ok' after Tesla Autopilot saves 8 lives in Storm Dennis", "url": "https://www.mirror.co.uk/news/uk-news/elon-musk-glad-everyone-ok-21527013", "date": "2020-02-19", "written_by": "independent", "quote": "Elon replied with a heart emoji and said: ''Glad you're all ok.''" }, { "kind": "news report", "citation": "La Vanguardia (2020). El Autopilot de Tesla salva la vida a 8 personas de la tormenta Dennis. La Vanguardia, 19 February 2020, citing the Mirror; one of the four Spanish-language sources cited by the OECD Monitor.", "title": "El Autopilot de Tesla salva la vida a 8 personas de la tormenta Dennis", "url": "https://www.lavanguardia.com/motor/actualidad/20200219/473657698342/el-autopilot-de-tesla-salva-la-vida-a-8-personas-tormenta-dennis-reino-unido-arbol-elon-musk.html", "date": "2020-02-19", "written_by": "independent", "quote": "Los dos vehículos, que circulaban con el piloto automático, activaron los frenos de emergencia justo en el momento en que un roble de 400 años caía" }, { "kind": "news report", "citation": "RAC (2020). Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis. RAC Drive news, undated on the page; Google News lists 19 February 2020.", "title": "Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis", "url": "https://www.rac.co.uk/drive/news/autonomous-vehicles-news/tesla-model-xs-automatic-brakes-just-saved-two-families-from-a-falling-tree/", "date": null, "written_by": "independent", "quote": "an oak tree came crashing down onto their bonnet rather than their roof, thanks to the smart safety feature" } ], "replication": { "produced_by": [ "Automatic Emergency Braking active on a Tesla Model X whose cameras and radar register an obstacle entering its path", "A hazard that arrives in front of the car, here a tree falling across the carriageway, rather than onto the roof from above", "A stop short of the point where the trunk lands, leaving the bonnet rather than the cabin to take the impact" ], "must_hold": [ "The system has time to detect and brake, which Sanderson put at about a second", "The vehicle's structure withstands the part of the impact that still lands. Whitelock credited the car's other safety features", "Occupants are belted. The Whitelock passengers were sore from the seatbelts" ], "echoes": [] }, "paired_incident": null, "headline": "Two Tesla Model X cars stop as an oak falls; eight walk away", "metric": "eight occupants walked away", "comparator": null, "later": { "status": "unknown", "date": null, "note": "Later coverage on 19 February 2020 only added Elon Musk's reply that he was glad everyone was OK; both cars were written off and no further development was reported.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2020-02-18-956e", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0108", "catalog_version": "1.0.0", "source_fingerprint": "711695c7ca3fbdc1da9ec1e4e39bb39f6e8dcfa022a9f5500d8c002d80cf18d3", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0108-source-0001", "AIBD-0108-source-0002", "AIBD-0108-source-0003", "AIBD-0108-source-0004", "AIBD-0108-source-0005", "AIBD-0108-source-0006", "AIBD-0108-source-0007", "AIBD-0108-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "unassessed", "statement": "By Laurence Sanderson's account his car was on Autopilot and the emergency braking stopped it so the trunk hit the bonnet rather than the cabin. Josh Whitelock said he was not sure whether his loan car's automatic brakes were enabled and credited its other safety features. No Tesla data, police finding or engineering assessment of whether either system braked, or whether the drivers would have stopped in time themselves, is reported. Elon Musk's reply, “Glad you're all ok”, acknowledges the outcome, not the mechanism." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 400-year-old oak struck two cars at the bonnet. Eight people walked away with, at worst, two black eyes, a bump on the head and bruising. Both drivers and the Mirror call it life-saving. But that rests on the drivers' accounts, no telemetry or official assessment is reported, and the second driver was unsure the brakes were enabled." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: seven independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 400-year-old oak struck two cars at the bonnet. Eight people walked away with, at worst, two black eyes, a bump on the head and bruising. Both drivers and the Mirror call it life-saving. But that rests on the drivers' accounts, no telemetry or official assessment is reported, and the second driver was unsure the brakes were enabled." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 400-year-old oak struck two cars at the bonnet. Eight people walked away with, at worst, two black eyes, a bump on the head and bruising. Both drivers and the Mirror call it life-saving. But that rests on the drivers' accounts, no telemetry or official assessment is reported, and the second driver was unsure the brakes were enabled." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", 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The car on the other side is a model x as well. 9 lives saved." }, { "kind": "news report", "citation": "Rudd A (2020). Elon Musk 'glad everyone is ok' after Tesla Autopilot saves 8 lives in Storm Dennis. Daily Mirror, 19 February 2020.", "title": "Elon Musk 'glad everyone is ok' after Tesla Autopilot saves 8 lives in Storm Dennis", "url": "https://www.mirror.co.uk/news/uk-news/elon-musk-glad-everyone-ok-21527013", "date": "2020-02-19", "written_by": "independent", "quote": "Elon replied with a heart emoji and said: ''Glad you're all ok.''" }, { "kind": "news report", "citation": "La Vanguardia (2020). El Autopilot de Tesla salva la vida a 8 personas de la tormenta Dennis. La Vanguardia, 19 February 2020, citing the Mirror; one of the four Spanish-language sources cited by the OECD Monitor.", "title": "El Autopilot de Tesla salva la vida a 8 personas de la tormenta Dennis", "url": "https://www.lavanguardia.com/motor/actualidad/20200219/473657698342/el-autopilot-de-tesla-salva-la-vida-a-8-personas-tormenta-dennis-reino-unido-arbol-elon-musk.html", "date": "2020-02-19", "written_by": "independent", "quote": "Los dos vehículos, que circulaban con el piloto automático, activaron los frenos de emergencia justo en el momento en que un roble de 400 años caía" }, { "kind": "news report", "citation": "RAC (2020). Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis. RAC Drive news, undated on the page; Google News lists 19 February 2020.", "title": "Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis", "url": "https://www.rac.co.uk/drive/news/autonomous-vehicles-news/tesla-model-xs-automatic-brakes-just-saved-two-families-from-a-falling-tree/", "written_by": "independent", "quote": "an oak tree came crashing down onto their bonnet rather than their roof, thanks to the smart safety feature" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0108-source-0001", "AIBD-0108-source-0002", "AIBD-0108-source-0003", "AIBD-0108-source-0004", "AIBD-0108-source-0005", "AIBD-0108-source-0006", "AIBD-0108-source-0007", "AIBD-0108-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Rudd A (2020). 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The Sun, 17 February 2020.", "title": "Families escape after Tesla Model X's automatic brakes stopped a falling tree from crushing them during Storm Dennis", "url": "https://www.thesun.co.uk/motors/10979882/families-miracle-escape-teslas-automatic-brakes-stopped-tree/", "date": "2020-02-17", "written_by": "independent", "quote": "The A31 was blocked in both directions due to the massive tree fall." }, { "kind": "other", "citation": "Sanderson L (@sterlingandlaw) (2020). Tweet to @elonmusk and @Tesla with two photographs of the crushed car, 15 February 2020, 23:14 UTC; text retrieved through the fxtwitter API.", "title": "Tweet by Laurence Sanderson, 15 February 2020", "url": "https://twitter.com/sterlingandlaw/status/1228819929832525826", "date": "2020-02-15", "written_by": "beneficiary", "quote": "The tree below fell on our car today. Autopilot kicked in and saved us. 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La Vanguardia, 19 February 2020, citing the Mirror; one of the four Spanish-language sources cited by the OECD Monitor.", "title": "El Autopilot de Tesla salva la vida a 8 personas de la tormenta Dennis", "url": "https://www.lavanguardia.com/motor/actualidad/20200219/473657698342/el-autopilot-de-tesla-salva-la-vida-a-8-personas-tormenta-dennis-reino-unido-arbol-elon-musk.html", "date": "2020-02-19", "written_by": "independent", "quote": "Los dos vehículos, que circulaban con el piloto automático, activaron los frenos de emergencia justo en el momento en que un roble de 400 años caía" }, { "kind": "news report", "citation": "RAC (2020). Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis. RAC Drive news, undated on the page; Google News lists 19 February 2020.", "title": "Tesla Model X's automatic brakes just saved two families from a falling tree during Storm Dennis", "url": "https://www.rac.co.uk/drive/news/autonomous-vehicles-news/tesla-model-xs-automatic-brakes-just-saved-two-families-from-a-falling-tree/", "written_by": "independent", "quote": "an oak tree came crashing down onto their bonnet rather than their roof, thanks to the smart safety feature" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Two Model X cars stopped as an oak fell on the A31 in Storm Dennis; eight occupants walked away, both drivers credit the emergency brakes.", "account": "On the evening of Saturday 15 February 2020, during Storm Dennis, a 400-year-old oak fell across the A31 at Sturminster Marshall, Dorset. It hit two Tesla Model X cars going in opposite directions. Laurence Sanderson of Brentwood, Essex, was driving wife Anna and three children to a half-term holiday. He told the Mirror the car was on Autopilot, the emergency braking kicked in and the trunk landed on the bonnet. The other car, a Tesla loan vehicle driven by Josh Whitelock of Wimborne with Kitty McConnell and her mother Julia, also stopped suddenly. Whitelock told the Bournemouth Echo he was not sure its automatic brakes were enabled. Anna Sanderson had two black eyes and bruising. Nobody was seriously hurt." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The driver reported that the system applied emergency braking." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Both vehicles were Tesla Model X cars, including one loan car. The installed Autopilot software was not identified." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; both cars were Tesla Model X, one a Tesla loan car, and no Autopilot hardware or software version is given" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Autopilot driver-assistance suite with Automatic Emergency Braking, on two Model X cars" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Two Tesla Model X cars stopped as a 400-year-old oak fell across the A31 at Sturminster Marshall during Storm Dennis; eight occupants walked away, and automatic emergency braking may have saved them", "headline": "Two Tesla Model X cars stop as an oak falls; eight walk away" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "711695c7ca3fbdc1da9ec1e4e39bb39f6e8dcfa022a9f5500d8c002d80cf18d3" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the evening of Saturday 15 February 2020, during Storm Dennis, a 400-year-old oak fell across the A31 at Sturminster Marshall, Dorset. It hit two Tesla Model X cars going in opposite directions. Laurence Sanderson of Brentwood, Essex, was driving wife Anna and three children to a half-term holiday. He told the Mirror the car was on Autopilot, the emergency braking kicked in and the trunk landed on the bonnet. The other car, a Tesla loan vehicle driven by Josh Whitelock of Wimborne with Kitty McConnell and her mother Julia, also stopped suddenly. Whitelock told the Bournemouth Echo he was not sure its automatic brakes were enabled. Anna Sanderson had two black eyes and bruising. Nobody was seriously hurt.", "replication": { "produced_by": [ "Automatic Emergency Braking active on a Tesla Model X whose cameras and radar register an obstacle entering its path", "A hazard that arrives in front of the car, here a tree falling across the carriageway, rather than onto the roof from above", "A stop short of the point where the trunk lands, leaving the bonnet rather than the cabin to take the impact" ], "must_hold": [ "The system has time to detect and brake, which Sanderson put at about a second", "The vehicle's structure withstands the part of the impact that still lands. Whitelock credited the car's other safety features", "Occupants are belted. The Whitelock passengers were sore from the seatbelts" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0016", "title": "Halicin: a deep-learning-identified antibiotic validated in vitro and in mice, with no verified human outcome", "summary": "A deep-learning screen identified halicin, active in vitro and in mice and confirmed by other labs; no human outcome.", "date_observed": "2020-02-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Jonathan Stokes, Regina Barzilay, James Collins and colleagues at MIT, the Broad Institute, Harvard and McMaster University published in Cell on 20 February 2020. They reported halicin, a molecule identified by a directed-message-passing neural network trained on 2,335 molecules to predict inhibition of E. coli growth. Halicin, originally investigated as a kinase inhibitor for diabetes, is structurally divergent from conventional antibiotics. It reduced Acinetobacter baumannii in a mouse wound model and cleared Clostridioides difficile in a mouse infection model. Independent laboratories at KACST in Riyadh (December 2021) and Central South University in Changsha (September 2022) confirmed antibacterial activity in vitro. The latter also in a mouse abscess model. No clinical use or human trial result appears in any cited source.", "category": "general benefit", "unexpected": false, "purpose": "Built to predict molecules that inhibit bacterial growth and surface antibiotic candidates. Halicin was that purpose.", "system": "Directed-message-passing neural network (D-MPNN) for antibacterial activity prediction (Chemprop-style, MIT)", "model_version": "Chemprop (directed-message passing neural network)", "developer": "Massachusetts Institute of Technology (Collins and Barzilay laboratories) with the Broad Institute", "deployer": "MIT / Broad Institute / McMaster University research teams", "location": "Cambridge, United States", "domain": "Biomedicine / antibiotic discovery", "segment": "Academic research", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "The sources document in vitro and murine results and independent laboratory confirmation. No individually attributable real-world outcome such as a treated patient or an approved drug." } ], "ai_role": { "status": "assessed", "statement": "The neural network's prediction selected halicin for testing from compounds not previously recognized as antibiotics. Wet-lab experiments by the authors and later by independent groups confirmed the activity. The outcome so far is a laboratory and animal-model result." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Stokes, J. M. et al. (2020). A Deep Learning Approach to Antibiotic Discovery. Cell 180, 688–702 (PMC8349178).", "title": "A deep learning approach to antibiotic discovery", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8349178/", "date": "2020-02-20", "written_by": "makers", "quote": "sterilization of 3 out of 4 mice after 72 hr of treatment, and 4 out of 4 mice after 96 hr of treatment." }, { "kind": "peer-reviewed study", "citation": "Booq, R. Y., Tawfik, E. A., Alfassam, H. A., Alfahad, A. J. and Alyamani, E. J. (2021). Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria. Antibiotics 10(12), 1480 (PMC8698312).", "title": "Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8698312/", "date": "2021-12-02", "written_by": "independent", "quote": "The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations—including the A. baumannii multidrug-resistant (MDR) isolate." }, { "kind": "peer-reviewed study", "citation": "Hussain, Z. et al. (2022). Study on antibacterial effect of halicin (SU3327) against Enterococcus faecalis and Enterococcus faecium. Pathogens and Disease 80(1), ftac037.", "title": "Study on antibacterial effect of halicin (SU3327) against Enterococcus faecalis and Enterococcus faecium", "url": "https://academic.oup.com/femspd/article/80/1/ftac037/6713948", "date": "2022-09-24", "written_by": "independent", "quote": "the minimum inhibitory concentrations (MIC) of halicin against different strains of Enterococcus faecalis and Enterococcus faecium ranged from 4 to 8 μg/ml." } ], "replication": { "produced_by": [ "A growth-inhibition training set of a few thousand molecules", "A message-passing network ranking large chemical libraries", "Wet-lab confirmation of predicted actives and animal-model testing" ], "must_hold": [ "Predicted compounds must be available for synthesis or purchase", "Activity must be confirmed experimentally. A verified real-world outcome would require clinical use" ], "echoes": [ { "date": "2023-05-25", "setting": "Abaucin, a narrow-spectrum anti-Acinetobacter baumannii compound identified by a neural network trained on about 7,500 screened molecules (McMaster and MIT), controlled infection in a mouse wound model; preclinical only", "model_version": null, "outcome": "recurred", "source": "https://www.nature.com/articles/s41589-023-01349-8" } ] }, "paired_incident": null, "headline": "MIT neural network finds halicin, active in vitro and in mice", "metric": null, "comparator": { "against": "vehicle control and the first-line antibiotic metronidazole in a mouse Clostridioides difficile infection model", "before": "vehicle or the antibiotic metronidazole (lower clearance rate)", "after": "sterilization of 3 out of 4 mice after 72 hr of treatment, and 4 out of 4 mice after 96 hr of treatment", "basis": "measured", "quote": "Excitingly, we observed that halicin resulted in C. difficile clearance at a greater rate than vehicle or the antibiotic metronidazole (Figure 5F), which is not only a first-line treatment for C. difficile infection, but also the antibiotic most similar to halicin based on Tanimoto score (Figure 2H, Table S2H). Indeed, halicin resulted in sterilization of 3 out of 4 mice after 72 hr of treatment, and 4 out of 4 mice after 96 hr of treatment.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8349178/" }, "later": { "status": "persisted", "date": "2021-12-02", "note": "An independent laboratory at KACST in Riyadh confirmed halicin's in vitro activity against gram-positive and gram-negative strains, including a multidrug-resistant A. baumannii isolate; the compound remains preclinical.", "quote": "The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations—including the A. baumannii multidrug-resistant (MDR) isolate.", "url": "https://europepmc.org/article/PMC/PMC8698312" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced all three evidence quotes with the sentences as printed in the cited papers, because the Booq quote had been given a subject borrowed from the Discussion and the Hussain and Stokes quotes silently abbreviated or dropped words.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8349178/ ; https://pmc.ncbi.nlm.nih.gov/articles/PMC8698312/ ; https://academic.oup.com/femspd/article/80/1/ftac037/6713948", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC8698312", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Massachusetts_Institute_of_Technology; https://en.wikipedia.org/wiki/Massachusetts_Institute_of_Technology", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent peer-reviewed studies and the makers' peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0016", "catalog_version": "1.0.0", "source_fingerprint": "0e6e61d4447ed41359c83cadadf51134cefa7b3dbdc88c8bf85eab0ca77cb7db", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0016-source-0001", "AIBD-0016-source-0002", "AIBD-0016-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Massachusetts Institute of Technology (Collins and Barzilay laboratories) with the Broad Institute", "deployer": "MIT / Broad Institute / McMaster University research teams" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The neural network's prediction selected halicin for testing from compounds not previously recognized as antibiotics. Wet-lab experiments by the authors and later by independent groups confirmed the activity. The outcome so far is a laboratory and animal-model result." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The neural network's prediction selected halicin for testing from compounds not previously recognized as antibiotics. Wet-lab experiments by the authors and later by independent groups confirmed the activity. The outcome so far is a laboratory and animal-model result." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: two independent peer-reviewed studies and the makers' peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The sources document in vitro and murine results and independent laboratory confirmation. No individually attributable real-world outcome such as a treated patient or an approved drug." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The sources document in vitro and murine results and independent laboratory confirmation. No individually attributable real-world outcome such as a treated patient or an approved drug." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2021-12-02", "note": "An independent laboratory at KACST in Riyadh confirmed halicin's in vitro activity against gram-positive and gram-negative strains, including a multidrug-resistant A. baumannii isolate; the compound remains preclinical.", "quote": "The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations—including the A. baumannii multidrug-resistant (MDR) isolate.", "url": "https://europepmc.org/article/PMC/PMC8698312" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0016" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jonathan Stokes, Regina Barzilay, James Collins and colleagues at MIT, the Broad Institute, Harvard and McMaster University published in Cell on 20 February 2020. They reported halicin, a molecule identified by a directed-message-passing neural network trained on 2,335 molecules to predict inhibition of E. coli growth. Halicin, originally investigated as a kinase inhibitor for diabetes, is structurally divergent from conventional antibiotics. It reduced Acinetobacter baumannii in a mouse wound model and cleared Clostridioides difficile in a mouse infection model. Independent laboratories at KACST in Riyadh (December 2021) and Central South University in Changsha (September 2022) confirmed antibacterial activity in vitro. The latter also in a mouse abscess model. 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Halicin was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cambridge, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to predict molecules that inhibit bacterial growth and surface antibiotic candidates. 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M. et al. (2020). A Deep Learning Approach to Antibiotic Discovery. Cell 180, 688–702 (PMC8349178).", "title": "A deep learning approach to antibiotic discovery", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8349178/", "date": "2020-02-20", "written_by": "makers", "quote": "sterilization of 3 out of 4 mice after 72 hr of treatment, and 4 out of 4 mice after 96 hr of treatment." }, { "kind": "peer-reviewed study", "citation": "Booq, R. Y., Tawfik, E. A., Alfassam, H. A., Alfahad, A. J. and Alyamani, E. J. (2021). Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria. Antibiotics 10(12), 1480 (PMC8698312).", "title": "Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8698312/", "date": "2021-12-02", "written_by": "independent", "quote": "The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations—including the A. baumannii multidrug-resistant (MDR) isolate." }, { "kind": "peer-reviewed study", "citation": "Hussain, Z. et al. (2022). Study on antibacterial effect of halicin (SU3327) against Enterococcus faecalis and Enterococcus faecium. Pathogens and Disease 80(1), ftac037.", "title": "Study on antibacterial effect of halicin (SU3327) against Enterococcus faecalis and Enterococcus faecium", "url": "https://academic.oup.com/femspd/article/80/1/ftac037/6713948", "date": "2022-09-24", "written_by": "independent", "quote": "the minimum inhibitory concentrations (MIC) of halicin against different strains of Enterococcus faecalis and Enterococcus faecium ranged from 4 to 8 μg/ml." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0016-source-0001", "AIBD-0016-source-0002", "AIBD-0016-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Stokes, J. 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Antibiotics 10(12), 1480 (PMC8698312).", "title": "Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8698312/", "date": "2021-12-02", "written_by": "independent", "quote": "The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations—including the A. baumannii multidrug-resistant (MDR) isolate." }, { "kind": "peer-reviewed study", "citation": "Hussain, Z. et al. (2022). Study on antibacterial effect of halicin (SU3327) against Enterococcus faecalis and Enterococcus faecium. 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They reported halicin, a molecule identified by a directed-message-passing neural network trained on 2,335 molecules to predict inhibition of E. coli growth. Halicin, originally investigated as a kinase inhibitor for diabetes, is structurally divergent from conventional antibiotics. It reduced Acinetobacter baumannii in a mouse wound model and cleared Clostridioides difficile in a mouse infection model. Independent laboratories at KACST in Riyadh (December 2021) and Central South University in Changsha (September 2022) confirmed antibacterial activity in vitro. The latter also in a mouse abscess model. No clinical use or human trial result appears in any cited source." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model predicted antibacterial activity to select compounds for laboratory testing." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A directed-message-passing neural network." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Chemprop (directed-message passing neural network)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Directed-message-passing neural network (D-MPNN) for antibacterial activity prediction (Chemprop-style, MIT)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Massachusetts Institute of Technology (Collins and Barzilay laboratories) with the Broad Institute" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Halicin: a deep-learning-identified antibiotic validated in vitro and in mice, with no verified human outcome", "headline": "MIT neural network finds halicin, active in vitro and in mice" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0e6e61d4447ed41359c83cadadf51134cefa7b3dbdc88c8bf85eab0ca77cb7db" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jonathan Stokes, Regina Barzilay, James Collins and colleagues at MIT, the Broad Institute, Harvard and McMaster University published in Cell on 20 February 2020. They reported halicin, a molecule identified by a directed-message-passing neural network trained on 2,335 molecules to predict inhibition of E. coli growth. Halicin, originally investigated as a kinase inhibitor for diabetes, is structurally divergent from conventional antibiotics. It reduced Acinetobacter baumannii in a mouse wound model and cleared Clostridioides difficile in a mouse infection model. Independent laboratories at KACST in Riyadh (December 2021) and Central South University in Changsha (September 2022) confirmed antibacterial activity in vitro. The latter also in a mouse abscess model. No clinical use or human trial result appears in any cited source.", "replication": { "produced_by": [ "A growth-inhibition training set of a few thousand molecules", "A message-passing network ranking large chemical libraries", "Wet-lab confirmation of predicted actives and animal-model testing" ], "must_hold": [ "Predicted compounds must be available for synthesis or purchase", "Activity must be confirmed experimentally. A verified real-world outcome would require clinical use" ], "echoes": [ { "date": "2023-05-25", "setting": "Abaucin, a narrow-spectrum anti-Acinetobacter baumannii compound identified by a neural network trained on about 7,500 screened molecules (McMaster and MIT), controlled infection in a mouse wound model; preclinical only", "outcome": "recurred", "source": "https://www.nature.com/articles/s41589-023-01349-8" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0109", "title": "Tesla Model S on Autopilot braked and steered right to avoid a wrong-way driver on Highway 49 in Cabarrus County, North Carolina, before driver Bret Peters had reacted", "summary": "Bret Peters's Model S on Autopilot braked and moved right as a wrong-way car came at him on Highway 49, NC; TeslaCam recorded the near miss.", "date_observed": "2020-02-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Before dawn on 27 February 2020, Bret Peters, a father and former state trooper, was driving his 2020 Tesla Model S on Autopilot. He was on Highway 49 near Cabarrus Arena in Concord, Cabarrus County, North Carolina. A car traveling the wrong way at about 60 mph came toward him in his lane. He wrote on Facebook that he did not see it until after Autopilot hit the brakes and started steering away. TeslaCam footage, aired by Fox 46 Charlotte and described by Electrek and the Daily Mail, shows the Tesla moving into the right lane. The oncoming car swerves onto the grassy median. There was no collision, and no police or Tesla statement is reported.", "category": "protective response", "unexpected": false, "purpose": "Autopilot is a driver-assistance system that steers, accelerates and brakes within a lane and includes collision-avoidance features. Braking and moving away from an oncoming vehicle is within that intended use as the driver describes it.", "system": "Tesla Autopilot on a 2020 Model S, with TeslaCam dashcam recording", "model_version": "2020 Tesla Model S per the Daily Mail; Autopilot software version not reported", "developer": "Tesla", "deployer": null, "location": "Concord, North Carolina, United States", "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2020-03-07-752c" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "By his account and the footage as described, one driver was moved out of a wrong-way car's path at about 60 mph before he reacted. The other driver also swerved onto the median, so whether a collision would have occurred is unknown. No avoided injury or damage can be measured." } ], "ai_role": { "status": "assessed", "statement": "By Peters's account Autopilot braked and began a lane change to the right before he had seen the oncoming car. The TeslaCam footage, as described by Electrek and the Daily Mail, shows the Tesla moving right while the wrong-way car veers off-road. The claim rests on the driver's statements and the footage. Neither Tesla nor police is quoted, and the oncoming driver's own swerve means the system's action cannot be shown to have been decisive." }, "evidence": [ { "kind": "news report", "citation": "Edmonds L, Pero J (2020). Incredible moment Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway. Daily Mail, 9 March 2020, quoting Peters's Facebook post and his interview with Fox 46 Charlotte.", "title": "Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway", "url": "https://www.dailymail.co.uk/news/article-8092899/Model-S-Tesla-swerves-Autopilot-avoid-wrong-way-driver-dark-North-Carolina-highway.html", "date": "2020-03-09", "written_by": "independent", "quote": "The car coming at me was masked by the cultural lighting and I didn't see them until AFTER Autopilot hit the brakes and started steering away from the oncoming car." }, { "kind": "news report", "citation": "Lambert F (2020). Tesla Autopilot automatically avoids head-on collision with car in wrong lane. Electrek, 9 March 2020, embedding the Fox 46 Charlotte report and placing the event 'last week'.", "title": "Tesla Autopilot automatically avoids head-on collision with car in wrong lane", "url": "https://electrek.co/2020/03/09/tesla-autopilot-automatically-avoids-head-on-collision-car-wrong-lane/", "date": "2020-03-09", "written_by": "independent", "quote": "it shows that the vehicle in the wrong lane started swerving off-road as it was getting closer to the Tesla, but the latter also moved toward the right lane" }, { "kind": "news report", "citation": "Crider J (2020). 'Dear Tesla & Elon Musk.. Because Of You I Won't Be Going To A Funeral'. CleanTechnica, 8 March 2020, relaying a since-deleted Reddit post and the Fox 46 Charlotte report.", "title": "'Dear Tesla & Elon Musk ... 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Incredible moment Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway. Daily Mail, 9 March 2020, quoting Peters's Facebook post and his interview with Fox 46 Charlotte.", "title": "Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway", "url": "https://www.dailymail.co.uk/news/article-8092899/Model-S-Tesla-swerves-Autopilot-avoid-wrong-way-driver-dark-North-Carolina-highway.html", "date": "2020-03-09", "written_by": "independent", "quote": "The car coming at me was masked by the cultural lighting and I didn't see them until AFTER Autopilot hit the brakes and started steering away from the oncoming car." }, { "kind": "news report", "citation": "Lambert F (2020). Tesla Autopilot automatically avoids head-on collision with car in wrong lane. Electrek, 9 March 2020, embedding the Fox 46 Charlotte report and placing the event 'last week'.", "title": "Tesla Autopilot automatically avoids head-on collision with car in wrong lane", "url": "https://electrek.co/2020/03/09/tesla-autopilot-automatically-avoids-head-on-collision-car-wrong-lane/", "date": "2020-03-09", "written_by": "independent", "quote": "it shows that the vehicle in the wrong lane started swerving off-road as it was getting closer to the Tesla, but the latter also moved toward the right lane" }, { "kind": "news report", "citation": "Crider J (2020). 'Dear Tesla & Elon Musk.. Because Of You I Won't Be Going To A Funeral'. CleanTechnica, 8 March 2020, relaying a since-deleted Reddit post and the Fox 46 Charlotte report.", "title": "'Dear Tesla & Elon Musk ... Because Of You I Won't Be Going To A Funeral'", "url": "https://cleantechnica.com/2020/03/08/dear-tesla-elon-musk-because-of-you-i-wont-be-going-to-a-funeral/", "date": "2020-03-08", "written_by": "independent", "quote": "Before I could put my foot on the brake, it had already started changing lanes" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0109-source-0001", "AIBD-0109-source-0002", "AIBD-0109-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Edmonds L, Pero J (2020). Incredible moment Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway. Daily Mail, 9 March 2020, quoting Peters's Facebook post and his interview with Fox 46 Charlotte.", "title": "Model S Tesla swerves on Autopilot to avoid wrong-way driver on a dark North Carolina highway", "url": "https://www.dailymail.co.uk/news/article-8092899/Model-S-Tesla-swerves-Autopilot-avoid-wrong-way-driver-dark-North-Carolina-highway.html", "date": "2020-03-09", "written_by": "independent", "quote": "The car coming at me was masked by the cultural lighting and I didn't see them until AFTER Autopilot hit the brakes and started steering away from the oncoming car." }, { "kind": "news report", "citation": "Lambert F (2020). Tesla Autopilot automatically avoids head-on collision with car in wrong lane. Electrek, 9 March 2020, embedding the Fox 46 Charlotte report and placing the event 'last week'.", "title": "Tesla Autopilot automatically avoids head-on collision with car in wrong lane", "url": "https://electrek.co/2020/03/09/tesla-autopilot-automatically-avoids-head-on-collision-car-wrong-lane/", "date": "2020-03-09", "written_by": "independent", "quote": "it shows that the vehicle in the wrong lane started swerving off-road as it was getting closer to the Tesla, but the latter also moved toward the right lane" }, { "kind": "news report", "citation": "Crider J (2020). 'Dear Tesla & Elon Musk.. Because Of You I Won't Be Going To A Funeral'. CleanTechnica, 8 March 2020, relaying a since-deleted Reddit post and the Fox 46 Charlotte report.", "title": "'Dear Tesla & Elon Musk ... Because Of You I Won't Be Going To A Funeral'", "url": "https://cleantechnica.com/2020/03/08/dear-tesla-elon-musk-because-of-you-i-wont-be-going-to-a-funeral/", "date": "2020-03-08", "written_by": "independent", "quote": "Before I could put my foot on the brake, it had already started changing lanes" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Bret Peters's Model S on Autopilot braked and moved right as a wrong-way car came at him on Highway 49, NC; TeslaCam recorded the near miss.", "account": "Before dawn on 27 February 2020, Bret Peters, a father and former state trooper, was driving his 2020 Tesla Model S on Autopilot. He was on Highway 49 near Cabarrus Arena in Concord, Cabarrus County, North Carolina. A car traveling the wrong way at about 60 mph came toward him in his lane. He wrote on Facebook that he did not see it until after Autopilot hit the brakes and started steering away. TeslaCam footage, aired by Fox 46 Charlotte and described by Electrek and the Daily Mail, shows the Tesla moving into the right lane. The oncoming car swerves onto the grassy median. There was no collision, and no police or Tesla statement is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The driver reported that Autopilot braked and began changing lanes." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The report identified a 2020 Tesla Model S, without an installed Autopilot release." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "2020 Tesla Model S per the Daily Mail; Autopilot software version not reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Autopilot on a 2020 Model S, with TeslaCam dashcam recording" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Tesla Model S on Autopilot braked and steered right to avoid a wrong-way driver on Highway 49 in Cabarrus County, North Carolina, before driver Bret Peters had reacted", "headline": "Tesla Autopilot brakes and steers clear of a wrong-way driver" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7cf9b39d840930f0bfc162270db094f304c2a731033a0bf0a7b5e2df9de54356" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Before dawn on 27 February 2020, Bret Peters, a father and former state trooper, was driving his 2020 Tesla Model S on Autopilot. He was on Highway 49 near Cabarrus Arena in Concord, Cabarrus County, North Carolina. A car traveling the wrong way at about 60 mph came toward him in his lane. He wrote on Facebook that he did not see it until after Autopilot hit the brakes and started steering away. TeslaCam footage, aired by Fox 46 Charlotte and described by Electrek and the Daily Mail, shows the Tesla moving into the right lane. The oncoming car swerves onto the grassy median. There was no collision, and no police or Tesla statement is reported.", "replication": { "produced_by": [ "Autopilot engaged on a divided highway at night, with an adjacent lane the system has registered as empty", "An oncoming vehicle entering the Tesla's lane within range of its forward cameras and radar", "Automatic braking and a lane change executed before the driver reacts" ], "must_hold": [ "A clear adjacent lane exists; Peters said the car knew nobody was to his right", "The oncoming vehicle is detected early enough at a closing speed of around 60 mph plus the Tesla's own", "The driver does not override the maneuver" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0063", "title": "Lunit INSIGHT CXR flags incidental nodules on chest radiographs taken for other reasons; 13 patients at Yongin Severance Hospital had resectable lung cancer", "summary": "AI on routine chest X-rays flagged nodules in 13 patients not suspected of lung cancer; all had resectable cancer, 7 stage I, and surgery.", "date_observed": "2020-03-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At Yongin Severance Hospital, Yongin, South Korea, the deep-learning software Lunit INSIGHT CXR (versions 2 and 3, Lunit Inc.) was applied to chest radiographs. Kwak and colleagues reported in PLOS ONE on 10 March 2023 on 75 patients with resectable lung cancer between March 2020 and February 2022. Of these, 13 (17.3%) had cancers found incidentally because the software flagged a nodule on a radiograph taken for an unrelated reason. One was a 60-year-old man, a current smoker, imaged before cholecystectomy, whose left upper lobe adenocarcinoma was stage IA1. He saw a pulmonologist three days later, after the radiologist's report. The paper reports eight of the 13 saw a pulmonologist the same day, before the radiologist's official report. Its Table 1 is not fully consistent with this figure. All 13 had resection and seven were stage I needing no further treatment.", "category": "benefit created", "unexpected": false, "purpose": "Lunit INSIGHT CXR is built to detect and localize abnormalities, including nodules, on chest radiographs. Incidental detection of lung cancer is its intended function.", "system": "Lunit INSIGHT CXR", "model_version": "versions 2 and 3", "developer": "Lunit Inc.", "deployer": "Yongin Severance Hospital, Yonsei University College of Medicine", "location": "Yongin, South Korea", "domain": "Healthcare - thoracic radiology / lung cancer", "segment": "AI applied to routine hospital chest radiographs", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Thirteen patients had early, resectable lung cancer diagnosed and operated on. Seven were stage I and needed no further treatment. A survival benefit is plausible but not demonstrated in the paper." }, { "group": "organizational", "depth": 1, "reason": "Eight patients were seen by a pulmonologist on the day of the radiograph, before the formal report, shortening the diagnostic pathway." } ], "ai_role": { "status": "assessed", "statement": "The software flagged all 13 nodules and its results were visible to ordering clinicians on PACS immediately after the radiograph. The authors assume from medical-record timestamps that the AI results aided the same-day consultations in 8 of 13 patients. They acknowledge that whether clinicians acted on the AI result or on the radiologist's report cannot be settled from the study. Radiologists also read the films. In 12 of 13 cases the radiologist's report described an abnormality at the site. There the contribution is earlier attention to findings nobody was looking for. In one (patient 12) the report read “No active lung disease”, so the AI flagged a cancer that the formal report missed." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Kwak SH, Kim EK, Kim MH, Lee EH, Shin HJ (2023). Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs. PLOS ONE 18(3):e0281690.", "title": "Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10004566/", "date": "2023-03-10", "written_by": "deployer", "quote": "Eight patients (61.5%) consulted a pulmonologist promptly on the same day when the chest radiograph was taken and before they received the radiologist's official report." }, { "kind": "peer-reviewed study", "citation": "Kwak SH et al. (2023). PLOS ONE 18(3):e0281690 (second quotation).", "title": "Incidentally found resectable lung cancer with the usage of artificial intelligence on chest radiographs", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10004566/", "date": "2023-03-10", "written_by": "deployer", "quote": "Seven patients (53.8%) were in stage I, which meant no additional treatment was required after surgery." } ], "replication": { "produced_by": [ "Routine AI analysis of chest radiographs with results visible to ordering clinicians in real time", "A prompt pulmonology referral pathway for AI-flagged nodules" ], "must_hold": [ "Clinicians review AI flags on films ordered for non-pulmonary reasons", "CT follow-up and tissue diagnosis for flagged nodules" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "81", "title": "Researchers find evidence of racial, gender, and socioeconomic bias in chest X-ray classifiers", "url": "https://incidentdatabase.ai/cite/81", "severity": null, "group": "personal", "basis": "Same system class and task, AI classification of routine chest radiographs: the classifiers studied showed gender, racial and socioeconomic bias that underdiagnoses patients, the group Lunit's incidental nodule flags benefited." }, "headline": "Lunit INSIGHT CXR finds 13 resectable lung cancers incidentally", "metric": "13 (17.3%) had cancers found incidentally because the software flagged a nodule", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later report on these 13 patients or on the Yongin Severance deployment appears in the cited paper.", "quote": null, "url": null }, "value": null, "developer_country": "South Korea", "deployer_country": "South Korea", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 81 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/81", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account and AI-role statement corrected against the paper's Table 1 and limitations: the example patient (patient 2) is a current smoker who saw a pulmonologist three days after the radiologist's report, the same-day consultations are the authors' timestamp-based assumption rather than a demonstrated AI effect, and one of the 13 radiologist reports (patient 12) read “No active lung disease”.", "source": "Kwak SH, Kim EK, Kim MH, Lee EH, Shin HJ (2023). PLOS ONE 18(3):e0281690, Table 1 and Discussion (limitations), https://pmc.ncbi.nlm.nih.gov/articles/PMC10004566/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.lunit.io/en/contact; https://ko.wikipedia.org/wiki/%EC%9A%A9%EC%9D%B8%EC%84%B8%EB%B8%8C%EB%9E%80%EC%8A%A4%EB%B3%91%EC%9B%90", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0063", "catalog_version": "1.0.0", "source_fingerprint": "3d322e6fbf2835ba613f9621741daa31fd7c7800a98629b503274e8e027bf96d", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0063-source-0001", "AIBD-0063-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Lunit Inc.", "deployer": "Yongin Severance Hospital, Yonsei University College of Medicine" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The software flagged all 13 nodules and its results were visible to ordering clinicians on PACS immediately after the radiograph. The authors assume from medical-record timestamps that the AI results aided the same-day consultations in 8 of 13 patients. They acknowledge that whether clinicians acted on the AI result or on the radiologist's report cannot be settled from the study. Radiologists also read the films. In 12 of 13 cases the radiologist's report described an abnormality at the site. There the contribution is earlier attention to findings nobody was looking for. In one (patient 12) the report read “No active lung disease”, so the AI flagged a cancer that the formal report missed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Lunit INSIGHT CXR flagged all 13 nodules and made the results available to clinicians immediately after the chest X-rays. In one patient, it flagged a nodule that proved cancerous where the radiologist had reported no active lung disease.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The software flagged all 13 nodules and its results were visible to ordering clinicians on PACS immediately after the radiograph. The authors assume from medical-record timestamps that the AI results aided the same-day consultations in 8 of 13 patients. They acknowledge that whether clinicians acted on the AI result or on the radiologist's report cannot be settled from the study. Radiologists also read the films. In 12 of 13 cases the radiologist's report described an abnormality at the site. There the contribution is earlier attention to findings nobody was looking for. In one (patient 12) the report read “No active lung disease”, so the AI flagged a cancer that the formal report missed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Thirteen patients had early, resectable lung cancer diagnosed and operated on. Seven were stage I and needed no further treatment. A survival benefit is plausible but not demonstrated in the paper." }, { "group": "organizational", "depth": 1, "reason": "Eight patients were seen by a pulmonologist on the day of the radiograph, before the formal report, shortening the diagnostic pathway." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Thirteen patients had early, resectable lung cancer diagnosed and operated on. Seven were stage I and needed no further treatment. A survival benefit is plausible but not demonstrated in the paper." }, { "group": "organizational", "depth": 1, "reason": "Eight patients were seen by a pulmonologist on the day of the radiograph, before the formal report, shortening the diagnostic pathway." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Thirteen patients had early, resectable lung cancer diagnosed and operated on. Seven were stage I and needed no further treatment. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "versions 2 and 3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Lunit INSIGHT CXR versions 2 and 3.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Lunit INSIGHT CXR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Lunit Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lunit INSIGHT CXR flags incidental nodules on chest radiographs taken for other reasons; 13 patients at Yongin Severance Hospital had resectable lung cancer", "headline": "Lunit INSIGHT CXR finds 13 resectable lung cancers incidentally" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3d322e6fbf2835ba613f9621741daa31fd7c7800a98629b503274e8e027bf96d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At Yongin Severance Hospital, Yongin, South Korea, the deep-learning software Lunit INSIGHT CXR (versions 2 and 3, Lunit Inc.) was applied to chest radiographs. Kwak and colleagues reported in PLOS ONE on 10 March 2023 on 75 patients with resectable lung cancer between March 2020 and February 2022. Of these, 13 (17.3%) had cancers found incidentally because the software flagged a nodule on a radiograph taken for an unrelated reason. One was a 60-year-old man, a current smoker, imaged before cholecystectomy, whose left upper lobe adenocarcinoma was stage IA1. He saw a pulmonologist three days later, after the radiologist's report. The paper reports eight of the 13 saw a pulmonologist the same day, before the radiologist's official report. Its Table 1 is not fully consistent with this figure. All 13 had resection and seven were stage I needing no further treatment.", "replication": { "produced_by": [ "Routine AI analysis of chest radiographs with results visible to ordering clinicians in real time", "A prompt pulmonology referral pathway for AI-flagged nodules" ], "must_hold": [ "Clinicians review AI flags on films ordered for non-pulmonary reasons", "CT follow-up and tissue diagnosis for flagged nodules" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0322", "title": "PlantVillage Nuru helps Busia County cassava farmer Josephine Arisat select clean cuttings; her yields may have risen from 0.5 kg to 2–5 kg per plant", "summary": "PlantVillage's own 23 Mar 2020 post: after 18 months using Nuru, introduced via Self Help Africa and Ugunja Resource Center, Arisat reports 2.0–5.0 kg per plant against 0.5 kg; no independent source.", "date_observed": "2020-03-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A PlantVillage (Pennsylvania State University) blog post dated 23 March 2020, profiles Josephine Arisat of Asing'e location, Busia County. The CGIAR Platform for Big Data in Agriculture's project page links it as a “Success story from a cassava farmer in Busia County, Kenya”. She has grown cassava since 1995 and had been using the PlantVillage Nuru smartphone app “for a period of One and a half years”. Organizations “such as SHA and Ugunja Resource Center” introduced it. She is quoted: “Initially, I used to harvest rotten cassava tubers whereas their leaves looked healthy. I never knew that Cassava leaves can showcase diseases”. With Nuru she can scan leaves for cassava mosaic disease, cassava green mite or cassava brown streak disease and get management advice. The post states that before Nuru she “would harvest just 0.5kg per Cassava plant”. Using the app to select healthy cuttings to replant, “she harvests between 2.0–5.0 kg per Cassava plant”. It also records that she switched in 2016 to certified seed (MM06 and Mygeria varieties) and joined an aggregation selling to True Trade in 2019. She recommends one-meter spacing. The post does not separate any of these from the app's effect. Per CGIAR's page, Nuru was tested in Busia County “in partnership with Self Help Africa, a charity helping 28,000 farmers in the cassava value chain”. It says over 100 lead farmers there received smartphones at the start of 2019. Mrisho et al. (Frontiers in Plant Science, 2020), co-authored by PlantVillage and IITA developers, measured Nuru's symptom-recognition accuracy. It was 65% in 2020 versus 40–58% for extension agents and 18–31% for farmers, including 50 farmers from Busia County. That paper reports no individual outcomes. Business Insider (10 August 2022) independently quotes a Kilifi County farmer, Caroline Dama Kitsao, on Nuru. “The levels of pests and diseases in our farms have reduced, and our crops are more healthy”, she said. It quotes PlantVillage's David Hughes claiming yield increases “between 130% to 530%”. No peer-reviewed or agency source documents Arisat's case. Separate records cover Nuru's accuracy study and FAO fall armyworm use.", "category": "benefit created", "unexpected": false, "purpose": "Nuru is built to recognize cassava disease and pest symptoms on leaves offline and give management advice. Selecting clean cuttings from diagnosed plants is that intended use.", "system": "PlantVillage Nuru (offline TensorFlow convolutional neural network for cassava disease and pest symptoms on a smartphone)", "model_version": null, "developer": "PlantVillage, Pennsylvania State University, with the International Institute of Tropical Agriculture (IITA)", "deployer": "Self Help Africa and Ugunja Resource Center (lead-farmer program in Busia County)", "location": "Asing'e, Busia County, Kenya", "domain": "Agriculture / crop disease diagnosis", "segment": "Smallholder cassava", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The documented outcome is a higher cassava yield, and the type names the diagnostic information that produced it.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Arisat's reported rise from 0.5 kg to 2.0 to 5.0 kg per plant is a measurable improvement in her harvest. It comes only from the developer's blog, with no independent source." } ], "ai_role": { "status": "unassessed", "statement": "Only the maker's account exists for this case. PlantVillage's post attributes the yield change, in the farmer's words, to Nuru's leaf-scanning diagnosis guiding removal of diseased plants and selection of clean cuttings. The independent evidence concerns the model's accuracy (Mrisho et al. 2020, developer co-authored) and another farmer's self-report in Business Insider, not Arisat. So the AI's share of her outcome cannot be assessed." }, "evidence": [ { "kind": "press release", "citation": "PlantVillage (2020). Successful stories of cassava farmers in Busia County. PlantVillage blog, Pennsylvania State University, 23 March 2020 (developer-authored; linked from the CGIAR Big Data Inspire Challenge project page).", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "Before using PlantVillage Nuru smartphone application, Josephine would harvest just 0.5kg per Cassava plant." }, { "kind": "press release", "citation": "PlantVillage (2020), same post.", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "she harvests between 2.0-5.0 kg per Cassava plant." }, { "kind": "press release", "citation": "CGIAR Platform for Big Data in Agriculture (undated). PlantVillage Nuru: Pest and disease monitoring using artificial intelligence. Inspire Challenge 2017 pilot and 2019 scale-up project page (partner-written; links the Arisat post as a success story).", "title": "PlantVillage Nuru: Pest and disease monitoring using artificial intelligence", "url": "https://bigdata.cgiar.org/inspire/inspire-challenge-2017/pest-and-disease-monitoring-by-using-artificial-intelligence/", "date": null, "written_by": "makers", "quote": "In Busia County, Kenya, PlantVillage is working with over 100 Lead Farmers who received smartphones at the beginning of 2019." }, { "kind": "peer-reviewed study", "citation": "Mrisho LM, Mbilinyi NA, Ndalahwa M, Ramcharan AM, Kehs AK, McCloskey PC, Murithi H, Hughes DP, Legg JP (2020). Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD. Frontiers in Plant Science 11:590889 (PMC7775399; developer co-authored).", "title": "Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7775399/", "date": "2020-12-17", "written_by": "makers", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40-58%) and farmers (18-31%)." }, { "kind": "news report", "citation": "Business Insider (2022). US state university developed an AI assistant for African farmers. 10 August 2022.", "title": "US state university developed an AI assistant for African farmers", "url": "https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8", "date": "2022-08-10", "written_by": "independent", "quote": "The levels of pests and diseases in our farms have reduced, and our crops are more healthy." } ], "replication": { "produced_by": [ "A smartphone with Nuru supplied through a lead-farmer scheme (Self Help Africa, Ugunja Resource Center) with training", "Use of the diagnosis to uproot diseased plants and select clean cuttings for replanting" ], "must_hold": [ "Symptoms are visible on leaves. Mrisho et al. report accuracy rising when six leaves per plant are scanned", "The app's effect is separable from certified seed, spacing and market changes, which the post does not attempt" ], "echoes": [ { "date": "2022-08-10", "setting": "Kilifi County cassava and maize farmer Caroline Dama Kitsao, who joined PlantVillage in 2020, quoted by Business Insider (self-report)", "model_version": null, "outcome": "recurred", "source": "https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8" } ] }, "paired_incident": null, "headline": "Nuru may have lifted cassava yield from 0.5 kg to 2–5 kg a plant", "metric": "2.0–5.0 kg per plant against 0.5 kg", "comparator": { "against": "the same farmer's harvests before she used the Nuru app", "before": "0.5kg per Cassava plant", "after": "between 2.0-5.0 kg per Cassava plant", "basis": "assumed", "quote": "Before using PlantVillage Nuru smartphone application, Josephine would harvest just 0.5kg per Cassava plant. With an AI assistant in her hand helping her to select healthy cassava cuttings to replant, she harvests between 2.0-5.0 kg per Cassava plant.", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county" }, "later": { "status": "scaled", "date": "2022-08-10", "note": "By August 2022 Business Insider reported Nuru extended to eight more countries, with PlantVillage's David Hughes claiming cassava yield increases of 130% to 530%, and CGIAR's project page records 240 phones distributed to Bungoma, Kilifi and Tanzania in April 2021.", "quote": "PlantVillage has expanded some of its projects, including Nuru, to Uganda, Tanzania, Ethiopia, Mozambique, Malawi, Burkina Faso, Nepal, and Honduras.", "url": "https://web.archive.org/web/20221002175306/https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8" }, "value": null, "developer_country": "United States", "deployer_country": "Kenya", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 2 for personal on the documented outcome, with the reason stated on each rating.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county; https://web.archive.org/web/20221002175306/https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://selfhelpafrica.org/ie/where-we-work/kenya/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Self Help Africa.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0322", "catalog_version": "1.0.0", "source_fingerprint": "78586b05c4ff5ef3d2e0a49c22ce8058798b8291e04bffa7cc718fa6336d9411", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0322-source-0001", "AIBD-0322-source-0002", "AIBD-0322-source-0003", "AIBD-0322-source-0004", "AIBD-0322-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "PlantVillage, Pennsylvania State University, with the International Institute of Tropical Agriculture (IITA)", "deployer": "Self Help Africa and Ugunja Resource Center (lead-farmer program in Busia County)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "Only the maker's account exists for this case. PlantVillage's post attributes the yield change, in the farmer's words, to Nuru's leaf-scanning diagnosis guiding removal of diseased plants and selection of clean cuttings. The independent evidence concerns the model's accuracy (Mrisho et al. 2020, developer co-authored) and another farmer's self-report in Business Insider, not Arisat. So the AI's share of her outcome cannot be assessed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Arisat's reported rise from 0.5 kg to 2.0 to 5.0 kg per plant is a measurable improvement in her harvest. It comes only from the developer's blog, with no independent source." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the makers' peer-reviewed study and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Arisat's reported rise from 0.5 kg to 2.0 to 5.0 kg per plant is a measurable improvement in her harvest. It comes only from the developer's blog, with no independent source." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Arisat's reported rise from 0.5 kg to 2.0 to 5.0 kg per plant is a measurable improvement in her harvest. 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University) blog post dated 23 March 2020, profiles Josephine Arisat of Asing'e location, Busia County. The CGIAR Platform for Big Data in Agriculture's project page links it as a “Success story from a cassava farmer in Busia County, Kenya”. She has grown cassava since 1995 and had been using the PlantVillage Nuru smartphone app “for a period of One and a half years”. Organizations “such as SHA and Ugunja Resource Center” introduced it. She is quoted: “Initially, I used to harvest rotten cassava tubers whereas their leaves looked healthy. I never knew that Cassava leaves can showcase diseases”. With Nuru she can scan leaves for cassava mosaic disease, cassava green mite or cassava brown streak disease and get management advice. The post states that before Nuru she “would harvest just 0.5kg per Cassava plant”. Using the app to select healthy cuttings to replant, “she harvests between 2.0–5.0 kg per Cassava plant”. It also records that she switched in 2016 to certified seed (MM06 and Mygeria varieties) and joined an aggregation selling to True Trade in 2019. She recommends one-meter spacing. The post does not separate any of these from the app's effect. Per CGIAR's page, Nuru was tested in Busia County “in partnership with Self Help Africa, a charity helping 28,000 farmers in the cassava value chain”. It says over 100 lead farmers there received smartphones at the start of 2019. Mrisho et al. (Frontiers in Plant Science, 2020), co-authored by PlantVillage and IITA developers, measured Nuru's symptom-recognition accuracy. It was 65% in 2020 versus 40–58% for extension agents and 18–31% for farmers, including 50 farmers from Busia County. That paper reports no individual outcomes. Business Insider (10 August 2022) independently quotes a Kilifi County farmer, Caroline Dama Kitsao, on Nuru. “The levels of pests and diseases in our farms have reduced, and our crops are more healthy”, she said. It quotes PlantVillage's David Hughes claiming yield increases “between 130% to 530%”. No peer-reviewed or agency source documents Arisat's case. Separate records cover Nuru's accuracy study and FAO fall armyworm use.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Arisat's reported rise from 0.5 kg to 2.0 to 5.0 kg per plant is a measurable improvement in her harvest. 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Successful stories of cassava farmers in Busia County. PlantVillage blog, Pennsylvania State University, 23 March 2020 (developer-authored; linked from the CGIAR Big Data Inspire Challenge project page).", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "Before using PlantVillage Nuru smartphone application, Josephine would harvest just 0.5kg per Cassava plant." }, { "kind": "press release", "citation": "PlantVillage (2020), same post.", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "she harvests between 2.0-5.0 kg per Cassava plant." }, { "kind": "press release", "citation": "CGIAR Platform for Big Data in Agriculture (undated). PlantVillage Nuru: Pest and disease monitoring using artificial intelligence. Inspire Challenge 2017 pilot and 2019 scale-up project page (partner-written; links the Arisat post as a success story).", "title": "PlantVillage Nuru: Pest and disease monitoring using artificial intelligence", "url": "https://bigdata.cgiar.org/inspire/inspire-challenge-2017/pest-and-disease-monitoring-by-using-artificial-intelligence/", "written_by": "makers", "quote": "In Busia County, Kenya, PlantVillage is working with over 100 Lead Farmers who received smartphones at the beginning of 2019." }, { "kind": "peer-reviewed study", "citation": "Mrisho LM, Mbilinyi NA, Ndalahwa M, Ramcharan AM, Kehs AK, McCloskey PC, Murithi H, Hughes DP, Legg JP (2020). Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD. Frontiers in Plant Science 11:590889 (PMC7775399; developer co-authored).", "title": "Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7775399/", "date": "2020-12-17", "written_by": "makers", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40-58%) and farmers (18-31%)." }, { "kind": "news report", "citation": "Business Insider (2022). US state university developed an AI assistant for African farmers. 10 August 2022.", "title": "US state university developed an AI assistant for African farmers", "url": "https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8", "date": "2022-08-10", "written_by": "independent", "quote": "The levels of pests and diseases in our farms have reduced, and our crops are more healthy." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0322-source-0001", "AIBD-0322-source-0002", "AIBD-0322-source-0003", "AIBD-0322-source-0004", "AIBD-0322-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "PlantVillage (2020). Successful stories of cassava farmers in Busia County. PlantVillage blog, Pennsylvania State University, 23 March 2020 (developer-authored; linked from the CGIAR Big Data Inspire Challenge project page).", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "Before using PlantVillage Nuru smartphone application, Josephine would harvest just 0.5kg per Cassava plant." }, { "kind": "press release", "citation": "PlantVillage (2020), same post.", "title": "Successful stories of cassava farmers in Busia County", "url": "https://plantvillage.psu.edu/blogposts/71-successful-stories-of-cassava-farmers-in-busia-county", "date": "2020-03-23", "written_by": "makers", "quote": "she harvests between 2.0-5.0 kg per Cassava plant." }, { "kind": "press release", "citation": "CGIAR Platform for Big Data in Agriculture (undated). PlantVillage Nuru: Pest and disease monitoring using artificial intelligence. Inspire Challenge 2017 pilot and 2019 scale-up project page (partner-written; links the Arisat post as a success story).", "title": "PlantVillage Nuru: Pest and disease monitoring using artificial intelligence", "url": "https://bigdata.cgiar.org/inspire/inspire-challenge-2017/pest-and-disease-monitoring-by-using-artificial-intelligence/", "written_by": "makers", "quote": "In Busia County, Kenya, PlantVillage is working with over 100 Lead Farmers who received smartphones at the beginning of 2019." }, { "kind": "peer-reviewed study", "citation": "Mrisho LM, Mbilinyi NA, Ndalahwa M, Ramcharan AM, Kehs AK, McCloskey PC, Murithi H, Hughes DP, Legg JP (2020). Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD. Frontiers in Plant Science 11:590889 (PMC7775399; developer co-authored).", "title": "Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7775399/", "date": "2020-12-17", "written_by": "makers", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40-58%) and farmers (18-31%)." }, { "kind": "news report", "citation": "Business Insider (2022). US state university developed an AI assistant for African farmers. 10 August 2022.", "title": "US state university developed an AI assistant for African farmers", "url": "https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8", "date": "2022-08-10", "written_by": "independent", "quote": "The levels of pests and diseases in our farms have reduced, and our crops are more healthy." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "PlantVillage's own 23 Mar 2020 post: after 18 months using Nuru, introduced via Self Help Africa and Ugunja Resource Center, Arisat reports 2.0–5.0 kg per plant against 0.5 kg; no independent source.", "account": "A PlantVillage (Pennsylvania State University) blog post dated 23 March 2020, profiles Josephine Arisat of Asing'e location, Busia County. The CGIAR Platform for Big Data in Agriculture's project page links it as a “Success story from a cassava farmer in Busia County, Kenya”. She has grown cassava since 1995 and had been using the PlantVillage Nuru smartphone app “for a period of One and a half years”. Organizations “such as SHA and Ugunja Resource Center” introduced it. She is quoted: “Initially, I used to harvest rotten cassava tubers whereas their leaves looked healthy. I never knew that Cassava leaves can showcase diseases”. With Nuru she can scan leaves for cassava mosaic disease, cassava green mite or cassava brown streak disease and get management advice. The post states that before Nuru she “would harvest just 0.5kg per Cassava plant”. Using the app to select healthy cuttings to replant, “she harvests between 2.0–5.0 kg per Cassava plant”. It also records that she switched in 2016 to certified seed (MM06 and Mygeria varieties) and joined an aggregation selling to True Trade in 2019. She recommends one-meter spacing. The post does not separate any of these from the app's effect. Per CGIAR's page, Nuru was tested in Busia County “in partnership with Self Help Africa, a charity helping 28,000 farmers in the cassava value chain”. It says over 100 lead farmers there received smartphones at the start of 2019. Mrisho et al. (Frontiers in Plant Science, 2020), co-authored by PlantVillage and IITA developers, measured Nuru's symptom-recognition accuracy. It was 65% in 2020 versus 40–58% for extension agents and 18–31% for farmers, including 50 farmers from Busia County. That paper reports no individual outcomes. Business Insider (10 August 2022) independently quotes a Kilifi County farmer, Caroline Dama Kitsao, on Nuru. “The levels of pests and diseases in our farms have reduced, and our crops are more healthy”, she said. It quotes PlantVillage's David Hughes claiming yield increases “between 130% to 530%”. No peer-reviewed or agency source documents Arisat's case. Separate records cover Nuru's accuracy study and FAO fall armyworm use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PlantVillage Nuru (offline TensorFlow convolutional neural network for cassava disease and pest symptoms on a smartphone)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "PlantVillage, Pennsylvania State University, with the International Institute of Tropical Agriculture (IITA)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "PlantVillage Nuru helps Busia County cassava farmer Josephine Arisat select clean cuttings; her yields may have risen from 0.5 kg to 2–5 kg per plant", "headline": "Nuru may have lifted cassava yield from 0.5 kg to 2–5 kg a plant" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "78586b05c4ff5ef3d2e0a49c22ce8058798b8291e04bffa7cc718fa6336d9411" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A PlantVillage (Pennsylvania State University) blog post dated 23 March 2020, profiles Josephine Arisat of Asing'e location, Busia County. The CGIAR Platform for Big Data in Agriculture's project page links it as a “Success story from a cassava farmer in Busia County, Kenya”. She has grown cassava since 1995 and had been using the PlantVillage Nuru smartphone app “for a period of One and a half years”. Organizations “such as SHA and Ugunja Resource Center” introduced it. She is quoted: “Initially, I used to harvest rotten cassava tubers whereas their leaves looked healthy. I never knew that Cassava leaves can showcase diseases”. With Nuru she can scan leaves for cassava mosaic disease, cassava green mite or cassava brown streak disease and get management advice. The post states that before Nuru she “would harvest just 0.5kg per Cassava plant”. Using the app to select healthy cuttings to replant, “she harvests between 2.0–5.0 kg per Cassava plant”. It also records that she switched in 2016 to certified seed (MM06 and Mygeria varieties) and joined an aggregation selling to True Trade in 2019. She recommends one-meter spacing. The post does not separate any of these from the app's effect. Per CGIAR's page, Nuru was tested in Busia County “in partnership with Self Help Africa, a charity helping 28,000 farmers in the cassava value chain”. It says over 100 lead farmers there received smartphones at the start of 2019. Mrisho et al. (Frontiers in Plant Science, 2020), co-authored by PlantVillage and IITA developers, measured Nuru's symptom-recognition accuracy. It was 65% in 2020 versus 40–58% for extension agents and 18–31% for farmers, including 50 farmers from Busia County. That paper reports no individual outcomes. Business Insider (10 August 2022) independently quotes a Kilifi County farmer, Caroline Dama Kitsao, on Nuru. “The levels of pests and diseases in our farms have reduced, and our crops are more healthy”, she said. It quotes PlantVillage's David Hughes claiming yield increases “between 130% to 530%”. No peer-reviewed or agency source documents Arisat's case. Separate records cover Nuru's accuracy study and FAO fall armyworm use.", "replication": { "produced_by": [ "A smartphone with Nuru supplied through a lead-farmer scheme (Self Help Africa, Ugunja Resource Center) with training", "Use of the diagnosis to uproot diseased plants and select clean cuttings for replanting" ], "must_hold": [ "Symptoms are visible on leaves. Mrisho et al. report accuracy rising when six leaves per plant are scanned", "The app's effect is separable from certified seed, spacing and market changes, which the post does not attempt" ], "echoes": [ { "date": "2022-08-10", "setting": "Kilifi County cassava and maize farmer Caroline Dama Kitsao, who joined PlantVillage in 2020, quoted by Business Insider (self-report)", "outcome": "recurred", "source": "https://www.businessinsider.com/us-state-university-developed-an-ai-assistant-for-african-farmers-2022-8" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0307", "title": "Odakyu Electric Railway starts a Panasonic deep-learning “fall detection system” on existing station cameras at Kyōdō and Soshigaya-Ōkura stations", "summary": "From 1 April 2020 Odakyu's system analyzes existing platform camera video to flag people who fall onto the tracks or linger at the platform edge and alerts station staff; no outcomes are reported.", "date_observed": "2020-04-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Odakyu Electric Railway announced on 30 March 2020 (press release republished by Nikkei) a 転落検知システム (fall detection system). It would operate from the first train on 1 April 2020 at Kyōdō (経堂) and Soshigaya-Ōkura (祖師ヶ谷大蔵) stations on the Odakyu Line. It uses video from existing station cameras. Built with Panasonic System Solutions Japan, the system applies Panasonic's image-analysis and deep-learning technology to analyze the camera feeds in real time. It alerts a dedicated terminal in the station office, showing the camera image, when it detects a person fallen from the platform onto the tracks. It does the same for a person who has stayed at the platform edge for a set time and risks contact with a train. Staff can then take safety measures such as an emergency stop. Pre-learning to set each camera's detection area and to distinguish people from trains had run at both stations since December 2019. Impress Watch reported the launch on 31 March 2020. Neither source reports any detection, prevented accident or performance figure, and no later outcome report was found. Impress Watch (7 October 2024) reported a separate trial of Asilla's behavior-recognition “AI Security asilla” on all 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations. It ran from 10 October 2024 to 9 January 2025. It tested detection of falls from the platform, wheelchair and white-cane users, people lingering on the platform, disputes between passengers and suspicious objects. Results were not reported. Romanizations of station names are ours; the sources give them in Japanese.", "category": "general benefit", "unexpected": false, "purpose": "Built to detect people falling from the platform onto the tracks or lingering at the platform edge and alert station staff. No detection event is documented.", "system": "転落検知システム (fall detection system): Panasonic image-analysis and deep-learning on existing station cameras", "model_version": null, "developer": "Panasonic System Solutions Japan, with Odakyu Electric Railway", "deployer": "Odakyu Electric Railway", "location": "Kyōdō and Soshigaya-Ōkura stations, Odakyu Line, Japan", "domain": "Railway safety / platform fall detection", "segment": "Station platform monitoring", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No fall, alert or prevented accident is reported by any source." }, { "group": "organizational", "depth": null, "reason": "The operator describes the intended staff workflow; no count of alerts, false alarms or staff time saved is published." } ], "ai_role": { "status": "unassessed", "statement": "No event involving the system is documented. The account comes from Odakyu's own launch release and Impress Watch's report of it. They describe what the deep-learning analysis is meant to detect and how staff are alerted. The 2024 Asilla trial at two other stations is a separate system whose results were not reported." }, "evidence": [ { "kind": "news report", "citation": "Impress Watch (2020). 既設の駅構内カメラで転落者自動検知。小田急. 31 March 2020.", "title": "既設の駅構内カメラで転落者自動検知。小田急", "url": "https://www.watch.impress.co.jp/docs/news/1243957.html", "date": "2020-03-31", "written_by": "independent", "quote": "ホームから線路への転落者を自動検知、駅係員に通知する「転落検知システム」の運用を4月1日より開始。小田急線経堂駅と祖師ヶ谷大蔵駅に設置される。" }, { "kind": "press release", "citation": "Odakyu Electric Railway (2020). 小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始. Press release of 30 March 2020, republished by Nikkei.", "title": "小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始", "url": "https://www.nikkei.com/article/DGXLRSP531980_Q0A330C2000000/", "date": "2020-03-30", "written_by": "deployer", "quote": "パナソニックが有する画像解析とディープラーニング（深層学習）技術を鉄道環境に応用し、既設の駅構内カメラの映像をリアルタイムに解析を行い" }, { "kind": "news report", "citation": "Impress Watch (2024). 小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知. 7 October 2024 (the Asilla trial echo).", "title": "小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知", "url": "https://www.watch.impress.co.jp/docs/news/1629496.html", "date": "2024-10-07", "written_by": "independent", "quote": "ホームからの転落や車いす利用者、不審者・不審物を適正に検知可能かを検証する。" } ], "replication": { "produced_by": [ "Existing station cameras covering the platform edge and track at two stations", "Panasonic deep-learning image analysis trained from December 2019 to set detection areas and tell people from trains", "A dedicated terminal in the station office that shows the alert and video for staff to act on" ], "must_hold": [ "Station staff present to confirm the alert and order an emergency stop", "Detection areas calibrated per camera; the sources give no accuracy or false-alarm figures" ], "echoes": [ { "date": "2024-10-10", "setting": "Trial of Asilla's “AI Security asilla” behavior-recognition AI on 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations, 10 October 2024 to 9 January 2025, including detection of falls from the platform", "model_version": "AI Security asilla", "outcome": "unknown", "source": "Impress Watch, 7 October 2024, https://www.watch.impress.co.jp/docs/news/1629496.html" } ] }, "paired_incident": null, "headline": "Odakyu starts Panasonic fall-detection AI on station cameras", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2024-10-10", "note": "Odakyu later extended AI analysis of existing station cameras, including detection of falls from the platform, to two more stations (Kakio and Tamagawa-Gakuen-mae) in a trial from 10 October 2024 to 9 January 2025, but with a different vendor's system (Asilla), and no result for either system has been reported.", "quote": "小田急電鉄と小田急ビルサービス、アジラは、小田急線柿生駅、玉川学園前駅で、コンコースやホームなどの既設駅構内カメラの映像に、行動認識AIを活用した解析を行なうことに関する実証実験を行なう。ホームからの転落や車いす利用者、不審者・不審物を適正に検知可能かを検証する。", "url": "https://www.watch.impress.co.jp/docs/news/1629496.html" }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.watch.impress.co.jp/docs/news/1629496.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%83%91%E3%83%8A%E3%82%BD%E3%83%8B%E3%83%83%E3%82%AF_%E3%82%B3%E3%83%8D%E3%82%AF%E3%83%88; https://en.wikipedia.org/wiki/Odakyu_Electric_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0307", "catalog_version": "1.0.0", "source_fingerprint": "c44bc917ed3fdf686824c871338c7e216102b6fb829b483716a82177e1352767", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0307-source-0001", "AIBD-0307-source-0002", "AIBD-0307-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Panasonic System Solutions Japan, with Odakyu Electric Railway", "deployer": "Odakyu Electric Railway" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "No event involving the system is documented. The account comes from Odakyu's own launch release and Impress Watch's report of it. They describe what the deep-learning analysis is meant to detect and how staff are alerted. The 2024 Asilla trial at two other stations is a separate system whose results were not reported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No fall, alert or prevented accident is reported by any source." }, { "group": "organizational", "reason": "The operator describes the intended staff workflow; no count of alerts, false alarms or staff time saved is published." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No fall, alert or prevented accident is reported by any source." }, { "group": "organizational", "reason": "The operator describes the intended staff workflow; no count of alerts, false alarms or staff time saved is published." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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"2024-10-10", "note": "Odakyu later extended AI analysis of existing station cameras, including detection of falls from the platform, to two more stations (Kakio and Tamagawa-Gakuen-mae) in a trial from 10 October 2024 to 9 January 2025, but with a different vendor's system (Asilla), and no result for either system has been reported.", "quote": "小田急電鉄と小田急ビルサービス、アジラは、小田急線柿生駅、玉川学園前駅で、コンコースやホームなどの既設駅構内カメラの映像に、行動認識AIを活用した解析を行なうことに関する実証実験を行なう。ホームからの転落や車いす利用者、不審者・不審物を適正に検知可能かを検証する。", "url": "https://www.watch.impress.co.jp/docs/news/1629496.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0307" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Odakyu Electric Railway announced on 30 March 2020 (press release republished by Nikkei) a 転落検知システム (fall detection system). It would operate from the first train on 1 April 2020 at Kyōdō (経堂) and Soshigaya-Ōkura (祖師ヶ谷大蔵) stations on the Odakyu Line. It uses video from existing station cameras. Built with Panasonic System Solutions Japan, the system applies Panasonic's image-analysis and deep-learning technology to analyze the camera feeds in real time. It alerts a dedicated terminal in the station office, showing the camera image, when it detects a person fallen from the platform onto the tracks. It does the same for a person who has stayed at the platform edge for a set time and risks contact with a train. Staff can then take safety measures such as an emergency stop. Pre-learning to set each camera's detection area and to distinguish people from trains had run at both stations since December 2019. Impress Watch reported the launch on 31 March 2020. Neither source reports any detection, prevented accident or performance figure, and no later outcome report was found. Impress Watch (7 October 2024) reported a separate trial of Asilla's behavior-recognition “AI Security asilla” on all 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations. It ran from 10 October 2024 to 9 January 2025. It tested detection of falls from the platform, wheelchair and white-cane users, people lingering on the platform, disputes between passengers and suspicious objects. Results were not reported. Romanizations of station names are ours; the sources give them in Japanese.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No fall, alert or prevented accident is reported by any source." }, { "group": "organizational", "reason": "The operator describes the intended staff workflow; no count of alerts, false alarms or staff time saved is published." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect people falling from the platform onto the tracks or lingering at the platform edge and alert station staff. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Kyōdō and Soshigaya-Ōkura stations, Odakyu Line, Japan", "developer_country": "Japan", "deployer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect people falling from the platform onto the tracks or lingering at the platform edge and alert station staff. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-04-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.watch.impress.co.jp/docs/news/1629496.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%83%91%E3%83%8A%E3%82%BD%E3%83%8B%E3%83%83%E3%82%AF_%E3%82%B3%E3%83%8D%E3%82%AF%E3%83%88; https://en.wikipedia.org/wiki/Odakyu_Electric_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Existing station cameras covering the platform edge and track at two stations", "Panasonic deep-learning image analysis trained from December 2019 to set detection areas and tell people from trains", "A dedicated terminal in the station office that shows the alert and video for staff to act on" ], "must_hold": [ "Station staff present to confirm the alert and order an emergency stop", "Detection areas calibrated per camera; the sources give no accuracy or false-alarm figures" ], "echoes": [ { "date": "2024-10-10", "setting": "Trial of Asilla's “AI Security asilla” behavior-recognition AI on 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations, 10 October 2024 to 9 January 2025, including detection of falls from the platform", "model_version": "AI Security asilla", "outcome": "unknown", "source": "Impress Watch, 7 October 2024, https://www.watch.impress.co.jp/docs/news/1629496.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Existing station cameras covering the platform edge and track at two stations", "Panasonic deep-learning image analysis trained from December 2019 to set detection areas and tell people from trains", "A dedicated terminal in the station office that shows the alert and video for staff to act on" ], "must_hold": [ "Station staff present to confirm the alert and order an emergency stop", "Detection areas calibrated per camera; the sources give no accuracy or false-alarm figures" ], "echoes": [ { "date": "2024-10-10", "setting": "Trial of Asilla's “AI Security asilla” behavior-recognition AI on 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations, 10 October 2024 to 9 January 2025, including detection of falls from the platform", "model_version": "AI Security asilla", "outcome": "unknown", "source": "Impress Watch, 7 October 2024, https://www.watch.impress.co.jp/docs/news/1629496.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.watch.impress.co.jp/docs/news/1629496.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%83%91%E3%83%8A%E3%82%BD%E3%83%8B%E3%83%83%E3%82%AF_%E3%82%B3%E3%83%8D%E3%82%AF%E3%83%88; https://en.wikipedia.org/wiki/Odakyu_Electric_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Railway safety / platform fall detection", "segment": "Station platform monitoring" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Impress Watch (2020). 既設の駅構内カメラで転落者自動検知。小田急. 31 March 2020.", "title": "既設の駅構内カメラで転落者自動検知。小田急", "url": "https://www.watch.impress.co.jp/docs/news/1243957.html", "date": "2020-03-31", "written_by": "independent", "quote": "ホームから線路への転落者を自動検知、駅係員に通知する「転落検知システム」の運用を4月1日より開始。小田急線経堂駅と祖師ヶ谷大蔵駅に設置される。" }, { "kind": "press release", "citation": "Odakyu Electric Railway (2020). 小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始. Press release of 30 March 2020, republished by Nikkei.", "title": "小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始", "url": "https://www.nikkei.com/article/DGXLRSP531980_Q0A330C2000000/", "date": "2020-03-30", "written_by": "deployer", "quote": "パナソニックが有する画像解析とディープラーニング（深層学習）技術を鉄道環境に応用し、既設の駅構内カメラの映像をリアルタイムに解析を行い" }, { "kind": "news report", "citation": "Impress Watch (2024). 小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知. 7 October 2024 (the Asilla trial echo).", "title": "小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知", "url": "https://www.watch.impress.co.jp/docs/news/1629496.html", "date": "2024-10-07", "written_by": "independent", "quote": "ホームからの転落や車いす利用者、不審者・不審物を適正に検知可能かを検証する。" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0307-source-0001", "AIBD-0307-source-0002", "AIBD-0307-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Impress Watch (2020). 既設の駅構内カメラで転落者自動検知。小田急. 31 March 2020.", "title": "既設の駅構内カメラで転落者自動検知。小田急", "url": "https://www.watch.impress.co.jp/docs/news/1243957.html", "date": "2020-03-31", "written_by": "independent", "quote": "ホームから線路への転落者を自動検知、駅係員に通知する「転落検知システム」の運用を4月1日より開始。小田急線経堂駅と祖師ヶ谷大蔵駅に設置される。" }, { "kind": "press release", "citation": "Odakyu Electric Railway (2020). 小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始. Press release of 30 March 2020, republished by Nikkei.", "title": "小田急電鉄、既設の駅構内カメラを活用した「転落検知システム」を運用開始", "url": "https://www.nikkei.com/article/DGXLRSP531980_Q0A330C2000000/", "date": "2020-03-30", "written_by": "deployer", "quote": "パナソニックが有する画像解析とディープラーニング（深層学習）技術を鉄道環境に応用し、既設の駅構内カメラの映像をリアルタイムに解析を行い" }, { "kind": "news report", "citation": "Impress Watch (2024). 小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知. 7 October 2024 (the Asilla trial echo).", "title": "小田急、駅構内カメラ映像に行動認識AI　転落や車いす、不審者検知", "url": "https://www.watch.impress.co.jp/docs/news/1629496.html", "date": "2024-10-07", "written_by": "independent", "quote": "ホームからの転落や車いす利用者、不審者・不審物を適正に検知可能かを検証する。" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "From 1 April 2020 Odakyu's system analyzes existing platform camera video to flag people who fall onto the tracks or linger at the platform edge and alerts station staff; no outcomes are reported.", "account": "Odakyu Electric Railway announced on 30 March 2020 (press release republished by Nikkei) a 転落検知システム (fall detection system). It would operate from the first train on 1 April 2020 at Kyōdō (経堂) and Soshigaya-Ōkura (祖師ヶ谷大蔵) stations on the Odakyu Line. It uses video from existing station cameras. Built with Panasonic System Solutions Japan, the system applies Panasonic's image-analysis and deep-learning technology to analyze the camera feeds in real time. It alerts a dedicated terminal in the station office, showing the camera image, when it detects a person fallen from the platform onto the tracks. It does the same for a person who has stayed at the platform edge for a set time and risks contact with a train. Staff can then take safety measures such as an emergency stop. Pre-learning to set each camera's detection area and to distinguish people from trains had run at both stations since December 2019. Impress Watch reported the launch on 31 March 2020. Neither source reports any detection, prevented accident or performance figure, and no later outcome report was found. Impress Watch (7 October 2024) reported a separate trial of Asilla's behavior-recognition “AI Security asilla” on all 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations. It ran from 10 October 2024 to 9 January 2025. It tested detection of falls from the platform, wheelchair and white-cane users, people lingering on the platform, disputes between passengers and suspicious objects. Results were not reported. Romanizations of station names are ours; the sources give them in Japanese." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "転落検知システム (fall detection system): Panasonic image-analysis and deep-learning on existing station cameras" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Panasonic System Solutions Japan, with Odakyu Electric Railway" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Odakyu Electric Railway starts a Panasonic deep-learning “fall detection system” on existing station cameras at Kyōdō and Soshigaya-Ōkura stations", "headline": "Odakyu starts Panasonic fall-detection AI on station cameras" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c44bc917ed3fdf686824c871338c7e216102b6fb829b483716a82177e1352767" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Odakyu Electric Railway announced on 30 March 2020 (press release republished by Nikkei) a 転落検知システム (fall detection system). It would operate from the first train on 1 April 2020 at Kyōdō (経堂) and Soshigaya-Ōkura (祖師ヶ谷大蔵) stations on the Odakyu Line. It uses video from existing station cameras. Built with Panasonic System Solutions Japan, the system applies Panasonic's image-analysis and deep-learning technology to analyze the camera feeds in real time. It alerts a dedicated terminal in the station office, showing the camera image, when it detects a person fallen from the platform onto the tracks. It does the same for a person who has stayed at the platform edge for a set time and risks contact with a train. Staff can then take safety measures such as an emergency stop. Pre-learning to set each camera's detection area and to distinguish people from trains had run at both stations since December 2019. Impress Watch reported the launch on 31 March 2020. Neither source reports any detection, prevented accident or performance figure, and no later outcome report was found. Impress Watch (7 October 2024) reported a separate trial of Asilla's behavior-recognition “AI Security asilla” on all 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations. It ran from 10 October 2024 to 9 January 2025. It tested detection of falls from the platform, wheelchair and white-cane users, people lingering on the platform, disputes between passengers and suspicious objects. Results were not reported. Romanizations of station names are ours; the sources give them in Japanese.", "replication": { "produced_by": [ "Existing station cameras covering the platform edge and track at two stations", "Panasonic deep-learning image analysis trained from December 2019 to set detection areas and tell people from trains", "A dedicated terminal in the station office that shows the alert and video for staff to act on" ], "must_hold": [ "Station staff present to confirm the alert and order an emergency stop", "Detection areas calibrated per camera; the sources give no accuracy or false-alarm figures" ], "echoes": [ { "date": "2024-10-10", "setting": "Trial of Asilla's “AI Security asilla” behavior-recognition AI on 20 existing cameras at Kakio and Tamagawa-Gakuen-mae stations, 10 October 2024 to 9 January 2025, including detection of falls from the platform", "model_version": "AI Security asilla", "outcome": "unknown", "source": "Impress Watch, 7 October 2024, https://www.watch.impress.co.jp/docs/news/1629496.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0250", "title": "Fujitsu Zinrai collision-risk prediction trialled with the Japan Coast Guard at the Tokyo Wan Vessel Traffic Service Center: warnings about two minutes earlier, nearly double the warnings", "summary": "The Maritime Executive (15 Apr 2020): in a Dec 2019 to Mar 2020 trial, six experienced controllers re-ran past near-miss cases with and without AI risk predictions from AIS and radar data; warnings...", "date_observed": "2020-04-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Maritime Executive reported on 15 Apr 2020 that Fujitsu Limited and the Japan Coast Guard had field-tested an artificial-intelligence system to predict vessel collisions. The test ran from December 2019 to March 2020 at the Tokyo Wan Vessel Traffic Service Center. It provides navigation support under an outsourcing contract with the Coast Guard. It uses Fujitsu Human Centric AI Zinrai from Fujitsu Laboratories. The technology detects near misses between vessels and predicts areas where collision risk concentrates in Tokyo Bay. In the center's training environment, six experienced maritime traffic controllers and instructors simulated control tasks based on past near-miss accidents. They compared conventional operation with operation supported by risk information computed from past AIS data and Coast Guard risk-recommendation records. It shortened the time before a controller sent a risk warning to a vessel by an average of about two minutes. The number of warnings issued to risk-prone vessels nearly doubled, and it was found particularly effective for newcomers. The article cites the Japan Transport Safety Board's count of 2,863 marine collisions in Japan from 2009 to 2019. The results come from a simulation, not live traffic.", "category": "general benefit", "unexpected": false, "purpose": "The technology was built to detect near misses and predict collision-risk areas to help vessel traffic controllers warn ships earlier.", "system": "Fujitsu Human Centric AI Zinrai collision-risk prediction using AIS and radar data", "model_version": "Fujitsu Human Centric AI Zinrai", "developer": "Fujitsu Laboratories / Fujitsu Limited", "deployer": "Japan Coast Guard, Tokyo Wan Vessel Traffic Service Center (trial)", "location": null, "domain": "Maritime safety", "segment": "Vessel traffic services / collision-risk prediction", "benefit_type": "Reduced Task Time", "taxonomy_note": "The trial was simulated, and the earlier warning serves collision avoidance, which no measured outcome documents.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Simulation results only. No live operational outcome is documented." }, { "group": "societal", "depth": null, "reason": "No collision avoided or reduced is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The AI produced risk information that controllers used to decide warnings. The two-minute gain and doubled warning count were measured against conventional operation in replayed near-miss scenarios with six controllers." }, "evidence": [ { "kind": "news report", "citation": "The Maritime Executive (15 Apr 2020). AI System Tested by Tokyo Bay Vessel Traffic Controllers.", "title": "AI System Tested by Tokyo Bay Vessel Traffic Controllers", "url": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers", "date": "2020-04-15", "written_by": "independent", "quote": "It was also confirmed that the number of warnings issued for risk-prone vessels nearly doubled with the technology, indicating proactive preventive measures" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2020-04-16-d2f1: Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial.", "title": "Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial", "url": "https://oecd.ai/en/incidents/2020-04-16-d2f1", "date": "2020-04-16", "written_by": "independent", "quote": "Fujitsu, in partnership with the Japan Coast Guard, tested its Zinrai AI system in Tokyo Bay from December 2019 to March 2020." }, { "kind": "press release", "citation": "Fujitsu Limited (28 Sep 2021). Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes.", "title": "Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes", "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html", "date": "2021-09-28", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A VTS center with radar and AIS feeds and archived risk recommendations", "Replayed near-miss scenarios in a training environment", "Experienced controllers comparing conventional and AI-supported operation" ], "must_hold": [ "Risk predictions are computed in real time on live traffic", "Controllers trust and act on the predictions" ], "echoes": [ { "date": "2026-04-15", "setting": "Shipboard AI watchkeeping (Orca AI) on 139 container ships: 52% fewer high-severity close encounters in the first year, per a NorthStandard study", "model_version": null, "outcome": "unknown", "source": "https://www.rivieramm.com/news-content-hub/news-content-hub/northstandard-study-demonstrates-benefits-of-ai-navigation-support-88473" } ] }, "paired_incident": null, "headline": "Fujitsu Zinrai trial speeds vessel warnings by about two minutes", "metric": "the number of warnings issued to risk-prone vessels nearly doubled", "comparator": { "against": "conventional control operation without AI risk information, in a simulation of past near-miss cases", "before": "conventional operation (no absolute figure given)", "after": "risk warning sent an average of approximately two minutes earlier; number of warnings issued for risk-prone vessels nearly doubled", "basis": "measured", "quote": "It was found that the new technology could shorten the time before a risk warning is sent to a vessel by the operation controller by an average of approximately two minutes, enabling the early detection of vessels at risk of collision. It was also confirmed that the number of warnings issued for risk-prone vessels nearly doubled with the technology, indicating proactive preventive measures and the potential to enhance safety in Tokyo Bay.", "url": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers" }, "later": { "status": "persisted", "date": "2021-09-28", "note": "Fujitsu ran a second field trial at the same center from 17 November 2020 to 2 September 2021 with an added course-following algorithm, reported about 90% fewer unnecessary alerts than the earlier technology, and planned a commercial navigation-support service from March 2022.", "quote": "Results of the trial demonstrated that this technology can reduce unnecessary alerts by about 90% on all sea routes, especially on curved sections where alerts frequently occurred.", "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html" }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers; https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html; https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Fujitsu; https://en.wikipedia.org/wiki/Japan_Coast_Guard", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0250", "catalog_version": "1.0.0", "source_fingerprint": "033c4a9735cf57678c91e223cbfac009a844380672754fa4cd48f9b713bbcd65", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0250-source-0001", "AIBD-0250-source-0002", "AIBD-0250-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fujitsu Laboratories / Fujitsu Limited", "deployer": "Japan Coast Guard, Tokyo Wan Vessel Traffic Service Center (trial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI produced risk information that controllers used to decide warnings. The two-minute gain and doubled warning count were measured against conventional operation in replayed near-miss scenarios with six controllers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The AI produced risk information that controllers used to decide warnings. The two-minute gain and doubled warning count were measured against conventional operation in replayed near-miss scenarios with six controllers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, a registry entry and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Simulation results only. No live operational outcome is documented." }, { "group": "societal", "reason": "No collision avoided or reduced is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Simulation results only. No live operational outcome is documented." }, { "group": "societal", "reason": "No collision avoided or reduced is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": 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unnecessary alerts than the earlier technology, and planned a commercial navigation-support service from March 2022.", "quote": "Results of the trial demonstrated that this technology can reduce unnecessary alerts by about 90% on all sea routes, especially on curved sections where alerts frequently occurred.", "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0250" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not 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AI System Tested by Tokyo Bay Vessel Traffic Controllers.", "title": "AI System Tested by Tokyo Bay Vessel Traffic Controllers", "url": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers", "date": "2020-04-15", "written_by": "independent", "quote": "It was also confirmed that the number of warnings issued for risk-prone vessels nearly doubled with the technology, indicating proactive preventive measures" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2020-04-16-d2f1: Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial.", "title": "Fujitsu AI System Reduces Ship Collision Risks in Tokyo Bay Trial", "url": "https://oecd.ai/en/incidents/2020-04-16-d2f1", "date": "2020-04-16", "written_by": "independent", "quote": "Fujitsu, in partnership with the Japan Coast Guard, tested its Zinrai AI system in Tokyo Bay from December 2019 to March 2020." }, { "kind": "press release", "citation": "Fujitsu Limited (28 Sep 2021). Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes.", "title": "Fujitsu Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision Risks on Complex Maritime Routes", "url": "https://info.archives.global.fujitsu/global/about/resources/news/press-releases/2021/0928-01.html", "date": "2021-09-28", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0250-source-0001", "AIBD-0250-source-0002", "AIBD-0250-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Maritime Executive (15 Apr 2020). 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The test ran from December 2019 to March 2020 at the Tokyo Wan Vessel Traffic Service Center. It provides navigation support under an outsourcing contract with the Coast Guard. It uses Fujitsu Human Centric AI Zinrai from Fujitsu Laboratories. The technology detects near misses between vessels and predicts areas where collision risk concentrates in Tokyo Bay. In the center's training environment, six experienced maritime traffic controllers and instructors simulated control tasks based on past near-miss accidents. They compared conventional operation with operation supported by risk information computed from past AIS data and Coast Guard risk-recommendation records. It shortened the time before a controller sent a risk warning to a vessel by an average of about two minutes. The number of warnings issued to risk-prone vessels nearly doubled, and it was found particularly effective for newcomers. The article cites the Japan Transport Safety Board's count of 2,863 marine collisions in Japan from 2009 to 2019. The results come from a simulation, not live traffic." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The system estimated collision risk from vessel-position and radar data." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used Fujitsu Human Centric AI Zinrai." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. 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The test ran from December 2019 to March 2020 at the Tokyo Wan Vessel Traffic Service Center. It provides navigation support under an outsourcing contract with the Coast Guard. It uses Fujitsu Human Centric AI Zinrai from Fujitsu Laboratories. The technology detects near misses between vessels and predicts areas where collision risk concentrates in Tokyo Bay. In the center's training environment, six experienced maritime traffic controllers and instructors simulated control tasks based on past near-miss accidents. They compared conventional operation with operation supported by risk information computed from past AIS data and Coast Guard risk-recommendation records. It shortened the time before a controller sent a risk warning to a vessel by an average of about two minutes. The number of warnings issued to risk-prone vessels nearly doubled, and it was found particularly effective for newcomers. The article cites the Japan Transport Safety Board's count of 2,863 marine collisions in Japan from 2009 to 2019. The results come from a simulation, not live traffic.", "replication": { "produced_by": [ "A VTS center with radar and AIS feeds and archived risk recommendations", "Replayed near-miss scenarios in a training environment", "Experienced controllers comparing conventional and AI-supported operation" ], "must_hold": [ "Risk predictions are computed in real time on live traffic", "Controllers trust and act on the predictions" ], "echoes": [ { "date": "2026-04-15", "setting": "Shipboard AI watchkeeping (Orca AI) on 139 container ships: 52% fewer high-severity close encounters in the first year, per a NorthStandard study", "outcome": "unknown", "source": "https://www.rivieramm.com/news-content-hub/news-content-hub/northstandard-study-demonstrates-benefits-of-ai-navigation-support-88473" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0200", "title": "AI teams out-earn human growers in Wageningen's Autonomous Greenhouse Challenges (cucumber 2018, cherry tomato 2020)", "summary": "2018 cucumber challenge: winning algorithm raised sellable yield 6% and net profit 17% over reference growers; 2020 cherry-tomato challenge: all five AI compartments beat the growers' net profit.", "date_observed": "2020-05-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Wageningen University & Research runs the Autonomous Greenhouse Challenge in six identical 96 m² high-tech compartments at Bleiswijk, with the organizing team publishing the results. In the first challenge in 2018, five international teams grew cucumber remotely for four months. They set climate, irrigation and crop setpoints with their own AI algorithms. One team outperformed the manually operated reference. The 2020 paper reports that the winning algorithm increased commercially sellable production by 6% and net profit by 17% over the reference growers. In the second challenge, cherry tomato cv. Axiany was transplanted on 16 December 2019. Five teams (Automatoes, AiCU, DIGILOG, IUA.CAAS, The Automators) took remote control on 20 December 2019. Harvest ran from 13 February to 29 May 2020. Net profit ranged from 3.10 to 6.86 €/m² and all AI-operated compartments exceeded the Dutch growers' reference compartment. Compartment 306 (Automatoes) had the highest income (37.2 €/m²) and highest net profit, while the reference had high energy and labor costs. The challenge was funded by Tencent. A third edition grew lettuce in 2023. 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In the first challenge in 2018, five international teams grew cucumber remotely for four months. They set climate, irrigation and crop setpoints with their own AI algorithms. One team outperformed the manually operated reference. The 2020 paper reports that the winning algorithm increased commercially sellable production by 6% and net profit by 17% over the reference growers. In the second challenge, cherry tomato cv. Axiany was transplanted on 16 December 2019. Five teams (Automatoes, AiCU, DIGILOG, IUA.CAAS, The Automators) took remote control on 20 December 2019. Harvest ran from 13 February to 29 May 2020. Net profit ranged from 3.10 to 6.86 €/m² and all AI-operated compartments exceeded the Dutch growers' reference compartment. Compartment 306 (Automatoes) had the highest income (37.2 €/m²) and highest net profit, while the reference had high energy and labor costs. The challenge was funded by Tencent. A third edition grew lettuce in 2023. Net profit is computed from the organizers' price and cost model in an experimental facility, not a commercial farm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Team AI algorithms in the Autonomous Greenhouse Challenge (2020: Automatoes, AiCU, DIGILOG, IUA.CAAS, The Automators)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "International competing teams; challenge organized by Wageningen University & Research and funded by Tencent" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI teams out-earn human growers in Wageningen's Autonomous Greenhouse Challenges (cucumber 2018, cherry tomato 2020)", "headline": "AI teams out-earn growers in Wageningen's greenhouse challenges" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b86f09c18fa311bbedd939f9162a59ce2fcd7f2d55951fd48ee0e390f675cc4a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Wageningen University & Research runs the Autonomous Greenhouse Challenge in six identical 96 m² high-tech compartments at Bleiswijk, with the organizing team publishing the results. 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A wild boar walked into his path (Daily Star, 9 June 2020). He told Het Laatste Nieuws he pulled the steering wheel himself and the car then took over and straightened its course. He felt the wheel working against him (Daily Star; DH.be, 11 June 2020). The Daily Star says the boar was barely touched, if at all. Electrek reads the footage as a possible strike on the car's side. No injury is reported. The video, shared on Twitter by Pranay Pathole, drew Musk's reply that Autopilot's “prime directive” is not to crash (Electrek, 8 June 2020). He added that its cameras, sonar and radar make it “superhuman”. Le Figaro (12 June 2020) credited the swerve to Autopilot rather than the driver's reflexes, contrary to his own account. No Tesla data is reported.", "category": "protective response", "unexpected": false, "purpose": "Autopilot is a driver-assistance system that steers, accelerates and brakes within a lane and includes collision-avoidance features. Keeping the car under control after an evasive swerve is within that intended use as the driver and Musk describe it.", "system": "Tesla Autopilot (with the active safety features it powers)", "model_version": "Tesla Model 3 per the Daily Star; Autopilot hardware and software version not reported", "developer": "Tesla", "deployer": null, "location": "Houthalen-Helchteren, Belgium", "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": "The driver's account credits the car with steadying his own swerve, and whether the boar was struck is unclear.", "registry_ids": { "oecd_aim": "2020-06-10-258f" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "One driver kept control of his car after swerving around a wild boar at 4 am and arrived unhurt. By his account the car straightened the swerve he had begun. Whether he would have lost control or struck the animal without that correction is unknown. No avoided injury or damage is measured, so a removed risk is not established." } ], "ai_role": { "status": "assessed", "statement": "By Van Hoesen's account to Het Laatste Nieuws, relayed by the Daily Star and DH.be, he turned the wheel to avoid the boar. The car then took over, straightening the course and working against his steering. On that account the system's contribution was stabilization after a human evasive input, not the initial avoidance. Le Figaro credits Autopilot with the swerve itself, and Electrek notes Autopilot had been thought incapable of such drastic maneuvers. Musk's reply endorses the Autopilot reading but adds no data. No Tesla telemetry, police report or engineering assessment is cited." }, "evidence": [ { "kind": "news report", "citation": "Jackson S (2020). Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig. Daily Star, 9 June 2020.", "title": "Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig", "url": "https://www.dailystar.co.uk/news/world-news/elon-musk-says-tesla-car-22163770", "date": "2020-06-09", "written_by": "independent", "quote": "Kenneth was driving a Tesla Model 3 in the Kazernelaan in Houthalen-Helchteren on Saturday, May 30." }, { "kind": "news report", "citation": "Lambert F (2020). Watch Tesla Autopilot avoid running over a pig in the middle of the road. Electrek, 8 June 2020.", "title": "Watch Tesla Autopilot avoid running over a pig in the middle of the road", "url": "https://electrek.co/2020/06/08/tesla-autopilot-avoid-pig-video/", "date": "2020-06-08", "written_by": "independent", "quote": "Autopilot prime directive is: Don’t crash. What seems fast to humans is slow to a computer." }, { "kind": "news report", "citation": "La DH (2020). Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: 'Le système est surhumain'. DH.be, 11 June 2020.", "title": "Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: \"Le système est surhumain\"", "url": "https://www.dhnet.be/actu/belgique/un-boulanger-belge-fait-reagir-elon-musk-en-personne-suite-a-l-exploit-de-sa-tesla-le-systeme-est-surhumain-5ee2512d9978e21bd06f5947", "date": "2020-06-11", "written_by": "independent", "quote": "J'ai tourné le volant, mais la voiture a immédiatement repris le contrôle pour me remettre sur la route" }, { "kind": "news report", "citation": "L'Avenir (2020). VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne. Lavenir.net, 10 June 2020.", "title": "VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne", "url": "https://www.lavenir.net/cnt/dmf20200610_01481837/video-un-belge-evite-un-sanglier-grace-a-sa-tesla-et-fait-reagir-elon-musk-en-personne", "date": "2020-06-10", "written_by": "independent", "quote": "Alors que ce boulanger flamand se rendait au travail vers 4h du matin, les caméras intégrées dans sa voiture ont repéré un sanglier sur la route." }, { "kind": "news report", "citation": "Le Figaro (2020). Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot. Le Figaro, 12 June 2020.", "title": "Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot", "url": "https://www.lefigaro.fr/flash-actu/le-conducteur-d-une-tesla-evite-de-justesse-un-sanglier-grace-a-l-autopilot-20200612", "date": "2020-06-12", "written_by": "independent", "quote": "a pu faire un important écart non pas grâce aux réflexes du conducteur, mais grâce au système de pilotage automatique de la Tesla" }, { "kind": "registry label", "citation": "OECD.AI (2020). Tesla Autopilot Prevents Collision with Wild Boar in Belgium. OECD AI Incidents and Hazards Monitor, entry 2020-06-10-258f.", "title": "Tesla Autopilot Prevents Collision with Wild Boar in Belgium", "url": "https://oecd.ai/en/incidents/2020-06-10-258f", "date": null, "written_by": "independent", "quote": "A Belgian baker narrowly avoided a collision with a wild boar when his Tesla's Autopilot system intervened, taking control to steer the car away from the animal." } ], "replication": { "produced_by": [ "A Tesla with Autopilot engaged, by the driver's account, on an unlit road at about 4 am, with its cameras recording from four sides", "A sudden steering input by the driver to avoid an animal, after which the car's control systems straighten the course" ], "must_hold": [ "The road is otherwise empty, so the swerve and the correction stay within the carriageway", "The driver does not fight the correction. Van Hoesen said he felt the wheel working against him", "The animal is small enough, or far enough away, to be missed or only grazed" ], "echoes": [] }, "paired_incident": null, "headline": "Tesla Model 3 steadies a Belgian baker's swerve around a wild boar", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2020-06-10-258f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0364", "catalog_version": "1.0.0", "source_fingerprint": "2bfa51f58b9122fd96cecb438d131bb83ee05d2aa9884d384e4470f0042b1c49", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0364-source-0001", "AIBD-0364-source-0002", "AIBD-0364-source-0003", "AIBD-0364-source-0004", "AIBD-0364-source-0005", "AIBD-0364-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "By Van Hoesen's account to Het Laatste Nieuws, relayed by the Daily Star and DH.be, he turned the wheel to avoid the boar. The car then took over, straightening the course and working against his steering. On that account the system's contribution was stabilization after a human evasive input, not the initial avoidance. Le Figaro credits Autopilot with the swerve itself, and Electrek notes Autopilot had been thought incapable of such drastic maneuvers. Musk's reply endorses the Autopilot reading but adds no data. No Tesla telemetry, police report or engineering assessment is cited." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "By Van Hoesen's account to Het Laatste Nieuws, relayed by the Daily Star and DH.be, he turned the wheel to avoid the boar. The car then took over, straightening the course and working against his steering. On that account the system's contribution was stabilization after a human evasive input, not the initial avoidance. Le Figaro credits Autopilot with the swerve itself, and Electrek notes Autopilot had been thought incapable of such drastic maneuvers. 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"outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Kenneth Van Hoesen, a Flemish baker, was driving his Tesla Model 3 on the Kazernelaan in Houthalen-Helchteren, Belgium, at 4 am on 30 May 2020. A wild boar walked into his path (Daily Star, 9 June 2020). He told Het Laatste Nieuws he pulled the steering wheel himself and the car then took over and straightened its course. He felt the wheel working against him (Daily Star; DH.be, 11 June 2020). The Daily Star says the boar was barely touched, if at all. Electrek reads the footage as a possible strike on the car's side. No injury is reported. The video, shared on Twitter by Pranay Pathole, drew Musk's reply that Autopilot's “prime directive” is not to crash (Electrek, 8 June 2020). He added that its cameras, sonar and radar make it “superhuman”. Le Figaro (12 June 2020) credited the swerve to Autopilot rather than the driver's reflexes, contrary to his own account. No Tesla data is reported.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "One driver kept control of his car after swerving around a wild boar at 4 am and arrived unhurt. By his account the car straightened the swerve he had begun. Whether he would have lost control or struck the animal without that correction is unknown. No avoided injury or damage is measured, so a removed risk is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Autopilot is a driver-assistance system that steers, accelerates and brakes within a lane and includes collision-avoidance features. 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Van Hoesen said he felt the wheel working against him", "The animal is small enough, or far enough away, to be missed or only grazed" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2020-06-10-258f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road vehicle crash avoidance", "segment": "Automotive" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Jackson S (2020). Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig. Daily Star, 9 June 2020.", "title": "Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig", "url": "https://www.dailystar.co.uk/news/world-news/elon-musk-says-tesla-car-22163770", "date": "2020-06-09", "written_by": "independent", "quote": "Kenneth was driving a Tesla Model 3 in the Kazernelaan in Houthalen-Helchteren on Saturday, May 30." }, { "kind": "news report", "citation": "Lambert F (2020). Watch Tesla Autopilot avoid running over a pig in the middle of the road. Electrek, 8 June 2020.", "title": "Watch Tesla Autopilot avoid running over a pig in the middle of the road", "url": "https://electrek.co/2020/06/08/tesla-autopilot-avoid-pig-video/", "date": "2020-06-08", "written_by": "independent", "quote": "Autopilot prime directive is: Don’t crash. What seems fast to humans is slow to a computer." }, { "kind": "news report", "citation": "La DH (2020). Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: 'Le système est surhumain'. DH.be, 11 June 2020.", "title": "Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: \"Le système est surhumain\"", "url": "https://www.dhnet.be/actu/belgique/un-boulanger-belge-fait-reagir-elon-musk-en-personne-suite-a-l-exploit-de-sa-tesla-le-systeme-est-surhumain-5ee2512d9978e21bd06f5947", "date": "2020-06-11", "written_by": "independent", "quote": "J'ai tourné le volant, mais la voiture a immédiatement repris le contrôle pour me remettre sur la route" }, { "kind": "news report", "citation": "L'Avenir (2020). VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne. Lavenir.net, 10 June 2020.", "title": "VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne", "url": "https://www.lavenir.net/cnt/dmf20200610_01481837/video-un-belge-evite-un-sanglier-grace-a-sa-tesla-et-fait-reagir-elon-musk-en-personne", "date": "2020-06-10", "written_by": "independent", "quote": "Alors que ce boulanger flamand se rendait au travail vers 4h du matin, les caméras intégrées dans sa voiture ont repéré un sanglier sur la route." }, { "kind": "news report", "citation": "Le Figaro (2020). Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot. Le Figaro, 12 June 2020.", "title": "Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot", "url": "https://www.lefigaro.fr/flash-actu/le-conducteur-d-une-tesla-evite-de-justesse-un-sanglier-grace-a-l-autopilot-20200612", "date": "2020-06-12", "written_by": "independent", "quote": "a pu faire un important écart non pas grâce aux réflexes du conducteur, mais grâce au système de pilotage automatique de la Tesla" }, { "kind": "registry label", "citation": "OECD.AI (2020). Tesla Autopilot Prevents Collision with Wild Boar in Belgium. OECD AI Incidents and Hazards Monitor, entry 2020-06-10-258f.", "title": "Tesla Autopilot Prevents Collision with Wild Boar in Belgium", "url": "https://oecd.ai/en/incidents/2020-06-10-258f", "written_by": "independent", "quote": "A Belgian baker narrowly avoided a collision with a wild boar when his Tesla's Autopilot system intervened, taking control to steer the car away from the animal." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0364-source-0001", "AIBD-0364-source-0002", "AIBD-0364-source-0003", "AIBD-0364-source-0004", "AIBD-0364-source-0005", "AIBD-0364-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Jackson S (2020). Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig. Daily Star, 9 June 2020.", "title": "Elon Musk says Tesla car is 'superhuman' after it automatically swerves pig", "url": "https://www.dailystar.co.uk/news/world-news/elon-musk-says-tesla-car-22163770", "date": "2020-06-09", "written_by": "independent", "quote": "Kenneth was driving a Tesla Model 3 in the Kazernelaan in Houthalen-Helchteren on Saturday, May 30." }, { "kind": "news report", "citation": "Lambert F (2020). Watch Tesla Autopilot avoid running over a pig in the middle of the road. Electrek, 8 June 2020.", "title": "Watch Tesla Autopilot avoid running over a pig in the middle of the road", "url": "https://electrek.co/2020/06/08/tesla-autopilot-avoid-pig-video/", "date": "2020-06-08", "written_by": "independent", "quote": "Autopilot prime directive is: Don’t crash. What seems fast to humans is slow to a computer." }, { "kind": "news report", "citation": "La DH (2020). Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: 'Le système est surhumain'. DH.be, 11 June 2020.", "title": "Un boulanger belge fait réagir Elon Musk en personne suite à l'exploit de sa Tesla: \"Le système est surhumain\"", "url": "https://www.dhnet.be/actu/belgique/un-boulanger-belge-fait-reagir-elon-musk-en-personne-suite-a-l-exploit-de-sa-tesla-le-systeme-est-surhumain-5ee2512d9978e21bd06f5947", "date": "2020-06-11", "written_by": "independent", "quote": "J'ai tourné le volant, mais la voiture a immédiatement repris le contrôle pour me remettre sur la route" }, { "kind": "news report", "citation": "L'Avenir (2020). VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne. Lavenir.net, 10 June 2020.", "title": "VIDÉO | Un Belge évite un sanglier grâce à sa Tesla et fait réagir Elon Musk en personne", "url": "https://www.lavenir.net/cnt/dmf20200610_01481837/video-un-belge-evite-un-sanglier-grace-a-sa-tesla-et-fait-reagir-elon-musk-en-personne", "date": "2020-06-10", "written_by": "independent", "quote": "Alors que ce boulanger flamand se rendait au travail vers 4h du matin, les caméras intégrées dans sa voiture ont repéré un sanglier sur la route." }, { "kind": "news report", "citation": "Le Figaro (2020). Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot. Le Figaro, 12 June 2020.", "title": "Le conducteur d'une Tesla évite de justesse un sanglier grâce à l'Autopilot", "url": "https://www.lefigaro.fr/flash-actu/le-conducteur-d-une-tesla-evite-de-justesse-un-sanglier-grace-a-l-autopilot-20200612", "date": "2020-06-12", "written_by": "independent", "quote": "a pu faire un important écart non pas grâce aux réflexes du conducteur, mais grâce au système de pilotage automatique de la Tesla" }, { "kind": "registry label", "citation": "OECD.AI (2020). Tesla Autopilot Prevents Collision with Wild Boar in Belgium. OECD AI Incidents and Hazards Monitor, entry 2020-06-10-258f.", "title": "Tesla Autopilot Prevents Collision with Wild Boar in Belgium", "url": "https://oecd.ai/en/incidents/2020-06-10-258f", "written_by": "independent", "quote": "A Belgian baker narrowly avoided a collision with a wild boar when his Tesla's Autopilot system intervened, taking control to steer the car away from the animal." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Baker Kenneth Van Hoesen swerved around a wild boar at 4 am on 30 May 2020 in Houthalen-Helchteren; he says his Model 3 then took over and straightened the car; Musk replied on Twitter.", "account": "Kenneth Van Hoesen, a Flemish baker, was driving his Tesla Model 3 on the Kazernelaan in Houthalen-Helchteren, Belgium, at 4 am on 30 May 2020. A wild boar walked into his path (Daily Star, 9 June 2020). He told Het Laatste Nieuws he pulled the steering wheel himself and the car then took over and straightened its course. He felt the wheel working against him (Daily Star; DH.be, 11 June 2020). The Daily Star says the boar was barely touched, if at all. Electrek reads the footage as a possible strike on the car's side. No injury is reported. The video, shared on Twitter by Pranay Pathole, drew Musk's reply that Autopilot's “prime directive” is not to crash (Electrek, 8 June 2020). He added that its cameras, sonar and radar make it “superhuman”. Le Figaro (12 June 2020) credited the swerve to Autopilot rather than the driver's reflexes, contrary to his own account. No Tesla data is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The driver reported that the system stabilized the car after his evasive steering." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The report identified a Tesla Model 3, without an installed Autopilot release." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Tesla Model 3 per the Daily Star; Autopilot hardware and software version not reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Autopilot (with the active safety features it powers)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kenneth Van Hoesen's Tesla Model 3 straightens its course after he swerves around a wild boar at 4 am on the Kazernelaan in Houthalen-Helchteren; Elon Musk calls the system superhuman (30 May 2020)", "headline": "Tesla Model 3 steadies a Belgian baker's swerve around a wild boar" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2bfa51f58b9122fd96cecb438d131bb83ee05d2aa9884d384e4470f0042b1c49" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Kenneth Van Hoesen, a Flemish baker, was driving his Tesla Model 3 on the Kazernelaan in Houthalen-Helchteren, Belgium, at 4 am on 30 May 2020. A wild boar walked into his path (Daily Star, 9 June 2020). He told Het Laatste Nieuws he pulled the steering wheel himself and the car then took over and straightened its course. He felt the wheel working against him (Daily Star; DH.be, 11 June 2020). The Daily Star says the boar was barely touched, if at all. Electrek reads the footage as a possible strike on the car's side. No injury is reported. The video, shared on Twitter by Pranay Pathole, drew Musk's reply that Autopilot's “prime directive” is not to crash (Electrek, 8 June 2020). He added that its cameras, sonar and radar make it “superhuman”. Le Figaro (12 June 2020) credited the swerve to Autopilot rather than the driver's reflexes, contrary to his own account. No Tesla data is reported.", "replication": { "produced_by": [ "A Tesla with Autopilot engaged, by the driver's account, on an unlit road at about 4 am, with its cameras recording from four sides", "A sudden steering input by the driver to avoid an animal, after which the car's control systems straighten the course" ], "must_hold": [ "The road is otherwise empty, so the swerve and the correction stay within the carriageway", "The driver does not fight the correction. Van Hoesen said he felt the wheel working against him", "The animal is small enough, or far enough away, to be missed or only grazed" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0024", "title": "Samsung Galaxy wearable heart-rate and ECG recordings supporting arrhythmia diagnosis and treatment", "summary": "Galaxy Fit recorded a resting pulse of 188 bpm; a routine ECG next day showed WPW and the band's records supported referral for successful ablation (South Korea, 2020).", "date_observed": "2020-06-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 18 June 2020 a 26-year-old woman working 12-hour days in a multinational company's quality control department in South Korea experienced severe palpitations for hours. Her Samsung Galaxy Fit (SM-R370), which measures pulse by photoplethysmography, recorded a peak resting pulse rate of 188 bpm. The next day, 19 June 2020, a routine health-examination 12-lead electrocardiogram (ECG) was taken while she was asymptomatic. It showed a shortened PR interval and delta waves, establishing Wolff-Parkinson-White syndrome. The authors are from the Department of Occupational and Environmental Medicine at Kangbuk Samsung Hospital. They recommended electrophysiology study based on the ECG, her symptoms and the pulse records from the band. Electrophysiology study and radiofrequency catheter ablation of the bypass tract followed on 29 June 2020 at the authors' hospital. After discharge she monitored for recurrence with a smartwatch. The case was reported in Annals of Occupational and Environmental Medicine on 24 March 2021. A 2024 report describes a Galaxy Watch 4 ECG capturing polymorphic ventricular tachycardia that led to a vasospastic angina diagnosis.", "category": "benefit created", "unexpected": false, "purpose": "The Galaxy Fit's optical sensor is built to track heart rate, and the Galaxy Watch ECG app to record single-lead ECGs for rhythm assessment. The benefit came from those functions.", "system": "Samsung Galaxy Fit heart-rate monitor and Galaxy Watch ECG app", "model_version": "Galaxy Fit SM-R370 (event); Galaxy Watch Series 4 in echo", "developer": "Samsung Electronics", "deployer": null, "location": null, "domain": "Healthcare (cardiology; occupational medicine)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "A young worker's band documented a 188 bpm tachycardia. With a routine ECG showing WPW the next day and her symptoms, it backed referral for electrophysiology study. Successful radiofrequency catheter ablation came 11 days after the recorded episode. A material benefit to one person, though the diagnosis itself came from the routine ECG." } ], "ai_role": { "status": "assessed", "statement": "The band's heart-rate algorithm recorded the 188 bpm episode that documented the tachycardia. Clinicians diagnosed WPW on a 12-lead ECG and performed the ablation. The echo relied on the Galaxy Watch ECG app's trace, read by cardiologists." }, "evidence": [ { "kind": "case report", "citation": "Mun E, Hong J, Kwon S, Lee SH, Kim W, Lee C (2021). Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020. Annals of Occupational and Environmental Medicine 33:e8. (Authors at Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine; hospital staff, not Samsung Electronics.)", "title": "Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020", "url": "https://europepmc.org/article/PMC/PMC8075737", "date": "2021-03-24", "written_by": "independent", "quote": "her peak resting pulse rate reached 188 beats per minute" }, { "kind": "case report", "citation": "Avidan Y, Tabachnikov V, Danon A, Schliamser JE (2024). Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope. JACC: Case Reports.", "title": "Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope", "url": "https://europepmc.org/article/PMC/PMC11522799", "date": "2024-10-02", "written_by": "independent", "quote": "After 1 year of outpatient follow-up, there were no further clinical events." }, { "kind": "peer-reviewed study", "citation": "Bogár B et al. (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "Samsung Galaxy Fit was used for arrhythmia registration in one patient." } ], "replication": { "produced_by": [ "The wearer uses a Samsung Galaxy band or watch with heart-rate tracking or the ECG app", "A symptomatic arrhythmia occurs while the device is worn and the reading or trace is shown to a clinician", "A clinician confirms the rhythm and treats it" ], "must_hold": [ "The device recording is reviewed promptly", "A 12-lead ECG or inpatient monitoring is available for confirmation", "Definitive therapy (ablation, drugs, device) is accessible" ], "echoes": [ { "date": "2024-10-02", "setting": "54-year-old male recreational athlete, Haifa, Israel (authors' institution); Galaxy Watch 4 single-lead ECG during syncope showed polymorphic VT; vasospastic angina with coronary disease, verapamil and wearable defibrillator, no events at one year (publication date)", "model_version": "Samsung Galaxy Watch Series 4 (ECG app)", "outcome": "recurred", "source": "Avidan et al. (2024). JACC Case Rep. https://europepmc.org/article/PMC/PMC11522799" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "severity": null, "group": "personal", "basis": "No Samsung wearable incident exists; the nearest wearable false alarm is Apple Watch Crash Detection misclassifying skiing and dialing 911, harming watch users and dispatchers, the inverse of a Galaxy Fit's true 188 bpm detection." }, "headline": "Galaxy Fit pulse of 188 bpm leads to WPW diagnosis and ablation", "metric": "recorded a peak resting pulse rate of 188 beats per minute", "comparator": null, "later": { "status": "persisted", "date": "2021-03-24", "note": "After catheter ablation on 29 June 2020 the patient kept using a smartwatch to monitor for recurrence, as the case report published in March 2021 records.", "quote": "She received EPS on June 29 at our hospital, and radio frequency catheter ablation was simultaneously conducted to eliminate the bypass tract. Since her discharge, she has kept monitoring symptom recurrence with a smartwatch.", "url": "https://europepmc.org/article/PMC/PMC8075737" }, "value": null, "developer_country": "South Korea", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the account, title, summary and rating reason so that the WPW diagnosis rests on the routine health-examination ECG of 19 June 2020 with the band's pulse records as one of three inputs to the referral for electrophysiology study, replaced “curative” with the source's “successful” ablation, dropped the unsourced “Samsung Health Monitor” app name, noted the Kangbuk Samsung Hospital affiliation on the Mun citation, and marked Haifa as the authors' institution.", "source": "https://europepmc.org/article/PMC/PMC8075737 ; https://europepmc.org/article/PMC/PMC11522799", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC8075737", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Samsung_Electronics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Samsung Electronics.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study and two independent case reports. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0024", "catalog_version": "1.0.0", "source_fingerprint": "67a92f155e7f2ebf4927dbd0c87e3d3e1e18574630515c58052b468e13c22261", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0024-source-0001", "AIBD-0024-source-0002", "AIBD-0024-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Samsung Electronics" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The band's heart-rate algorithm recorded the 188 bpm episode that documented the tachycardia. Clinicians diagnosed WPW on a 12-lead ECG and performed the ablation. The echo relied on the Galaxy Watch ECG app's trace, read by cardiologists." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The band's heart-rate algorithm recorded the 188 bpm episode that documented the tachycardia. Clinicians diagnosed WPW on a 12-lead ECG and performed the ablation. The echo relied on the Galaxy Watch ECG app's trace, read by cardiologists." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A young worker's band documented a 188 bpm tachycardia. With a routine ECG showing WPW the next day and her symptoms, it backed referral for electrophysiology study. Successful radiofrequency catheter ablation came 11 days after the recorded episode. A material benefit to one person, though the diagnosis itself came from the routine ECG." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study and two independent case reports. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A young worker's band documented a 188 bpm tachycardia. With a routine ECG showing WPW the next day and her symptoms, it backed referral for electrophysiology study. Successful radiofrequency catheter ablation came 11 days after the recorded episode. A material benefit to one person, though the diagnosis itself came from the routine ECG." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A young worker's band documented a 188 bpm tachycardia. With a routine ECG showing WPW the next day and her symptoms, it backed referral for electrophysiology study. Successful radiofrequency catheter ablation came 11 days after the recorded episode. A material benefit to one person, though the diagnosis itself came from the routine ECG." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "No Samsung wearable incident exists; the nearest wearable false alarm is Apple Watch Crash Detection misclassifying skiing and dialing 911, harming watch users and dispatchers, the inverse of a Galaxy Fit's true 188 bpm detection.", "links": [ { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "group": "personal", "basis": "No Samsung wearable incident exists; the nearest wearable false alarm is Apple Watch Crash Detection misclassifying skiing and dialing 911, harming watch users and dispatchers, the inverse of a Galaxy Fit's true 188 bpm detection.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": 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188 bpm detection." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2021-03-24", "note": "After catheter ablation on 29 June 2020 the patient kept using a smartwatch to monitor for recurrence, as the case report published in March 2021 records.", "quote": "She received EPS on June 29 at our hospital, and radio frequency catheter ablation was simultaneously conducted to eliminate the bypass tract. Since her discharge, she has kept monitoring symptom recurrence with a smartwatch.", "url": "https://europepmc.org/article/PMC/PMC8075737" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0024" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 18 June 2020 a 26-year-old woman working 12-hour days in a multinational company's quality control department in South Korea experienced severe palpitations for hours. Her Samsung Galaxy Fit (SM-R370), which measures pulse by photoplethysmography, recorded a peak resting pulse rate of 188 bpm. The next day, 19 June 2020, a routine health-examination 12-lead electrocardiogram (ECG) was taken while she was asymptomatic. It showed a shortened PR interval and delta waves, establishing Wolff-Parkinson-White syndrome. The authors are from the Department of Occupational and Environmental Medicine at Kangbuk Samsung Hospital. They recommended electrophysiology study based on the ECG, her symptoms and the pulse records from the band. Electrophysiology study and radiofrequency catheter ablation of the bypass tract followed on 29 June 2020 at the authors' hospital. After discharge she monitored for recurrence with a smartwatch. The case was reported in Annals of Occupational and Environmental Medicine on 24 March 2021. A 2024 report describes a Galaxy Watch 4 ECG capturing polymorphic ventricular tachycardia that led to a vasospastic angina diagnosis.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A young worker's band documented a 188 bpm tachycardia. With a routine ECG showing WPW the next day and her symptoms, it backed referral for electrophysiology study. Successful radiofrequency catheter ablation came 11 days after the recorded episode. A material benefit to one person, though the diagnosis itself came from the routine ECG." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The Galaxy Fit's optical sensor is built to track heart rate, and the Galaxy Watch ECG app to record single-lead ECGs for rhythm assessment. 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The benefit came from those functions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-06-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the account, title, summary and rating reason so that the WPW diagnosis rests on the routine health-examination ECG of 19 June 2020 with the band's pulse records as one of three inputs to the referral for electrophysiology study, replaced “curative” with the source's “successful” ablation, dropped the unsourced “Samsung Health Monitor” app name, noted the Kangbuk Samsung Hospital affiliation on the Mun citation, and marked Haifa as the authors' institution.", "source": "https://europepmc.org/article/PMC/PMC8075737 ; https://europepmc.org/article/PMC/PMC11522799", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC8075737", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Samsung_Electronics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Samsung Electronics.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer uses a Samsung Galaxy band or watch with heart-rate tracking or the ECG app", "A symptomatic arrhythmia occurs while the device is worn and the reading or trace is shown to a clinician", "A clinician confirms the rhythm and treats it" ], "must_hold": [ "The device recording is reviewed promptly", "A 12-lead ECG or inpatient monitoring is available for confirmation", "Definitive therapy (ablation, drugs, device) is accessible" ], "echoes": [ { "date": "2024-10-02", "setting": "54-year-old male recreational athlete, Haifa, Israel (authors' institution); Galaxy Watch 4 single-lead ECG during syncope showed polymorphic VT; vasospastic angina with coronary disease, verapamil and wearable defibrillator, no events at one year (publication date)", "model_version": "Samsung Galaxy Watch Series 4 (ECG app)", "outcome": "recurred", "source": "Avidan et al. (2024). JACC Case Rep. https://europepmc.org/article/PMC/PMC11522799" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer uses a Samsung Galaxy band or watch with heart-rate tracking or the ECG app", "A symptomatic arrhythmia occurs while the device is worn and the reading or trace is shown to a clinician", "A clinician confirms the rhythm and treats it" ], "must_hold": [ "The device recording is reviewed promptly", "A 12-lead ECG or inpatient monitoring is available for confirmation", "Definitive therapy (ablation, drugs, device) is accessible" ], "echoes": [ { "date": "2024-10-02", "setting": "54-year-old male recreational athlete, Haifa, Israel (authors' institution); Galaxy Watch 4 single-lead ECG during syncope showed polymorphic VT; vasospastic angina with coronary disease, verapamil and wearable defibrillator, no events at one year (publication date)", "model_version": "Samsung Galaxy Watch Series 4 (ECG app)", "outcome": "recurred", "source": "Avidan et al. (2024). JACC Case Rep. https://europepmc.org/article/PMC/PMC11522799" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the account, title, summary and rating reason so that the WPW diagnosis rests on the routine health-examination ECG of 19 June 2020 with the band's pulse records as one of three inputs to the referral for electrophysiology study, replaced “curative” with the source's “successful” ablation, dropped the unsourced “Samsung Health Monitor” app name, noted the Kangbuk Samsung Hospital affiliation on the Mun citation, and marked Haifa as the authors' institution.", "source": "https://europepmc.org/article/PMC/PMC8075737 ; https://europepmc.org/article/PMC/PMC11522799", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC8075737", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Samsung_Electronics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Samsung Electronics.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; occupational medicine)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Mun E, Hong J, Kwon S, Lee SH, Kim W, Lee C (2021). Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020. Annals of Occupational and Environmental Medicine 33:e8. (Authors at Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine; hospital staff, not Samsung Electronics.)", "title": "Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020", "url": "https://europepmc.org/article/PMC/PMC8075737", "date": "2021-03-24", "written_by": "independent", "quote": "her peak resting pulse rate reached 188 beats per minute" }, { "kind": "case report", "citation": "Avidan Y, Tabachnikov V, Danon A, Schliamser JE (2024). Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope. JACC: Case Reports.", "title": "Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope", "url": "https://europepmc.org/article/PMC/PMC11522799", "date": "2024-10-02", "written_by": "independent", "quote": "After 1 year of outpatient follow-up, there were no further clinical events." }, { "kind": "peer-reviewed study", "citation": "Bogár B et al. (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "Samsung Galaxy Fit was used for arrhythmia registration in one patient." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0024-source-0001", "AIBD-0024-source-0002", "AIBD-0024-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Mun E, Hong J, Kwon S, Lee SH, Kim W, Lee C (2021). Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020. Annals of Occupational and Environmental Medicine 33:e8. (Authors at Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine; hospital staff, not Samsung Electronics.)", "title": "Digital health care and arrhythmia: a case of WPW syndrome in South Korea, 2020", "url": "https://europepmc.org/article/PMC/PMC8075737", "date": "2021-03-24", "written_by": "independent", "quote": "her peak resting pulse rate reached 188 beats per minute" }, { "kind": "case report", "citation": "Avidan Y, Tabachnikov V, Danon A, Schliamser JE (2024). Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope. JACC: Case Reports.", "title": "Polymorphic Ventricular Tachycardia Detected by a Smartwatch in a Patient With Recurrent Syncope", "url": "https://europepmc.org/article/PMC/PMC11522799", "date": "2024-10-02", "written_by": "independent", "quote": "After 1 year of outpatient follow-up, there were no further clinical events." }, { "kind": "peer-reviewed study", "citation": "Bogár B et al. (2024). Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review. Healthcare 12(9):892.", "title": "Detection of Arrhythmias Using Smartwatches—A Systematic Literature Review", "url": "https://europepmc.org/article/PMC/PMC11083549", "date": "2024-04-25", "written_by": "independent", "quote": "Samsung Galaxy Fit was used for arrhythmia registration in one patient." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Galaxy Fit recorded a resting pulse of 188 bpm; a routine ECG next day showed WPW and the band's records supported referral for successful ablation (South Korea, 2020).", "account": "On 18 June 2020 a 26-year-old woman working 12-hour days in a multinational company's quality control department in South Korea experienced severe palpitations for hours. Her Samsung Galaxy Fit (SM-R370), which measures pulse by photoplethysmography, recorded a peak resting pulse rate of 188 bpm. The next day, 19 June 2020, a routine health-examination 12-lead electrocardiogram (ECG) was taken while she was asymptomatic. It showed a shortened PR interval and delta waves, establishing Wolff-Parkinson-White syndrome. The authors are from the Department of Occupational and Environmental Medicine at Kangbuk Samsung Hospital. They recommended electrophysiology study based on the ECG, her symptoms and the pulse records from the band. Electrophysiology study and radiofrequency catheter ablation of the bypass tract followed on 29 June 2020 at the authors' hospital. After discharge she monitored for recurrence with a smartwatch. The case was reported in Annals of Occupational and Environmental Medicine on 24 March 2021. A 2024 report describes a Galaxy Watch 4 ECG capturing polymorphic ventricular tachycardia that led to a vasospastic angina diagnosis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The wearable recorded the rapid heart-rate episode for later clinical assessment." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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Her Samsung Galaxy Fit (SM-R370), which measures pulse by photoplethysmography, recorded a peak resting pulse rate of 188 bpm. The next day, 19 June 2020, a routine health-examination 12-lead electrocardiogram (ECG) was taken while she was asymptomatic. It showed a shortened PR interval and delta waves, establishing Wolff-Parkinson-White syndrome. The authors are from the Department of Occupational and Environmental Medicine at Kangbuk Samsung Hospital. They recommended electrophysiology study based on the ECG, her symptoms and the pulse records from the band. Electrophysiology study and radiofrequency catheter ablation of the bypass tract followed on 29 June 2020 at the authors' hospital. After discharge she monitored for recurrence with a smartwatch. The case was reported in Annals of Occupational and Environmental Medicine on 24 March 2021. A 2024 report describes a Galaxy Watch 4 ECG capturing polymorphic ventricular tachycardia that led to a vasospastic angina diagnosis.", "replication": { "produced_by": [ "The wearer uses a Samsung Galaxy band or watch with heart-rate tracking or the ECG app", "A symptomatic arrhythmia occurs while the device is worn and the reading or trace is shown to a clinician", "A clinician confirms the rhythm and treats it" ], "must_hold": [ "The device recording is reviewed promptly", "A 12-lead ECG or inpatient monitoring is available for confirmation", "Definitive therapy (ablation, drugs, device) is accessible" ], "echoes": [ { "date": "2024-10-02", "setting": "54-year-old male recreational athlete, Haifa, Israel (authors' institution); Galaxy Watch 4 single-lead ECG during syncope showed polymorphic VT; vasospastic angina with coronary disease, verapamil and wearable defibrillator, no events at one year (publication date)", "model_version": "Samsung Galaxy Watch Series 4 (ECG app)", "outcome": "recurred", "source": "Avidan et al. (2024). JACC Case Rep. https://europepmc.org/article/PMC/PMC11522799" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0194", "title": "icipe MaxEnt model maps desert locust breeding regions in East Africa with mean AUC up to 0.887", "summary": "Peer-reviewed MaxEnt model trained on 5,406 FAO breeding records (1985–2020) projected breeding suitability for Kenya, Uganda, South Sudan and Sudan; no operational outcome reported.", "date_observed": "2020-07-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Researchers at the International Center of Insect Physiology and Ecology (icipe) used MaxEnt to predict desert locust breeding regions. The paper describes MaxEnt as a machine learning algorithm. Co-authors came from the Desert Locust Control Organization for Eastern Africa, Kenya's Plant Protection Services and FAO (Keith Cressman). Of 9,134 records accessed from FAO and the Moroccan anti-locust center, 5,406 breeding sites from Morocco (367), Mauritania (2,661) and Saudi Arabia (1,703) were used. They date from 1985–2020, with a 70/30 training-test split. The Mauritania model had the highest mean AUC (0.887), followed by Saudi Arabia (0.884) and Morocco (0.820). The models were projected to potential oviposition and breeding areas in Kenya, Uganda, South Sudan and Sudan. The authors thank DLCO-EA and Kenya's Ministry of Agriculture for field data. The paper does not report use of the predictions in control operations.", "category": "general benefit", "unexpected": false, "purpose": "Predict regions suitable for desert locust breeding so that preventive control can be targeted before hoppers cause damage.", "system": "MaxEnt ecological-niche model of desert locust breeding (Kimathi et al.)", "model_version": "Maxent software, Version 3.4.1 (printed in the reference list as 'Version 3.4. 1')", "developer": "International Center of Insect Physiology and Ecology (icipe) with DLCO-EA, Kenya Plant Protection Services and FAO co-authors", "deployer": "None documented (research model)", "location": null, "domain": "Agriculture / pest forecasting", "segment": "Desert locust early warning", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No use of the predictions by FAO, DLCO-EA or national control centers is documented in the paper." }, { "group": "societal", "depth": null, "reason": "No field outcome is reported." } ], "ai_role": { "status": "assessed", "statement": "The paper itself labels MaxEnt a machine learning algorithm and reports cross-validated AUCs. Nothing in the cited source shows that a forecast changed a survey or control decision." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Kimathi E, Tonnang HEZ, Subramanian S, Cressman K, Abdel-Rahman EM, Tesfayohannes M, Niassy S, Torto B, Dubois T, Tanga CM, Kassie M, Ekesi S, Mwangi D, Kelemu S. Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa. Scientific Reports 10:11937 (2020). doi:10.1038/s41598-020-68895-2", "title": "Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa", "url": "https://doi.org/10.1038/s41598-020-68895-2", "date": "2020-07-20", "written_by": "makers", "quote": "The model generated from Mauritania had the highest mean AUC value (0.887), followed by the models from Saudi Arabia (0.884), and Morocco (0.820)." } ], "replication": { "produced_by": [ "FAO and Moroccan breeding-site time series 1985–2020", "Bioclimatic covariates and NOAA CPC soil moisture data", "A 70/30 cross-validation split" ], "must_hold": [ "Environmental drivers in the East African projection area comparable to the training countries" ], "echoes": [] }, "paired_incident": null, "headline": "icipe MaxEnt model maps locust breeding, mean AUC up to 0.887", "metric": "the Mauritania model had the highest mean AUC (0.887)", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No report of the breeding predictions being used in control operations or evaluated later was found.", "quote": null, "url": null }, "value": null, "developer_country": "Kenya", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the model version from the cited sources.", "source": "https://www.nature.com/articles/s41598-020-68895-2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Centre_of_Insect_Physiology_and_Ecology", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. 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{ "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Researchers at the International Center of Insect Physiology and Ecology (icipe) used MaxEnt to predict desert locust breeding regions. The paper describes MaxEnt as a machine learning algorithm. Co-authors came from the Desert Locust Control Organization for Eastern Africa, Kenya's Plant Protection Services and FAO (Keith Cressman). Of 9,134 records accessed from FAO and the Moroccan anti-locust center, 5,406 breeding sites from Morocco (367), Mauritania (2,661) and Saudi Arabia (1,703) were used. They date from 1985–2020, with a 70/30 training-test split. The Mauritania model had the highest mean AUC (0.887), followed by Saudi Arabia (0.884) and Morocco (0.820). The models were projected to potential oviposition and breeding areas in Kenya, Uganda, South Sudan and Sudan. The authors thank DLCO-EA and Kenya's Ministry of Agriculture for field data. The paper does not report use of the predictions in control operations.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No use of the predictions by FAO, DLCO-EA or national control centers is documented in the paper." }, { "group": "societal", "reason": "No field outcome is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Predict regions suitable for desert locust breeding so that preventive control can be targeted before hoppers cause damage." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Kenya" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Predict regions suitable for desert locust breeding so that preventive control can be targeted before hoppers cause damage." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-07-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the model version from the cited sources.", "source": "https://www.nature.com/articles/s41598-020-68895-2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Centre_of_Insect_Physiology_and_Ecology", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "FAO and Moroccan breeding-site time series 1985–2020", "Bioclimatic covariates and NOAA CPC soil moisture data", "A 70/30 cross-validation split" ], "must_hold": [ "Environmental drivers in the East African projection area comparable to the training countries" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the model version from the cited sources.", "source": "https://www.nature.com/articles/s41598-020-68895-2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Centre_of_Insect_Physiology_and_Ecology", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Agriculture / pest forecasting", "segment": "Desert locust early warning" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Kimathi E, Tonnang HEZ, Subramanian S, Cressman K, Abdel-Rahman EM, Tesfayohannes M, Niassy S, Torto B, Dubois T, Tanga CM, Kassie M, Ekesi S, Mwangi D, Kelemu S. Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa. Scientific Reports 10:11937 (2020). doi:10.1038/s41598-020-68895-2", "title": "Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa", "url": "https://doi.org/10.1038/s41598-020-68895-2", "date": "2020-07-20", "written_by": "makers", "quote": "The model generated from Mauritania had the highest mean AUC value (0.887), followed by the models from Saudi Arabia (0.884), and Morocco (0.820)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0194-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Kimathi E, Tonnang HEZ, Subramanian S, Cressman K, Abdel-Rahman EM, Tesfayohannes M, Niassy S, Torto B, Dubois T, Tanga CM, Kassie M, Ekesi S, Mwangi D, Kelemu S. Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa. Scientific Reports 10:11937 (2020). doi:10.1038/s41598-020-68895-2", "title": "Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa", "url": "https://doi.org/10.1038/s41598-020-68895-2", "date": "2020-07-20", "written_by": "makers", "quote": "The model generated from Mauritania had the highest mean AUC value (0.887), followed by the models from Saudi Arabia (0.884), and Morocco (0.820)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Peer-reviewed MaxEnt model trained on 5,406 FAO breeding records (1985–2020) projected breeding suitability for Kenya, Uganda, South Sudan and Sudan; no operational outcome reported.", "account": "Researchers at the International Center of Insect Physiology and Ecology (icipe) used MaxEnt to predict desert locust breeding regions. The paper describes MaxEnt as a machine learning algorithm. Co-authors came from the Desert Locust Control Organization for Eastern Africa, Kenya's Plant Protection Services and FAO (Keith Cressman). Of 9,134 records accessed from FAO and the Moroccan anti-locust center, 5,406 breeding sites from Morocco (367), Mauritania (2,661) and Saudi Arabia (1,703) were used. They date from 1985–2020, with a 70/30 training-test split. The Mauritania model had the highest mean AUC (0.887), followed by Saudi Arabia (0.884) and Morocco (0.820). The models were projected to potential oviposition and breeding areas in Kenya, Uganda, South Sudan and Sudan. The authors thank DLCO-EA and Kenya's Ministry of Agriculture for field data. The paper does not report use of the predictions in control operations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model estimated areas suitable for desert locust breeding." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used Maxent software version 3.4.1." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The model used occurrence and environmental data to estimate suitable habitat." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The Maxent algorithm." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Maxent software, Version 3.4.1 (printed in the reference list as 'Version 3.4. 1')" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Maxent 3.4.1.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "MaxEnt ecological-niche model of desert locust breeding (Kimathi et al.)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "International Center of Insect Physiology and Ecology (icipe) with DLCO-EA, Kenya Plant Protection Services and FAO co-authors" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "icipe MaxEnt model maps desert locust breeding regions in East Africa with mean AUC up to 0.887", "headline": "icipe MaxEnt model maps locust breeding, mean AUC up to 0.887" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "33798993354ecdd72fedbddf597bee26b796c39ebb5bf3624dd34785df4b6695" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Researchers at the International Center of Insect Physiology and Ecology (icipe) used MaxEnt to predict desert locust breeding regions. The paper describes MaxEnt as a machine learning algorithm. Co-authors came from the Desert Locust Control Organization for Eastern Africa, Kenya's Plant Protection Services and FAO (Keith Cressman). Of 9,134 records accessed from FAO and the Moroccan anti-locust center, 5,406 breeding sites from Morocco (367), Mauritania (2,661) and Saudi Arabia (1,703) were used. They date from 1985–2020, with a 70/30 training-test split. The Mauritania model had the highest mean AUC (0.887), followed by Saudi Arabia (0.884) and Morocco (0.820). The models were projected to potential oviposition and breeding areas in Kenya, Uganda, South Sudan and Sudan. The authors thank DLCO-EA and Kenya's Ministry of Agriculture for field data. The paper does not report use of the predictions in control operations.", "replication": { "produced_by": [ "FAO and Moroccan breeding-site time series 1985–2020", "Bioclimatic covariates and NOAA CPC soil moisture data", "A 70/30 cross-validation split" ], "must_hold": [ "Environmental drivers in the East African projection area comparable to the training countries" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0334", "title": "Colombia's Constitutional Court presents PretorIA (July 2020), an AI system to classify and search tutela rulings for selection; still in user testing in April 2021, no outcome metrics published", "summary": "PretorIA, presented by the Corte Constitucional on 27 July 2020 to support tutela selection (620,242 tutelas in 2019), was in user-testing in Apr 2021 (Dejusticia); no quantified outcome found.", "date_observed": "2020-07-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 27 July 2020 Colombia's Corte Constitucional presented PretorIA at a virtual press conference organized by Corferias, according to Ámbito Jurídico. It is an artificial-intelligence system meant to support the selection of tutela (constitutional protection) rulings for review. The court receives about 620,242 tutela files a year (more than 2,500 rulings a day). PretorIA was to group, analyze and classify them by criteria the court prioritizes, offering search, categorization (initially for health rulings) and statistics. Developers claimed it could process rulings in under two minutes where a person needs at least a day to read 30 files. Semana (3 July 2020) reported that the program was developed by the court with the Universidad de Buenos Aires and the Universidad del Rosario. Alongside, the court unanimously decided to stop receiving paper files and to accept electronic filing from 30 July 2020. In January 2020 the court's president Gloria Ortiz had described the forthcoming tool to El Tiempo as Prometea, the Argentine system it derives from. Dejusticia's independent research (19 April 2021, with Derechos Digitales) found PretorIA still in a testing phase with court staff. It performed four functions (classification of lower-court rulings, search, non-narrative summaries and statistics), supported by a four-person in-house AI and data team. The Universidad de los Andes algorithm registry records a 2018 pilot and 2020 deployment without quantified metrics. No court statement of a verified outcome was reachable (the court's PretorIA page renders no text).", "category": "general benefit", "unexpected": false, "purpose": "Support, without replacing, the selection of tutela rulings for Constitutional Court review by classifying, searching and summarizing incoming rulings. The claimed benefit is faster, better-informed selection.", "system": "PretorIA (Corte Constitucional tutela classification and search system, derived from Argentina's Prometea)", "model_version": null, "developer": "Corte Constitucional de Colombia with the Universidad de Buenos Aires (IALAB, Juan Corvalán) and the Universidad del Rosario", "deployer": "Corte Constitucional de Colombia", "location": "Bogotá, Colombia", "domain": "Justice administration: constitutional review case selection", "segment": "Constitutional court case management", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The intended good is faster triage of tutela files, and no measured outcome exists because the system was still in testing.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No litigant outcome is documented." }, { "group": "organizational", "depth": null, "reason": "General benefit. The processing-time claim is a developer statement at launch and the system was in testing in April 2021." }, { "group": "societal", "depth": null, "reason": "General benefit. No effect on tutela selection quality or timeliness is documented." } ], "ai_role": { "status": "assessed", "statement": "PretorIA classifies and indexes lower-court tutela rulings for the court's selection staff. Selection remains a human decision (“amplía las capacidades de conocimiento del juez, sin reemplazarlo”, per Ámbito Jurídico). The only descriptions read are news reports of the court's own launch presentation and Dejusticia's research note. It states the system was still in user testing in April 2021. No court evaluation, metric or case outcome was found, and the court's PretorIA web page was not available." }, "evidence": [ { "kind": "news report", "citation": "Ámbito Jurídico (2020). 'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional. Legis, 27 Jul 2020.", "title": "'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional", "url": "https://www.ambitojuridico.com/noticias/tecnologia/constitucional-y-derechos-humanos/pretoria-la-nueva-herramienta-tecnologica-que", "date": "2020-07-27", "written_by": "independent", "quote": "el sistema puede procesar las sentencias en medio digital en menos de 2 minutos y arrojar las características y criterios claves de las sentencias" }, { "kind": "news report", "citation": "Redacción Semana (2020). El salto de la Corte Constitucional a la tutela electrónica. Semana, 3 Jul 2020.", "title": "El salto de la Corte Constitucional a la tutela electrónica", "url": "https://www.semana.com/nacion/articulo/corte-constitucional-implementara-revision-electronica-de-tutelas/683872/", "date": "2020-07-03", "written_by": "independent", "quote": "El programa Pretoria fue desarrollado por la Corte Constitucional, la Universidad de Buenos Aires y la Universidad del Rosario." }, { "kind": "report", "citation": "Dejusticia (2021). Conoce nuestra investigación sobre PretorIA, la tecnología que incorpora la Inteligencia Artificial a la Corte Constitucional. Research by Víctor Práxedes Saavedra and Juan Carlos Upegui with Derechos Digitales, 19 Apr 2021.", "title": "Conoce nuestra investigación sobre PretorIA", "url": "https://web.archive.org/web/20210419173924/https://www.dejusticia.org/conoce-nuestra-investigacion-sobre-pretoria-la-tecnologia-que-incorpora-la-inteligencia-artificial-a-la-corte-constitucional/", "date": "2021-04-19", "written_by": "independent", "quote": "En este momento PretorIA está en fase de prueba con los usuarios, es decir, los funcionarios de la Corte, para hacer los últimos ajustes." }, { "kind": "news report", "citation": "El Tiempo (2020). 'Se parte en dos la historia de la tutela': presidenta de la Corte Constitucional (interview with Gloria Ortiz). 25 Jan 2020.", "title": "Corte ahora usa inteligencia artificial para manejar alud de tutelas", "url": "https://www.eltiempo.com/justicia/cortes/se-parte-en-dos-la-historia-de-la-tutela-presidenta-de-la-corte-constitucional-455344", "date": "2020-01-25", "written_by": "independent", "quote": "Un “ser” de inteligencia artificial tendrá a su cargo la revolución. Se llama Prometea." } ], "replication": { "produced_by": [ "Transfer of the Prometea approach from the Universidad de Buenos Aires to the court, with the Universidad del Rosario", "Electronic filing of tutela files to the court from 30 July 2020, replacing paper", "A four-person in-house AI and data-science team at the court", "Classification categories defined by the court, starting with health rulings" ], "must_hold": [ "Rulings arriving in digital, machine-readable form", "Classification accuracy acceptable to selection staff (not published)", "Human selection staff using the tool's output rather than bypassing it", "Continued institutional ownership after the launch partners withdrew" ], "echoes": [] }, "paired_incident": null, "headline": "Corte Constitucional's PretorIA remains in user testing in 2021", "metric": null, "comparator": { "against": "a person reading tutela files by hand to find the chamber's selection criterion", "before": "una persona tarda al menos un día para leer 30 expedientes", "after": "el sistema puede procesar las sentencias en medio digital en menos de 2 minutos", "basis": "assumed", "quote": "Y es que mientras una persona tarda al menos un día para leer 30 expedientes y encontrar el criterio o prioridad definida por el despacho, el sistema puede procesar las sentencias en medio digital en menos de 2 minutos y arrojar las características y criterios claves de las sentencias, lo que facilitará el análisis de la información para aplicar los criterios de selección.", "url": "https://www.ambitojuridico.com/noticias/tecnologia/constitucional-y-derechos-humanos/pretoria-la-nueva-herramienta-tecnologica-que" }, "later": { "status": "unknown", "date": null, "note": "Dejusticia reported on 19 April 2021 that PretorIA was still in user testing with court staff. 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facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Justice administration: constitutional review case selection", "segment": "Constitutional court case management" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Ámbito Jurídico (2020). 'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional. Legis, 27 Jul 2020.", "title": "'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional", "url": "https://www.ambitojuridico.com/noticias/tecnologia/constitucional-y-derechos-humanos/pretoria-la-nueva-herramienta-tecnologica-que", "date": "2020-07-27", "written_by": "independent", "quote": "el sistema puede procesar las sentencias en medio digital en menos de 2 minutos y arrojar las características y criterios claves de las sentencias" }, { "kind": "news report", "citation": "Redacción Semana (2020). El salto de la Corte Constitucional a la tutela electrónica. Semana, 3 Jul 2020.", "title": "El salto de la Corte Constitucional a la tutela electrónica", "url": "https://www.semana.com/nacion/articulo/corte-constitucional-implementara-revision-electronica-de-tutelas/683872/", "date": "2020-07-03", "written_by": "independent", "quote": "El programa Pretoria fue desarrollado por la Corte Constitucional, la Universidad de Buenos Aires y la Universidad del Rosario." }, { "kind": "report", "citation": "Dejusticia (2021). Conoce nuestra investigación sobre PretorIA, la tecnología que incorpora la Inteligencia Artificial a la Corte Constitucional. Research by Víctor Práxedes Saavedra and Juan Carlos Upegui with Derechos Digitales, 19 Apr 2021.", "title": "Conoce nuestra investigación sobre PretorIA", "url": "https://web.archive.org/web/20210419173924/https://www.dejusticia.org/conoce-nuestra-investigacion-sobre-pretoria-la-tecnologia-que-incorpora-la-inteligencia-artificial-a-la-corte-constitucional/", "date": "2021-04-19", "written_by": "independent", "quote": "En este momento PretorIA está en fase de prueba con los usuarios, es decir, los funcionarios de la Corte, para hacer los últimos ajustes." }, { "kind": "news report", "citation": "El Tiempo (2020). 'Se parte en dos la historia de la tutela': presidenta de la Corte Constitucional (interview with Gloria Ortiz). 25 Jan 2020.", "title": "Corte ahora usa inteligencia artificial para manejar alud de tutelas", "url": "https://www.eltiempo.com/justicia/cortes/se-parte-en-dos-la-historia-de-la-tutela-presidenta-de-la-corte-constitucional-455344", "date": "2020-01-25", "written_by": "independent", "quote": "Un “ser” de inteligencia artificial tendrá a su cargo la revolución. Se llama Prometea." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0334-source-0001", "AIBD-0334-source-0002", "AIBD-0334-source-0003", "AIBD-0334-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Ámbito Jurídico (2020). 'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional. Legis, 27 Jul 2020.", "title": "'Pretoria', la nueva herramienta tecnológica que apoyará la selección de tutelas de la Corte Constitucional", "url": "https://www.ambitojuridico.com/noticias/tecnologia/constitucional-y-derechos-humanos/pretoria-la-nueva-herramienta-tecnologica-que", "date": "2020-07-27", "written_by": "independent", "quote": "el sistema puede procesar las sentencias en medio digital en menos de 2 minutos y arrojar las características y criterios claves de las sentencias" }, { "kind": "news report", "citation": "Redacción Semana (2020). El salto de la Corte Constitucional a la tutela electrónica. Semana, 3 Jul 2020.", "title": "El salto de la Corte Constitucional a la tutela electrónica", "url": "https://www.semana.com/nacion/articulo/corte-constitucional-implementara-revision-electronica-de-tutelas/683872/", "date": "2020-07-03", "written_by": "independent", "quote": "El programa Pretoria fue desarrollado por la Corte Constitucional, la Universidad de Buenos Aires y la Universidad del Rosario." }, { "kind": "report", "citation": "Dejusticia (2021). Conoce nuestra investigación sobre PretorIA, la tecnología que incorpora la Inteligencia Artificial a la Corte Constitucional. Research by Víctor Práxedes Saavedra and Juan Carlos Upegui with Derechos Digitales, 19 Apr 2021.", "title": "Conoce nuestra investigación sobre PretorIA", "url": "https://web.archive.org/web/20210419173924/https://www.dejusticia.org/conoce-nuestra-investigacion-sobre-pretoria-la-tecnologia-que-incorpora-la-inteligencia-artificial-a-la-corte-constitucional/", "date": "2021-04-19", "written_by": "independent", "quote": "En este momento PretorIA está en fase de prueba con los usuarios, es decir, los funcionarios de la Corte, para hacer los últimos ajustes." }, { "kind": "news report", "citation": "El Tiempo (2020). 'Se parte en dos la historia de la tutela': presidenta de la Corte Constitucional (interview with Gloria Ortiz). 25 Jan 2020.", "title": "Corte ahora usa inteligencia artificial para manejar alud de tutelas", "url": "https://www.eltiempo.com/justicia/cortes/se-parte-en-dos-la-historia-de-la-tutela-presidenta-de-la-corte-constitucional-455344", "date": "2020-01-25", "written_by": "independent", "quote": "Un “ser” de inteligencia artificial tendrá a su cargo la revolución. Se llama Prometea." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "PretorIA, presented by the Corte Constitucional on 27 July 2020 to support tutela selection (620,242 tutelas in 2019), was in user-testing in Apr 2021 (Dejusticia); no quantified outcome found.", "account": "On 27 July 2020 Colombia's Corte Constitucional presented PretorIA at a virtual press conference organized by Corferias, according to Ámbito Jurídico. It is an artificial-intelligence system meant to support the selection of tutela (constitutional protection) rulings for review. The court receives about 620,242 tutela files a year (more than 2,500 rulings a day). PretorIA was to group, analyze and classify them by criteria the court prioritizes, offering search, categorization (initially for health rulings) and statistics. Developers claimed it could process rulings in under two minutes where a person needs at least a day to read 30 files. Semana (3 July 2020) reported that the program was developed by the court with the Universidad de Buenos Aires and the Universidad del Rosario. Alongside, the court unanimously decided to stop receiving paper files and to accept electronic filing from 30 July 2020. In January 2020 the court's president Gloria Ortiz had described the forthcoming tool to El Tiempo as Prometea, the Argentine system it derives from. Dejusticia's independent research (19 April 2021, with Derechos Digitales) found PretorIA still in a testing phase with court staff. It performed four functions (classification of lower-court rulings, search, non-narrative summaries and statistics), supported by a four-person in-house AI and data team. The Universidad de los Andes algorithm registry records a 2018 pilot and 2020 deployment without quantified metrics. No court statement of a verified outcome was reachable (the court's PretorIA page renders no text)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PretorIA (Corte Constitucional tutela classification and search system, derived from Argentina's Prometea)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Corte Constitucional de Colombia with the Universidad de Buenos Aires (IALAB, Juan Corvalán) and the Universidad del Rosario" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Colombia's Constitutional Court presents PretorIA (July 2020), an AI system to classify and search tutela rulings for selection; still in user testing in April 2021, no outcome metrics published", "headline": "Corte Constitucional's PretorIA remains in user testing in 2021" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b363a1be26ae57097aeae6dcfa46929befb925386d55fb901f8f3ad6b9094ce9" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 27 July 2020 Colombia's Corte Constitucional presented PretorIA at a virtual press conference organized by Corferias, according to Ámbito Jurídico. It is an artificial-intelligence system meant to support the selection of tutela (constitutional protection) rulings for review. The court receives about 620,242 tutela files a year (more than 2,500 rulings a day). PretorIA was to group, analyze and classify them by criteria the court prioritizes, offering search, categorization (initially for health rulings) and statistics. Developers claimed it could process rulings in under two minutes where a person needs at least a day to read 30 files. Semana (3 July 2020) reported that the program was developed by the court with the Universidad de Buenos Aires and the Universidad del Rosario. Alongside, the court unanimously decided to stop receiving paper files and to accept electronic filing from 30 July 2020. In January 2020 the court's president Gloria Ortiz had described the forthcoming tool to El Tiempo as Prometea, the Argentine system it derives from. Dejusticia's independent research (19 April 2021, with Derechos Digitales) found PretorIA still in a testing phase with court staff. It performed four functions (classification of lower-court rulings, search, non-narrative summaries and statistics), supported by a four-person in-house AI and data team. The Universidad de los Andes algorithm registry records a 2018 pilot and 2020 deployment without quantified metrics. No court statement of a verified outcome was reachable (the court's PretorIA page renders no text).", "replication": { "produced_by": [ "Transfer of the Prometea approach from the Universidad de Buenos Aires to the court, with the Universidad del Rosario", "Electronic filing of tutela files to the court from 30 July 2020, replacing paper", "A four-person in-house AI and data-science team at the court", "Classification categories defined by the court, starting with health rulings" ], "must_hold": [ "Rulings arriving in digital, machine-readable form", "Classification accuracy acceptable to selection staff (not published)", "Human selection staff using the tool's output rather than bypassing it", "Continued institutional ownership after the launch partners withdrew" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0248", "title": "Optage and Sanyo Electric Railway trial AI analysis of crossing cameras at three crossings, August to October 2020, with full deployment targeted for spring 2021", "summary": "Mynavi News (12 Aug 2020, from a press release): edge-device AI detects people including prams and wheelchairs in crossings and signals drivers via special signal lamps and an IP-VPN link to the op...", "date_observed": "2020-08-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mynavi News reported on 12 Aug 2020, from a press release, a field trial of AI image analysis of crossing surveillance cameras. Optage, Sanyo Electric Railway and the Sanyo Electric Railway Information Center had begun it. It ran from early August to mid-October 2020 at three crossings on Sanyo Electric Railway lines. Edge devices analyze the video in real time to detect people, including those with prams or wheelchairs. They aim to stop trains safely by signaling the driver through a special signal lamp and notifying the operations center over an IP-VPN. Accuracy in rain and at night was to be verified with K4Digital. Full deployment was targeted for spring 2021. No results are reported, and the OECD AI Incidents Monitor entry notes that no incidents had been reported.", "category": "general benefit", "unexpected": false, "purpose": "The trial was built to detect people in crossings in real time and alert train drivers.", "system": "AI image analysis of crossing cameras on edge devices with special-signal-lamp and IP-VPN alerts", "model_version": null, "developer": "Optage (with K4Digital for accuracy verification)", "deployer": "Sanyo Electric Railway and Sanyo Electric Railway Information Center (trial)", "location": null, "domain": "Railway safety", "segment": "Level-crossing obstacle detection", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No outcome is documented." }, { "group": "organizational", "depth": null, "reason": "No outcome is documented." }, { "group": "personal", "depth": null, "reason": "No outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "Trial design only. No detection or accuracy results were published in the sources." }, "evidence": [ { "kind": "news report", "citation": "Mynavi News (12 Aug 2020). Optage / Sanyo Electric Railway AI crossing image-analysis trial (press-release based).", "title": "オプテージと山陽電気鉄道、AI画像解析で踏切の安全性向上を目指す実証実験", "url": "https://news.mynavi.jp/article/20200812-1216717", "date": "2020-08-12", "written_by": "independent", "quote": "雨天時や夜間の精度の検証(K4Digital社協力)も行われる" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2020-08-11-4fb3: AI Image Analysis Trial to Enhance Railway Crossing Safety in Japan.", "title": "AI Image Analysis Trial to Enhance Railway Crossing Safety in Japan", "url": "https://oecd.ai/en/incidents/2020-08-11-4fb3", "date": "2020-08-11", "written_by": "independent", "quote": "The system aims to prevent accidents by alerting train operators in real time, with full deployment targeted for spring 2021." } ], "replication": { "produced_by": [ "Existing crossing surveillance cameras", "Edge-device inference and a special signal lamp link", "A telecom partner supplying the analysis" ], "must_hold": [ "Accuracy in rain and at night, which the trial set out to verify" ], "echoes": [ { "date": "2022-11-14", "setting": "Seibu Railway full operation of AI crossing anomaly detection (Response.jp)", "model_version": null, "outcome": "recurred", "source": "https://response.jp/article/2022/11/11/363968.html" } ] }, "paired_incident": null, "headline": "Optage and Sanyo Electric Railway trial AI crossing cameras", "metric": null, "comparator": { "against": "the conventional crossing-detection system (従来システム)", "before": "従来システムでは難しかった歩行者やベビーカー、車イスなどを含む\"人\"の検知", "after": "AIの画像解析技術が活用されており", "basis": "assumed", "quote": "従来システムでは難しかった歩行者やベビーカー、車イスなどを含む\"人\"の検知にAIの画像解析技術が活用されており", "url": "https://news.mynavi.jp/article/20200812-1216717" }, "later": { "status": "unknown", "date": null, "note": "No source confirms whether the full deployment targeted for spring 2021 took place.", "quote": null, "url": null }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://news.mynavi.jp/article/20200812-1216717", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E3%82%AA%E3%83%97%E3%83%86%E3%83%BC%E3%82%B8; https://en.wikipedia.org/wiki/Sanyo_Electric_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0248", "catalog_version": "1.0.0", "source_fingerprint": "875b7ddd759f558729893af7d1b83c0b01966bac3ce01c0176a4f45fcb46d45c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0248-source-0001", "AIBD-0248-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Optage (with K4Digital for accuracy verification)", "deployer": "Sanyo Electric Railway and Sanyo Electric Railway Information Center (trial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Trial design only. No detection or accuracy results were published in the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and a registry entry. 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Optage, Sanyo Electric Railway and the Sanyo Electric Railway Information Center had begun it. It ran from early August to mid-October 2020 at three crossings on Sanyo Electric Railway lines. Edge devices analyze the video in real time to detect people, including those with prams or wheelchairs. They aim to stop trains safely by signaling the driver through a special signal lamp and notifying the operations center over an IP-VPN. Accuracy in rain and at night was to be verified with K4Digital. Full deployment was targeted for spring 2021. No results are reported, and the OECD AI Incidents Monitor entry notes that no incidents had been reported.", "replication": { "produced_by": [ "Existing crossing surveillance cameras", "Edge-device inference and a special signal lamp link", "A telecom partner supplying the analysis" ], "must_hold": [ "Accuracy in rain and at night, which the trial set out to verify" ], "echoes": [ { "date": "2022-11-14", "setting": "Seibu Railway full operation of AI crossing anomaly detection (Response.jp)", "outcome": "recurred", "source": "https://response.jp/article/2022/11/11/363968.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0323", "title": "Whale Safe's acoustic, sighting and habitat-model whale presence ratings support voluntary ship slow-downs in the Santa Barbara Channel, with 59–85% cooperation", "summary": "Launched 17 Sep 2020 by UCSB's Benioff lab; grades ships' cooperation with NOAA's 10-knot zones. KCBX: vessels slowed 59% of the time in 2023; BWBS 2024 report: 85% cooperation. No vessel outcome.", "date_observed": "2020-09-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Benioff Ocean Initiative (now Benioff Ocean Science Laboratory) at UC Santa Barbara built Whale Safe. Partners were Woods Hole Oceanographic Institution, NTNU, UC Santa Cruz, the University of Washington, NOAA's Southwest Fisheries Science Center and Conserve.io. It was launched on 17 September 2020 (Mongabay, 23 September 2020). Its methodology page describes a moored acoustic buoy whose “tiny computer” detects and classifies blue, humpback and fin whale calls. Next, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. It also describes naturalist sightings via the Whale Alert and Spotter Pro apps, NOAA aerial surveys and the WhaleWatch 2.0 blue whale habitat model. These feed a daily Whale Presence Rating. AIS tracks are used to grade each vessel's “cooperation rate” with NOAA's voluntary 10-knot speed reduction zone. UC Santa Barbara's news office (21 September 2022) called the buoy system “AI-powered”. It quoted director Douglas McCauley: “Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates”. KCBX (11 April 2024) reported from Whale Safe data: “in 2023, large vessels only slowed down 59% of the time in designated slow speed zones”. The Santa Barbara Independent (16 July 2026) reported on a 2024 Protecting Blue Whales and Blue Skies (BWBS) report. It gave “an 85 percent cooperation rate overall by fleets” and a 50 percent reduction in fatal strikes. The BWBS site states 2025 participating vessels “posed 40% less risk to whales when compared to the baseline of transits in the area in 2016”. Nazario et al. (Cambridge Prisms: Coastal Futures, 2026) write that the initiative “has successfully helped improve voluntary vessel speed reduction cooperation”, citing whalesafe.com. The cooperation and risk figures belong to NOAA's and BWBS's voluntary program, which predates Whale Safe (2007 onward per UCSB). No cited source isolates Whale Safe's effect on any vessel. Cascadia's John Calambokidis told Mongabay in 2020 that voluntary slow-downs “haven't been very effective”. A separate record concerns a different system (LFDCS gliders and a NOAA Right Whale Slow Zone).", "category": "general benefit", "unexpected": false, "purpose": "Built to tell ship operators, in near real time, when whales are likely present in the shipping lanes. It also grades their cooperation with voluntary 10-knot zones so they slow down. The published ratings and report cards are that intended use.", "system": "Whale Safe (near real-time acoustic buoy with automated call detection and classification reviewed by analysts, naturalist sightings, WhaleWatch 2.0 blue whale habitat model, and AIS-based vessel speed report cards)", "model_version": "WhaleWatch 2.0", "developer": "Benioff Ocean Science Laboratory, Marine Science Institute, UC Santa Barbara, with Woods Hole Oceanographic Institution, Norwegian University of Science and Technology, UC Santa Cruz, University of Washington, NOAA Southwest Fisheries Science Center and Conserve.io", "deployer": "Shipping companies transiting NOAA's voluntary vessel speed reduction zone in the Santa Barbara Channel; the Protecting Blue Whales and Blue Skies program", "location": "Santa Barbara Channel, California, United States", "domain": "Marine conservation / shipping", "segment": "Endangered-species vessel-strike mitigation", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Shipping lines' cooperation rates (59% of distance in 2023 per KCBX; 85% fleet cooperation in a 2024 BWBS report) are program-wide figures. No source attributes a change in any operator's behavior to Whale Safe's ratings or report cards." }, { "group": "societal", "depth": null, "reason": "Strike-risk reductions (about 50% in 2024, 40% against a 2016 baseline in 2025) are BWBS's modeled estimates for participating vessels, not counts of whales saved. None is attributed to Whale Safe." } ], "ai_role": { "status": "assessed", "statement": "The automated detector on the buoy flags and classifies candidate whale calls, which an analyst confirms before they enter the daily rating. The habitat model is a statistical ensemble and the report cards are AIS arithmetic. The cooperation and risk figures belong to NOAA's and BWBS's voluntary slow-down program, which Whale Safe monitors and publicizes. No cited source separates Whale Safe's contribution from incentives, outreach and retailer pressure. The developer's own news office is the source of the claim that cooperation rose every year since launch." }, "evidence": [ { "kind": "news report", "citation": "Mongabay (2020). New tool alerts ships when whales are near. But will they slow down? 23 September 2020.", "title": "New tool alerts ships when whales are near. But will they slow down?", "url": "https://news.mongabay.com/2020/09/new-tool-alerts-ships-when-whales-are-near-but-will-they-slow-down/", "date": "2020-09-23", "written_by": "independent", "quote": "Launched Sept. 17, the Whale Safe system alerts ship operators to whales' presence, with the aim of encouraging vessels to slow down when whales are near." }, { "kind": "press release", "citation": "UC Santa Barbara, The Current (2022). Safe Harbor. 21 September 2022 (developer institution's news office).", "title": "Safe Harbor", "url": "https://news.ucsb.edu/2022/020717/safe-harbor", "date": "2022-09-21", "written_by": "makers", "quote": "Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates - which is good news," }, { "kind": "news report", "citation": "Wernik A (2024). UCSB's whale collision prevention tool reveals speed limit violations by large ships. KCBX, 11 April 2024.", "title": "UCSB's whale collision prevention tool reveals speed limit violations by large ships", "url": "https://www.kcbx.org/environment-and-energy/2024-04-11/ucsbs-whale-collision-prevention-tool-reveals-speed-limit-violations-by-large-ships", "date": "2024-04-11", "written_by": "independent", "quote": "The data showed that in 2023, large vessels only slowed down 59% of the time in designated slow speed zones." }, { "kind": "news report", "citation": "Santa Barbara Independent (2026). Record 60 Shipping Lines Take Part in Slowdown Program. 16 July 2026.", "title": "Record 60 Shipping Lines Take Part in Slowdown Program", "url": "https://www.independent.com/2026/07/16/record-60-shipping-lines-take-part-in-slowdown-program/", "date": "2026-07-16", "written_by": "independent", "quote": "According to a report in 2024 by BWBS, lowered vessel speeds reduced fatal whale strikes by 50 percent, and there was an 85 percent cooperation rate overall by fleets" }, { "kind": "press release", "citation": "Protecting Blue Whales and Blue Skies (2026). Reducing the Risk of Ship Strikes to Endangered Whales. bluewhalesblueskies.org (programme site).", "title": "Reducing the Risk of Ship Strikes to Endangered Whales", "url": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/", "date": null, "written_by": "deployer", "quote": "Participating vessels during the 2025 VSR season posed 40% less risk to whales when compared to the baseline of transits in the area in 2016." }, { "kind": "peer-reviewed study", "citation": "Nazario EC, Bailey H, et al. (2026). The role of species distribution models and multiple data sources in implementing dynamic ocean management. Cambridge Prisms: Coastal Futures, doi:10.1017/cft.2026.10041 (PMC13419462).", "title": "The role of species distribution models and multiple data sources in implementing dynamic ocean management", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "date": null, "written_by": "independent", "quote": "It has successfully helped improve voluntary vessel speed reduction cooperation" }, { "kind": "press release", "citation": "Whale Safe (undated). Methodology. whalesafe.com (developer's page).", "title": "Methodology | Whale Safe", "url": "https://whalesafe.com/methodology/", "date": null, "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected" } ], "replication": { "produced_by": [ "A moored passive acoustic buoy with automated detection and classification (Baumgartner et al. 2019 system) plus analyst review", "Sightings from naturalists and NOAA aerial surveys, a daily blue whale habitat model, and AIS tracks processed by Global Fishing Watch", "An existing NOAA voluntary speed-reduction zone with BWBS incentives for shipping lines" ], "must_hold": [ "The acoustic buoy is online (the site reported the Santa Barbara system offline on 20 October 2026) and whales vocalize within range", "Operators choose to slow in a voluntary zone. Cooperation remains incentive-driven and uneven" ], "echoes": [ { "date": "2022-09-21", "setting": "Whale Safe expanded to the San Francisco Bay region with The Marine Mammal Center", "model_version": null, "outcome": "unknown", "source": "https://news.ucsb.edu/2022/020717/safe-harbor" } ] }, "paired_incident": null, "headline": "Whale Safe ratings support ship slow-downs; cooperation 59–85%", "metric": "an 85 percent cooperation rate overall by fleets", "comparator": { "against": "the 2016 baseline of vessel transits in the area, under the BWBS voluntary speed program that Whale Safe supports (not Whale Safe alone)", "before": "the baseline of transits in the area in 2016", "after": "40% less risk to whales during the 2025 VSR season", "basis": "measured", "quote": "Participating vessels during the 2025 VSR season posed 40% less risk to whales when compared to the baseline of transits in the area in 2016.", "url": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/" }, "later": { "status": "scaled", "date": "2022-09-21", "note": "Two years after the Santa Barbara Channel launch, UC Santa Barbara announced a second Whale Safe system for the San Francisco Bay area with The Marine Mammal Center, and by July 2026 the Santa Barbara Independent reported a record 60 shipping lines in the slow-down program.", "quote": "“We are excited to partner with The Marine Mammal Center to bring the next Whale Safe system to the Bay Area — another hotspot for whale-ship collisions,” McCauley said.", "url": "https://news.ucsb.edu/2022/020717/safe-harbor" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/; https://news.ucsb.edu/2022/020717/safe-harbor; https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study, three independent news reports, two press releases from the makers and the deployer's press release. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0323", "catalog_version": "1.0.0", "source_fingerprint": "bc4659cae89266ee7d36dff972be946ba0cff4976c1b48080696fcaf664acd93", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0323-source-0001", "AIBD-0323-source-0002", "AIBD-0323-source-0003", "AIBD-0323-source-0004", "AIBD-0323-source-0005", "AIBD-0323-source-0006", "AIBD-0323-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Benioff Ocean Science Laboratory, Marine Science Institute, UC Santa Barbara, with Woods Hole Oceanographic Institution, Norwegian University of Science and Technology, UC Santa Cruz, University of Washington, NOAA Southwest Fisheries Science Center and Conserve.io", "deployer": "Shipping companies transiting NOAA's voluntary vessel speed reduction zone in the Santa Barbara Channel; the Protecting Blue Whales and Blue Skies program" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The automated detector on the buoy flags and classifies candidate whale calls, which an analyst confirms before they enter the daily rating. 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The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Shipping lines' cooperation rates (59% of distance in 2023 per KCBX; 85% fleet cooperation in a 2024 BWBS report) are program-wide figures. No source attributes a change in any operator's behavior to Whale Safe's ratings or report cards." }, { "group": "societal", "reason": "Strike-risk reductions (about 50% in 2024, 40% against a 2016 baseline in 2025) are BWBS's modeled estimates for participating vessels, not counts of whales saved. 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None is attributed to Whale Safe." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "an 85 percent cooperation rate overall by fleets", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", 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Whale Safe system to the Bay Area — another hotspot for whale-ship collisions,” McCauley said.", "url": "https://news.ucsb.edu/2022/020717/safe-harbor" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0323" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Benioff Ocean Initiative (now Benioff Ocean Science Laboratory) at UC Santa Barbara built Whale Safe. Partners were Woods Hole Oceanographic Institution, NTNU, UC Santa Cruz, the University of Washington, NOAA's Southwest Fisheries Science Center and Conserve.io. It was launched on 17 September 2020 (Mongabay, 23 September 2020). Its methodology page describes a moored acoustic buoy whose “tiny computer” detects and classifies blue, humpback and fin whale calls. Next, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. It also describes naturalist sightings via the Whale Alert and Spotter Pro apps, NOAA aerial surveys and the WhaleWatch 2.0 blue whale habitat model. These feed a daily Whale Presence Rating. AIS tracks are used to grade each vessel's “cooperation rate” with NOAA's voluntary 10-knot speed reduction zone. UC Santa Barbara's news office (21 September 2022) called the buoy system “AI-powered”. It quoted director Douglas McCauley: “Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates”. KCBX (11 April 2024) reported from Whale Safe data: “in 2023, large vessels only slowed down 59% of the time in designated slow speed zones”. The Santa Barbara Independent (16 July 2026) reported on a 2024 Protecting Blue Whales and Blue Skies (BWBS) report. It gave “an 85 percent cooperation rate overall by fleets” and a 50 percent reduction in fatal strikes. The BWBS site states 2025 participating vessels “posed 40% less risk to whales when compared to the baseline of transits in the area in 2016”. Nazario et al. (Cambridge Prisms: Coastal Futures, 2026) write that the initiative “has successfully helped improve voluntary vessel speed reduction cooperation”, citing whalesafe.com. The cooperation and risk figures belong to NOAA's and BWBS's voluntary program, which predates Whale Safe (2007 onward per UCSB). No cited source isolates Whale Safe's effect on any vessel. Cascadia's John Calambokidis told Mongabay in 2020 that voluntary slow-downs “haven't been very effective”. A separate record concerns a different system (LFDCS gliders and a NOAA Right Whale Slow Zone).", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Shipping lines' cooperation rates (59% of distance in 2023 per KCBX; 85% fleet cooperation in a 2024 BWBS report) are program-wide figures. No source attributes a change in any operator's behavior to Whale Safe's ratings or report cards." }, { "group": "societal", "reason": "Strike-risk reductions (about 50% in 2024, 40% against a 2016 baseline in 2025) are BWBS's modeled estimates for participating vessels, not counts of whales saved. None is attributed to Whale Safe." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to tell ship operators, in near real time, when whales are likely present in the shipping lanes. It also grades their cooperation with voluntary 10-knot zones so they slow down. The published ratings and report cards are that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Santa Barbara Channel, California, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to tell ship operators, in near real time, when whales are likely present in the shipping lanes. It also grades their cooperation with voluntary 10-knot zones so they slow down. The published ratings and report cards are that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-09-17", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/; https://news.ucsb.edu/2022/020717/safe-harbor; https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A moored passive acoustic buoy with automated detection and classification (Baumgartner et al. 2019 system) plus analyst review", "Sightings from naturalists and NOAA aerial surveys, a daily blue whale habitat model, and AIS tracks processed by Global Fishing Watch", "An existing NOAA voluntary speed-reduction zone with BWBS incentives for shipping lines" ], "must_hold": [ "The acoustic buoy is online (the site reported the Santa Barbara system offline on 20 October 2026) and whales vocalize within range", "Operators choose to slow in a voluntary zone. Cooperation remains incentive-driven and uneven" ], "echoes": [ { "date": "2022-09-21", "setting": "Whale Safe expanded to the San Francisco Bay region with The Marine Mammal Center", "outcome": "unknown", "source": "https://news.ucsb.edu/2022/020717/safe-harbor" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A moored passive acoustic buoy with automated detection and classification (Baumgartner et al. 2019 system) plus analyst review", "Sightings from naturalists and NOAA aerial surveys, a daily blue whale habitat model, and AIS tracks processed by Global Fishing Watch", "An existing NOAA voluntary speed-reduction zone with BWBS incentives for shipping lines" ], "must_hold": [ "The acoustic buoy is online (the site reported the Santa Barbara system offline on 20 October 2026) and whales vocalize within range", "Operators choose to slow in a voluntary zone. Cooperation remains incentive-driven and uneven" ], "echoes": [ { "date": "2022-09-21", "setting": "Whale Safe expanded to the San Francisco Bay region with The Marine Mammal Center", "outcome": "unknown", "source": "https://news.ucsb.edu/2022/020717/safe-harbor" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/; https://news.ucsb.edu/2022/020717/safe-harbor; https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Marine conservation / shipping", "segment": "Endangered-species vessel-strike mitigation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Mongabay (2020). New tool alerts ships when whales are near. But will they slow down? 23 September 2020.", "title": "New tool alerts ships when whales are near. But will they slow down?", "url": "https://news.mongabay.com/2020/09/new-tool-alerts-ships-when-whales-are-near-but-will-they-slow-down/", "date": "2020-09-23", "written_by": "independent", "quote": "Launched Sept. 17, the Whale Safe system alerts ship operators to whales' presence, with the aim of encouraging vessels to slow down when whales are near." }, { "kind": "press release", "citation": "UC Santa Barbara, The Current (2022). Safe Harbor. 21 September 2022 (developer institution's news office).", "title": "Safe Harbor", "url": "https://news.ucsb.edu/2022/020717/safe-harbor", "date": "2022-09-21", "written_by": "makers", "quote": "Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates - which is good news," }, { "kind": "news report", "citation": "Wernik A (2024). UCSB's whale collision prevention tool reveals speed limit violations by large ships. KCBX, 11 April 2024.", "title": "UCSB's whale collision prevention tool reveals speed limit violations by large ships", "url": "https://www.kcbx.org/environment-and-energy/2024-04-11/ucsbs-whale-collision-prevention-tool-reveals-speed-limit-violations-by-large-ships", "date": "2024-04-11", "written_by": "independent", "quote": "The data showed that in 2023, large vessels only slowed down 59% of the time in designated slow speed zones." }, { "kind": "news report", "citation": "Santa Barbara Independent (2026). Record 60 Shipping Lines Take Part in Slowdown Program. 16 July 2026.", "title": "Record 60 Shipping Lines Take Part in Slowdown Program", "url": "https://www.independent.com/2026/07/16/record-60-shipping-lines-take-part-in-slowdown-program/", "date": "2026-07-16", "written_by": "independent", "quote": "According to a report in 2024 by BWBS, lowered vessel speeds reduced fatal whale strikes by 50 percent, and there was an 85 percent cooperation rate overall by fleets" }, { "kind": "press release", "citation": "Protecting Blue Whales and Blue Skies (2026). Reducing the Risk of Ship Strikes to Endangered Whales. bluewhalesblueskies.org (programme site).", "title": "Reducing the Risk of Ship Strikes to Endangered Whales", "url": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/", "written_by": "deployer", "quote": "Participating vessels during the 2025 VSR season posed 40% less risk to whales when compared to the baseline of transits in the area in 2016." }, { "kind": "peer-reviewed study", "citation": "Nazario EC, Bailey H, et al. (2026). The role of species distribution models and multiple data sources in implementing dynamic ocean management. Cambridge Prisms: Coastal Futures, doi:10.1017/cft.2026.10041 (PMC13419462).", "title": "The role of species distribution models and multiple data sources in implementing dynamic ocean management", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "written_by": "independent", "quote": "It has successfully helped improve voluntary vessel speed reduction cooperation" }, { "kind": "press release", "citation": "Whale Safe (undated). Methodology. whalesafe.com (developer's page).", "title": "Methodology | Whale Safe", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0323-source-0001", "AIBD-0323-source-0002", "AIBD-0323-source-0003", "AIBD-0323-source-0004", "AIBD-0323-source-0005", "AIBD-0323-source-0006", "AIBD-0323-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Mongabay (2020). New tool alerts ships when whales are near. But will they slow down? 23 September 2020.", "title": "New tool alerts ships when whales are near. But will they slow down?", "url": "https://news.mongabay.com/2020/09/new-tool-alerts-ships-when-whales-are-near-but-will-they-slow-down/", "date": "2020-09-23", "written_by": "independent", "quote": "Launched Sept. 17, the Whale Safe system alerts ship operators to whales' presence, with the aim of encouraging vessels to slow down when whales are near." }, { "kind": "press release", "citation": "UC Santa Barbara, The Current (2022). Safe Harbor. 21 September 2022 (developer institution's news office).", "title": "Safe Harbor", "url": "https://news.ucsb.edu/2022/020717/safe-harbor", "date": "2022-09-21", "written_by": "makers", "quote": "Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates - which is good news," }, { "kind": "news report", "citation": "Wernik A (2024). UCSB's whale collision prevention tool reveals speed limit violations by large ships. KCBX, 11 April 2024.", "title": "UCSB's whale collision prevention tool reveals speed limit violations by large ships", "url": "https://www.kcbx.org/environment-and-energy/2024-04-11/ucsbs-whale-collision-prevention-tool-reveals-speed-limit-violations-by-large-ships", "date": "2024-04-11", "written_by": "independent", "quote": "The data showed that in 2023, large vessels only slowed down 59% of the time in designated slow speed zones." }, { "kind": "news report", "citation": "Santa Barbara Independent (2026). Record 60 Shipping Lines Take Part in Slowdown Program. 16 July 2026.", "title": "Record 60 Shipping Lines Take Part in Slowdown Program", "url": "https://www.independent.com/2026/07/16/record-60-shipping-lines-take-part-in-slowdown-program/", "date": "2026-07-16", "written_by": "independent", "quote": "According to a report in 2024 by BWBS, lowered vessel speeds reduced fatal whale strikes by 50 percent, and there was an 85 percent cooperation rate overall by fleets" }, { "kind": "press release", "citation": "Protecting Blue Whales and Blue Skies (2026). Reducing the Risk of Ship Strikes to Endangered Whales. bluewhalesblueskies.org (programme site).", "title": "Reducing the Risk of Ship Strikes to Endangered Whales", "url": "https://bluewhalesblueskies.org/impact/reducing-ship-strikes/", "written_by": "deployer", "quote": "Participating vessels during the 2025 VSR season posed 40% less risk to whales when compared to the baseline of transits in the area in 2016." }, { "kind": "peer-reviewed study", "citation": "Nazario EC, Bailey H, et al. (2026). The role of species distribution models and multiple data sources in implementing dynamic ocean management. Cambridge Prisms: Coastal Futures, doi:10.1017/cft.2026.10041 (PMC13419462).", "title": "The role of species distribution models and multiple data sources in implementing dynamic ocean management", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13419462/", "written_by": "independent", "quote": "It has successfully helped improve voluntary vessel speed reduction cooperation" }, { "kind": "press release", "citation": "Whale Safe (undated). Methodology. whalesafe.com (developer's page).", "title": "Methodology | Whale Safe", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Launched 17 Sep 2020 by UCSB's Benioff lab; grades ships' cooperation with NOAA's 10-knot zones. KCBX: vessels slowed 59% of the time in 2023; BWBS 2024 report: 85% cooperation. No vessel outcome.", "account": "The Benioff Ocean Initiative (now Benioff Ocean Science Laboratory) at UC Santa Barbara built Whale Safe. Partners were Woods Hole Oceanographic Institution, NTNU, UC Santa Cruz, the University of Washington, NOAA's Southwest Fisheries Science Center and Conserve.io. It was launched on 17 September 2020 (Mongabay, 23 September 2020). Its methodology page describes a moored acoustic buoy whose “tiny computer” detects and classifies blue, humpback and fin whale calls. Next, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. It also describes naturalist sightings via the Whale Alert and Spotter Pro apps, NOAA aerial surveys and the WhaleWatch 2.0 blue whale habitat model. These feed a daily Whale Presence Rating. AIS tracks are used to grade each vessel's “cooperation rate” with NOAA's voluntary 10-knot speed reduction zone. UC Santa Barbara's news office (21 September 2022) called the buoy system “AI-powered”. It quoted director Douglas McCauley: “Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates”. KCBX (11 April 2024) reported from Whale Safe data: “in 2023, large vessels only slowed down 59% of the time in designated slow speed zones”. The Santa Barbara Independent (16 July 2026) reported on a 2024 Protecting Blue Whales and Blue Skies (BWBS) report. It gave “an 85 percent cooperation rate overall by fleets” and a 50 percent reduction in fatal strikes. The BWBS site states 2025 participating vessels “posed 40% less risk to whales when compared to the baseline of transits in the area in 2016”. Nazario et al. (Cambridge Prisms: Coastal Futures, 2026) write that the initiative “has successfully helped improve voluntary vessel speed reduction cooperation”, citing whalesafe.com. The cooperation and risk figures belong to NOAA's and BWBS's voluntary program, which predates Whale Safe (2007 onward per UCSB). No cited source isolates Whale Safe's effect on any vessel. Cascadia's John Calambokidis told Mongabay in 2020 that voluntary slow-downs “haven't been very effective”. A separate record concerns a different system (LFDCS gliders and a NOAA Right Whale Slow Zone)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The detector identified possible whale calls for an analyst to confirm." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used WhaleWatch 2.0." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "WhaleWatch 2.0" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Whale Safe (near real-time acoustic buoy with automated call detection and classification reviewed by analysts, naturalist sightings, WhaleWatch 2.0 blue whale habitat model, and AIS-based vessel speed report cards)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Benioff Ocean Science Laboratory, Marine Science Institute, UC Santa Barbara, with Woods Hole Oceanographic Institution, Norwegian University of Science and Technology, UC Santa Cruz, University of Washington, NOAA Southwest Fisheries Science Center and Conserve.io" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Whale Safe's acoustic, sighting and habitat-model whale presence ratings support voluntary ship slow-downs in the Santa Barbara Channel, with 59–85% cooperation", "headline": "Whale Safe ratings support ship slow-downs; cooperation 59–85%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "bc4659cae89266ee7d36dff972be946ba0cff4976c1b48080696fcaf664acd93" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Benioff Ocean Initiative (now Benioff Ocean Science Laboratory) at UC Santa Barbara built Whale Safe. Partners were Woods Hole Oceanographic Institution, NTNU, UC Santa Cruz, the University of Washington, NOAA's Southwest Fisheries Science Center and Conserve.io. It was launched on 17 September 2020 (Mongabay, 23 September 2020). Its methodology page describes a moored acoustic buoy whose “tiny computer” detects and classifies blue, humpback and fin whale calls. Next, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. It also describes naturalist sightings via the Whale Alert and Spotter Pro apps, NOAA aerial surveys and the WhaleWatch 2.0 blue whale habitat model. These feed a daily Whale Presence Rating. AIS tracks are used to grade each vessel's “cooperation rate” with NOAA's voluntary 10-knot speed reduction zone. UC Santa Barbara's news office (21 September 2022) called the buoy system “AI-powered”. It quoted director Douglas McCauley: “Every year since the original launch of Whale Safe we have seen an increase in ship cooperation rates”. KCBX (11 April 2024) reported from Whale Safe data: “in 2023, large vessels only slowed down 59% of the time in designated slow speed zones”. The Santa Barbara Independent (16 July 2026) reported on a 2024 Protecting Blue Whales and Blue Skies (BWBS) report. It gave “an 85 percent cooperation rate overall by fleets” and a 50 percent reduction in fatal strikes. The BWBS site states 2025 participating vessels “posed 40% less risk to whales when compared to the baseline of transits in the area in 2016”. Nazario et al. (Cambridge Prisms: Coastal Futures, 2026) write that the initiative “has successfully helped improve voluntary vessel speed reduction cooperation”, citing whalesafe.com. The cooperation and risk figures belong to NOAA's and BWBS's voluntary program, which predates Whale Safe (2007 onward per UCSB). No cited source isolates Whale Safe's effect on any vessel. Cascadia's John Calambokidis told Mongabay in 2020 that voluntary slow-downs “haven't been very effective”. A separate record concerns a different system (LFDCS gliders and a NOAA Right Whale Slow Zone).", "replication": { "produced_by": [ "A moored passive acoustic buoy with automated detection and classification (Baumgartner et al. 2019 system) plus analyst review", "Sightings from naturalists and NOAA aerial surveys, a daily blue whale habitat model, and AIS tracks processed by Global Fishing Watch", "An existing NOAA voluntary speed-reduction zone with BWBS incentives for shipping lines" ], "must_hold": [ "The acoustic buoy is online (the site reported the Santa Barbara system offline on 20 October 2026) and whales vocalize within range", "Operators choose to slow in a voluntary zone. Cooperation remains incentive-driven and uneven" ], "echoes": [ { "date": "2022-09-21", "setting": "Whale Safe expanded to the San Francisco Bay region with The Marine Mammal Center", "outcome": "unknown", "source": "https://news.ucsb.edu/2022/020717/safe-harbor" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0032", "title": "Telangana Police “Darpan” face-matching reunites Som Soni with his family after five years", "summary": "Darpan matched Som Soni, missing from Allahabad since 14 July 2015, to a boy in a Goalpara, Assam child home; reunited October 2020.", "date_observed": "2020-10-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Darpan, a facial-recognition tool built by Telangana State Police, matches photographs of missing children against photographs of children lodged in child homes across the country. A routine matching run matched Som Soni to a boy police had found on 23 July 2015. He had been admitted to a child welfare center at Goalpara, Assam (spelled “Golapara” in the reports). Soni had gone missing from his home in Allahabad (Uttar Pradesh) on 14 July 2015 aged eight. ETV Bharat describes him as a resident of Handia in Allahabad. The case lay with Handia police station. Telangana Police notified Handia police. His parents traveled to Goalpara and identified him. The case was announced on 9 October 2020 by Swati Lakra, ADGP of the Telangana Police Women Safety Wing. The exact day of the reunion is not given.", "category": "benefit created", "unexpected": false, "purpose": "Darpan was built to match missing-child photographs with children found in institutions so they can be returned to their families. This reunification is that intended benefit.", "system": "Darpan face-recognition portal for missing and found children", "model_version": null, "developer": "Telangana State Police", "deployer": "Telangana State Police, with Goalpara Police (Assam) and Handia Police Station (Allahabad, Uttar Pradesh)", "location": "Goalpara, India", "domain": "Policing / missing persons and child protection", "segment": "Missing children in child-care institutions", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The good is a family reunited, and the type names the identity match that located the boy.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A child separated from his parents for five years, living in an institution in another state, was identified and returned to his family. The sources describe the match as having “changed the lives of the child and his parents”." } ], "ai_role": { "status": "assessed", "statement": "The face match was the sole lead. The boy had been in an Assam institution for five years with no identification until Darpan matched his photograph to the Uttar Pradesh missing-child record. Police then contacted the parents. Verification rested on the parents identifying him in person. The Telangana CID news page was not available. So the record relies on news reports quoting the ADGP." }, "evidence": [ { "kind": "news report", "citation": "The Tribune (2020). Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software. The Tribune, 9 October 2020.", "title": "Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software", "url": "https://www.tribuneindia.com/news/nation/face-recognition-tool-reunites-up-boy-with-parents-after-5-years-153319", "date": "2020-10-09", "written_by": "independent", "quote": "The software is used in routine to carry out the matching, and often leads to successfully uniting children with their families." }, { "kind": "news report", "citation": "ETV Bharat (2020). 5 years on, missing UP boy traced to Assam through 'DARPAN'. ETV Bharat, 9 October 2020.", "title": "Missing UP boy traced to Assam through Telangana police's face recognition tool", "url": "https://www.etvbharat.com/english/bharat/bharat-news/5-years-on-missing-up-boy-traced-to-assam-through-darpan/na20201009182148536", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana police, using the face recognition tool to match photographs of missing children with those of children found at various child homes across the country, detected the boy" }, { "kind": "news report", "citation": "Telangana Today (2020). TS Police 'Darpan' helps child from UP reunite with parents after 5 years. Telangana Today, 9 October 2020.", "title": "TS Police 'Darpan' helps child from UP reunite with parents after 5 years", "url": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana State Police played a major role in reuniting the missing child with his parents after five years." }, { "kind": "news report", "citation": "The Hans India (2020). Telangana Police's Darpan helps MP boy to reunite with parents after 10 years. The Hans India, 14 December 2020.", "title": "Telangana Police's Darpan helps MP boy to reunite with parents after 10 years", "url": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "date": "2020-12-14", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A pool of missing-child photographs (the reports do not say how these are collected)", "Photographs of children in child-care institutions supplied by welfare departments", "Routine matching runs by Telangana State Police" ], "must_hold": [ "Institutions keep supplying current photographs of found children", "Matches are verified in person by family and local police before handover", "Child's appearance five or ten years after disappearance remains matchable" ], "echoes": [ { "date": "2020-12-12", "setting": "Rahul Srivastava, missing from Jabalpur, Madhya Pradesh since 2010 (7 October 2010 per ETV Bharat; July 2010 per The Hans India), was matched by Darpan in March 2020 to a child welfare center in Howrah, West Bengal, and handed to his parents by West Bengal Police on 12 December 2020", "model_version": null, "outcome": "recurred", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805 ; https://www.etvbharat.com/english/state/telangana/10-years-on-missing-boy-re-united-with-family-by-darpan/na20201214172158693" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "483", "title": "Indian Police Allegedly Tortured and Killed Innocent Man Following Facial Misidentification", "url": "https://incidentdatabase.ai/cite/483", "severity": null, "group": "personal", "basis": "Same deployer and task: Telangana Police facial-recognition matching; Darpan matched a missing boy to his family, while a Medak police face match misidentified Mohammed Khadeer, who died in custody." }, "headline": "Darpan reunites Som Soni with his family after five years", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2020-12-12", "note": "Two months later Darpan matched another missing child, Rahul from Jabalpur, to a Howrah child welfare home; he was handed to his parents on 12 December 2020.", "quote": "The tool helped the police to detect Rahul by his photographs.", "url": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 483 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/483", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed Darpan and its matching runs to Telangana State Police rather than its Women Safety Wing, which the reports give only as ADGP Swati Lakra's title; replaced the inferred “missing from Handia” and the unsourced “FIRs” with what the reports state; and noted that the two echo sources disagree on Rahul Srivastava's disappearance date.", "source": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Telangana_Police; https://en.wikipedia.org/wiki/Telangana_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0032", "catalog_version": "1.0.0", "source_fingerprint": "c3599adb7d26fe935f2a9e8a89fbcd5cf79d3e545b17d1c488a8e6508920580a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0032-source-0001", "AIBD-0032-source-0002", "AIBD-0032-source-0003", "AIBD-0032-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Telangana State Police", "deployer": "Telangana State Police, with Goalpara Police (Assam) and Handia Police Station (Allahabad, Uttar Pradesh)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The face match was the sole lead. The boy had been in an Assam institution for five years with no identification until Darpan matched his photograph to the Uttar Pradesh missing-child record. Police then contacted the parents. Verification rested on the parents identifying him in person. The Telangana CID news page was not available. So the record relies on news reports quoting the ADGP." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The face match was the sole lead. The boy had been in an Assam institution for five years with no identification until Darpan matched his photograph to the Uttar Pradesh missing-child record. Police then contacted the parents. Verification rested on the parents identifying him in person. The Telangana CID news page was not available. So the record relies on news reports quoting the ADGP." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A child separated from his parents for five years, living in an institution in another state, was identified and returned to his family. The sources describe the match as having “changed the lives of the child and his parents”." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A child separated from his parents for five years, living in an institution in another state, was identified and returned to his family. The sources describe the match as having “changed the lives of the child and his parents”." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A child separated from his parents for five years, living in an institution in another state, was identified and returned to his family. The sources describe the match as having “changed the lives of the child and his parents”." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same deployer and task: Telangana Police facial-recognition matching; Darpan matched a missing boy to his family, while a Medak police face match misidentified Mohammed Khadeer, who died in custody.", "links": [ { "database": "AI Incident Database", "identifier": "483", "title": "Indian Police Allegedly Tortured and Killed Innocent Man Following Facial Misidentification", "url": "https://incidentdatabase.ai/cite/483", "group": "personal", "basis": "Same deployer and task: Telangana Police facial-recognition matching; Darpan matched a missing boy to his family, while a Medak police face match misidentified Mohammed Khadeer, who died in custody.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "483", "title": "Indian Police Allegedly Tortured and Killed Innocent Man Following Facial Misidentification", "url": "https://incidentdatabase.ai/cite/483", "group": "personal", "basis": "Same deployer and task: Telangana Police facial-recognition matching; Darpan matched a missing boy to his family, while a Medak police face match misidentified Mohammed Khadeer, who died in custody." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2020-12-12", "note": "Two months later Darpan matched another missing child, Rahul from Jabalpur, to a Howrah child welfare home; he was handed to his parents on 12 December 2020.", "quote": "The tool helped the police to detect Rahul by his photographs.", "url": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0032" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The good is a family reunited, and the type names the identity match that located the boy." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, 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A routine matching run matched Som Soni to a boy police had found on 23 July 2015. He had been admitted to a child welfare center at Goalpara, Assam (spelled “Golapara” in the reports). Soni had gone missing from his home in Allahabad (Uttar Pradesh) on 14 July 2015 aged eight. ETV Bharat describes him as a resident of Handia in Allahabad. The case lay with Handia police station. Telangana Police notified Handia police. His parents traveled to Goalpara and identified him. The case was announced on 9 October 2020 by Swati Lakra, ADGP of the Telangana Police Women Safety Wing. The exact day of the reunion is not given.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A child separated from his parents for five years, living in an institution in another state, was identified and returned to his family. The sources describe the match as having “changed the lives of the child and his parents”." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Darpan was built to match missing-child photographs with children found in institutions so they can be returned to their families. This reunification is that intended benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Goalpara, India", "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Darpan was built to match missing-child photographs with children found in institutions so they can be returned to their families. This reunification is that intended benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2020-10-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 483 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/483", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed Darpan and its matching runs to Telangana State Police rather than its Women Safety Wing, which the reports give only as ADGP Swati Lakra's title; replaced the inferred “missing from Handia” and the unsourced “FIRs” with what the reports state; and noted that the two echo sources disagree on Rahul Srivastava's disappearance date.", "source": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Telangana_Police; https://en.wikipedia.org/wiki/Telangana_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A pool of missing-child photographs (the reports do not say how these are collected)", "Photographs of children in child-care institutions supplied by welfare departments", "Routine matching runs by Telangana State Police" ], "must_hold": [ "Institutions keep supplying current photographs of found children", "Matches are verified in person by family and local police before handover", "Child's appearance five or ten years after disappearance remains matchable" ], "echoes": [ { "date": "2020-12-12", "setting": "Rahul Srivastava, missing from Jabalpur, Madhya Pradesh since 2010 (7 October 2010 per ETV Bharat; July 2010 per The Hans India), was matched by Darpan in March 2020 to a child welfare center in Howrah, West Bengal, and handed to his parents by West Bengal Police on 12 December 2020", "outcome": "recurred", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805 ; https://www.etvbharat.com/english/state/telangana/10-years-on-missing-boy-re-united-with-family-by-darpan/na20201214172158693" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A pool of missing-child photographs (the reports do not say how these are collected)", "Photographs of children in child-care institutions supplied by welfare departments", "Routine matching runs by Telangana State Police" ], "must_hold": [ "Institutions keep supplying current photographs of found children", "Matches are verified in person by family and local police before handover", "Child's appearance five or ten years after disappearance remains matchable" ], "echoes": [ { "date": "2020-12-12", "setting": "Rahul Srivastava, missing from Jabalpur, Madhya Pradesh since 2010 (7 October 2010 per ETV Bharat; July 2010 per The Hans India), was matched by Darpan in March 2020 to a child welfare center in Howrah, West Bengal, and handed to his parents by West Bengal Police on 12 December 2020", "outcome": "recurred", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805 ; https://www.etvbharat.com/english/state/telangana/10-years-on-missing-boy-re-united-with-family-by-darpan/na20201214172158693" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 483 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/483", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed Darpan and its matching runs to Telangana State Police rather than its Women Safety Wing, which the reports give only as ADGP Swati Lakra's title; replaced the inferred “missing from Handia” and the unsourced “FIRs” with what the reports state; and noted that the two echo sources disagree on Rahul Srivastava's disappearance date.", "source": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Telangana_Police; https://en.wikipedia.org/wiki/Telangana_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / missing persons and child protection", "segment": "Missing children in child-care institutions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Tribune (2020). Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software. The Tribune, 9 October 2020.", "title": "Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software", "url": "https://www.tribuneindia.com/news/nation/face-recognition-tool-reunites-up-boy-with-parents-after-5-years-153319", "date": "2020-10-09", "written_by": "independent", "quote": "The software is used in routine to carry out the matching, and often leads to successfully uniting children with their families." }, { "kind": "news report", "citation": "ETV Bharat (2020). 5 years on, missing UP boy traced to Assam through 'DARPAN'. ETV Bharat, 9 October 2020.", "title": "Missing UP boy traced to Assam through Telangana police's face recognition tool", "url": "https://www.etvbharat.com/english/bharat/bharat-news/5-years-on-missing-up-boy-traced-to-assam-through-darpan/na20201009182148536", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana police, using the face recognition tool to match photographs of missing children with those of children found at various child homes across the country, detected the boy" }, { "kind": "news report", "citation": "Telangana Today (2020). TS Police 'Darpan' helps child from UP reunite with parents after 5 years. Telangana Today, 9 October 2020.", "title": "TS Police 'Darpan' helps child from UP reunite with parents after 5 years", "url": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana State Police played a major role in reuniting the missing child with his parents after five years." }, { "kind": "news report", "citation": "The Hans India (2020). Telangana Police's Darpan helps MP boy to reunite with parents after 10 years. The Hans India, 14 December 2020.", "title": "Telangana Police's Darpan helps MP boy to reunite with parents after 10 years", "url": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "date": "2020-12-14", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0032-source-0001", "AIBD-0032-source-0002", "AIBD-0032-source-0003", "AIBD-0032-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Tribune (2020). Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software. The Tribune, 9 October 2020.", "title": "Boy missing from UP found in Assam after 5 years with help of Telangana Police's facial recognition software", "url": "https://www.tribuneindia.com/news/nation/face-recognition-tool-reunites-up-boy-with-parents-after-5-years-153319", "date": "2020-10-09", "written_by": "independent", "quote": "The software is used in routine to carry out the matching, and often leads to successfully uniting children with their families." }, { "kind": "news report", "citation": "ETV Bharat (2020). 5 years on, missing UP boy traced to Assam through 'DARPAN'. ETV Bharat, 9 October 2020.", "title": "Missing UP boy traced to Assam through Telangana police's face recognition tool", "url": "https://www.etvbharat.com/english/bharat/bharat-news/5-years-on-missing-up-boy-traced-to-assam-through-darpan/na20201009182148536", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana police, using the face recognition tool to match photographs of missing children with those of children found at various child homes across the country, detected the boy" }, { "kind": "news report", "citation": "Telangana Today (2020). TS Police 'Darpan' helps child from UP reunite with parents after 5 years. Telangana Today, 9 October 2020.", "title": "TS Police 'Darpan' helps child from UP reunite with parents after 5 years", "url": "https://telanganatoday.com/ts-police-darpan-helps-child-from-up-reunite-with-parents-after-5-years", "date": "2020-10-09", "written_by": "independent", "quote": "Telangana State Police played a major role in reuniting the missing child with his parents after five years." }, { "kind": "news report", "citation": "The Hans India (2020). Telangana Police's Darpan helps MP boy to reunite with parents after 10 years. The Hans India, 14 December 2020.", "title": "Telangana Police's Darpan helps MP boy to reunite with parents after 10 years", "url": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805", "date": "2020-12-14", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Darpan matched Som Soni, missing from Allahabad since 14 July 2015, to a boy in a Goalpara, Assam child home; reunited October 2020.", "account": "Darpan, a facial-recognition tool built by Telangana State Police, matches photographs of missing children against photographs of children lodged in child homes across the country. A routine matching run matched Som Soni to a boy police had found on 23 July 2015. He had been admitted to a child welfare center at Goalpara, Assam (spelled “Golapara” in the reports). Soni had gone missing from his home in Allahabad (Uttar Pradesh) on 14 July 2015 aged eight. ETV Bharat describes him as a resident of Handia in Allahabad. The case lay with Handia police station. Telangana Police notified Handia police. His parents traveled to Goalpara and identified him. The case was announced on 9 October 2020 by Swati Lakra, ADGP of the Telangana Police Women Safety Wing. The exact day of the reunion is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Darpan face-recognition portal for missing and found children" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Telangana State Police" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Telangana Police “Darpan” face-matching reunites Som Soni with his family after five years", "headline": "Darpan reunites Som Soni with his family after five years" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c3599adb7d26fe935f2a9e8a89fbcd5cf79d3e545b17d1c488a8e6508920580a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Darpan, a facial-recognition tool built by Telangana State Police, matches photographs of missing children against photographs of children lodged in child homes across the country. A routine matching run matched Som Soni to a boy police had found on 23 July 2015. He had been admitted to a child welfare center at Goalpara, Assam (spelled “Golapara” in the reports). Soni had gone missing from his home in Allahabad (Uttar Pradesh) on 14 July 2015 aged eight. ETV Bharat describes him as a resident of Handia in Allahabad. The case lay with Handia police station. Telangana Police notified Handia police. His parents traveled to Goalpara and identified him. The case was announced on 9 October 2020 by Swati Lakra, ADGP of the Telangana Police Women Safety Wing. The exact day of the reunion is not given.", "replication": { "produced_by": [ "A pool of missing-child photographs (the reports do not say how these are collected)", "Photographs of children in child-care institutions supplied by welfare departments", "Routine matching runs by Telangana State Police" ], "must_hold": [ "Institutions keep supplying current photographs of found children", "Matches are verified in person by family and local police before handover", "Child's appearance five or ten years after disappearance remains matchable" ], "echoes": [ { "date": "2020-12-12", "setting": "Rahul Srivastava, missing from Jabalpur, Madhya Pradesh since 2010 (7 October 2010 per ETV Bharat; July 2010 per The Hans India), was matched by Darpan in March 2020 to a child welfare center in Howrah, West Bengal, and handed to his parents by West Bengal Police on 12 December 2020", "outcome": "recurred", "source": "https://www.thehansindia.com/telangana/telangana-polices-darpan-helps-mp-boy-to-reunite-with-parents-after-10-years-661805 ; https://www.etvbharat.com/english/state/telangana/10-years-on-missing-boy-re-united-with-family-by-darpan/na20201214172158693" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0052", "title": "People with severe paralysis regained control of a computer at home", "summary": "Two people with ALS regained control of a computer at home using Stentrode and eye tracking.", "date_observed": "2020-10-28", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Two people with ALS received a Stentrode implant at the Royal Melbourne Hospital. Attempted movements generated computer clicks, while an eye tracker moved the cursor. Participant 1 used a support-vector machine, and participant 2 used a manually tuned threshold classifier. They began use at home without research staff on days 86 and 71 after implantation, although a caregiver still helped set up the system. Both could text, shop, and check finances. A later report followed four implanted participants, including the original two, for 12 months. It reported no serious device-related events and eight mild device effects.", "category": "benefit created", "unexpected": false, "purpose": "Restore digital device control for people with severe paralysis without open-brain surgery", "system": "Synchron Stentrode with a participant-specific decoder and Tobii Dynavox eye tracking", "model_version": null, "developer": "Synchron Inc. with the University of Melbourne", "deployer": "Royal Melbourne Hospital (implantation and follow-up); participants' homes (use)", "location": "Melbourne, Australia", "domain": "Neurotechnology / assistive communication", "segment": "People with ALS and severe upper-limb paralysis", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": { "clinicaltrials_gov": "NCT03834857" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "Participants regained sustained control of everyday computer tasks at home. No separate societal outcome was measured." } ], "ai_role": { "status": "assessed", "statement": "Participant 1 used a support-vector machine trained on movement attempts. Participant 2 used a manually tuned threshold classifier. Both converted brain signals into clicks, while an eye tracker handled cursor movement. The measured benefit belonged to the combined system." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Oxley TJ, Yoo PE, Rind GS, et al. (2021). Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience. Journal of NeuroInterventional Surgery 13(2):102-108.", "title": "Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "date": "2020-10-28", "written_by": "makers", "quote": "Completion of IADL tasks including text messaging, online shopping and managing finances independently was demonstrated in both participants." }, { "kind": "peer-reviewed study", "citation": "Peter Mitchell et al., “Assessment of Safety of a Fully Implanted Endovascular Brain-Computer Interface for Severe Paralysis in 4 Patients: The Stentrode With Thought-Controlled Digital Switch (SWITCH) Study,” JAMA Neurology 80, no. 3 (2023): 270–278, doi:10.1001/jamaneurol.2022.4847. Published online January 9, 2023.", "title": "Assessment of Safety of a Fully Implanted Endovascular Brain-Computer Interface for Severe Paralysis in 4 Patients: The Stentrode With Thought-Controlled Digital Switch (SWITCH) Study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9857731/", "date": "2023-01-09", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "An implanted electrode array recorded attempted movements.", "A participant-specific decoder converted signals into computer clicks.", "Eye tracking supplied cursor movement, and caregivers helped with setup." ], "must_hold": [ "Suitable venous anatomy and preserved motor-cortex activity.", "Clinical follow-up, training, caregiver assistance, and antiplatelet treatment." ], "echoes": [ { "date": "2023-01-09", "setting": "The same SWITCH study, expanded to four implanted participants", "model_version": null, "outcome": "recurred", "source": "Mitchell et al. (2023), doi:10.1001/jamaneurol.2022.4847. The first two participants overlap with the earlier report." } ] }, "paired_incident": null, "headline": "People with severe paralysis regained control of a computer at home", "metric": "typed 13.81 and 20.10 correct characters per minute", "comparator": { "against": "An earlier, separate study of the Utrecht implanted interface", "before": "Home use began 197 days after implantation in that earlier participant", "after": "Home use began on days 86 and 71 in the two Stentrode participants", "basis": "measured", "quote": "The current study achieved unsupervised home use of multiple-click actions within 86 days (participant 1) and 71 days (participant 2) of neurointerventional surgery.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/" }, "later": { "status": "persisted", "date": "2023-01-09", "note": "A report covering four implanted participants, including the original two, found no serious device-related events during 12 months of follow-up. Eight mild device effects occurred.", "quote": null, "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9857731/" }, "value": null, "developer_country": "United States", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “two men” with “two people” in the title and account because no cited source gives the participants' sex; added the paper's implant timing (mid-2019 and early 2020) and an explicit note that the publication date stands in for the date observed; renamed the model version to the paper's own registration (NCT03834857) because the JNIS paper never uses the SWITCH name; and treated Mitchell 2023 as independent because its lead and senior authors are Royal Melbourne Hospital investigators.", "source": "Oxley et al. (2021) J NeuroInterv Surg, PMC7848062; Mitchell et al. (2023) JAMA Neurology, PMID 36622685; RMH statement 24 January 2023", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/; https://europepmc.org/abstract/MED/36622685", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://synchron.com/news; https://en.wikipedia.org/wiki/Royal_Melbourne_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0052", "catalog_version": "1.0.0", "source_fingerprint": "1bedfa433679e79d0899a74679fd4d86a39e5fc243628f6951ae8a1aa7d24871", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0052-source-0001", "AIBD-0052-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "NCT03834857" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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The measured benefit belonged to the combined system." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "value_present", "value": { "kind": "text", "text": "Depth 2 understates the restored practical ability. A separate societal grade would require a demonstrated societal benefit." }, "provenance": { "kind": "curatorial", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Depth 2 understates the restored practical ability. A separate societal grade would require a demonstrated societal benefit." } }, "assessments[].assessor_date": { "state": "value_present", "value": { "kind": "structured", "data": { "assessor": "AIBD, AI-assisted source review", "date": "2026-10-25" } }, "provenance": { "kind": "curatorial", "basis": "Review of the sources listed in the lineage assessment.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD, 25 October 2026." } }, "assessments[].depth": { "state": "value_present", "value": { "kind": "structured", "data": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Participants regained sustained control of everyday computer tasks at home. No separate societal outcome was measured." } ] } }, "provenance": { "kind": "curatorial", "basis": "Local five-level depth rubric; Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Depth 3 for a restored ability that participants used at home." } }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "text", "text": "Peer-reviewed studies by the developers and clinical team. The outline is retained." }, "provenance": { "kind": "curatorial", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Peer-reviewed studies by the developers and clinical team. The outline is retained." } }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "text", "text": "Depth 3 for a restored ability that participants used at home." }, "provenance": { "kind": "curatorial", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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They do not establish routine commercial access at the time of the study." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "An early feasibility study of an implanted brain–computer interface." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An early feasibility study of an implanted brain–computer interface." } }, "case_links[]": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0265 describes the Utrecht interface cited as a historical comparison. The studies were not head-to-head." }, "provenance": { "kind": "curatorial", "basis": "2020 Discussion.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0265 describes the Utrecht interface cited as a historical comparison. The studies were not head-to-head." } }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "initial_abilities": { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "locator": "Results" }, "decoder_difference": { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "locator": "Supplementary Appendix, pp. 6–8" }, "follow_up": { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9857731/", "locator": "Results and Table 2" } } }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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(2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Investigational implantation and supervised training, followed by use at home." } }, "economics[].amount": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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The comparison with the Utrecht interface involved different participants and protocols." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "A prospective, open-label feasibility study without a control group. The later report includes the first two participants." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A prospective, open-label feasibility study without a control group. 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Caregiver assistance with setup remained necessary." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The first participants began home use without research staff on days 86 and 71 after implantation. Caregiver assistance with setup remained necessary." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "NCT03834857" }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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Without a control group, superiority over other assistive systems cannot be established." } }, "external_references[]": { "state": "value_present", "value": { "kind": "structured", "data": { "ClinicalTrials.gov": "NCT03834857" } }, "provenance": { "kind": "source_review", "basis": "Original study registration, inspected through the ClinicalTrials.gov API.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "NCT03834857" } }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "The four-person follow-up found no serious device-related events over 12 months. Eight mild device effects occurred, and one participant later demonstrated texting without eye tracking." }, "provenance": { "kind": "source_review", "basis": "2023 Results: Safety and Feasibility end points; Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The four-person follow-up found no serious device-related events over 12 months. Eight mild device effects occurred, and one participant later demonstrated texting without eye tracking." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Clinicians selected and implanted participants, monitored safety, and managed antiplatelet treatment. Researchers tuned decoders, and caregivers helped with setup at home." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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Researchers tuned decoders, and caregivers helped with setup at home." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0052" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The system required implantation, a chest receiver, a computer, eye tracking, individual training, caregiver support, and clinical follow-up." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience. Journal of NeuroInterventional Surgery 13(2):102-108.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "date": "2020-10-28" }, { "source_ref": "AIBD-0052-source-0002", "citation": "Peter Mitchell et al., “Assessment of Safety of a Fully Implanted Endovascular Brain-Computer Interface for Severe Paralysis in 4 Patients: The Stentrode With Thought-Controlled Digital Switch (SWITCH) Study,” JAMA Neurology 80, no. 3 (2023): 270–278, doi:10.1001/jamaneurol.2022.4847. 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No translation was used." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English. No translation was used." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "Synchron funded and participated in the later study. 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An independent safety monitor reviewed safety data, but this does not make the whole efficacy study independent." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0052-source-0001", "retained_source_order": [ "AIBD-0052-source-0001", "AIBD-0052-source-0002" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7848062/", "locator": "Results; Methods; Supplementary Appendix, pp. 3–10.", "contribution": "Original home-use outcomes, distinct decoders, training, caregiver setup, and safety.", "relationship": "Original first-in-human report by developers and clinicians.", "source_refs": [ "AIBD-0052-source-0001" ] }, { "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC7848062/supplementaryFiles", "locator": "neurintsurg-2020-016862supp001.pdf, pp. 3–10.", "contribution": "Detailed decoder architecture, training splits, click logic, and patient-reported outcomes.", "relationship": "Supplement to the initial report.", "source_refs": [ "AIBD-0052-source-0001" ] }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9857731/", "locator": "Methods; Results; Table 2; Funding and sponsor role.", "contribution": "Follow-up of four implanted participants, overlap, mild adverse effects, and independent safety-monitor role.", "relationship": "Developer-funded extension of the same trial.", "source_refs": [ "AIBD-0052-source-0002" ] }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/instance/9857731/bin/jamaneurol-e224847-s001.pdf", "locator": "2023 Supplement 1.", "contribution": "Referenced for additional methods; no uninspected details are used.", "relationship": "Supplement to the later paper.", "source_refs": [ "AIBD-0052-source-0002" ] }, { "url": "https://clinicaltrials.gov/study/NCT03834857", "locator": "Identification, status, design, and eligibility.", "contribution": "Original registration and study sponsor.", "relationship": "Sponsor-supplied registry entry.", "source_refs": [ "AIBD-0052-source-0001" ] } ], "excluded_or_consolidated_sources": [ { "url": "https://www.thermh.org.au/news/small-brain-device-proves-big-game-changer-for-severely-paralysed-patients", "reason": "The original clinical papers directly document the same outcomes and add methods and limitations." }, { "url": "https://www.thermh.org.au/news/brain-interface-proves-to-be-safe-and-effective", "reason": "The original clinical papers directly document the same outcomes and add methods and limitations." } ], "review_scope": "Methods, results, counts, chronology, AI identity and operation, human responsibilities, limitations, and economic evidence." } }, "provenance": { "kind": "source_review", "basis": "The original materials and exact locators are listed in this assessment.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001", "AIBD-0052-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original studies and their supporting materials are linked to the findings that they support." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "Two people with ALS regained control of a computer at home using Stentrode and eye tracking." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two people with ALS regained control of a computer at home using Stentrode and eye tracking." } }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "Participants controlled selections through attempted movements. The system did not choose messages or purchases for them." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. 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Eye tracking moved the cursor." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "sampling_Hz": 2000, "prediction_stride_ms": 100, "participant_1": { "classifier": "binary SVM, Gaussian radial basis kernel", "features": 78, "frequency_Hz": [ 4, 30 ], "train_trials": 24, "validation_trials": 18, "test_trials": 16, "parameter_freeze_day": 92, "C_gamma": "selected to maximize validation F1; numerical values not reported" }, "participant_2": { "classifier": "threshold", "feature": "mean normalized spectral power", "frequency_Hz": [ 12, 70 ], "calibration_seconds": 30, "lower_threshold": "while typing", "higher_threshold": "otherwise, restored after 15 seconds without typing" }, "short_click_consecutive_predictions": [ 3, 9 ], "long_click_minimum_predictions": 10 } }, "provenance": { "kind": "source_review", "basis": "2020 Supplementary Appendix, pp. 6–8: Decoder.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The first participant used a trained SVM. The second used a threshold that changed during typing. Both produced short and held clicks." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Electrical signals recorded from a cerebral vein were converted into no click, a short click, or a held click." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Electrical signals recorded from a cerebral vein were converted into no click, a short click, or a held click." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A support-vector machine with a radial-basis kernel for participant 1, and a manually tuned threshold classifier for participant 2." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A support-vector machine with a radial-basis kernel for participant 1, and a manually tuned threshold classifier for participant 2." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original paper and Supplementary Appendix: Decoder.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No software release or trained-weight identifier is reported. NCT03834857 identifies the trial, not the model.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "No software release or trained-weight identifier is reported. NCT03834857 identifies the trial, not the model." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "Stentrode, with a custom decoder and Tobii Dynavox software." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Stentrode, with a custom decoder and Tobii Dynavox software." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Synchron supplied Stentrode. The research team developed the decoding method, and Tobii Dynavox supplied eye tracking and computer-access software." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. 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(2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "People with severe paralysis regained control of a computer at home" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1bedfa433679e79d0899a74679fd4d86a39e5fc243628f6951ae8a1aa7d24871" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Content fingerprint refreshed after the October 25, 2026 source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "A caregiver attached the receiver and opened the software. The participant then used eye movements and brain-generated clicks to operate a computer." }, "provenance": { "kind": "source_review", "basis": "Oxley et al. (2020), Results and Methods; Supplementary Appendix, pp. 3–10. Mitchell et al. (2023), Methods, Results, and Table 2.", "record_fields": [], "source_refs": [ "AIBD-0052-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A caregiver attached the receiver and opened the software. The participant then used eye movements and brain-generated clicks to operate a computer." } } }, "summary": { "total": 91, "addressed": 91, "known": 74, "reviewed": 80, "record_mapped": 8, "not_assessed": 3, "complete": false, "by_state": { "value_present": 74, "not_reported": 14, "unresolved": 0, "not_assessed": 3, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0093", "title": "Togo's Novissi program targeted rural emergency cash with machine learning on satellite imagery and mobile-phone data", "summary": "ML on satellite imagery and phone metadata set eligibility for Novissi rural cash; 138,531 beneficiaries paid, Nov 2020 to Aug 2021", "date_observed": "2020-11-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Government of Togo launched the Novissi emergency cash program on 8 April 2020. On 2 November 2020 it extended it to rural areas using a machine-learning pipeline built with UC Berkeley and IPA researchers. Satellite imagery produced poverty estimates for every canton to rank the poorest. Within eligible cantons a model trained on mobile-phone metadata predicted each subscriber's consumption to decide who was paid. Beneficiaries self-registered by USSD and received mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men). The World Bank and Government of Togo report 138,531 rural beneficiaries from November 2020 to August 2021, funded by GiveDirectly (US$10 million). The Nature evaluation found phone-based targeting reduced exclusion errors by 4–21% relative to geographic alternatives.", "category": "benefit created", "unexpected": false, "purpose": "Prioritize the poorest cantons and the poorest mobile subscribers within them for COVID-19 emergency cash transfers in the absence of a social registry.", "system": "Novissi rural targeting pipeline: satellite-imagery poverty maps for canton ranking plus supervised machine learning on anonymized mobile-phone call detail records for individual eligibility", "model_version": "gradient boosting regressor with Microsoft's LightGBM", "developer": "Innovations for Poverty Action, CEGA and UC Berkeley (Aiken and Blumenstock, UC Berkeley; Bellue, University of Mannheim; Karlan and Udry, Northwestern University) for the Government of Togo", "deployer": "Government of Togo, Ministry of Digital Economy and Transformation, with GiveDirectly", "location": "Rural cantons, Togo", "domain": "Social protection and humanitarian cash transfers", "segment": "Government social assistance", "benefit_type": "Increased Scalability", "taxonomy_note": "The good for beneficiaries is emergency cash, and the type names the program's reach into rural areas with no registry.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Five mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men) to each of 138,531 rural beneficiaries during COVID-19 restrictions (World Bank study, Table 1)." }, { "group": "organizational", "depth": 2, "reason": "The Government of Togo delivered shock-responsive rural assistance without a social registry. The World Bank documents the model as a reusable case study." }, { "group": "societal", "depth": 3, "reason": "Material to many: 138,531 rural beneficiaries reached, and the Nature evaluation reports exclusion errors 4–21% lower than geographic targeting." } ], "ai_role": { "status": "assessed", "statement": "Decisive for who was paid: canton ranking and individual eligibility were both set by machine-learning predictions, while humans fixed the budget, thresholds and registration rules. The Nature evaluation is co-authored by the team that built the targeting method. The World Bank/Government of Togo case study is independent of the developers." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Aiken, E., Bellue, S., Karlan, D., Udry, C., Blumenstock, J. E. (2022). Machine learning and phone data can improve targeting of humanitarian aid. Nature 603, 864–870 (the quotation is the Extended Data Fig. 1 caption, panel a, with its reference markers omitted).", "title": "Machine learning and phone data can improve targeting of humanitarian aid", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/", "date": "2022-03-16", "written_by": "makers", "quote": "Satellite imagery of Togo is used to construct micro-estimates of poverty (middle), which are overlayed with population data to produce canton-level estimates of wealth." }, { "kind": "report", "citation": "Lawson, C., Koudeka, M., Cárdenas Martínez, A. L., Alberro Encinas, L. I., George Karippacheril, T. (2023). Novissi Togo: Harnessing Artificial Intelligence to Deliver Shock-Responsive Social Protection. World Bank and Government of Togo, Social Protection and Jobs Discussion Paper No. 2306, September 2023 (month only; first day used).", "title": "Novissi Togo: Harnessing Artificial Intelligence to Deliver Shock-Responsive Social Protection", "url": "https://documents.worldbank.org/curated/en/099751009222330502/pdf/IDU0e83f857301ff1047bf082710a8d21ddf42c3.pdf", "date": "2023-09-01", "written_by": "deployer", "quote": "Subsequently, the program was extended on November 2, 2020, to rural areas with a high prevalence of poverty (henceforth referred to as model 2)." }, { "kind": "press release", "citation": "GiveDirectly (2021). Innovations in Togo and the future of cash distribution. GiveDirectly, The Future of Cash, published 20 April 2021 (implementing partner and funder, not the AI developer).", "title": "Innovations in Togo and the future of cash distribution", "url": "https://www.givedirectly.org/togo/", "date": "2021-04-20", "written_by": "deployer", "quote": "Leveraging machine learning in combination with satellite imagery and cell phone metadata, the program was able to identify those living in extreme poverty" } ], "replication": { "produced_by": [ "Satellite-imagery poverty map ranking cantons", "Consumption model trained on mobile-phone metadata with a recent phone survey as ground truth", "USSD self-registration and mobile-money payment rails", "Government and GiveDirectly funding decision" ], "must_hold": [ "Target population owns and uses mobile phones (non-subscribers are excluded by design)", "Operators provide anonymized call detail records", "Recent ground-truth survey available for training", "Mobile-money infrastructure in place" ], "echoes": [ { "date": "2021-01-01", "setting": "Nigeria Rapid Response Register: ML poverty maps from satellite imagery selected 1,163 poorest urban wards for COVID-19 cash (month only known; first day used)", "model_version": null, "outcome": "recurred", "source": "Date: Human Rights Watch (2021) 'began in January 2021', https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living, and Smythe and Blumenstock (2022) PNAS 'mid-January 2021', https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/; ward count: World Bank (2021) PAD P176935, https://documents.worldbank.org/curated/en/717321706545772846/pdf/Nigeria-National-Social-Safety-Net-Program-Scale-Up-Project.pdf (the PAD itself dates the USSD self-registration launch to June 2021)" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "546", "title": "Algorithm to Distribute Social Welfare Reported for Oversimplifying Economic Vulnerability", "url": "https://incidentdatabase.ai/cite/546", "severity": null, "group": "personal", "basis": "World Bank-backed poverty-targeting algorithm for cash transfers oversimplified household vulnerability, excluding poor Jordanians; Novissi used the same machine-learning targeting of the poor." }, "headline": "Novissi targeting pays 138,531 rural beneficiaries in Togo", "metric": "reduced exclusion errors by 4–21% relative to geographic alternatives", "comparator": { "against": "the geographic targeting options considered by the Government of Togo", "before": "errors of exclusion of 59%–78% for the feasible alternatives", "after": "errors of exclusion of 53% for the phone-based approach, a reduction of 4–21%", "basis": "measured", "quote": "Relative to the geographic targeting options considered by the Government of Togo, the machine-learning approach reduces errors of exclusion by 4–21%.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/" }, "later": null, "value": null, "developer_country": "United States", "deployer_country": "Togo", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 546 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the GiveDirectly item to its printed title and 20 April 2021 date, marked the World Bank discussion paper as month-only, restored “(middle)” to the Nature quote and labeled it as the Extended Data Fig. 1 caption, re-stated the developer team from the Nature affiliations (Bellue at Mannheim, Karlan and Udry at Northwestern) and the World Bank's IPA/CEGA/UC Berkeley description, reworded summary and headline because the ML set eligibility while 138,531 is the count of registrants validated and paid, and cited HRW and PNAS rather than the PAD for the January 2021 Nigeria echo date since the PAD gives June 2021.", "source": "https://www.givedirectly.org/togo/; https://www.ebi.ac.uk/europepmc/webservices/rest/PMC8967719/fullTextXML; https://documents.worldbank.org/curated/en/099751009222330502/pdf/IDU0e83f857301ff1047bf082710a8d21ddf42c3.pdf; https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/; https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Scalability under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://poverty-action.org/contact-us; https://numerique.gouv.tg/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Innovations for Poverty Action.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the deployer's report and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0093", "catalog_version": "1.0.0", "source_fingerprint": "77448671472da44e0b4790a875da6f9da6fe878d11942d8dda8a6b9513fc8e36", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0093-source-0001", "AIBD-0093-source-0002", "AIBD-0093-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Innovations for Poverty Action, CEGA and UC Berkeley (Aiken and Blumenstock, UC Berkeley; Bellue, University of Mannheim; Karlan and Udry, Northwestern University) for the Government of Togo", "deployer": "Government of Togo, Ministry of Digital Economy and Transformation, with GiveDirectly" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Decisive for who was paid: canton ranking and individual eligibility were both set by machine-learning predictions, while humans fixed the budget, thresholds and registration rules. The Nature evaluation is co-authored by the team that built the targeting method. The World Bank/Government of Togo case study is independent of the developers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Decisive for who was paid: canton ranking and individual eligibility were both set by machine-learning predictions, while humans fixed the budget, thresholds and registration rules. The Nature evaluation is co-authored by the team that built the targeting method. The World Bank/Government of Togo case study is independent of the developers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Five mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men) to each of 138,531 rural beneficiaries during COVID-19 restrictions (World Bank study, Table 1)." }, { "group": "organizational", "depth": 2, "reason": "The Government of Togo delivered shock-responsive rural assistance without a social registry. The World Bank documents the model as a reusable case study." }, { "group": "societal", "depth": 3, "reason": "Material to many: 138,531 rural beneficiaries reached, and the Nature evaluation reports exclusion errors 4–21% lower than geographic targeting." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study, the deployer's report and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Five mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men) to each of 138,531 rural beneficiaries during COVID-19 restrictions (World Bank study, Table 1)." }, { "group": "organizational", "depth": 2, "reason": "The Government of Togo delivered shock-responsive rural assistance without a social registry. The World Bank documents the model as a reusable case study." }, { "group": "societal", "depth": 3, "reason": "Material to many: 138,531 rural beneficiaries reached, and the Nature evaluation reports exclusion errors 4–21% lower than geographic targeting." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Five mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men) to each of 138,531 rural beneficiaries during COVID-19 restrictions (World Bank study, Table 1)." }, { "group": "organizational", "depth": 2, "reason": "The Government of Togo delivered shock-responsive rural assistance without a social registry. The World Bank documents the model as a reusable case study." }, { "group": "societal", "depth": 3, "reason": "Material to many: 138,531 rural beneficiaries reached, and the Nature evaluation reports exclusion errors 4–21% lower than geographic targeting." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "World Bank-backed poverty-targeting algorithm for cash transfers oversimplified household vulnerability, 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E. (2022). Machine learning and phone data can improve targeting of humanitarian aid. Nature 603, 864–870 (the quotation is the Extended Data Fig. 1 caption, panel a, with its reference markers omitted).", "title": "Machine learning and phone data can improve targeting of humanitarian aid", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/", "date": "2022-03-16", "written_by": "makers", "quote": "Satellite imagery of Togo is used to construct micro-estimates of poverty (middle), which are overlayed with population data to produce canton-level estimates of wealth." }, { "kind": "report", "citation": "Lawson, C., Koudeka, M., Cárdenas Martínez, A. L., Alberro Encinas, L. I., George Karippacheril, T. (2023). Novissi Togo: Harnessing Artificial Intelligence to Deliver Shock-Responsive Social Protection. 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GiveDirectly, The Future of Cash, published 20 April 2021 (implementing partner and funder, not the AI developer).", "title": "Innovations in Togo and the future of cash distribution", "url": "https://www.givedirectly.org/togo/", "date": "2021-04-20", "written_by": "deployer", "quote": "Leveraging machine learning in combination with satellite imagery and cell phone metadata, the program was able to identify those living in extreme poverty" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ML on satellite imagery and phone metadata set eligibility for Novissi rural cash; 138,531 beneficiaries paid, Nov 2020 to Aug 2021", "account": "The Government of Togo launched the Novissi emergency cash program on 8 April 2020. On 2 November 2020 it extended it to rural areas using a machine-learning pipeline built with UC Berkeley and IPA researchers. Satellite imagery produced poverty estimates for every canton to rank the poorest. Within eligible cantons a model trained on mobile-phone metadata predicted each subscriber's consumption to decide who was paid. Beneficiaries self-registered by USSD and received mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men). The World Bank and Government of Togo report 138,531 rural beneficiaries from November 2020 to August 2021, funded by GiveDirectly (US$10 million). The Nature evaluation found phone-based targeting reduced exclusion errors by 4–21% relative to geographic alternatives." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The models estimated poverty to rank areas and determine eligibility for payments." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "LightGBM, used for gradient-boosted regression." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "gradient boosting regressor with Microsoft's LightGBM" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Novissi rural targeting pipeline: satellite-imagery poverty maps for canton ranking plus supervised machine learning on anonymized mobile-phone call detail records for individual eligibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Innovations for Poverty Action, CEGA and UC Berkeley (Aiken and Blumenstock, UC Berkeley; Bellue, University of Mannheim; Karlan and Udry, Northwestern University) for the Government of Togo" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Togo's Novissi program targeted rural emergency cash with machine learning on satellite imagery and mobile-phone data", "headline": "Novissi targeting pays 138,531 rural beneficiaries in Togo" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "77448671472da44e0b4790a875da6f9da6fe878d11942d8dda8a6b9513fc8e36" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Government of Togo launched the Novissi emergency cash program on 8 April 2020. On 2 November 2020 it extended it to rural areas using a machine-learning pipeline built with UC Berkeley and IPA researchers. Satellite imagery produced poverty estimates for every canton to rank the poorest. Within eligible cantons a model trained on mobile-phone metadata predicted each subscriber's consumption to decide who was paid. Beneficiaries self-registered by USSD and received mobile-money installments of 8,170 CFA (women) or 7,000 CFA (men). The World Bank and Government of Togo report 138,531 rural beneficiaries from November 2020 to August 2021, funded by GiveDirectly (US$10 million). The Nature evaluation found phone-based targeting reduced exclusion errors by 4–21% relative to geographic alternatives.", "replication": { "produced_by": [ "Satellite-imagery poverty map ranking cantons", "Consumption model trained on mobile-phone metadata with a recent phone survey as ground truth", "USSD self-registration and mobile-money payment rails", "Government and GiveDirectly funding decision" ], "must_hold": [ "Target population owns and uses mobile phones (non-subscribers are excluded by design)", "Operators provide anonymized call detail records", "Recent ground-truth survey available for training", "Mobile-money infrastructure in place" ], "echoes": [ { "date": "2021-01-01", "setting": "Nigeria Rapid Response Register: ML poverty maps from satellite imagery selected 1,163 poorest urban wards for COVID-19 cash (month only known; first day used)", "outcome": "recurred", "source": "Date: Human Rights Watch (2021) 'began in January 2021', https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living, and Smythe and Blumenstock (2022) PNAS 'mid-January 2021', https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/; ward count: World Bank (2021) PAD P176935, https://documents.worldbank.org/curated/en/717321706545772846/pdf/Nigeria-National-Social-Safety-Net-Program-Scale-Up-Project.pdf (the PAD itself dates the USSD self-registration launch to June 2021)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0221", "title": "Dytective gamified online dyslexia screener reaches 80.6% recall on 3,644 Spanish-speaking children (PLoS ONE 2020); a 2026 re-analysis finds a demographic confound", "summary": "Rello et al.'s random-forest screener, tested on 3,644 children from 113 organizations in five countries, 79.8% accuracy; the tool has been used over 200,000 times. A 2026 paper reports confounding.", "date_observed": "2020-12-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Luz Rello (IE University, Madrid), Baeza-Yates, Ali, Bigham and Serra published in PLoS ONE (2 December 2020) a web-based gamified test of 32 linguistic exercises. Its performance measures feed a random-forest classifier with 200 trees. The study enrolled 3,644 participants aged 7–17, 392 with a professional dyslexia diagnosis, recruited through 113 organizations in Argentina, Chile, Colombia, Spain and the USA. They were 60 primary and secondary schools, 22 specialized dyslexia centers, 18 non-profits and 3 universities. The classifier reached 79.8% accuracy with 80.6% recall and 79.3% precision for the dyslexia class. A tablet validation with 1,395 participants aged 12–17 gave 78.1% recall and 76.2% precision. The authors state that an online Spanish screening tool based on their methods had already been used by more than 200,000 people. They disclose a patent application (US 15/493,060, Rello and Ballesteros). Sudha and Murali (Frontiers in Digital Health, 23 September 2026) re-analyzed the same 3,644-participant dataset. They report that dyslexia prevalence in the dataset differs 4.7-fold by native-language status. Four demographic columns alone reach AUC 0.724 against 0.744 for all 192 task metrics. Including them yields a twelve-fold disparity in false-positive rate between language groups.", "category": "general benefit", "unexpected": false, "purpose": "Dytective was designed to screen children for dyslexia risk cheaply online. The accuracy figures and usage are that purpose.", "system": "Dytective online gamified dyslexia screening test with a random-forest classifier", "model_version": "Weka 3.8.3 implementation with 200 trees and unlimited height", "developer": "Luz Rello and co-authors (IE University, Northeastern, University of Washington, Carnegie Mellon, University of Barcelona), per the paper's author list", "deployer": "Schools, dyslexia centers and non-profits in Argentina, Chile, Colombia, Spain and the USA (study participants); public online use in Spanish-speaking countries", "location": null, "domain": "Education / learning-disability screening", "segment": "School-age dyslexia screening", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individually attributable outcome: the sources report classifier accuracy (80.6% recall) and aggregate use (over 200,000 people), not what followed a screening result." }, { "group": "organizational", "depth": null, "reason": "No outcome documented for the 60 participating schools or the other organizations beyond supplying participants." } ], "ai_role": { "status": "assessed", "statement": "The random-forest classifier is the screening decision. The 2026 re-analysis shows that demographic variables alone reach nearly the same AUC in this dataset and that false-positive rates differ twelve-fold between language groups. So the measured accuracy may partly reflect sample composition." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Rello L, Baeza-Yates R, Ali A, Bigham JP, Serra M (2020). Predicting risk of dyslexia with an online gamified test. PLoS ONE 15(12): e0241687 (PMC7710040).", "title": "Predicting risk of dyslexia with an online gamified test", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7710040/", "date": "2020-12-02", "written_by": "makers", "quote": "An online screening tool in Spanish based on our methods has already been used by more than 200,000 people." }, { "kind": "peer-reviewed study", "citation": "Sudha M, Murali S (2026). GRAPHOS re-examined: graph-theoretic features do not improve dyslexia screening, and a demographic confound in the Dytective dataset. Frontiers in Digital Health 8; doi 10.3389/fdgth.2026.1927725 (PMC13656794).", "title": "GRAPHOS re-examined: graph-theoretic features do not improve dyslexia screening, and a demographic confound in the Dytective dataset", "url": "https://europepmc.org/article/PMC/PMC13656794", "date": "2026-09-23", "written_by": "independent", "quote": "dyslexia prevalence in this dataset differs 4.7-fold by native-language status" }, { "kind": "peer-reviewed study", "citation": "Rello L, Baeza-Yates R, Ali A, Bigham JP, Serra M (2020). Predicting risk of dyslexia with an online gamified test. PLoS ONE 15(12): e0241687 (publisher page).", "title": "Predicting risk of dyslexia with an online gamified test", "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241687", "date": "2020-12-02", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Sudha M, Murali S (2026). GRAPHOS re-examined: graph-theoretic features do not improve dyslexia screening, and a demographic confound in the Dytective dataset. Frontiers in Digital Health 8; doi 10.3389/fdgth.2026.1927725 (publisher page).", "title": "GRAPHOS re-examined: graph-theoretic features do not improve dyslexia screening, and a demographic confound in the Dytective dataset", "url": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1927725/full", "date": "2026-09-23", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Thirty-two gamified linguistic exercises administered in a browser", "A labeled sample of 3,644 children, 392 with professional diagnoses, gathered through 113 organizations", "A random-forest classifier trained on performance measures" ], "must_hold": [ "Samples balanced on native language and other demographics, which the 2026 re-analysis finds this dataset is not", "Professional diagnosis as the reference standard", "Spanish-language content for Spanish-speaking populations" ], "echoes": [ { "date": "2026-09-23", "setting": "Independent re-analysis of the same Dytective dataset (Vellore Institute of Technology)", "model_version": null, "outcome": "did not recur", "source": "Sudha M, Murali S (2026), Frontiers in Digital Health, https://europepmc.org/article/PMC/PMC13656794 (demographic columns alone reach AUC 0.724 against 0.744 for all task metrics)" } ] }, "paired_incident": null, "headline": "Dytective online dyslexia screener reaches 80.6% recall", "metric": "79.8% accuracy with 80.6% recall and 79.3% precision", "comparator": null, "later": { "status": "reversed", "date": "2026-09-23", "note": "An independent re-analysis of the same dataset reported that four demographic columns alone nearly match the 192 task metrics' discrimination and that including them yields a twelve-fold false-positive disparity between language groups, undercutting the screener's reported performance.", "quote": "A subgroup audit shows that dyslexia prevalence in this dataset differs 4.7-fold by native-language status, that four demographic columns alone reach AUC 0.724 against 0.744 for all 192 task metrics, and that including them yields a twelve-fold disparity in false-positive rate between language groups.", "url": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1927725/full" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1927725/full; https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241687", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent peer-reviewed studies and two peer-reviewed studies from the makers. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0221", "catalog_version": "1.0.0", "source_fingerprint": "e723d6e44874754325c61a6d300b394d99fe295639512e138bbc0909d8c0f3e4", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0221-source-0001", "AIBD-0221-source-0002", "AIBD-0221-source-0003", "AIBD-0221-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Luz Rello and co-authors (IE University, Northeastern, University of Washington, Carnegie Mellon, University of Barcelona), per the paper's author list", "deployer": "Schools, dyslexia centers and non-profits in Argentina, Chile, Colombia, Spain and the USA (study participants); public online use in Spanish-speaking countries" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The random-forest classifier is the screening decision. 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So the measured accuracy may partly reflect sample composition." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: two independent peer-reviewed studies and two peer-reviewed studies from the makers. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individually attributable outcome: the sources report classifier accuracy (80.6% recall) and aggregate use (over 200,000 people), not what followed a screening result." }, { "group": "organizational", "reason": "No outcome documented for the 60 participating schools or the other organizations beyond supplying participants." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Weka 3.8.3 implementation with 200 trees and unlimited height" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Implemented with Weka 3.8.3. No separate release identifies the fitted classifier.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Dytective online gamified dyslexia screening test with a random-forest classifier" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Luz Rello and co-authors (IE University, Northeastern, University of Washington, Carnegie Mellon, University of Barcelona), per the paper's author list" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Dytective gamified online dyslexia screener reaches 80.6% recall on 3,644 Spanish-speaking children (PLoS ONE 2020); a 2026 re-analysis finds a demographic confound", "headline": "Dytective online dyslexia screener reaches 80.6% recall" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e723d6e44874754325c61a6d300b394d99fe295639512e138bbc0909d8c0f3e4" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Luz Rello (IE University, Madrid), Baeza-Yates, Ali, Bigham and Serra published in PLoS ONE (2 December 2020) a web-based gamified test of 32 linguistic exercises. Its performance measures feed a random-forest classifier with 200 trees. The study enrolled 3,644 participants aged 7–17, 392 with a professional dyslexia diagnosis, recruited through 113 organizations in Argentina, Chile, Colombia, Spain and the USA. They were 60 primary and secondary schools, 22 specialized dyslexia centers, 18 non-profits and 3 universities. The classifier reached 79.8% accuracy with 80.6% recall and 79.3% precision for the dyslexia class. A tablet validation with 1,395 participants aged 12–17 gave 78.1% recall and 76.2% precision. The authors state that an online Spanish screening tool based on their methods had already been used by more than 200,000 people. They disclose a patent application (US 15/493,060, Rello and Ballesteros). Sudha and Murali (Frontiers in Digital Health, 23 September 2026) re-analyzed the same 3,644-participant dataset. They report that dyslexia prevalence in the dataset differs 4.7-fold by native-language status. Four demographic columns alone reach AUC 0.724 against 0.744 for all 192 task metrics. Including them yields a twelve-fold disparity in false-positive rate between language groups.", "replication": { "produced_by": [ "Thirty-two gamified linguistic exercises administered in a browser", "A labeled sample of 3,644 children, 392 with professional diagnoses, gathered through 113 organizations", "A random-forest classifier trained on performance measures" ], "must_hold": [ "Samples balanced on native language and other demographics, which the 2026 re-analysis finds this dataset is not", "Professional diagnosis as the reference standard", "Spanish-language content for Spanish-speaking populations" ], "echoes": [ { "date": "2026-09-23", "setting": "Independent re-analysis of the same Dytective dataset (Vellore Institute of Technology)", "outcome": "did not recur", "source": "Sudha M, Murali S (2026), Frontiers in Digital Health, https://europepmc.org/article/PMC/PMC13656794 (demographic columns alone reach AUC 0.724 against 0.744 for all task metrics)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0191", "title": "PlantVillage Nuru identifies cassava disease symptoms at 65% accuracy against 40–58% for extension agents", "summary": "IITA-led evaluation in Kenya and Tanzania: the offline deep-learning app out-diagnosed extension officers (40–58%) and farmers (18–31%); six-leaf assessment raised accuracy to 74–88%.", "date_observed": "2020-12-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Nuru is a deep-learning object-detection model inside the free PlantVillage Android app, trained on 2,756 cassava leaf images and able to run offline. PlantVillage (Penn State) developed it with FAO, IITA, CIMMYT and others. IITA researchers compared Nuru with cassava experts, agricultural extension officers and farmers. The targets were cassava mosaic disease (CMD), cassava brown streak disease (CBSD) and cassava green mite damage. They inspected plants in the field and scored a 170-image cassava symptom recognition assessment tool (CaSRAT) built from a farm in Mkuranga, Tanzania. CaSRAT was also used with 30 extension agents and 50 farmers from Busia County, western Kenya, before and after they were introduced to the app. Nuru diagnosed cassava disease symptoms at 65% accuracy in 2020 versus 40–58% for extension agents and 18–31% for farmers. It rose to 74–88% with six leaves per plant assessed. Mild symptoms were recognized at only 13–37%. Two weeks of practical use gave extension workers only a slight gain. No farm-level outcome is reported.", "category": "general benefit", "unexpected": false, "purpose": "Diagnose cassava mosaic disease, cassava brown streak disease and cassava green mite damage from leaf images on an offline Android phone.", "system": "PlantVillage Nuru cassava model (deep-learning object detection)", "model_version": "PlantVillage Nuru V2.6.0-39", "developer": "PlantVillage, Pennsylvania State University, with FAO, IITA, CIMMYT and others", "deployer": "IITA field evaluation with extension officers and farmers in Busia County, Kenya, and in Tanzania", "location": "Busia County, Kenya; Mkuranga, Tanzania", "domain": "Agriculture / crop disease diagnosis", "segment": "Smallholder cassava", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The paper also frames Nuru as an e-extension tool for transferring diagnostic knowledge, but the measured result is diagnostic accuracy.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Farmers scored 18–31% on diagnosis. The paper reports only a “slight increase” in extension workers' skill after two weeks and no yield or income outcome." }, { "group": "organizational", "depth": null, "reason": "No deployment outcome for extension services is documented beyond the accuracy comparison." } ], "ai_role": { "status": "assessed", "statement": "The study measures the model's diagnostic accuracy against humans. It does not document any alert that changed a management decision. Authors include the model's developers at IITA and Penn State, so the source is peer-reviewed rather than independent of the makers." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Mrisho LM, Mbilinyi NA, Ndalahwa M, Ramcharan AM, Kehs AK, McCloskey PC, Murithi H, Hughes DP, Legg JP. Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD. Frontiers in Plant Science 11:590889 (2020). doi:10.3389/fpls.2020.590889", "title": "Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD", "url": "https://doi.org/10.3389/fpls.2020.590889", "date": "2020-12-18", "written_by": "makers", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40-58%) and farmers (18-31%)." }, { "kind": "peer-reviewed study", "citation": "Adjéi EA, Traoré K, Sawadogo/Compaoré EMFW, et al. Perception and adoption by cassava farmers of the PlantVillage Nuru application disseminated in the agricultural environment of Côte d'Ivoire: a case study in the departments of Dabou, Bouaké, and Man. Frontiers in Agronomy 6 (2024). doi:10.3389/fagro.2024.1433204", "title": "Perception and adoption by cassava farmers of the PlantVillage Nuru application disseminated in the agricultural environment of Côte d'Ivoire: a case study in the departments of Dabou, Bouaké, and Man", "url": "https://www.frontiersin.org/journals/agronomy/articles/10.3389/fagro.2024.1433204/full", "date": "2024-09-13", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A model trained on 2,756 cassava leaf images", "Field plants and a 170-image CaSRAT set scored by consensus of cassava experts", "Comparison groups of 30 extension agents and 50 farmers from Busia County" ], "must_hold": [ "Symptoms expressed on the assessed leaves (mild symptoms were recognized at only 13–37%)", "Six leaves per plant assessed to reach 74–88%" ], "echoes": [ { "date": "2018-06-25", "setting": "Fall armyworm model in the same app, launched by FAO and Penn State", "model_version": "Nuru fall armyworm", "outcome": "unknown", "source": "FAO news release, 25 June 2018" } ] }, "paired_incident": null, "headline": "PlantVillage Nuru out-diagnoses extension agents, 65% vs 40–58%", "metric": "65% accuracy in 2020 versus 40–58% for extension agents and 18–31% for farmers", "comparator": { "against": "agricultural extension agents and farmers diagnosing the same cassava symptoms", "before": "40–58% accuracy (agricultural extension agents); 18–31% (farmers)", "after": "65% accuracy in 2020 (Nuru)", "basis": "measured", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40–58%) and farmers (18–31%).", "url": "https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2020.590889/full" }, "later": { "status": "scaled", "date": "2024-09-13", "note": "A September 2024 study reports that the WAVE center has disseminated Nuru to cassava farmers in Côte d'Ivoire since 2020, with a 45% adoption rate among 152 respondents in three departments.", "quote": "In this regard, WAVE has been disseminating a plant disease detection smart application, “PlantVillage Nuru” to farmers since 2020.", "url": "https://www.frontiersin.org/journals/agronomy/articles/10.3389/fagro.2024.1433204/full" }, "value": null, "developer_country": "United States", "deployer_country": "Nigeria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Learning among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2020.590889/full; https://www.frontiersin.org/journals/agronomy/articles/10.3389/fagro.2024.1433204/full; https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2020.590889/full", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://en.wikipedia.org/wiki/International_Institute_of_Tropical_Agriculture", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study and the makers' peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0191", "catalog_version": "1.0.0", "source_fingerprint": "f6256232ccb15115e087f28114b76bd5cde4d3a11a241a11093c09cbe1ffa2cb", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0191-source-0001", "AIBD-0191-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "PlantVillage, Pennsylvania State University, with FAO, IITA, CIMMYT and others", "deployer": "IITA field evaluation with extension officers and farmers in Busia County, Kenya, and in Tanzania" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The study measures the model's diagnostic accuracy against humans. 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Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD. Frontiers in Plant Science 11:590889 (2020). doi:10.3389/fpls.2020.590889", "title": "Accuracy of a Smartphone-Based Object Detection Model, PlantVillage Nuru, in Identifying the Foliar Symptoms of the Viral Diseases of Cassava-CMD and CBSD", "url": "https://doi.org/10.3389/fpls.2020.590889", "date": "2020-12-18", "written_by": "makers", "quote": "Nuru could diagnose symptoms of cassava diseases at a higher accuracy (65% in 2020) than the agricultural extension agents (40-58%) and farmers (18-31%)." }, { "kind": "peer-reviewed study", "citation": "Adjéi EA, Traoré K, Sawadogo/Compaoré EMFW, et al. Perception and adoption by cassava farmers of the PlantVillage Nuru application disseminated in the agricultural environment of Côte d'Ivoire: a case study in the departments of Dabou, Bouaké, and Man. 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Frontiers in Agronomy 6 (2024). doi:10.3389/fagro.2024.1433204", "title": "Perception and adoption by cassava farmers of the PlantVillage Nuru application disseminated in the agricultural environment of Côte d'Ivoire: a case study in the departments of Dabou, Bouaké, and Man", "url": "https://www.frontiersin.org/journals/agronomy/articles/10.3389/fagro.2024.1433204/full", "date": "2024-09-13", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "IITA-led evaluation in Kenya and Tanzania: the offline deep-learning app out-diagnosed extension officers (40–58%) and farmers (18–31%); six-leaf assessment raised accuracy to 74–88%.", "account": "Nuru is a deep-learning object-detection model inside the free PlantVillage Android app, trained on 2,756 cassava leaf images and able to run offline. 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No farm-level outcome is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "Nuru detected signs of cassava disease in photographs." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used PlantVillage Nuru V2.6.0-39." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "PlantVillage Nuru V2.6.0-39" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "PlantVillage Nuru 2.6.0-39.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PlantVillage Nuru cassava model (deep-learning object detection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "PlantVillage, Pennsylvania State University, with FAO, IITA, CIMMYT and others" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "PlantVillage Nuru identifies cassava disease symptoms at 65% accuracy against 40–58% for extension agents", "headline": "PlantVillage Nuru out-diagnoses extension agents, 65% vs 40–58%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f6256232ccb15115e087f28114b76bd5cde4d3a11a241a11093c09cbe1ffa2cb" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nuru is a deep-learning object-detection model inside the free PlantVillage Android app, trained on 2,756 cassava leaf images and able to run offline. PlantVillage (Penn State) developed it with FAO, IITA, CIMMYT and others. IITA researchers compared Nuru with cassava experts, agricultural extension officers and farmers. The targets were cassava mosaic disease (CMD), cassava brown streak disease (CBSD) and cassava green mite damage. They inspected plants in the field and scored a 170-image cassava symptom recognition assessment tool (CaSRAT) built from a farm in Mkuranga, Tanzania. CaSRAT was also used with 30 extension agents and 50 farmers from Busia County, western Kenya, before and after they were introduced to the app. Nuru diagnosed cassava disease symptoms at 65% accuracy in 2020 versus 40–58% for extension agents and 18–31% for farmers. It rose to 74–88% with six leaves per plant assessed. Mild symptoms were recognized at only 13–37%. Two weeks of practical use gave extension workers only a slight gain. No farm-level outcome is reported.", "replication": { "produced_by": [ "A model trained on 2,756 cassava leaf images", "Field plants and a 170-image CaSRAT set scored by consensus of cassava experts", "Comparison groups of 30 extension agents and 50 farmers from Busia County" ], "must_hold": [ "Symptoms expressed on the assessed leaves (mild symptoms were recognized at only 13–37%)", "Six leaves per plant assessed to reach 74–88%" ], "echoes": [ { "date": "2018-06-25", "setting": "Fall armyworm model in the same app, launched by FAO and Penn State", "model_version": "Nuru fall armyworm", "outcome": "unknown", "source": "FAO news release, 25 June 2018" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0001", "title": "A brain–spine interface restored control of walking after paralysis", "summary": "Gert-Jan Oskam used the STIMO-BSI interface to stand, walk, and climb stairs after a spinal cord injury.", "date_observed": "2021-01-01", "date_basis": "event", "date_precision": "year", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Gert-Jan Oskam received the STIMO-BSI brain–spine interface after an incomplete cervical spinal cord injury. The decoder translated signals from his brain into spinal stimulation. He regained control of standing and walking, including stairs and uneven ground. After 40 rehabilitation sessions, he could also walk more than 10 meters with crutches while the stimulation was off.\n\nThe researchers reported stable control for over a year, including seven months of home use. An infection required removal of one cortical implant 167 days after implantation. Rehabilitation continued after treatment, and the implant was replaced in March 2023. The report concerns one participant.", "category": "benefit created", "unexpected": false, "purpose": "Researchers connected movement intentions to spinal stimulation to restore control of standing and walking.", "system": "STIMO-BSI brain–spine interface", "model_version": null, "developer": "NeuroRestore (EPFL/CHUV/UNIL) with CEA-Clinatec and ONWARD Medical", "deployer": "Lausanne University Hospital (CHUV)", "location": "Lausanne, Switzerland", "domain": "Healthcare / neurorehabilitation", "segment": "Spinal cord injury rehabilitation", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Life-changing benefit to one identifiable person: standing, walking, stair climbing and independent home use restored after ten years of paralysis. Some recovery persists when the device is switched off." } ], "ai_role": { "status": "assessed", "statement": "The REW-MSLM decoder estimated intended leg movements from cortical signals and adjusted spinal stimulation. Researchers calibrated it for the participant and set the permitted stimulation ranges." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Henri Lorach et al. “Walking Naturally after Spinal Cord Injury Using a Brain–Spine Interface.” Nature 618 (2023): 126–133. https://doi.org/10.1038/s41586-023-06094-5. Methods; Figure 4; Extended Data Figure 1; Device explantation; Data and code availability.", "title": "Walking naturally after spinal cord injury using a brain-spine interface", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/", "date": "2023-05-24", "written_by": "makers", "quote": "The participant regained the ability to walk with crutches overground even when the BSI was switched off." }, { "kind": "press release", "citation": "EPFL (2023). Thought-controlled walking again after spinal cord injury. EPFL News (developer institution release).", "title": "Thought-controlled walking again after spinal cord injury", "url": "https://actu.epfl.ch/news/thought-controlled-walking-again-after-spinal-co-4", "date": "2023-05-24", "written_by": "makers", "quote": "Thanks to algorithms based on adaptive artificial intelligence methods, movement intentions are decoded in real time from brain recordings." }, { "kind": "news report", "citation": "Chasan A (2023). Paralyzed man walks again using implants connecting brain with spinal cord. CBS News.", "title": "Paralyzed man walks again using implants connecting brain with spinal cord", "url": "https://www.cbsnews.com/news/paralyzed-man-walks-again-using-implants-connecting-brain-with-spinal-cord/", "date": "2023-05-24", "written_by": "independent", "quote": "The brain-spine interface (BSI) has remained stable for a year, allowing Gert-Jan Oskam to stand, walk, climb stairs and traverse complex terrains." }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury.” September 19, 2024. ¶¶ 2, 6–7.", "title": "ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury", "url": "https://www.globenewswire.com/news-release/2024/09/19/2948718/0/en/ONWARD-Medical-Announces-Third-Implant-of-Brain-Computer-Interface-BCI-System-to-Restore-Movement-after-Spinal-Cord-Injury.html", "date": "2024-09-19", "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement.” January 22, 2026, 1–3.", "title": "ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement", "url": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2", "date": "2026-01-22", "written_by": "makers", "quote": null }, { "kind": "dataset", "citation": "Henri Lorach. “BSI Dataset and Scripts.” Zenodo, March 2, 2023. https://doi.org/10.5281/zenodo.7680471.", "title": "BSI dataset and scripts", "url": "https://zenodo.org/records/7680471", "date": "2023-03-02", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Incomplete cervical spinal cord injury with preserved cortical movement intention and residual lumbosacral circuits that epidural stimulation can recruit", "Epidural cortical recording (WIMAGINE) paired with lumbosacral epidural stimulation, decoder calibrated to the individual", "Supervised neurorehabilitation within a regulated feasibility trial (STIMO-BSI, NCT04632290)" ], "must_hold": [ "Decoder calibration remains fast and decoding performance stable over months", "Spinal stimulation still recruits leg muscles (intact circuits below the lesion)", "Participant can tolerate implanted hardware and use the wireless system independently" ], "echoes": [ { "date": "2024-09-19", "setting": "CHUV, Lausanne. A second participant received the later ARC-BCI system for lower-limb movement; this was the third ARC-BCI participant overall.", "model_version": "ARC-BCI (WIMAGINE + ARC-IM)", "outcome": "unknown", "source": "https://www.globenewswire.com/news-release/2024/09/19/2948718/0/en/ONWARD-Medical-Announces-Third-Implant-of-Brain-Computer-Interface-BCI-System-to-Restore-Movement-after-Spinal-Cord-Injury.html" }, { "date": "2026-01-22", "setting": "CHUV, Lausanne; two further participants (35-year-old woman, upper limb; 39-year-old man, lower limb), bringing the total to seven ARC-BCI implants", "model_version": "ARC-BCI", "outcome": "unknown", "source": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2" } ] }, "paired_incident": null, "headline": "A brain–spine interface restored control of walking after paralysis", "metric": "Walked more than 10 meters with crutches and no stimulation after rehabilitation.", "comparator": { "against": "epidural spinal cord stimulation alone (STIMO), after which his recovery had plateaued for three years", "before": "after three years of regular training with stimulation only, he had reached a plateau of recovery; EES only condition showed significantly shorter step length due to increase of failed steps; WISCI II score 6 before STIMO", "after": "the BSI enabled walking with gait features that were markedly closer to those quantified in healthy individuals; WISCI II 16 after STIMO-BSI", "basis": "measured", "quote": "Compared to stimulation alone, the BSI enabled walking with gait features that were markedly closer to those quantified in healthy individuals (Extended Data Fig. 4a). The BSI ensured a continuous link between the intended movement and the modulation of stimulation protocols, which translated into the ability to walk overground", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/" }, "later": { "status": "scaled", "date": "2026-01-22", "note": "ONWARD reported that seven participants had received the later ARC-BCI system in feasibility studies. Implantation counts do not establish how many recovered movement.", "quote": null, "url": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2" }, "value": null, "developer_country": "Switzerland", "deployer_country": "Switzerland", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the Global News evidence title from the URL slug to the printed headline and added the byline to its citation, and extended the Al Jazeera quote to the full sentence so that it no longer ends mid-sentence without an ellipsis.", "source": "https://globalnews.ca/news/9722725/paralyzed-man-walks-brain-implants-netherlands; https://www.aljazeera.com/news/2023/5/25/paralysed-man-walks-with-device-that-connects-brain-spinal-cord", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/; https://www.clinicaltrialsarena.com/news/onward-implants-second-patient-with-brain-chip-in-spinal-cord-injury-trial/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.neurorestore.swiss/; https://en.wikipedia.org/wiki/Lausanne_University_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Read the original study and methods, distinguished the decoder from its hardware, added the reported implant infection and evaluation details, and traced follow-up reports to ONWARD’s original announcements.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study, the makers' dataset and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0001", "catalog_version": "1.0.0", "source_fingerprint": "8873303244c63de171fbafa7edcbbdab0d046d1d708a96d4a635b291d144f0e5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003", "AIBD-0001-source-0004", "AIBD-0001-source-0005", "AIBD-0001-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "NCT04632290" ], "role": "Clinical feasibility study" }, "provenance": { "kind": "source_review", "basis": "The original paper identifies the study registration.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "record_ids": [ "NCT04632290" ] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "NeuroRestore and CEA-Clinatec developed the interface. 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Researchers calibrated it for the participant and set the permitted stimulation ranges." }, "provenance": { "kind": "source_review", "basis": "Extended Data Figure 1; Methods: Online decoder training.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The REW-MSLM decoder estimated intended leg movements from cortical signals and adjusted spinal stimulation. Researchers calibrated it for the participant and set the permitted stimulation ranges." } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The REW-MSLM decoder estimated intended leg movements from cortical signals and adjusted spinal stimulation. 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Some recovery persists when the device is switched off." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the makers' peer-reviewed study, the makers' dataset and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "text", "text": "The participant regained movement and used the interface at home over several months." }, "provenance": { "kind": "source_review", "basis": "Results: Neurorehabilitation and neurological recovery; Independent use of the BSI.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Walking was observed in clinical tests and during home use." }, "provenance": { "kind": "source_review", "basis": "Results; Independent use of the BSI.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Walking was observed in clinical tests and during home use." } }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Life-changing benefit to one identifiable person: standing, walking, stair climbing and independent home use restored after ten years of paralysis. Some recovery persists when the device is switched off." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "value_present", "value": { "kind": "text", "text": "ARC-BCI remained investigational and unavailable for commercial use in ONWARD’s January 2026 announcement." }, "provenance": { "kind": "source_review", "basis": "ONWARD January 22, 2026, p. 3, Other Investigational Products.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ARC-BCI remained investigational and unavailable for commercial use in ONWARD’s January 2026 announcement." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "One participant in a clinical feasibility study." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design and participant.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "One participant in a clinical feasibility study." } }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "value_present", "value": { "kind": "text", "text": "The Swiss clinical team worked with CEA-Clinatec in France. Brain mapping took place in Grenoble, while surgery and rehabilitation took place in Lausanne." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design and participant.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Swiss clinical team worked with CEA-Clinatec in France. 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The study did not compare different decoders." }, "provenance": { "kind": "source_review", "basis": "Figure 3; Extended Data Figure 4.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Brain-controlled stimulation produced more natural steps than stimulation triggered by motion sensors. The study did not compare different decoders." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Walking with brain-controlled stimulation was compared with stimulation triggered by motion sensors and with no stimulation." }, "provenance": { "kind": "source_review", "basis": "Figure 3; Extended Data Figure 4; Methods: Electromyography and kinematics.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Walking with brain-controlled stimulation was compared with stimulation triggered by motion sensors and with no stimulation." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Researchers followed one participant and compared walking under different stimulation conditions. Six independent physiotherapists assessed gait videos without knowing the condition." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design and participant; Observational gait analysis.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers followed one participant and compared walking under different stimulation conditions. Six independent physiotherapists assessed gait videos without knowing the condition." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "After rehabilitation, the participant walked more than 10 meters with crutches and no stimulation. Brain-controlled stimulation also improved walking across uneven terrain." }, "provenance": { "kind": "source_review", "basis": "Figures 3–4; Neurorehabilitation and neurological recovery.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "After rehabilitation, the participant walked more than 10 meters with crutches and no stimulation. 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The repository lists source data and MATLAB scripts, which were not executed." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Henri Lorach et al. “Walking Naturally after Spinal Cord Injury Using a Brain–Spine Interface.” Nature 618 (2023): 126–133. https://doi.org/10.1038/s41586-023-06094-5. Methods; Figure 4; Extended Data Figure 1; Device explantation; Data and code availability.", "title": "Walking naturally after spinal cord injury using a brain-spine interface", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/", "date": "2023-05-24", "written_by": "makers", "quote": "The participant regained the ability to walk with crutches overground even when the BSI was switched off." }, { "kind": "press release", "citation": "EPFL (2023). Thought-controlled walking again after spinal cord injury. 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CBS News.", "title": "Paralyzed man walks again using implants connecting brain with spinal cord", "url": "https://www.cbsnews.com/news/paralyzed-man-walks-again-using-implants-connecting-brain-with-spinal-cord/", "date": "2023-05-24", "written_by": "independent", "quote": "The brain-spine interface (BSI) has remained stable for a year, allowing Gert-Jan Oskam to stand, walk, climb stairs and traverse complex terrains." }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury.” September 19, 2024. ¶¶ 2, 6–7.", "title": "ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury", "url": "https://www.globenewswire.com/news-release/2024/09/19/2948718/0/en/ONWARD-Medical-Announces-Third-Implant-of-Brain-Computer-Interface-BCI-System-to-Restore-Movement-after-Spinal-Cord-Injury.html", "date": "2024-09-19", "written_by": "makers" }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement.” January 22, 2026, 1–3.", "title": "ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement", "url": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2", "date": "2026-01-22", "written_by": "makers" }, { "kind": "dataset", "citation": "Henri Lorach. “BSI Dataset and Scripts.” Zenodo, March 2, 2023. https://doi.org/10.5281/zenodo.7680471.", "title": "BSI dataset and scripts", "url": "https://zenodo.org/records/7680471", "date": "2023-03-02", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003", "AIBD-0001-source-0004", "AIBD-0001-source-0005", "AIBD-0001-source-0006" ], "role": "Sources retained for this entry" }, "provenance": { "kind": "curatorial", "basis": "Synchronized identifiers with the retained source list.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "English." }, "provenance": { "kind": "source_review", "basis": "Language of the retained six sources.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003", "AIBD-0001-source-0004", "AIBD-0001-source-0005", "AIBD-0001-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Henri Lorach et al. “Walking Naturally after Spinal Cord Injury Using a Brain–Spine Interface.” Nature 618 (2023): 126–133. https://doi.org/10.1038/s41586-023-06094-5. Methods; Figure 4; Extended Data Figure 1; Device explantation; Data and code availability.", "title": "Walking naturally after spinal cord injury using a brain-spine interface", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/", "date": "2023-05-24", "written_by": "makers", "quote": "The participant regained the ability to walk with crutches overground even when the BSI was switched off." }, { "kind": "press release", "citation": "EPFL (2023). Thought-controlled walking again after spinal cord injury. EPFL News (developer institution release).", "title": "Thought-controlled walking again after spinal cord injury", "url": "https://actu.epfl.ch/news/thought-controlled-walking-again-after-spinal-co-4", "date": "2023-05-24", "written_by": "makers", "quote": "Thanks to algorithms based on adaptive artificial intelligence methods, movement intentions are decoded in real time from brain recordings." }, { "kind": "news report", "citation": "Chasan A (2023). Paralyzed man walks again using implants connecting brain with spinal cord. CBS News.", "title": "Paralyzed man walks again using implants connecting brain with spinal cord", "url": "https://www.cbsnews.com/news/paralyzed-man-walks-again-using-implants-connecting-brain-with-spinal-cord/", "date": "2023-05-24", "written_by": "independent", "quote": "The brain-spine interface (BSI) has remained stable for a year, allowing Gert-Jan Oskam to stand, walk, climb stairs and traverse complex terrains." }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury.” September 19, 2024. ¶¶ 2, 6–7.", "title": "ONWARD Medical Announces Third Implant of Brain-Computer Interface (BCI) System to Restore Movement after Spinal Cord Injury", "url": "https://www.globenewswire.com/news-release/2024/09/19/2948718/0/en/ONWARD-Medical-Announces-Third-Implant-of-Brain-Computer-Interface-BCI-System-to-Restore-Movement-after-Spinal-Cord-Injury.html", "date": "2024-09-19", "written_by": "makers" }, { "kind": "press release", "citation": "ONWARD Medical. “ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement.” January 22, 2026, 1–3.", "title": "ONWARD Medical Completes Two Additional Brain-Computer Interface Implants Paired with Spinal Cord Stimulation Technology to Restore Thought-Driven Movement", "url": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2", "date": "2026-01-22", "written_by": "makers" }, { "kind": "dataset", "citation": "Henri Lorach. “BSI Dataset and Scripts.” Zenodo, March 2, 2023. https://doi.org/10.5281/zenodo.7680471.", "title": "BSI dataset and scripts", "url": "https://zenodo.org/records/7680471", "date": "2023-03-02", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0001-source-0001", "retained_source_order": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003", "AIBD-0001-source-0004", "AIBD-0001-source-0005", "AIBD-0001-source-0006" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10232367/", "source_refs": [ "AIBD-0001-source-0001" ], "display_name": "Nature", "contribution": "Original clinical results, decoder methods, adverse event, and data availability.", "locator": "Methods; Figures 2–4; Device explantation; Data and code availability." }, { "url": "https://actu.epfl.ch/news/thought-controlled-walking-again-after-spinal-co-4", "source_refs": [ "AIBD-0001-source-0002" ], "display_name": "EPFL", "contribution": "Firsthand institutional account and the participant’s description of daily life.", "locator": "Recovery of neurological functions." }, { "url": "https://www.cbsnews.com/news/paralyzed-man-walks-again-using-implants-connecting-brain-with-spinal-cord/", "source_refs": [ "AIBD-0001-source-0003" ], "display_name": "CBS News", "contribution": "Identifies the participant by name in its account of his news briefing.", "locator": "Opening account and news-briefing quotation." }, { "url": "https://www.globenewswire.com/news-release/2024/09/19/2948718/0/en/ONWARD-Medical-Announces-Third-Implant-of-Brain-Computer-Interface-BCI-System-to-Restore-Movement-after-Spinal-Cord-Injury.html", "source_refs": [ "AIBD-0001-source-0004" ], "display_name": "ONWARD Medical", "contribution": "Original announcement of the September 2024 implantation and its relation to the 2021 work.", "locator": "¶¶ 2, 6–7." }, { "url": "https://ir.onwd.com/static-files/48e1c5b9-e843-4895-ac81-e0e936a841e2", "source_refs": [ "AIBD-0001-source-0005" ], "display_name": "ONWARD Medical", "contribution": "Original January 2026 participant count and investigational status.", "locator": "pp. 1–3." }, { "url": "https://zenodo.org/records/7680471", "source_refs": [ "AIBD-0001-source-0006" ], "display_name": "Zenodo", "contribution": "Original dataset deposit and file inventory.", "locator": "Metadata and file list." } ], "version_relationships": [ { "source_refs": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003" ], "relationship": "The institutional account and news briefing concern the same clinical study, not additional independent trials." } ], "superseded_sources": [ { "url": "https://globalnews.ca/news/9722725/paralyzed-man-walks-brain-implants-netherlands", "reason": "Its 2021 chronology is also established by the original 2024 ONWARD announcement." }, { "url": "https://www.aljazeera.com/news/2023/5/25/paralysed-man-walks-with-device-that-connects-brain-spinal-cord", "reason": "Repeats the same study and participant statements." }, { "url": "https://www.clinicaltrialsarena.com/news/onward-implants-second-patient-with-brain-chip-in-spinal-cord-injury-trial/", "reason": "Replaced by ONWARD’s original announcement." } ] } }, "provenance": { "kind": "source_review", "basis": "Read the original study, institutional account, participant report, company announcements, and repository metadata.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001", "AIBD-0001-source-0002", "AIBD-0001-source-0003", "AIBD-0001-source-0004", "AIBD-0001-source-0005", "AIBD-0001-source-0006" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Nature study provides the clinical evidence. ONWARD’s announcements document later implantations, and Zenodo hosts the data." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Gert-Jan Oskam used the STIMO-BSI interface to stand, walk, and climb stairs after a spinal cord injury.", "account": "Gert-Jan Oskam received the STIMO-BSI brain–spine interface after an incomplete cervical spinal cord injury. The decoder translated signals from his brain into spinal stimulation. He regained control of standing and walking, including stairs and uneven ground. After 40 rehabilitation sessions, he could also walk more than 10 meters with crutches while the stimulation was off.\n\nThe researchers reported stable control for over a year, including seven months of home use. An infection required removal of one cortical implant 167 days after implantation. Rehabilitation continued after treatment, and the implant was replaced in March 2023. The report concerns one participant." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "Stimulation followed movement intentions within preset amplitude limits. The participant could start activities and adjust the permitted range." }, "provenance": { "kind": "source_review", "basis": "Extended Data Figure 1; Independent use of the BSI.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Stimulation followed movement intentions within preset amplitude limits. The participant could start activities and adjust the permitted range." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The decoder estimated intended leg movements and adjusted spinal stimulation." }, "provenance": { "kind": "source_review", "basis": "Extended Data Figure 1.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The decoder estimated intended leg movements and adjusted spinal stimulation." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "WIMAGINE implants recorded brain activity. A portable computer controlled an ACTIVA RC pulse generator and a Specify 5-6-5 spinal lead." }, "provenance": { "kind": "source_review", "basis": "Digital bridge from brain to spinal cord; Extended Data Figure 1.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "WIMAGINE implants recorded brain activity. A portable computer controlled an ACTIVA RC pulse generator and a Specify 5-6-5 spinal lead." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Cortical signals entered the decoder. Its predictions set the timing and strength of spinal stimulation." }, "provenance": { "kind": "source_review", "basis": "Extended Data Figure 1.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Cortical signals entered the decoder. Its predictions set the timing and strength of spinal stimulation." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "REW-MSLM, a decoder that combines a hidden Markov model with multilinear regressions." }, "provenance": { "kind": "source_review", "basis": "Methods: Decoding motor intentions with the brain–spine interface.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "REW-MSLM, a decoder that combines a hidden Markov model with multilinear regressions." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Methods: Decoding motor intentions; Online decoder training.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The Nature methods identify the decoder and its calibration procedure but no release identifier.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The decoder was calibrated for the participant. The paper names no software release." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "STIMO-BSI brain–spine interface" }, "provenance": { "kind": "source_review", "basis": "Title and Methods.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "STIMO-BSI brain–spine interface" } }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "NeuroRestore (EPFL/CHUV/UNIL) with CEA-Clinatec and ONWARD Medical" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A brain–spine interface restored control of walking after paralysis", "headline": "A brain–spine interface restored control of walking after paralysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8873303244c63de171fbafa7edcbbdab0d046d1d708a96d4a635b291d144f0e5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Researchers calibrated the decoder, followed by 40 rehabilitation sessions and continued use at home." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design and participant.", "record_fields": [], "source_refs": [ "AIBD-0001-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers calibrated the decoder, followed by 40 rehabilitation sessions and continued use at home." } } }, "summary": { "total": 91, "addressed": 91, "known": 63, "reviewed": 44, "record_mapped": 20, "not_assessed": 27, "complete": false, "by_state": { "value_present": 63, "not_reported": 1, "unresolved": 0, "not_assessed": 27, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0083", "title": "Brazil's TCU captures R$426 million through its ALICE tender-analysis robot in 2021", "summary": "TCU says its ALICE tender-analysis robot captured R$426m in 2021 (R$194m in 2020); specific cases reported only via press", "date_observed": "2021-01-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Tribunal de Contas da União (TCU) operates ALICE, a text-mining robot. It reads federal tender notices and electronic-auction records daily and sends auditors a list of possible irregularities. Trade press in 2017 and 2018 expanded the name as “Análise de Licitações e Editais”. The TCU's own July 2020 release calls it the “Sistema de Análise de Licitações e Contratos (Alice)”. In its 4 March 2022 statement on 2021 control benefits, the TCU reported the value captured through Alice. It was R$426 million in 2021 against R$194 million in 2020. Only the year is given, so 1 January 2021 is used. Trade press in September 2017 quoted TCU auditor Valéria Nakano that Alice found two DNIT notices worth R$39 million. They were for maintaining BR-153 stretches already under concession, blocked by an acórdão within two months. That acórdão could not be obtained, so the example is unverified.", "category": "general benefit", "unexpected": false, "purpose": "Daily automated screening of federal procurement notices to direct external-control auditors to likely irregularities", "system": "ALICE, expanded as 'Análise de Licitações e Editais' in 2017 and 2018 press reports and named 'Sistema de Análise de Licitações e Contratos (Alice)' in the TCU's July 2020 release, with companion tools SOFIA and MONICA; evolved into ALICE 360 by 2026", "model_version": null, "developer": "Tribunal de Contas da União (TCU), in-house", "deployer": "Tribunal de Contas da União (TCU); also shared with DNIT and the Ministry of Infrastructure under a 2020 agreement", "location": "Brasília, Brazil", "domain": "Public administration: external audit and procurement control", "segment": "Supreme audit institution", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate program figure with no discrete attributable event." }, { "group": "organizational", "depth": null, "reason": "The R$426 million is an annual total of control benefits credited to the Alice system, not a single verified event." }, { "group": "societal", "depth": null, "reason": "Aggregate. The TCU's own benefit-measurement methodology, not an independent evaluation." } ], "ai_role": { "status": "unassessed", "statement": "The TCU attributes the 2021 figure to control actions supported by Alice under its benefit-measurement method. It says “o segundo de fato reflete o benefício calculado, que resultou da ação de controle e foi medido”. No independent evaluation or counterfactual was found. The 2017 DNIT/BR-153 example rests on a trade-press interview with a TCU auditor. The TCU acórdão was not available. Developer and deployer are the same public body." }, "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas da União (2022). Atuação do TCU gera recorde de benefícios financeiros em 2021. TCU press office, 4 Mar 2022.", "title": "Atuação do TCU gera recorde de benefícios financeiros em 2021", "url": "https://portal.tcu.gov.br/imprensa/noticias/atuacao-do-tcu-gera-recorde-de-beneficios-financeiros-em-2021", "date": "2022-03-04", "written_by": "makers", "quote": "No sistema Alice, uma das ferramentas de Tecnologia da Informação do TCU, o valor captado foi de R$ 426 milhões em 2021" }, { "kind": "press release", "citation": "Tribunal de Contas da União (2020). TCU, Ministério da Infraestrutura e DNIT firmam acordo para aperfeiçoar fiscalização e prevenir fraudes em licitações. TCU press office, 10 Jul 2020.", "title": "TCU, Ministério da Infraestrutura e DNIT firmam acordo", "url": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "date": "2020-07-10", "written_by": "makers", "quote": "Pelo acordo, o TCU viabilizará ao MInfra e ao DNIT acesso remoto ao Sistema de Análise de Orçamentos (SAO) e ao Sistema de Análise de Licitações e Contratos (Alice)." }, { "kind": "press release", "citation": "Tribunal de Contas da União (2024). Uso de inteligência artificial aprimora processos internos no Tribunal de Contas da União. TCU press office, 22 Feb 2024.", "title": "Uso de inteligência artificial aprimora processos internos no TCU", "url": "https://portal.tcu.gov.br/imprensa/noticias/uso-de-inteligencia-artificial-aprimora-processos-internos-no-tcu.htm", "date": "2024-02-22", "written_by": "makers", "quote": "Realiza análise de editais e atas de pregão para identificar riscos em licitações." }, { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais, 27 Sep 2017 (quoting TCU auditor Valéria Nakano).", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão" }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 20 Mar 2018, republished by Ministério Público de Contas do Espírito Santo.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://www.mpc.es.gov.br/2018/03/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes/", "date": "2018-03-20", "written_by": "independent", "quote": "O maior ganho que a gente tem é que os órgãos retiram, anulam ou cancelam" }, { "kind": "other", "citation": "Zênite (2026). TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA (summary of TCU Acórdão 1.145/2026-Plenário, rel. Min. Jorge Oliveira, 6 May 2026). Blog da Zênite, 14 May 2026.", "title": "TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA", "url": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "date": "2026-05-14", "written_by": "independent", "quote": "o projeto evoluiu para o uso intensivo de IA para capturar distorções complexas" } ], "replication": { "produced_by": [ "Daily text-mining of the Diário Oficial and Comprasnet notices by Alice with e-mailed alerts to auditors", "Low-cost follow-up by auditors (phone call, e-mail, ofício) or formal acórdão when needed", "Agencies withdrawing, annulling or redoing flawed notices after contact" ], "must_hold": [ "Structured publication of notices on federal systems", "Auditor capacity to act on the daily list", "A benefit-measurement method that records actual, not potential, benefits" ], "echoes": [ { "date": "2024-12-30", "setting": "The CGU's ALICE (Analisador de Licitações, Contratos e Editais), which the CGU says it developed: R$257.25 million saved in concluded 2024 audits (CGU, 30 December 2024)", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG version of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "model_version": null, "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" }, { "date": "2026-05-06", "setting": "TCU Acórdão 1.145/2026 notes ALICE 360's move to intensive AI use; no outcome figures given (Zênite summary)", "model_version": null, "outcome": "unknown", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "461", "title": "IRS Audited Black Taxpayers More Frequently Reportedly Due to Algorithm", "url": "https://incidentdatabase.ai/cite/461", "severity": null, "group": "societal", "basis": "IRS audit-selection algorithm, an audit body's targeting tool like TCU's ALICE, skewed audits toward Black taxpayers, harming the taxpayers the audit function serves." }, "headline": "TCU's ALICE tender-analysis robot captures R$426m in 2021", "metric": "captured R$426m in 2021 (R$194m in 2020)", "comparator": null, "later": { "status": "persisted", "date": "2026-05-06", "note": "A TCU plenary ruling of 6 May 2026 (Acórdão 1.145/2026) records that the tool, now called Alice 360, has moved to intensive use of AI, with LLM-based query screens; no outcome figures are given.", "quote": "As evoluções incrementais já implementadas no Alice 360 incluem a transição das telas de consulta para sistemas baseados em Modelos de Linguagem de Grande Escala (LLM).", "url": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" }, "value": null, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 461 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/461", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “CGU's adaptation of ALICE” with the CGU's own statement that it developed its ALICE (Analisador de Licitações, Contratos e Editais); stated that December 2022 is when TCE-MG published the result of its audit of August 2022 tenders; and gave both expansions of the TCU tool's name because the TCU's July 2020 release calls it “Sistema de Análise de Licitações e Contratos (Alice)” while the 2017 and 2018 press pieces expand it as “Análise de Licitações e Editais”.", "source": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, one other independent source and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0083", "catalog_version": "1.0.0", "source_fingerprint": "4201a828e804f23a9a8050043534e32c43730b904be02d130fecad0f2240b181", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0083-source-0001", "AIBD-0083-source-0002", "AIBD-0083-source-0003", "AIBD-0083-source-0004", "AIBD-0083-source-0005", "AIBD-0083-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tribunal de Contas da União (TCU), in-house", "deployer": "Tribunal de Contas da União (TCU); also shared with DNIT and the Ministry of Infrastructure under a 2020 agreement" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The TCU attributes the 2021 figure to control actions supported by Alice under its benefit-measurement method. It says “o segundo de fato reflete o benefício calculado, que resultou da ação de controle e foi medido”. No independent evaluation or counterfactual was found. The 2017 DNIT/BR-153 example rests on a trade-press interview with a TCU auditor. The TCU acórdão was not available. Developer and deployer are the same public body." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, one other independent source and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate program figure with no discrete attributable event." }, { "group": "organizational", "reason": "The R$426 million is an annual total of control benefits credited to the Alice system, not a single verified event." }, { "group": "societal", "reason": "Aggregate. The TCU's own benefit-measurement methodology, not an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate program figure with no discrete attributable event." }, { "group": "organizational", "reason": "The R$426 million is an annual total of control benefits credited to the Alice system, not a single verified event." }, { "group": "societal", "reason": "Aggregate. The TCU's own benefit-measurement methodology, not an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "IRS audit-selection algorithm, an audit body's targeting tool like TCU's ALICE, skewed audits toward Black taxpayers, harming the taxpayers the audit function serves.", "links": [ { "database": "AI Incident Database", "identifier": "461", "title": "IRS Audited Black Taxpayers More Frequently Reportedly Due to Algorithm", "url": "https://incidentdatabase.ai/cite/461", "group": "societal", "basis": "IRS audit-selection algorithm, an audit body's targeting tool like TCU's ALICE, skewed audits toward Black taxpayers, harming the taxpayers the audit function serves.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "captured R$426m in 2021 (R$194m in 2020)", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "461", "title": "IRS Audited Black Taxpayers More Frequently Reportedly Due to Algorithm", "url": "https://incidentdatabase.ai/cite/461", "group": "societal", "basis": "IRS audit-selection algorithm, an audit body's targeting tool like TCU's ALICE, skewed audits toward Black taxpayers, harming the taxpayers the audit function serves." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-05-06", "note": "A TCU plenary ruling of 6 May 2026 (Acórdão 1.145/2026) records that the tool, now called Alice 360, has moved to intensive use of AI, with LLM-based query screens; no outcome figures are given.", "quote": "As evoluções incrementais já implementadas no Alice 360 incluem a transição das telas de consulta para sistemas baseados em Modelos de Linguagem de Grande Escala (LLM).", "url": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0083" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tribunal de Contas da União (TCU) operates ALICE, a text-mining robot. It reads federal tender notices and electronic-auction records daily and sends auditors a list of possible irregularities. Trade press in 2017 and 2018 expanded the name as “Análise de Licitações e Editais”. The TCU's own July 2020 release calls it the “Sistema de Análise de Licitações e Contratos (Alice)”. In its 4 March 2022 statement on 2021 control benefits, the TCU reported the value captured through Alice. It was R$426 million in 2021 against R$194 million in 2020. Only the year is given, so 1 January 2021 is used. Trade press in September 2017 quoted TCU auditor Valéria Nakano that Alice found two DNIT notices worth R$39 million. They were for maintaining BR-153 stretches already under concession, blocked by an acórdão within two months. That acórdão could not be obtained, so the example is unverified.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate program figure with no discrete attributable event." }, { "group": "organizational", "reason": "The R$426 million is an annual total of control benefits credited to the Alice system, not a single verified event." }, { "group": "societal", "reason": "Aggregate. The TCU's own benefit-measurement methodology, not an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Daily automated screening of federal procurement notices to direct external-control auditors to likely irregularities" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Brasília, Brazil", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Daily automated screening of federal procurement notices to direct external-control auditors to likely irregularities" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-01-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 461 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/461", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “CGU's adaptation of ALICE” with the CGU's own statement that it developed its ALICE (Analisador de Licitações, Contratos e Editais); stated that December 2022 is when TCE-MG published the result of its audit of August 2022 tenders; and gave both expansions of the TCU tool's name because the TCU's July 2020 release calls it “Sistema de Análise de Licitações e Contratos (Alice)” while the 2017 and 2018 press pieces expand it as “Análise de Licitações e Editais”.", "source": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Daily text-mining of the Diário Oficial and Comprasnet notices by Alice with e-mailed alerts to auditors", "Low-cost follow-up by auditors (phone call, e-mail, ofício) or formal acórdão when needed", "Agencies withdrawing, annulling or redoing flawed notices after contact" ], "must_hold": [ "Structured publication of notices on federal systems", "Auditor capacity to act on the daily list", "A benefit-measurement method that records actual, not potential, benefits" ], "echoes": [ { "date": "2024-12-30", "setting": "The CGU's ALICE (Analisador de Licitações, Contratos e Editais), which the CGU says it developed: R$257.25 million saved in concluded 2024 audits (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG version of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" }, { "date": "2026-05-06", "setting": "TCU Acórdão 1.145/2026 notes ALICE 360's move to intensive AI use; no outcome figures given (Zênite summary)", "outcome": "unknown", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Daily text-mining of the Diário Oficial and Comprasnet notices by Alice with e-mailed alerts to auditors", "Low-cost follow-up by auditors (phone call, e-mail, ofício) or formal acórdão when needed", "Agencies withdrawing, annulling or redoing flawed notices after contact" ], "must_hold": [ "Structured publication of notices on federal systems", "Auditor capacity to act on the daily list", "A benefit-measurement method that records actual, not potential, benefits" ], "echoes": [ { "date": "2024-12-30", "setting": "The CGU's ALICE (Analisador de Licitações, Contratos e Editais), which the CGU says it developed: R$257.25 million saved in concluded 2024 audits (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG version of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" }, { "date": "2026-05-06", "setting": "TCU Acórdão 1.145/2026 notes ALICE 360's move to intensive AI use; no outcome figures given (Zênite summary)", "outcome": "unknown", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 461 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/461", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “CGU's adaptation of ALICE” with the CGU's own statement that it developed its ALICE (Analisador de Licitações, Contratos e Editais); stated that December 2022 is when TCE-MG published the result of its audit of August 2022 tenders; and gave both expansions of the TCU tool's name because the TCU's July 2020 release calls it “Sistema de Análise de Licitações e Contratos (Alice)” while the 2017 and 2018 press pieces expand it as “Análise de Licitações e Editais”.", "source": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; 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external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas da União (2022). Atuação do TCU gera recorde de benefícios financeiros em 2021. TCU press office, 4 Mar 2022.", "title": "Atuação do TCU gera recorde de benefícios financeiros em 2021", "url": "https://portal.tcu.gov.br/imprensa/noticias/atuacao-do-tcu-gera-recorde-de-beneficios-financeiros-em-2021", "date": "2022-03-04", "written_by": "makers", "quote": "No sistema Alice, uma das ferramentas de Tecnologia da Informação do TCU, o valor captado foi de R$ 426 milhões em 2021" }, { "kind": "press release", "citation": "Tribunal de Contas da União (2020). TCU, Ministério da Infraestrutura e DNIT firmam acordo para aperfeiçoar fiscalização e prevenir fraudes em licitações. TCU press office, 10 Jul 2020.", "title": "TCU, Ministério da Infraestrutura e DNIT firmam acordo", "url": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "date": "2020-07-10", "written_by": "makers", "quote": "Pelo acordo, o TCU viabilizará ao MInfra e ao DNIT acesso remoto ao Sistema de Análise de Orçamentos (SAO) e ao Sistema de Análise de Licitações e Contratos (Alice)." }, { "kind": "press release", "citation": "Tribunal de Contas da União (2024). Uso de inteligência artificial aprimora processos internos no Tribunal de Contas da União. TCU press office, 22 Feb 2024.", "title": "Uso de inteligência artificial aprimora processos internos no TCU", "url": "https://portal.tcu.gov.br/imprensa/noticias/uso-de-inteligencia-artificial-aprimora-processos-internos-no-tcu.htm", "date": "2024-02-22", "written_by": "makers", "quote": "Realiza análise de editais e atas de pregão para identificar riscos em licitações." }, { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais, 27 Sep 2017 (quoting TCU auditor Valéria Nakano).", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão" }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 20 Mar 2018, republished by Ministério Público de Contas do Espírito Santo.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://www.mpc.es.gov.br/2018/03/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes/", "date": "2018-03-20", "written_by": "independent", "quote": "O maior ganho que a gente tem é que os órgãos retiram, anulam ou cancelam" }, { "kind": "other", "citation": "Zênite (2026). TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA (summary of TCU Acórdão 1.145/2026-Plenário, rel. Min. Jorge Oliveira, 6 May 2026). Blog da Zênite, 14 May 2026.", "title": "TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA", "url": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "date": "2026-05-14", "written_by": "independent", "quote": "o projeto evoluiu para o uso intensivo de IA para capturar distorções complexas" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0083-source-0001", "AIBD-0083-source-0002", "AIBD-0083-source-0003", "AIBD-0083-source-0004", "AIBD-0083-source-0005", "AIBD-0083-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas da União (2022). Atuação do TCU gera recorde de benefícios financeiros em 2021. TCU press office, 4 Mar 2022.", "title": "Atuação do TCU gera recorde de benefícios financeiros em 2021", "url": "https://portal.tcu.gov.br/imprensa/noticias/atuacao-do-tcu-gera-recorde-de-beneficios-financeiros-em-2021", "date": "2022-03-04", "written_by": "makers", "quote": "No sistema Alice, uma das ferramentas de Tecnologia da Informação do TCU, o valor captado foi de R$ 426 milhões em 2021" }, { "kind": "press release", "citation": "Tribunal de Contas da União (2020). TCU, Ministério da Infraestrutura e DNIT firmam acordo para aperfeiçoar fiscalização e prevenir fraudes em licitações. TCU press office, 10 Jul 2020.", "title": "TCU, Ministério da Infraestrutura e DNIT firmam acordo", "url": "https://portal.tcu.gov.br/imprensa/noticias/tcu-ministerio-da-infraestrutura-e-dnit-firmam-acordo-para-aperfeicoar-fiscalizacao-e-prevenir-fraudes-em-licitacoes", "date": "2020-07-10", "written_by": "makers", "quote": "Pelo acordo, o TCU viabilizará ao MInfra e ao DNIT acesso remoto ao Sistema de Análise de Orçamentos (SAO) e ao Sistema de Análise de Licitações e Contratos (Alice)." }, { "kind": "press release", "citation": "Tribunal de Contas da União (2024). Uso de inteligência artificial aprimora processos internos no Tribunal de Contas da União. TCU press office, 22 Feb 2024.", "title": "Uso de inteligência artificial aprimora processos internos no TCU", "url": "https://portal.tcu.gov.br/imprensa/noticias/uso-de-inteligencia-artificial-aprimora-processos-internos-no-tcu.htm", "date": "2024-02-22", "written_by": "makers", "quote": "Realiza análise de editais e atas de pregão para identificar riscos em licitações." }, { "kind": "news report", "citation": "Inforchannel (2017). TCU cria robô para varredura diária de irregularidades em editais, 27 Sep 2017 (quoting TCU auditor Valéria Nakano).", "title": "TCU cria robô para varredura diária de irregularidades em editais", "url": "https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/", "date": "2017-09-27", "written_by": "independent", "quote": "o Tribunal de Contas, via Alice, descobriu que o DNIT estdual publicou dois editais, de R$ 39 milhões, para manutenção da BR 153, mas em trechos que estão sob concessão" }, { "kind": "news report", "citation": "Gomes, H. S. (2018). Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações. G1, 20 Mar 2018, republished by Ministério Público de Contas do Espírito Santo.", "title": "Como as robôs Alice, Sofia e Monica ajudam o TCU a caçar irregularidades em licitações", "url": "https://www.mpc.es.gov.br/2018/03/como-as-robos-alice-sofia-e-monica-ajudam-o-tcu-a-cacar-irregularidades-em-licitacoes/", "date": "2018-03-20", "written_by": "independent", "quote": "O maior ganho que a gente tem é que os órgãos retiram, anulam ou cancelam" }, { "kind": "other", "citation": "Zênite (2026). TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA (summary of TCU Acórdão 1.145/2026-Plenário, rel. Min. Jorge Oliveira, 6 May 2026). Blog da Zênite, 14 May 2026.", "title": "TCU aponta irregularidades em contratações públicas e destaca avanço do Alice 360 com IA", "url": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/", "date": "2026-05-14", "written_by": "independent", "quote": "o projeto evoluiu para o uso intensivo de IA para capturar distorções complexas" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "TCU says its ALICE tender-analysis robot captured R$426m in 2021 (R$194m in 2020); specific cases reported only via press", "account": "The Tribunal de Contas da União (TCU) operates ALICE, a text-mining robot. It reads federal tender notices and electronic-auction records daily and sends auditors a list of possible irregularities. Trade press in 2017 and 2018 expanded the name as “Análise de Licitações e Editais”. The TCU's own July 2020 release calls it the “Sistema de Análise de Licitações e Contratos (Alice)”. In its 4 March 2022 statement on 2021 control benefits, the TCU reported the value captured through Alice. It was R$426 million in 2021 against R$194 million in 2020. Only the year is given, so 1 January 2021 is used. Trade press in September 2017 quoted TCU auditor Valéria Nakano that Alice found two DNIT notices worth R$39 million. They were for maintaining BR-153 stretches already under concession, blocked by an acórdão within two months. That acórdão could not be obtained, so the example is unverified." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALICE, expanded as 'Análise de Licitações e Editais' in 2017 and 2018 press reports and named 'Sistema de Análise de Licitações e Contratos (Alice)' in the TCU's July 2020 release, with companion tools SOFIA and MONICA; evolved into ALICE 360 by 2026" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tribunal de Contas da União (TCU), in-house" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Brazil's TCU captures R$426 million through its ALICE tender-analysis robot in 2021", "headline": "TCU's ALICE tender-analysis robot captures R$426m in 2021" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4201a828e804f23a9a8050043534e32c43730b904be02d130fecad0f2240b181" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tribunal de Contas da União (TCU) operates ALICE, a text-mining robot. It reads federal tender notices and electronic-auction records daily and sends auditors a list of possible irregularities. Trade press in 2017 and 2018 expanded the name as “Análise de Licitações e Editais”. The TCU's own July 2020 release calls it the “Sistema de Análise de Licitações e Contratos (Alice)”. In its 4 March 2022 statement on 2021 control benefits, the TCU reported the value captured through Alice. It was R$426 million in 2021 against R$194 million in 2020. Only the year is given, so 1 January 2021 is used. Trade press in September 2017 quoted TCU auditor Valéria Nakano that Alice found two DNIT notices worth R$39 million. They were for maintaining BR-153 stretches already under concession, blocked by an acórdão within two months. That acórdão could not be obtained, so the example is unverified.", "replication": { "produced_by": [ "Daily text-mining of the Diário Oficial and Comprasnet notices by Alice with e-mailed alerts to auditors", "Low-cost follow-up by auditors (phone call, e-mail, ofício) or formal acórdão when needed", "Agencies withdrawing, annulling or redoing flawed notices after contact" ], "must_hold": [ "Structured publication of notices on federal systems", "Auditor capacity to act on the daily list", "A benefit-measurement method that records actual, not potential, benefits" ], "echoes": [ { "date": "2024-12-30", "setting": "The CGU's ALICE (Analisador de Licitações, Contratos e Editais), which the CGU says it developed: R$257.25 million saved in concluded 2024 audits (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG version of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" }, { "date": "2026-05-06", "setting": "TCU Acórdão 1.145/2026 notes ALICE 360's move to intensive AI use; no outcome figures given (Zênite summary)", "outcome": "unknown", "source": "https://zenite.blog.br/tcu-aponta-irregularidades-em-contratacoes-publicas-e-destaca-avanco-do-alice-360-com-ia/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0094", "title": "Nigeria's Rapid Response Register used machine-learning poverty maps to select 1,163 urban wards for COVID-19 cash transfers", "summary": "ML poverty maps chose 1,163 poorest urban wards for Nigeria's COVID-19 cash register; 49,000 beneficiary households as of 15 October 2021", "date_observed": "2021-01-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Lacking an urban social registry, Nigeria's National Social Safety Nets Coordinating Office (NASSCO) built the Rapid Response Register for a government-funded COVID-19 cash transfer. Ward-level poverty maps came from machine learning (ML) algorithms applied to satellite imagery with household-survey labels, by Berkeley and Columbia researchers with World Bank economists. The maps selected 1,163 of the poorest urban wards, population over 20 million. Residents self-registered by USSD after SMS blasts (first wave June 2021), then in-person verification. Human Rights Watch records the program began in January 2021. The PNAS authors state disbursement began mid-January 2021 (day not given; first day of month used). World Bank monitoring reports 49,000 beneficiary households of the government's COVID-CT as of 15 October 2021. It reports over 1.75 million registrations by November 2021, against a government target of one million households.", "category": "benefit created", "unexpected": false, "purpose": "Geographically target a COVID-19 urban cash transfer to the poorest wards where no social registry existed.", "system": "Ward-level poverty maps from supervised machine learning (deep learning) on satellite imagery, used for geographic targeting in the Rapid Response Register", "model_version": null, "developer": "Joshua Blumenstock (UC Berkeley) and Isabella Smythe (Columbia University), using wealth estimates by Chi et al. (2021), with World Bank economists Jonathan Lain and Tara Vishwanath, for the Government of Nigeria", "deployer": "National Social Safety Nets Coordinating Office (NASSCO), Federal Government of Nigeria", "location": "Urban wards across Nigeria", "domain": "Social protection and cash transfers", "segment": "Government social assistance", "benefit_type": "Increased Scalability", "taxonomy_note": "The good for households is cash, and the type names the register's reach into urban wards it could not otherwise cover.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Households in selected wards were beneficiaries of the government's COVID-CT. The PNAS authors say disbursement began mid-January 2021. The World Bank ISR records 49,000 beneficiary households as of 15 October 2021 without saying how many had been paid." }, { "group": "organizational", "depth": 2, "reason": "NASSCO stood up an urban registry within months through USSD self-registration guided by the ML poverty map. Over 1.75 million registrations succeeded (PAD, Nov 2021)." }, { "group": "societal", "depth": 3, "reason": "Material to many: 1,163 wards with over 20 million residents made eligible. PNAS simulation finds the ML maps would cut inclusion errors by 61.7% versus the survey-based benchmark." } ], "ai_role": { "status": "assessed", "statement": "Decisive at the geographic stage: the ML poverty map alone chose which 1,163 wards were eligible. Individual inclusion depended on USSD self-registration and in-person verification, not AI. Payment and registration counts come from World Bank operational documents, not from the map developers. The PNAS paper and World Bank blog are co-authored by the developers." }, "evidence": [ { "kind": "report", "citation": "World Bank (2021). Project Appraisal Document: Nigeria National Social Safety Net Program - Scale Up (P176935).", "title": "Nigeria - National Social Safety Net Program - Scale Up - Project", "url": "https://documents.worldbank.org/curated/en/717321706545772846/pdf/Nigeria-National-Social-Safety-Net-Program-Scale-Up-Project.pdf", "date": "2021-11-23", "written_by": "makers", "quote": "1,163 of the poorest urban wards with a total population of over 20 million people were selected based on the ward-level poverty maps produced by applying cutting-edge machine learning algorithms" }, { "kind": "report", "citation": "World Bank (2025). Implementation Status and Results Report, National Social Safety Net Program-Scale Up (P176935), Sequence 6.", "title": "Disclosable Version of the ISR - National Social Safety Net Program-Scale Up - P176935 - Sequence No: 6", "url": "https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf", "date": "2025-01-29", "written_by": "makers", "quote": "Baseline numbers based on the 49,000 beneficiary HHs of the COVID-CT implemented by the government as of October 15, 2021." }, { "kind": "peer-reviewed study", "citation": "Smythe, I. S., Blumenstock, J. E. (2022). Geographic microtargeting of social assistance with high-resolution poverty maps. PNAS 119(32).", "title": "Geographic microtargeting of social assistance with high-resolution poverty maps", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/", "date": "2022-08-01", "written_by": "makers", "quote": "the government elected to use our high-resolution poverty maps to target the COVID-19 Rapid Response Registration (RRR) Cash Transfer Project" }, { "kind": "report", "citation": "Human Rights Watch (2021). Between Hunger and the Virus: The Impact of the Covid-19 Pandemic on People Living in Poverty in Lagos, Nigeria.", "title": "Between Hunger and the Virus", "url": "https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living", "date": "2021-07-28", "written_by": "independent", "quote": "a new 'rapid response' cash transfer program, which began in January 2021 and is intended to reach 1 million people nationwide, primarily in urban poor communities" }, { "kind": "press release", "citation": "Blumenstock, J., Lain, J., Smythe, I., Vishwanath, T. (2021). Using Big Data and machine learning to locate the poor in Nigeria. World Bank Data Blog.", "title": "Using Big Data and machine learning to locate the poor in Nigeria", "url": "https://blogs.worldbank.org/en/opendata/using-big-data-and-machine-learning-locate-poor-nigeria", "date": "2021-02-22", "written_by": "makers", "quote": "which is being guided by the mapping exercise described below" } ], "replication": { "produced_by": [ "Deep-learning poverty map trained on geo-located household surveys", "Government decision to adopt the ward ranking for eligibility", "SMS blasts and USSD self-registration", "In-person verification, de-duplication and payment onboarding" ], "must_hold": [ "Ground-truth survey data for training labels", "Ward boundaries compatible with map resolution", "Mobile-phone access in target wards", "Government funding for transfers and identity verification capacity" ], "echoes": [ { "date": "2020-11-02", "setting": "Togo Novissi rural expansion using satellite poverty maps and phone-data targeting", "model_version": null, "outcome": "recurred", "source": "Aiken et al. (2022) Nature, https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/ (expansion 'beginning in November 2020'); the 2 November 2020 date is from World Bank and Government of Togo (2023), Novissi Togo case study, https://documents.worldbank.org/curated/en/099751009222330502/pdf/IDU0e83f857301ff1047bf082710a8d21ddf42c3.pdf" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "546", "title": "Algorithm to Distribute Social Welfare Reported for Oversimplifying Economic Vulnerability", "url": "https://incidentdatabase.ai/cite/546", "severity": null, "group": "personal", "basis": "World Bank-developed poverty-targeting algorithm for cash transfers (Takaful) oversimplified vulnerability and excluded poor Jordanians; Nigeria's register used World Bank poverty maps." }, "headline": "ML poverty maps select 1,163 wards for Nigeria's COVID-19 cash", "metric": "49,000 beneficiary households of the government's COVID-CT as of 15 October 2021", "comparator": { "against": "survey-based poverty map benchmark (DHS/NLSS data)", "before": "0.79 precision at the ward level (survey benchmark)", "after": "0.92 precision at the ward level (ML-based maps)", "basis": "measured", "quote": "In targeting the poor, the ML-based approach increases precision relative to the benchmark from 0.82 to 0.86 at the LGA level and from 0.79 to 0.92 at the ward level. In targeting the extreme poor, the increase is from 0.30 to 0.39 at the LGA level and from 0.31 to 0.41 at the ward level.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/" }, "later": { "status": "scaled", "date": "2025-01-29", "note": "The World Bank's 2021 scale-up project adopted the same machine-learning poverty maps to choose expansion wards for the RRR, and its January 2025 status report counts over 5 million households supported by the direct benefit transfer program after delays and a switch to biometric-verified payments, without breaking out the RRR-targeted share.", "quote": "The direct benefit transfer program to date has supported over 5 million households. Following the CBN circular of December 2023, mandating the use of NIN or BVN to operate an account after March 2024, and the recommendation from the presidential panel, all transfers since March 2024 are made to beneficiaries who’s NIN or BVN have been verified.", "url": "https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf" }, "value": null, "developer_country": null, "deployer_country": "Nigeria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 546 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Placed Isabella Smythe at Columbia University and credited Chi et al.“s wealth estimates and the two named World Bank economists as the PNAS paper and World Bank blog state them, removed the unsupported word 'paid” from the 49,000-household figure because the ISR says only “beneficiary HHs” as of 15 October 2021, and added the World Bank Novissi case study as the source of the 2 November 2020 echo date that the Nature paper gives only as November 2020.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/; https://blogs.worldbank.org/en/opendata/using-big-data-and-machine-learning-locate-poor-nigeria; https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/; https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Scalability under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://search.worldbank.org/api/v2/wds?qterm=NASSCO%20National%20Social%20Safety%20Nets%20Coordinating%20Office&format=json&rows=5", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, the makers' peer-reviewed study, two reports from the makers and the makers' press release. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0094", "catalog_version": "1.0.0", "source_fingerprint": "2c38cee688ad632630951f3abfc422b1428ba2fa70d62d9811d8d9d82e0d75d9", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0094-source-0001", "AIBD-0094-source-0002", "AIBD-0094-source-0003", "AIBD-0094-source-0004", "AIBD-0094-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Joshua Blumenstock (UC Berkeley) and Isabella Smythe (Columbia University), using wealth estimates by Chi et al. (2021), with World Bank economists Jonathan Lain and Tara Vishwanath, for the Government of Nigeria", "deployer": "National Social Safety Nets Coordinating Office (NASSCO), Federal Government of Nigeria" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Decisive at the geographic stage: the ML poverty map alone chose which 1,163 wards were eligible. Individual inclusion depended on USSD self-registration and in-person verification, not AI. Payment and registration counts come from World Bank operational documents, not from the map developers. The PNAS paper and World Bank blog are co-authored by the developers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Decisive at the geographic stage: the ML poverty map alone chose which 1,163 wards were eligible. Individual inclusion depended on USSD self-registration and in-person verification, not AI. Payment and registration counts come from World Bank operational documents, not from the map developers. The PNAS paper and World Bank blog are co-authored by the developers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Households in selected wards were beneficiaries of the government's COVID-CT. The PNAS authors say disbursement began mid-January 2021. The World Bank ISR records 49,000 beneficiary households as of 15 October 2021 without saying how many had been paid." }, { "group": "organizational", "depth": 2, "reason": "NASSCO stood up an urban registry within months through USSD self-registration guided by the ML poverty map. Over 1.75 million registrations succeeded (PAD, Nov 2021)." }, { "group": "societal", "depth": 3, "reason": "Material to many: 1,163 wards with over 20 million residents made eligible. PNAS simulation finds the ML maps would cut inclusion errors by 61.7% versus the survey-based benchmark." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report, the makers' peer-reviewed study, two reports from the makers and the makers' press release. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Households in selected wards were beneficiaries of the government's COVID-CT. The PNAS authors say disbursement began mid-January 2021. The World Bank ISR records 49,000 beneficiary households as of 15 October 2021 without saying how many had been paid." }, { "group": "organizational", "depth": 2, "reason": "NASSCO stood up an urban registry within months through USSD self-registration guided by the ML poverty map. Over 1.75 million registrations succeeded (PAD, Nov 2021)." }, { "group": "societal", "depth": 3, "reason": "Material to many: 1,163 wards with over 20 million residents made eligible. PNAS simulation finds the ML maps would cut inclusion errors by 61.7% versus the survey-based benchmark." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Households in selected wards were beneficiaries of the government's COVID-CT. The PNAS authors say disbursement began mid-January 2021. The World Bank ISR records 49,000 beneficiary households as of 15 October 2021 without saying how many had been paid." }, { "group": "organizational", "depth": 2, "reason": "NASSCO stood up an urban registry within months through USSD self-registration guided by the ML poverty map. Over 1.75 million registrations succeeded (PAD, Nov 2021)." }, { "group": "societal", "depth": 3, "reason": "Material to many: 1,163 wards with over 20 million residents made eligible. 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Project Appraisal Document: Nigeria National Social Safety Net Program - Scale Up (P176935).", "title": "Nigeria - National Social Safety Net Program - Scale Up - Project", "url": "https://documents.worldbank.org/curated/en/717321706545772846/pdf/Nigeria-National-Social-Safety-Net-Program-Scale-Up-Project.pdf", "date": "2021-11-23", "written_by": "makers", "quote": "1,163 of the poorest urban wards with a total population of over 20 million people were selected based on the ward-level poverty maps produced by applying cutting-edge machine learning algorithms" }, { "kind": "report", "citation": "World Bank (2025). Implementation Status and Results Report, National Social Safety Net Program-Scale Up (P176935), Sequence 6.", "title": "Disclosable Version of the ISR - National Social Safety Net Program-Scale Up - P176935 - Sequence No: 6", "url": "https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf", "date": "2025-01-29", "written_by": "makers", "quote": "Baseline numbers based on the 49,000 beneficiary HHs of the COVID-CT implemented by the government as of October 15, 2021." }, { "kind": "peer-reviewed study", "citation": "Smythe, I. S., Blumenstock, J. E. (2022). Geographic microtargeting of social assistance with high-resolution poverty maps. PNAS 119(32).", "title": "Geographic microtargeting of social assistance with high-resolution poverty maps", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/", "date": "2022-08-01", "written_by": "makers", "quote": "the government elected to use our high-resolution poverty maps to target the COVID-19 Rapid Response Registration (RRR) Cash Transfer Project" }, { "kind": "report", "citation": "Human Rights Watch (2021). Between Hunger and the Virus: The Impact of the Covid-19 Pandemic on People Living in Poverty in Lagos, Nigeria.", "title": "Between Hunger and the Virus", "url": "https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living", "date": "2021-07-28", "written_by": "independent", "quote": "a new 'rapid response' cash transfer program, which began in January 2021 and is intended to reach 1 million people nationwide, primarily in urban poor communities" }, { "kind": "press release", "citation": "Blumenstock, J., Lain, J., Smythe, I., Vishwanath, T. (2021). Using Big Data and machine learning to locate the poor in Nigeria. World Bank Data Blog.", "title": "Using Big Data and machine learning to locate the poor in Nigeria", "url": "https://blogs.worldbank.org/en/opendata/using-big-data-and-machine-learning-locate-poor-nigeria", "date": "2021-02-22", "written_by": "makers", "quote": "which is being guided by the mapping exercise described below" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0094-source-0001", "AIBD-0094-source-0002", "AIBD-0094-source-0003", "AIBD-0094-source-0004", "AIBD-0094-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "World Bank (2021). Project Appraisal Document: Nigeria National Social Safety Net Program - Scale Up (P176935).", "title": "Nigeria - National Social Safety Net Program - Scale Up - Project", "url": "https://documents.worldbank.org/curated/en/717321706545772846/pdf/Nigeria-National-Social-Safety-Net-Program-Scale-Up-Project.pdf", "date": "2021-11-23", "written_by": "makers", "quote": "1,163 of the poorest urban wards with a total population of over 20 million people were selected based on the ward-level poverty maps produced by applying cutting-edge machine learning algorithms" }, { "kind": "report", "citation": "World Bank (2025). Implementation Status and Results Report, National Social Safety Net Program-Scale Up (P176935), Sequence 6.", "title": "Disclosable Version of the ISR - National Social Safety Net Program-Scale Up - P176935 - Sequence No: 6", "url": "https://documents.worldbank.org/curated/en/099012925120031079/pdf/P17693518b066e0ff1b62c194b8b78c78dd.pdf", "date": "2025-01-29", "written_by": "makers", "quote": "Baseline numbers based on the 49,000 beneficiary HHs of the COVID-CT implemented by the government as of October 15, 2021." }, { "kind": "peer-reviewed study", "citation": "Smythe, I. S., Blumenstock, J. E. (2022). Geographic microtargeting of social assistance with high-resolution poverty maps. PNAS 119(32).", "title": "Geographic microtargeting of social assistance with high-resolution poverty maps", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9371736/", "date": "2022-08-01", "written_by": "makers", "quote": "the government elected to use our high-resolution poverty maps to target the COVID-19 Rapid Response Registration (RRR) Cash Transfer Project" }, { "kind": "report", "citation": "Human Rights Watch (2021). Between Hunger and the Virus: The Impact of the Covid-19 Pandemic on People Living in Poverty in Lagos, Nigeria.", "title": "Between Hunger and the Virus", "url": "https://www.hrw.org/report/2021/07/28/between-hunger-and-the-virus/the-impact-of-the-covid-19-pandemic-on-people-living", "date": "2021-07-28", "written_by": "independent", "quote": "a new 'rapid response' cash transfer program, which began in January 2021 and is intended to reach 1 million people nationwide, primarily in urban poor communities" }, { "kind": "press release", "citation": "Blumenstock, J., Lain, J., Smythe, I., Vishwanath, T. (2021). Using Big Data and machine learning to locate the poor in Nigeria. World Bank Data Blog.", "title": "Using Big Data and machine learning to locate the poor in Nigeria", "url": "https://blogs.worldbank.org/en/opendata/using-big-data-and-machine-learning-locate-poor-nigeria", "date": "2021-02-22", "written_by": "makers", "quote": "which is being guided by the mapping exercise described below" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ML poverty maps chose 1,163 poorest urban wards for Nigeria's COVID-19 cash register; 49,000 beneficiary households as of 15 October 2021", "account": "Lacking an urban social registry, Nigeria's National Social Safety Nets Coordinating Office (NASSCO) built the Rapid Response Register for a government-funded COVID-19 cash transfer. Ward-level poverty maps came from machine learning (ML) algorithms applied to satellite imagery with household-survey labels, by Berkeley and Columbia researchers with World Bank economists. The maps selected 1,163 of the poorest urban wards, population over 20 million. Residents self-registered by USSD after SMS blasts (first wave June 2021), then in-person verification. Human Rights Watch records the program began in January 2021. The PNAS authors state disbursement began mid-January 2021 (day not given; first day of month used). World Bank monitoring reports 49,000 beneficiary households of the government's COVID-CT as of 15 October 2021. It reports over 1.75 million registrations by November 2021, against a government target of one million households." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Ward-level poverty maps from supervised machine learning (deep learning) on satellite imagery, used for geographic targeting in the Rapid Response Register" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Joshua Blumenstock (UC Berkeley) and Isabella Smythe (Columbia University), using wealth estimates by Chi et al. (2021), with World Bank economists Jonathan Lain and Tara Vishwanath, for the Government of Nigeria" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Nigeria's Rapid Response Register used machine-learning poverty maps to select 1,163 urban wards for COVID-19 cash transfers", "headline": "ML poverty maps select 1,163 wards for Nigeria's COVID-19 cash" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2c38cee688ad632630951f3abfc422b1428ba2fa70d62d9811d8d9d82e0d75d9" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Lacking an urban social registry, Nigeria's National Social Safety Nets Coordinating Office (NASSCO) built the Rapid Response Register for a government-funded COVID-19 cash transfer. Ward-level poverty maps came from machine learning (ML) algorithms applied to satellite imagery with household-survey labels, by Berkeley and Columbia researchers with World Bank economists. The maps selected 1,163 of the poorest urban wards, population over 20 million. Residents self-registered by USSD after SMS blasts (first wave June 2021), then in-person verification. Human Rights Watch records the program began in January 2021. The PNAS authors state disbursement began mid-January 2021 (day not given; first day of month used). World Bank monitoring reports 49,000 beneficiary households of the government's COVID-CT as of 15 October 2021. It reports over 1.75 million registrations by November 2021, against a government target of one million households.", "replication": { "produced_by": [ "Deep-learning poverty map trained on geo-located household surveys", "Government decision to adopt the ward ranking for eligibility", "SMS blasts and USSD self-registration", "In-person verification, de-duplication and payment onboarding" ], "must_hold": [ "Ground-truth survey data for training labels", "Ward boundaries compatible with map resolution", "Mobile-phone access in target wards", "Government funding for transfers and identity verification capacity" ], "echoes": [ { "date": "2020-11-02", "setting": "Togo Novissi rural expansion using satellite poverty maps and phone-data targeting", "outcome": "recurred", "source": "Aiken et al. (2022) Nature, https://pmc.ncbi.nlm.nih.gov/articles/PMC8967719/ (expansion 'beginning in November 2020'); the 2 November 2020 date is from World Bank and Government of Togo (2023), Novissi Togo case study, https://documents.worldbank.org/curated/en/099751009222330502/pdf/IDU0e83f857301ff1047bf082710a8d21ddf42c3.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0105", "title": "GLAD deforestation alert subscriptions reduce deforestation probability in Africa by 18%", "summary": "Independent evaluation: subscriptions to GLAD Landsat alerts (bagged decision trees) cut deforestation probability in Africa by 18%.", "date_observed": "2021-01-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Global Forest Watch's GLAD deforestation alerts are produced by the University of Maryland from Landsat imagery. Bagged decision trees estimate the per-pixel likelihood of forest loss. The method was published on 2 March 2016. Moffette, Alix-Garcia, Shea and Pickens evaluated the alerts' effect in Nature Climate Change on 4 January 2021, analyzing subscriptions to alerts across 22 tropical countries. They found that subscriptions decreased the probability of deforestation in Africa by 18 percent relative to 2011–2016 baseline levels. Effects were stronger in protected areas and concessions. There was no detectable effect on other continents, and little effect where alerts existed without subscribers. They valued the avoided emissions at USD 149–696 million.", "category": "general benefit", "unexpected": false, "purpose": "Detect humid tropical forest disturbance in near real time from Landsat imagery to support land management and enforcement.", "system": "GLAD (Global Land Analysis and Discovery) Landsat deforestation alerts on Global Forest Watch", "model_version": null, "developer": "University of Maryland GLAD laboratory (Hansen et al.)", "deployer": "World Resources Institute (Global Forest Watch) and alert subscribers", "location": null, "domain": "Conservation and biodiversity", "segment": "Forest monitoring and enforcement", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate statistical effect across subscribed areas, no discrete attributable event." }, { "group": "organizational", "depth": null, "reason": "Effect measured at the level of subscribed administrative areas and concessions." }, { "group": "societal", "depth": null, "reason": "Continent-level reduction estimate with no single identifiable beneficiary." } ], "ai_role": { "status": "assessed", "statement": "The alerts are a machine-learning product (bagged decision trees). The evaluation attributes the 18 percent reduction to subscriptions to those alerts rather than to their mere availability. The evaluation's lead authors are independent economists, but co-authors are from WRI (operator) and the University of Maryland (producer)." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Moffette, F., Alix-Garcia, J., Shea, K., & Pickens, A. H. (2021). The impact of near-real-time deforestation alerts across the tropics. Nature Climate Change.", "title": "The impact of near-real-time deforestation alerts across the tropics", "url": "https://www.nature.com/articles/s41558-020-00956-w", "date": "2021-01-04", "written_by": "independent", "quote": "subscriptions to alerts in 22 tropical countries decrease the probability of deforestation in Africa by 18%" }, { "kind": "peer-reviewed study", "citation": "Hansen, M. C., Krylov, A., Tyukavina, A., Potapov, P. V., et al. (2016). Humid tropical forest disturbance alerts using Landsat data. Environmental Research Letters 11(3).", "title": "Humid tropical forest disturbance alerts using Landsat data", "url": "https://iopscience.iop.org/article/10.1088/1748-9326/11/3/034008", "date": "2016-03-02", "written_by": "makers", "quote": "A set of bagged decision trees was applied to each new Landsat observation and antecedent Landsat metrics." }, { "kind": "press release", "citation": "Berger, A., Carter, S., Schofield, T., Pickens, A., Reiche, J. (2026). Explore GFW's Updated Integrated Disturbance Alerts. Global Forest Watch / Global Nature Watch blog, 13 January 2026.", "title": "Explore GFW's Updated Integrated Disturbance Alerts", "url": "https://globalnaturewatch.org/blog/data-and-tools/integrated-deforestation-alerts/", "date": "2026-01-13", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Weekly Landsat coverage and a conservative classifier", "Free public platform with subscription-based alert delivery", "Subscribers with enforcement or management capacity" ], "must_hold": [ "Alerts reach actors who can respond", "Cloud cover does not suppress detections for long periods", "Protected-area or concession managers retain enforcement authority" ], "echoes": [ { "date": "2021-01-04", "setting": "Same study: subscriptions in Asia and Latin America", "model_version": null, "outcome": "did not recur", "source": "Moffette et al. (2021), abstract: no effect on other continents" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1159", "title": "Government‑Backed AI4Peat Mapping Tool Allegedly Misidentifies Granite Outcrops and Quarries as Peat", "url": "https://incidentdatabase.ai/cite/1159", "severity": null, "group": "societal", "basis": "Natural England's ML land-cover mapping from imagery misclassified granite and quarries as peat, misdirecting conservation; GLAD's Landsat classifier maps forest loss for the same users." }, "headline": "GLAD alerts cut deforestation probability in Africa by 18%", "metric": "decreased the probability of deforestation in Africa by 18 percent", "comparator": { "against": "average 2011–2016 deforestation levels, with areas lacking alert subscribers as the counterfactual across 22 tropical countries", "before": "average 2011–2016 levels", "after": "probability of deforestation in Africa decreased by 18%; no effect on other continents", "basis": "measured", "quote": "Here, we show that subscriptions to alerts in 22 tropical countries decrease the probability of deforestation in Africa by 18% relative to the average 2011–2016 levels. There is no effect on other continents, and the availability of alerts does not significantly change deforestation outcomes.", "url": "https://www.nature.com/articles/s41558-020-00956-w" }, "later": { "status": "persisted", "date": "2026-01-13", "note": "Global Forest Watch kept the Landsat-based GLAD alerts (GLAD-L) running and in 2022 folded them into an integrated disturbance alerts layer with GLAD-S2, RADD and, from January 2026, DIST-ALERT.", "quote": "GLAD-L is GFW's longest-standing alert product from the UMD Global Land Analysis and Discovery (GLAD) lab and uses imagery from NASA's Landsat satellites to detect tree cover loss at 30-meter resolution.", "url": "https://globalnaturewatch.org/blog/data-and-tools/integrated-deforestation-alerts/" }, "value": { "amount": "between US$149 million and US$696 million", "what": "value of avoided deforestation in Africa, priced at the social cost of carbon", "who": "society, through avoided carbon emissions", "estimate": true, "quote": "Calculated using the social cost of carbon for avoided deforestation in Africa, we estimate the alert system’s value to be between US$149 million and US$696 million.", "url": "https://www.nature.com/articles/s41558-020-00956-w" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1159 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1159", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.nature.com/articles/s41558-020-00956-w; https://globalnaturewatch.org/blog/data-and-tools/integrated-deforestation-alerts/; https://www.nature.com/articles/s41558-020-00956-w", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://glad.umd.edu/; https://en.wikipedia.org/wiki/World_Resources_Institute", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study, the makers' peer-reviewed study and the deployer's press release. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0105", "catalog_version": "1.0.0", "source_fingerprint": "37e5d9f524fe3cd7cc54508a97a4988c9794e794016ba1511c8e9c3b9a34783f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0105-source-0001", "AIBD-0105-source-0002", "AIBD-0105-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0105-legacy-value", "DIV-0005" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0105-legacy-value", "DIV-0005" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Maryland GLAD laboratory (Hansen et al.)", "deployer": "World Resources Institute (Global Forest Watch) and alert subscribers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The alerts are a machine-learning product (bagged decision trees). The evaluation attributes the 18 percent reduction to subscriptions to those alerts rather than to their mere availability. The evaluation's lead authors are independent economists, but co-authors are from WRI (operator) and the University of Maryland (producer)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The alerts are a machine-learning product (bagged decision trees). The evaluation attributes the 18 percent reduction to subscriptions to those alerts rather than to their mere availability. The evaluation's lead authors are independent economists, but co-authors are from WRI (operator) and the University of Maryland (producer)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study, the makers' peer-reviewed study and the deployer's press release. 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Nairobi-based produce platform Selina Wamucii developed and funded it. Kuzi generates a real-time heat map of locusts across Africa, shows potential migration routes and offers a breeding index. It uses satellite data, soil sensor data, ground meteorological observation and machine learning. CEO John Oroko said farmers and pastoralists could sign up for free SMS alerts, in Kiswahili, Amharic and Somali, with up to three months' notice. He said the app was available in Kenya, Uganda, Ethiopia and Somalia, and funders were being sought for enhancements. Synced reported the same claims on 18 January 2021. Neither source gives any forecast evaluation, official adoption or an alert that changed an outcome.", "category": "general benefit", "unexpected": false, "purpose": "Predict where desert locusts will breed and migrate and warn farmers and pastoralists by SMS months in advance.", "system": "Kuzi (machine-learning locust prediction and SMS alert tool)", "model_version": null, "developer": "Selina Wamucii, Nairobi", "deployer": "Selina Wamucii (free SMS service for users in Kenya, Uganda, Ethiopia and Somalia)", "location": "Nairobi, Kenya", "domain": "Agriculture / pest early warning", "segment": "Desert locust forecasting", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The launch coverage describes locust warnings, with no forecast evaluation or outcome documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No user, ministry or FAO confirmation of an alert received or acted on." }, { "group": "societal", "depth": null, "reason": "No evaluation of forecast skill or of crop losses avoided." } ], "ai_role": { "status": "unassessed", "statement": "Only the maker's CEO is quoted; no evaluation of the machine-learning model, no official use, and no documented alert that changed an outcome were found." }, "evidence": [ { "kind": "news report", "citation": "Diwakar A. Kuzi, an AI-powered tool helping African farmers fight locusts. TRT World, 13 January 2021.", "title": "Kuzi, an AI-powered tool helping African farmers fight locusts", "url": "https://www.trtworld.com/magazine/kuzi-an-ai-powered-tool-helping-african-farmers-fight-locusts-43222", "date": "2021-01-13", "written_by": "independent", "quote": "farmers and pastoralists can now sign up to receive free SMS alerts that give them up to three months advance notice" }, { "kind": "news report", "citation": "Synced. Kenyan-Developed APP Utilizes ML to Predicate the Migration and Breeding of Locusts. 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Synced Review, 18 January 2021.", "title": "Kenyan-Developed APP Utilizes ML to Predicate the Migration and Breeding of Locusts", "url": "https://syncedreview.com/2021/01/18/kenyan-developed-app-utilizes-ml-to-predicate-the-migration-and-breeding-of-locusts/", "date": "2021-01-18", "written_by": "independent", "quote": "Kuzi is available to users in countries including Kenya, Uganda, Ethiopia, and Somalia to help them control the pest outbreak." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Selina Wamucii's Kuzi combines satellite, soil-sensor and weather data with machine learning to map locust risk for Kenya, Uganda, Ethiopia and Somalia; maker statements only, no outcome evidence.", "account": "TRT World reported on 13 January 2021 on Kuzi, named after the Swahili word for the locust-eating wattled starling. Nairobi-based produce platform Selina Wamucii developed and funded it. Kuzi generates a real-time heat map of locusts across Africa, shows potential migration routes and offers a breeding index. It uses satellite data, soil sensor data, ground meteorological observation and machine learning. CEO John Oroko said farmers and pastoralists could sign up for free SMS alerts, in Kiswahili, Amharic and Somali, with up to three months' notice. He said the app was available in Kenya, Uganda, Ethiopia and Somalia, and funders were being sought for enhancements. Synced reported the same claims on 18 January 2021. Neither source gives any forecast evaluation, official adoption or an alert that changed an outcome." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Kuzi (machine-learning locust prediction and SMS alert tool)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Selina Wamucii, Nairobi" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kuzi, a Kenyan machine-learning locust tool, offers free SMS alerts up to three months ahead", "headline": "Kuzi's SMS alerts may warn of locusts up to three months ahead" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "80b7cab691859b2593ba8acee1ccae6dbce1e236932861e7b7d7dc520fe2536c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "TRT World reported on 13 January 2021 on Kuzi, named after the Swahili word for the locust-eating wattled starling. Nairobi-based produce platform Selina Wamucii developed and funded it. Kuzi generates a real-time heat map of locusts across Africa, shows potential migration routes and offers a breeding index. It uses satellite data, soil sensor data, ground meteorological observation and machine learning. CEO John Oroko said farmers and pastoralists could sign up for free SMS alerts, in Kiswahili, Amharic and Somali, with up to three months' notice. He said the app was available in Kenya, Uganda, Ethiopia and Somalia, and funders were being sought for enhancements. Synced reported the same claims on 18 January 2021. Neither source gives any forecast evaluation, official adoption or an alert that changed an outcome.", "replication": { "produced_by": [ "Satellite, soil-sensor and ground meteorological data feeds", "SMS delivery in Kiswahili, Amharic and Somali" ], "must_hold": [ "Funding for further features, which the CEO said was being sought" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0174", "title": "A third company linked to suspected money laundering", "summary": "Bank F’s network tool found phone numbers and email addresses shared by three companies. Further account checks indicated possible money laundering.", "date_observed": "2021-01-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Hong Kong Monetary Authority's report “AML/CFT Regtech: Case Studies and Insights” (January 2021; press release 21 January 2021) presents anonymized bank case studies. Bank F is a subsidiary and regional head office of a large global bank in Asia-Pacific, per the report. It implemented a network (graph) analytics solution in Hong Kong in 2013. It identified high-risk customers and transactions from wholesale client, correspondent banking, trade, payments and external registry data. In a 2015 example, a relationship manager gathered intelligence about trade-based money laundering (TBML) related to a drug cartel in one account. The manager linked it to a second account via the CRM tool. The tool then identified additional companies linked to the first two parties through linked phone numbers and email addresses. Account reviews for Companies A, B and C revealed potential money laundering concerns. The report states that by 2016 Bank F covered its top 20 commercial banking sites and about 80% of its trade lending book. The tool has led to review of around 100 customer relationships holding around USD 500 million in clean or unsecured exposures, it says. The report’s USD 50 million figure assumes that 10% of those exposures would otherwise be unrecoverable. It does not document USD 50 million in realized savings. The foreword adds that such techniques are already neutralizing mule account networks linked to face mask scams. The 2015 example carries no day.", "category": "protective response", "unexpected": false, "purpose": "Identify high-risk customers, transactions and hidden relationships for AML/CFT and trade-based money laundering investigations.", "system": "Bank F network (graph) analytics solution implemented in Hong Kong in 2013", "model_version": null, "developer": "Bank F (anonymized subsidiary and regional head office of a large global bank); the report names no vendor", "deployer": "Bank F, Hong Kong", "location": "Hong Kong, China", "domain": "Anti-money laundering", "segment": "Trade finance and trade-based money laundering", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The report records reviews of around 100 customer relationships. It also records a third linked company whose review revealed potential money laundering concerns. Losses avoided are estimated, not observed." }, { "group": "societal", "depth": null, "reason": "The foreword's statement about neutralizing mule account networks is general and not tied to a documented outcome." } ], "ai_role": { "status": "assessed", "statement": "The HKMA report attributes the identification of Company C to the network analytics tool's matching of linked phone numbers and email addresses. A human relationship manager supplied the initial lead. Whether the tool uses machine learning is not stated. The bank built and deployed the tool itself. The HKMA, which wrote the report, is the regulator." }, "evidence": [ { "kind": "descriptive report", "citation": "Hong Kong Monetary Authority and Deloitte, AML/CFT Regtech: Case Studies and Insights (January 2021), Bank F, 24–25.", "title": "AML/CFT Regtech: Case Studies and Insights", "url": "https://www.hkma.gov.hk/media/eng/doc/key-information/guidelines-and-circular/2021/20210121e2a1.pdf", "date": "2021-01-21", "written_by": "independent", "quote": "Since deployment, the tool has led to the review of around 100 customer relationships for AML/CFT reasons." }, { "kind": "press release", "citation": "Hong Kong Monetary Authority, press release, 21 January 2021", "title": "AML/CFT Regtech: Case Studies and Insights", "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/2021/01/20210121-3/", "date": "2021-01-21", "written_by": "independent", "quote": "AML/CFT Regtech: Case Studies and Insights", "supports_benefit": false } ], "replication": { "produced_by": [ "Integration of wholesale client, correspondent banking, trade, payments and external registry data in one network model", "A human intelligence lead (the relationship manager's TBML suspicion) used as the seed for network expansion" ], "must_hold": [ "Data of sufficient quality across sources, which the report says Bank F stressed", "Governance that lets analytic findings trigger account reviews and STR filings" ], "echoes": [ { "date": null, "setting": "Bank F, top 20 commercial banking sites globally (2016)", "model_version": null, "outcome": "recurred", "source": "HKMA report: coverage of about 80% of the trade lending book; around 100 relationships reviewed since deployment" }, { "date": null, "setting": "Bank A, Hong Kong, pilot using IP addresses and login data for about 50 customers (2020)", "model_version": null, "outcome": "recurred", "source": "HKMA report: undisclosed clusters of relationships identified from shared IP addresses and simultaneous logins" }, { "date": "2021-01-21", "setting": "Fraud and Money Laundering Intelligence Taskforce member banks", "model_version": null, "outcome": "unknown", "source": "HKMA foreword: techniques 'neutralising mule account networks linked to face mask scams', no figures" } ] }, "paired_incident": null, "headline": "A third company linked to suspected money laundering", "metric": "even if 10% were unrecoverable the tool contributed around USD 50 million in savings", "comparator": null, "later": { "status": "unknown", "date": null, "note": "Nothing dated after the January 2021 HKMA report was found for Bank F's tool; the report's own scale-up figures predate it.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.hkma.gov.hk/media/eng/doc/key-information/guidelines-and-circular/2021/20210121e2a1.pdf", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent descriptive report and one independent press release. For the benefit itself, the cited sources include no independent study of the benefit and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0174", "catalog_version": "1.0.0", "source_fingerprint": "f71e252dd0e9ecdf3e46dff9d0e825723825b89435967072388b85b57705a63e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0174-source-0001", "AIBD-0174-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Bank F (anonymized subsidiary and regional head office of a large global bank); the report names no vendor", "deployer": "Bank F, Hong Kong" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The HKMA report attributes the identification of Company C to the network analytics tool's matching of linked phone numbers and email addresses. A human relationship manager supplied the initial lead. Whether the tool uses machine learning is not stated. The bank built and deployed the tool itself. The HKMA, which wrote the report, is the regulator." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The HKMA report attributes the identification of Company C to the network analytics tool's matching of linked phone numbers and email addresses. A human relationship manager supplied the initial lead. Whether the tool uses machine learning is not stated. The bank built and deployed the tool itself. The HKMA, which wrote the report, is the regulator." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The report records reviews of around 100 customer relationships. It also records a third linked company whose review revealed potential money laundering concerns. Losses avoided are estimated, not observed." }, { "group": "societal", "reason": "The foreword's statement about neutralizing mule account networks is general and not tied to a documented outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent descriptive report and one independent press release. For the benefit itself, the cited sources include no independent study of the benefit and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The report records reviews of around 100 customer relationships. It also records a third linked company whose review revealed potential money laundering concerns. Losses avoided are estimated, not observed." }, { "group": "societal", "reason": "The foreword's statement about neutralizing mule account networks is general and not tied to a documented outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The report records reviews of around 100 customer relationships. It also records a third linked company whose review revealed potential money laundering concerns. Losses avoided are estimated, not observed." }, { "group": "societal", "reason": "The foreword's statement about neutralizing mule account networks is general and not tied to a documented outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "even if 10% were unrecoverable the tool contributed around USD 50 million in savings", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Nothing dated after the January 2021 HKMA report was found for Bank F's tool; the report's own scale-up figures predate it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0174" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Hong Kong Monetary Authority's report “AML/CFT Regtech: Case Studies and Insights” (January 2021; press release 21 January 2021) presents anonymized bank case studies. Bank F is a subsidiary and regional head office of a large global bank in Asia-Pacific, per the report. It implemented a network (graph) analytics solution in Hong Kong in 2013. It identified high-risk customers and transactions from wholesale client, correspondent banking, trade, payments and external registry data. In a 2015 example, a relationship manager gathered intelligence about trade-based money laundering (TBML) related to a drug cartel in one account. The manager linked it to a second account via the CRM tool. The tool then identified additional companies linked to the first two parties through linked phone numbers and email addresses. Account reviews for Companies A, B and C revealed potential money laundering concerns. The report states that by 2016 Bank F covered its top 20 commercial banking sites and about 80% of its trade lending book. The tool has led to review of around 100 customer relationships holding around USD 500 million in clean or unsecured exposures, it says. Even if 10% were unrecoverable, the tool contributed around USD 50 million in savings, it says. The foreword adds that such techniques are already neutralizing mule account networks linked to face mask scams. The 2015 example carries no day.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The report records reviews of around 100 customer relationships. It also records a third linked company whose review revealed potential money laundering concerns. Losses avoided are estimated, not observed." }, { "group": "societal", "reason": "The foreword's statement about neutralizing mule account networks is general and not tied to a documented outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify high-risk customers, transactions and hidden relationships for AML/CFT and trade-based money laundering investigations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Hong Kong, China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify high-risk customers, transactions and hidden relationships for AML/CFT and trade-based money laundering investigations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-01-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; 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around 100 relationships reviewed since deployment" }, { "setting": "Bank A, Hong Kong, pilot using IP addresses and login data for about 50 customers (2020)", "outcome": "recurred", "source": "HKMA report: undisclosed clusters of relationships identified from shared IP addresses and simultaneous logins" }, { "date": "2021-01-21", "setting": "Fraud and Money Laundering Intelligence Taskforce member banks", "outcome": "unknown", "source": "HKMA foreword: techniques 'neutralising mule account networks linked to face mask scams', no figures" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Integration of wholesale client, correspondent banking, trade, payments and external registry data in one network model", "A human intelligence lead (the relationship manager's TBML suspicion) used as the seed for network expansion" ], "must_hold": [ "Data of sufficient quality across sources, which the report says Bank F stressed", "Governance that lets analytic findings trigger account reviews and STR filings" ], "echoes": [ { "setting": "Bank F, top 20 commercial banking sites globally (2016)", "outcome": "recurred", "source": "HKMA report: coverage of about 80% of the trade lending book; around 100 relationships reviewed since deployment" }, { "setting": "Bank A, Hong Kong, pilot using IP addresses and login data for about 50 customers (2020)", "outcome": "recurred", "source": "HKMA report: undisclosed clusters of relationships identified from shared IP addresses and simultaneous logins" }, { "date": "2021-01-21", "setting": "Fraud and Money Laundering Intelligence Taskforce member banks", "outcome": "unknown", "source": "HKMA foreword: techniques 'neutralising mule account networks linked to face mask scams', no figures" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://www.hkma.gov.hk/media/eng/doc/key-information/guidelines-and-circular/2021/20210121e2a1.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Anti-money laundering", "segment": "Trade finance and trade-based money laundering" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Hong Kong Monetary Authority and Deloitte, AML/CFT Regtech: Case Studies and Insights (January 2021), Bank F, 24–25.", "title": "AML/CFT Regtech: Case Studies and Insights", "url": "https://www.hkma.gov.hk/media/eng/doc/key-information/guidelines-and-circular/2021/20210121e2a1.pdf", "date": "2021-01-21", "written_by": "independent", "quote": "Since deployment, the tool has led to the review of around 100 customer relationships for AML/CFT reasons." }, { "kind": "press release", "citation": "Hong Kong Monetary Authority, press release, 21 January 2021", "title": "AML/CFT Regtech: Case Studies and Insights", "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/2021/01/20210121-3/", "date": "2021-01-21", "written_by": "independent", "quote": "AML/CFT Regtech: Case Studies and Insights", "supports_benefit": false } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0174-source-0001", "AIBD-0174-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "HKMA and Deloitte describe Bank F’s experience. The bank supplied the account. The USD 50 million figure assumes that 10% of the unsecured exposure would have been lost; it is not a measured saving." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0174-source-0001", "AIBD-0174-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "HKMA and Deloitte describe Bank F’s experience. The bank supplied the account. The USD 50 million figure assumes that 10% of the unsecured exposure would have been lost; it is not a measured saving." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0174-source-0001", "retained_source_order": [ "AIBD-0174-source-0001", "AIBD-0174-source-0002" ], "origins": [ { "url": "https://www.hkma.gov.hk/media/eng/doc/key-information/guidelines-and-circular/2021/20210121e2a1.pdf", "locator": "Foreword, p. 4; Bank F, pp. 24–25; costs, p. 43; acknowledgments, p. 47.", "contribution": "The bank’s account, the network analysis, and the hypothetical USD 50 million avoided-loss calculation.", "relationship": "HKMA/Deloitte report based on participating banks’ experience; not an independent audit of realized savings.", "source_refs": [ "AIBD-0174-source-0001" ] }, { "url": "https://www.hkma.gov.hk/eng/news-and-media/press-releases/2021/01/20210121-3/", "locator": "Publication announcement dated 21 January 2021.", "contribution": "Establishes the report’s release date.", "relationship": "Agency press release, not another evaluation.", "source_refs": [ "AIBD-0174-source-0002" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0174-source-0001", "AIBD-0174-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "HKMA and Deloitte describe Bank F’s experience. The bank supplied the account. The USD 50 million figure assumes that 10% of the unsecured exposure would have been lost; it is not a measured saving." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Bank F’s network tool found phone numbers and email addresses shared by three companies. Further account checks indicated possible money laundering.", "account": "The Hong Kong Monetary Authority's report “AML/CFT Regtech: Case Studies and Insights” (January 2021; press release 21 January 2021) presents anonymized bank case studies. Bank F is a subsidiary and regional head office of a large global bank in Asia-Pacific, per the report. It implemented a network (graph) analytics solution in Hong Kong in 2013. It identified high-risk customers and transactions from wholesale client, correspondent banking, trade, payments and external registry data. In a 2015 example, a relationship manager gathered intelligence about trade-based money laundering (TBML) related to a drug cartel in one account. The manager linked it to a second account via the CRM tool. The tool then identified additional companies linked to the first two parties through linked phone numbers and email addresses. Account reviews for Companies A, B and C revealed potential money laundering concerns. The report states that by 2016 Bank F covered its top 20 commercial banking sites and about 80% of its trade lending book. The tool has led to review of around 100 customer relationships holding around USD 500 million in clean or unsecured exposures, it says. The report’s USD 50 million figure assumes that 10% of those exposures would otherwise be unrecoverable. It does not document USD 50 million in realized savings. The foreword adds that such techniques are already neutralizing mule account networks linked to face mask scams. The 2015 example carries no day." } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Bank F network (graph) analytics solution implemented in Hong Kong in 2013" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Bank F (anonymized subsidiary and regional head office of a large global bank); the report names no vendor" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A third company linked to suspected money laundering", "headline": "A third company linked to suspected money laundering" } }, "provenance": { "kind": "legacy_record", "basis": "Wording aligned with the source review of 25 October 2026; the longer account retains previously collected details.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f71e252dd0e9ecdf3e46dff9d0e825723825b89435967072388b85b57705a63e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Hong Kong Monetary Authority's report “AML/CFT Regtech: Case Studies and Insights” (January 2021; press release 21 January 2021) presents anonymized bank case studies. Bank F is a subsidiary and regional head office of a large global bank in Asia-Pacific, per the report. It implemented a network (graph) analytics solution in Hong Kong in 2013. It identified high-risk customers and transactions from wholesale client, correspondent banking, trade, payments and external registry data. In a 2015 example, a relationship manager gathered intelligence about trade-based money laundering (TBML) related to a drug cartel in one account. The manager linked it to a second account via the CRM tool. The tool then identified additional companies linked to the first two parties through linked phone numbers and email addresses. Account reviews for Companies A, B and C revealed potential money laundering concerns. The report states that by 2016 Bank F covered its top 20 commercial banking sites and about 80% of its trade lending book. The tool has led to review of around 100 customer relationships holding around USD 500 million in clean or unsecured exposures, it says. Even if 10% were unrecoverable, the tool contributed around USD 50 million in savings, it says. The foreword adds that such techniques are already neutralizing mule account networks linked to face mask scams. The 2015 example carries no day.", "replication": { "produced_by": [ "Integration of wholesale client, correspondent banking, trade, payments and external registry data in one network model", "A human intelligence lead (the relationship manager's TBML suspicion) used as the seed for network expansion" ], "must_hold": [ "Data of sufficient quality across sources, which the report says Bank F stressed", "Governance that lets analytic findings trigger account reviews and STR filings" ], "echoes": [ { "setting": "Bank F, top 20 commercial banking sites globally (2016)", "outcome": "recurred", "source": "HKMA report: coverage of about 80% of the trade lending book; around 100 relationships reviewed since deployment" }, { "setting": "Bank A, Hong Kong, pilot using IP addresses and login data for about 50 customers (2020)", "outcome": "recurred", "source": "HKMA report: undisclosed clusters of relationships identified from shared IP addresses and simultaneous logins" }, { "date": "2021-01-21", "setting": "Fraud and Money Laundering Intelligence Taskforce member banks", "outcome": "unknown", "source": "HKMA foreword: techniques 'neutralising mule account networks linked to face mask scams', no figures" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 2, "record_mapped": 28, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0320", "title": "Microsoft Translator adds Inuktitut (2021), Inuinnaqtun and romanized Inuktitut (2022) and Inuktitut text-to-speech (2024) with the Government of Nunavut", "summary": "Neural MT for Inuktut dialects built with the Government of Nunavut and volunteer speakers; Nunatsiaq News and VICE report launches and translation errors; no measured user outcome documented.", "date_observed": "2021-01-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Microsoft added Inuktitut text translation to Microsoft Translator, Office and Translator for Bing on 27 January 2021. The date is from Arctic Portal, relaying the Microsoft Translator blog. Microsoft worked with the Government of Nunavut for language data; Inuktitut speakers volunteered to validate and test translations. VICE (18 February 2021) reported Nunavut language officials finding the output “riddled with mistakes”. Solomon Awa said: “Sometimes it's close, but sometimes it gave the opposite meaning, or one that was misleading”. Languages commissioner Karliin Aariak called it “a great tool to be like a first step”. Retired Université Laval researcher Louis-Jacques Dorais called it a “tour de force” despite a wrong test sentence. Nunatsiaq News (28 February 2022) reported Inuinnaqtun and romanized Inuktitut added during Uqausirmut Quviasuutiqarniq. Fewer than 600 speak Inuinnaqtun fluently, per the Kitikmeot Heritage Society. Microsoft's own feature (1 February 2022) says “Text translation is based on neural machine translation models”. It says the Government of Nunavut “turned to the community to help build and test the language models”. It lists intended uses (unilingual patients communicating with doctors, younger people with elders, emails in Office) without data. Nunatsiaq News (9 December 2024) reported the 5 December launch of Inuktitut text-to-speech voices “Taqqiq” and “Siqiniq”. They were built from thousands of government documents, hired speakers' recordings and Bible Society and Nunavut Inuit Heritage Trust audio. The report noted presenters' accounts of the translator confusing “condo and condom, and prime rib and prime minister”. Voice contributor Leah Ayaruaq McKay said she plans to use it to help her husband learn Inuktitut. Government of Nunavut web pages were not available and are not among the sources. No cited source measures use, accuracy or an outcome for any user.", "category": "general benefit", "unexpected": false, "purpose": "Built to translate text between Inuktut dialects and other languages (and, from 2024, to read Inuktitut aloud). This lets residents, learners and government users read and write in Inuktut. The launches are that intended use.", "system": "Microsoft Translator Inuktitut, Inuinnaqtun and romanized Inuktitut text translation (neural machine translation) and Inuktitut text-to-speech", "model_version": null, "developer": "Microsoft (Azure Cognitive Services Translator and Speech) with the Government of Nunavut and community volunteers, including the Kitikmeot Heritage Society for Inuinnaqtun", "deployer": "Government of Nunavut; public users of Microsoft Translator, Office and Bing", "location": "Nunavut, Canada", "domain": "Language technology / Indigenous language access", "segment": "Public translation tools for Inuktut dialects", "benefit_type": "Increased Inclusion", "taxonomy_note": "The good is an Indigenous official language made usable in mainstream software, with no measured outcome and reported translation errors.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Users are described (a translator who found errors, a voice contributor planning to use it for her husband's learning). No measured benefit for any person is documented." }, { "group": "organizational", "depth": null, "reason": "The Government of Nunavut's and Microsoft's stated uses (healthcare communication, Office email, compliance with language law) are expectations without reported data." }, { "group": "societal", "depth": null, "reason": "Language-vitality effects are asserted by officials. VICE notes Inuktut use fell from 72 to 65 percent between 2001 and 2016, without any link to the tool." } ], "ai_role": { "status": "assessed", "statement": "Microsoft states the translation is neural machine translation trained on Government of Nunavut data and validated by volunteer speakers. Independent reporting records both the launches and specific wrong translations (opposite meanings in 2021; “condo and condom” confusions recounted in 2024). Translators said the output needs a fluent reviewer. No cited source reports a user outcome, usage figure or accuracy measurement. 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Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft. Microsoft News Center Canada, 1 February 2022.", "title": "Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft", "url": "https://news.microsoft.com/en-ca/2022/02/01/government-of-nunavut-preserving-endangered-inuit-languages-and-culture-with-the-help-of-artificial-intelligence-and-microsoft/", "date": "2022-02-01", "written_by": "makers", "quote": "Text translation is based on neural machine translation models." }, { "kind": "news report", "citation": "Pelletier J (2024). 'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech. Nunatsiaq News, 9 December 2024.", "title": "'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech", "url": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/", "date": "2024-12-09", "written_by": "independent", "quote": "Several presenters explained the artificial intelligence mixed up words like condo and condom, and prime rib and prime minister." } ], "replication": { "produced_by": [ "Language data supplied by the Government of Nunavut and recordings by hired and volunteer speakers", "Volunteer fluent speakers validating and testing translations before launch" ], "must_hold": [ "Output is checked by a fluent speaker; Nunavut translators and the languages commissioner describe it as a first step needing review", "Dialect differences across the Arctic are tolerated by users of a standardized model" ], "echoes": [ { "date": "2022-02-28", "setting": "Inuinnaqtun and romanized Inuktitut added with updated Inuktitut models", "model_version": null, "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/inuinnaqtun-and-romanized-inuktitut-added-to-microsoft-translator/" }, { "date": "2024-12-05", "setting": "Inuktitut text-to-speech voices launched in Iqaluit", "model_version": null, "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/" } ] }, "paired_incident": null, "headline": "Microsoft Translator adds Inuktitut and Inuinnaqtun with Nunavut", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2024-12-05", "note": "After the January 2021 launch, Inuinnaqtun and romanized Inuktitut were added in February 2022 and Inuktitut text-to-speech voices launched on 5 December 2024, while presenters still reported word confusions.", "quote": "Microsoft Canada and the Government of Nunavut announced Dec. 5 that Inuktitut text-to-speech is available now on Microsoft Translator.", "url": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/" }, "value": null, "developer_country": "United States", "deployer_country": "Canada", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft; https://en.wikipedia.org/wiki/Nunavut", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports and the makers' press release. 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It says the Government of Nunavut “turned to the community to help build and test the language models”. It lists intended uses (unilingual patients communicating with doctors, younger people with elders, emails in Office) without data. Nunatsiaq News (9 December 2024) reported the 5 December launch of Inuktitut text-to-speech voices “Taqqiq” and “Siqiniq”. They were built from thousands of government documents, hired speakers' recordings and Bible Society and Nunavut Inuit Heritage Trust audio. The report noted presenters' accounts of the translator confusing “condo and condom, and prime rib and prime minister”. Voice contributor Leah Ayaruaq McKay said she plans to use it to help her husband learn Inuktitut. Government of Nunavut web pages were not available and are not among the sources. 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The launches are that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-01-27", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Inclusion under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft; https://en.wikipedia.org/wiki/Nunavut", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Language data supplied by the Government of Nunavut and recordings by hired and volunteer speakers", "Volunteer fluent speakers validating and testing translations before launch" ], "must_hold": [ "Output is checked by a fluent speaker; Nunavut translators and the languages commissioner describe it as a first step needing review", "Dialect differences across the Arctic are tolerated by users of a standardized model" ], "echoes": [ { "date": "2022-02-28", "setting": "Inuinnaqtun and romanized Inuktitut added with updated Inuktitut models", "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/inuinnaqtun-and-romanized-inuktitut-added-to-microsoft-translator/" }, { "date": "2024-12-05", "setting": "Inuktitut text-to-speech voices launched in Iqaluit", "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Language data supplied by the Government of Nunavut and recordings by hired and volunteer speakers", "Volunteer fluent speakers validating and testing translations before launch" ], "must_hold": [ "Output is checked by a fluent speaker; 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it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft; https://en.wikipedia.org/wiki/Nunavut", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Language technology / Indigenous language access", "segment": "Public translation tools for Inuktut dialects" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Arctic Portal (2021). Inuit language now available in Microsoft Translator! 1 February 2021 (summarises the Microsoft Translator blog of 27 January 2021).", "title": "Inuit language now available in Microsoft Translator!", "url": "https://arcticportal.org/news-events/news/2489-inuit-language-is-now-available-in-microsoft-translator", "date": "2021-02-01", "written_by": "independent", "quote": "On 27 January 2021 Microsoft announced that they added Inuktitut text translation to their Translator app, Office and Translator for Bing." }, { "kind": "news report", "citation": "Cavanagh M (2021). New Tech Can Finally Translate Inuit Language-Sort Of. VICE, 18 February 2021.", "title": "New Tech Can Finally Translate Inuit Language-Sort Of", "url": "https://www.vice.com/en/article/tech-microsoft-translator-inuit-language-inuktitut/", "date": "2021-02-18", "written_by": "independent", "quote": "Sometimes it's close, but sometimes it gave the opposite meaning, or one that was misleading," }, { "kind": "news report", "citation": "Nunatsiaq News (2022). Inuinnaqtun and romanized Inuktitut added to Microsoft Translator. 28 February 2022.", "title": "Inuinnaqtun and romanized Inuktitut added to Microsoft Translator", "url": "https://nunatsiaq.com/stories/article/inuinnaqtun-and-romanized-inuktitut-added-to-microsoft-translator/", "date": "2022-02-28", "written_by": "independent", "quote": "Inuinnaqtun and romanized Inuktitut have been added to Microsoft's translation services as a part of the Nunavut government's annual celebration of the Inuktut languages." }, { "kind": "press release", "citation": "Microsoft Canada (2022). Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft. Microsoft News Center Canada, 1 February 2022.", "title": "Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft", "url": "https://news.microsoft.com/en-ca/2022/02/01/government-of-nunavut-preserving-endangered-inuit-languages-and-culture-with-the-help-of-artificial-intelligence-and-microsoft/", "date": "2022-02-01", "written_by": "makers", "quote": "Text translation is based on neural machine translation models." }, { "kind": "news report", "citation": "Pelletier J (2024). 'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech. Nunatsiaq News, 9 December 2024.", "title": "'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech", "url": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/", "date": "2024-12-09", "written_by": "independent", "quote": "Several presenters explained the artificial intelligence mixed up words like condo and condom, and prime rib and prime minister." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0320-source-0001", "AIBD-0320-source-0002", "AIBD-0320-source-0003", "AIBD-0320-source-0004", "AIBD-0320-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Arctic Portal (2021). Inuit language now available in Microsoft Translator! 1 February 2021 (summarises the Microsoft Translator blog of 27 January 2021).", "title": "Inuit language now available in Microsoft Translator!", "url": "https://arcticportal.org/news-events/news/2489-inuit-language-is-now-available-in-microsoft-translator", "date": "2021-02-01", "written_by": "independent", "quote": "On 27 January 2021 Microsoft announced that they added Inuktitut text translation to their Translator app, Office and Translator for Bing." }, { "kind": "news report", "citation": "Cavanagh M (2021). New Tech Can Finally Translate Inuit Language-Sort Of. VICE, 18 February 2021.", "title": "New Tech Can Finally Translate Inuit Language-Sort Of", "url": "https://www.vice.com/en/article/tech-microsoft-translator-inuit-language-inuktitut/", "date": "2021-02-18", "written_by": "independent", "quote": "Sometimes it's close, but sometimes it gave the opposite meaning, or one that was misleading," }, { "kind": "news report", "citation": "Nunatsiaq News (2022). Inuinnaqtun and romanized Inuktitut added to Microsoft Translator. 28 February 2022.", "title": "Inuinnaqtun and romanized Inuktitut added to Microsoft Translator", "url": "https://nunatsiaq.com/stories/article/inuinnaqtun-and-romanized-inuktitut-added-to-microsoft-translator/", "date": "2022-02-28", "written_by": "independent", "quote": "Inuinnaqtun and romanized Inuktitut have been added to Microsoft's translation services as a part of the Nunavut government's annual celebration of the Inuktut languages." }, { "kind": "press release", "citation": "Microsoft Canada (2022). Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft. Microsoft News Center Canada, 1 February 2022.", "title": "Government of Nunavut preserving endangered Inuit languages and culture with the help of artificial intelligence and Microsoft", "url": "https://news.microsoft.com/en-ca/2022/02/01/government-of-nunavut-preserving-endangered-inuit-languages-and-culture-with-the-help-of-artificial-intelligence-and-microsoft/", "date": "2022-02-01", "written_by": "makers", "quote": "Text translation is based on neural machine translation models." }, { "kind": "news report", "citation": "Pelletier J (2024). 'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech. Nunatsiaq News, 9 December 2024.", "title": "'My name is Taqqiq, I can read text': Microsoft Translator adds Inuktitut text-to-speech", "url": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/", "date": "2024-12-09", "written_by": "independent", "quote": "Several presenters explained the artificial intelligence mixed up words like condo and condom, and prime rib and prime minister." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Neural MT for Inuktut dialects built with the Government of Nunavut and volunteer speakers; Nunatsiaq News and VICE report launches and translation errors; no measured user outcome documented.", "account": "Microsoft added Inuktitut text translation to Microsoft Translator, Office and Translator for Bing on 27 January 2021. The date is from Arctic Portal, relaying the Microsoft Translator blog. Microsoft worked with the Government of Nunavut for language data; Inuktitut speakers volunteered to validate and test translations. VICE (18 February 2021) reported Nunavut language officials finding the output “riddled with mistakes”. Solomon Awa said: “Sometimes it's close, but sometimes it gave the opposite meaning, or one that was misleading”. Languages commissioner Karliin Aariak called it “a great tool to be like a first step”. Retired Université Laval researcher Louis-Jacques Dorais called it a “tour de force” despite a wrong test sentence. Nunatsiaq News (28 February 2022) reported Inuinnaqtun and romanized Inuktitut added during Uqausirmut Quviasuutiqarniq. Fewer than 600 speak Inuinnaqtun fluently, per the Kitikmeot Heritage Society. Microsoft's own feature (1 February 2022) says “Text translation is based on neural machine translation models”. It says the Government of Nunavut “turned to the community to help build and test the language models”. It lists intended uses (unilingual patients communicating with doctors, younger people with elders, emails in Office) without data. Nunatsiaq News (9 December 2024) reported the 5 December launch of Inuktitut text-to-speech voices “Taqqiq” and “Siqiniq”. They were built from thousands of government documents, hired speakers' recordings and Bible Society and Nunavut Inuit Heritage Trust audio. The report noted presenters' accounts of the translator confusing “condo and condom, and prime rib and prime minister”. Voice contributor Leah Ayaruaq McKay said she plans to use it to help her husband learn Inuktitut. Government of Nunavut web pages were not available and are not among the sources. No cited source measures use, accuracy or an outcome for any user." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Microsoft Translator Inuktitut, Inuinnaqtun and romanized Inuktitut text translation (neural machine translation) and Inuktitut text-to-speech" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Microsoft (Azure Cognitive Services Translator and Speech) with the Government of Nunavut and community volunteers, including the Kitikmeot Heritage Society for Inuinnaqtun" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Microsoft Translator adds Inuktitut (2021), Inuinnaqtun and romanized Inuktitut (2022) and Inuktitut text-to-speech (2024) with the Government of Nunavut", "headline": "Microsoft Translator adds Inuktitut and Inuinnaqtun with Nunavut" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "824cfe9e0b6314ed4d617ecd8af812aec238077922fffe86888be49f238e040d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Microsoft added Inuktitut text translation to Microsoft Translator, Office and Translator for Bing on 27 January 2021. The date is from Arctic Portal, relaying the Microsoft Translator blog. Microsoft worked with the Government of Nunavut for language data; Inuktitut speakers volunteered to validate and test translations. VICE (18 February 2021) reported Nunavut language officials finding the output “riddled with mistakes”. Solomon Awa said: “Sometimes it's close, but sometimes it gave the opposite meaning, or one that was misleading”. Languages commissioner Karliin Aariak called it “a great tool to be like a first step”. Retired Université Laval researcher Louis-Jacques Dorais called it a “tour de force” despite a wrong test sentence. Nunatsiaq News (28 February 2022) reported Inuinnaqtun and romanized Inuktitut added during Uqausirmut Quviasuutiqarniq. Fewer than 600 speak Inuinnaqtun fluently, per the Kitikmeot Heritage Society. Microsoft's own feature (1 February 2022) says “Text translation is based on neural machine translation models”. It says the Government of Nunavut “turned to the community to help build and test the language models”. It lists intended uses (unilingual patients communicating with doctors, younger people with elders, emails in Office) without data. Nunatsiaq News (9 December 2024) reported the 5 December launch of Inuktitut text-to-speech voices “Taqqiq” and “Siqiniq”. They were built from thousands of government documents, hired speakers' recordings and Bible Society and Nunavut Inuit Heritage Trust audio. The report noted presenters' accounts of the translator confusing “condo and condom, and prime rib and prime minister”. Voice contributor Leah Ayaruaq McKay said she plans to use it to help her husband learn Inuktitut. Government of Nunavut web pages were not available and are not among the sources. No cited source measures use, accuracy or an outcome for any user.", "replication": { "produced_by": [ "Language data supplied by the Government of Nunavut and recordings by hired and volunteer speakers", "Volunteer fluent speakers validating and testing translations before launch" ], "must_hold": [ "Output is checked by a fluent speaker; Nunavut translators and the languages commissioner describe it as a first step needing review", "Dialect differences across the Arctic are tolerated by users of a standardized model" ], "echoes": [ { "date": "2022-02-28", "setting": "Inuinnaqtun and romanized Inuktitut added with updated Inuktitut models", "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/inuinnaqtun-and-romanized-inuktitut-added-to-microsoft-translator/" }, { "date": "2024-12-05", "setting": "Inuktitut text-to-speech voices launched in Iqaluit", "outcome": "unknown", "source": "https://nunatsiaq.com/stories/article/my-name-is-taqqiq-i-can-read-text-microsoft-translator-adds-inuktitut-text-to-speech/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0167", "title": "IdentiFlight automated curtailment at Top of the World cuts the eagle fatality rate by an estimated 50–82%, with wide uncertainty", "summary": "Peregrine Fund, WEST and USGS researchers estimated an 82% (75%–89%) relative cut in eagle deaths at a Wyoming wind farm after IdentiFlight curtailment; a 2023 reanalysis put it at 50% (−159%, 89%).", "date_observed": "2021-01-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "McClure et al. (Journal of Applied Ecology, Crossref publication date 31 January 2021) tested an automated curtailment system. The site was Top of the World Windpower Facility, Wyoming, USA. Authors are from The Peregrine Fund, Western EcoSystems Technology and the U.S. Geological Survey. The cameras detect and classify flying objects and decide whether to curtail individual turbines. The design was before–after–control–impact, with a control site 15 km away. Correcting for carcass detection probability, they estimated fatalities fell 63% at the treatment site (95% confidence interval, CI, 59%–66%). They rose 113% at the control site, an 82% (75%–89%) relative reduction. They noted fatalities were not eliminated. Recharge reported the claim on 28 January 2021. Huso and Dalthorp (Journal of Applied Ecology, 30 August 2023) reanalyzed the data and reported four major errors. Corrected, these give 50% (−159%, 89%), consistent with no effect. McClure et al. replied the same day that their data support the efficacy of automated curtailment. Duerr et al. (PLoS One, 26 January 2023) assessed an IdentiFlight installation in California. It correctly identified 77% of eagles and 85% of non-eagles, with 5,439 curtailment orders for non-eagle targets against 850 for eagles. The OECD AI Incidents Monitor logged the 82% result as a positive record.", "category": "general benefit", "unexpected": false, "purpose": "IdentiFlight is built to detect and classify flying eagles and curtail individual turbines to avoid collisions; reduced eagle fatalities are the intended outcome.", "system": "IdentiFlight automated eagle detection and turbine curtailment (camera system with machine-learning classification)", "model_version": null, "developer": "IdentiFlight (Boulder Imaging)", "deployer": "Top of the World Windpower Facility, Wyoming", "location": "Wyoming, United States", "domain": "Energy", "segment": "Wind power wildlife mitigation", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Reduced eagle fatalities are an aggregate estimate whose size is disputed; no individually attributable outcome is documented." }, { "group": "organizational", "depth": null, "reason": "The operator's benefit (fewer protected-species fatalities) is not quantified independently of the disputed estimate." } ], "ai_role": { "status": "assessed", "statement": "The system's classification decisions trigger curtailment, so any fatality reduction runs through the AI. The peer-reviewed estimate is independent of the maker but is challenged by a peer-reviewed reanalysis (50%, interval including zero). The California assessment shows 23% of eagles missed and six times more non-eagle than eagle curtailments. The size of the benefit is therefore unsettled." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "McClure, C. J. W., Rolek, B. W., Dunn, L., McCabe, J. 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J. W. et al., 'Reanalysis ignores pertinent data, includes inappropriate observations, and disregards realities of applied ecology: Response to Huso and Dalthorp (2023)', Journal of Applied Ecology (2023), doi:10.1111/1365-2664.14490", "title": "Reanalysis ignores pertinent data, includes inappropriate observations, and disregards realities of applied ecology: Response to Huso and Dalthorp (2023)", "url": "https://doi.org/10.1111/1365-2664.14490", "date": "2023-08-30", "written_by": "independent", "quote": "As we show here, our data do indeed provide support for the efficacy of automated curtailment." }, { "kind": "peer-reviewed study", "citation": "Duerr, A. E., Parsons, A. E., Nagy, L. R., Kuehn, M. J., Bloom, P. H., 'Effectiveness of an artificial intelligence-based system to curtail wind turbines to reduce eagle collisions', PLoS One (2023), doi:10.1371/journal.pone.0278754", "title": "Effectiveness of an artificial intelligence-based system to curtail wind turbines to reduce eagle collisions", "url": "https://doi.org/10.1371/journal.pone.0278754", "date": "2023-01-26", "written_by": "independent", "quote": "The system correctly identified 77% of eagles and 85% of non-eagles." }, { "kind": "news report", "citation": "Andrew Lee, 'Wind farm eagle deaths cut by 82% as smart cameras spot birds then halt turbines', Recharge, 28 January 2021", "title": "Wind farm eagle deaths 'cut by 82%' as smart cameras spot birds then halt turbines", "url": "https://www.rechargenews.com/wind/wind-farm-eagle-deaths-cut-by-82-as-smart-cameras-spot-birds-then-halt-turbines/2-1-953479", "date": "2021-01-28", "written_by": "independent", "quote": "Optical and machine-learning system that prompts 'informed curtailment' reduces fatalities in Wyoming test, it is claimed" }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2021-01-28-085c", "title": "AI System IdentiFlight Reduces Eagle Deaths at Wind Farms by 82%", "url": "https://oecd.ai/en/incidents/2021-01-28-085c", "date": "2021-01-28", "written_by": "independent", "quote": "has reduced eagle fatalities by 82% at wind farms, according to multiple studies." }, { "kind": "peer-reviewed study", "citation": "McClure, C. J. W., Rolek, B. W., Dunn, L., McCabe, J. D., Martinson, L., Katzner, T. E. (2022). Confirmation that eagle fatalities can be reduced by automated curtailment of wind turbines. Ecological Solutions and Evidence, published online 26 Aug 2022. doi:10.1002/2688-8319.12173", "title": "Confirmation that eagle fatalities can be reduced by automated curtailment of wind turbines", "url": "https://doi.org/10.1002/2688-8319.12173", "date": "2022-08-26", "written_by": "independent", "quote": "We demonstrate that eagle fatalities were reduced by 85% (95% highest density interval = 12%, 100%) after implementation of automated curtailment." }, { "kind": "peer-reviewed study", "citation": "McClure, C. J. W., Rolek, B. W., Dunn, L., McCabe, J. D., Martinson, L., Katzner, T. (2021). Eagle fatalities are reduced by automated curtailment of wind turbines. Journal of Applied Ecology 58(3): 446-452, as recorded in the USGS Publications Warehouse.", "title": "Eagle fatalities are reduced by automated curtailment of wind turbines", "url": "https://pubs.usgs.gov/publication/70219527", "date": "2021-01-28", "written_by": "independent", "quote": null }, { "kind": "peer-reviewed study", "citation": "Huso, M., Dalthorp, D. (2023). Reanalysis indicates little evidence of reduction in eagle mortality rate by automated curtailment of wind turbines. Journal of Applied Ecology, 30 August 2023, as recorded in the USGS Publications Warehouse.", "title": "Reanalysis indicates little evidence of reduction in eagle mortality rate by automated curtailment of wind turbines", "url": "https://pubs.usgs.gov/publication/70248352", "date": "2023-08-30", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Camera towers covering turbine airspace with per-turbine curtailment control", "Carcass searches corrected for detection probability at treatment and control sites", "A single post-treatment year at one site, which the reanalysis says limits causal inference" ], "must_hold": [ "Eagle abundance and flight behavior comparable to the Wyoming site", "Operators willing to accept curtailment losses, including misidentified non-eagle targets", "Longer, replicated monitoring to resolve the disputed effect size" ], "echoes": [ { "date": "2023-01-26", "setting": "IdentiFlight installation at a California wind project; identification accuracy and virtual curtailments measured, no fatality outcome", "model_version": null, "outcome": "unknown", "source": "https://doi.org/10.1371/journal.pone.0278754" }, { "date": "2022-09-20", "setting": "Germany, IdentiFlight cameras deployed for lesser spotted eagles", "model_version": null, "outcome": "unknown", "source": "https://oecd.ai/en/incidents/2022-09-20-caeb" }, { "date": "2022-08-26", "setting": "Same site, same authors, additional data and revised analysis", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1002/2688-8319.12173" } ] }, "paired_incident": null, "headline": "IdentiFlight cuts eagle deaths by an estimated 50–82%", "metric": "82% (75%–89%) relative cut in eagle deaths at a Wyoming wind farm", "comparator": { "against": "a control wind facility 15 km away without automated curtailment, before and after the installation", "before": "increasing at the control site by 113% (51%–218%)", "after": "the number of fatalities at the treatment site declined by 63% (95% CI = 59%–66%)", "basis": "measured", "quote": "After correcting for carcass detection probability and scaling fatality estimates to turbine‐years, we estimate that the number of fatalities at the treatment site declined by 63% (95% CI = 59%–66%) between before and after periods while increasing at the control site by 113% (51%–218%). 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(Journal of Applied Ecology, Crossref publication date 31 January 2021) tested an automated curtailment system. The site was Top of the World Windpower Facility, Wyoming, USA. Authors are from The Peregrine Fund, Western EcoSystems Technology and the U.S. Geological Survey. The cameras detect and classify flying objects and decide whether to curtail individual turbines. The design was before–after–control–impact, with a control site 15 km away. Correcting for carcass detection probability, they estimated fatalities fell 63% at the treatment site (95% confidence interval, CI, 59%–66%). They rose 113% at the control site, an 82% (75%–89%) relative reduction. They noted fatalities were not eliminated. Recharge reported the claim on 28 January 2021. Huso and Dalthorp (Journal of Applied Ecology, 30 August 2023) reanalyzed the data and reported four major errors. Corrected, these give 50% (−159%, 89%), consistent with no effect. McClure et al. replied the same day that their data support the efficacy of automated curtailment. Duerr et al. (PLoS One, 26 January 2023) assessed an IdentiFlight installation in California. It correctly identified 77% of eagles and 85% of non-eagles, with 5,439 curtailment orders for non-eagle targets against 850 for eagles. 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(Journal of Applied Ecology, Crossref publication date 31 January 2021) tested an automated curtailment system. The site was Top of the World Windpower Facility, Wyoming, USA. Authors are from The Peregrine Fund, Western EcoSystems Technology and the U.S. Geological Survey. The cameras detect and classify flying objects and decide whether to curtail individual turbines. The design was before–after–control–impact, with a control site 15 km away. Correcting for carcass detection probability, they estimated fatalities fell 63% at the treatment site (95% confidence interval, CI, 59%–66%). They rose 113% at the control site, an 82% (75%–89%) relative reduction. They noted fatalities were not eliminated. Recharge reported the claim on 28 January 2021. Huso and Dalthorp (Journal of Applied Ecology, 30 August 2023) reanalyzed the data and reported four major errors. Corrected, these give 50% (−159%, 89%), consistent with no effect. McClure et al. replied the same day that their data support the efficacy of automated curtailment. Duerr et al. (PLoS One, 26 January 2023) assessed an IdentiFlight installation in California. It correctly identified 77% of eagles and 85% of non-eagles, with 5,439 curtailment orders for non-eagle targets against 850 for eagles. 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(Journal of Applied Ecology, Crossref publication date 31 January 2021) tested an automated curtailment system. The site was Top of the World Windpower Facility, Wyoming, USA. Authors are from The Peregrine Fund, Western EcoSystems Technology and the U.S. Geological Survey. The cameras detect and classify flying objects and decide whether to curtail individual turbines. The design was before–after–control–impact, with a control site 15 km away. Correcting for carcass detection probability, they estimated fatalities fell 63% at the treatment site (95% confidence interval, CI, 59%–66%). They rose 113% at the control site, an 82% (75%–89%) relative reduction. They noted fatalities were not eliminated. Recharge reported the claim on 28 January 2021. Huso and Dalthorp (Journal of Applied Ecology, 30 August 2023) reanalyzed the data and reported four major errors. Corrected, these give 50% (−159%, 89%), consistent with no effect. McClure et al. replied the same day that their data support the efficacy of automated curtailment. Duerr et al. (PLoS One, 26 January 2023) assessed an IdentiFlight installation in California. It correctly identified 77% of eagles and 85% of non-eagles, with 5,439 curtailment orders for non-eagle targets against 850 for eagles. The OECD AI Incidents Monitor logged the 82% result as a positive record.", "replication": { "produced_by": [ "Camera towers covering turbine airspace with per-turbine curtailment control", "Carcass searches corrected for detection probability at treatment and control sites", "A single post-treatment year at one site, which the reanalysis says limits causal inference" ], "must_hold": [ "Eagle abundance and flight behavior comparable to the Wyoming site", "Operators willing to accept curtailment losses, including misidentified non-eagle targets", "Longer, replicated monitoring to resolve the disputed effect size" ], "echoes": [ { "date": "2023-01-26", "setting": "IdentiFlight installation at a California wind project; identification accuracy and virtual curtailments measured, no fatality outcome", "outcome": "unknown", "source": "https://doi.org/10.1371/journal.pone.0278754" }, { "date": "2022-09-20", "setting": "Germany, IdentiFlight cameras deployed for lesser spotted eagles", "outcome": "unknown", "source": "https://oecd.ai/en/incidents/2022-09-20-caeb" }, { "date": "2022-08-26", "setting": "Same site, same authors, additional data and revised analysis", "outcome": "recurred", "source": "https://doi.org/10.1002/2688-8319.12173" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0356", "title": "Rainforest Connection's Guardian acoustic AI sends chainsaw alerts to community patrols; logging in West Sumatra may have stopped as a result", "summary": "RFCx Guardian sensors detect chainsaws with AI and alert patrols; a 2021 Reuters report from Solok, West Sumatra quotes a patroller that logging stopped. No dated intervention is documented.", "date_observed": "2021-02-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Rainforest Connection (RFCx), a US non-profit founded by Topher White, deploys solar-powered “Guardian” acoustic sensors. In its own words, they use “sound & artificial intelligence” to track chainsaws, vehicle engines, hunting dogs and gunshots. They send real-time alerts to a mobile app so that “an agent nearby” can respond. RFCx states it has protected over 726,000 (impact page) or 750,000 (guardian page) hectares across 8,662+ projects in 137 countries. The only non-vendor account read is a Thomson Reuters Foundation report published by The Straits Times on 11 February 2021. It is from Solok regency, West Sumatra, Indonesia, where 27 Guardian sensors had been installed more than a year earlier. Audio streams are analyzed by AI trained to pick out chainsaw sounds, and an alert goes to community patrols. Patroller Jasrialdi said logging “has totally stopped” in the area. The head of West Sumatra's forestry department, Yozarwardi Usama Putra, said he would like to expand the “early-warning system”. The same report attributes the decline in logging to a wider enforcement crackdown as well. It says RFCx planned to collect data for peer review to prove the system curbs logging. No park authority, ministry or court document records a specific alert leading to an interception, so no event is recorded.", "category": "general benefit", "unexpected": false, "purpose": "Real-time acoustic detection of illegal logging and poaching sounds so that rangers or community patrols can respond; the reported benefit is the intended one.", "system": "Rainforest Connection Guardian bioacoustic monitoring with cloud AI sound classification and app alerts", "model_version": "Guardian G1 (2015-2019, repurposed smartphones), G2 (2020-2025), G3 (2026-present) per rfcx.org", "developer": "Rainforest Connection (RFCx)", "deployer": "Community forest patrols and the West Sumatra forestry department (Solok regency, Indonesia); RFCx partners in other countries", "location": "Solok regency, West Sumatra, Indonesia (reported deployment); global program", "domain": "Forest protection and anti-poaching", "segment": "Non-profit conservation technology with community and government partners", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome is documented." }, { "group": "organizational", "depth": null, "reason": "The West Sumatra patrol's reported easier work is not tied to a dated alert or action." }, { "group": "societal", "depth": null, "reason": "RFCx's hectare figures are self-reported aggregates with no independent evaluation." } ], "ai_role": { "status": "assessed", "statement": "RFCx's own pages describe AI classification of streamed audio generating app alerts for responders. The 2021 Reuters report confirms the mechanism at the Solok site: AI picks out chainsaw sounds and patrols are alerted. It quotes a patroller that logging stopped, while also crediting a government enforcement crackdown. Apart from that single news item, only the maker's account is among the sources. No park authority, ministry or court record of an AI-triggered interception was found. RFCx itself said in 2021 that peer-review data to prove the effect was still being collected." }, "evidence": [ { "kind": "press release", "citation": "Rainforest Connection (n.d.). Real-Time Threat Detection (Guardian). rfcx.org, fetched 20 Oct 2026.", "title": "Real-Time Threat Detection", "url": "https://rfcx.org/guardian", "date": null, "written_by": "makers", "quote": "An agent nearby receives a real-time alert of the detected threat via our app, enabling rapid response before any damage can occur." }, { "kind": "press release", "citation": "Rainforest Connection (n.d.). Impact & Partnerships. rfcx.org, fetched 20 Oct 2026.", "title": "Impact & Partnerships", "url": "https://rfcx.org/impact", "date": null, "written_by": "makers", "quote": "We work closely with NGOs and governmental organizations, including WWF, IUCN, Conservation International, the Jane Goodall Institute and the United Nations, to strengthen on-the-ground protection" }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging. The Straits Times, 11 Feb 2021.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "If the system hears a chainsaw, it sends an alert via an app to community patrols, who can check on the ground for logging." }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Same report, patroller statement.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging (patroller quote)", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "(Logging) has totally stopped - people are afraid of coming to this area" } ], "replication": { "produced_by": [ "Acoustic sensors with mobile-network or satellite uplink placed in forest canopy", "Cloud AI classifier trained on chainsaw and other threat sounds", "Community patrols or rangers able to reach alert locations", "Parallel government enforcement crackdown in the reported area" ], "must_hold": [ "Network coverage or satellite link at the sensor site", "Patrol capacity to respond to alerts on the ground", "Low false-alert rate so responders keep acting", "Independent evaluation to separate the sensor effect from enforcement" ], "echoes": [ { "date": null, "setting": "Tembé indigenous territory, Brazil, Guardian units used by indigenous rangers against illegal logging (RFCx guardian page)", "model_version": null, "outcome": "unknown", "source": "https://rfcx.org/guardian" }, { "date": null, "setting": "Vancouver shipping lanes (whales) and a Greek national park (gunshots), per the 2021 Reuters report", "model_version": null, "outcome": "unknown", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging" } ] }, "paired_incident": null, "headline": "RFCx Guardian alerts may have stopped logging in Solok", "metric": null, "comparator": { "against": "logging in the area before the sensors (amid a wider enforcement crackdown)", "before": null, "after": "(Logging) has totally stopped", "basis": "assumed", "quote": "\"(Logging) has totally stopped - people are afraid of coming to this area,\" said patroller Jasrialdi, who goes by one name like many Indonesians.", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging" }, "later": { "status": "unknown", "date": null, "note": "The 2021 report says RFCx planned to collect data for peer review that year; nothing dated after 11 February 2021 about Solok was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Indonesia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://projects.propublica.org/nonprofits/search?q=rainforest+connection; https://dishut.sumbarprov.go.id/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0356", "catalog_version": "1.0.0", "source_fingerprint": "1692d66dd5159d9e6b4caecbeb60c423c7f3bd62e6050b1ae6009910c1d99a4f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0356-source-0001", "AIBD-0356-source-0002", "AIBD-0356-source-0003", "AIBD-0356-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Rainforest Connection (RFCx)", "deployer": "Community forest patrols and the West Sumatra forestry department (Solok regency, Indonesia); RFCx partners in other countries" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "RFCx's own pages describe AI classification of streamed audio generating app alerts for responders. 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"infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Rainforest Connection (RFCx), a US non-profit founded by Topher White, deploys solar-powered “Guardian” acoustic sensors. In its own words, they use “sound & artificial intelligence” to track chainsaws, vehicle engines, hunting dogs and gunshots. They send real-time alerts to a mobile app so that “an agent nearby” can respond. RFCx states it has protected over 726,000 (impact page) or 750,000 (guardian page) hectares across 8,662+ projects in 137 countries. The only non-vendor account read is a Thomson Reuters Foundation report published by The Straits Times on 11 February 2021. It is from Solok regency, West Sumatra, Indonesia, where 27 Guardian sensors had been installed more than a year earlier. Audio streams are analyzed by AI trained to pick out chainsaw sounds, and an alert goes to community patrols. Patroller Jasrialdi said logging “has totally stopped” in the area. The head of West Sumatra's forestry department, Yozarwardi Usama Putra, said he would like to expand the “early-warning system”. The same report attributes the decline in logging to a wider enforcement crackdown as well. It says RFCx planned to collect data for peer review to prove the system curbs logging. No park authority, ministry or court document records a specific alert leading to an interception, so no event is recorded.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual outcome is documented." }, { "group": "organizational", "reason": "The West Sumatra patrol's reported easier work is not tied to a dated alert or action." }, { "group": "societal", "reason": "RFCx's hectare figures are self-reported aggregates with no independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Real-time acoustic detection of illegal logging and poaching sounds so that rangers or community patrols can respond; the reported benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Solok regency, West Sumatra, Indonesia (reported deployment); global program", "developer_country": "United States", "deployer_country": "Indonesia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Real-time acoustic detection of illegal logging and poaching sounds so that rangers or community patrols can respond; the reported benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-02-11", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://projects.propublica.org/nonprofits/search?q=rainforest+connection; https://dishut.sumbarprov.go.id/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Acoustic sensors with mobile-network or satellite uplink placed in forest canopy", "Cloud AI classifier trained on chainsaw and other threat sounds", "Community patrols or rangers able to reach alert locations", "Parallel government enforcement crackdown in the reported area" ], "must_hold": [ "Network coverage or satellite link at the sensor site", "Patrol capacity to respond to alerts on the ground", "Low false-alert rate so responders keep acting", "Independent evaluation to separate the sensor effect from enforcement" ], "echoes": [ { "setting": "Tembé indigenous territory, Brazil, Guardian units used by indigenous rangers against illegal logging (RFCx guardian page)", "outcome": "unknown", "source": "https://rfcx.org/guardian" }, { "setting": "Vancouver shipping lanes (whales) and a Greek national park (gunshots), per the 2021 Reuters report", "outcome": "unknown", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Acoustic sensors with mobile-network or satellite uplink placed in forest canopy", "Cloud AI classifier trained on chainsaw and other threat sounds", "Community patrols or rangers able to reach alert locations", "Parallel government enforcement crackdown in the reported area" ], "must_hold": [ "Network coverage or satellite link at the sensor site", "Patrol capacity to respond to alerts on the ground", "Low false-alert rate so responders keep acting", "Independent evaluation to separate the sensor effect from enforcement" ], "echoes": [ { "setting": "Tembé indigenous territory, Brazil, Guardian units used by indigenous rangers against illegal logging (RFCx guardian page)", "outcome": "unknown", "source": "https://rfcx.org/guardian" }, { "setting": "Vancouver shipping lanes (whales) and a Greek national park (gunshots), per the 2021 Reuters report", "outcome": "unknown", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://projects.propublica.org/nonprofits/search?q=rainforest+connection; https://dishut.sumbarprov.go.id/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Forest protection and anti-poaching", "segment": "Non-profit conservation technology with community and government partners" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Rainforest Connection (n.d.). Real-Time Threat Detection (Guardian). rfcx.org, fetched 20 Oct 2026.", "title": "Real-Time Threat Detection", "url": "https://rfcx.org/guardian", "written_by": "makers", "quote": "An agent nearby receives a real-time alert of the detected threat via our app, enabling rapid response before any damage can occur." }, { "kind": "press release", "citation": "Rainforest Connection (n.d.). Impact & Partnerships. rfcx.org, fetched 20 Oct 2026.", "title": "Impact & Partnerships", "url": "https://rfcx.org/impact", "written_by": "makers", "quote": "We work closely with NGOs and governmental organizations, including WWF, IUCN, Conservation International, the Jane Goodall Institute and the United Nations, to strengthen on-the-ground protection" }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging. The Straits Times, 11 Feb 2021.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "If the system hears a chainsaw, it sends an alert via an app to community patrols, who can check on the ground for logging." }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Same report, patroller statement.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging (patroller quote)", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "(Logging) has totally stopped - people are afraid of coming to this area" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0356-source-0001", "AIBD-0356-source-0002", "AIBD-0356-source-0003", "AIBD-0356-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Rainforest Connection (n.d.). Real-Time Threat Detection (Guardian). rfcx.org, fetched 20 Oct 2026.", "title": "Real-Time Threat Detection", "url": "https://rfcx.org/guardian", "written_by": "makers", "quote": "An agent nearby receives a real-time alert of the detected threat via our app, enabling rapid response before any damage can occur." }, { "kind": "press release", "citation": "Rainforest Connection (n.d.). Impact & Partnerships. rfcx.org, fetched 20 Oct 2026.", "title": "Impact & Partnerships", "url": "https://rfcx.org/impact", "written_by": "makers", "quote": "We work closely with NGOs and governmental organizations, including WWF, IUCN, Conservation International, the Jane Goodall Institute and the United Nations, to strengthen on-the-ground protection" }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging. The Straits Times, 11 Feb 2021.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "If the system hears a chainsaw, it sends an alert via an app to community patrols, who can check on the ground for logging." }, { "kind": "news report", "citation": "Thomson Reuters Foundation (2021). Same report, patroller statement.", "title": "Treetop sensors help Indonesia eavesdrop on forests to curb illegal logging (patroller quote)", "url": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging", "date": "2021-02-11", "written_by": "independent", "quote": "(Logging) has totally stopped - people are afraid of coming to this area" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "RFCx Guardian sensors detect chainsaws with AI and alert patrols; a 2021 Reuters report from Solok, West Sumatra quotes a patroller that logging stopped. No dated intervention is documented.", "account": "Rainforest Connection (RFCx), a US non-profit founded by Topher White, deploys solar-powered “Guardian” acoustic sensors. In its own words, they use “sound & artificial intelligence” to track chainsaws, vehicle engines, hunting dogs and gunshots. They send real-time alerts to a mobile app so that “an agent nearby” can respond. RFCx states it has protected over 726,000 (impact page) or 750,000 (guardian page) hectares across 8,662+ projects in 137 countries. The only non-vendor account read is a Thomson Reuters Foundation report published by The Straits Times on 11 February 2021. It is from Solok regency, West Sumatra, Indonesia, where 27 Guardian sensors had been installed more than a year earlier. Audio streams are analyzed by AI trained to pick out chainsaw sounds, and an alert goes to community patrols. Patroller Jasrialdi said logging “has totally stopped” in the area. The head of West Sumatra's forestry department, Yozarwardi Usama Putra, said he would like to expand the “early-warning system”. The same report attributes the decline in logging to a wider enforcement crackdown as well. It says RFCx planned to collect data for peer review to prove the system curbs logging. No park authority, ministry or court document records a specific alert leading to an interception, so no event is recorded." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The system classified recorded sounds and alerted responders to possible logging." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Guardian G1 used repurposed smartphones in 2015–2019. Later deployments used G2 from 2020 and G3 from 2026." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Guardian G1 (2015-2019, repurposed smartphones), G2 (2020-2025), G3 (2026-present) per rfcx.org" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Rainforest Connection Guardian bioacoustic monitoring with cloud AI sound classification and app alerts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rainforest Connection (RFCx)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rainforest Connection's Guardian acoustic AI sends chainsaw alerts to community patrols; logging in West Sumatra may have stopped as a result", "headline": "RFCx Guardian alerts may have stopped logging in Solok" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1692d66dd5159d9e6b4caecbeb60c423c7f3bd62e6050b1ae6009910c1d99a4f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Rainforest Connection (RFCx), a US non-profit founded by Topher White, deploys solar-powered “Guardian” acoustic sensors. In its own words, they use “sound & artificial intelligence” to track chainsaws, vehicle engines, hunting dogs and gunshots. They send real-time alerts to a mobile app so that “an agent nearby” can respond. RFCx states it has protected over 726,000 (impact page) or 750,000 (guardian page) hectares across 8,662+ projects in 137 countries. The only non-vendor account read is a Thomson Reuters Foundation report published by The Straits Times on 11 February 2021. It is from Solok regency, West Sumatra, Indonesia, where 27 Guardian sensors had been installed more than a year earlier. Audio streams are analyzed by AI trained to pick out chainsaw sounds, and an alert goes to community patrols. Patroller Jasrialdi said logging “has totally stopped” in the area. The head of West Sumatra's forestry department, Yozarwardi Usama Putra, said he would like to expand the “early-warning system”. The same report attributes the decline in logging to a wider enforcement crackdown as well. It says RFCx planned to collect data for peer review to prove the system curbs logging. No park authority, ministry or court document records a specific alert leading to an interception, so no event is recorded.", "replication": { "produced_by": [ "Acoustic sensors with mobile-network or satellite uplink placed in forest canopy", "Cloud AI classifier trained on chainsaw and other threat sounds", "Community patrols or rangers able to reach alert locations", "Parallel government enforcement crackdown in the reported area" ], "must_hold": [ "Network coverage or satellite link at the sensor site", "Patrol capacity to respond to alerts on the ground", "Low false-alert rate so responders keep acting", "Independent evaluation to separate the sensor effect from enforcement" ], "echoes": [ { "setting": "Tembé indigenous territory, Brazil, Guardian units used by indigenous rangers against illegal logging (RFCx guardian page)", "outcome": "unknown", "source": "https://rfcx.org/guardian" }, { "setting": "Vancouver shipping lanes (whales) and a Greek national park (gunshots), per the 2021 Reuters report", "outcome": "unknown", "source": "https://www.straitstimes.com/asia/se-asia/treetop-sensors-help-indonesia-eavesdrop-on-forests-to-curb-illegal-logging" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0324", "title": "Shanghai's Nanjing Building digital twin (Huangpu District with Huawei) alerts a guard to an opened third-floor window; a sensor, not AI, detected it and the anecdote carries three dates", "summary": "A Huawei-hosted launch on 25 Feb 2021 presented a window-opening alert sent to a guard's wristband. Knews and Jiefang Daily say that a window sensor detected it; the story is retold with three dates.", "date_observed": "2021-02-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry says Shanghai, with Huawei, launched an AI-powered digital twin in the Nanjing Building. It says the twin “detected a high-risk behavior (open window), alerted security, and enabled immediate intervention”. The anecdote appears in Eastday (reporter Xue Ningwei, 25 Feb 2021, via Sohu). During Spring Festival a customer on the third floor opened a window and held a phone out to photograph Nanjing Road. A guard arrived to stop it. Eastday says how the guard knew was “revealed at today's launch”, the “Shanghai city minimum management unit digital governance” release. It was held at the Huangpu District city operations center, hosted by Huawei Technologies per smartcity.team (1 Mar 2021). Jiefang Daily (7 May 2021, via GMW) retells the same window scene during the May Day holiday, naming guard Fan Tianyu. Banyuetan/Xinhua (reporter Zhou Lin, 6 Jul 2021, via The Paper) retells it during the Dragon Boat holiday with the same guard and wording. No single date can be fixed. The Cyberspace Administration of China repost (4 Mar 2021) phrases it conditionally (“if a visitor opens a window...”). The only witnessed detection was a Knews reporter's deliberate “open window” test at the launch. Huawei engineer Chen Tao also simulated smoking there for the camera algorithm. Both Knews and Jiefang Daily say a window-mounted sensor detected the opening and pushed an alert to the guard's wristband through the digital twin. The AI algorithms described (20-plus per Knews and Jiefang Daily, 50-plus per Eastday) run on the 170-plus cameras for smoking, crowd flow and bike parking. Jiefang Daily reports 995 door/window alerts from January to May 2021. It quotes an official that over 80% were triggered by visitors trying the IoT devices. The building is Huawei's flagship store. No harm occurred and no beneficiary is identifiable. The deployment itself is well documented (Huangpu District and Huawei, built January 2021; 17 device categories, 80-plus sensor sets, 170-plus cameras). No English-language report was found, and the China Central Television (CCTV-2) segment is not among the sources. The system's zhiding.cn copy is marked “industry-supplied copy”.", "category": "general benefit", "unexpected": false, "purpose": "The digital twin was built to monitor the building's “vital signs” (vibration, smoke, lifts, crowd flow, open windows) and push alerts to staff. Window opening was named at the launch as a falling-object risk the system flags.", "system": "Nanjing Building 1:1 'living' digital twin on Huawei Cloud: 80-plus IoT sensor sets in 17 categories, 170-plus cameras, and 20-plus (Knews, Jiefang Daily) or 50-plus (Eastday) AI algorithms for smoking, crowd-flow and parking detection", "model_version": null, "developer": "Huawei (Huawei Cloud, big data, AI, edge computing) with Huangpu District government under the Shanghai City Operations Management Center", "deployer": "Huangpu District City Operations Center and the Nanjing Building's operator (the Huawei flagship store)", "location": "Nanjing Building, Nanjing Road East at Henan Road Central, Huangpu District, Shanghai, China", "domain": "Urban governance and building safety", "segment": "Smart-building monitoring under Shanghai's 'one network to manage all'", "benefit_type": "Increased Product Safety", "taxonomy_note": "The detection is attributed to a window contact sensor routed through the digital twin, and the anecdote is a launch vignette.", "registry_ids": { "oecd_aim": "2021-02-25-adca" }, "ratings": [ { "group": "societal", "depth": null, "reason": "No pedestrian was shown at risk and no falling object occurred; the only documented trigger was a reporter's test, so no outcome is documented." }, { "group": "organizational", "depth": null, "reason": "Jiefang Daily reports 995 door/window alerts handled in January to May 2021. It says that over 80% were visitors trying the devices and that real events were far fewer. No efficiency measure is given." } ], "ai_role": { "status": "assessed", "statement": "For the window alert the sources document a window-mounted sensor whose signal passes through the Huawei Cloud digital twin to a guard's wristband. Knews and Jiefang Daily both say so, and neither attributes the detection to an AI algorithm. The 20- to 50-plus AI algorithms described run on cameras for smoking, crowd flow and bike parking. The one smoking alert shown at the launch was simulated by a Huawei engineer. The Monitor's statement that an AI system “detected a high-risk behavior (open window)” is therefore unsupported by its own sources." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2021-02-25-adca, 'Shanghai Deploys AI Digital Twin for Real-Time Urban Safety Management' (AI-generated summary).", "title": "Shanghai Deploys AI Digital Twin for Real-Time Urban Safety Management", "url": "https://oecd.ai/en/incidents/2021-02-25-adca", "date": "2021-02-25", "written_by": "independent", "quote": "The system detected a high-risk behavior (open window), alerted security, and enabled immediate intervention, preventing potential harm to pedestrians." }, { "kind": "news report", "citation": "Eastday (Xue Ningwei), 25 February 2021, '改变从一栋楼开始！上海\"一网统管\"探索城市最小管理单元数字治理', via Sohu.", "title": "改变从一栋楼开始！上海“一网统管”探索城市最小管理单元数字治理", "url": "https://www.sohu.com/a/452580009_120823584", "date": "2021-02-25", "written_by": "independent", "quote": "春节期间，一位被美丽街景吸引的顾客走到3楼打开窗户，将手机探出窗外拍照，这一具有潜在高空坠物风险的举动被随即而来的店内保安制止。" }, { "kind": "news report", "citation": "Knews / Shanghai Media Group, 25 February 2021, '南京大楼，如何实现\"数字孪生\"？', via NetEase (163.com).", "title": "南京大楼，如何实现“数字孪生”？", "url": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html", "date": "2021-02-25", "written_by": "independent", "quote": "通过这个小小的开窗传感器，就能将开窗信息实时回传给数字孪生系统" }, { "kind": "news report", "citation": "Jiefang Daily, 7 May 2021, '传感器如\"五官\"，南京大楼在数字世界\"活\"了', via Guangming Online (GMW).", "title": "传感器如“五官”，南京大楼在数字世界“活”了", "url": "https://tech.gmw.cn/2021-05/07/content_34826280.htm", "date": "2021-05-07", "written_by": "independent", "quote": "超过八成都是参观者体验物联设备时所触发的，真实事件远没有数据体现得那么多" }, { "kind": "news report", "citation": "Banyuetan / Xinhua (Zhou Lin), 6 July 2021, '\"数字孪生城市\"来了：城市治理可望告别\"盲人摸象\"', via The Paper.", "title": "“数字孪生城市”来了：城市治理可望告别“盲人摸象”", "url": "https://m.thepaper.cn/newsDetail_forward_13463904", "date": "2021-07-06", "written_by": "independent", "quote": "安装在窗户上的传感器第一时间监测到开窗行为，店内保安范天玉佩戴的智能手环立即接到系统自动报警" }, { "kind": "news report", "citation": "Cyberspace Administration of China, 4 March 2021, repost of '改变从一栋楼开始！上海\"一网统管\"探索城市最小管理单元数字治理' from the 'Cyberspace Shanghai' WeChat account.", "title": "改变从一栋楼开始！上海“一网统管”探索城市最小管理单元数字治理", "url": "https://www.cac.gov.cn/2021-03/04/c_1616435886725223.htm", "date": "2021-03-04", "written_by": "independent", "quote": "就会第一时间检测到高空坠物隐患", "supports_benefit": false }, { "kind": "news report", "citation": "smartcity.team, 1 March 2021, '上海：城市最小管理单元数字治理成果发布，数字治理助力一网统管' (case write-up of the 25 February 2021 launch).", "title": "上海：城市最小管理单元数字治理成果发布，数字治理助力一网统管", "url": "https://www.smartcity.team/cases/smartcitycases/shanghaichengshizuixiaoguanlidanyuan/", "date": "2021-03-01", "written_by": "independent", "quote": "由华为技术有限公司主办", "supports_benefit": false }, { "kind": "press release", "citation": "zhiding.cn (big-data channel), 25 February 2021, '上海\"一网统管\"发布城市最小管理单元数字治理成果', marked '来源：业界供稿' (industry-supplied copy).", "title": "上海“一网统管”发布城市最小管理单元数字治理成果", "url": "http://big-data.zhiding.cn/2021/0225/3132347.shtml", "date": "2021-02-25", "written_by": "makers", "quote": "来源：业界供稿" } ], "replication": { "produced_by": [ "Window-mounted contact sensors reporting to the building's digital twin", "An alert pushed to a security guard's smart wristband", "A guard on site who closes the window" ], "must_hold": [ "A real, not visitor-triggered, window opening: Jiefang Daily reports that over 80% of 995 logged door/window alerts were visitors trying the devices", "An identifiable risk to pedestrians below, which no source documents" ], "echoes": [ { "date": "2021-02-25", "setting": "Knews reporter's deliberate “open window” test at the Huangpu District city operations center launch", "model_version": null, "outcome": "recurred", "source": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html" }, { "date": null, "setting": "Same window anecdote retold by Jiefang Daily as a May Day holiday event (guard Fan Tianyu) and by Banyuetan as a Dragon Boat holiday event", "model_version": null, "outcome": "unknown", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" } ] }, "paired_incident": null, "headline": "Huawei digital twin's window alert comes from a sensor, not AI", "metric": "995 door/window alerts from January to May 2021", "comparator": null, "later": { "status": "persisted", "date": "2021-05-07", "note": "Jiefang Daily reported that from January to early May 2021 the digital twin had logged 995 door/window alerts, 439 smoking alerts and 55 fire-lane obstruction alerts, while an official said more than 80% of the handled events were triggered by visitors trying the IoT devices.", "quote": "从今年1月至今，南京大楼“数字孪生”已积累超过50万条数据，处置吸烟告警439次、消防通道阻挡55次、开门开窗告警995次。不过据相关负责人透露，这些处置的事件中，超过八成都是参观者体验物联设备时所触发的，真实事件远没有数据体现得那么多。", "url": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" }, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Huawei; https://en.wikipedia.org/wiki/Huangpu,_Shanghai", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://oecd.ai/en/incidents/2021-02-25-adca", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports, a registry entry and the makers' press release. For the benefit itself, the cited sources include no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0324", "catalog_version": "1.0.0", "source_fingerprint": "8669bbed86919d4c8309ae6c1e79acccd087298e13f3e76750b2c908666b88be", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0324-source-0001", "AIBD-0324-source-0002", "AIBD-0324-source-0003", "AIBD-0324-source-0004", "AIBD-0324-source-0005", "AIBD-0324-source-0006", "AIBD-0324-source-0007", "AIBD-0324-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Huawei (Huawei Cloud, big data, AI, edge computing) with Huangpu District government under the Shanghai City Operations Management Center", "deployer": "Huangpu District City Operations Center and the Nanjing Building's operator (the Huawei flagship store)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "For the window alert the sources document a window-mounted sensor whose signal passes through the Huawei Cloud digital twin to a guard's wristband. Knews and Jiefang Daily both say so, and neither attributes the detection to an AI algorithm. The 20- to 50-plus AI algorithms described run on cameras for smoking, crowd flow and bike parking. The one smoking alert shown at the launch was simulated by a Huawei engineer. The Monitor's statement that an AI system “detected a high-risk behavior (open window)” is therefore unsupported by its own sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "For the window alert the sources document a window-mounted sensor whose signal passes through the Huawei Cloud digital twin to a guard's wristband. Knews and Jiefang Daily both say so, and neither attributes the detection to an AI algorithm. The 20- to 50-plus AI algorithms described run on cameras for smoking, crowd flow and bike parking. The one smoking alert shown at the launch was simulated by a Huawei engineer. The Monitor's statement that an AI system “detected a high-risk behavior (open window)” is therefore unsupported by its own sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports, a registry entry and the makers' press release. For the benefit itself, the cited sources include no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No pedestrian was shown at risk and no falling object occurred; the only documented trigger was a reporter's test, so no outcome is documented." }, { "group": "organizational", "reason": "Jiefang Daily reports 995 door/window alerts handled in January to May 2021. It says that over 80% were visitors trying the devices and that real events were far fewer. No efficiency measure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No pedestrian was shown at risk and no falling object occurred; the only documented trigger was a reporter's test, so no outcome is documented." }, { "group": "organizational", "reason": "Jiefang Daily reports 995 door/window alerts handled in January to May 2021. It says that over 80% were visitors trying the devices and that real events were far fewer. No efficiency measure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "995 door/window alerts from January to May 2021", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2021-02-25-adca" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2021-05-07", "note": "Jiefang Daily reported that from January to early May 2021 the digital twin had logged 995 door/window alerts, 439 smoking alerts and 55 fire-lane obstruction alerts, while an official said more than 80% of the handled events were triggered by visitors trying the IoT devices.", "quote": "从今年1月至今，南京大楼“数字孪生”已积累超过50万条数据，处置吸烟告警439次、消防通道阻挡55次、开门开窗告警995次。不过据相关负责人透露，这些处置的事件中，超过八成都是参观者体验物联设备时所触发的，真实事件远没有数据体现得那么多。", "url": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0324" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "The detection is attributed to a window contact sensor routed through the digital twin, and the anecdote is a launch vignette." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry says Shanghai, with Huawei, launched an AI-powered digital twin in the Nanjing Building. It says the twin “detected a high-risk behavior (open window), alerted security, and enabled immediate intervention”. The anecdote appears in Eastday (reporter Xue Ningwei, 25 Feb 2021, via Sohu). During Spring Festival a customer on the third floor opened a window and held a phone out to photograph Nanjing Road. A guard arrived to stop it. Eastday says how the guard knew was “revealed at today's launch”, the “Shanghai city minimum management unit digital governance” release. It was held at the Huangpu District city operations center, hosted by Huawei Technologies per smartcity.team (1 Mar 2021). Jiefang Daily (7 May 2021, via GMW) retells the same window scene during the May Day holiday, naming guard Fan Tianyu. Banyuetan/Xinhua (reporter Zhou Lin, 6 Jul 2021, via The Paper) retells it during the Dragon Boat holiday with the same guard and wording. No single date can be fixed. The Cyberspace Administration of China repost (4 Mar 2021) phrases it conditionally (“if a visitor opens a window...”). The only witnessed detection was a Knews reporter's deliberate “open window” test at the launch. Huawei engineer Chen Tao also simulated smoking there for the camera algorithm. Both Knews and Jiefang Daily say a window-mounted sensor detected the opening and pushed an alert to the guard's wristband through the digital twin. The AI algorithms described (20-plus per Knews and Jiefang Daily, 50-plus per Eastday) run on the 170-plus cameras for smoking, crowd flow and bike parking. Jiefang Daily reports 995 door/window alerts from January to May 2021. It quotes an official that over 80% were triggered by visitors trying the IoT devices. The building is Huawei's flagship store. No harm occurred and no beneficiary is identifiable. The deployment itself is well documented (Huangpu District and Huawei, built January 2021; 17 device categories, 80-plus sensor sets, 170-plus cameras). No English-language report was found, and the China Central Television (CCTV-2) segment is not among the sources. The system's zhiding.cn copy is marked “industry-supplied copy”.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No pedestrian was shown at risk and no falling object occurred; the only documented trigger was a reporter's test, so no outcome is documented." }, { "group": "organizational", "reason": "Jiefang Daily reports 995 door/window alerts handled in January to May 2021. It says that over 80% were visitors trying the devices and that real events were far fewer. No efficiency measure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The digital twin was built to monitor the building's “vital signs” (vibration, smoke, lifts, crowd flow, open windows) and push alerts to staff. Window opening was named at the launch as a falling-object risk the system flags." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Nanjing Building, Nanjing Road East at Henan Road Central, Huangpu District, Shanghai, China", "developer_country": "China", "deployer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The digital twin was built to monitor the building's “vital signs” (vibration, smoke, lifts, crowd flow, open windows) and push alerts to staff. Window opening was named at the launch as a falling-object risk the system flags." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-02-25", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Huawei; https://en.wikipedia.org/wiki/Huangpu,_Shanghai", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://oecd.ai/en/incidents/2021-02-25-adca", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Window-mounted contact sensors reporting to the building's digital twin", "An alert pushed to a security guard's smart wristband", "A guard on site who closes the window" ], "must_hold": [ "A real, not visitor-triggered, window opening: Jiefang Daily reports that over 80% of 995 logged door/window alerts were visitors trying the devices", "An identifiable risk to pedestrians below, which no source documents" ], "echoes": [ { "date": "2021-02-25", "setting": "Knews reporter's deliberate “open window” test at the Huangpu District city operations center launch", "outcome": "recurred", "source": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html" }, { "setting": "Same window anecdote retold by Jiefang Daily as a May Day holiday event (guard Fan Tianyu) and by Banyuetan as a Dragon Boat holiday event", "outcome": "unknown", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Window-mounted contact sensors reporting to the building's digital twin", "An alert pushed to a security guard's smart wristband", "A guard on site who closes the window" ], "must_hold": [ "A real, not visitor-triggered, window opening: Jiefang Daily reports that over 80% of 995 logged door/window alerts were visitors trying the devices", "An identifiable risk to pedestrians below, which no source documents" ], "echoes": [ { "date": "2021-02-25", "setting": "Knews reporter's deliberate “open window” test at the Huangpu District city operations center launch", "outcome": "recurred", "source": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html" }, { "setting": "Same window anecdote retold by Jiefang Daily as a May Day holiday event (guard Fan Tianyu) and by Banyuetan as a Dragon Boat holiday event", "outcome": "unknown", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Huawei; https://en.wikipedia.org/wiki/Huangpu,_Shanghai", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://oecd.ai/en/incidents/2021-02-25-adca", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Urban governance and building safety", "segment": "Smart-building monitoring under Shanghai's 'one network to manage all'" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2021-02-25-adca, 'Shanghai Deploys AI Digital Twin for Real-Time Urban Safety Management' (AI-generated summary).", "title": "Shanghai Deploys AI Digital Twin for Real-Time Urban Safety Management", "url": "https://oecd.ai/en/incidents/2021-02-25-adca", "date": "2021-02-25", "written_by": "independent", "quote": "The system detected a high-risk behavior (open window), alerted security, and enabled immediate intervention, preventing potential harm to pedestrians." }, { "kind": "news report", "citation": "Eastday (Xue Ningwei), 25 February 2021, '改变从一栋楼开始！上海\"一网统管\"探索城市最小管理单元数字治理', via Sohu.", "title": "改变从一栋楼开始！上海“一网统管”探索城市最小管理单元数字治理", "url": "https://www.sohu.com/a/452580009_120823584", "date": "2021-02-25", "written_by": "independent", "quote": "春节期间，一位被美丽街景吸引的顾客走到3楼打开窗户，将手机探出窗外拍照，这一具有潜在高空坠物风险的举动被随即而来的店内保安制止。" }, { "kind": "news report", "citation": "Knews / Shanghai Media Group, 25 February 2021, '南京大楼，如何实现\"数字孪生\"？', via NetEase (163.com).", "title": "南京大楼，如何实现“数字孪生”？", "url": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html", "date": "2021-02-25", "written_by": "independent", "quote": "通过这个小小的开窗传感器，就能将开窗信息实时回传给数字孪生系统" }, { "kind": "news report", "citation": "Jiefang Daily, 7 May 2021, '传感器如\"五官\"，南京大楼在数字世界\"活\"了', via Guangming Online (GMW).", "title": "传感器如“五官”，南京大楼在数字世界“活”了", "url": "https://tech.gmw.cn/2021-05/07/content_34826280.htm", "date": "2021-05-07", "written_by": "independent", "quote": "超过八成都是参观者体验物联设备时所触发的，真实事件远没有数据体现得那么多" }, { "kind": "news report", "citation": "Banyuetan / Xinhua (Zhou Lin), 6 July 2021, '\"数字孪生城市\"来了：城市治理可望告别\"盲人摸象\"', via The Paper.", "title": "“数字孪生城市”来了：城市治理可望告别“盲人摸象”", "url": "https://m.thepaper.cn/newsDetail_forward_13463904", "date": "2021-07-06", "written_by": "independent", "quote": "安装在窗户上的传感器第一时间监测到开窗行为，店内保安范天玉佩戴的智能手环立即接到系统自动报警" }, { "kind": "news report", "citation": "Cyberspace Administration of China, 4 March 2021, repost of '改变从一栋楼开始！上海\"一网统管\"探索城市最小管理单元数字治理' from the 'Cyberspace Shanghai' WeChat account.", "title": "改变从一栋楼开始！上海“一网统管”探索城市最小管理单元数字治理", "url": "https://www.cac.gov.cn/2021-03/04/c_1616435886725223.htm", "date": "2021-03-04", "written_by": "independent", "quote": "就会第一时间检测到高空坠物隐患", "supports_benefit": false }, { "kind": "news report", "citation": "smartcity.team, 1 March 2021, '上海：城市最小管理单元数字治理成果发布，数字治理助力一网统管' (case write-up of the 25 February 2021 launch).", "title": "上海：城市最小管理单元数字治理成果发布，数字治理助力一网统管", "url": "https://www.smartcity.team/cases/smartcitycases/shanghaichengshizuixiaoguanlidanyuan/", "date": "2021-03-01", "written_by": "independent", "quote": "由华为技术有限公司主办", "supports_benefit": false }, { "kind": "press release", "citation": "zhiding.cn (big-data channel), 25 February 2021, '上海\"一网统管\"发布城市最小管理单元数字治理成果', marked '来源：业界供稿' (industry-supplied copy).", "title": "上海“一网统管”发布城市最小管理单元数字治理成果", "url": "http://big-data.zhiding.cn/2021/0225/3132347.shtml", "date": "2021-02-25", "written_by": "makers", "quote": "来源：业界供稿" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0324-source-0001", "AIBD-0324-source-0002", "AIBD-0324-source-0003", "AIBD-0324-source-0004", "AIBD-0324-source-0005", "AIBD-0324-source-0006", "AIBD-0324-source-0007", "AIBD-0324-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The CAC page reposts news about the building. Smartcity.team compiles launch coverage. Neither is a regulatory finding or an independent study of the window incident." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0324-source-0006", "AIBD-0324-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The CAC page reposts news about the building. Smartcity.team compiles launch coverage. Neither is a regulatory finding or an independent study of the window incident." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0324-source-0001", "retained_source_order": [ "AIBD-0324-source-0001", "AIBD-0324-source-0002", "AIBD-0324-source-0003", "AIBD-0324-source-0004", "AIBD-0324-source-0005", "AIBD-0324-source-0006", "AIBD-0324-source-0007", "AIBD-0324-source-0008" ], "origins": [ { "url": "https://www.cac.gov.cn/2021-03/04/c_1616435886725223.htm", "locator": "Source credit and 实时体验: 大楼也有数字生命体征.", "contribution": "Hardware and platform context; a repeated window-alert account.", "relationship": "A government-hosted news repost, not a regulatory instrument.", "source_refs": [ "AIBD-0324-source-0006" ] }, { "url": "https://www.smartcity.team/cases/smartcitycases/shanghaichengshizuixiaoguanlidanyuan/", "locator": "Byline 本站综合编辑; launch and window passages.", "contribution": "Compiled launch coverage and a repeated incident description.", "relationship": "Secondary compilation, not independent benefit verification.", "source_refs": [ "AIBD-0324-source-0007" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0324-source-0006", "AIBD-0324-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The CAC page reposts news about the building. Smartcity.team compiles launch coverage. Neither is a regulatory finding or an independent study of the window incident." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Huawei-hosted launch on 25 Feb 2021 presented a window-opening alert sent to a guard's wristband. Knews and Jiefang Daily say that a window sensor detected it; the story is retold with three dates.", "account": "The OECD AI Incidents entry says Shanghai, with Huawei, launched an AI-powered digital twin in the Nanjing Building. It says the twin “detected a high-risk behavior (open window), alerted security, and enabled immediate intervention”. The anecdote appears in Eastday (reporter Xue Ningwei, 25 Feb 2021, via Sohu). During Spring Festival a customer on the third floor opened a window and held a phone out to photograph Nanjing Road. A guard arrived to stop it. Eastday says how the guard knew was “revealed at today's launch”, the “Shanghai city minimum management unit digital governance” release. It was held at the Huangpu District city operations center, hosted by Huawei Technologies per smartcity.team (1 Mar 2021). Jiefang Daily (7 May 2021, via GMW) retells the same window scene during the May Day holiday, naming guard Fan Tianyu. Banyuetan/Xinhua (reporter Zhou Lin, 6 Jul 2021, via The Paper) retells it during the Dragon Boat holiday with the same guard and wording. No single date can be fixed. The Cyberspace Administration of China repost (4 Mar 2021) phrases it conditionally (“if a visitor opens a window...”). The only witnessed detection was a Knews reporter's deliberate “open window” test at the launch. Huawei engineer Chen Tao also simulated smoking there for the camera algorithm. Both Knews and Jiefang Daily say a window-mounted sensor detected the opening and pushed an alert to the guard's wristband through the digital twin. The AI algorithms described (20-plus per Knews and Jiefang Daily, 50-plus per Eastday) run on the 170-plus cameras for smoking, crowd flow and bike parking. Jiefang Daily reports 995 door/window alerts from January to May 2021. It quotes an official that over 80% were triggered by visitors trying the IoT devices. The building is Huawei's flagship store. No harm occurred and no beneficiary is identifiable. The deployment itself is well documented (Huangpu District and Huawei, built January 2021; 17 device categories, 80-plus sensor sets, 170-plus cameras). No English-language report was found, and the China Central Television (CCTV-2) segment is not among the sources. The system's zhiding.cn copy is marked “industry-supplied copy”." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Nanjing Building 1:1 'living' digital twin on Huawei Cloud: 80-plus IoT sensor sets in 17 categories, 170-plus cameras, and 20-plus (Knews, Jiefang Daily) or 50-plus (Eastday) AI algorithms for smoking, crowd-flow and parking detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Huawei (Huawei Cloud, big data, AI, edge computing) with Huangpu District government under the Shanghai City Operations Management Center" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Shanghai's Nanjing Building digital twin (Huangpu District with Huawei) alerts a guard to an opened third-floor window; a sensor, not AI, detected it and the anecdote carries three dates", "headline": "Huawei digital twin's window alert comes from a sensor, not AI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8669bbed86919d4c8309ae6c1e79acccd087298e13f3e76750b2c908666b88be" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry says Shanghai, with Huawei, launched an AI-powered digital twin in the Nanjing Building. It says the twin “detected a high-risk behavior (open window), alerted security, and enabled immediate intervention”. The anecdote appears in Eastday (reporter Xue Ningwei, 25 Feb 2021, via Sohu). During Spring Festival a customer on the third floor opened a window and held a phone out to photograph Nanjing Road. A guard arrived to stop it. Eastday says how the guard knew was “revealed at today's launch”, the “Shanghai city minimum management unit digital governance” release. It was held at the Huangpu District city operations center, hosted by Huawei Technologies per smartcity.team (1 Mar 2021). Jiefang Daily (7 May 2021, via GMW) retells the same window scene during the May Day holiday, naming guard Fan Tianyu. Banyuetan/Xinhua (reporter Zhou Lin, 6 Jul 2021, via The Paper) retells it during the Dragon Boat holiday with the same guard and wording. No single date can be fixed. The Cyberspace Administration of China repost (4 Mar 2021) phrases it conditionally (“if a visitor opens a window...”). The only witnessed detection was a Knews reporter's deliberate “open window” test at the launch. Huawei engineer Chen Tao also simulated smoking there for the camera algorithm. Both Knews and Jiefang Daily say a window-mounted sensor detected the opening and pushed an alert to the guard's wristband through the digital twin. The AI algorithms described (20-plus per Knews and Jiefang Daily, 50-plus per Eastday) run on the 170-plus cameras for smoking, crowd flow and bike parking. Jiefang Daily reports 995 door/window alerts from January to May 2021. It quotes an official that over 80% were triggered by visitors trying the IoT devices. The building is Huawei's flagship store. No harm occurred and no beneficiary is identifiable. The deployment itself is well documented (Huangpu District and Huawei, built January 2021; 17 device categories, 80-plus sensor sets, 170-plus cameras). No English-language report was found, and the China Central Television (CCTV-2) segment is not among the sources. The system's zhiding.cn copy is marked “industry-supplied copy”.", "replication": { "produced_by": [ "Window-mounted contact sensors reporting to the building's digital twin", "An alert pushed to a security guard's smart wristband", "A guard on site who closes the window" ], "must_hold": [ "A real, not visitor-triggered, window opening: Jiefang Daily reports that over 80% of 995 logged door/window alerts were visitors trying the devices", "An identifiable risk to pedestrians below, which no source documents" ], "echoes": [ { "date": "2021-02-25", "setting": "Knews reporter's deliberate “open window” test at the Huangpu District city operations center launch", "outcome": "recurred", "source": "https://www.163.com/dy/article/G3NCP8NI0514EGPO.html" }, { "setting": "Same window anecdote retold by Jiefang Daily as a May Day holiday event (guard Fan Tianyu) and by Banyuetan as a Dragon Boat holiday event", "outcome": "unknown", "source": "https://tech.gmw.cn/2021-05/07/content_34826280.htm" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 2, "record_mapped": 28, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0028", "title": "Medtronic MiniMed predictive low-glucose suspend reducing hypoglycemia with a successful pregnancy", "summary": "MiniMed 640G predictive low-glucose suspend cut hypoglycemia in a T1D woman after two miscarriages; term birth of a 4,137 g boy.", "date_observed": "2021-03-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case report appeared in Diabetology International on 6 March 2021 (event dates not reported). It describes a 22-year-old Brazilian woman in Japan with type 1 diabetes for 11 years. She miscarried at 7 and 9 weeks in two earlier pregnancies. At about 6 weeks of her third pregnancy she was switched to a Medtronic MiniMed 640G sensor-augmented pump with predictive low glucose suspend. The pump suspended insulin for about 249 minutes per day. Hypoglycemic episodes fell from 2.1–2.5 to 1.4 per day and time below 70 mg/dL from 1.1–1.4% to 0.5%. She delivered a 4,137 g boy by cesarean section at 39 weeks and 3 days with no significant complications.", "category": "benefit created", "unexpected": false, "purpose": "Predictive low glucose suspend is built to stop insulin delivery when sensor glucose is predicted to fall low, to avoid hypoglycemia. The benefit was that purpose, with a successful pregnancy as the downstream outcome.", "system": "Medtronic MiniMed sensor-augmented pump / automated insulin delivery with predictive low glucose suspend (SmartGuard)", "model_version": "MiniMed 640G (event); MiniMed 780G in echo", "developer": "Medtronic", "deployer": null, "location": null, "domain": "Healthcare (diabetes; obstetrics)", "segment": "Diabetes technology", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "After two miscarriages, hypoglycemia frequency and glucose variability fell on the device and the pregnancy reached term with a healthy infant. A life-changing benefit, though the source does not prove the device caused the live birth." } ], "ai_role": { "status": "assessed", "statement": "The pump's predictive algorithm autonomously suspended insulin for about four hours a day. The authors link this to fewer hypoglycemic episodes and lower variability. Obstetric and diabetes care were delivered by clinicians. The causal link to carrying the pregnancy is inferred, not demonstrated." }, "evidence": [ { "kind": "case report", "citation": "Honoki H, Yagi K, Tsuda S, Wada T, Enkaku A, Nakagawa-Yokoyama M, Kamigishi M, Shikata M, Takikawa-Nishida A, Fujisaka S, Chujo D, Sasaoka T, Nakashima A, Saito S, Tobe K (2021). Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature. Diabetology International 12:324-329.", "title": "Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature", "url": "https://doi.org/10.1007/s13340-020-00489-9", "date": "2021-03-06", "written_by": "deployer", "quote": "She gave birth to a 4137 g boy at 39 weeks without significant complications." }, { "kind": "case report", "citation": "Honoki H et al. (2021). Diabetology International 12:324-329.", "title": "Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8172753/", "date": "2021-03-06", "written_by": "deployer", "quote": "SAP-PLGS makes it possible to avoid severe hypoglycemia following the compensation of insulin to mitigate transient hyperglycemia." }, { "kind": "case report", "citation": "Zadáková E, Horová E (2025). Case Report: Hybrid closed-loop insulin pump can significantly improve awareness of hypoglycemia. Frontiers in Clinical Diabetes and Healthcare 6:1536038.", "title": "Hybrid closed-loop insulin pump can significantly improve awareness of hypoglycemia", "url": "https://europepmc.org/article/PMC/PMC11886589", "date": "2025-02-21", "written_by": "deployer", "quote": "since the initiation of the AID, there has been no episode of severe hypoglycemia" } ], "replication": { "produced_by": [ "A person with type 1 diabetes and frequent or unrecognized hypoglycemia uses a Medtronic pump with CGM and predictive low glucose suspend enabled", "Sensor glucose is predicted to fall and the algorithm suspends basal insulin", "Hypoglycemia frequency and variability fall and the clinical goal (pregnancy, restored awareness) is reached" ], "must_hold": [ "Sensor is worn and calibrated with suspend enabled", "The user does not override suspensions", "Clinical follow-up adjusts settings" ], "echoes": [ { "date": "2025-02-21", "setting": "45-year-old man with type 1 diabetes since 1996 and impaired hypoglycemia awareness, Czechia; MiniMed 780G SmartGuard started mid-2021 after his driving license was suspended in April 2021; no severe hypoglycemia since, Clarke and Gold scores 6 to 2 by early 2022, license reinstated, time below range 23% to 1% by June 2024 (publication date)", "model_version": "Medtronic MiniMed 780G (SmartGuard)", "outcome": "recurred", "source": "Zadáková & Horová (2025). Front Clin Diabetes Healthc 6:1536038. https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/" } ] }, "paired_incident": null, "headline": "MiniMed 640G cuts hypoglycemia; mother delivers a 4,137 g boy", "metric": "hypoglycemic episodes fell from 2.1–2.5 to 1.4 per day", "comparator": { "against": "her two earlier pregnancies on a MiniMed 620G sensor-augmented pump without predictive low glucose suspend", "before": "Hypoglycemic episodes (/day) 2.5 and 2.1; time with AUC below 70 mg/dL 1.1% and 1.4%", "after": "Hypoglycemic episodes (/day) 1.4; mean AUC < 70 mg/dL of 0.5%", "basis": "measured", "quote": "Ratio of time range with average AUC blow 70 mg/dL (%) 1.1 1.4 0.5 Hypoglycemic episodes (/day) 2.5 2.1 1.4", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8172753/" }, "later": { "status": "unknown", "date": null, "note": "No development for this patient after the 2021 case report was found; the 2025 MiniMed 780G report concerns a different patient.", "quote": null, "url": null }, "value": null, "developer_country": "Ireland", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Medtronic", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: three case reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0028", "catalog_version": "1.0.0", "source_fingerprint": "bc612c5c94bfaded6e8e94f6847b0dc67055260e052df115570b962bac88c0b1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0028-source-0001", "AIBD-0028-source-0002", "AIBD-0028-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Medtronic" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The pump's predictive algorithm autonomously suspended insulin for about four hours a day. The authors link this to fewer hypoglycemic episodes and lower variability. Obstetric and diabetes care were delivered by clinicians. The causal link to carrying the pregnancy is inferred, not demonstrated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The pump's predictive algorithm autonomously suspended insulin for about four hours a day. The authors link this to fewer hypoglycemic episodes and lower variability. Obstetric and diabetes care were delivered by clinicians. The causal link to carrying the pregnancy is inferred, not demonstrated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After two miscarriages, hypoglycemia frequency and glucose variability fell on the device and the pregnancy reached term with a healthy infant. A life-changing benefit, though the source does not prove the device caused the live birth." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: three case reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After two miscarriages, hypoglycemia frequency and glucose variability fell on the device and the pregnancy reached term with a healthy infant. A life-changing benefit, though the source does not prove the device caused the live birth." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After two miscarriages, hypoglycemia frequency and glucose variability fell on the device and the pregnancy reached term with a healthy infant. A life-changing benefit, though the source does not prove the device caused the live birth." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": 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Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature. Diabetology International 12:324-329.", "title": "Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature", "url": "https://doi.org/10.1007/s13340-020-00489-9", "date": "2021-03-06", "written_by": "deployer", "quote": "She gave birth to a 4137 g boy at 39 weeks without significant complications." }, { "kind": "case report", "citation": "Honoki H et al. (2021). Diabetology International 12:324-329.", "title": "Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8172753/", "date": "2021-03-06", "written_by": "deployer", "quote": "SAP-PLGS makes it possible to avoid severe hypoglycemia following the compensation of insulin to mitigate transient hyperglycemia." }, { "kind": "case report", "citation": "Zadáková E, Horová E (2025). Case Report: Hybrid closed-loop insulin pump can significantly improve awareness of hypoglycemia. Frontiers in Clinical Diabetes and Healthcare 6:1536038.", "title": "Hybrid closed-loop insulin pump can significantly improve awareness of hypoglycemia", "url": "https://europepmc.org/article/PMC/PMC11886589", "date": "2025-02-21", "written_by": "deployer", "quote": "since the initiation of the AID, there has been no episode of severe hypoglycemia" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0028-source-0001", "AIBD-0028-source-0002", "AIBD-0028-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Honoki H, Yagi K, Tsuda S, Wada T, Enkaku A, Nakagawa-Yokoyama M, Kamigishi M, Shikata M, Takikawa-Nishida A, Fujisaka S, Chujo D, Sasaoka T, Nakashima A, Saito S, Tobe K (2021). Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature. Diabetology International 12:324-329.", "title": "Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature", "url": "https://doi.org/10.1007/s13340-020-00489-9", "date": "2021-03-06", "written_by": "deployer", "quote": "She gave birth to a 4137 g boy at 39 weeks without significant complications." }, { "kind": "case report", "citation": "Honoki H et al. (2021). 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Frontiers in Clinical Diabetes and Healthcare 6:1536038.", "title": "Hybrid closed-loop insulin pump can significantly improve awareness of hypoglycemia", "url": "https://europepmc.org/article/PMC/PMC11886589", "date": "2025-02-21", "written_by": "deployer", "quote": "since the initiation of the AID, there has been no episode of severe hypoglycemia" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "MiniMed 640G predictive low-glucose suspend cut hypoglycemia in a T1D woman after two miscarriages; term birth of a 4,137 g boy.", "account": "A case report appeared in Diabetology International on 6 March 2021 (event dates not reported). It describes a 22-year-old Brazilian woman in Japan with type 1 diabetes for 11 years. She miscarried at 7 and 9 weeks in two earlier pregnancies. At about 6 weeks of her third pregnancy she was switched to a Medtronic MiniMed 640G sensor-augmented pump with predictive low glucose suspend. The pump suspended insulin for about 249 minutes per day. Hypoglycemic episodes fell from 2.1–2.5 to 1.4 per day and time below 70 mg/dL from 1.1–1.4% to 0.5%. She delivered a 4,137 g boy by cesarean section at 39 weeks and 3 days with no significant complications." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The pump predicted low glucose and suspended insulin delivery." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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It describes a 22-year-old Brazilian woman in Japan with type 1 diabetes for 11 years. She miscarried at 7 and 9 weeks in two earlier pregnancies. At about 6 weeks of her third pregnancy she was switched to a Medtronic MiniMed 640G sensor-augmented pump with predictive low glucose suspend. The pump suspended insulin for about 249 minutes per day. Hypoglycemic episodes fell from 2.1–2.5 to 1.4 per day and time below 70 mg/dL from 1.1–1.4% to 0.5%. She delivered a 4,137 g boy by cesarean section at 39 weeks and 3 days with no significant complications.", "replication": { "produced_by": [ "A person with type 1 diabetes and frequent or unrecognized hypoglycemia uses a Medtronic pump with CGM and predictive low glucose suspend enabled", "Sensor glucose is predicted to fall and the algorithm suspends basal insulin", "Hypoglycemia frequency and variability fall and the clinical goal (pregnancy, restored awareness) is reached" ], "must_hold": [ "Sensor is worn and calibrated with suspend enabled", "The user does not override suspensions", "Clinical follow-up adjusts settings" ], "echoes": [ { "date": "2025-02-21", "setting": "45-year-old man with type 1 diabetes since 1996 and impaired hypoglycemia awareness, Czechia; MiniMed 780G SmartGuard started mid-2021 after his driving license was suspended in April 2021; no severe hypoglycemia since, Clarke and Gold scores 6 to 2 by early 2022, license reinstated, time below range 23% to 1% by June 2024 (publication date)", "model_version": "Medtronic MiniMed 780G (SmartGuard)", "outcome": "recurred", "source": "Zadáková & Horová (2025). Front Clin Diabetes Healthc 6:1536038. https://pmc.ncbi.nlm.nih.gov/articles/PMC11886589/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0103", "title": "BirdCast forecast alerts underpin Houston's Lights Out Nights proclamation", "summary": "Houston Audubon issues Lights Out alerts from BirdCast forecasts; City of Houston proclaimed Lights Out Nights on 9 April 2021.", "date_observed": "2021-04-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "BirdCast is produced by the Cornell Lab of Ornithology with Colorado State University and now Purdue University and the University of Illinois. It forecasts nocturnal bird migration from a model trained on 23 years of weather-radar bird detections and reanalysis weather data. Houston Audubon states its staff use the BirdCast forecast maps to track migration predictions. They issue Lights Out Action Alerts when a chance of high migration coincides with weather events. Alerts ask residents and businesses to turn off nonessential lights from 11 p.m. to 6 a.m. during spring and fall migration. On 9 April 2021 the City of Houston proclaimed “Lights Out Nights” to help migrating birds. No Houston collision reduction is documented. A separate 21-year Chicago study co-authored by BirdCast scientists estimated halving lighted window area cuts collisions 11-fold in spring and 6-fold in fall.", "category": "protective response", "unexpected": false, "purpose": "Forecast nightly bird migration intensity from weather radar and weather models so that cities, building owners and residents can reduce lighting on high-migration nights.", "system": "BirdCast migration forecast model and Lights Out Action Alerts", "model_version": null, "developer": "Cornell Lab of Ornithology, Colorado State University (forecasts now produced with Purdue University and University of Illinois)", "deployer": "Houston Audubon (Birds Houston) and City of Houston", "location": "Houston, United States", "domain": "Conservation and biodiversity", "segment": "Migratory bird collision prevention / urban lighting policy", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Residents and building managers receive timed alerts, but no individual outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "A municipal proclamation and partner alert program were adopted; the partner page reports no measured change in collisions at Houston buildings." }, { "group": "societal", "depth": null, "reason": "The collision evidence is a Chicago study co-authored by BirdCast scientists; Houston's own collision change is unmeasured." } ], "ai_role": { "status": "assessed", "statement": "The learned forecast model identifies the nights on which alerts are issued. The proclamation and alert program are documented by the operating partner, not the model's makers. The collision-reduction evidence comes from a separate Chicago study co-authored by BirdCast scientists and is not specific to Houston. The counterfactual for Houston is unproven." }, "evidence": [ { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "date": null, "written_by": "deployer", "quote": "April 9, 2021: City of Houston proclaims 'Lights Out Nights' in Houston to help migrating birds traveling through the region" }, { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "date": null, "written_by": "deployer", "quote": "our staff were able to track migration predictions for the region and issue alerts to the community when a chance of high migration coincided with weather events" }, { "kind": "press release", "citation": "BirdCast (n.d.). Migration forecast maps. birdcast.org.", "title": "Migration forecast maps", "url": "https://birdcast.org/migration-tools/migration-forecast-maps/", "date": null, "written_by": "makers", "quote": "By learning associations between weather variables and migration, we can use the model to predict a bird migration intensity given a particular weather forecast." }, { "kind": "peer-reviewed study", "citation": "Van Doren, B. M., Willard, D. E., Hennen, M., Horton, K. G., et al. (2021). Drivers of fatal bird collisions in an urban center. PNAS 118(24).", "title": "Drivers of fatal bird collisions in an urban center", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "date": "2021-06-07", "written_by": "makers", "quote": "We estimate that halving lighted window area decreases collision counts by 11× in spring and 6× in fall." } ], "replication": { "produced_by": [ "Continental weather-radar archive to train the forecast", "A local partner that translates forecasts into alerts", "Municipal endorsement of lights-out practice" ], "must_hold": [ "Forecast skill on peak nights", "Building managers actually act on alerts", "Monitoring to measure collisions before and after" ], "echoes": [ { "date": "2026-08-27", "setting": "City of Raleigh joins Lights Out; lights off 11 p.m.–6 a.m. on a seasonal schedule, BirdCast referenced as a resource", "model_version": null, "outcome": "unknown", "source": "https://raleighnc.gov/climate-action-and-sustainability/news/raleigh-joins-lights-out-bird-migration" } ] }, "paired_incident": null, "headline": "BirdCast forecasts underpin Houston's Lights Out Nights", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2022-04-17", "note": "Birds Houston's program timeline records Houston-area cities jointly asking businesses and residents to go Lights Out for birds in April 2022 and a statewide Lights Out gathering at Texas A&M University in August 2023.", "quote": "April 9, 2021: City of Houston proclaims \"Lights Out Nights\" in Houston April 17, 2022: Houston-area cities ask businesses and residents to go 'Lights Out' for birds August 25th, 2023: State-wide Gathering and Lights Out Exhibit at Texas A&M University", "url": "https://birdshouston.org/conservation/lights-out.html" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the account so that Houston Audubon's alerts go out when a chance of high migration coincides with weather events, as its page says, and described the Chicago collision study as co-authored by BirdCast scientists rather than independent, matching the PNAS author affiliations and the record's own authorship marking.", "source": "https://birdshouston.org/conservation/lights-out.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://birdshouston.org/conservation/lights-out.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Cornell_Lab_of_Ornithology; https://birdshouston.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' press release and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0103", "catalog_version": "1.0.0", "source_fingerprint": "64721b437e1ee54d480ed358ebeb277ab8816c11ea5d66523e905862833fdcff", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0103-source-0001", "AIBD-0103-source-0002", "AIBD-0103-source-0003", "AIBD-0103-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Cornell Lab of Ornithology, Colorado State University (forecasts now produced with Purdue University and University of Illinois)", "deployer": "Houston Audubon (Birds Houston) and City of Houston" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The learned forecast model identifies the nights on which alerts are issued. The proclamation and alert program are documented by the operating partner, not the model's makers. The collision-reduction evidence comes from a separate Chicago study co-authored by BirdCast scientists and is not specific to Houston. The counterfactual for Houston is unproven." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The learned forecast model identifies the nights on which alerts are issued. The proclamation and alert program are documented by the operating partner, not the model's makers. The collision-reduction evidence comes from a separate Chicago study co-authored by BirdCast scientists and is not specific to Houston. The counterfactual for Houston is unproven." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Residents and building managers receive timed alerts, but no individual outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "A municipal proclamation and partner alert program were adopted; the partner page reports no measured change in collisions at Houston buildings." }, { "group": "societal", "reason": "The collision evidence is a Chicago study co-authored by BirdCast scientists; Houston's own collision change is unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study, the makers' press release and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Residents and building managers receive timed alerts, but no individual outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "A municipal proclamation and partner alert program were adopted; the partner page reports no measured change in collisions at Houston buildings." }, { "group": "societal", "reason": "The collision evidence is a Chicago study co-authored by BirdCast scientists; Houston's own collision change is unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Residents and building managers receive timed alerts, but no individual outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "A municipal proclamation and partner alert program were adopted; the partner page reports no measured change in collisions at Houston buildings." }, { "group": "societal", "reason": "The collision evidence is a Chicago study co-authored by BirdCast scientists; Houston's own collision change is unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2022-04-17", "note": "Birds Houston's program timeline records Houston-area cities jointly asking businesses and residents to go Lights Out for birds in April 2022 and a statewide Lights Out gathering at Texas A&M University in August 2023.", "quote": "April 9, 2021: City of Houston proclaims \"Lights Out Nights\" in Houston April 17, 2022: Houston-area cities ask businesses and residents to go 'Lights Out' for birds August 25th, 2023: State-wide Gathering and Lights Out Exhibit at Texas A&M University", "url": "https://birdshouston.org/conservation/lights-out.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0103" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "BirdCast is produced by the Cornell Lab of Ornithology with Colorado State University and now Purdue University and the University of Illinois. It forecasts nocturnal bird migration from a model trained on 23 years of weather-radar bird detections and reanalysis weather data. Houston Audubon states its staff use the BirdCast forecast maps to track migration predictions. They issue Lights Out Action Alerts when a chance of high migration coincides with weather events. Alerts ask residents and businesses to turn off nonessential lights from 11 p.m. to 6 a.m. during spring and fall migration. On 9 April 2021 the City of Houston proclaimed “Lights Out Nights” to help migrating birds. No Houston collision reduction is documented. A separate 21-year Chicago study co-authored by BirdCast scientists estimated halving lighted window area cuts collisions 11-fold in spring and 6-fold in fall.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Residents and building managers receive timed alerts, but no individual outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "A municipal proclamation and partner alert program were adopted; the partner page reports no measured change in collisions at Houston buildings." }, { "group": "societal", "reason": "The collision evidence is a Chicago study co-authored by BirdCast scientists; Houston's own collision change is unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Forecast nightly bird migration intensity from weather radar and weather models so that cities, building owners and residents can reduce lighting on high-migration nights." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Houston, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Forecast nightly bird migration intensity from weather radar and weather models so that cities, building owners and residents can reduce lighting on high-migration nights." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-04-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the account so that Houston Audubon's alerts go out when a chance of high migration coincides with weather events, as its page says, and described the Chicago collision study as co-authored by BirdCast scientists rather than independent, matching the PNAS author affiliations and the record's own authorship marking.", "source": "https://birdshouston.org/conservation/lights-out.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://birdshouston.org/conservation/lights-out.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Cornell_Lab_of_Ornithology; https://birdshouston.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Continental weather-radar archive to train the forecast", "A local partner that translates forecasts into alerts", "Municipal endorsement of lights-out practice" ], "must_hold": [ "Forecast skill on peak nights", "Building managers actually act on alerts", "Monitoring to measure collisions before and after" ], "echoes": [ { "date": "2026-08-27", "setting": "City of Raleigh joins Lights Out; 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lights off 11 p.m.–6 a.m. on a seasonal schedule, BirdCast referenced as a resource", "outcome": "unknown", "source": "https://raleighnc.gov/climate-action-and-sustainability/news/raleigh-joins-lights-out-bird-migration" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the account so that Houston Audubon's alerts go out when a chance of high migration coincides with weather events, as its page says, and described the Chicago collision study as co-authored by BirdCast scientists rather than independent, matching the PNAS author affiliations and the record's own authorship marking.", "source": "https://birdshouston.org/conservation/lights-out.html; https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://birdshouston.org/conservation/lights-out.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Cornell_Lab_of_Ornithology; https://birdshouston.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Conservation and biodiversity", "segment": "Migratory bird collision prevention / urban lighting policy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "written_by": "deployer", "quote": "April 9, 2021: City of Houston proclaims 'Lights Out Nights' in Houston to help migrating birds traveling through the region" }, { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "written_by": "deployer", "quote": "our staff were able to track migration predictions for the region and issue alerts to the community when a chance of high migration coincided with weather events" }, { "kind": "press release", "citation": "BirdCast (n.d.). Migration forecast maps. birdcast.org.", "title": "Migration forecast maps", "url": "https://birdcast.org/migration-tools/migration-forecast-maps/", "written_by": "makers", "quote": "By learning associations between weather variables and migration, we can use the model to predict a bird migration intensity given a particular weather forecast." }, { "kind": "peer-reviewed study", "citation": "Van Doren, B. M., Willard, D. E., Hennen, M., Horton, K. G., et al. (2021). Drivers of fatal bird collisions in an urban center. PNAS 118(24).", "title": "Drivers of fatal bird collisions in an urban center", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "date": "2021-06-07", "written_by": "makers", "quote": "We estimate that halving lighted window area decreases collision counts by 11× in spring and 6× in fall." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0103-source-0001", "AIBD-0103-source-0002", "AIBD-0103-source-0003", "AIBD-0103-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "written_by": "deployer", "quote": "April 9, 2021: City of Houston proclaims 'Lights Out Nights' in Houston to help migrating birds traveling through the region" }, { "kind": "press release", "citation": "Houston Audubon / Birds Houston (n.d.). Lights Out for Birds. birdshouston.org.", "title": "Lights Out for Birds", "url": "https://birdshouston.org/conservation/lights-out.html", "written_by": "deployer", "quote": "our staff were able to track migration predictions for the region and issue alerts to the community when a chance of high migration coincided with weather events" }, { "kind": "press release", "citation": "BirdCast (n.d.). Migration forecast maps. birdcast.org.", "title": "Migration forecast maps", "url": "https://birdcast.org/migration-tools/migration-forecast-maps/", "written_by": "makers", "quote": "By learning associations between weather variables and migration, we can use the model to predict a bird migration intensity given a particular weather forecast." }, { "kind": "peer-reviewed study", "citation": "Van Doren, B. M., Willard, D. E., Hennen, M., Horton, K. G., et al. (2021). Drivers of fatal bird collisions in an urban center. PNAS 118(24).", "title": "Drivers of fatal bird collisions in an urban center", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8214683/", "date": "2021-06-07", "written_by": "makers", "quote": "We estimate that halving lighted window area decreases collision counts by 11× in spring and 6× in fall." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Houston Audubon issues Lights Out alerts from BirdCast forecasts; City of Houston proclaimed Lights Out Nights on 9 April 2021.", "account": "BirdCast is produced by the Cornell Lab of Ornithology with Colorado State University and now Purdue University and the University of Illinois. It forecasts nocturnal bird migration from a model trained on 23 years of weather-radar bird detections and reanalysis weather data. Houston Audubon states its staff use the BirdCast forecast maps to track migration predictions. They issue Lights Out Action Alerts when a chance of high migration coincides with weather events. Alerts ask residents and businesses to turn off nonessential lights from 11 p.m. to 6 a.m. during spring and fall migration. On 9 April 2021 the City of Houston proclaimed “Lights Out Nights” to help migrating birds. No Houston collision reduction is documented. A separate 21-year Chicago study co-authored by BirdCast scientists estimated halving lighted window area cuts collisions 11-fold in spring and 6-fold in fall." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "BirdCast migration forecast model and Lights Out Action Alerts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Cornell Lab of Ornithology, Colorado State University (forecasts now produced with Purdue University and University of Illinois)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "BirdCast forecast alerts underpin Houston's Lights Out Nights proclamation", "headline": "BirdCast forecasts underpin Houston's Lights Out Nights" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "64721b437e1ee54d480ed358ebeb277ab8816c11ea5d66523e905862833fdcff" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "BirdCast is produced by the Cornell Lab of Ornithology with Colorado State University and now Purdue University and the University of Illinois. It forecasts nocturnal bird migration from a model trained on 23 years of weather-radar bird detections and reanalysis weather data. Houston Audubon states its staff use the BirdCast forecast maps to track migration predictions. They issue Lights Out Action Alerts when a chance of high migration coincides with weather events. Alerts ask residents and businesses to turn off nonessential lights from 11 p.m. to 6 a.m. during spring and fall migration. On 9 April 2021 the City of Houston proclaimed “Lights Out Nights” to help migrating birds. No Houston collision reduction is documented. A separate 21-year Chicago study co-authored by BirdCast scientists estimated halving lighted window area cuts collisions 11-fold in spring and 6-fold in fall.", "replication": { "produced_by": [ "Continental weather-radar archive to train the forecast", "A local partner that translates forecasts into alerts", "Municipal endorsement of lights-out practice" ], "must_hold": [ "Forecast skill on peak nights", "Building managers actually act on alerts", "Monitoring to measure collisions before and after" ], "echoes": [ { "date": "2026-08-27", "setting": "City of Raleigh joins Lights Out; lights off 11 p.m.–6 a.m. on a seasonal schedule, BirdCast referenced as a resource", "outcome": "unknown", "source": "https://raleighnc.gov/climate-action-and-sustainability/news/raleigh-joins-lights-out-bird-migration" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0071", "title": "AI handwriting analysis shows two scribes wrote the Great Isaiah Scroll (1QIsaa)", "summary": "AI handwriting analysis showed two scribes wrote the Great Isaiah Scroll, switching at columns 27–29; published in PLOS ONE 21 April 2021", "date_observed": "2021-04-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 21 April 2021 Mladen Popović, Maruf Dhali and Lambert Schomaker of the University of Groningen published an artificial-intelligence analysis in PLOS ONE. It examined the handwriting of the Great Isaiah Scroll (1QIsaa) from the Dead Sea Scrolls. They used pattern recognition on digitized images of the scroll's 54 columns. The columns fell into two statistically distinct groups, with a transition in columns 27–29. They concluded that two main scribes with different writing patterns were responsible for the scroll, against the view that one scribe wrote it. Some earlier scholars had suggested a change after column 27 on other grounds; the AI analysis supplied quantitative evidence. The team is both developer of the method and author of the finding; acceptance rests on the journal's peer review.", "category": "benefit created", "unexpected": false, "purpose": "Writer identification in ancient manuscripts to distinguish individual scribes", "system": "Groningen AI-based writer-identification pipeline (neural-network binarisation with textural and allographic feature analysis)", "model_version": "BiNet", "developer": "University of Groningen (Dhali, Schomaker, Popović)", "deployer": "University of Groningen", "location": "Groningen, Netherlands", "domain": "History and archives", "segment": "Palaeography of the Dead Sea Scrolls", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: a new scholarly finding for Dead Sea Scrolls research published after peer review; no institutional change reported" }, { "group": "societal", "depth": 1, "reason": "Small: knowledge about the production of one manuscript; the sources claim no wider effect" } ], "ai_role": { "status": "assessed", "statement": "The AI analysis produced the statistical separation of the columns into two groups. The scribal interpretation and the conclusion that two scribes were responsible were made by the authors. The method's developers and the finding's authors are the same team. The only non-developer cited source is the University of Groningen's statement as carried by phys.org. Independent coverage (Smithsonian, CNN) is not among the sources." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Popović, M., Dhali, M. A., Schomaker, L. (2021). Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsaa). PLOS ONE.", "title": "Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsaa)", "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249769", "date": "2021-04-21", "written_by": "makers", "quote": "Demonstrating that two main scribes, each showing different writing patterns, were responsible for the Great Isaiah Scroll" }, { "kind": "press release", "citation": "University of Groningen, via Phys.org (2021). Cracking the code of the Dead Sea Scrolls. Phys.org.", "title": "Cracking the code of the Dead Sea Scrolls", "url": "https://phys.org/news/2021-04-code-dead-sea-scrolls.html", "date": "2021-04-21", "written_by": "makers", "quote": "His analysis of textural and allographic features showed that the 54 columns of text in the Great Isaiah Scroll fell into two different groups." } ], "replication": { "produced_by": [ "High-resolution digital images of all 54 columns", "Neural-network separation of ink from background", "Textural and allographic features compared statistically across column groups" ], "must_hold": [ "Sufficient legible text per column", "Features that separate writers rather than pens or parchment", "Statistical significance of the separation" ], "echoes": [] }, "paired_incident": null, "headline": "Groningen AI finds two scribes wrote the Great Isaiah Scroll", "metric": "two scribes wrote the Great Isaiah Scroll, switching at columns 27–29", "comparator": { "against": "the prevailing scholarly view that a single scribe copied the whole scroll", "before": "the entire manuscript was copied by one scribe, with minor interventions by other, contemporaneous and also much later, scribes", "after": "two main scribes, each showing different writing patterns, were responsible for the Great Isaiah Scroll", "basis": "measured", "quote": "While only [5], [26] have stated that two scribes were each responsible for copying half of the manuscript, columns 1–27 and columns 28–54, most scholars have argued or assumed that the entire manuscript was copied by one scribe, with minor interventions by other, contemporaneous and also much later, scribes [27]–[29].", "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249769" }, "later": { "status": "unknown", "date": null, "note": "The cited sources state only an intention to analyze other scrolls next; no later development was found,.", "quote": null, "url": null }, "value": null, "developer_country": "Netherlands", "deployer_country": "Netherlands", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Verification sweep: the University of Groningen release reproduces the developers' own account; those sources are now marked as written by the makers. 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Phys.org.", "title": "Cracking the code of the Dead Sea Scrolls", "url": "https://phys.org/news/2021-04-code-dead-sea-scrolls.html", "date": "2021-04-21", "written_by": "makers", "quote": "His analysis of textural and allographic features showed that the 54 columns of text in the Great Isaiah Scroll fell into two different groups." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI handwriting analysis showed two scribes wrote the Great Isaiah Scroll, switching at columns 27–29; published in PLOS ONE 21 April 2021", "account": "On 21 April 2021 Mladen Popović, Maruf Dhali and Lambert Schomaker of the University of Groningen published an artificial-intelligence analysis in PLOS ONE. It examined the handwriting of the Great Isaiah Scroll (1QIsaa) from the Dead Sea Scrolls. They used pattern recognition on digitized images of the scroll's 54 columns. The columns fell into two statistically distinct groups, with a transition in columns 27–29. They concluded that two main scribes with different writing patterns were responsible for the scroll, against the view that one scribe wrote it. Some earlier scholars had suggested a change after column 27 on other grounds; the AI analysis supplied quantitative evidence. The team is both developer of the method and author of the finding; acceptance rests on the journal's peer review." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software analyzed handwriting features and separated the columns into two groups." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "BiNet." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "BiNet" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Groningen AI-based writer-identification pipeline (neural-network binarisation with textural and allographic feature analysis)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Groningen (Dhali, Schomaker, Popović)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI handwriting analysis shows two scribes wrote the Great Isaiah Scroll (1QIsaa)", "headline": "Groningen AI finds two scribes wrote the Great Isaiah Scroll" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "96f49483ad7531aecb93038584939a5df29721a08728eea28456344da4911d81" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 21 April 2021 Mladen Popović, Maruf Dhali and Lambert Schomaker of the University of Groningen published an artificial-intelligence analysis in PLOS ONE. It examined the handwriting of the Great Isaiah Scroll (1QIsaa) from the Dead Sea Scrolls. They used pattern recognition on digitized images of the scroll's 54 columns. The columns fell into two statistically distinct groups, with a transition in columns 27–29. They concluded that two main scribes with different writing patterns were responsible for the scroll, against the view that one scribe wrote it. Some earlier scholars had suggested a change after column 27 on other grounds; the AI analysis supplied quantitative evidence. The team is both developer of the method and author of the finding; acceptance rests on the journal's peer review.", "replication": { "produced_by": [ "High-resolution digital images of all 54 columns", "Neural-network separation of ink from background", "Textural and allographic features compared statistically across column groups" ], "must_hold": [ "Sufficient legible text per column", "Features that separate writers rather than pens or parchment", "Statistical significance of the separation" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0193", "title": "eLocust3m and AI data cleaning feed FAO's East Africa locust control, which may have averted USD 1.56 billion in losses", "summary": "PlantVillage's app, built with FAO in under a month in 2020, gathered 240,000+ records; AI removed unusable data; FAO credits the tech-enabled operation with averting USD 1.56 billion in losses.", "date_observed": "2021-05-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In early 2020 desert locust swarms swept the Horn of Africa. FAO's senior locust forecaster Keith Cressman asked Penn State's PlantVillage to adapt its app. PlantVillage had built FAO's fall armyworm app. eLocust3M was released on Google Play on 20 February 2020. Anyone with a smartphone could record georeferenced locust sightings; algorithms checked photos. Penn State also extended a deep-learning soil-moisture model to the affected region. FAO reported receiving up to 2,500 records a day, nearly 25 percent unusable or incorrect. It asked PlantVillage to use artificial intelligence to identify and remove the unwanted data before sharing locations with ground and air control teams. The New York Times reported over 240,000 records collected in a year by PlantVillage scouts, government personnel and citizens. The wider operation also used Garmin satellite devices, EarthRanger (Vulcan) and 28 aircraft coordinated with 51 Degrees. FAO's 6 May 2021 feature says East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. They protected 36.6 million people's food security and avoided USD 1.56 billion in losses, it says. The Times quoted FAO's estimate of USD 1.5 billion averted since February 2020. It quoted FAO's Cyril Ferrand saying swarms were prevented from spilling into the Sahel.", "category": "harm prevented", "unexpected": false, "purpose": "Collect georeferenced locust sightings from anyone with a smartphone. Automatically check photos and remove unusable records so that FAO can direct survey and control teams.", "system": "eLocust3m (PlantVillage) with AI data validation feeding FAO's Desert Locust Information Service", "model_version": "eLocust3M", "developer": "PlantVillage, Pennsylvania State University, with FAO", "deployer": "FAO Desert Locust Information Service and national locust control operations in Kenya, Ethiopia and Somalia", "location": null, "domain": "Agriculture / pest early warning", "segment": "Desert locust control", "benefit_type": "Reduced Risk", "taxonomy_note": "The AI cleaned one data stream in a wider operation, and the averted-loss figure is FAO's estimate for the whole effort.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 3, "reason": "FAO states that East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. FAO says they protected 36.6 million people's food security. The Times quotes FAO's USD 1.5 billion averted since February 2020. These are estimates for the whole operation; AI data handling was one part." }, { "group": "organizational", "depth": 2, "reason": "FAO received up to 2,500 records a day with nearly 25 percent unusable. PlantVillage's AI removed the unwanted data. Over 240,000 records were collected in a year from scouts and citizens who could not have used the discontinued eLocust3 tablets." }, { "group": "personal", "depth": null, "reason": "No individually documented farmer outcome in the sources." } ], "ai_role": { "status": "assessed", "statement": "Two AI uses are documented: algorithms that double-check submitted photos (Times) and AI that filters unusable records out of FAO's daily intake (FAO). A Penn State deep-learning soil-moisture model is mentioned by the maker's university. The outcome figures belong to the entire control operation and no source isolates the AI's contribution. FAO is both co-developer and deployer, so its feature is maker-authored. The Times report is independent with named sources (Cressman, Ferrand, Hughes, Jeptoo, Owuor, Craig)." }, "evidence": [ { "kind": "press release", "citation": "FAO. A high-tech response is helping countries win the battle against Desert Locusts. FAO feature story, 6 May 2021.", "title": "A high-tech response is helping countries win the battle against Desert Locusts", "url": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en", "date": "2021-05-06", "written_by": "makers", "quote": "nearly 25 percent of the data is unusable or incorrect and FAO again turned to PlantVIllage to harness artificial intelligence to rapidly identify and remove the unwanted data." }, { "kind": "news report", "citation": "Nuwer R. As Locusts Swarmed East Africa, This Tech Helped Squash Them. The New York Times, 8 April 2021.", "title": "As Locusts Swarmed East Africa, This Tech Helped Squash Them", "url": "https://www.nytimes.com/2021/04/08/science/locust-swarms-africa.html", "date": "2021-04-08", "written_by": "independent", "quote": "Since February 2020, the F.A.O. estimates that this effort in East Africa has averted the loss of agricultural products with a commercial value of $1.5 billion" }, { "kind": "press release", "citation": "LaJeunesse S. Penn State responds: App aids UN efforts to control Africa's locust infestation. Penn State News, 21 February 2020.", "title": "Penn State responds: App aids UN efforts to control Africa's locust infestation", "url": "https://www.psu.edu/news/research/story/penn-state-responds-app-aids-un-efforts-control-africas-locust-infestation", "date": "2020-02-21", "written_by": "makers", "quote": "a very basic version, eLocust3M, was rapidly developed by Penn State and released for use on mobile phones through Google Play Store on Feb. 20." }, { "kind": "press release", "citation": "FAO. FAO Desert Locust campaign: East Africa upsurge suppressed, Kenya free from Desert Locust. Interview with Cyril Ferrand and Carla Mucavi, FAO newsroom, 15 June 2022.", "title": "FAO Desert Locust campaign: East Africa upsurge suppressed, Kenya free from Desert Locust", "url": "https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en", "date": "2022-06-15", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "An upsurge with swarms across Kenya, Ethiopia and Somalia in 2020 and no trained locust trackers in those countries", "An existing FAO-PlantVillage app blueprint (fall armyworm) adaptable in under a month", "Scouts recruited and trained by PlantVillage and governments", "Aerial control assets (28 aircraft) coordinated through EarthRanger with 51 Degrees" ], "must_hold": [ "Smartphone coverage among scouts, with Garmin satellite devices where there is no network", "FAO's Desert Locust Information Service acting on records daily", "Control teams and aircraft available to act on reported locations" ], "echoes": [ { "date": "2021-01-13", "setting": "Kenya, Uganda, Ethiopia, Somalia: Kuzi machine-learning locust forecasting with SMS alerts by Selina Wamucii", "model_version": "Kuzi", "outcome": "unknown", "source": "TRT World, 13 January 2021" }, { "date": "2020-07-20", "setting": "East Africa: icipe MaxEnt prediction of breeding regions", "model_version": "MaxEnt (Kimathi et al.)", "outcome": "unknown", "source": "Kimathi et al. 2020, Scientific Reports, doi:10.1038/s41598-020-68895-2" } ] }, "paired_incident": null, "headline": "Locust control fed by eLocust3m may have averted USD 1.56 billion", "metric": "protected the food security of 36.6 million people and avoided USD 1.56 billion in losses", "comparator": { "against": "no locust control operations in East Africa (FAO's estimate of the losses that the control campaign averted)", "before": "loss of 4 million tonnes of cereal and 800 million litres of milk production, USD 1.56 billion in cereal and milk losses", "after": "those losses prevented and the food security of 36.6 million people protected", "basis": "assumed", "quote": "In East Africa locust control operations have prevented the loss of 4 million tonnes of cereal and 800 million litres of milk production, while protecting the food security of 36.6 million people and avoiding USD 1.56 billion in cereal and milk losses.", "url": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en" }, "later": { "status": "persisted", "date": "2022-06-15", "note": "In June 2022 FAO declared the East Africa upsurge over and said it had trained 3,800 people across the region to use applications such as eLocust3 to report locusts.", "quote": "We have trained 3 800 people in the entire region on how to use innovative applications such as eLocust3 to recognize and report on Desert Locust.", "url": "https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en" }, "value": { "amount": "USD 1.56 billion", "what": "cereal and milk losses avoided by the locust control operations in East Africa that the app and AI data cleaning fed", "who": "East African farmers and herders (the food security of 36.6 million people)", "estimate": true, "quote": "In East Africa locust control operations have prevented the loss of 4 million tonnes of cereal and 800 million litres of milk production, while protecting the food security of 36.6 million people and avoiding USD 1.56 billion in cereal and milk losses.", "url": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en" }, "developer_country": "United States", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version, the value as stated from the cited sources.", "source": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en; https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en; https://www.psu.edu/news/research/story/penn-state-responds-app-aids-un-efforts-control-africas-locust-infestation; https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://www.fao.org/contact-us/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0193", "catalog_version": "1.0.0", "source_fingerprint": "7a5092b62a3325fadb137449f080787adc9da3bf2ff54dec74ee80646e5f1f07", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0193-source-0001", "AIBD-0193-source-0002", "AIBD-0193-source-0003", "AIBD-0193-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0193-legacy-value", "DIV-0006" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0193-legacy-value", "DIV-0006" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "PlantVillage, Pennsylvania State University, with FAO", "deployer": "FAO Desert Locust Information Service and national locust control operations in Kenya, Ethiopia and Somalia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Two AI uses are documented: algorithms that double-check submitted photos (Times) and AI that filters unusable records out of FAO's daily intake (FAO). A Penn State deep-learning soil-moisture model is mentioned by the maker's university. The outcome figures belong to the entire control operation and no source isolates the AI's contribution. FAO is both co-developer and deployer, so its feature is maker-authored. The Times report is independent with named sources (Cressman, Ferrand, Hughes, Jeptoo, Owuor, Craig)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "Two AI uses are documented: algorithms that double-check submitted photos (Times) and AI that filters unusable records out of FAO's daily intake (FAO). A Penn State deep-learning soil-moisture model is mentioned by the maker's university. The outcome figures belong to the entire control operation and no source isolates the AI's contribution. FAO is both co-developer and deployer, so its feature is maker-authored. The Times report is independent with named sources (Cressman, Ferrand, Hughes, Jeptoo, Owuor, Craig)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "FAO states that East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. FAO says they protected 36.6 million people's food security. The Times quotes FAO's USD 1.5 billion averted since February 2020. These are estimates for the whole operation; AI data handling was one part." }, { "group": "organizational", "depth": 2, "reason": "FAO received up to 2,500 records a day with nearly 25 percent unusable. PlantVillage's AI removed the unwanted data. Over 240,000 records were collected in a year from scouts and citizens who could not have used the discontinued eLocust3 tablets." }, { "group": "personal", "reason": "No individually documented farmer outcome in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and three press releases from the makers. 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Anyone with a smartphone could record georeferenced locust sightings; algorithms checked photos. Penn State also extended a deep-learning soil-moisture model to the affected region. FAO reported receiving up to 2,500 records a day, nearly 25 percent unusable or incorrect. It asked PlantVillage to use artificial intelligence to identify and remove the unwanted data before sharing locations with ground and air control teams. The New York Times reported over 240,000 records collected in a year by PlantVillage scouts, government personnel and citizens. The wider operation also used Garmin satellite devices, EarthRanger (Vulcan) and 28 aircraft coordinated with 51 Degrees. FAO's 6 May 2021 feature says East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. They protected 36.6 million people's food security and avoided USD 1.56 billion in losses, it says. The Times quoted FAO's estimate of USD 1.5 billion averted since February 2020. It quoted FAO's Cyril Ferrand saying swarms were prevented from spilling into the Sahel.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "FAO estimates that the East African control campaign protected food supplies for 36.6 million people. AI helped process locust reports within that wider operation." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "FAO states that East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. FAO says they protected 36.6 million people's food security. The Times quotes FAO's USD 1.5 billion averted since February 2020. These are estimates for the whole operation; AI data handling was one part." }, { "group": "organizational", "depth": 2, "reason": "FAO received up to 2,500 records a day with nearly 25 percent unusable. PlantVillage's AI removed the unwanted data. Over 240,000 records were collected in a year from scouts and citizens who could not have used the discontinued eLocust3 tablets." }, { "group": "personal", "reason": "No individually documented farmer outcome in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Collect georeferenced locust sightings from anyone with a smartphone. 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Automatically check photos and remove unusable records so that FAO can direct survey and control teams." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-05-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version, the value as stated from the cited sources.", "source": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en; https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en; https://www.psu.edu/news/research/story/penn-state-responds-app-aids-un-efforts-control-africas-locust-infestation; https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://www.fao.org/contact-us/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An upsurge with swarms across Kenya, Ethiopia and Somalia in 2020 and no trained locust trackers in those countries", "An existing FAO-PlantVillage app blueprint (fall armyworm) adaptable in under a month", "Scouts recruited and trained by PlantVillage and governments", "Aerial control assets (28 aircraft) coordinated through EarthRanger with 51 Degrees" ], "must_hold": [ "Smartphone coverage among scouts, with Garmin satellite devices where there is no network", "FAO's Desert Locust Information Service acting on records daily", "Control teams and aircraft available to act on reported locations" ], "echoes": [ { "date": "2021-01-13", "setting": "Kenya, Uganda, Ethiopia, Somalia: Kuzi machine-learning locust forecasting with SMS alerts by Selina Wamucii", "model_version": "Kuzi", "outcome": "unknown", "source": "TRT World, 13 January 2021" }, { "date": "2020-07-20", "setting": "East Africa: icipe MaxEnt prediction of breeding regions", "model_version": "MaxEnt (Kimathi et al.)", "outcome": "unknown", "source": "Kimathi et al. 2020, Scientific Reports, doi:10.1038/s41598-020-68895-2" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Scouts need smartphones or satellite devices where networks are unavailable. FAO staff must review reports daily, and control teams and aircraft must be available to act on them." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version, the value as stated from the cited sources.", "source": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en; https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en; https://www.psu.edu/news/research/story/penn-state-responds-app-aids-un-efforts-control-africas-locust-infestation; https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Pennsylvania_State_University; https://www.fao.org/contact-us/en", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Agriculture / pest early warning", "segment": "Desert locust control" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "FAO. 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Interview with Cyril Ferrand and Carla Mucavi, FAO newsroom, 15 June 2022.", "title": "FAO Desert Locust campaign: East Africa upsurge suppressed, Kenya free from Desert Locust", "url": "https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en", "date": "2022-06-15", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0193-source-0001", "AIBD-0193-source-0002", "AIBD-0193-source-0003", "AIBD-0193-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "FAO. A high-tech response is helping countries win the battle against Desert Locusts. FAO feature story, 6 May 2021.", "title": "A high-tech response is helping countries win the battle against Desert Locusts", "url": "https://www.fao.org/newsroom/story/A-high-tech-response-is-helping-countries-win-the-battle-against-Desert-Locusts/en", "date": "2021-05-06", "written_by": "makers", "quote": "nearly 25 percent of the data is unusable or incorrect and FAO again turned to PlantVIllage to harness artificial intelligence to rapidly identify and remove the unwanted data." }, { "kind": "news report", "citation": "Nuwer R. As Locusts Swarmed East Africa, This Tech Helped Squash Them. 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Penn State News, 21 February 2020.", "title": "Penn State responds: App aids UN efforts to control Africa's locust infestation", "url": "https://www.psu.edu/news/research/story/penn-state-responds-app-aids-un-efforts-control-africas-locust-infestation", "date": "2020-02-21", "written_by": "makers", "quote": "a very basic version, eLocust3M, was rapidly developed by Penn State and released for use on mobile phones through Google Play Store on Feb. 20." }, { "kind": "press release", "citation": "FAO. FAO Desert Locust campaign: East Africa upsurge suppressed, Kenya free from Desert Locust. Interview with Cyril Ferrand and Carla Mucavi, FAO newsroom, 15 June 2022.", "title": "FAO Desert Locust campaign: East Africa upsurge suppressed, Kenya free from Desert Locust", "url": "https://www.fao.org/newsroom/detail/fao-desert-locust-campaign-east-africa-upsurge-supressed-kenya-free-from-desert-locust/en", "date": "2022-06-15", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "PlantVillage's app, built with FAO in under a month in 2020, gathered 240,000+ records; AI removed unusable data; FAO credits the tech-enabled operation with averting USD 1.56 billion in losses.", "account": "In early 2020 desert locust swarms swept the Horn of Africa. FAO's senior locust forecaster Keith Cressman asked Penn State's PlantVillage to adapt its app. PlantVillage had built FAO's fall armyworm app. eLocust3M was released on Google Play on 20 February 2020. Anyone with a smartphone could record georeferenced locust sightings; algorithms checked photos. Penn State also extended a deep-learning soil-moisture model to the affected region. FAO reported receiving up to 2,500 records a day, nearly 25 percent unusable or incorrect. It asked PlantVillage to use artificial intelligence to identify and remove the unwanted data before sharing locations with ground and air control teams. The New York Times reported over 240,000 records collected in a year by PlantVillage scouts, government personnel and citizens. The wider operation also used Garmin satellite devices, EarthRanger (Vulcan) and 28 aircraft coordinated with 51 Degrees. FAO's 6 May 2021 feature says East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. They protected 36.6 million people's food security and avoided USD 1.56 billion in losses, it says. The Times quoted FAO's estimate of USD 1.5 billion averted since February 2020. It quoted FAO's Cyril Ferrand saying swarms were prevented from spilling into the Sahel." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software checked submitted photographs and filtered unusable reports before FAO analysis." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used eLocust3M." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "eLocust3M" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "eLocust3m (PlantVillage) with AI data validation feeding FAO's Desert Locust Information Service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "PlantVillage, Pennsylvania State University, with FAO" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "eLocust3m and AI data cleaning feed FAO's East Africa locust control, which may have averted USD 1.56 billion in losses", "headline": "Locust control fed by eLocust3m may have averted USD 1.56 billion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7a5092b62a3325fadb137449f080787adc9da3bf2ff54dec74ee80646e5f1f07" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In early 2020 desert locust swarms swept the Horn of Africa. FAO's senior locust forecaster Keith Cressman asked Penn State's PlantVillage to adapt its app. PlantVillage had built FAO's fall armyworm app. eLocust3M was released on Google Play on 20 February 2020. Anyone with a smartphone could record georeferenced locust sightings; algorithms checked photos. Penn State also extended a deep-learning soil-moisture model to the affected region. FAO reported receiving up to 2,500 records a day, nearly 25 percent unusable or incorrect. It asked PlantVillage to use artificial intelligence to identify and remove the unwanted data before sharing locations with ground and air control teams. The New York Times reported over 240,000 records collected in a year by PlantVillage scouts, government personnel and citizens. The wider operation also used Garmin satellite devices, EarthRanger (Vulcan) and 28 aircraft coordinated with 51 Degrees. FAO's 6 May 2021 feature says East African control operations prevented the loss of 4 million tonnes of cereal and 800 million liters of milk. They protected 36.6 million people's food security and avoided USD 1.56 billion in losses, it says. The Times quoted FAO's estimate of USD 1.5 billion averted since February 2020. It quoted FAO's Cyril Ferrand saying swarms were prevented from spilling into the Sahel.", "replication": { "produced_by": [ "An upsurge with swarms across Kenya, Ethiopia and Somalia in 2020 and no trained locust trackers in those countries", "An existing FAO-PlantVillage app blueprint (fall armyworm) adaptable in under a month", "Scouts recruited and trained by PlantVillage and governments", "Aerial control assets (28 aircraft) coordinated through EarthRanger with 51 Degrees" ], "must_hold": [ "Smartphone coverage among scouts, with Garmin satellite devices where there is no network", "FAO's Desert Locust Information Service acting on records daily", "Control teams and aircraft available to act on reported locations" ], "echoes": [ { "date": "2021-01-13", "setting": "Kenya, Uganda, Ethiopia, Somalia: Kuzi machine-learning locust forecasting with SMS alerts by Selina Wamucii", "model_version": "Kuzi", "outcome": "unknown", "source": "TRT World, 13 January 2021" }, { "date": "2020-07-20", "setting": "East Africa: icipe MaxEnt prediction of breeding regions", "model_version": "MaxEnt (Kimathi et al.)", "outcome": "unknown", "source": "Kimathi et al. 2020, Scientific Reports, doi:10.1038/s41598-020-68895-2" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Scouts and residents sent locust sightings through eLocust3m. PlantVillage’s software removed unusable data. FAO used the reports to direct control teams and aircraft." } } }, "summary": { "total": 91, "addressed": 91, "known": 42, "reviewed": 0, "record_mapped": 42, "not_assessed": 49, "complete": false, "by_state": { "value_present": 42, "not_reported": 0, "unresolved": 0, "not_assessed": 49, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0099", "title": "Targeted staff calls help mothers keep listening to mMitra health messages", "summary": "mMitra’s call scheduler reduced cumulative engagement drops by 32% compared with regular messaging alone over seven weeks.", "date_observed": "2021-06-01", "date_basis": "event", "date_precision": "month", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "ARMMAN tested a scheduler that selected mothers for live calls within its mMitra health-information program in India. The seven-week study began on 26 April 2021 and included 23,003 women. Participants received regular recorded messages, with two groups also receiving staff calls allocated either by the model or in rotation. Model-selected calls reduced cumulative engagement drops by 32.0% compared with messaging alone (p = .044) and by 28.3% compared with rotation-based calls (p = .098). The outcome counted weekly listening, not clinical health. Later studies examined revised models and health behaviors in other cohorts.", "category": "general benefit", "unexpected": false, "purpose": "Allocate limited health-worker service calls to the beneficiaries whose program engagement they are most likely to preserve.", "system": "mMitra’s service-call scheduler, using a restless multi-armed bandit policy with clustered transition estimates and a random forest", "model_version": null, "developer": "Google and Harvard University (Milind Tambe's group) with ARMMAN", "deployer": "ARMMAN", "location": "India (ARMMAN mMitra program areas)", "domain": "Maternal and child health mHealth", "segment": "Non-profit health program", "benefit_type": "Improved Customer Retention", "taxonomy_note": "The benefit concerns continued access to health information. It does not establish improved clinical health or retention of paying customers.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The study found a measurable improvement in sustained access to health information, without establishing clinical health gains." }, { "group": "organizational", "depth": 2, "reason": "ARMMAN improved engagement within its limited capacity for staff calls." } ], "ai_role": { "status": "assessed", "statement": "The model selected participants for limited staff calls. The trial compared that policy with rotation-based calls and regular messaging alone. The developers and ARMMAN jointly conducted the study." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Mate, Aditya, et al. Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 12017–25. https://doi.org/10.1609/aaai.v36i11.21460.", "title": "Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health", "url": "https://ojs.aaai.org/index.php/AAAI/article/view/21460", "date": "2022-06-28", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Taneja, Aparna, and Milind Tambe. Google Research, August 24, 2022.", "title": "Using ML to Boost Engagement with a Maternal and Child Health Program in India", "url": "https://research.google/blog/using-ml-to-boost-engagement-with-a-maternal-and-child-health-program-in-india/", "date": "2022-08-24", "written_by": "makers", "quote": null }, { "kind": "preprint", "citation": "Verma, Shresth, Arpan Dasgupta, Neha Madhiwalla, Aparna Taneja, and Milind Tambe. arXiv:2604.07384, April 8, 2026.", "title": "Decisions and Deployment: The Five-Year SAHELI Project (2020–2025) on Restless Multi-Armed Bandits for Improving Maternal and Child Health Behaviors", "url": "https://arxiv.org/abs/2604.07384", "date": "2026-04-08", "written_by": "makers", "quote": null }, { "kind": "preprint", "citation": "Dasgupta, Arpan, Sarvesh Gharat, Neha Madhiwalla, Aparna Hegde, Milind Tambe, and Aparna Taneja. arXiv:2507.20755, July 28, 2025.", "title": "Beyond Listenership: AI-Predicted Interventions Drive Improvements in Maternal Health Behaviours", "url": "https://arxiv.org/abs/2507.20755", "date": "2025-07-28", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Verma, Shresth, et al. “Expanding Impact of Mobile Health Programs: SAHELI for Maternal and Child Care.” AI Magazine 44 (2023): 363–76. https://doi.org/10.1002/aaai.12126.", "title": "Expanding impact of mobile health programs: SAHELI for maternal and child care", "url": "https://doi.org/10.1002/aaai.12126", "date": "2023-10-12", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Historical listening data that supported estimates of future engagement", "A policy that selected participants for limited staff calls", "ARMMAN health workers who made the calls" ], "must_hold": [ "A weekly definition of engagement based on listening for more than 30 seconds", "A known limit on staff calls", "Usable registration details and listening logs" ], "echoes": [ { "date": null, "setting": "A separate deployment comparison followed a February–April 2022 enrollment cohort for 12 weeks against an equal-sized holdout group", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1002/aaai.12126" }, { "date": null, "setting": "A separate February–April 2024 study of a later decision-focused model, followed by selected telephone surveys", "model_version": null, "outcome": "recurred", "source": "https://arxiv.org/abs/2507.20755" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "124", "title": "Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' Needs", "url": "https://incidentdatabase.ai/cite/124", "severity": null, "group": "personal", "basis": "Optum's algorithm choosing which patients get extra-care outreach under-predicted Black patients' needs; ARMMAN's bandit likewise selects which mothers receive limited service calls." }, "headline": "More mothers keep listening to health messages", "metric": "32.0% fewer cumulative engagement drops than standard care", "comparator": { "against": "Regular health messages alone, and messages with staff calls allocated in rotation", "before": "Cumulative weekly engagement drops in the comparison groups", "after": "32.0% fewer versus messaging alone (p = .044); 28.3% fewer versus rotation (p = .098)", "basis": "measured", "quote": "the RMAB group has 32.0% and 28.3% less cumulative engagement drops as compared to the CSOC and RR groups respectively", "url": "https://ojs.aaai.org/index.php/AAAI/article/view/21460" }, "later": { "status": "scaled", "date": null, "note": "The developers reported that SAHELI had been in routine use since April 2022. A later study compared its engagement results with a holdout group.", "quote": null, "url": "https://doi.org/10.1002/aaai.12126" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 124 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/124", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Verification sweep: the p-values now follow the paper's Table 3 (0.044 against standard care, 0.098 against round robin); ARMMAN's page is marked as written by a co-developer. The record is admitted on the peer-reviewed AAAI paper.", "source": "https://ojs.aaai.org/index.php/AAAI/article/view/21460", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://research.google/blog/using-ml-to-boost-engagement-with-a-maternal-and-child-health-program-in-india/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://research.google/locations/india/; https://armman.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://ojs.aaai.org/index.php/AAAI/article/view/21460", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers, the makers' report and two preprints from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0099", "catalog_version": "1.0.0", "source_fingerprint": "95fb8c5721877ef56c794c65055396bdc43b8e4609455bf0bd59d0d13fd5b24a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "structured", "data": { "records": [ { "id": "AIBD-0099-E01", "design": "three-arm randomized field study", "start_date": "2021-04-26", "duration_weeks": 7, "sample_n": 23003, "arms": [ { "name": "model-selected calls", "n": 7668 }, { "name": "round-robin calls", "n": 7668 }, { "name": "regular messages only", "n": 7667 } ], "outcomes": [ { "metric": "cumulative engagement drops", "comparison": "regular messages only", "relative_reduction_percent": 32.0, "p": 0.044 }, { "metric": "cumulative engagement drops", "comparison": "round-robin calls", "relative_reduction_percent": 28.3, "p": 0.098 } ], "clinical_outcome_measured": false, "source_refs": [ "AIBD-0099-source-0001" ], "locator": "Tables 2–3" }, { "id": "AIBD-0099-E02", "design": "later randomized assignment with selected, matched survey analysis", "intervention_start": "2024-02-05", "intervention_end": "2024-04-21", "registered_n": 34453, "survey_method": "Respondents who answered intervention calls were matched with surveyed controls on Whittle index.", "outcomes": [ { "metric": "reported postpartum calcium use", "control": 0.244, "intervention": 0.306, "p": 0.041262 }, { "metric": "reported postpartum iron use", "control": 0.234, "intervention": 0.283, "p": 0.098111 }, { "metric": "birth-weight response score", "control": 0.766, "intervention": 0.836, "p": 0.007991 } ], "scope": "Reported significant findings are for cohorts 1 and 2. Cohort 3 did not show significant differences. These are survey outcomes, not measured morbidity or mortality.", "source_refs": [ "AIBD-0099-source-0004" ], "locator": "§§3–4; Tables 2–5" }, { "id": "AIBD-0099-E03", "design": "later deployment comparison with a matched holdout group", "registration_period": "February–April 2022", "follow_up_weeks": 12, "intervention_n": 5000, "comparison": "An equal-sized holdout group with similar initial engagement and demographic features received no live service calls.", "allocation_caution": "The paper does not describe random assignment for this comparison.", "outcomes": [ { "metric": "cumulative engagement drops", "relative_reduction_percent": 30.5 }, { "metric": "additional listening over the holdout group", "seconds_total": 59336, "seconds_per_intervention_participant_approx": 12 } ], "scope": "Later SAHELI deployment, distinct from the 2021 randomized trial. The study measures listening rather than clinical outcomes.", "source_refs": [ "AIBD-0099-source-0005" ], "locator": "“Engagement results”; Table 2 and Figure 6." } ] } }, "provenance": { "kind": "source_review", "basis": "Original sources and locators are preserved with each observation.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original evaluation and any distinct follow-up analyses." }, "record_ids": [ "AIBD-0099-E01", "AIBD-0099-E02", "AIBD-0099-E03" ] }, "monetary observations": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "A1, study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed studies do not report a monetary cost or benefit.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed studies do not report a monetary cost or benefit." }, "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "ARMMAN ran mMitra and supplied health workers. The research partners developed and evaluated the scheduler with the NGO." }, "provenance": { "kind": "source_review", "basis": "Affiliations; pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ARMMAN ran mMitra and supplied health workers. The research partners developed and evaluated the scheduler with the NGO." } }, "actors[].ownership_control": { "state": "value_present", "value": { "kind": "text", "text": "ARMMAN operated the health program and held its participant records. Research partners used anonymized data." }, "provenance": { "kind": "source_review", "basis": "Ethics and data discussion.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ARMMAN operated the health program and held its participant records. Research partners used anonymized data." } }, "ai_contribution": { "state": "value_present", "value": { "kind": "text", "text": "The scheduler selected who received a call. Comparing it with round-robin calling tested that selection policy." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The scheduler selected who received a call. Comparing it with round-robin calling tested that selection policy." } }, "ai_relationship": { "state": "value_present", "value": { "kind": "text", "text": "Machine learning estimated listening behavior, and a bandit policy allocated staff calls." }, "provenance": { "kind": "source_review", "basis": "pp. 12019–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Machine learning estimated listening behavior, and a bandit policy allocated staff calls." } }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "structured", "data": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The study found a measurable improvement in sustained access to health information, without establishing clinical health gains." }, { "group": "organizational", "depth": 2, "reason": "ARMMAN improved engagement within its limited capacity for staff calls." } ] } }, "provenance": { "kind": "source_review", "basis": "Application of the existing AIBD depth rubric to the reported benefit.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Personal: 2; Organizational: 2" } }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: two peer-reviewed studies from the makers, the makers' report and two preprints from the makers. 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(2023), Table 2.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The developers reported continuous SAHELI use from April 2022." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "A randomized field study of call scheduling." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A randomized field study of call scheduling." } }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Optum's algorithm choosing which patients get extra-care outreach under-predicted Black patients' needs; ARMMAN's bandit likewise selects which mothers receive limited service calls.", "links": [ { "database": "AI Incident Database", "identifier": "124", "title": "Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' Needs", "url": "https://incidentdatabase.ai/cite/124", "group": "personal", "basis": "Optum's algorithm choosing which patients get extra-care outreach under-predicted Black patients' needs; ARMMAN's bandit likewise selects which mothers receive limited service calls.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "links": [ { "proposition": "Original randomized field study, system details, operational constraints, and engagement results.", "source_refs": [ "AIBD-0099-source-0001" ], "locator": "pp. 12018–23, especially Tables 2–3." }, { "proposition": "Reports routine weekly use after testing.", "source_refs": [ "AIBD-0099-source-0002" ], "locator": "Closing deployment update." }, { "proposition": "Names the later SAHELI deployment and describes the transition to decision-focused learning.", "source_refs": [ "AIBD-0099-source-0003" ], "locator": "Opening deployment history; §§3–4 and Tables 1–2." }, { "proposition": "Original report of a separate 2024 intervention and selected survey follow-up on health behaviors.", "source_refs": [ "AIBD-0099-source-0004" ], "locator": "§§3–4, Tables 1–5." }, { "proposition": "The developers document routine use from April 2022, a separate comparison of engagement, changes to the deployed system, and public code and a data dictionary.", "source_refs": [ "AIBD-0099-source-0005" ], "locator": "“Previous study”; “Deploying SAHELI”; “Application use and payoff,” Table 2; “Responsible AI practices”; endnote 1." } ] } }, "provenance": { "kind": "source_review", "basis": "Original-source lineage.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources are linked to the findings that they support." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "text", "text": "A peer-reviewed randomized study supports the engagement finding. The authors developed the system and included the implementing NGO." }, "provenance": { "kind": "source_review", "basis": "Affiliations; Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A peer-reviewed randomized study supports the engagement finding. The authors developed the system and included the implementing NGO." } }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "Selecting live-call recipients with the model helped sustain listening within the available staff capacity." }, "provenance": { "kind": "source_review", "basis": "Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Selecting live-call recipients with the model helped sustain listening within the available staff capacity." } }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Affiliations and data discussion.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "Researchers were based in India, the United States, and Singapore. The paper does not identify where participant data were hosted or transferred.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers were based in India, the United States, and Singapore. The paper does not identify where participant data were hosted or transferred." } }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "ARMMAN tested the scheduler in its operating mMitra program." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ARMMAN tested the scheduler in its operating mMitra program." } }, "economics[].amount": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No cash amount is reported for the benefit or delivery cost.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "No cash amount is reported for the benefit or delivery cost." } }, "economics[].costs[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The resource constraint was staff capacity: about 225 calls per week in each calling group.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The resource constraint was staff capacity: about 225 calls per week in each calling group." } }, "economics[].counterfactual": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study compared calling policies at similar call capacity, rather than comparing cash expenditure.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The study compared calling policies at similar call capacity, rather than comparing cash expenditure." } }, "economics[].currency_price_basis": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No monetary estimate is reported.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "No monetary estimate is reported." } }, "economics[].gross_net": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No gross or net financial benefit was calculated.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "No gross or net financial benefit was calculated." } }, "economics[].measure_type": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study reports a limit on staff calls, not a monetary benefit.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The study reports a limit on staff calls, not a monetary benefit." } }, "economics[].period_unit": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "Resources were allocated weekly over a seven-week study.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "Resources were allocated weekly over a seven-week study." } }, "economics[].realization": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The engagement improvement was observed. No monetary saving was measured.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The engagement improvement was observed. No monetary saving was measured." } }, "economics[].recipient_payer": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "ARMMAN supplied the staff calls. The paper does not report their cost.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "ARMMAN supplied the staff calls. The paper does not report their cost." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "No return or payback estimate is reported.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "No return or payback estimate is reported." } }, "economics[].valuation_method": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Study methods and results, pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The authors did not assign a monetary value to the engagement improvement.", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations", "display": { "answer": "The authors did not assign a monetary value to the engagement improvement." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The comparison with round-robin calling favored the model, but its p-value was .098. The comparison with messaging alone had p = .044." }, "provenance": { "kind": "source_review", "basis": "Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The comparison with round-robin calling favored the model, but its p-value was .098. The comparison with messaging alone had p = .044." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Regular messages alone, and regular messages with staff calls allocated in rotation." }, "provenance": { "kind": "source_review", "basis": "p. 12021.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Regular messages alone, and regular messages with staff calls allocated in rotation." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Researchers randomly assigned participants to model-selected calls, round-robin calls, or regular messaging alone." }, "provenance": { "kind": "source_review", "basis": "p. 12021.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers randomly assigned participants to model-selected calls, round-robin calls, or regular messaging alone." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "Engagement drops fell by 32.0% versus regular messages alone and 28.3% versus round-robin calling." }, "provenance": { "kind": "source_review", "basis": "Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Engagement drops fell by 32.0% versus regular messages alone and 28.3% versus round-robin calling." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Each calling group received about 225 staff calls a week for seven weeks." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Each calling group received about 225 staff calls a week for seven weeks." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0099-E01", "AIBD-0099-E02", "AIBD-0099-E03" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Identifiers assigned to the evaluations described here.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0099-E01, AIBD-0099-E02, AIBD-0099-E03" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Call logs identified weeks in which a participant listened to at least one message for more than 30 seconds." }, "provenance": { "kind": "source_review", "basis": "pp. 12018, 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Call logs identified weeks in which a participant listened to at least one message for more than 30 seconds." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Cumulative weekly drops in listening engagement." }, "provenance": { "kind": "source_review", "basis": "p. 12022.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Cumulative weekly drops in listening engagement." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "Public SAHELI code and a data dictionary cover the later deployed system. They do not identify the software release used in the 2021 trial." }, "provenance": { "kind": "source_review", "basis": "Mate et al. (2022), p. 12023; Verma et al. (2023), endnote 1; the linked repository README and data dictionary.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Public SAHELI code and a data dictionary cover the later deployed system. They do not identify the software release used in the 2021 trial." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "The groups contained 7,668, 7,668, and 7,667 participants, respectively." }, "provenance": { "kind": "source_review", "basis": "Table 2.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The groups contained 7,668, 7,668, and 7,667 participants, respectively." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The study measured listening, not clinical health. Cumulative drops can count the same participant in more than one week." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–23; Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study measured listening, not clinical health. Cumulative drops can count the same participant in more than one week." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "124", "title": "Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' Needs", "url": "https://incidentdatabase.ai/cite/124", "group": "personal", "basis": "Optum's algorithm choosing which patients get extra-care outreach under-predicted Black patients' needs; ARMMAN's bandit likewise selects which mothers receive limited service calls." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "SAHELI entered routine use in April 2022. Later studies evaluated revised models and health-behavior outcomes." }, "provenance": { "kind": "source_review", "basis": "Verma et al. (2023), Table 2; 2025 preprint, §§3–4.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0005", "AIBD-0099-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "SAHELI entered routine use in April 2022. Later studies evaluated revised models and health-behavior outcomes." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "ARMMAN staff made the calls without knowing the participants’ assigned study group." }, "provenance": { "kind": "source_review", "basis": "p. 12021.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ARMMAN staff made the calls without knowing the participants’ assigned study group." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0099" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The program needed telephone access, listening logs, registration records, and staff who could place live calls." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The program needed telephone access, listening logs, registration records, and staff who could place live calls." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Pregnant women and new mothers enrolled in the program." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Pregnant women and new mothers enrolled in the program." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "The study included 23,003 women. The model group contained 7,668, of whom about 20% received a staff call." }, "provenance": { "kind": "source_review", "basis": "Table 2; p. 12022.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study included 23,003 women. The model group contained 7,668, of whom about 20% received a staff call." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Continued access to maternal and child health information." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18, 12022.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Continued access to maternal and child health information." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "The scheduling policy reduced loss of engagement with health messages." }, "provenance": { "kind": "source_review", "basis": "Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The scheduling policy reduced loss of engagement with health messages." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Limited staff time meant that only some participants received calls. The measured benefit was an aggregate change in listening." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Limited staff time meant that only some participants received calls. The measured benefit was an aggregate change in listening." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Listening was measured over seven weeks." }, "provenance": { "kind": "source_review", "basis": "p. 12021.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Listening was measured over seven weeks." } }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Mothers enrolled in mMitra and ARMMAN’s outreach program." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Mothers enrolled in mMitra and ARMMAN’s outreach program." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Observed in a randomized field study." }, "provenance": { "kind": "source_review", "basis": "Table 3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Observed in a randomized field study." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "The program could call only a small share of participants each week. The study did not establish which clinical outcomes followed." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–23.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The program could call only a small share of participants each week. The study did not establish which clinical outcomes followed." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Sustained listening was the intended benefit." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Sustained listening was the intended benefit." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "The field study took place in ARMMAN’s mMitra program in India." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The field study took place in ARMMAN’s mMitra program in India." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "The system selected mothers for limited staff calls to encourage continued listening to mMitra messages." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system selected mothers for limited staff calls to encourage continued listening to mMitra messages." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "start": "2021-04-26", "duration_weeks": 7, "precision": "day", "display": "From 26 April 2021, for seven weeks", "refs": [ "AIBD-0099-source-0001" ], "current_date_observed": "2021-04-26", "instruction": "Use the observed result period for the case date. Keep the full study period separately; the normalized sort date does not imply a more precise observation.", "observed_result_period": "2021-06", "observed_result_precision": "month", "observed_result_basis": "The study reports its result seven weeks after 26 April 2021, placing the endpoint in June." } }, "provenance": { "kind": "source_review", "basis": "Original study timing.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The seven-week study began on 26 April 2021." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "text", "text": "A 2022 deployment study also found fewer engagement drops. A 2024 study reported some better health behaviors among selected survey respondents." }, "provenance": { "kind": "source_review", "basis": "Verma et al. (2023), “Engagement results”; 2025 preprint, §§3–4 and Tables 2–5.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0005", "AIBD-0099-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A 2022 deployment study also found fewer engagement drops. A 2024 study reported some better health behaviors among selected survey respondents." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "The scheduler needs usable listening histories, current registration details, and a known limit on staff calls." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The scheduler needs usable listening histories, current registration details, and a known limit on staff calls." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 124 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/124", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Verification sweep: the p-values now follow the paper's Table 3 (0.044 against standard care, 0.098 against round robin); ARMMAN's page is marked as written by a co-developer. 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The 2025 preprint is the original source for later health-behavior findings." } }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "role": "retained evidence" }, "provenance": { "kind": "source_review", "basis": "Retained evidence in the reviewed order.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0099-source-0001, AIBD-0099-source-0002, AIBD-0099-source-0003, AIBD-0099-source-0004, AIBD-0099-source-0005" } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "English." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–23, especially Tables 2–3.; Closing deployment update.; Opening deployment history; §§3–4 and Tables 1–2.; §§3–4, Tables 1–5.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The sources come from the development and implementation partnership. Repeated trial results are not independent corroboration." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–23, especially Tables 2–3.; Closing deployment update.; Opening deployment history; §§3–4 and Tables 1–2.; §§3–4, Tables 1–5.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources come from the development and implementation partnership. Repeated trial results are not independent corroboration." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0099-source-0001", "retained_source_order": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "origins": [ { "url": "https://ojs.aaai.org/index.php/AAAI/article/view/21460", "title": "Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health", "locator": "pp. 12018–23, especially Tables 2–3.", "contribution": "Original randomized field study, system details, operational constraints, and engagement results.", "relationship": "Primary study by the developers and implementing NGO, with Google Research, Harvard, ARMMAN, and Singapore Management University affiliations.", "source_refs": [ "AIBD-0099-source-0001" ], "access": "Original publisher PDF downloaded. Methods, system description, evaluation, results, and limitations were read.", "publication_date": "2022-06-28" }, { "url": "https://ojs.aaai.org/index.php/AAAI/article/download/21460/21209", "locator": "Published nine-page paper.", "contribution": "Published nine-page paper.", "relationship": "Access copy, supplement, or earlier version of the same work.", "source_refs": [ "AIBD-0099-source-0001" ] }, { "url": "https://arxiv.org/abs/2109.08075", "locator": "Earlier preprint, first submitted 16 September 2021, revised 27 October 2021.", "contribution": "Earlier preprint, first submitted 16 September 2021, revised 27 October 2021.", "relationship": "Access copy, supplement, or earlier version of the same work.", "source_refs": [ "AIBD-0099-source-0001" ] }, { "url": "https://research.google/blog/using-ml-to-boost-engagement-with-a-maternal-and-child-health-program-in-india/", "title": "Using ML to Boost Engagement with a Maternal and Child Health Program in India", "locator": "Closing deployment update.", "contribution": "Reports routine weekly use after testing.", "relationship": "Original follow-up from the developers; the experimental figures repeat A1.", "source_refs": [ "AIBD-0099-source-0002" ], "access": "Original page retrieved. The deployment update and relevant system and privacy passages were read.", "publication_date": "2022-08-24" }, { "url": "https://arxiv.org/abs/2604.07384", "title": "Decisions and Deployment: The Five-Year SAHELI Project (2020–2025) on Restless Multi-Armed Bandits for Improving Maternal and Child Health Behaviors", "locator": "Opening deployment history; §§3–4 and Tables 1–2.", "contribution": "Names the later SAHELI deployment and describes the transition to decision-focused learning.", "relationship": "Retrospective chapter by developers and ARMMAN. Its older trial and later health-behavior findings derive from earlier studies.", "source_refs": [ "AIBD-0099-source-0003" ], "access": "Original arXiv HTML was read in the deployment-history, empirical-evaluation, architecture, and reference sections.", "publication_date": "2026-04-08" }, { "url": "https://arxiv.org/abs/2507.20755", "title": "Beyond Listenership: AI-Predicted Interventions Drive Improvements in Maternal Health Behaviours", "locator": "§§3–4, Tables 1–5.", "contribution": "Original report of a separate 2024 intervention and selected survey follow-up on health behaviors.", "relationship": "Primary preprint by developers and ARMMAN. The analysis uses selected respondents and matching, not a complete randomized-cohort outcome comparison.", "source_refs": [ "AIBD-0099-source-0004" ], "access": "Original HTML methods, tables, results, ethics, and references were read.", "publication_date": "2025-07-28" }, { "url": "https://doi.org/10.1002/aaai.12126", "title": "Expanding impact of mobile health programs: SAHELI for maternal and child care", "locator": "“Previous study”; “Deploying SAHELI”; “Application use and payoff,” Table 2; “Responsible AI practices”; endnote 1.", "contribution": "The developers document routine use from April 2022, a separate comparison of engagement, changes to the deployed system, and public code and a data dictionary.", "relationship": "Original account of later deployment by the development and implementation partnership. Its repetition of the 2021 trial is not independent corroboration.", "source_refs": [ "AIBD-0099-source-0005" ], "access": "The original publisher HTML was read in the sections covering the previous study, system architecture and pipeline, resource requirements, deployment results, fairness and responsible AI, and endnote 1. The linked repository README and data dictionary were read; code was not executed.", "publication_date": "2023-10-12" }, { "url": "https://github.com/armman-projects/SAHELI", "title": "SAHELI source code", "locator": "README, data_description.md, and repository file listing.", "contribution": "Original implementation repository linked in endnote 1. It contains a pipeline, Whittle-index functions, and a data dictionary for the later system; it does not identify the exact release used in the 2021 trial.", "relationship": "Original implementation repository linked in endnote 1. It contains a pipeline, Whittle-index functions, and a data dictionary for the later system; it does not identify the exact release used in the 2021 trial.", "source_refs": [ "AIBD-0099-source-0005" ] } ], "excluded_or_consolidated_sources": [ { "old_source_ref": "AIBD-0099-source-0002", "url": "https://arxiv.org/pdf/2109.08075", "retained_source_ref": "AIBD-0099-source-0001", "reason": "Mirror or version consolidated into the original work." }, { "old_source_ref": "AIBD-0099-source-0003", "url": "https://armman.org/mmitra/", "reason": "A summary or secondary account was replaced by the original evidence. Any unique earlier quotation remains in the audit artifact." } ], "review_scope": "Original evidence, systems, evaluation methods and results, costs, chronology, human roles, limitations, and follow-up.", "chronology_source": { "url": "https://arxiv.org/abs/2109.08075v1", "title": "Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health", "date": "2021-09-16", "role": "First public version of A1. The trial itself began 26 April 2021." }, "source_relationship_note": "Versions, supplements, reanalyses, and repeated developer statements are not independent replications." } }, "provenance": { "kind": "source_review", "basis": "The original evidence and exact locators are preserved in this assessment.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001", "AIBD-0099-source-0002", "AIBD-0099-source-0003", "AIBD-0099-source-0004", "AIBD-0099-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The 2022 paper reports the trial. The 2023 deployment paper links code. The 2026 chapter’s health-behavior findings originate in the 2025 preprint." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "mMitra’s call scheduler reduced cumulative engagement drops by 32% compared with regular messaging alone over seven weeks." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–23, especially Tables 2–3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "mMitra’s call scheduler reduced cumulative engagement drops by 32% compared with regular messaging alone over seven weeks." } }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "The model selected call recipients. ARMMAN staff placed the calls and supported participants." }, "provenance": { "kind": "source_review", "basis": "pp. 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The model selected call recipients. ARMMAN staff placed the calls and supported participants." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model ranked participants for staff calls within the weekly calling limit." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The model ranked participants for staff calls within the weekly calling limit." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The system modeled two weekly listening states and used 40 groups derived from historical data." }, "provenance": { "kind": "source_review", "basis": "pp. 12019–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system modeled two weekly listening states and used 40 groups derived from historical data." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Registration details and listening logs produced a weekly list of participants for staff to call." }, "provenance": { "kind": "source_review", "basis": "pp. 12018–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Registration details and listening logs produced a weekly list of participants for staff to call." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A restless multi-armed bandit policy used Whittle indices. K-means grouped past listening patterns, and a random forest assigned new participants to groups." }, "provenance": { "kind": "source_review", "basis": "pp. 12019–21.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A restless multi-armed bandit policy used Whittle indices. K-means grouped past listening patterns, and a random forest assigned new participants to groups." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "System description.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The 2021 paper identifies the algorithms and training approach, but not a numbered software release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The 2021 paper identifies the algorithms and training approach, but not a numbered software release." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "The mMitra service-call scheduler." }, "provenance": { "kind": "source_review", "basis": "pp. 12017–18.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The mMitra service-call scheduler." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Researchers from Google Research, Harvard, and Singapore Management University worked with ARMMAN." }, "provenance": { "kind": "source_review", "basis": "Author affiliations.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers from Google Research, Harvard, and Singapore Management University worked with ARMMAN." } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "Targeted staff calls help mothers keep listening to mMitra health messages" }, "provenance": { "kind": "source_review", "basis": "pp. 12018–23, especially Tables 2–3.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Targeted staff calls help mothers keep listening to mMitra health messages" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "95fb8c5721877ef56c794c65055396bdc43b8e4609455bf0bd59d0d13fd5b24a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Participants received recorded health messages. Each week, the scheduler selected a subset for live calls that encouraged continued listening." }, "provenance": { "kind": "source_review", "basis": "pp. 12018, 12021–22.", "record_fields": [], "source_refs": [ "AIBD-0099-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Participants received recorded health messages. Each week, the scheduler selected a subset for live calls that encouraged continued listening." } } }, "summary": { "total": 91, "addressed": 91, "known": 66, "reviewed": 74, "record_mapped": 5, "not_assessed": 12, "complete": false, "by_state": { "value_present": 66, "not_reported": 13, "unresolved": 0, "not_assessed": 12, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0291", "title": "A smart wristwatch prompts a patient's readmission to the emergency department for investigation and management of a postoperative pulmonary embolism (Toronto, JBJS Case Connector 2021)", "summary": "Toronto Western Hospital orthopedic surgeons report a smart wristwatch prompting ED readmission for postoperative pulmonary embolism investigation and management; details are limited to the abstract.", "date_observed": "2021-06-08", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Drynan, Leroux and Zywiel reported a case in JBJS Case Connector (volume 11, issue 2, April-June 2021). They are from the Division of Orthopedic Surgery, Toronto Western Hospital, University of Toronto. It was published online 8 June 2021. The event date is not available. In the abstract's words, a smart wristwatch prompted a patient's readmission to the emergency department for postoperative pulmonary embolism investigation and management. The abstract adds that constant patient monitoring and alerts are advantages of community-based smart technology. It says that surrounding issues must be considered in implementation. The abstract is the only available account. The patient's age, sex, operation, what the watch measured or alerted, the device's brand, and the clinical outcome are therefore not known.", "category": "benefit created", "unexpected": false, "purpose": "Consumer activity monitors are built to track heart rate and activity and to alert the wearer. The abstract credits the watch with prompting the readmission but does not say which function did so.", "system": "Smart wristwatch / personal activity monitor (brand, model and alert type not stated in the abstract)", "model_version": null, "developer": "Not stated (the abstract does not name the device's maker)", "deployer": null, "location": "Toronto, Canada (authors' institution; the abstract does not state where the case occurred)", "domain": "Healthcare (orthopedic surgery; postoperative monitoring)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "The abstract states that the watch prompted the patient's readmission for postoperative pulmonary embolism investigation and management, a serious condition caught in time. The outcome is not detailed, and details are limited to the abstract." } ], "ai_role": { "status": "unassessed", "statement": "The abstract is the only available account. It credits a smart wristwatch with prompting the readmission and refers to monitoring and alerts. It does not say what the device measured, whether an automatic alert fired, or what brand or algorithm was involved. The device's contribution cannot be assessed. The accessible abstract does not establish that AI contributed to the patient’s care." }, "evidence": [ { "kind": "case report", "citation": "Drynan D, Leroux TS, Zywiel MG (2021). Acute Postoperative Pulmonary Embolism Detected at Home by a Patient's Personal Activity Monitor: A Case Report. JBJS Case Connector 11(2). doi:10.2106/JBJS.CC.20.00841 (abstract only; full text paywalled).", "title": "Acute Postoperative Pulmonary Embolism Detected at Home by a Patient's Personal Activity Monitor: A Case Report", "url": "https://doi.org/10.2106/JBJS.CC.20.00841", "date": "2021-06-08", "written_by": "independent", "quote": "prompting a patient readmission to the emergency department" } ], "replication": { "produced_by": [ "A postoperative patient at home wearing a personal activity monitor", "The device producing a reading or alert that the patient or family took as a reason to return to hospital. The abstract does not say which.", "An emergency department that investigated for pulmonary embolism" ], "must_hold": [ "The physiological change from the embolism is one the watch's sensors register", "The wearer acts on the device rather than waiting for scheduled follow-up" ], "echoes": [] }, "paired_incident": null, "headline": "Smart wristwatch prompts ED readmission for pulmonary embolism", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The abstract gives no outcome, device name, or later development. No second account is established.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 4 for personal on the documented outcome, with the reason stated on each rating.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated the publisher and Europe PMC abstract into one clinical case report. The publisher full text remains inaccessible, so its references, device mechanism, clinical outcome, and AI contribution have not been verified. The two abstracts are not separate evidence.", "source": "https://doi.org/10.2106/JBJS.CC.20.00841", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Clarified that an AI contribution is unconfirmed. Retained the case and its depth assessment, but withheld it from homepage highlights.", "source": "https://doi.org/10.2106/JBJS.CC.20.00841", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. 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Acute Postoperative Pulmonary Embolism Detected at Home by a Patient's Personal Activity Monitor: A Case Report. JBJS Case Connector 11(2). doi:10.2106/JBJS.CC.20.00841 (abstract only; full text paywalled).", "title": "Acute Postoperative Pulmonary Embolism Detected at Home by a Patient's Personal Activity Monitor: A Case Report", "url": "https://doi.org/10.2106/JBJS.CC.20.00841", "date": "2021-06-08", "written_by": "independent", "quote": "prompting a patient readmission to the emergency department" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. Other field assessments are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0291-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0291-source-0001" ], "url": "https://doi.org/10.2106/JBJS.CC.20.00841", "relationship": "Original clinical case report by the treating orthopedic team; only its abstract was accessible.", "access_url": "https://pubmed.ncbi.nlm.nih.gov/34101671/", "api_access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:34101671&format=json&resultType=core", "review_extent": "Abstract and bibliographic record read. Europe PMC labels full text subscription required." } ], "same_work_access_versions": [ "https://www.ovid.com/10.2106/JBJS.CC.20.00841", "https://europepmc.org/article/MED/34101671" ], "limitations": [ "Full text, references, notes, and any supplementary material could not be inspected.", "The abstract does not establish the watch model, algorithm, AI contribution, or eventual clinical outcome." ], "ordering_basis": "One original work remains, cited by its DOI.", "lead_source_ref": "AIBD-0291-source-0001", "retained_source_order": [ "AIBD-0291-source-0001" ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source, embedded references, supplements and related firsthand accounts to the extent documented in the access notes.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0291-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Only the abstract was accessible. It does not identify the watch, explain an AI contribution, or describe the patient’s eventual outcome.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Toronto Western Hospital orthopedic surgeons report a smart wristwatch prompting ED readmission for postoperative pulmonary embolism investigation and management; details are limited to the abstract.", "account": "Drynan, Leroux and Zywiel reported a case in JBJS Case Connector (volume 11, issue 2, April-June 2021). They are from the Division of Orthopedic Surgery, Toronto Western Hospital, University of Toronto. It was published online 8 June 2021. The event date is not available. In the abstract's words, a smart wristwatch prompted a patient's readmission to the emergency department for postoperative pulmonary embolism investigation and management. The abstract adds that constant patient monitoring and alerts are advantages of community-based smart technology. It says that surrounding issues must be considered in implementation. The abstract is the only available account. The patient's age, sex, operation, what the watch measured or alerted, the device's brand, and the clinical outcome are therefore not known." } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. Other field assessments are preserved.", "record_fields": [ "account" ], "source_refs": [ "AIBD-0291-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smart wristwatch / personal activity monitor (brand, model and alert type not stated in the abstract)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the abstract does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A smart wristwatch prompts a patient's readmission to the emergency department for investigation and management of a postoperative pulmonary embolism (Toronto, JBJS Case Connector 2021)", "headline": "Smart wristwatch prompts ED readmission for pulmonary embolism" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3e92e088cd102fc7f7f7bfe21135e9d3b02cb62c32c19fdc1f2f9d57f6e050b3" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Drynan, Leroux and Zywiel reported a case in JBJS Case Connector (volume 11, issue 2, April-June 2021). They are from the Division of Orthopedic Surgery, Toronto Western Hospital, University of Toronto. It was published online 8 June 2021. The event date is not available. In the abstract's words, a smart wristwatch prompted a patient's readmission to the emergency department for postoperative pulmonary embolism investigation and management. The abstract adds that constant patient monitoring and alerts are advantages of community-based smart technology. It says that surrounding issues must be considered in implementation. The abstract is the only available account. The patient's age, sex, operation, what the watch measured or alerted, the device's brand, and the clinical outcome are therefore not known.", "replication": { "produced_by": [ "A postoperative patient at home wearing a personal activity monitor", "The device producing a reading or alert that the patient or family took as a reason to return to hospital. The abstract does not say which.", "An emergency department that investigated for pulmonary embolism" ], "must_hold": [ "The physiological change from the embolism is one the watch's sensors register", "The wearer acts on the device rather than waiting for scheduled follow-up" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. Other field assessments are preserved.", "record_fields": [ "account" ], "source_refs": [ "AIBD-0291-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 4, "record_mapped": 24, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0051", "title": "BrainGate participants T5 and T10 use a wireless intracortical brain-computer interface at home to control a tablet and type", "summary": "Two men with tetraplegia used a wireless BrainGate iBCI at home for web browsing, apps and typing, with 24-hour home recording.", "date_observed": "2021-06-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A BrainGate pilot-trial study (Simeral et al.) appeared in IEEE Transactions on Biomedical Engineering in 2021. Authors are at Brown University, Massachusetts General Hospital, Providence VA Medical Center and Stanford University. Two men with tetraplegia from C4 spinal cord injury, T5 (63) and T10 (35), used a 192-electrode intracortical brain-computer interface (iBCI). Wireless transmitters replaced its cables. Sessions were in their homes. A Kalman filter decoder and a linear discriminant classifier converted neural activity into cursor velocity and clicks. Both controlled an unmodified commercial tablet to browse the web and run apps. T5 typed 196 correct characters in 14.6 minutes (13.4 per minute) in Notepad. Neural data were recorded continuously from T10 for 24 hours at home. Calendar dates are not given.", "category": "benefit created", "unexpected": false, "purpose": "Restore computer access and communication for people with paralysis by decoding intended movement from motor cortex", "system": "BrainGate wireless intracortical brain-computer interface (Kalman filter velocity decoder plus linear discriminant click classifier)", "model_version": null, "developer": "BrainGate consortium (Brown University, Massachusetts General Hospital, Providence VA Medical Center, Stanford University)", "deployer": "BrainGate consortium (pilot clinical trial); sessions in participants' homes with research staff present", "location": null, "domain": "Neurotechnology / assistive communication", "segment": "People with tetraplegia", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable participants gained tablet control, web browsing and typing at home. Use was within supervised research sessions rather than independent daily use, so the gain is material but not yet life-changing." }, { "group": "societal", "depth": 1, "reason": "First human demonstration of wireless broadband iBCI use at home; a step toward practical deployment rather than a population-level change." } ], "ai_role": { "status": "assessed", "statement": "Machine-learning decoders (Kalman filter and linear discriminant classifier) are the mechanism that translates intracortical activity into cursor movement and clicks. Wireless hardware enabled home use. The decoded control is what produced the tablet and typing capacity." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Simeral JD, Hosman T, Saab J, et al. (2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Transactions on Biomedical Engineering 68(7).", "title": "Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "date": "2021-06-17", "written_by": "makers", "quote": "Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications." }, { "kind": "peer-reviewed study", "citation": "Simeral JD, et al. (2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Trans Biomed Eng.", "title": "Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia (decoder description)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "date": "2021-06-17", "written_by": "makers", "quote": "For iBCI cursor tasks, a Kalman filter decoder and a linear discriminant classifier were used to estimate continuous 2-D cursor velocity and click state, respectively." }, { "kind": "peer-reviewed study", "citation": "Nuyujukian P, Albites Sanabria J, Saab J, et al. (2018). Cortical control of a tablet computer by people with paralysis. PLoS One 13(11).", "title": "Cortical control of a tablet computer by people with paralysis", "url": "https://europepmc.org/abstract/MED/30462658", "date": "2018-11-21", "written_by": "makers", "quote": "Neural activity was decoded in real time as a point-and-click wireless Bluetooth mouse, allowing participants to use common and recreational applications" } ], "replication": { "produced_by": [ "Chronically implanted microelectrode arrays with usable spiking signals", "Daily Kalman filter and linear discriminant decoder calibration", "Wireless transmitters removing the cable tether" ], "must_hold": [ "Stable array signal quality years after implantation", "Research staff available to set up sessions", "Participant retains intention-to-move signals in motor cortex" ], "echoes": [ { "date": "2018-11-21", "setting": "Three BrainGate2 participants controlling an unmodified tablet with a cabled iBCI", "model_version": null, "outcome": "recurred", "source": "Nuyujukian et al. (2018) PLoS One, PMID 30462658" } ] }, "paired_incident": null, "headline": "BrainGate wireless iBCI lets T5 and T10 use a tablet at home", "metric": "T5 typed 196 correct characters in 14.6 minutes (13.4 per minute)", "comparator": { "against": "the cabled intracortical BCI", "before": null, "after": "Communication bitrates were equivalent between cabled and wireless configurations.", "basis": "measured", "quote": "Communication bitrates were equivalent between cabled and wireless configurations.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/BrainGate; https://www.braingate.org/about-braingate/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to BrainGate consortium.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0051", "catalog_version": "1.0.0", "source_fingerprint": "1444ea6548649f977386d2fee1ba8ef864277f63962b987cbdc9ee7d4dd30db6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0051-source-0001", "AIBD-0051-source-0002", "AIBD-0051-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "BrainGate consortium (Brown University, Massachusetts General Hospital, Providence VA Medical Center, Stanford University)", "deployer": "BrainGate consortium (pilot clinical trial); sessions in participants' homes with research staff present" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Machine-learning decoders (Kalman filter and linear discriminant classifier) are the mechanism that translates intracortical activity into cursor movement and clicks. Wireless hardware enabled home use. The decoded control is what produced the tablet and typing capacity." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Machine-learning decoders (Kalman filter and linear discriminant classifier) are the mechanism that translates intracortical activity into cursor movement and clicks. Wireless hardware enabled home use. The decoded control is what produced the tablet and typing capacity." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable participants gained tablet control, web browsing and typing at home. Use was within supervised research sessions rather than independent daily use, so the gain is material but not yet life-changing." }, { "group": "societal", "depth": 1, "reason": "First human demonstration of wireless broadband iBCI use at home; a step toward practical deployment rather than a population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: two peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable participants gained tablet control, web browsing and typing at home. Use was within supervised research sessions rather than independent daily use, so the gain is material but not yet life-changing." }, { "group": "societal", "depth": 1, "reason": "First human demonstration of wireless broadband iBCI use at home; a step toward practical deployment rather than a population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable participants gained tablet control, web browsing and typing at home. Use was within supervised research sessions rather than independent daily use, so the gain is material but not yet life-changing." }, { "group": "societal", "depth": 1, "reason": "First human demonstration of wireless broadband iBCI use at home; a step toward practical deployment rather than a population-level change." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, 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(2018) PLoS One, PMID 30462658" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Chronically implanted microelectrode arrays with usable spiking signals", "Daily Kalman filter and linear discriminant decoder calibration", "Wireless transmitters removing the cable tether" ], "must_hold": [ "Stable array signal quality years after implantation", "Research staff available to set up sessions", "Participant retains intention-to-move signals in motor cortex" ], "echoes": [ { "date": "2018-11-21", "setting": "Three BrainGate2 participants controlling an unmodified tablet with a cabled iBCI", "outcome": "recurred", "source": "Nuyujukian et al. 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(2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Transactions on Biomedical Engineering 68(7).", "title": "Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "date": "2021-06-17", "written_by": "makers", "quote": "Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications." }, { "kind": "peer-reviewed study", "citation": "Simeral JD, et al. (2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Trans Biomed Eng.", "title": "Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia (decoder description)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "date": "2021-06-17", "written_by": "makers", "quote": "For iBCI cursor tasks, a Kalman filter decoder and a linear discriminant classifier were used to estimate continuous 2-D cursor velocity and click state, respectively." }, { "kind": "peer-reviewed study", "citation": "Nuyujukian P, Albites Sanabria J, Saab J, et al. (2018). Cortical control of a tablet computer by people with paralysis. PLoS One 13(11).", "title": "Cortical control of a tablet computer by people with paralysis", "url": "https://europepmc.org/abstract/MED/30462658", "date": "2018-11-21", "written_by": "makers", "quote": "Neural activity was decoded in real time as a point-and-click wireless Bluetooth mouse, allowing participants to use common and recreational applications" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0051-source-0001", "AIBD-0051-source-0002", "AIBD-0051-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Simeral JD, Hosman T, Saab J, et al. (2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. IEEE Transactions on Biomedical Engineering 68(7).", "title": "Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8218873/", "date": "2021-06-17", "written_by": "makers", "quote": "Participants also used the wireless iBCI to control a standard commercial tablet computer to browse the web and use several mobile applications." }, { "kind": "peer-reviewed study", "citation": "Simeral JD, et al. (2021). Home Use of a Percutaneous Wireless Intracortical Brain-Computer Interface by Individuals With Tetraplegia. 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PLoS One 13(11).", "title": "Cortical control of a tablet computer by people with paralysis", "url": "https://europepmc.org/abstract/MED/30462658", "date": "2018-11-21", "written_by": "makers", "quote": "Neural activity was decoded in real time as a point-and-click wireless Bluetooth mouse, allowing participants to use common and recreational applications" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Two men with tetraplegia used a wireless BrainGate iBCI at home for web browsing, apps and typing, with 24-hour home recording.", "account": "A BrainGate pilot-trial study (Simeral et al.) appeared in IEEE Transactions on Biomedical Engineering in 2021. Authors are at Brown University, Massachusetts General Hospital, Providence VA Medical Center and Stanford University. Two men with tetraplegia from C4 spinal cord injury, T5 (63) and T10 (35), used a 192-electrode intracortical brain-computer interface (iBCI). Wireless transmitters replaced its cables. Sessions were in their homes. A Kalman filter decoder and a linear discriminant classifier converted neural activity into cursor velocity and clicks. Both controlled an unmodified commercial tablet to browse the web and run apps. T5 typed 196 correct characters in 14.6 minutes (13.4 per minute) in Notepad. Neural data were recorded continuously from T10 for 24 hours at home. Calendar dates are not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "BrainGate wireless intracortical brain-computer interface (Kalman filter velocity decoder plus linear discriminant click classifier)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "BrainGate consortium (Brown University, Massachusetts General Hospital, Providence VA Medical Center, Stanford University)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "BrainGate participants T5 and T10 use a wireless intracortical brain-computer interface at home to control a tablet and type", "headline": "BrainGate wireless iBCI lets T5 and T10 use a tablet at home" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1444ea6548649f977386d2fee1ba8ef864277f63962b987cbdc9ee7d4dd30db6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A BrainGate pilot-trial study (Simeral et al.) appeared in IEEE Transactions on Biomedical Engineering in 2021. Authors are at Brown University, Massachusetts General Hospital, Providence VA Medical Center and Stanford University. Two men with tetraplegia from C4 spinal cord injury, T5 (63) and T10 (35), used a 192-electrode intracortical brain-computer interface (iBCI). Wireless transmitters replaced its cables. Sessions were in their homes. A Kalman filter decoder and a linear discriminant classifier converted neural activity into cursor velocity and clicks. Both controlled an unmodified commercial tablet to browse the web and run apps. T5 typed 196 correct characters in 14.6 minutes (13.4 per minute) in Notepad. Neural data were recorded continuously from T10 for 24 hours at home. Calendar dates are not given.", "replication": { "produced_by": [ "Chronically implanted microelectrode arrays with usable spiking signals", "Daily Kalman filter and linear discriminant decoder calibration", "Wireless transmitters removing the cable tether" ], "must_hold": [ "Stable array signal quality years after implantation", "Research staff available to set up sessions", "Participant retains intention-to-move signals in motor cortex" ], "echoes": [ { "date": "2018-11-21", "setting": "Three BrainGate2 participants controlling an unmodified tablet with a cabled iBCI", "outcome": "recurred", "source": "Nuyujukian et al. (2018) PLoS One, PMID 30462658" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0041", "title": "Rijksmuseum uses neural networks to reconstruct the strips cut from Rembrandt's The Night Watch in 1715", "summary": "Rijksmuseum used neural networks to reconstruct The Night Watch's 1715-trimmed edges, displayed complete from 23 June 2021.", "date_observed": "2021-06-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 23 June 2021 the Rijksmuseum in Amsterdam displayed Rembrandt's The Night Watch with reconstructions of the strips cut from all four sides in 1715. The canvas was trimmed to fit a wall in the Town Hall. Rijksmuseum senior scientist Robert Erdmann trained artificial neural networks on the original and on a seventeenth-century copy attributed to Gerrit Lundens. They generated the missing sections in his style. Printed reconstructions were mounted around the original for the following months. Director Taco Dibbits said: “Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic.” Hyperallergic reported the project independently on 24 June 2021.", "category": "benefit created", "unexpected": false, "purpose": "The networks were built specifically to reconstruct the trimmed sections from the Lundens copy; the display was that purpose.", "system": "Artificial neural networks trained on The Night Watch and the Lundens copy (Rijksmuseum, Robert Erdmann)", "model_version": null, "developer": "Rijksmuseum (Robert Erdmann)", "deployer": "Rijksmuseum", "location": "Amsterdam, Netherlands", "domain": "Cultural heritage / museums", "segment": "Art conservation and display", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 1, "reason": "Visitors could see the composition complete for the first time in 300 years; a cultural benefit from a temporary display." }, { "group": "organizational", "depth": 1, "reason": "The museum gained a research-based reconstruction and a public exhibition." } ], "ai_role": { "status": "assessed", "statement": "The neural networks generated the pixel content of the missing strips in Rembrandt's style from the Lundens copy. The copy's existence and curatorial choices were preconditions." }, "evidence": [ { "kind": "press release", "citation": "Rijksmuseum (23 Jun 2021). For the first time in 300 years The Night Watch is complete again. Press release (operating institution's statement).", "title": "For the first time in 300 years The Night Watch is complete again", "url": "https://www.rijksmuseum.nl/en/press/press-releases/for-the-first-time-in-300-years-the-night-watch-is-complete-again", "date": "2021-06-23", "written_by": "makers", "quote": "Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic." }, { "kind": "news report", "citation": "Bishara H (24 Jun 2021). See Rembrandt's 'The Night Watch' in Its Entirety, Thanks to AI Restoration. 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For the first time in 300 years The Night Watch is complete again. Press release (operating institution's statement).", "title": "For the first time in 300 years The Night Watch is complete again", "url": "https://www.rijksmuseum.nl/en/press/press-releases/for-the-first-time-in-300-years-the-night-watch-is-complete-again", "date": "2021-06-23", "written_by": "makers", "quote": "Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic." }, { "kind": "news report", "citation": "Bishara H (24 Jun 2021). See Rembrandt's 'The Night Watch' in Its Entirety, Thanks to AI Restoration. Hyperallergic.", "title": "See Rembrandt's 'The Night Watch' in Its Entirety, Thanks to AI Restoration", "url": "https://hyperallergic.com/artificial-intelligence-helps-reconstruct-the-night-watch-rembrandt/", "date": "2021-06-24", "written_by": "independent", "quote": "Each generation has used the tools available to it to attempt to reconstruct the painting." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0041-source-0001", "AIBD-0041-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Rijksmuseum (23 Jun 2021). For the first time in 300 years The Night Watch is complete again. Press release (operating institution's statement).", "title": "For the first time in 300 years The Night Watch is complete again", "url": "https://www.rijksmuseum.nl/en/press/press-releases/for-the-first-time-in-300-years-the-night-watch-is-complete-again", "date": "2021-06-23", "written_by": "makers", "quote": "Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic." }, { "kind": "news report", "citation": "Bishara H (24 Jun 2021). See Rembrandt's 'The Night Watch' in Its Entirety, Thanks to AI Restoration. Hyperallergic.", "title": "See Rembrandt's 'The Night Watch' in Its Entirety, Thanks to AI Restoration", "url": "https://hyperallergic.com/artificial-intelligence-helps-reconstruct-the-night-watch-rembrandt/", "date": "2021-06-24", "written_by": "independent", "quote": "Each generation has used the tools available to it to attempt to reconstruct the painting." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Rijksmuseum used neural networks to reconstruct The Night Watch's 1715-trimmed edges, displayed complete from 23 June 2021.", "account": "On 23 June 2021 the Rijksmuseum in Amsterdam displayed Rembrandt's The Night Watch with reconstructions of the strips cut from all four sides in 1715. The canvas was trimmed to fit a wall in the Town Hall. Rijksmuseum senior scientist Robert Erdmann trained artificial neural networks on the original and on a seventeenth-century copy attributed to Gerrit Lundens. They generated the missing sections in his style. Printed reconstructions were mounted around the original for the following months. Director Taco Dibbits said: “Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic.” Hyperallergic reported the project independently on 24 June 2021." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Artificial neural networks trained on The Night Watch and the Lundens copy (Rijksmuseum, Robert Erdmann)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rijksmuseum (Robert Erdmann)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rijksmuseum uses neural networks to reconstruct the strips cut from Rembrandt's The Night Watch in 1715", "headline": "Rijksmuseum neural networks restore The Night Watch's strips" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b8b62b5b855f35d5eb89bc476b8d30d14f9e7c2f4b63239f985c99cac8750321" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 23 June 2021 the Rijksmuseum in Amsterdam displayed Rembrandt's The Night Watch with reconstructions of the strips cut from all four sides in 1715. The canvas was trimmed to fit a wall in the Town Hall. Rijksmuseum senior scientist Robert Erdmann trained artificial neural networks on the original and on a seventeenth-century copy attributed to Gerrit Lundens. They generated the missing sections in his style. Printed reconstructions were mounted around the original for the following months. Director Taco Dibbits said: “Thanks to this reconstruction, we can now see that the composition as it was painted by Rembrandt was even more dynamic.” Hyperallergic reported the project independently on 24 June 2021.", "replication": { "produced_by": [ "A contemporaneous copy showing the lost sections", "High-resolution imaging of the original", "Neural networks trained to map the copy's style to the original's" ], "must_hold": [ "The copy is reliable for composition", "The museum presents the output as reconstruction, not original" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0011", "title": "SARUAV convolutional-network detector locates an unconscious 65-year-old in tall grass during a Bieszczady Mountain Rescue search", "summary": "29 June 2021: SARUAV CNN flagged a 65-year-old man unconscious in tall grass after 24+ h; GOPR Bieszczady retrieved him alive", "date_observed": "2021-06-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Monday 28 June 2021 at about 4 pm a 65-year-old man with Alzheimer's disease left his home in Cergowa, south-east Poland. He had a stroke the previous day. Police and tracking dogs did not find him after a storm. On Tuesday 29 June the Bieszczady Mountain Rescue Service (GOPR Bieszczady) flew four drone flights. It ran SARUAV, software from University of Wrocław researchers that uses convolutional neural networks (CNNs) to find people in nadir aerial images, on 782 images. After 4 h 31 min of analysis the system detected him and returned his coordinates. He was lying unconscious in grass over two meters tall after more than 24 hours outdoors. GOPR rescuers carried him out and handed him to the ambulance service. No cited source gives the day of the find outright. 29 June follows from the 28 June 4 pm departure and the GOPR communique quoted by Świat Dronów. It opens “Od wczoraj – 28 czerwca” (“since yesterday, 28 June”) and says the program flagged him after almost 24 hours.", "category": "harm prevented", "unexpected": false, "purpose": "Built to detect people automatically in drone imagery for search and rescue; this benefit is that purpose.", "system": "SARUAV (Search and Rescue with Unmanned Aerial Vehicle) human detection software", "model_version": "SARUAV, run on images from DJI Matrice 300 drones", "developer": "SARUAV Ltd. / University of Wrocław (team of Tomasz Niedzielski)", "deployer": "Bieszczady Mountain Rescue Service (GOPR Bieszczady)", "location": "Cergowa, Poland", "domain": "Search and rescue", "segment": "Mountain rescue", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "A 65-year-old man with Alzheimer's and a stroke a day earlier lay unconscious in two-meter grass after over 24 hours outdoors. He was found and handed to the ambulance service alive." }, { "group": "organizational", "depth": 2, "reason": "GOPR Bieszczady closed a search that police, dogs and ground teams had not resolved, in what it called the first such find in Poland." } ], "ai_role": { "status": "assessed", "statement": "The CNN detector returned the man's coordinates after police and tracking dogs had failed. Rescuers then retrieved him. Three of the five case-report authors work for SARUAV Ltd., so the independent confirmation is the GOPR Bieszczady account quoted in the Polish press." }, "evidence": [ { "kind": "case report", "citation": "Niedzielski, T., Jurecka, M., Miziński, B., Pawul, W., Motyl, T. (2021). First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland). Remote Sensing 13(23):4903. doi:10.3390/rs13234903.", "title": "First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland)", "url": "https://doi.org/10.3390/rs13234903", "date": "2021-12-03", "written_by": "makers", "quote": "After 4 h 31 min of the analysis, the system successfully detected the missing person and provided his coordinates" }, { "kind": "news report", "citation": "Olejarka, B. (2021). Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce. Super Express (Rzeszów).", "title": "Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce", "url": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html", "date": "2021-07-09", "written_by": "independent", "quote": "Mamy odnalezienie! Pierwsze w Polsce skuteczne odnalezienie poszukiwanego za pomocą drona i programu SARUAV!" }, { "kind": "news report", "citation": "oiot.pl (2021). Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "title": "Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "url": "https://oiot.pl/dron-saruav-uratowal-zycie-czlowiekowi-w-polsce/", "date": "2021-06-30", "written_by": "independent", "quote": "Pomoc dotarła na czas, a zaginiony został bezpiecznie przekazany w ręce pogotowia ratunkowego." }, { "kind": "news report", "citation": "Świat Dronów (2021). Polski system SARUAV uratował życie zaginionemu mężczyźnie.", "title": "Polski system SARUAV uratował życie zaginionemu mężczyźnie", "url": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "date": "2021-06-30", "written_by": "independent", "quote": "Po prawie 24 godzinach od zginięcia program wskazał potencjalnego poszukiwanego" }, { "kind": "press release", "citation": "University of Wrocław (n.d.). Another missing person found using the SARUAV system. uwr.edu.pl.", "title": "Another missing person found using the SARUAV system", "url": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/", "date": null, "written_by": "makers", "quote": "the world's first automatic detection of a missing person on aerial imagery taken from a drone" } ], "replication": { "produced_by": [ "Nadir drone imagery at close range over the search area", "CNN detector run during the search, with rescuers able to verify hits and reach the coordinates" ], "must_hold": [ "The person is within the imaged area and visible from above", "Processing completes while the person can still be helped" ], "echoes": [ { "date": "2024-08-01", "setting": "Sand in Taufers area, South Tyrol, Italy, “beginning of August 2024” (first day of month used): Bergrettungsdienst im Alpenverein Südtirol drone team used SARUAV to find a missing person, deceased, in terrain helicopters had searched; reported by the developer's university (University of Wrocław), not an independent source", "model_version": null, "outcome": "recurred", "source": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/" } ] }, "paired_incident": null, "headline": "SARUAV finds an unconscious 65-year-old alive in tall grass", "metric": "After 4 h 31 min of analysis the system detected him and returned his coordinates", "comparator": { "against": "the ground search by police officers and rescuers with tracking dogs, which had failed", "before": "Psy zgubiły trop (the dogs lost the scent); police and rescuers could not find him", "after": "Po prawie 24 godzinach od zginięcia program wskazał potencjalnego poszukiwanego (after almost 24 hours the program indicated the probable missing person)", "basis": "measured", "quote": "Burza, która przeszła nad terenem gdzie zgubił się chory 65-letni mężczyzna, utrudniła poszukiwania. Psy zgubiły trop. Pomogła nowoczesna technologia i to w ostatniej chwili, bo mężczyzna leżał w ponad dwumetrowych zaroślach bez ruchu.", "url": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html" }, "later": null, "value": null, "developer_country": "Poland", "deployer_country": "Poland", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added to the account that the 29 June date is derived from the 28 June departure and the GOPR communique rather than stated outright in any source, and dated the Świat Dronów report 30 June 2021 from its page metadata; the August 2024 echo keeps its disclosed first-of-month placeholder because dates must be full ISO days.", "source": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html; https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.saruav.pl/; https://pl.wikipedia.org/wiki/Grupa_Bieszczadzka_GOPR", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' case report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0011", "catalog_version": "1.0.0", "source_fingerprint": "d4256ad892f41eb9433d9d2982c154a0f8fd762436e63458ebdcd743a48027f3", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0011-source-0001", "AIBD-0011-source-0002", "AIBD-0011-source-0003", "AIBD-0011-source-0004", "AIBD-0011-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "SARUAV Ltd. / University of Wrocław (team of Tomasz Niedzielski)", "deployer": "Bieszczady Mountain Rescue Service (GOPR Bieszczady)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The CNN detector returned the man's coordinates after police and tracking dogs had failed. Rescuers then retrieved him. Three of the five case-report authors work for SARUAV Ltd., so the independent confirmation is the GOPR Bieszczady account quoted in the Polish press." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The CNN detector returned the man's coordinates after police and tracking dogs had failed. Rescuers then retrieved him. Three of the five case-report authors work for SARUAV Ltd., so the independent confirmation is the GOPR Bieszczady account quoted in the Polish press." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "A 65-year-old man with Alzheimer's and a stroke a day earlier lay unconscious in two-meter grass after over 24 hours outdoors. He was found and handed to the ambulance service alive." }, { "group": "organizational", "depth": 2, "reason": "GOPR Bieszczady closed a search that police, dogs and ground teams had not resolved, in what it called the first such find in Poland." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports, the makers' case report and the makers' press release. 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"coverage": "partial", "family": "evaluations", "display": { "answer": "After 4 h 31 min of analysis the system detected him and returned his coordinates", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0011" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Monday 28 June 2021 at about 4 pm a 65-year-old man with Alzheimer's disease left his home in Cergowa, south-east Poland. He had a stroke the previous day. Police and tracking dogs did not find him after a storm. On Tuesday 29 June the Bieszczady Mountain Rescue Service (GOPR Bieszczady) flew four drone flights. It ran SARUAV, software from University of Wrocław researchers that uses convolutional neural networks (CNNs) to find people in nadir aerial images, on 782 images. After 4 h 31 min of analysis the system detected him and returned his coordinates. He was lying unconscious in grass over two meters tall after more than 24 hours outdoors. GOPR rescuers carried him out and handed him to the ambulance service. No cited source gives the day of the find outright. 29 June follows from the 28 June 4 pm departure and the GOPR communique quoted by Świat Dronów. It opens “Od wczoraj – 28 czerwca” (“since yesterday, 28 June”) and says the program flagged him after almost 24 hours.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "A 65-year-old man with Alzheimer's and a stroke a day earlier lay unconscious in two-meter grass after over 24 hours outdoors. He was found and handed to the ambulance service alive." }, { "group": "organizational", "depth": 2, "reason": "GOPR Bieszczady closed a search that police, dogs and ground teams had not resolved, in what it called the first such find in Poland." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect people automatically in drone imagery for search and rescue; this benefit is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cergowa, Poland", "developer_country": "Poland", "deployer_country": "Poland" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect people automatically in drone imagery for search and rescue; this benefit is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-06-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added to the account that the 29 June date is derived from the 28 June departure and the GOPR communique rather than stated outright in any source, and dated the Świat Dronów report 30 June 2021 from its page metadata; the August 2024 echo keeps its disclosed first-of-month placeholder because dates must be full ISO days.", "source": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html; https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.saruav.pl/; https://pl.wikipedia.org/wiki/Grupa_Bieszczadzka_GOPR", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Nadir drone imagery at close range over the search area", "CNN detector run during the search, with rescuers able to verify hits and reach the coordinates" ], "must_hold": [ "The person is within the imaged area and visible from above", "Processing completes while the person can still be helped" ], "echoes": [ { "date": "2024-08-01", "setting": "Sand in Taufers area, South Tyrol, Italy, “beginning of August 2024” (first day of month used): Bergrettungsdienst im Alpenverein Südtirol drone team used SARUAV to find a missing person, deceased, in terrain helicopters had searched; reported by the developer's university (University of Wrocław), not an independent source", "outcome": "recurred", "source": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Nadir drone imagery at close range over the search area", "CNN detector run during the search, with rescuers able to verify hits and reach the coordinates" ], "must_hold": [ "The person is within the imaged area and visible from above", "Processing completes while the person can still be helped" ], "echoes": [ { "date": "2024-08-01", "setting": "Sand in Taufers area, South Tyrol, Italy, “beginning of August 2024” (first day of month used): Bergrettungsdienst im Alpenverein Südtirol drone team used SARUAV to find a missing person, deceased, in terrain helicopters had searched; reported by the developer's university (University of Wrocław), not an independent source", "outcome": "recurred", "source": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added to the account that the 29 June date is derived from the 28 June departure and the GOPR communique rather than stated outright in any source, and dated the Świat Dronów report 30 June 2021 from its page metadata; the August 2024 echo keeps its disclosed first-of-month placeholder because dates must be full ISO days.", "source": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html; https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.saruav.pl/; https://pl.wikipedia.org/wiki/Grupa_Bieszczadzka_GOPR", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Search and rescue", "segment": "Mountain rescue" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Niedzielski, T., Jurecka, M., Miziński, B., Pawul, W., Motyl, T. (2021). First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland). Remote Sensing 13(23):4903. doi:10.3390/rs13234903.", "title": "First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland)", "url": "https://doi.org/10.3390/rs13234903", "date": "2021-12-03", "written_by": "makers", "quote": "After 4 h 31 min of the analysis, the system successfully detected the missing person and provided his coordinates" }, { "kind": "news report", "citation": "Olejarka, B. (2021). Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce. Super Express (Rzeszów).", "title": "Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce", "url": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html", "date": "2021-07-09", "written_by": "independent", "quote": "Mamy odnalezienie! Pierwsze w Polsce skuteczne odnalezienie poszukiwanego za pomocą drona i programu SARUAV!" }, { "kind": "news report", "citation": "oiot.pl (2021). Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "title": "Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "url": "https://oiot.pl/dron-saruav-uratowal-zycie-czlowiekowi-w-polsce/", "date": "2021-06-30", "written_by": "independent", "quote": "Pomoc dotarła na czas, a zaginiony został bezpiecznie przekazany w ręce pogotowia ratunkowego." }, { "kind": "news report", "citation": "Świat Dronów (2021). Polski system SARUAV uratował życie zaginionemu mężczyźnie.", "title": "Polski system SARUAV uratował życie zaginionemu mężczyźnie", "url": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "date": "2021-06-30", "written_by": "independent", "quote": "Po prawie 24 godzinach od zginięcia program wskazał potencjalnego poszukiwanego" }, { "kind": "press release", "citation": "University of Wrocław (n.d.). Another missing person found using the SARUAV system. uwr.edu.pl.", "title": "Another missing person found using the SARUAV system", "url": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/", "written_by": "makers", "quote": "the world's first automatic detection of a missing person on aerial imagery taken from a drone" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0011-source-0001", "AIBD-0011-source-0002", "AIBD-0011-source-0003", "AIBD-0011-source-0004", "AIBD-0011-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Niedzielski, T., Jurecka, M., Miziński, B., Pawul, W., Motyl, T. (2021). First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland). Remote Sensing 13(23):4903. doi:10.3390/rs13234903.", "title": "First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland)", "url": "https://doi.org/10.3390/rs13234903", "date": "2021-12-03", "written_by": "makers", "quote": "After 4 h 31 min of the analysis, the system successfully detected the missing person and provided his coordinates" }, { "kind": "news report", "citation": "Olejarka, B. (2021). Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce. Super Express (Rzeszów).", "title": "Bieszczady. Dron odnalazł zagubionego człowieka! Pierwszy raz w Polsce", "url": "https://www.se.pl/rzeszow/bieszczady-pierwszy-raz-w-polsce-dron-odnalazl-zagubionego-czlowieka-galeria-aa-Lokr-ga7B-yzAt.html", "date": "2021-07-09", "written_by": "independent", "quote": "Mamy odnalezienie! Pierwsze w Polsce skuteczne odnalezienie poszukiwanego za pomocą drona i programu SARUAV!" }, { "kind": "news report", "citation": "oiot.pl (2021). Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "title": "Historia pisze się na naszych oczach: dron z polskim oprogramowaniem SARUAV uratował życie człowiekowi!", "url": "https://oiot.pl/dron-saruav-uratowal-zycie-czlowiekowi-w-polsce/", "date": "2021-06-30", "written_by": "independent", "quote": "Pomoc dotarła na czas, a zaginiony został bezpiecznie przekazany w ręce pogotowia ratunkowego." }, { "kind": "news report", "citation": "Świat Dronów (2021). Polski system SARUAV uratował życie zaginionemu mężczyźnie.", "title": "Polski system SARUAV uratował życie zaginionemu mężczyźnie", "url": "https://www.swiatdronow.pl/polski-system-saruav-uratowal-zycie-zaginionemu-mezczyznie", "date": "2021-06-30", "written_by": "independent", "quote": "Po prawie 24 godzinach od zginięcia program wskazał potencjalnego poszukiwanego" }, { "kind": "press release", "citation": "University of Wrocław (n.d.). Another missing person found using the SARUAV system. uwr.edu.pl.", "title": "Another missing person found using the SARUAV system", "url": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/", "written_by": "makers", "quote": "the world's first automatic detection of a missing person on aerial imagery taken from a drone" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "29 June 2021: SARUAV CNN flagged a 65-year-old man unconscious in tall grass after 24+ h; GOPR Bieszczady retrieved him alive", "account": "On Monday 28 June 2021 at about 4 pm a 65-year-old man with Alzheimer's disease left his home in Cergowa, south-east Poland. He had a stroke the previous day. Police and tracking dogs did not find him after a storm. On Tuesday 29 June the Bieszczady Mountain Rescue Service (GOPR Bieszczady) flew four drone flights. It ran SARUAV, software from University of Wrocław researchers that uses convolutional neural networks (CNNs) to find people in nadir aerial images, on 782 images. After 4 h 31 min of analysis the system detected him and returned his coordinates. He was lying unconscious in grass over two meters tall after more than 24 hours outdoors. GOPR rescuers carried him out and handed him to the ambulance service. No cited source gives the day of the find outright. 29 June follows from the 28 June 4 pm departure and the GOPR communique quoted by Świat Dronów. It opens “Od wczoraj – 28 czerwca” (“since yesterday, 28 June”) and says the program flagged him after almost 24 hours." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The detector located a person in aerial photographs and returned his coordinates." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "SARUAV analyzed photographs from DJI Matrice 300 drones." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "SARUAV analyzed aerial photographs to locate people." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "SARUAV, run on images from DJI Matrice 300 drones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SARUAV (Search and Rescue with Unmanned Aerial Vehicle) human detection software" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "SARUAV Ltd. / University of Wrocław (team of Tomasz Niedzielski)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "SARUAV convolutional-network detector locates an unconscious 65-year-old in tall grass during a Bieszczady Mountain Rescue search", "headline": "SARUAV finds an unconscious 65-year-old alive in tall grass" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d4256ad892f41eb9433d9d2982c154a0f8fd762436e63458ebdcd743a48027f3" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Monday 28 June 2021 at about 4 pm a 65-year-old man with Alzheimer's disease left his home in Cergowa, south-east Poland. He had a stroke the previous day. Police and tracking dogs did not find him after a storm. On Tuesday 29 June the Bieszczady Mountain Rescue Service (GOPR Bieszczady) flew four drone flights. It ran SARUAV, software from University of Wrocław researchers that uses convolutional neural networks (CNNs) to find people in nadir aerial images, on 782 images. After 4 h 31 min of analysis the system detected him and returned his coordinates. He was lying unconscious in grass over two meters tall after more than 24 hours outdoors. GOPR rescuers carried him out and handed him to the ambulance service. No cited source gives the day of the find outright. 29 June follows from the 28 June 4 pm departure and the GOPR communique quoted by Świat Dronów. It opens “Od wczoraj – 28 czerwca” (“since yesterday, 28 June”) and says the program flagged him after almost 24 hours.", "replication": { "produced_by": [ "Nadir drone imagery at close range over the search area", "CNN detector run during the search, with rescuers able to verify hits and reach the coordinates" ], "must_hold": [ "The person is within the imaged area and visible from above", "Processing completes while the person can still be helped" ], "echoes": [ { "date": "2024-08-01", "setting": "Sand in Taufers area, South Tyrol, Italy, “beginning of August 2024” (first day of month used): Bergrettungsdienst im Alpenverein Südtirol drone team used SARUAV to find a missing person, deceased, in terrain helicopters had searched; reported by the developer's university (University of Wrocław), not an independent source", "outcome": "recurred", "source": "https://uwr.edu.pl/en/another-missing-person-found-using-the-saruav-system/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0337", "title": "ATO's nearest-neighbor myTax prompts reached nearly 340,000 taxpayers at tax time 2020; resulting adjustments had an estimated $37 million revenue impact", "summary": "ATO page: at tax time 2020 nearly 340,000 myTax users (7.5%) got real-time prompts from nearest-neighbor checks; adjustments had an estimated revenue impact of about $37 million.", "date_observed": "2021-07-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Australian Taxation Office (ATO) page “How we use data and analytics” states that the ATO uses machine learning, a common form of artificial intelligence. Nearest neighbor methods compare amounts being entered into myTax with those of other people in similar circumstances. If a claim is significantly different from what is expected, a message prompts the taxpayer to check the figures. During tax time in 2020 nearly 340,000 taxpayers, around 7.5% of myTax users, received a pop-up message, the page reports. It suggested they review a specific label. These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million. The same page says the ATO also uses machine-learning algorithms to forecast call-center volumes and speech recognition to transcribe inbound calls. Separately, in 2020 it automated 93,000 franking-credit refunds worth over $42 million for self-preparers over 60 (not described as machine learning). The only cited source independent of the ATO is The Mandarin's report of 25 February 2025. It says the Australian National Audit Office (ANAO) found the ATO's AI governance arrangements only partly effective, and gives no outcome figures. No non-vendor primary source on record gives a recovered figure attributable to machine learning. The $37 million is the ATO's own estimate. The page is undated; the outcome concerns tax time 2020. An Internet Archive copy dated 14 July 2021 contains the 340,000 and $37 million figures.", "category": "benefit created", "unexpected": false, "purpose": "Built to prompt myTax users in real time to check claims that differ from those of similar taxpayers before lodgment. The recorded adjustments are that purpose.", "system": "ATO myTax real-time analytics prompts using nearest-neighbor comparison models", "model_version": null, "developer": "Australian Taxation Office (in-house data and analytics)", "deployer": "Australian Taxation Office", "location": "Australia (national, online myTax lodgment)", "domain": "Public administration: tax compliance", "segment": "National revenue agency", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Taxpayers who corrected claims are not individually documented; the page gives no individual outcome beyond the aggregate prompt count." }, { "group": "organizational", "depth": 1, "reason": "The ATO's own estimate of about $37 million revenue impact from one tax time, with no independent verification and no comparison with total collections given." }, { "group": "societal", "depth": 1, "reason": "Protects public revenue at modest scale: prompts reached 7.5% of myTax users and the stated impact is an estimate." } ], "ai_role": { "status": "assessed", "statement": "The ATO page states that nearest-neighbor methods generate the prompts and that the ATO uses machine learning. It attributes the adjustments to the prompts, though taxpayers themselves make the changes. Only the deployer's account is among the sources for the outcome. The ATO built and runs the system in-house, so its page is both the developer's and the deployer's account. The ANAO audit reported by The Mandarin found AI governance “partly effective” and offers no outcome figures in the cited excerpt." }, "evidence": [ { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics. ato.gov.au (undated page).", "title": "How we use data and analytics", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "date": null, "written_by": "makers", "quote": "During tax time in 2020, nearly 340,000 taxpayers (around 7.5% of myTax users), received a pop-up message through myTax suggesting they review a specific label." }, { "kind": "report", "citation": "Australian Taxation Office (2021). How we use data and analytics. ato.gov.au, Internet Archive capture of 14 Jul 2021 (earliest capture found; same figures as the live page).", "title": "How we use data and analytics (Internet Archive capture, 14 Jul 2021)", "url": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/", "date": "2021-07-14", "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on real-time analytics prompts.", "title": "How we use data and analytics (revenue impact of prompts)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "date": null, "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, description of the nearest neighbour method.", "title": "How we use data and analytics (nearest neighbour)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "date": null, "written_by": "makers", "quote": "Nearest neighbour methods are used to compare amounts being entered into myTax, with those of other people in similar circumstances, along with other checks." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on machine learning.", "title": "How we use data and analytics (machine learning)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "date": null, "written_by": "makers", "quote": "We use a common form of artificial intelligence known as machine learning." }, { "kind": "news report", "citation": "Bajkowski, J. (2025). Auditor whacks ATO over artificial intelligence. The Mandarin, 25 Feb 2025 (ANAO finding).", "title": "Auditor whacks ATO over artificial intelligence", "url": "https://www.themandarin.com.au/287193-auditor-whacks-ato-over-artificial-intelligence/", "date": "2025-02-25", "written_by": "independent", "quote": "partly effective" } ], "replication": { "produced_by": [ "Large volumes of pre-filled third-party data (over 85 million pieces in 2020) giving a comparison base", "Nearest-neighbor comparison of entered amounts against taxpayers in similar circumstances", "A real-time prompt inside myTax before lodgment", "Taxpayers' own decision to adjust a flagged label" ], "must_hold": [ "Comparison groups and thresholds that keep prompts credible to taxpayers", "Continued use of myTax self-preparation at scale", "AI governance that the ANAO found only partly effective in 2025 being maintained or improved", "The ATO's method of estimating revenue impact remaining the only measure, since no independent evaluation is among the sources" ], "echoes": [] }, "paired_incident": null, "headline": "myTax prompts had an estimated $37 million revenue impact", "metric": "adjustments estimated to have a revenue impact of around $37 million", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The Mandarin reported on 25 February 2025 that the ANAO had judged the ATO's AI governance only partly effective. That report gives no later outcome figure for the myTax prompts.", "quote": null, "url": null }, "value": { "amount": "$37 million", "what": "revenue impact of the adjustments taxpayers made after myTax prompts at tax time 2020 (ATO's own estimate)", "who": "the Australian Taxation Office (Australian Government revenue)", "estimate": true, "quote": "During tax time in 2020, nearly 340,000 taxpayers (around 7.5% of myTax users), received a pop-up message through myTax suggesting they review a specific label. These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million.", "url": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/" }, "developer_country": "Australia", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Taxation_Office; https://en.wikipedia.org/wiki/Australian_Taxation_Office", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two reports from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0337", "catalog_version": "1.0.0", "source_fingerprint": "d2f5abf5d3213502938cfd894230a985bb5b4c03032873aec1aeebf4b1f80f2e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0337-source-0001", "AIBD-0337-source-0002", "AIBD-0337-source-0003", "AIBD-0337-source-0004", "AIBD-0337-source-0005", "AIBD-0337-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0337-legacy-value", "DIV-0007" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0337-legacy-value", "DIV-0007" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Australian Taxation Office (in-house data and analytics)", "deployer": "Australian Taxation Office" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ATO page states that nearest-neighbor methods generate the prompts and that the ATO uses machine learning. It attributes the adjustments to the prompts, though taxpayers themselves make the changes. Only the deployer's account is among the sources for the outcome. The ATO built and runs the system in-house, so its page is both the developer's and the deployer's account. The ANAO audit reported by The Mandarin found AI governance “partly effective” and offers no outcome figures in the cited excerpt." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The ATO page states that nearest-neighbor methods generate the prompts and that the ATO uses machine learning. It attributes the adjustments to the prompts, though taxpayers themselves make the changes. Only the deployer's account is among the sources for the outcome. The ATO built and runs the system in-house, so its page is both the developer's and the deployer's account. 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Nearest neighbor methods compare amounts being entered into myTax with those of other people in similar circumstances. If a claim is significantly different from what is expected, a message prompts the taxpayer to check the figures. During tax time in 2020 nearly 340,000 taxpayers, around 7.5% of myTax users, received a pop-up message, the page reports. It suggested they review a specific label. These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million. The same page says the ATO also uses machine-learning algorithms to forecast call-center volumes and speech recognition to transcribe inbound calls. Separately, in 2020 it automated 93,000 franking-credit refunds worth over $42 million for self-preparers over 60 (not described as machine learning). The only cited source independent of the ATO is The Mandarin's report of 25 February 2025. It says the Australian National Audit Office (ANAO) found the ATO's AI governance arrangements only partly effective, and gives no outcome figures. No non-vendor primary source on record gives a recovered figure attributable to machine learning. The $37 million is the ATO's own estimate. The page is undated; the outcome concerns tax time 2020. 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The recorded adjustments are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-07-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; 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https://en.wikipedia.org/wiki/Australian_Taxation_Office", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: tax compliance", "segment": "National revenue agency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Australian Taxation Office (n.d.). 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How we use data and analytics. ato.gov.au, Internet Archive capture of 14 Jul 2021 (earliest capture found; same figures as the live page).", "title": "How we use data and analytics (Internet Archive capture, 14 Jul 2021)", "url": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/", "date": "2021-07-14", "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on real-time analytics prompts.", "title": "How we use data and analytics (revenue impact of prompts)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, description of the nearest neighbour method.", "title": "How we use data and analytics (nearest neighbour)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "Nearest neighbour methods are used to compare amounts being entered into myTax, with those of other people in similar circumstances, along with other checks." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on machine learning.", "title": "How we use data and analytics (machine learning)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "We use a common form of artificial intelligence known as machine learning." }, { "kind": "news report", "citation": "Bajkowski, J. (2025). Auditor whacks ATO over artificial intelligence. 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How we use data and analytics. ato.gov.au, Internet Archive capture of 14 Jul 2021 (earliest capture found; same figures as the live page).", "title": "How we use data and analytics (Internet Archive capture, 14 Jul 2021)", "url": "https://web.archive.org/web/20210714025448/https://www.ato.gov.au/About-ATO/Commitments-and-reporting/Information-and-privacy/How-we-use-data-and-analytics/", "date": "2021-07-14", "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on real-time analytics prompts.", "title": "How we use data and analytics (revenue impact of prompts)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, description of the nearest neighbour method.", "title": "How we use data and analytics (nearest neighbour)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "Nearest neighbour methods are used to compare amounts being entered into myTax, with those of other people in similar circumstances, along with other checks." }, { "kind": "report", "citation": "Australian Taxation Office (n.d.). How we use data and analytics, section on machine learning.", "title": "How we use data and analytics (machine learning)", "url": "https://www.ato.gov.au/about-ato/commitments-and-reporting/information-and-privacy/how-we-use-data-and-analytics", "written_by": "makers", "quote": "We use a common form of artificial intelligence known as machine learning." }, { "kind": "news report", "citation": "Bajkowski, J. (2025). Auditor whacks ATO over artificial intelligence. The Mandarin, 25 Feb 2025 (ANAO finding).", "title": "Auditor whacks ATO over artificial intelligence", "url": "https://www.themandarin.com.au/287193-auditor-whacks-ato-over-artificial-intelligence/", "date": "2025-02-25", "written_by": "independent", "quote": "partly effective" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ATO page: at tax time 2020 nearly 340,000 myTax users (7.5%) got real-time prompts from nearest-neighbor checks; adjustments had an estimated revenue impact of about $37 million.", "account": "The Australian Taxation Office (ATO) page “How we use data and analytics” states that the ATO uses machine learning, a common form of artificial intelligence. Nearest neighbor methods compare amounts being entered into myTax with those of other people in similar circumstances. If a claim is significantly different from what is expected, a message prompts the taxpayer to check the figures. During tax time in 2020 nearly 340,000 taxpayers, around 7.5% of myTax users, received a pop-up message, the page reports. It suggested they review a specific label. These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million. The same page says the ATO also uses machine-learning algorithms to forecast call-center volumes and speech recognition to transcribe inbound calls. Separately, in 2020 it automated 93,000 franking-credit refunds worth over $42 million for self-preparers over 60 (not described as machine learning). The only cited source independent of the ATO is The Mandarin's report of 25 February 2025. It says the Australian National Audit Office (ANAO) found the ATO's AI governance arrangements only partly effective, and gives no outcome figures. No non-vendor primary source on record gives a recovered figure attributable to machine learning. The $37 million is the ATO's own estimate. The page is undated; the outcome concerns tax time 2020. An Internet Archive copy dated 14 July 2021 contains the 340,000 and $37 million figures." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ATO myTax real-time analytics prompts using nearest-neighbor comparison models" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Australian Taxation Office (in-house data and analytics)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ATO's nearest-neighbor myTax prompts reached nearly 340,000 taxpayers at tax time 2020; resulting adjustments had an estimated $37 million revenue impact", "headline": "myTax prompts had an estimated $37 million revenue impact" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d2f5abf5d3213502938cfd894230a985bb5b4c03032873aec1aeebf4b1f80f2e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Australian Taxation Office (ATO) page “How we use data and analytics” states that the ATO uses machine learning, a common form of artificial intelligence. Nearest neighbor methods compare amounts being entered into myTax with those of other people in similar circumstances. If a claim is significantly different from what is expected, a message prompts the taxpayer to check the figures. During tax time in 2020 nearly 340,000 taxpayers, around 7.5% of myTax users, received a pop-up message, the page reports. It suggested they review a specific label. These prompts caused taxpayers to make adjustments estimated to have a revenue impact of around $37 million. The same page says the ATO also uses machine-learning algorithms to forecast call-center volumes and speech recognition to transcribe inbound calls. Separately, in 2020 it automated 93,000 franking-credit refunds worth over $42 million for self-preparers over 60 (not described as machine learning). The only cited source independent of the ATO is The Mandarin's report of 25 February 2025. It says the Australian National Audit Office (ANAO) found the ATO's AI governance arrangements only partly effective, and gives no outcome figures. No non-vendor primary source on record gives a recovered figure attributable to machine learning. The $37 million is the ATO's own estimate. The page is undated; the outcome concerns tax time 2020. An Internet Archive copy dated 14 July 2021 contains the 340,000 and $37 million figures.", "replication": { "produced_by": [ "Large volumes of pre-filled third-party data (over 85 million pieces in 2020) giving a comparison base", "Nearest-neighbor comparison of entered amounts against taxpayers in similar circumstances", "A real-time prompt inside myTax before lodgment", "Taxpayers' own decision to adjust a flagged label" ], "must_hold": [ "Comparison groups and thresholds that keep prompts credible to taxpayers", "Continued use of myTax self-preparation at scale", "AI governance that the ANAO found only partly effective in 2025 being maintained or improved", "The ATO's method of estimating revenue impact remaining the only measure, since no independent evaluation is among the sources" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0082", "title": "CGU, supported by ALICE, cuts R$2.38 million from a 2021 Hospital Federal de Ipanema glove tender and R$5.95 million from an undated INCA glove tender", "summary": "With ALICE support, CGU cut R$2.38m from a 2021 Ipanema hospital glove tender and R$5.95m from an INCA tender; R$8.33m avoided", "date_observed": "2021-07-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A CGU statement of 4 October 2023 describes five preventive audits of tenders by federal hospitals and institutes in Rio de Janeiro. The automated tool ALICE supported them. The CGU says this prevented at least R$8.33 million of overpriced purchases. At the Instituto Nacional de Câncer (INCA), a glove auction estimated at R$11 million was re-estimated at R$5.1 million after ALICE indicated prices above market. That avoided about R$5.95 million. At the Hospital Federal de Ipanema, Pregão 15/2021 for gloves (estimated R$34 million) had reused the price survey of Pregão 05/2021. On CGU's recommendation it was suspended and re-estimated, cutting R$2,381,663.00. The auction held on 21 July 2021 bought every item at or below the new estimates, totaling R$14,315,793.42.", "category": "harm prevented", "unexpected": false, "purpose": "Preventive audit of federal procurement notices using automated risk alerts to stop overpriced purchases before award", "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU automated audit-trail and AI alert tool", "model_version": null, "developer": "Controladoria-Geral da União (CGU), in-house (launched 2015 per the release)", "deployer": "Controladoria-Geral da União (CGU)", "location": "Rio de Janeiro, Brazil", "domain": "Public administration: government audit and procurement control", "segment": "Federal internal control of health-sector purchasing", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No identifiable individual beneficiary; patients benefit only indirectly through preserved hospital budgets." }, { "group": "organizational", "depth": 2, "reason": "Material to the hospitals and the federal budget: R$2,381,663.00 cut from one auction and about R$5.95 million from another. R$8.33 million avoided across the five audits per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale relative to federal purchasing of about R$119 billion a year." } ], "ai_role": { "status": "assessed", "statement": "The CGU states the audits were done “com apoio da ferramenta automatizada ALICE”. At INCA, it says, the overpricing risk was identified “com a ajuda do ALICE”. For the Ipanema tender, suspension followed a CGU recommendation after analysis of the price survey. ALICE's documented role is alerting and supporting the audit; auditors and managers decided. Developer and deployer are the same public body. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." }, "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2023). CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi. gov.br/cgu, 4 Oct 2023.", "title": "CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "por recomendação da CGU, o certame foi suspenso e uma nova estimativa de preços foi realizada. A nova análise reduziu o valor total do pregão em R$ 2.381.663,00." }, { "kind": "press release", "citation": "Controladoria-Geral da União (2023). Same release, 'ALICE' section with 2023 aggregates.", "title": "CGU atua em editais de licitação em hospitais federais (ALICE section)", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "a partir de 16.743 compras analisadas no âmbito nacional, o ALICE emitiu alertas que resultaram na suspensão de 59 compras no valor aproximado de R$ 3.1 bilhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal.", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE, da Controladoria-Geral da União. gov.br/cgu, 30 Dec 2024.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "ALICE alerts on price surveys inconsistent with prices practiced in comparable purchases in the same region", "CGU preventive audits completed before the auction, with recommendations to re-estimate prices", "Hospital managers suspending and re-running the price estimate" ], "must_hold": [ "Tender notices published on the federal purchasing portal where ALICE reads them daily", "Time between publication and auction sufficient for audit and correction", "Availability of market price references" ], "echoes": [ { "date": "2025-01-14", "setting": "Three 2024 Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2024-12-30", "setting": "2024 aggregate: 206 preventive audits opened, R$257.25 million saved (CGU, 30 December 2024)", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "101", "title": "Dutch Families Wrongfully Accused of Tax Fraud Due to Discriminatory Algorithm", "url": "https://incidentdatabase.ai/cite/101", "severity": null, "group": "organizational", "basis": "Dutch Tax Authority's fraud-risk algorithm, a government audit-targeting tool like ALICE, wrongly accused thousands of families of fraud and damaged the authority itself." }, "headline": "CGU, with ALICE support, avoids R$8.33m in overpriced purchases", "metric": "prevented at least R$8.33 million of overpriced purchases", "comparator": { "against": "the original estimated value of Pregão 15/2021, which reused the price survey of Pregão 05/2021", "before": "valor estimado de R$ 34 mi", "after": "reduziu o valor total do pregão em R$ 2.381.663,00; all items bought for R$ 14.315.793,42 on 21 July 2021", "basis": "measured", "quote": "Observou-se, no entanto, que foi utilizada a mesma pesquisa de preço do pregão de n. º 05/2021 e por recomendação da CGU, o certame foi suspenso e uma nova estimativa de preços foi realizada. A nova análise reduziu o valor total do pregão em R$ 2.381.663,00. Em 21 de julho de 2021, o pregão foi realizado e todos os itens foram adquiridos por valores unitários iguais ou inferiores aos estimados pela unidade, totalizando o montante de R$ 14.315.793,42.", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, "later": { "status": "scaled", "date": "2024-12-30", "note": "By the end of 2024 the CGU reported 126 bodies registered to receive ALICE alerts, including 94 state, district and municipal units, and R$257.25 million saved in concluded 2024 audits.", "quote": "Em 2024, 126 entes foram cadastrados para recebimento de alertas do robô ALICE, sendo 32 órgãos federais, 33 unidades da esfera estadual e distrital e 61 unidades da esfera municipal. Para os próximos anos, A Controladoria-Geral da União tem a perspectiva de ampliar o uso do robô ALICE para mais gestores federais, estaduais e municipais.", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, "value": { "amount": "R$ 8,33 milhões", "what": "overpriced hospital purchases avoided across five preventive audits", "who": "the federal government (hospitals and institutes in Rio de Janeiro)", "estimate": false, "quote": "A Controladoria-Geral da União (CGU) realizou, preventivamente, cinco auditorias em editais de contratações de hospitais federais e institutos sediados no Rio de Janeiro/RJ. A ação evitou que, pelo menos, R$ 8,33 milhões fossem desperdiçados em aquisições de insumos e serviços hospitalares com sobrepreço.", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 101 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/101", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attached the 2021 date only to the Ipanema Pregão 15/2021 in the title because the CGU release gives no date or tender number for the INCA glove auction; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the CGU documents overpriced purchases under way that its ALICE-supported audits stopped before award; and set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi; https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao; https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' report and two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0082", "catalog_version": "1.0.0", "source_fingerprint": "42ab95f8d05e6b0d3a12512a6105db2fa0170e9798a3b5b43802a768a9a3651c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0082-source-0001", "AIBD-0082-source-0002", "AIBD-0082-source-0003", "AIBD-0082-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0082-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Controladoria-Geral da União (CGU), in-house (launched 2015 per the release)", "deployer": "Controladoria-Geral da União (CGU)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The CGU states the audits were done “com apoio da ferramenta automatizada ALICE”. At INCA, it says, the overpricing risk was identified “com a ajuda do ALICE”. For the Ipanema tender, suspension followed a CGU recommendation after analysis of the price survey. ALICE's documented role is alerting and supporting the audit; auditors and managers decided. Developer and deployer are the same public body. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The CGU states the audits were done “com apoio da ferramenta automatizada ALICE”. At INCA, it says, the overpricing risk was identified “com a ajuda do ALICE”. For the Ipanema tender, suspension followed a CGU recommendation after analysis of the price survey. ALICE's documented role is alerting and supporting the audit; auditors and managers decided. Developer and deployer are the same public body. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary; patients benefit only indirectly through preserved hospital budgets." }, { "group": "organizational", "depth": 2, "reason": "Material to the hospitals and the federal budget: R$2,381,663.00 cut from one auction and about R$5.95 million from another. R$8.33 million avoided across the five audits per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale relative to federal purchasing of about R$119 billion a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' report and two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary; patients benefit only indirectly through preserved hospital budgets." }, { "group": "organizational", "depth": 2, "reason": "Material to the hospitals and the federal budget: R$2,381,663.00 cut from one auction and about R$5.95 million from another. R$8.33 million avoided across the five audits per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale relative to federal purchasing of about R$119 billion a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary; patients benefit only indirectly through preserved hospital budgets." }, { "group": "organizational", "depth": 2, "reason": "Material to the hospitals and the federal budget: R$2,381,663.00 cut from one auction and about R$5.95 million from another. R$8.33 million avoided across the five audits per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale relative to federal purchasing of about R$119 billion a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Dutch Tax Authority's fraud-risk algorithm, a government audit-targeting tool like ALICE, wrongly accused thousands of families of fraud and damaged the authority itself.", "links": [ { "database": "AI Incident Database", "identifier": "101", "title": "Dutch Families Wrongfully Accused of Tax Fraud Due to Discriminatory Algorithm", "url": "https://incidentdatabase.ai/cite/101", "group": "organizational", "basis": "Dutch Tax Authority's fraud-risk algorithm, a government audit-targeting tool like ALICE, wrongly accused thousands of families of fraud and damaged the authority itself.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 8,33 milhões", "what": "overpriced hospital purchases avoided across five preventive audits", "who": "the federal government (hospitals and institutes in Rio de Janeiro)", "estimate": false, "quote": "A Controladoria-Geral da União (CGU) realizou, preventivamente, cinco auditorias em editais de contratações de hospitais federais e institutos sediados no Rio de Janeiro/RJ. A ação evitou que, pelo menos, R$ 8,33 milhões fossem desperdiçados em aquisições de insumos e serviços hospitalares com sobrepreço.", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 8,33 milhões", "what": "overpriced hospital purchases avoided across five preventive audits", "who": "the federal government (hospitals and institutes in Rio de Janeiro)", "estimate": false, "quote": "A Controladoria-Geral da União (CGU) realizou, preventivamente, cinco auditorias em editais de contratações de hospitais federais e institutos sediados no Rio de Janeiro/RJ. A ação evitou que, pelo menos, R$ 8,33 milhões fossem desperdiçados em aquisições de insumos e serviços hospitalares com sobrepreço.", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 8,33 milhões", "what": "overpriced hospital purchases avoided across five preventive audits", "who": "the federal government (hospitals and institutes in Rio de Janeiro)", "estimate": false, "quote": "A Controladoria-Geral da União (CGU) realizou, preventivamente, cinco auditorias em editais de contratações de hospitais federais e institutos sediados no Rio de Janeiro/RJ. A ação evitou que, pelo menos, R$ 8,33 milhões fossem desperdiçados em aquisições de insumos e serviços hospitalares com sobrepreço.", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "prevented at least R$8.33 million of overpriced purchases", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "101", "title": "Dutch Families Wrongfully Accused of Tax Fraud Due to Discriminatory Algorithm", "url": "https://incidentdatabase.ai/cite/101", "group": "organizational", "basis": "Dutch Tax Authority's fraud-risk algorithm, a government audit-targeting tool like ALICE, wrongly accused thousands of families of fraud and damaged the authority itself." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2024-12-30", "note": "By the end of 2024 the CGU reported 126 bodies registered to receive ALICE alerts, including 94 state, district and municipal units, and R$257.25 million saved in concluded 2024 audits.", "quote": "Em 2024, 126 entes foram cadastrados para recebimento de alertas do robô ALICE, sendo 32 órgãos federais, 33 unidades da esfera estadual e distrital e 61 unidades da esfera municipal. Para os próximos anos, A Controladoria-Geral da União tem a perspectiva de ampliar o uso do robô ALICE para mais gestores federais, estaduais e municipais.", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0082" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A CGU statement of 4 October 2023 describes five preventive audits of tenders by federal hospitals and institutes in Rio de Janeiro. The automated tool ALICE supported them. The CGU says this prevented at least R$8.33 million of overpriced purchases. At the Instituto Nacional de Câncer (INCA), a glove auction estimated at R$11 million was re-estimated at R$5.1 million after ALICE indicated prices above market. That avoided about R$5.95 million. At the Hospital Federal de Ipanema, Pregão 15/2021 for gloves (estimated R$34 million) had reused the price survey of Pregão 05/2021. On CGU's recommendation it was suspended and re-estimated, cutting R$2,381,663.00. The auction held on 21 July 2021 bought every item at or below the new estimates, totaling R$14,315,793.42.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary; patients benefit only indirectly through preserved hospital budgets." }, { "group": "organizational", "depth": 2, "reason": "Material to the hospitals and the federal budget: R$2,381,663.00 cut from one auction and about R$5.95 million from another. R$8.33 million avoided across the five audits per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale relative to federal purchasing of about R$119 billion a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Preventive audit of federal procurement notices using automated risk alerts to stop overpriced purchases before award" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Rio de Janeiro, Brazil", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Preventive audit of federal procurement notices using automated risk alerts to stop overpriced purchases before award" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-07-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 101 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/101", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attached the 2021 date only to the Ipanema Pregão 15/2021 in the title because the CGU release gives no date or tender number for the INCA glove auction; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the CGU documents overpriced purchases under way that its ALICE-supported audits stopped before award; and set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi; https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao; https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALICE alerts on price surveys inconsistent with prices practiced in comparable purchases in the same region", "CGU preventive audits completed before the auction, with recommendations to re-estimate prices", "Hospital managers suspending and re-running the price estimate" ], "must_hold": [ "Tender notices published on the federal purchasing portal where ALICE reads them daily", "Time between publication and auction sufficient for audit and correction", "Availability of market price references" ], "echoes": [ { "date": "2025-01-14", "setting": "Three 2024 Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2024-12-30", "setting": "2024 aggregate: 206 preventive audits opened, R$257.25 million saved (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALICE alerts on price surveys inconsistent with prices practiced in comparable purchases in the same region", "CGU preventive audits completed before the auction, with recommendations to re-estimate prices", "Hospital managers suspending and re-running the price estimate" ], "must_hold": [ "Tender notices published on the federal purchasing portal where ALICE reads them daily", "Time between publication and auction sufficient for audit and correction", "Availability of market price references" ], "echoes": [ { "date": "2025-01-14", "setting": "Three 2024 Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2024-12-30", "setting": "2024 aggregate: 206 preventive audits opened, R$257.25 million saved (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 101 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/101", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attached the 2021 date only to the Ipanema Pregão 15/2021 in the title because the CGU release gives no date or tender number for the INCA glove auction; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the CGU documents overpriced purchases under way that its ALICE-supported audits stopped before award; and set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi; https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao; https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: government audit and procurement control", "segment": "Federal internal control of health-sector purchasing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2023). CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi. gov.br/cgu, 4 Oct 2023.", "title": "CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "por recomendação da CGU, o certame foi suspenso e uma nova estimativa de preços foi realizada. A nova análise reduziu o valor total do pregão em R$ 2.381.663,00." }, { "kind": "press release", "citation": "Controladoria-Geral da União (2023). Same release, 'ALICE' section with 2023 aggregates.", "title": "CGU atua em editais de licitação em hospitais federais (ALICE section)", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "a partir de 16.743 compras analisadas no âmbito nacional, o ALICE emitiu alertas que resultaram na suspensão de 59 compras no valor aproximado de R$ 3.1 bilhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal.", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE, da Controladoria-Geral da União. gov.br/cgu, 30 Dec 2024.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0082-source-0001", "AIBD-0082-source-0002", "AIBD-0082-source-0003", "AIBD-0082-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2023). CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi. gov.br/cgu, 4 Oct 2023.", "title": "CGU atua em editais de licitação em hospitais federais no Rio de Janeiro e evita desperdício de cerca de R$ 8,33 mi", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "por recomendação da CGU, o certame foi suspenso e uma nova estimativa de preços foi realizada. A nova análise reduziu o valor total do pregão em R$ 2.381.663,00." }, { "kind": "press release", "citation": "Controladoria-Geral da União (2023). Same release, 'ALICE' section with 2023 aggregates.", "title": "CGU atua em editais de licitação em hospitais federais (ALICE section)", "url": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi", "date": "2023-10-04", "written_by": "makers", "quote": "a partir de 16.743 compras analisadas no âmbito nacional, o ALICE emitiu alertas que resultaram na suspensão de 59 compras no valor aproximado de R$ 3.1 bilhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal.", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE, da Controladoria-Geral da União. gov.br/cgu, 30 Dec 2024.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "With ALICE support, CGU cut R$2.38m from a 2021 Ipanema hospital glove tender and R$5.95m from an INCA tender; R$8.33m avoided", "account": "A CGU statement of 4 October 2023 describes five preventive audits of tenders by federal hospitals and institutes in Rio de Janeiro. The automated tool ALICE supported them. The CGU says this prevented at least R$8.33 million of overpriced purchases. At the Instituto Nacional de Câncer (INCA), a glove auction estimated at R$11 million was re-estimated at R$5.1 million after ALICE indicated prices above market. That avoided about R$5.95 million. At the Hospital Federal de Ipanema, Pregão 15/2021 for gloves (estimated R$34 million) had reused the price survey of Pregão 05/2021. On CGU's recommendation it was suspended and re-estimated, cutting R$2,381,663.00. The auction held on 21 July 2021 bought every item at or below the new estimates, totaling R$14,315,793.42." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU automated audit-trail and AI alert tool" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Controladoria-Geral da União (CGU), in-house (launched 2015 per the release)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CGU, supported by ALICE, cuts R$2.38 million from a 2021 Hospital Federal de Ipanema glove tender and R$5.95 million from an undated INCA glove tender", "headline": "CGU, with ALICE support, avoids R$8.33m in overpriced purchases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "42ab95f8d05e6b0d3a12512a6105db2fa0170e9798a3b5b43802a768a9a3651c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A CGU statement of 4 October 2023 describes five preventive audits of tenders by federal hospitals and institutes in Rio de Janeiro. The automated tool ALICE supported them. The CGU says this prevented at least R$8.33 million of overpriced purchases. At the Instituto Nacional de Câncer (INCA), a glove auction estimated at R$11 million was re-estimated at R$5.1 million after ALICE indicated prices above market. That avoided about R$5.95 million. At the Hospital Federal de Ipanema, Pregão 15/2021 for gloves (estimated R$34 million) had reused the price survey of Pregão 05/2021. On CGU's recommendation it was suspended and re-estimated, cutting R$2,381,663.00. The auction held on 21 July 2021 bought every item at or below the new estimates, totaling R$14,315,793.42.", "replication": { "produced_by": [ "ALICE alerts on price surveys inconsistent with prices practiced in comparable purchases in the same region", "CGU preventive audits completed before the auction, with recommendations to re-estimate prices", "Hospital managers suspending and re-running the price estimate" ], "must_hold": [ "Tender notices published on the federal purchasing portal where ALICE reads them daily", "Time between publication and auction sufficient for audit and correction", "Availability of market price references" ], "echoes": [ { "date": "2025-01-14", "setting": "Three 2024 Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2024-12-30", "setting": "2024 aggregate: 206 preventive audits opened, R$257.25 million saved (CGU, 30 December 2024)", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0333", "title": "STF's Victor AI project: OCR text layer in production since December 2020 (10 million+ pages by May 2021); document splitter and theme classifier still pending in August 2021", "summary": "STF–UnB Victor: OCR layer live since Dec 2020 (10m+ pages by May 2021); splitter and repercussão geral classifier not yet in production (STF, 19 August 2021); time savings were projections.", "date_observed": "2021-08-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Victor is a Supremo Tribunal Federal (STF) and Universidade de Brasília (UnB) partnership. It began at the end of 2017 under Chief Justice Cármen Lúcia. It was designed to read extraordinary appeals and identify the most frequent repercussão geral themes. Its four tasks: converting images to text, splitting documents, classifying the main procedural documents and identifying repercussão geral themes. On 30 August 2018 Cármen Lúcia announced it was in operation, with tests on 27 themes and a claimed triage precision of 84%. She said work taking a clerk three hours would take five seconds. On 23 October 2018 Chief Justice Dias Toffoli spoke at a CNJ-reported seminar. He said it did in five seconds what cost a clerk 40 minutes to an hour, with 85% accuracy. The STF's own status report of 19 August 2021 states that only the optical character recognition (OCR) layer was effectively implemented. It ran from the end of December 2020 for extraordinary appeals and agravos, with over 10 million pages processed by May 2021. The splitter and classifier were still being put into production with no set date. The theme indication is always validated by the ministers. No measured time saving or case outcome was published; the successor tool VitorIA (2023) is recorded separately.", "category": "general benefit", "unexpected": false, "purpose": "Speed up admissibility analysis of extraordinary appeals by flagging the repercussão geral theme that applies. The production OCR layer is a precondition for that, not the classification itself.", "system": "Victor (STF–UnB artificial-intelligence project: OCR, document splitter, document classifier, repercussão geral theme classifier)", "model_version": null, "developer": "Supremo Tribunal Federal (STF) with the Universidade de Brasília (UnB)", "deployer": "Supremo Tribunal Federal (STF), Secretaria de Gestão de Precedentes", "location": "Brasília, Brazil", "domain": "Justice administration: appellate case triage", "segment": "Supreme court case management", "benefit_type": "Repetitive Task Automation", "taxonomy_note": "Only the OCR layer is in production, and the time savings claimed for triage are projections.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No litigant outcome is documented." }, { "group": "organizational", "depth": null, "reason": "OCR of 10 million pages is a throughput figure, not a measured saving, and the classifier was not in production." }, { "group": "societal", "depth": null, "reason": "No effect on case backlog or litigants is documented." } ], "ai_role": { "status": "assessed", "statement": "By the STF's own account of 19 August 2021, the AI classifier that would flag repercussão geral themes was not in production. The only live component was automatic OCR of incoming appeals, which the STF frames as part of the Victor project. Any theme indication is validated by the ministers. The time savings announced in 2018 (three hours or 40 minutes to five seconds) were forecasts made by chief justices at launch. All cited sources are the deployer's news service (STF) and the CNJ, which the same chief justice presided. No independent evaluation was found." }, "evidence": [ { "kind": "press release", "citation": "Supremo Tribunal Federal (2021). Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral. STF Notícias, 19 Aug 2021.", "title": "Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral", "url": "https://noticias.stf.jus.br/postsnoticias/projeto-victor-avanca-em-pesquisa-e-desenvolvimento-para-identificacao-dos-temas-de-repercussao-geral/", "date": "2021-08-19", "written_by": "makers", "quote": "No momento, o STF trabalha para implementar em produção o spliter e o classificador de peças, ainda sem data definida." }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2021). Same item, section 'Camada de texto dos documentos'.", "title": "Projeto Victor avança (OCR layer)", "url": "https://noticias.stf.jus.br/postsnoticias/projeto-victor-avanca-em-pesquisa-e-desenvolvimento-para-identificacao-dos-temas-de-repercussao-geral/", "date": "2021-08-19", "written_by": "makers", "quote": "Até maio de 2021, este procedimento ocorreu em mais de 10 milhões de páginas." }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2018). Ministra Cármen Lúcia anuncia início de funcionamento do Projeto Victor, de inteligência artificial. STF Notícias, 30 Aug 2018.", "title": "Ministra Cármen Lúcia anuncia início de funcionamento do Projeto Victor, de inteligência artificial", "url": "https://noticias.stf.jus.br/postsnoticias/ministra-carmen-lucia-anuncia-inicio-de-funcionamento-do-projeto-victor-de-inteligencia-artificial/", "date": "2018-08-30", "written_by": "makers", "quote": "Ela informou que atualmente o nível de precisão na triagem é de 84%, mas que atingirá 95% no próximo mês." }, { "kind": "report", "citation": "Montenegro, M. C. (2018). Inteligência artificial: Trabalho judicial de 40 minutos pode ser feito em 5 segundos. Agência CNJ de Notícias, 23 Oct 2018.", "title": "Inteligência artificial: Trabalho judicial de 40 minutos pode ser feito em 5 segundos", "url": "https://www.cnj.jus.br/inteligencia-artificial-trabalho-judicial-de-40-minutos-pode-ser-feito-em-5-segundos/", "date": "2018-10-23", "written_by": "independent", "quote": "O trabalho que custaria ao servidor de um tribunal entre 40 minutos e uma hora para fazer, o software faz em cinco segundos." }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2023). STF finaliza testes de nova ferramenta de Inteligência Artificial. 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STF Notícias, 30 Aug 2018.", "title": "Ministra Cármen Lúcia anuncia início de funcionamento do Projeto Victor, de inteligência artificial", "url": "https://noticias.stf.jus.br/postsnoticias/ministra-carmen-lucia-anuncia-inicio-de-funcionamento-do-projeto-victor-de-inteligencia-artificial/", "date": "2018-08-30", "written_by": "makers", "quote": "Ela informou que atualmente o nível de precisão na triagem é de 84%, mas que atingirá 95% no próximo mês." }, { "kind": "report", "citation": "Montenegro, M. C. (2018). Inteligência artificial: Trabalho judicial de 40 minutos pode ser feito em 5 segundos. 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It began at the end of 2017 under Chief Justice Cármen Lúcia. It was designed to read extraordinary appeals and identify the most frequent repercussão geral themes. Its four tasks: converting images to text, splitting documents, classifying the main procedural documents and identifying repercussão geral themes. On 30 August 2018 Cármen Lúcia announced it was in operation, with tests on 27 themes and a claimed triage precision of 84%. She said work taking a clerk three hours would take five seconds. On 23 October 2018 Chief Justice Dias Toffoli spoke at a CNJ-reported seminar. He said it did in five seconds what cost a clerk 40 minutes to an hour, with 85% accuracy. The STF's own status report of 19 August 2021 states that only the optical character recognition (OCR) layer was effectively implemented. It ran from the end of December 2020 for extraordinary appeals and agravos, with over 10 million pages processed by May 2021. The splitter and classifier were still being put into production with no set date. The theme indication is always validated by the ministers. No measured time saving or case outcome was published; the successor tool VitorIA (2023) is recorded separately." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Victor (STF–UnB artificial-intelligence project: OCR, document splitter, document classifier, repercussão geral theme classifier)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Supremo Tribunal Federal (STF) with the Universidade de Brasília (UnB)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "STF's Victor AI project: OCR text layer in production since December 2020 (10 million+ pages by May 2021); document splitter and theme classifier still pending in August 2021", "headline": "STF's Victor OCR processes 10 million+ pages; classifier pending" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4d5f8f71116fb7bb19b2d4484b2b91fcb96dc1b3e49c846c55f7fae0dffbeab5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Victor is a Supremo Tribunal Federal (STF) and Universidade de Brasília (UnB) partnership. It began at the end of 2017 under Chief Justice Cármen Lúcia. It was designed to read extraordinary appeals and identify the most frequent repercussão geral themes. Its four tasks: converting images to text, splitting documents, classifying the main procedural documents and identifying repercussão geral themes. On 30 August 2018 Cármen Lúcia announced it was in operation, with tests on 27 themes and a claimed triage precision of 84%. She said work taking a clerk three hours would take five seconds. On 23 October 2018 Chief Justice Dias Toffoli spoke at a CNJ-reported seminar. He said it did in five seconds what cost a clerk 40 minutes to an hour, with 85% accuracy. The STF's own status report of 19 August 2021 states that only the optical character recognition (OCR) layer was effectively implemented. It ran from the end of December 2020 for extraordinary appeals and agravos, with over 10 million pages processed by May 2021. The splitter and classifier were still being put into production with no set date. The theme indication is always validated by the ministers. No measured time saving or case outcome was published; the successor tool VitorIA (2023) is recorded separately.", "replication": { "produced_by": [ "STF–UnB research partnership with about 40 graduate scholarship holders", "Building a training set of extraordinary appeals, which took months", "Automatic OCR of all incoming appeal PDFs on the day of receipt (from December 2020)", "Validation of any theme indication by the ministers" ], "must_hold": [ "Filings arriving as PDFs that can be converted to text", "Splitter and classifier reaching production (not achieved by August 2021)", "Classifier accuracy acceptable to the Secretaria de Gestão de Precedentes", "Continued STF–UnB funding and staff" ], "echoes": [ { "date": "2023-05-17", "setting": "STF launched the successor tool VitorIA for grouping and classifying cases (recorded separately as AIBD-0085)", "outcome": "unknown", "source": "https://noticias.stf.jus.br/postsnoticias/stf-finaliza-testes-de-nova-ferramenta-de-inteligencia-artificial/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0268", "title": "Mayo Clinic AI-ECG flags low ejection fraction at 97.88%; 41-year-old treated, EF recovers to 55%", "summary": "At Mayo Clinic two ECGs scored 97.88% and 98.67% for reduced ejection fraction in a 41-year-old with no cardiac history; echo confirmed HFrEF, therapy followed, EF 55% at 4 months. Developer-authored.", "date_observed": "2021-08-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases.", "category": "benefit created", "unexpected": false, "purpose": "Screen 12-lead ECGs for a low left-ventricular ejection fraction with a convolutional neural network", "system": "Mayo Clinic AI-ECG low-ejection-fraction algorithm (AI-ECG dashboard)", "model_version": null, "developer": "Mayo Clinic (licensed to Eko and Anumana)", "deployer": "Mayo Clinic, Rochester", "location": "Rochester, Minnesota, USA", "domain": "Health; cardiology", "segment": "Adults presenting with unexplained symptoms and an ECG", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "New HFrEF identified and treated; ejection fraction 55% at four months." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported for this case." }, { "group": "societal", "depth": null, "reason": "Single case." } ], "ai_role": { "status": "assessed", "statement": "The AI-ECG probabilities (97.88% and 98.67%) prompted the echocardiogram and treatment, according to the authors. The source is the developer's own case report. The authors disclose that Mayo licensed the technology and that inventors may receive financial benefit. No independent account of the case exists." }, "evidence": [ { "kind": "case report", "citation": "Harmon DM, Witt DR, Friedman PA, Attia ZI. Cardiovasc Digit Health J 2(5):282-284 (2021)", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)" }, { "kind": "case report", "citation": "Harmon DM, et al. (2021), disclosures", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "Drs Friedman and Attia and other Mayo inventors may also receive financial benefit from this agreement through Mayo Clinic policies." }, { "kind": "case report", "citation": "Dhawan R, Omer M, Carpenter C, Friedman PA, Liu X. Pacing Clin Electrophysiol (2024)", "title": "Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram", "url": "https://doi.org/10.1111/pace.14980", "date": "2024-04-07", "written_by": "makers", "quote": "Artificial intelligence-enabled ECGs performed 6 years prior to clinical presentation consistently predicted a high probability (up to 91%) of low EF." }, { "kind": "case report", "citation": "Kenyon CR, Pietri MP, Rosenthal JL, Arsanjani R, Ayoub C. J Pers Med 14(6):559 (2024)", "title": "Artificial Intelligence Assists in the Early Identification of Cardiac Amyloidosis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/", "date": "2024-05-24", "written_by": "makers", "quote": "This facilitated an early diagnosis by the biopsy of AL cardiac amyloidosis and the prompt initiation of targeted therapy." }, { "kind": "case report", "citation": "Liu X, Friedman P, Cha YM, Deshmukh A, Mulpuru S, Asirvatham S. HeartRhythm Case Rep (2025)", "title": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/", "date": "2025-07-26", "written_by": "makers", "quote": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy" }, { "kind": "news report", "citation": "MedCity News (3 Apr 2024). Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds.", "title": "Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds", "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/", "date": "2024-04-03", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Routine 12-lead ECGs scored by the low-EF network", "A dashboard that clinicians consult during evaluation", "Confirmatory echocardiography and guideline-directed therapy" ], "must_hold": [ "The algorithm is deployed in the clinical workflow", "Clinicians act on a high probability score" ], "echoes": [ { "date": "2024-04-07", "setting": "Mayo Clinic Rochester: 70-year-old with LBBB-induced cardiomyopathy", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1111/pace.14980" }, { "date": "2024-05-24", "setting": "Mayo Clinic Phoenix: 69-year-old woman, AI-ECG amyloidosis probability prompted biopsy", "model_version": "AI-ECG amyloidosis model", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/" }, { "date": "2025-07-26", "setting": "Mayo Clinic Health System, La Crosse: AI-ECG used in defibrillator decision", "model_version": null, "outcome": "unknown", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/" } ] }, "paired_incident": null, "headline": "Mayo AI-ECG flags low EF; 41-year-old recovers to 55%", "metric": "at four months his ejection fraction had improved to 55%", "comparator": { "against": "the conventional reading of the same ECGs, which showed only nonspecific abnormalities", "before": "The ECG showed sinus tachycardia, premature ventricular complexes with rightward deviation, and a nonspecific T-wave abnormality (echocardiography then showed a left ventricular ejection fraction of 41%)", "after": "high probabilities of reduced ejection fraction (97.88% and 98.67%); at a 4-month follow-up visit, the patient had improved left ventricular ejection fraction to 55%", "basis": "measured", "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/" }, "later": { "status": "scaled", "date": "2024-04-03", "note": "The Mayo-developed low-ejection-fraction algorithm, licensed to Eko Health and trained on Mayo's ECG dataset, received FDA clearance in early April 2024 for use with Eko's digital stethoscopes, and Mayo authors continued to publish AI-ECG case reports through 2025.", "quote": "Eko Health received FDA clearance this week for a new AI-powered tool that aids in the early detection of low ejection fraction", "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/; https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Mayo_Clinic; https://en.wikipedia.org/wiki/Mayo_Clinic", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and four case reports from the makers. 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Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. 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Cardiovasc Digit Health J 2(5):282-284 (2021)", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)" }, { "kind": "case report", "citation": "Harmon DM, et al. (2021), disclosures", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "Drs Friedman and Attia and other Mayo inventors may also receive financial benefit from this agreement through Mayo Clinic policies." }, { "kind": "case report", "citation": "Dhawan R, Omer M, Carpenter C, Friedman PA, Liu X. Pacing Clin Electrophysiol (2024)", "title": "Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram", "url": "https://doi.org/10.1111/pace.14980", "date": "2024-04-07", "written_by": "makers", "quote": "Artificial intelligence-enabled ECGs performed 6 years prior to clinical presentation consistently predicted a high probability (up to 91%) of low EF." }, { "kind": "case report", "citation": "Kenyon CR, Pietri MP, Rosenthal JL, Arsanjani R, Ayoub C. J Pers Med 14(6):559 (2024)", "title": "Artificial Intelligence Assists in the Early Identification of Cardiac Amyloidosis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/", "date": "2024-05-24", "written_by": "makers", "quote": "This facilitated an early diagnosis by the biopsy of AL cardiac amyloidosis and the prompt initiation of targeted therapy." }, { "kind": "case report", "citation": "Liu X, Friedman P, Cha YM, Deshmukh A, Mulpuru S, Asirvatham S. HeartRhythm Case Rep (2025)", "title": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/", "date": "2025-07-26", "written_by": "makers", "quote": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy" }, { "kind": "news report", "citation": "MedCity News (3 Apr 2024). Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds.", "title": "Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds", "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/", "date": "2024-04-03", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0268-source-0001", "AIBD-0268-source-0002", "AIBD-0268-source-0003", "AIBD-0268-source-0004", "AIBD-0268-source-0005", "AIBD-0268-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Harmon DM, Witt DR, Friedman PA, Attia ZI. Cardiovasc Digit Health J 2(5):282-284 (2021)", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "The 2 ECGs evaluated by the AI-ECG algorithm revealed high probabilities of reduced ejection fraction (97.88% and 98.67%)" }, { "kind": "case report", "citation": "Harmon DM, et al. (2021), disclosures", "title": "Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence-enhanced electrocardiogram", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8890344/", "date": "2021-08-24", "written_by": "makers", "quote": "Drs Friedman and Attia and other Mayo inventors may also receive financial benefit from this agreement through Mayo Clinic policies." }, { "kind": "case report", "citation": "Dhawan R, Omer M, Carpenter C, Friedman PA, Liu X. Pacing Clin Electrophysiol (2024)", "title": "Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram", "url": "https://doi.org/10.1111/pace.14980", "date": "2024-04-07", "written_by": "makers", "quote": "Artificial intelligence-enabled ECGs performed 6 years prior to clinical presentation consistently predicted a high probability (up to 91%) of low EF." }, { "kind": "case report", "citation": "Kenyon CR, Pietri MP, Rosenthal JL, Arsanjani R, Ayoub C. J Pers Med 14(6):559 (2024)", "title": "Artificial Intelligence Assists in the Early Identification of Cardiac Amyloidosis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/", "date": "2024-05-24", "written_by": "makers", "quote": "This facilitated an early diagnosis by the biopsy of AL cardiac amyloidosis and the prompt initiation of targeted therapy." }, { "kind": "case report", "citation": "Liu X, Friedman P, Cha YM, Deshmukh A, Mulpuru S, Asirvatham S. HeartRhythm Case Rep (2025)", "title": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/", "date": "2025-07-26", "written_by": "makers", "quote": "Prospective use of artificial intelligence-enabled electrocardiogram to assist in clinical decision making regarding defibrillator therapy" }, { "kind": "news report", "citation": "MedCity News (3 Apr 2024). Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds.", "title": "Eko Health Gains FDA Clearance For Cardiology Algorithm That Can Detect Heart Failure in 15 Seconds", "url": "https://medcitynews.com/2024/04/eko-health-gains-fda-clearance-for-cardiology-algorithm-that-can-detect-heart-failure-in-15-seconds/", "date": "2024-04-03", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At Mayo Clinic two ECGs scored 97.88% and 98.67% for reduced ejection fraction in a 41-year-old with no cardiac history; echo confirmed HFrEF, therapy followed, EF 55% at 4 months. Developer-authored.", "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Mayo Clinic AI-ECG low-ejection-fraction algorithm (AI-ECG dashboard)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Mayo Clinic (licensed to Eko and Anumana)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Mayo Clinic AI-ECG flags low ejection fraction at 97.88%; 41-year-old treated, EF recovers to 55%", "headline": "Mayo AI-ECG flags low EF; 41-year-old recovers to 55%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2c17991dfd346309a798adef81faea306475571f2478c5048ad1a84d8169ae7d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Harmon, Witt, Friedman and Attia (Cardiovascular Digital Health Journal, 24 August 2021) report a 41-year-old man with class III obesity, sleep apnea, no cardiac history. Two electrocardiograms (ECGs) on Mayo's AI-ECG dashboard gave reduced-ejection-fraction probabilities of 97.88% and 98.67%. Echocardiography next day confirmed reduced function. Guideline-directed therapy for new heart failure with reduced ejection fraction (HFrEF) began. At four months his ejection fraction had risen to 55%, attributed by the authors to therapy, recovery from post-viral sequelae and weight loss. All four authors are at Mayo Clinic, which developed the algorithm and licensed it to Eko and Anumana. Friedman, Attia and other inventors may receive financial benefit. The same group published further cases. Dhawan et al. (PACE, 2024): AI-ECGs predicting left-bundle-branch-block cardiomyopathy six years before presentation. Kenyon et al. (J Pers Med, 2024): AI-ECG prompting an early AL amyloidosis diagnosis. Liu et al. (HeartRhythm Case Reports, 2025): defibrillator decision-making. No source outside Mayo was found for these cases.", "replication": { "produced_by": [ "Routine 12-lead ECGs scored by the low-EF network", "A dashboard that clinicians consult during evaluation", "Confirmatory echocardiography and guideline-directed therapy" ], "must_hold": [ "The algorithm is deployed in the clinical workflow", "Clinicians act on a high probability score" ], "echoes": [ { "date": "2024-04-07", "setting": "Mayo Clinic Rochester: 70-year-old with LBBB-induced cardiomyopathy", "outcome": "recurred", "source": "https://doi.org/10.1111/pace.14980" }, { "date": "2024-05-24", "setting": "Mayo Clinic Phoenix: 69-year-old woman, AI-ECG amyloidosis probability prompted biopsy", "model_version": "AI-ECG amyloidosis model", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11205191/" }, { "date": "2025-07-26", "setting": "Mayo Clinic Health System, La Crosse: AI-ECG used in defibrillator decision", "outcome": "unknown", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12666949/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0042", "title": "Baricitinib, identified with BenevolentAI, reduced COVID-19 deaths in trials", "summary": "Researchers used the Benevolent Platform to identify baricitinib as a candidate treatment for COVID-19.", "date_observed": "2021-09-01", "date_basis": "source publication", "date_precision": "day", "benefit_status": "mixed", "source_collection": null, "source_entry": null, "account": "BenevolentAI researchers reported in February 2020 that their knowledge graph had helped them identify baricitinib, an arthritis drug, as a possible treatment for COVID-19. They proposed clinical testing after reviewing its effects on inflammation and proteins involved in viral entry. In ACTT-2, 1,033 hospitalized adults received remdesivir with either baricitinib or a placebo. Median recovery took 7 days with baricitinib and 8 days with the placebo.\n\nCOV-BARRIER enrolled 1,525 adults. By day 28, 8% of patients receiving baricitinib had died, compared with 13% receiving a placebo. Both groups received standard care. Mortality was a secondary outcome. The trial did not meet its primary outcome of reduced disease progression, so its mortality result was not conclusive under the planned procedure for multiple comparisons.\n\nThe subsequent RECOVERY trial enrolled 8,156 patients. Mortality, its primary outcome, was 12% with baricitinib and 14% with usual care alone.", "category": "benefit created", "unexpected": false, "purpose": "Researchers searched for existing drugs that might treat COVID-19, using a biomedical knowledge graph that combines databases with information extracted from scientific papers.", "system": "Benevolent Platform", "model_version": null, "developer": "BenevolentAI", "deployer": "BenevolentAI research team", "location": "Multicountry trials (ACTT-2, COV-BARRIER, and RECOVERY): Argentina; Brazil; Denmark; Germany; India; Italy; Japan; Mexico; Russia; Singapore; South Korea; Spain; United Kingdom; United States", "domain": "Biomedicine / infectious disease therapeutics", "segment": "Hospitalized COVID-19 patients requiring supplemental oxygen or ventilatory support", "benefit_type": "Improved Physical Health", "taxonomy_note": "The clinical benefit is reduced mortality and faster recovery. AI assisted the researchers who proposed the drug for testing.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "Fewer patients died with baricitinib in COV-BARRIER and RECOVERY. RECOVERY confirmed lower 28-day mortality as its primary outcome in 8,156 patients." }, { "group": "organizational", "depth": 2, "reason": "ACTT-2 reported median recovery of 7 days with baricitinib and 8 days without it. That could free hospital capacity. A separate economic model estimated lower hospital costs, but neither establishes realized staffing or cash savings." }, { "group": "societal", "depth": 4, "reason": "WHO recommended baricitinib with corticosteroids for severe or critical COVID-19. That recommendation supports wider access to a treatment that reduced deaths in trials. Worldwide uptake and population-wide effects were not measured." } ], "ai_role": { "status": "assessed", "statement": "BenevolentAI researchers used the Benevolent Platform to search biomedical relationships and examine networks of proteins. They selected baricitinib after reviewing its targets, dosage, and pharmacology. The clinical investigators then tested the drug. None of these trials compared discovery with AI against discovery without it. The original correspondence and methods paper document AI-assisted selection. FDA authorization and WHO guidance concern the treatment." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Marconi VC, Ramanan AV, de Bono S, et al. (2021). Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19 (COV-BARRIER). Lancet Respir Med. Results and Figure 2; supplementary appendix 6, pp. 9–14, including the prespecified testing hierarchy.", "title": "Efficacy and safety of baricitinib for the treatment of hospitalised adults with COVID-19 (COV-BARRIER): a randomised, double-blind, parallel-group, placebo-controlled phase 3 trial", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "date": "2021-09-01", "written_by": "evaluator", "quote": "The 28-day all-cause mortality was 8% (n=62) for baricitinib and 13% (n=100) for placebo (hazard ratio [HR] 0·57 [95% CI 0·41–0·78]; nominal p=0·0018)" }, { "kind": "peer-reviewed study", "citation": "RECOVERY Collaborative Group. “Baricitinib in Patients Admitted to Hospital with COVID-19 (RECOVERY): A Randomised, Controlled, Open-Label, Platform Trial and Updated Meta-Analysis.” The Lancet 400 (2022): 359–368. Table 2, Figure 3, and Data sharing. https://doi.org/10.1016/S0140-6736(22)01109-6.", "title": "Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "date": "2022-07-28", "written_by": "independent", "quote": null }, { "kind": "other", "citation": "Richardson P, Griffin I, Tucker C, Smith D, Oechsle O, Phelan A, Rawling M, Savory E, Stebbing J (2020). Baricitinib as potential treatment for 2019-nCoV acute respiratory disease. Lancet.", "title": "Baricitinib as potential treatment for 2019-nCoV acute respiratory disease", "url": "https://europepmc.org/article/PMC/PMC7137985", "date": "2020-02-04", "written_by": "makers", "quote": "BenevolentAI's knowledge graph is a large repository of structured medical information, including numerous connections extracted from scientific literature by machine learning." }, { "kind": "peer-reviewed study", "citation": "Daniel P. Smith et al. “Expert-Augmented Computational Drug Repurposing Identified Baricitinib as a Treatment for COVID-19.” Frontiers in Pharmacology 12 (July 28, 2021): 709856. https://doi.org/10.3389/fphar.2021.709856.", "title": "Expert-Augmented Computational Drug Repurposing Identified Baricitinib as a Treatment for COVID-19", "url": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full", "date": "2021-07-28", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Kalil AC, Patterson TF, Mehta AK, et al. (2021). Baricitinib plus Remdesivir for Hospitalized Adults with Covid-19. N Engl J Med. Table 2 and trial oversight; supplementary appendix, pp. 19–23; protocol NCT04401579.", "title": "Baricitinib plus Remdesivir for Hospitalized Adults with Covid-19", "url": "https://europepmc.org/article/PMC/PMC7745180", "date": "2020-12-11", "written_by": "independent", "quote": "median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9)" }, { "kind": "press release", "citation": "U.S. Food and Drug Administration. “Coronavirus (COVID-19) Update: FDA Authorizes Drug Combination for Treatment of COVID-19.” November 19, 2020. Authorization, evidentiary standard, and ACTT-2 results.", "title": "FDA Authorizes Drug Combination for Treatment of COVID-19", "url": "https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19", "date": "2020-11-19", "written_by": "independent", "quote": "the drug baricitinib, in combination with remdesivir, for the treatment of suspected or laboratory confirmed COVID-19" }, { "kind": "report", "citation": "World Health Organization (2022). WHO recommends two new drugs to treat COVID-19.", "title": "WHO recommends two new drugs to treat COVID-19", "url": "https://www.who.int/news/item/14-01-2022-who-recommends-two-new-drugs-to-treat-covid-19", "date": "2022-01-14", "written_by": "independent", "quote": "The first drug, baricitinib, is strongly recommended for patients with severe or critical COVID-19." }, { "kind": "report", "citation": "BenevolentAI. “BenevolentAI Unaudited Preliminary Results for the Year Ended 31 December 2022,” March 16, 2023, Operational highlights, baricitinib bullet.", "title": "BenevolentAI Unaudited Preliminary Results for the Year Ended 31 December 2022", "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "date": "2023-03-16", "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "BenevolentAI. “BenevolentAI’s platform-derived hypothesis for COVID-19 treatment validated in US NIAID randomised control trial.” September 14, 2020. “About BenevolentAI,” headquarters statement.", "title": "BenevolentAI’s platform-derived hypothesis for COVID-19 treatment validated in US NIAID randomised control trial", "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "date": "2020-09-14", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Robert Ohsfeldt et al. “Cost-Effectiveness of Baricitinib Compared With Standard of Care: A Modeling Study in Hospitalized Patients With COVID-19 in the United States.” Clinical Therapeutics 43, no. 11 (2021): 1877–1893.e4. Tables IV–V and supplemental table S6. https://doi.org/10.1016/j.clinthera.2021.09.016.", "title": "Cost-Effectiveness of Baricitinib Compared With Standard of Care: A Modeling Study in Hospitalized Patients With COVID-19 in the United States", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8487786/", "date": "2021-10-04", "written_by": "evaluator", "quote": null } ], "replication": { "produced_by": [ "BenevolentAI researchers combined a biomedical knowledge graph with expert review to select baricitinib.", "Clinical investigators separately tested the drug alongside the care available in 2020 and 2021." ], "must_hold": [ "The clinical comparisons concern hospitalized patients and the eligibility criteria of each trial.", "Background treatment differed: remdesivir in ACTT-2, and mostly corticosteroids in COV-BARRIER and RECOVERY.", "Reproducing the AI selection would also require the January 2020 graph, software configuration, and researchers’ decisions. The complete snapshot is not public." ], "echoes": [ { "date": "2021-09-01", "setting": "COV-BARRIER: 1,525 adults. Lower mortality was a secondary finding after an unsuccessful primary comparison.", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/" }, { "date": "2022-07-28", "setting": "RECOVERY: 8,156 patients in 159 U.K. hospitals. Lower 28-day mortality was the primary finding. These were further tests of the drug, not repetitions of the AI discovery process.", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/" } ] }, "paired_incident": null, "headline": "An arthritis drug helped patients with severe COVID-19", "metric": "28-day all-cause mortality, a secondary endpoint, was 8% versus 13%", "comparator": { "against": "ACTT-2: remdesivir plus placebo versus remdesivir plus baricitinib", "before": "8 days (95% CI, 7 to 9)", "after": "7 days (95% confidence interval [CI], 6 to 8)", "basis": "measured", "quote": "Patients receiving baricitinib had a median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9)", "url": "https://europepmc.org/article/PMC/PMC7745180" }, "later": { "status": "persisted", "date": "2022-07-28", "note": "RECOVERY independently found lower 28-day mortality with baricitinib. WHO had recommended its use with corticosteroids for severe or critical COVID-19 in January 2022. 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Lancet 2020 (https://europepmc.org/article/PMC/PMC7137985); Kalil AC, et al. N Engl J Med 2021 (https://europepmc.org/article/PMC/PMC7745180); Marconi VC, et al. 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Put COV-BARRIER first for the mortality claim, preserved the failed primary endpoint and added the multiplicity limitation. Removed the generic FDA drug-list page from active evidence because it adds no case-specific support beyond the retained authorization. Distinguished NIAID-led ACTT-2 from the Lilly-sponsored COV-BARRIER analysis.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. 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Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added the developers’ original methods paper, identified the SVO component and January 2020 workflow, and clarified the scientists’ role in selecting baricitinib. 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Trial countries do not imply a separately demonstrated benefit in every country.", "source": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Rewrote the account and resolved all mandatory fields. Added RECOVERY and the original economic model, corrected the AI operator, distinguished projected wider benefits from observed patient outcomes, replaced WHO guidance counted as replication, and removed an unrelated Watson incident. Missing model and attribution details remain explicit. 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Distinguished reported findings, calculations, and inferences throughout the assessment.", "source": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "editor": "AIBD, Codex-assisted review" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent peer-reviewed studies, one independent report, one independent press release, the makers' peer-reviewed study, the makers' report, the makers' press release, the makers' other and two peer-reviewed studies from the evaluators. 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U.S. government researchers, Lilly, and Oxford organized trials. The FDA authorized treatment, and WHO recommended it." } }, "actors[].ownership_control": { "state": "value_present", "value": { "kind": "structured", "data": { "reported_status": "Historical control is documented in the company’s 2019 accounts.", "entity": "BenevolentAI Limited", "company_number": "09781806", "jurisdiction": "United Kingdom", "as_of": "2019-12-31", "controlling_person": "Kenneth Mulvany, a director and shareholder", "source_basis": "The accounts identify Mulvany as the person who controlled the company.", "aibd_calculated_voting_share": { "person": "Kenneth Patrick Mulvany", "snapshot_date": "2019-10-15", "ordinary_shares_held": 881000, "ordinary_shares_issued": 1831829, "preferred_shares_issued": 208623, "formula": "881,000 ÷ (1,831,829 + 208,623) × 100", "percent": 43.18, "interpretation": "Share of general voting shares in the October register. This is not a measure of all economic equity or proof of majority ownership.", "capital_check": "The December 2019 allotment left the ordinary and preferred counts unchanged. Its new G2 growth shares did not carry ordinary voting rights before an exit, apart from class resolutions.", "confidence": "High for the calculation from the filed snapshot. The snapshot does not establish every beneficial holding on an unobserved January 2020 date." }, "investor_context": { "investor": "Temasek", "jurisdiction": "Singapore", "investment_year": 2019, "reported_amount": "$90 million", "amount_note": "The announcements use the dollar sign without spelling out a currency. The amount is preserved as reported and is not converted or assigned to this research.", "government_relationship": "Temasek’s 2019 report identifies Singapore’s Minister for Finance as its sole shareholder. It also states that Temasek does not direct its portfolio companies’ business decisions.", "control_boundary": "An investment from a state-owned institution does not establish state control of BenevolentAI or direction of the baricitinib research." }, "temporal_scope": "Ownership surrounding the January 2020 discovery, not the developer’s present corporate structure." } }, "provenance": { "kind": "source_review", "basis": "Read original corporate filings and transaction announcements. 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FDA authorization and WHO guidance concern the treatment." } } }, "provenance": { "kind": "source_review", "basis": "The authors document AI-assisted candidate selection; no controlled comparison isolates its incremental contribution.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used the system to find relationships among proteins, diseases, and medicines before selecting baricitinib." } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "BenevolentAI researchers used the Benevolent Platform to search biomedical relationships and examine networks of proteins. They selected baricitinib after reviewing its targets, dosage, and pharmacology. The clinical investigators then tested the drug. None of these trials compared discovery with AI against discovery without it. The original correspondence and methods paper document AI-assisted selection. FDA authorization and WHO guidance concern the treatment." } } }, "provenance": { "kind": "source_review", "basis": "Direct use of AI-assisted discovery preceded separate clinical testing of the proposed drug.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used AI to investigate a new use for an existing medicine." } }, "assessments[].alternatives": { "state": "value_present", "value": { "kind": "structured", "data": { "personal": "Depth 5 is supported by mortality outcomes. The AI contribution is less certain than the drug benefit.", "organizational": "If only measured organizational gains were admitted, this rating would remain unresolved. The retained depth describes the potential capacity benefit.", "societal": "Depth 4 describes intended wider harm prevention. A recommendation alone does not establish a realized population-wide change." } }, "provenance": { "kind": "source_review", "basis": "Preserved the consequential alternatives rather than averaging different kinds of benefit.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital and societal grades describe possible benefits. A rule requiring observed benefits would leave those two grades unassigned." } }, "assessments[].assessor_date": { "state": "value_present", "value": { "kind": "structured", "data": { "assessor": "Codex-assisted AIBD review", "reviewed_on": "2026-10-25", "human_approval": "Not represented as an independent human review." } }, "provenance": { "kind": "curatorial", "basis": "Recorded the actual review method without attributing unperformed verification to Peter.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD, assisted by Codex, on 25 October 2026." } }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Fewer patients died with baricitinib in COV-BARRIER and RECOVERY. RECOVERY confirmed lower 28-day mortality as its primary outcome in 8,156 patients." }, { "group": "organizational", "depth": 2, "reason": "ACTT-2 reported median recovery of 7 days with baricitinib and 8 days without it. That could free hospital capacity. A separate economic model estimated lower hospital costs, but neither establishes realized staffing or cash savings." }, { "group": "societal", "depth": 4, "reason": "WHO recommended baricitinib with corticosteroids for severe or critical COVID-19. That recommendation supports wider access to a treatment that reduced deaths in trials. Worldwide uptake and population-wide effects were not measured." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed each stakeholder-specific rationale. Depth describes the stated benefit; support and realization are separate.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "For patients: 5 for fewer deaths and 2 for faster recovery. The broader assessments remain 2 for organizations and 4 for society." } }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Drug effects are supported by randomized trials, including an independent trial. The developers document the AI-assisted selection, but its incremental clinical contribution remains unmeasured.", "interpretation": "The shared solid fill describes the clinical evidence. It does not establish that all organizational or societal effects were measured." } }, "provenance": { "kind": "source_review", "basis": "Recomputed the display from the corrected source types and preserved the distinction between treatment and discovery evidence.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The solid fill denotes independently studied treatment benefits. It does not mean that the projected hospital and societal benefits occurred." } }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Fewer patients died with baricitinib in COV-BARRIER and RECOVERY. RECOVERY confirmed lower 28-day mortality as its primary outcome in 8,156 patients." }, { "group": "organizational", "depth": 2, "reason": "ACTT-2 reported median recovery of 7 days with baricitinib and 8 days without it. That could free hospital capacity. A separate economic model estimated lower hospital costs, but neither establishes realized staffing or cash savings." }, { "group": "societal", "depth": 4, "reason": "WHO recommended baricitinib with corticosteroids for severe or critical COVID-19. That recommendation supports wider access to a treatment that reduced deaths in trials. Worldwide uptake and population-wide effects were not measured." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed each stakeholder-specific rationale. Depth describes the stated benefit; support and realization are separate.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Lower mortality preserves lives. Faster recovery is a measurable health improvement. Shorter hospital stays could free capacity, and wider access could extend the treatment’s benefits." } }, "assessments[].rubric_version": { "state": "value_present", "value": { "kind": "structured", "data": { "rubric": "AIBD five-level depth scale and three beneficiary groups", "source_file": "aibd/templates/method.html", "source_revision": "4e31895", "applied_on": "2026-10-25", "personal_5": "Life preserved", "organizational_2": "Improved operational capability", "societal_4": "Serious harm averted; wider benefit remains intended rather than measured" } }, "provenance": { "kind": "curatorial", "basis": "Recorded the local rubric used for this review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD’s five-level scale, applied on 25 October 2026." } }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "structured", "data": { "personal": "Realized clinical benefit in randomized trials", "organizational": "Potential capacity improvement and modeled costs", "societal": "Observed recommendation, intended wider health benefit" } }, "provenance": { "kind": "source_review", "basis": "Separated realization from the depth of the benefit.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Trials established a benefit for patients. Hospital savings were modeled, and wider health benefits remain intended." } }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Fewer patients died with baricitinib in COV-BARRIER and RECOVERY. RECOVERY confirmed lower 28-day mortality as its primary outcome in 8,156 patients." }, { "group": "organizational", "depth": 2, "reason": "ACTT-2 reported median recovery of 7 days with baricitinib and 8 days without it. That could free hospital capacity. A separate economic model estimated lower hospital costs, but neither establishes realized staffing or cash savings." }, { "group": "societal", "depth": 4, "reason": "WHO recommended baricitinib with corticosteroids for severe or critical COVID-19. That recommendation supports wider access to a treatment that reduced deaths in trials. Worldwide uptake and population-wide effects were not measured." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed each stakeholder-specific rationale. Depth describes the stated benefit; support and realization are separate.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospitalized patients, hospitals, and the wider population that could receive treatment." } }, "availability": { "state": "value_present", "value": { "kind": "structured", "data": { "historical_ai_access": "BenevolentAI scientists used an internal research platform. The reviewed methods paper does not provide public access to the complete 2020 system.", "public_materials": "Published workflow, source databases, clinical articles, and linked trial materials.", "procurement_price": "Not reported for the discovery system.", "current_access": "Current licensing, geographic availability, and access to the historical snapshot are unresolved.", "treatment": "Baricitinib is a separate prescription medicine; the cited FDA and WHO statements describe historical authorization and guidance, not current individualized treatment advice.", "reviewed_on": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Separated access to the AI workflow from access to the drug.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "BenevolentAI used its internal platform. Its methods are published, but the complete January 2020 system is unavailable. Baricitinib is a prescription medicine." } }, "brief": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used the Benevolent Platform to identify baricitinib for COVID-19 testing. Randomized trials later found faster recovery or fewer deaths among hospitalized patients. The trials tested the drug rather than the additional value of AI-assisted discovery." }, "provenance": { "kind": "source_review", "basis": "The summary draws on the original discovery and clinical publications.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used AI to identify baricitinib for COVID-19 trials. Clinical investigators later found that patients recovered sooner and fewer died." } }, "case_kind": { "state": "value_present", "value": { "kind": "structured", "data": { "unit": "AI-assisted drug repurposing with subsequent clinical evaluations", "counting": "One discovery episode. The trials and articles are linked evidence, not additional AIBD cases." } }, "provenance": { "kind": "source_review", "basis": "Assigned the unit to the documented discovery episode and its follow-up.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Repurposing a medicine for COVID-19." } }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "related_evaluations": [ "NCT04401579", "NCT04421027", "NCT04381936" ], "same_discovery": "The three trials concern the drug selected in the January 2020 BenevolentAI work.", "duplicate_search": "No other existing AIBD record mentions baricitinib." } }, "provenance": { "kind": "curatorial", "basis": "Reviewed the local collection for duplicates and linked the original trial registrations.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ACTT-2, COV-BARRIER, and RECOVERY tested baricitinib after the initial proposal." } }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "links": [ { "claim": "AIBD-0042-claim-discovery", "support": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "locator": "Original correspondence; Methods and Results of the methods paper" }, { "claim": "AIBD-0042-claim-recovery", "support": [ "AIBD-0042-source-0005" ], "locator": "Table 2" }, { "claim": "AIBD-0042-claim-mortality", "support": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002" ], "locator": "COV-BARRIER Figure 2 and statistical hierarchy; RECOVERY Table 2" }, { "claim": "AIBD-0042-claim-policy", "support": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007" ], "locator": "Dated agency statements" }, { "claim": "AIBD-0042-claim-economics", "support": [ "AIBD-0042-source-0010" ], "locator": "Tables IV–V and supplemental table S6" } ], "qualifications": [ { "claim": "AIBD-0042-claim-mortality", "source": "AIBD-0042-source-0001", "qualification": "The COV-BARRIER primary outcome was not statistically significant; mortality was secondary." }, { "claim": "AIBD-0042-claim-economics", "source": "AIBD-0042-source-0010", "qualification": "Hospital savings reverse to higher costs in the mortality-only scenario." } ] } }, "provenance": { "kind": "source_review", "basis": "Mapped the statements to original findings and their material qualifications.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "References 3–4 describe the discovery, 5 reports recovery, 1–2 report mortality, 6–7 record agency decisions, and 10 estimates costs." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "structured", "data": { "clinical_outcomes": "Randomized trials support a drug benefit; RECOVERY independently confirms lower mortality.", "ai_use": "Original correspondence and detailed developer methods establish the reported workflow.", "ai_increment": "No controlled estimate of the benefit added by using AI.", "institutional_actions": "Direct agency statements establish the decisions and dates.", "wider_impact": "Hospital capacity and population-wide benefits were not measured. Economic effects are modeled." } }, "provenance": { "kind": "source_review", "basis": "Assessed each causal link separately.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Randomized trials establish the treatment benefit. The developers describe the AI workflow. No trial compares discovery with and without AI." } }, "claims[].missingness": { "state": "value_present", "value": { "kind": "structured", "data": { "model_release": "Not reported", "frozen_discovery_snapshot": "Not reported", "incremental_ai_benefit": "No controlled numerical uplift is reported. AIBD supplies a qualitative inference and documented workflow proxies.", "realized_hospital_savings": "Not reported", "worldwide_beneficiary_count": "Not reported", "control_of_developer_in_2020": "Historical control is established by the 2019 accounts. The separate voting-share calculation uses the October 2019 snapshot.", "cross_border_transfers": "Company funding is documented. Scientific-resource reuse is documented, with geographic links labeled as inferences. No patient-data route or case-level funding allocation is reported.", "inaccessible_upstream_materials": "See source access notes for the Sorrell supplement and the original WHO guideline PDF.", "return_payback": "No source-reported ROI or payment timetable. AIBD supplies labeled value scenarios and a reference ratio.", "strategic_effect": "AIBD provides a qualitative preparedness assessment. No quantitative national advantage is reported or invented." } }, "provenance": { "kind": "source_review", "basis": "Recorded consequential gaps without substituting zero or assuming that missing evidence disproves benefit.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The publications omit the exact software release, a comparison without AI, observed savings, and the number of people helped worldwide." } }, "claims[].proposition": { "state": "value_present", "value": { "kind": "structured", "data": { "claims": [ { "id": "AIBD-0042-claim-discovery", "statement": "BenevolentAI researchers used their graph to identify baricitinib for COVID-19 testing.", "type": "Original researchers’ account", "sources": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "locator": "Original correspondence; Methods and Results of the methods paper" }, { "id": "AIBD-0042-claim-recovery", "statement": "ACTT-2 found faster recovery with baricitinib added to remdesivir.", "type": "Randomized clinical finding", "sources": [ "AIBD-0042-source-0005" ], "locator": "Table 2" }, { "id": "AIBD-0042-claim-mortality", "statement": "COV-BARRIER and RECOVERY found lower mortality with baricitinib.", "type": "Randomized clinical findings with different primary outcomes", "sources": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002" ], "locator": "COV-BARRIER Figure 2 and statistical hierarchy; RECOVERY Table 2" }, { "id": "AIBD-0042-claim-policy", "statement": "FDA authorized use in November 2020 and WHO recommended use in January 2022.", "type": "Documented institutional decisions", "sources": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007" ], "locator": "Dated agency statements" }, { "id": "AIBD-0042-claim-economics", "statement": "A published model estimated treatment costs and health gains.", "type": "Sponsor-funded model, not observed AI savings", "sources": [ "AIBD-0042-source-0010" ], "locator": "Tables IV–V and supplemental table S6" } ] } }, "provenance": { "kind": "source_review", "basis": "Separated discovery, clinical, institutional, and modeled economic statements.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used AI to select baricitinib for testing. Clinical investigators subsequently found that patients recovered faster and fewer died." } }, "cross_border_flows[]": { "state": "value_present", "value": { "kind": "structured", "data": { "reported_status": "The funding relationship and reuse of named scientific resources are documented. Geographic knowledge flows are inferred from the resource producers and the U.K. discovery team.", "flows": [ { "type": "Investment", "origin": "Singapore", "destination": "United Kingdom", "from_actor": "Temasek", "to_actor": "BenevolentAI", "year": 2019, "reported_amount": "$90 million", "evidence_status": "Reported by the recipient and its transaction counsel", "scope": "Company-wide development of the platform and drug programs. The sources do not identify a baricitinib budget or the bank settlement route.", "source_refs": [ "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek" ] }, { "type": "Reuse of scientific information", "origin": "Japan", "destination": "United Kingdom", "resource": "KEGG", "evidence_status": "Documented use; geographic relationship inferred", "basis": "The methods paper names KEGG. Its developers trace the resource to the Japanese Human Genome Project.", "source_refs": [ "AIBD-0042-source-0004", "https://www.genome.jp/kegg/kegg1.html" ] }, { "type": "Reuse of scientific information", "origin": "Italy", "destination": "United Kingdom", "resource": "SIGNOR", "evidence_status": "Documented use; geographic relationship inferred", "basis": "The methods paper names SIGNOR. Its resource paper identifies an Italy-led collaboration that also includes U.K. researchers.", "source_refs": [ "AIBD-0042-source-0004", "https://doi.org/10.1093/nar/gkz949" ] }, { "type": "Published research followed by clinical testing", "origin": "United Kingdom", "destination": "U.S.-led ACTT-2 and the countries in the multinational COV-BARRIER trial", "evidence_status": "Documented sequence in the discovery and trial publications", "scope": "The treatment hypothesis crossed research settings. This does not mean that the original AI system was deployed at the trial sites.", "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0001" ] } ], "boundary": "Resource origins do not establish server locations, network routes, or transfers of patient data. The funding amount belongs to the company, not to this individual benefit.", "confidence": "High for the named funding relationship and resource use. Moderate for the inferred geographic relationships." } }, "provenance": { "kind": "source_review", "basis": "Combined direct transaction evidence, original resource histories, and the discovery methods. Kept documented relationships separate from inferred geographic links.", "record_fields": [], "source_refs": [ "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "AIBD-0042-source-0004", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "AIBD-0042-source-0003", "AIBD-0042-source-0005", "AIBD-0042-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Singapore’s Temasek invested in BenevolentAI. The U.K. researchers used Japanese and Italian scientific resources before trials in several countries.", "editor_note": "The geographic links follow the producers of KEGG and SIGNOR, which Smith and colleagues name in reference 4. They identify international knowledge reuse, not the route of a data transfer. Temasek funded the company as a whole." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "structured", "data": { "FDA": { "date": "2020-11-19", "action": "Issued the EUA to Eli Lilly for baricitinib with remdesivir in eligible hospitalized adults and children aged two or older requiring specified respiratory support." }, "WHO": { "date": "2022-01-14", "action": "Strongly recommended baricitinib with corticosteroids for severe or critical COVID-19." }, "later_evidence": "RECOVERY later confirmed lower 28-day mortality. These sources do not quantify adoption caused by the decisions." } }, "provenance": { "kind": "source_review", "basis": "Separated the decisions, later clinical evidence, and unmeasured implementation effects.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The FDA authorized baricitinib with remdesivir on 19 November 2020. WHO recommended it with corticosteroids on 14 January 2022." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "structured", "data": { "FDA": "ACTT-2 results and the emergency-use standard: reasonable belief that the combination may be effective, with known and potential benefits outweighing known and potential risks for the authorized population. An EUA differs from full approval.", "WHO": "Guideline review of clinical-trial evidence. WHO recommended baricitinib with corticosteroids and identified access and affordability as conditions for wider benefit.", "AI_scope": "Neither decision assessed the incremental value of the AI discovery method." } }, "provenance": { "kind": "source_review", "basis": "The FDA announcement states its evidentiary standard; WHO states the recommendation and access limitations.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The FDA relied on ACTT-2. WHO weighed the clinical evidence, harms, affordability, and access." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "structured", "data": { "decisions": [ { "id": "FDA-baricitinib-EUA-2020-11-19", "institution": "U.S. Food and Drug Administration", "jurisdiction": "United States", "task": "Whether to authorize emergency use of baricitinib with remdesivir for specified hospitalized patients with COVID-19." }, { "id": "WHO-baricitinib-guidance-2022-01-14", "institution": "World Health Organization", "scope": "International clinical guidance", "task": "Whether to recommend baricitinib for severe or critical COVID-19." } ] } }, "provenance": { "kind": "source_review", "basis": "Read the original dated agency announcements.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The FDA considered emergency authorization. WHO considered treatment guidance for severe or critical COVID-19." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "structured", "data": { "clinical_question": "Whether adding baricitinib improves recovery or survival with acceptable harms compared with the same background care.", "adoption_question": "Whether eligible patients can obtain treatment and whether clinical benefits persist in routine practice.", "unresolved": "The cited agency statements do not specify a numerical global uptake target or measure the effects caused by adopting their guidance." } }, "provenance": { "kind": "source_review", "basis": "The clinical questions follow the source outcomes; implementation remains a separate unanswered question.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Both agencies sought better survival or recovery with acceptable harms. They did not quantify the additional use or health improvement that their decisions caused." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "structured", "data": { "ai": "Used by BenevolentAI researchers in January 2020", "treatment": "Evaluated in randomized clinical trials and subsequently authorized or recommended", "scope": "The AI application and the drug have different deployment stages." } }, "provenance": { "kind": "source_review", "basis": "The methods paper documents actual use of the graph; clinical and policy sources concern the resulting treatment.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used the AI system in January 2020. Clinical trials and treatment authorization followed." } }, "economics[].amount": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital_base_case": { "incremental_expenditure_usd": -2436, "incremental_reimbursement_usd": -503, "incremental_net_cost_usd": -1932 }, "hospital_mortality_only": { "incremental_expenditure_usd": 1978, "incremental_reimbursement_usd": 0, "incremental_net_cost_usd": 1978 }, "payer_base_case": { "placebo_soc_total_usd": 329268, "baricitinib_soc_total_usd": 346544, "incremental_total_usd": 17276, "incremental_qalys": 0.6703, "usd_per_qaly_gained": 25774 }, "payer_mortality_only": { "incremental_total_usd": 17902, "incremental_qalys": 0.6664, "usd_per_qaly_gained": 26862 }, "rounding": "The published rounded components do not subtract exactly to the reported net amount of $1,932." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Table IV; appendix Tables S5–S6.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The model estimates US$1,932 less in net hospital costs per patient. Over a lifetime, costs rise US$17,276 and health improves by 0.6703 quality-adjusted life-years." } }, "economics[].costs[]": { "state": "value_present", "value": { "kind": "structured", "data": { "included": [ "Drug acquisition", "Medical care during admission", "Hospital reimbursement for inpatient care", "Postacute care and lifetime healthcare in the payer model", "Missed work in the payer model" ], "unit_inputs": { "baricitinib_2mg_tablet_usd": 75.5, "baricitinib_assumed_dose": "4 mg daily for up to 14 days or discharge", "hospital_day_mechanical_ventilation_usd": 3660, "hospital_day_noninvasive_ventilation_usd": 2450, "hospital_day_supplemental_oxygen_usd": 1828, "hospital_day_no_oxygen_usd": 1818 }, "not_reported": "The sources do not quantify this discovery project’s AI development, data licensing, compute, integration, maintenance, or human review costs." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Costs; Table III; Dosing and administration.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The model includes medicines, hospital care, later healthcare, and missed work. It excludes the costs of developing and operating the AI system." } }, "economics[].counterfactual": { "state": "value_present", "value": { "kind": "structured", "data": { "comparison": "Baricitinib plus standard care versus placebo plus the same standard care in the modeled COV-BARRIER population.", "base_case": "Uses numerical differences in mortality, recovery, and respiratory-support outcomes.", "mortality_only_scenario": "Limits treatment benefit to mortality reduction. Hospital costs rise rather than fall.", "AI_counterfactual": "No matched AI-versus-no-AI discovery scenario." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Model inputs; Analyses; Secondary Analyses.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The researchers compared baricitinib plus standard care with placebo plus the same care. Assuming only lower mortality reverses hospital savings to US$1,978 in additional costs per patient." } }, "economics[].currency_price_basis": { "state": "value_present", "value": { "kind": "structured", "data": { "currency": "USD", "jurisdiction": "United States", "price_basis": "The model uses U.S. dollar cost and payment inputs from 2020–2021. Some older care costs and future healthcare costs were inflated to 2020 USD; home-health and hospice reimbursement inputs use 2021 rates. The article does not establish that every input shares one uniform price year.", "conversion": "No currency conversion was used for these source figures." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Costs section, Table III, appendix input tables.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "U.S. dollars, with inputs from 2020–2021. Some costs were adjusted to 2020 prices, but the inputs do not share one price year." } }, "economics[].gross_net": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital": "Net costs mean expenditures minus reimbursement. Base case: expenditure falls $2,436 and reimbursement falls $503, yielding a reported $1,932 net cost reduction.", "payer": "Incremental total costs include inpatient, postacute, future all-cause healthcare, and indirect costs. More survivors accumulate additional lifetime medical costs.", "exclusions": "No AI development or operating costs, long-COVID burden, COVID-related readmissions, or measured value from using freed beds for other patients." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Costs; Discussion limitations; appendix Tables S5–S6.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospital costs are net of reimbursement. Lifetime costs include healthcare and missed work. The model excludes long COVID, COVID-related readmissions, and the value of freed beds." } }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital": "Modeled change in hospital expenditure and net costs after reimbursement.", "payer": "Modeled incremental lifetime healthcare and indirect costs, and cost per quality-adjusted life-year.", "AI_boundary": "The model evaluates the treatment that researchers identified with AI assistance. It does not value AI separately." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Population and Perspective, Secondary Analyses, Table IV and supplementary Tables S5–S6.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Estimated hospital savings and the lifetime cost of additional health from treatment with baricitinib. The study assigns no separate monetary value to AI." } }, "economics[].period_unit": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital": "Per modeled hospital admission, over the inpatient stay.", "payer": "Per modeled patient over a lifetime horizon.", "recurrence": "These are modeled per-patient differences, not recurring annual cash flows or a verified total across patients." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Population and Perspective; Model Framework.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospital costs cover one admission per patient. Costs to insurers cover each patient’s remaining lifetime." } }, "economics[].realization": { "state": "value_present", "value": { "kind": "structured", "data": { "state": "Modeled estimate", "basis": "Economic simulation using clinical trial effects and administrative cost inputs; no observed hospital ledger or cash saving was reported." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Methods and Secondary Analyses.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The amounts come from an economic model, without observed cash savings." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital_perspective": "Hospitals bear treatment costs and receive reimbursements. The estimated net saving reflects both components.", "payer_perspective": "Medicare, Medicaid, and private payers; the modeled mix is 52.9%, 19.2%, and 27.9%, respectively. The article also includes missed-work costs in its payer perspective.", "patients": "Clinical gains accrue to patients. The model excludes uninsured patients and does not establish individual out-of-pocket savings.", "AI_provider": "No payment, royalty, revenue, or profit to BenevolentAI is quantified by this analysis." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Population and Perspective; Table III; Costs.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Patients gain health. Hospitals pay for treatment and receive reimbursement from Medicare, Medicaid, and private insurers." } }, "economics[].return_payback": { "state": "value_present", "value": { "kind": "structured", "data": { "reported_status": "The source reports treatment costs and cost-effectiveness ratios, not a financial ROI, AI-project return, or exact payback date.", "aibd_calculated_health_value": { "name": "Incremental net monetary benefit", "perspective": "U.S. payer, per modeled patient over a lifetime", "formula": "Assumed USD value per quality-adjusted life-year × additional quality-adjusted life-years − additional lifetime costs", "source_inputs": { "base_additional_qalys": 0.6703, "base_additional_cost_usd": 17276, "mortality_only_additional_qalys": 0.6664, "mortality_only_additional_cost_usd": 17902 }, "scenarios": [ { "usd_per_qaly": 25000, "base_net_value_usd": -518.5, "mortality_only_net_value_usd": -1242, "assumption": "AIBD sensitivity scenario" }, { "usd_per_qaly": 50000, "base_net_value_usd": 16239, "mortality_only_net_value_usd": 15418, "assumption": "Threshold used in the original study" }, { "usd_per_qaly": 100000, "base_net_value_usd": 49754, "mortality_only_net_value_usd": 48738, "assumption": "AIBD sensitivity scenario" } ], "interpretation": "A valuation of additional health after additional costs, not a cash receipt or an estimate of AI’s separate contribution." }, "aibd_calculated_drug_cost_reference": { "formula": "$75.50 per 2-mg tablet × two tablets per day × 14 days", "full_course_reference_usd": 2114, "base_modeled_hospital_net_benefit_usd": 1932, "base_benefit_as_percent_of_reference": 91.4, "mortality_only_modeled_hospital_net_benefit_usd": -1978, "mortality_only_benefit_as_percent_of_reference": -93.6, "interpretation": "The model’s net hospital benefit divided by a full-course acquisition-cost benchmark. This is a reference ratio, not the model’s actual mean-cost ROI. Treatment could end earlier, dosing could differ, and acquisition prices could differ." }, "payback_assessment": { "accounting_horizon": "The modeled hospital admission", "base_case": "The model ends with lower net hospital costs.", "mortality_only_scenario": "The model ends with higher net hospital costs.", "cash_timing_status": "Purchase, payment, and savings dates are not reported, so an exact cash-payback day is not calculable from these totals." }, "estimation_confidence": "Arithmetic is reproducible from the published inputs. Economic conclusions depend on the model, valuation threshold, and clinical-effect assumptions." } }, "provenance": { "kind": "derivation", "basis": "Calculated the scenario values and reference ratios directly from the published economic model and appendix, with no invented AI attribution or cash-flow schedule.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "At US$50,000 per quality-adjusted life-year, AIBD values the additional health at US$16,239 per patient after costs: (50,000 × 0.6703) − 17,276. Cash returns and payment dates were not reported." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "structured", "data": { "method": "Linked inpatient, discharged, and recovered submodels based on COV-BARRIER effects, with duration of respiratory support rescaled using ACTT-2 data and U.S. administrative cost inputs. Hospital costs are days at each support level multiplied by daily cost, less reimbursement for net cost.", "discount_rate_per_year": 0.03, "sensitivity": "One-way and probabilistic sensitivity analyses (5,000 replications) for the payer model; a mortality-only scenario for both perspectives.", "payer_probabilistic_estimate": "Mean incremental cost $17,373 (95% interval −$3,300 to $38,306) and 0.674 QALYs (95% interval −0.096 to 1.441). These are model uncertainty results, not intervals from observed cash savings.", "source_dependency": "Some COV-BARRIER and Premier Healthcare Database inputs are data on file with Lilly and are not independently recoverable from the publication.", "funder": "Eli Lilly and Company.", "aibd_additional_calculations": "The return/payback field gives labeled net monetary benefit scenarios and a drug-cost reference ratio. These use the published model outputs; they are not new observations." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Model Framework, inputs, sensitivity analyses, Funding and appendix.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The researchers combined trial results with U.S. costs and applied a 3% annual discount rate. Hospital savings depend on clinical differences that were not all statistically conclusive." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "structured", "data": { "reported_status": "No controlled estimate of additional value from AI is reported.", "aibd_inference": "Automated extraction and graph exploration probably reduced the manual work needed to assemble and examine relevant biomedical relationships. The published workflow supports this inference, but does not establish how much time was saved or whether the same drug would have been selected without AI.", "inference_confidence": "Moderate for assistance with information retrieval and prioritization. A numerical contribution to clinical benefit is not identifiable from these studies.", "documented_workflow_proxies": { "approximately_added_relationships": 40000, "proteins_in_initial_network": 556, "approved_AAK1_inhibitors_examined": 47, "high_affinity_AAK1_candidates": 6, "selected_drug": "Baricitinib", "iteration_timescale": "The developers describe iterations within hourly timeframes." }, "estimation_basis": "The original correspondence and methods paper report these workflow quantities. They measure the scale of the work, not an improvement against a human-only control.", "attribution_boundary": "No share of the clinical or economic result is assigned to AI." } }, "provenance": { "kind": "derivation", "basis": "Derived a qualitative contribution assessment from the documented mechanism and process counts. No causal percentage or time saving was invented.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0005", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The software probably reduced the work needed to assemble and examine relevant biomedical findings.", "editor_note": "Smith and colleagues report about 40,000 added relationships and a starting network of 556 proteins (reference 4). These quantities support an inference of substantial assistance, but the authors did not time a comparable search without AI." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "Baricitinib plus remdesivir versus placebo plus remdesivir, alongside supportive care.", "COV-BARRIER": "Baricitinib plus standard care versus placebo plus standard care; 79.3% received systemic corticosteroids at baseline and 18.9% remdesivir.", "RECOVERY": "Baricitinib plus usual care versus usual care alone. At baseline 95% received corticosteroids and 23% tocilizumab.", "economic_model": "Baricitinib plus standard care versus placebo plus standard care, using the COV-BARRIER population and treatment estimates.", "AI_comparison": "None of these trials randomized use of AI in the drug-discovery process." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Methods and baseline characteristics.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Patients received baricitinib or no baricitinib alongside the same background care. ACTT-2 gave remdesivir to both groups." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "structured", "data": { "evaluations": [ { "id": "ACTT-2", "design": "Randomized, double-blind, placebo-controlled trial." }, { "id": "COV-BARRIER", "design": "Randomized, double-blind, placebo-controlled phase 3 trial." }, { "id": "RECOVERY-baricitinib", "design": "Randomized, open-label, controlled platform trial." }, { "id": "Ohsfeldt-2021-economic-model", "design": "Simulation using clinical trial estimates, U.S. hospital cost data, published price and utility inputs, and sensitivity analyses." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Methods.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Investigators randomly assigned treatment in all three trials. ACTT-2 and COV-BARRIER concealed assignments, while RECOVERY disclosed them. The economic study simulated costs and health." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": { "recovery_rate_ratio": 1.16, "confidence_interval_95": [ 1.01, 1.32 ], "p": 0.03, "median_difference_days": -1, "mortality_hazard_ratio": 0.65, "mortality_confidence_interval_95": [ 0.39, 1.09 ], "mortality_conclusion": "Not statistically conclusive." }, "COV-BARRIER": { "primary_odds_ratio": 0.85, "primary_confidence_interval_95": [ 0.67, 1.08 ], "primary_p": 0.18, "primary_absolute_difference_percentage_points": -2.7, "mortality_hazard_ratio": 0.57, "mortality_confidence_interval_95": [ 0.41, 0.78 ], "mortality_nominal_p": 0.0018, "reported_mortality_absolute_difference_percentage_points": -5.0, "limitation": "Mortality did not meet multiplicity-controlled significance because the preceding primary endpoint failed." }, "RECOVERY": { "age_adjusted_mortality_rate_ratio": 0.87, "confidence_interval_95": [ 0.77, 0.99 ], "p": 0.028, "raw_rates": "514/4148 versus 546/4008; the paper rounds these to 12% and 14%.", "caution": "Do not call the difference in death counts (32) the number of lives saved, because arm sizes differ." }, "economic_model": { "hospital_base_net_cost_difference_usd": -1932, "hospital_mortality_only_cost_difference_usd": 1978, "lifetime_payer_base_cost_difference_usd": 17276 } } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at ACTT-2 Table 2; COV-BARRIER Table 2; RECOVERY Table 2; economic model Table IV, appendix Tables S5–S6.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Median recovery was 7 rather than 8 days in ACTT-2. Deaths by day 28 were 8% versus 13% in COV-BARRIER and 12% versus 14% in RECOVERY." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "structured", "data": { "basis": "Randomized participants are the matched denominators. Treatment-arm sizes are not counts of people proven to have benefited.", "ACTT-2": { "baricitinib_assigned": 515, "control": 518 }, "COV-BARRIER": { "baricitinib_assigned": 764, "control": 761, "safety_analysis_population": 1502 }, "RECOVERY": { "baricitinib_assigned": 4148, "usual_care": 4008 }, "economic_model": "Costs are per modeled eligible adult admission or patient lifetime, according to perspective; no observed number of hospital admissions generating the stated savings." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Participant flow, intention-to-treat populations, model population and perspective.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ACTT-2 assigned 515 patients to baricitinib and 518 to control. COV-BARRIER assigned 764 and 761. RECOVERY assigned 4,148 and 4,008." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "structured", "data": { "evaluations": [ { "id": "ACTT-2", "registry": "NCT04401579" }, { "id": "COV-BARRIER", "registry": "NCT04421027" }, { "id": "RECOVERY-baricitinib", "registry": [ "NCT04381936", "ISRCTN50189673" ] }, { "id": "Ohsfeldt-2021-economic-model", "doi": "10.1016/j.clinthera.2021.09.016" } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Methods and article identifiers.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ACTT-2, COV-BARRIER, RECOVERY, and Ohsfeldt and colleagues’ 2021 economic study." } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "Clinical status on an eight-category ordinal scale; recovery was the first day in categories 1, 2, or 3 within 28 days. Trial staff collected clinical outcomes.", "COV-BARRIER": "Clinical progression on the NIAID ordinal scale, recorded mortality, and adjudicated safety events; study visits through day 28 and mortality assessment through day 60.", "RECOVERY": "Site staff completed follow-up forms at discharge, death, or day 28. Researchers also linked routinely collected healthcare and registry data.", "economic_model": "Three linked submodels covered inpatient care, discharge, and recovery. Model results are estimates rather than transactions or measured savings." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at ACTT-2 Outcomes; COV-BARRIER Procedures; RECOVERY Procedures; economics Model Framework.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Investigators used clinical assessments, follow-up forms, and health records. The economists combined trial findings with treatment prices and costs of care." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": { "metric": "Time to recovery", "role": "Primary outcome", "period_days": 28, "baricitinib_median_days": 7, "control_median_days": 8 }, "COV-BARRIER": { "primary": "Progression to high-flow oxygen, noninvasive ventilation, invasive ventilation, ECMO, or death by day 28.", "primary_values_percent": [ 27.8, 30.5 ], "mortality_role": "Prespecified key secondary outcome", "mortality_days": 28, "baricitinib_deaths": 62, "baricitinib_randomized": 764, "control_deaths": 100, "control_randomized": 761 }, "RECOVERY": { "metric": "All-cause mortality", "role": "Primary outcome", "period_days": 28, "baricitinib_deaths": 514, "baricitinib_randomized": 4148, "control_deaths": 546, "control_randomized": 4008 }, "economic_model": { "metrics": [ "Incremental hospital expenditure", "Incremental reimbursement", "Incremental net hospital costs", "Incremental lifetime payer costs", "Quality-adjusted life-years", "Cost per quality-adjusted life-year" ] } } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Main outcomes and results tables; economic model Table IV and supplementary Table S6.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The primary outcomes were recovery time in ACTT-2, disease progression in COV-BARRIER, and deaths within 28 days in RECOVERY. The economists estimated costs and quality-adjusted life-years." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "NCT04401579; the publication links its protocol, supplementary appendix, disclosures, and data-sharing statement.", "COV-BARRIER": "NCT04421027; supplementary appendix 6 contains protocol details, the statistical plan, and additional outcomes.", "RECOVERY": "NCT04381936 and ISRCTN50189673; the article links the protocol/statistical plan and supplementary appendix; https://www.recoverytrial.net/ supplies trial documents.", "economic_model": "Published methods and an original DOCX appendix provide equations, inputs, and result Tables S1–S6. Some trial and hospital-cost inputs remain proprietary data on file. The full executable economic model and its underlying individual records are not supplied in the reviewed materials.", "AI_system": "The developers publish workflow methods, but not the full proprietary graph, a frozen January 2020 checkpoint, or an executable end-to-end reconstruction." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Supplementary material links, methods and data-sharing sections.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0004", "AIBD-0042-source-0010", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Trial registrations, protocols, analysis plans, and appendices are public. The complete historical AI system and economic model are unavailable, and some cost inputs are unpublished." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": { "randomized": 1033, "sites": 67, "countries": [ "United States", "Singapore", "South Korea", "Mexico", "Japan", "Spain", "United Kingdom", "Denmark" ], "enrollment_start": "2020-05-08", "enrollment_end": "2020-07-01", "population": "Hospitalized adults with COVID-19." }, "COV-BARRIER": { "randomized": 1525, "sites": 101, "countries_count": 12, "enrollment_start": "2020-06-11", "enrollment_end": "2021-01-15", "population": "Hospitalized adults with COVID-19 and an elevated inflammatory marker; patients already receiving invasive mechanical ventilation were excluded from the main trial." }, "RECOVERY": { "randomized": 8156, "country": "United Kingdom", "enrollment_start": "2021-02-02", "enrollment_end": "2021-12-29", "population": "Hospitalized patients with suspected or confirmed COVID-19; age at least two years under the protocol, with 33 children in the comparison." }, "economic_model": { "country": "United States", "population": "A modeled adult population based on COV-BARRIER; inpatient cost inputs from the Premier Healthcare Database, April 1–September 15, 2020. Uninsured patients excluded." } } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Study design, participants, Results, and economic model Population/Costs.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trials enrolled hospitalized patients in 2020–2021: 1,033 in ACTT-2, 1,525 in COV-BARRIER, and 8,156 in RECOVERY. The economic study modeled insured U.S. adults." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "structured", "data": { "AI": "No controlled estimate of the AI workflow’s additional contribution; experts chose the candidate, and trials tested the medicine.", "ACTT-2": "Mortality was not the primary endpoint and its confidence interval included no effect. The trial occurred before corticosteroids became routine for these patients.", "COV-BARRIER": "The primary progression endpoint failed, leaving secondary mortality p values nominal under the prespecified hierarchy. Lilly sponsored, designed, and analyzed the trial.", "RECOVERY": "Open-label treatment, an age imbalance addressed in analysis, and a smaller mortality effect than earlier trials. Outcome data were available for more than 99% of randomized patients.", "economic_model": "Lilly funded the study. Base-case hospital savings depend on numerical clinical differences that were not all statistically conclusive; savings reverse in the mortality-only scenario. Some inputs are unpublished data on file. The model excludes long COVID, COVID-related readmissions, uninsured patients, and measured value from freed hospital capacity. Its U.S. costs may not generalize to individual hospitals or other countries." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Trial Discussion/Methods and economic model Discussion, Secondary Analyses, Funding/Conflicts.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "COV-BARRIER investigators did not establish less disease progression, which prevented confirmatory testing of mortality under their analysis plan. RECOVERY participants knew their treatment. Lilly funded COV-BARRIER and the economic study. None compared discovery with and without AI." } }, "external_references[]": { "state": "value_present", "value": { "kind": "structured", "data": { "trial_registrations": [ { "id": "NCT04401579", "trial": "ACTT-2" }, { "id": "NCT04421027", "trial": "COV-BARRIER" }, { "id": "NCT04381936", "trial": "RECOVERY" }, { "id": "ISRCTN50189673", "trial": "RECOVERY" } ], "scope_note": "No harm involving this system and episode is established by the reviewed sources. The prior Watson example involved another system." } }, "provenance": { "kind": "source_review", "basis": "Linked actual trial identifiers and removed an unrelated incident comparison.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ACTT-2: NCT04401579. COV-BARRIER: NCT04421027. RECOVERY: NCT04381936 and ISRCTN50189673." } }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2022-07-28", "note": "RECOVERY independently found lower 28-day mortality with baricitinib. WHO had recommended its use with corticosteroids for severe or critical COVID-19 in January 2022. The recommendation does not establish worldwide uptake.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/" } } }, "provenance": { "kind": "source_review", "basis": "Recorded further clinical confirmation and kept policy guidance separate from demonstrated uptake.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Oxford’s RECOVERY investigators independently confirmed lower mortality in July 2022." } }, "human_oversight": { "state": "value_present", "value": { "kind": "structured", "data": { "discovery": "Scientists iteratively queried the graph and assessed target binding, dose, and pharmacology before selecting the drug.", "clinical_testing": "Trial investigators, ethics committees, and monitoring arrangements governed treatment and follow-up.", "unreported": "The company’s internal software access controls and formal training requirements are not described." } }, "provenance": { "kind": "source_review", "basis": "The methods paper assigns enrichment, querying, and pharmacological assessment to named authors; trials describe their own oversight.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers chose the candidate drug. Clinicians prescribed treatment under trial protocols, with oversight from ethics committees and monitors." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0042" } }, "provenance": { "kind": "source_review", "basis": "Preserved the existing case identifier.", "record_fields": [ "id" ], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0042" } }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "structured", "data": { "data_sources": [ "KEGG", "Reactome", "STRING", "SIGNOR", "BioGRID", "ChEMBL", "CTD", "GWAS Catalog", "Gene Ontology", "OMIM", "Mondo" ], "software": "BenevolentAI knowledge graph and interactive network tools; SciPy is identified for enrichment analysis.", "unreported": [ "Compute hardware", "Cloud provider", "Hosting country", "Energy and water use", "Complete graph snapshot" ] } }, "provenance": { "kind": "source_review", "basis": "The methods paper names the data sources and software dependencies. Hardware and resource use are not documented.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The researchers used BenevolentAI’s graph, SciPy, and 11 biomedical resources, including KEGG, Reactome, and SIGNOR. Their methods paper does not identify the hardware or hosting provider." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "structured", "data": { "personal": "People hospitalized with COVID-19, principally adults who required supplemental oxygen or ventilatory support. Trials evaluated groups rather than identifying which particular people survived because of treatment.", "organizational": "Hospitals that treated eligible patients; shorter recovery is a proxy for resource use, and the monetary benefit is modeled.", "societal": "Health systems with access to baricitinib and the capacity to give it with appropriate clinical supervision. Trials establish patient effects, not an independently measured population-wide effect." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Trial eligibility and results; economic model Population and Perspective.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospitalized patients with COVID-19 and the hospitals and health systems treating them." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "structured", "data": { "known_exposure": [ { "study": "ACTT-2", "randomized": 1033, "baricitinib_assigned": 515, "control_assigned": 518 }, { "study": "COV-BARRIER", "randomized": 1525, "baricitinib_assigned": 764, "control_assigned": 761 }, { "study": "RECOVERY", "randomized": 8156, "baricitinib_assigned": 4148, "control_assigned": 4008 } ], "actually_benefiting": "The individual number whose recovery or survival changed because of baricitinib is not directly observed. Randomized comparisons estimate an average treatment effect. Trial enrollment, treatment assignment, patients discharged, and people whose lives were saved are different counts.", "population_total": "No verified worldwide beneficiary count is established by these trial reports." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Results, participant flow and mortality tables.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trials enrolled 10,714 participants in total, including controls. That total does not identify how many people benefited. The publications give no worldwide count." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The clinical benefit is reduced mortality and faster recovery. AI assisted the researchers who proposed the drug for testing." } }, "provenance": { "kind": "source_review", "basis": "Assigned Improved Physical Health to the documented clinical benefit.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved Physical Health" } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "structured", "data": { "benefits": [ { "id": "AIBD-0042-benefit-mortality", "title": "Fewer deaths", "statement": "In RECOVERY, 12% of patients receiving baricitinib died within 28 days, compared with 14% receiving usual care alone.", "benefit_type": "Improved Physical Health", "status": "reported", "beneficiaries": "Patients hospitalized with COVID-19.", "source_refs": [ "AIBD-0042-source-0002" ], "ratings": [ { "group": "personal", "depth": 5, "reason": "RECOVERY found lower 28-day mortality with baricitinib, a life-preserving benefit." } ], "evidence_word": "studied" }, { "id": "AIBD-0042-benefit-recovery", "title": "Faster recovery", "statement": "In ACTT-2, patients receiving remdesivir recovered in a median of 7 days with baricitinib, compared with 8 days with a placebo.", "benefit_type": "Improved Physical Health", "status": "reported", "beneficiaries": "Patients hospitalized with COVID-19.", "source_refs": [ "AIBD-0042-source-0005" ], "ratings": [ { "group": "personal", "depth": 2, "reason": "ACTT-2 found a shorter median recovery time in a randomized comparison, a measurable improvement in patients’ health." } ], "evidence_word": "studied" } ] } }, "provenance": { "kind": "source_review", "basis": "Separated the two measured clinical benefits already documented in the record. RECOVERY supports lower mortality; ACTT-2 supports faster recovery. The trials evaluated treatment effects, not the incremental value of AI-assisted drug selection. Each benefit has its own source references and beneficiary assessment. The existing hospital and societal assessments remain in the record.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0042-source-0002", "AIBD-0042-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Fewer deaths: In RECOVERY, 12% of patients receiving baricitinib died within 28 days, compared with 14% receiving usual care alone. Faster recovery: In ACTT-2, patients receiving remdesivir recovered in a median of 7 days with baricitinib, compared with 8 days with a placebo." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "The high-flow oxygen or noninvasive ventilation subgroup had median recovery of 10 versus 18 days (recovery rate ratio 1.51, 95% CI 1.10–2.08), compared with 7 versus 8 days overall. Subgroup estimates have lower precision.", "COV-BARRIER": "Effects were examined by age, sex, region, baseline respiratory support, symptom duration, remdesivir, and corticosteroids. The large mortality difference among patients receiving high-flow oxygen or noninvasive ventilation is a secondary subgroup result subject to the trial’s multiplicity limit. The trial did not establish a positive benefit in every participating country.", "RECOVERY": "No evidence of treatment-effect differences across the six prespecified subgroups (age, sex, ethnicity, symptom duration, respiratory support, corticosteroid use; interaction p values >0.18). This is not proof that all subgroups benefit equally.", "economic_access": "The U.S. cost model excluded uninsured patients because out-of-pocket cost data were unavailable. It does not establish savings in other jurisdictions." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at ACTT-2 Table 2; COV-BARRIER Figures 2–3; RECOVERY Figure 3; economic model Costs.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "ACTT-2 patients on high-flow oxygen or noninvasive ventilation recovered in a median of 10 rather than 18 days. This subgroup estimate is less precise. RECOVERY found no clear differences among subgroups." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "Clinical outcomes followed through day 28.", "COV-BARRIER": "Primary and key secondary outcomes through day 28; exploratory mortality through day 60, with 79/764 deaths versus 116/761 (hazard ratio 0.62, 95% CI 0.47–0.83).", "RECOVERY": "The reported main outcomes were assessed at 28 days; a planned six-month analysis is not evidence of a six-month result.", "economic_model": "Hospital estimates cover the admission; payer estimates extend over a modeled lifetime. The lifetime benefit is projected, not observed follow-up." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Trial Outcomes/Results; economic model Population and Perspective.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trials followed patients for 28 days. COV-BARRIER investigators also examined deaths through day 60 in an exploratory analysis. The economists projected costs and health over a lifetime." } }, "outcomes[].id": { "state": "value_present", "value": { "kind": "structured", "data": { "benefit_ids": [ "AIBD-0042-benefit-mortality", "AIBD-0042-benefit-recovery" ], "stakeholder_assessment_ids": { "personal": "AIBD-0042-outcome-personal", "organizational": "AIBD-0042-outcome-organizational", "societal": "AIBD-0042-outcome-societal" } } }, "provenance": { "kind": "curatorial", "basis": "Assigned separate stable identifiers to mortality and recovery while retaining the earlier stakeholder-assessment identifiers.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0042-benefit-mortality, AIBD-0042-benefit-recovery" } }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Fewer patients died with baricitinib in COV-BARRIER and RECOVERY. RECOVERY confirmed lower 28-day mortality as its primary outcome in 8,156 patients." }, { "group": "organizational", "depth": 2, "reason": "ACTT-2 reported median recovery of 7 days with baricitinib and 8 days without it. That could free hospital capacity. A separate economic model estimated lower hospital costs, but neither establishes realized staffing or cash savings." }, { "group": "societal", "depth": 4, "reason": "WHO recommended baricitinib with corticosteroids for severe or critical COVID-19. That recommendation supports wider access to a treatment that reduced deaths in trials. Worldwide uptake and population-wide effects were not measured." } ] } }, "provenance": { "kind": "source_review", "basis": "Preserved the personal, organizational, and societal targets with explicit distinctions in their support.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "People, organizations, and society." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "structured", "data": { "personal": "Observed treatment benefit in trials", "organizational": "Potential capacity benefit and modeled financial result, not measured realized savings", "societal": "International treatment recommendation observed; population-wide effects not measured" } }, "provenance": { "kind": "source_review", "basis": "Separated observed patient outcomes from projected or unmeasured wider effects.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0007", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Patient benefits were observed. Hospital savings were modeled. WHO recommended wider treatment. These studies did not measure population-wide effects." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "structured", "data": { "ACTT-2": "Serious adverse events occurred in 16.0% with baricitinib plus remdesivir and 21.0% with remdesivir alone. Venous thromboembolism occurred in 4.1% versus 3.1%, a difference of 1.0 percentage point (95% CI −1.3 to 3.3).", "COV-BARRIER": "Among 750 baricitinib recipients and 752 placebo recipients in the safety population, serious adverse events occurred in 110 (15%) versus 135 (18%), serious infections in 64 (9%) versus 74 (10%), and venous thromboembolism in 20 (3%) versus 19 (3%). These findings concern short treatment and follow-up and do not establish absence of rare or long-term harms.", "RECOVERY": "No significant excess in the prespecified infection, thrombotic, or bleeding outcomes was detected. Investigators reported 12 suspected serious adverse reactions attributed to baricitinib, including four serious infections other than COVID-19, three bowel perforations, and two pulmonary emboli.", "costs": "The model estimated lower hospital net costs only under its base-case assumptions. Its mortality-only scenario estimated higher hospital costs, and the lifetime payer model estimated higher overall cost because more patients survived." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Trial safety results; RECOVERY Results and appendix p. 61 reference; economic model Secondary Analyses.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Serious adverse events affected 15% of baricitinib recipients and 18% of controls in COV-BARRIER. RECOVERY investigators reported 12 suspected serious reactions. Short follow-up leaves rare and long-term harms uncertain." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "structured", "data": { "assessment": "Expected in purpose: researchers deliberately sought an existing medicine that could help people with COVID-19. Mortality reduction was a prespecified trial outcome, although it was secondary in COV-BARRIER. A failed progression endpoint and favorable mortality result are different findings, not grounds for calling the benefit accidental." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original source at Methods paper Introduction and workflow; trial prespecified Outcomes.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0004", "AIBD-0042-source-0001", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers deliberately sought a treatment, and investigators planned to measure mortality." } }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "location": "Multicountry trials (ACTT-2, COV-BARRIER, and RECOVERY): Argentina; Brazil; Denmark; Germany; India; Italy; Japan; Mexico; Russia; Singapore; South Korea; Spain; United Kingdom; United States", "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "developer_jurisdictions": [ "United Kingdom" ], "case_jurisdictions": [ "Argentina", "Brazil", "Denmark", "Germany", "India", "Italy", "Japan", "Mexico", "Russia", "Singapore", "South Korea", "Spain", "United Kingdom", "United States" ], "location_label": "Trial locations", "location_note": "Trial countries, with results pooled across sites. RECOVERY was conducted in the United Kingdom. Puerto Rico is included under the United States.", "ai_operation": "BenevolentAI research team, with author affiliations in London and Brooklyn. The exact compute location is not reported.", "clinical_evaluators": [ "ACTT-2: NIAID, United States", "COV-BARRIER: Eli Lilly, United States", "RECOVERY: University of Oxford, United Kingdom" ] } }, "provenance": { "kind": "source_review", "basis": "Separated the AI operator’s jurisdiction from trial locations and evaluators. Headquarters does not establish compute location.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "BenevolentAI operated in the United Kingdom. Trials ran in Argentina, Brazil, Denmark, Germany, India, Italy, Japan, Mexico, Russia, Singapore, South Korea, Spain, the United Kingdom, and the United States." } }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Researchers searched for existing drugs that might treat COVID-19, using a biomedical knowledge graph that combines databases with information extracted from scientific papers." } }, "provenance": { "kind": "source_review", "basis": "The original investigators state their intended search for a COVID-19 treatment.", "record_fields": [ "purpose" ], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers sought existing medicines that could treat COVID-19." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "discovery": { "start": "2020-01", "end": "2020-01", "precision": "month" }, "first_ai_publication": "2020-02-04", "actt2_enrollment": { "start": "2020-05-08", "end": "2020-07-01" }, "cov_barrier_enrollment": { "start": "2020-06-11", "end": "2021-01-15" }, "recovery_enrollment": { "start": "2021-02-02", "end": "2021-12-29" }, "case_date": "2021-09-01", "case_date_basis": "Original publication of the COV-BARRIER mortality findings", "date_precision": "day", "first_database_revision": "2026-10-20", "database_discovery_note": "No separate discovery date is recorded.", "last_reviewed": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Separated discovery, study periods, publication, and editorial dates.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers identified baricitinib in January 2020 and reported it on 4 February 2020. COV-BARRIER mortality results appeared on 1 September 2021." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "BenevolentAI researchers combined a biomedical knowledge graph with expert review to select baricitinib.", "Clinical investigators separately tested the drug alongside the care available in 2020 and 2021." ], "must_hold": [ "The clinical comparisons concern hospitalized patients and the eligibility criteria of each trial.", "Background treatment differed: remdesivir in ACTT-2, and mostly corticosteroids in COV-BARRIER and RECOVERY.", "Reproducing the AI selection would also require the January 2020 graph, software configuration, and researchers’ decisions. The complete snapshot is not public." ], "echoes": [ { "date": "2021-09-01", "setting": "COV-BARRIER: 1,525 adults. Lower mortality was a secondary finding after an unsuccessful primary comparison.", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/" }, { "date": "2022-07-28", "setting": "RECOVERY: 8,156 patients in 159 U.K. hospitals. Lower 28-day mortality was the primary finding. These were further tests of the drug, not repetitions of the AI discovery process.", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/" } ] } } }, "provenance": { "kind": "source_review", "basis": "Replaced the WHO recommendation with a genuine subsequent clinical trial. Different trial protocols and endpoints remain explicit.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "COV-BARRIER and RECOVERY both found fewer deaths with baricitinib. The trials tested the medicine, without repeating the AI discovery process." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "BenevolentAI researchers combined a biomedical knowledge graph with expert review to select baricitinib.", "Clinical investigators separately tested the drug alongside the care available in 2020 and 2021." ], "must_hold": [ "The clinical comparisons concern hospitalized patients and the eligibility criteria of each trial.", "Background treatment differed: remdesivir in ACTT-2, and mostly corticosteroids in COV-BARRIER and RECOVERY.", "Reproducing the AI selection would also require the January 2020 graph, software configuration, and researchers’ decisions. The complete snapshot is not public." ], "echoes": [ { "date": "2021-09-01", "setting": "COV-BARRIER: 1,525 adults. Lower mortality was a secondary finding after an unsuccessful primary comparison.", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/" }, { "date": "2022-07-28", "setting": "RECOVERY: 8,156 patients in 159 U.K. hospitals. Lower 28-day mortality was the primary finding. These were further tests of the drug, not repetitions of the AI discovery process.", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/" } ] } } }, "provenance": { "kind": "source_review", "basis": "Distinguished further drug trials from replication of the discovery workflow.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Testing the treatment again requires comparable patients and background care. Repeating the discovery requires the original graph, software configuration, and researchers’ decisions." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 225 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/225", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Recategorised from specific harm prevented to 1 because the sources show an AI-generated repurposing hypothesis confirmed at cohort level by randomized trials rather than a specific harm prevented for an identifiable beneficiary, and, on the fact-checker's other findings, made the ACTT-2 quote verbatim, relabelled the Lancet correspondence letter as “other”, used the exact source titles, replaced the unsupported “hospitals worldwide” with the trial sponsors as deployers, and stated in the summary and account that COV-BARRIER missed its primary endpoint and that its 28-day mortality reduction was a secondary endpoint.", "source": "Richardson P, et al. Lancet 2020 (https://europepmc.org/article/PMC/PMC7137985); Kalil AC, et al. N Engl J Med 2021 (https://europepmc.org/article/PMC/PMC7745180); Marconi VC, et al. Lancet Respir Med 2021 (https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC7745180; https://www.who.int/news/item/14-01-2022-who-recommends-two-new-drugs-to-treat-covid-19", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.benevolent.com/contact-us/; https://en.wikipedia.org/wiki/National_Institute_of_Allergy_and_Infectious_Diseases", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the AI hypothesis, recovery and mortality findings, and regulatory actions to their original sources. Put COV-BARRIER first for the mortality claim, preserved the failed primary endpoint and added the multiplicity limitation. Removed the generic FDA drug-list page from active evidence because it adds no case-specific support beyond the retained authorization. Distinguished NIAID-led ACTT-2 from the Lilly-sponsored COV-BARRIER analysis.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added the developers’ original methods paper, identified the SVO component and January 2020 workflow, and clarified the scientists’ role in selecting baricitinib. The exact model release remains unreported.", "source": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Corrected the developer jurisdiction to its contemporaneous U.K. headquarters and replaced the London-only location with the 14 countries in ACTT-2 and COV-BARRIER. Changed the chronology from the FDA authorization date to September 1, 2021, the original publication date of the COV-BARRIER mortality findings. Trial countries do not imply a separately demonstrated benefit in every country.", "source": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Rewrote the account and resolved all mandatory fields. Added RECOVERY and the original economic model, corrected the AI operator, distinguished projected wider benefits from observed patient outcomes, replaced WHO guidance counted as replication, and removed an unrelated Watson incident. Missing model and attribution details remain explicit. Reordered the sources by their contribution and remapped their identifiers.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "editor": "AIBD, Codex-assisted review" }, { "date": "2026-10-25", "change": "Added historical control from original corporate filings, documented funding and scientific-resource relationships, a labeled strategic assessment, and derived economic scenarios. Preserved the unreported exact model version, with a documented configuration proxy. Distinguished reported findings, calculations, and inferences throughout the assessment.", "source": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "editor": "AIBD, Codex-assisted review" } ] } }, "provenance": { "kind": "source_review", "basis": "Recorded the corrections with prior versions recoverable in repository history.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Ownership, funding, and economic estimates were added on 25 October 2026. Earlier versions remain available." } }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Biomedicine / infectious disease therapeutics", "segment": "Hospitalized COVID-19 patients requiring supplemental oxygen or ventilatory support" } }, "provenance": { "kind": "source_review", "basis": "The application concerns drug discovery and treatment of hospitalized patients.", "record_fields": [ "domain", "segment" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Biomedicine and hospital treatment of infectious disease." } }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "versions_and_access": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7302766/", "finding": "June 18, 2020 correction restores two omitted BenevolentAI authors." }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8425787/", "finding": "September 8, 2021 correction changes the baricitinib number at risk on day 14 in Figure 2A to 684." }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "supplements": "Original and final protocols, analysis plans, supplementary methods/results, and Figure S2 were inspected. Patient-level trial data were not reanalyzed." }, { "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC4780864/", "status": "Full original text, Figure 3 and its description, and methods inspected through Europe PMC XML. Supplementary Table S1 remained inaccessible." }, { "source_url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "status": "Original source inspected.", "locator": "Operational highlights, baricitinib bullet.", "reviewed_on": "2026-10-24" }, { "source_url": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full", "source_ref": "AIBD-0042-source-0004", "publication_date": "2021-07-28", "accessed_on": "2026-10-24", "status": "Original publisher text inspected.", "locator": "Materials and Methods; Results, opening paragraphs and figure 3; Discussion." }, { "source_url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "source_ref": "AIBD-0042-source-0009", "accessed_on": "2026-10-25", "language": "English", "status": "Original developer webpage inspected for corporate geography.", "locator": "About BenevolentAI, final paragraph: London headquarters.", "publication_date": "2020-09-14" }, { "source_ref": "AIBD-0042-source-0001", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "access_url": "https://rcastoragev2.blob.core.windows.net/bf64edd09bbf67d7978734149d4c838a/PMC8409066.pdf", "accessed_on": "2026-10-25", "status": "Original article text and table 1 inspected for country coverage and publication date.", "locator": "Table 1, p. 1411; publication date, p. 1407." }, { "source_ref": "AIBD-0042-source-0005", "source_url": "https://europepmc.org/article/PMC/PMC7745180", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC7745180/fullTextXML", "accessed_on": "2026-10-25", "status": "Full original article XML inspected after intermittent PMC browser checks.", "locator": "Methods, Design, paragraph 2 (section sc1.1)." }, { "source_ref": "AIBD-0042-source-0001", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC8409066/fullTextXML", "accessed_on": "2026-10-25", "status": "Original article text inspected through Europe PMC XML." }, { "source_ref": "AIBD-0042-source-0005", "source_url": "https://europepmc.org/article/PMC/PMC7745180", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC7745180/fullTextXML", "accessed_on": "2026-10-25", "status": "Original article text inspected through Europe PMC XML." }, { "source_ref": "AIBD-0042-source-0003", "source_url": "https://europepmc.org/article/PMC/PMC7137985", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC7137985/fullTextXML", "accessed_on": "2026-10-25", "status": "Original article text inspected through Europe PMC XML." }, { "source_ref": "AIBD-0042-source-0004", "source_url": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC8356560/fullTextXML", "accessed_on": "2026-10-25", "status": "Original article text inspected through Europe PMC XML." }, { "source_ref": "AIBD-0042-source-0002", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9333998/fullTextXML", "accessed_on": "2026-10-25", "status": "Original article text inspected through Europe PMC XML." }, { "source_ref": "AIBD-0042-source-0010", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8487786/", "accessed_on": "2026-10-25", "status": "Original article and supplemental table S6 inspected.", "supplement": "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx" }, { "source_ref": "AIBD-0042-source-0002", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "publication_date": "2022-07-28", "issue_date": "2022-07-30", "verification_url": "https://eprints.gla.ac.uk/292687/", "finding": "The university repository identifies July 28, 2022 as the original online publication date. July 30 is the issue date.", "accessed_on": "2026-10-25" }, { "source_ref": "AIBD-0042-source-0002", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9521822/", "accessed_on": "2026-10-25", "finding": "The October 2022 erratum states that the RECOVERY appendix was corrected on September 29, 2022. It does not identify the amendment, so no assertion about its effect on the findings is made." }, { "source_url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "accessed_on": "2026-10-25", "status": "Original scanned filing inspected, including a visual check of note 22.", "locator": "p. 43, note 22; p. 40, note 18." }, { "source_url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "accessed_on": "2026-10-25", "status": "Original scanned statement and relevant shareholder pages inspected.", "locator": "Share capital, p. 2; shareholder details, pp. 4–6 (unnumbered leaves)." }, { "source_url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "accessed_on": "2026-10-25", "status": "Original scanned return and share-rights pages inspected.", "locator": "pp. 2–3." }, { "source_url": "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "accessed_on": "2026-10-25", "status": "Original counsel announcement inspected.", "locator": "¶¶ 1–3." }, { "source_url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "accessed_on": "2026-10-25", "status": "Original developer announcement inspected.", "locator": "Opening paragraph; funding-purpose paragraph; About BenevolentAI." }, { "source_url": "https://www.genome.jp/kegg/kegg1.html", "accessed_on": "2026-10-25", "status": "Original resource overview inspected.", "locator": "KEGG overview and project history." }, { "source_url": "https://doi.org/10.1093/nar/gkz949", "accessed_on": "2026-10-25", "status": "Original resource paper inspected.", "locator": "Author affiliations; database access and download description." }, { "source_url": "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf", "accessed_on": "2026-10-25", "status": "Original report downloaded and read after browser access failed.", "locator": "p. 38, “Relating to Our Shareholder.”" } ], "limitations": [ "No trial randomized the discovery process to AI versus no AI. The full proprietary graph and ranking run are unavailable.", "COV-BARRIER was sponsor-designed and sponsor-analyzed. Its mortality inference is nominal under the prespecified testing hierarchy.", "The cited recommendation establishes guidance, not measured worldwide adoption or a count of lives saved.", "The original Sorrell et al. article was read. 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WHO recommends two new drugs to treat COVID-19.", "title": "WHO recommends two new drugs to treat COVID-19", "url": "https://www.who.int/news/item/14-01-2022-who-recommends-two-new-drugs-to-treat-covid-19", "date": "2022-01-14", "written_by": "independent", "quote": "The first drug, baricitinib, is strongly recommended for patients with severe or critical COVID-19." }, { "kind": "report", "citation": "BenevolentAI. “BenevolentAI Unaudited Preliminary Results for the Year Ended 31 December 2022,” March 16, 2023, Operational highlights, baricitinib bullet.", "title": "BenevolentAI Unaudited Preliminary Results for the Year Ended 31 December 2022", "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "date": "2023-03-16", "written_by": "makers" }, { "kind": "press release", "citation": "BenevolentAI. “BenevolentAI’s platform-derived hypothesis for COVID-19 treatment validated in US NIAID randomised control trial.” September 14, 2020. “About BenevolentAI,” headquarters statement.", "title": "BenevolentAI’s platform-derived hypothesis for COVID-19 treatment validated in US NIAID randomised control trial", "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "date": "2020-09-14", "written_by": "makers" }, { "kind": "peer-reviewed study", "citation": "Robert Ohsfeldt et al. “Cost-Effectiveness of Baricitinib Compared With Standard of Care: A Modeling Study in Hospitalized Patients With COVID-19 in the United States.” Clinical Therapeutics 43, no. 11 (2021): 1877–1893.e4. Tables IV–V and supplemental table S6. https://doi.org/10.1016/j.clinthera.2021.09.016.", "title": "Cost-Effectiveness of Baricitinib Compared With Standard of Care: A Modeling Study in Hospitalized Patients With COVID-19 in the United States", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8487786/", "date": "2021-10-04", "written_by": "evaluator" } ], "metadata_sources": [ { "url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "citation": "BenevolentAI Limited. Annual Report and Consolidated Financial Statements, 31 December 2019. Filed December 30, 2020.", "locator": "p. 43, note 22; p. 40, note 18.", "date": "2019-12-31", "contribution": "Historical company control and share-class rights immediately before the January 2020 research.", "relationship": "Original statutory company filing. 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Confirmation Statement CS01, October 15, 2019.", "locator": "Share capital, p. 2; shareholder details, pp. 4–6 (unnumbered leaves).", "date": "2019-10-15", "contribution": "The historical voting-share counts used for the labeled AIBD calculation.", "relationship": "Original company filing, with the ordinary and preferred share rights stated explicitly.", "access_note": "Original scanned statement and relevant shareholder pages inspected." }, { "url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "citation": "BenevolentAI Limited. Return of Allotment SH01, December 20, 2019. Filed January 8, 2020.", "locator": "pp. 2–3.", "date": "2019-12-20", "contribution": "A capital check showing that the new G2 growth shares did not carry ordinary voting rights before an exit.", "relationship": "Original company filing. This checks share-class rights, not changes in every beneficial owner.", "access_note": "Original scanned return and share-rights pages inspected." }, { "url": "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "citation": "Covington & Burling LLP. “Covington Advises BenevolentAI on $90M Investment from Temasek.” October 15, 2019.", "locator": "¶¶ 1–3.", "date": "2019-10-15", "contribution": "A participant’s confirmation of Singaporean investment in the developer.", "relationship": "The law firm advised BenevolentAI on the transaction. 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It does not allocate funding to the later baricitinib work.", "access_note": "Original developer announcement inspected." }, { "url": "https://www.genome.jp/kegg/kegg1.html", "citation": "Kanehisa Laboratories. “KEGG Database.”", "locator": "KEGG overview and project history.", "contribution": "The Japanese origin of a biomedical resource that the discovery researchers used.", "relationship": "Resource developers’ account of its history. Geographic reuse is inferred by combining it with the baricitinib methods paper.", "access_note": "Original resource overview inspected." }, { "url": "https://doi.org/10.1093/nar/gkz949", "citation": "Luana Licata et al. “SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 Update.” Nucleic Acids Research 48, no. 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It does not establish government control of BenevolentAI or the research.", "access_note": "Original report downloaded and read after browser access failed." } ] } }, "provenance": { "kind": "source_review", "basis": "Preserved the full clinical and discovery citations and added precise locators for corporate and geographic evidence.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "References 1–10 cover discovery, trials, and costs. 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No translation was needed." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "source_ref": "AIBD-0042-source-0001", "relationship": "Original trial by clinicians and the drug sponsor; not an independent evaluation of the AI discovery process." }, { "source_ref": "AIBD-0042-source-0002", "relationship": "Oxford-led trial, independent of BenevolentAI and the drug manufacturer. Baricitinib came from routine NHS stock." }, { "source_ref": "AIBD-0042-source-0003", "relationship": "BenevolentAI authors and an adviser report their own hypothesis." }, { "source_ref": "AIBD-0042-source-0004", "relationship": "Original methods paper from the developers. It adds technical detail, not an independent evaluation of AI’s clinical benefit." }, { "source_ref": "AIBD-0042-source-0005", "relationship": "NIAID controlled trial design and implementation. Lilly and Gilead supplied medicines and provided protocol input, but did not fund ACTT-2." }, { "source_ref": "AIBD-0042-source-0006", "relationship": "Original regulator statement; its efficacy figures derive from ACTT-2." }, { "source_ref": "AIBD-0042-source-0007", "relationship": "Original WHO recommendation based on trial synthesis, not another clinical experiment." }, { "source_ref": "AIBD-0042-source-0008", "relationship": "Developer’s retrospective identification, not independent verification of clinical benefit." }, { "source_ref": "AIBD-0042-source-0009", "relationship": "Original developer statement. Its clinical claims are not counted as additional verification of the trials." }, { "source_ref": "AIBD-0042-source-0010", "relationship": "Economic study funded by Eli Lilly, with company-employed coauthors. Trial inputs and cost assumptions are modeled, not another clinical experiment." } ], "caution": "An original source is not necessarily independent. FDA and WHO assess treatment evidence; they do not independently measure the contribution of the AI discovery workflow.", "metadata_sources": [ { "source_ref": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "relationship": "Original statutory company filing. The control statement is from the company’s accounts, not an inference from later ownership." }, { "source_ref": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "relationship": "Original company filing, with the ordinary and preferred share rights stated explicitly." }, { "source_ref": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "relationship": "Original company filing. This checks share-class rights, not changes in every beneficial owner." }, { "source_ref": "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "relationship": "The law firm advised BenevolentAI on the transaction. It is a firsthand participant, not an independent financial evaluator." }, { "source_ref": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "relationship": "The recipient’s own announcement. It does not allocate funding to the later baricitinib work." }, { "source_ref": "https://www.genome.jp/kegg/kegg1.html", "relationship": "Resource developers’ account of its history. Geographic reuse is inferred by combining it with the baricitinib methods paper." }, { "source_ref": "https://doi.org/10.1093/nar/gkz949", "relationship": "Original resource paper. It establishes its producers and access conditions, not server or patient-data routes." }, { "source_ref": "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf", "relationship": "The investor’s own institutional account. It does not establish government control of BenevolentAI or the research." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed authors, funding, and document purpose separately from study design.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The developers supplied four sources. Four were independent, and two involved the drug sponsor. Lilly funded COV-BARRIER and the economic study. Manufacturers supplied ACTT-2 medicines and protocol advice, without funding the trial." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0042-source-0001", "retained_source_order": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "contribution": "Lilly-funded COV-BARRIER: mortality and disease progression in 1,525 adults. Mortality was a secondary finding after an unsuccessful primary comparison.", "locator": "Results, Figure 2; supplementary appendix 6, pp. 9–14 and Figure S2. Table 1, p. 1411; publication date, p. 1407.", "relationship": "Original trial by clinicians and the drug sponsor; not an independent evaluation of the AI discovery process.", "source_refs": [ "AIBD-0042-source-0001" ], "display_name": "The Lancet Respiratory Medicine" }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "source_refs": [ "AIBD-0042-source-0002" ], "display_name": "The Lancet", "contribution": "RECOVERY: an independent randomized trial of 8,156 patients, with 28-day mortality as its primary outcome.", "locator": "Table 2; Figure 3; Methods; Declaration of interests; Data sharing.", "relationship": "Oxford-led trial, independent of BenevolentAI and the drug manufacturer. Baricitinib came from routine NHS stock." }, { "url": "https://europepmc.org/article/PMC/PMC7137985", "contribution": "The original February 2020 proposal to test baricitinib, using BenevolentAI’s graph.", "locator": "Lancet 395:e30–e31, text, figure, and references, corrected June 18, 2020.", "relationship": "BenevolentAI authors and an adviser report their own hypothesis.", "source_refs": [ "AIBD-0042-source-0003" ], "display_name": "The Lancet" }, { "url": "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full", "source_refs": [ "AIBD-0042-source-0004" ], "locator": "Materials and Methods; Results, opening paragraphs and figure 3; Discussion.", "display_name": "Frontiers in Pharmacology", "contribution": "The developers explain the graph, algorithms, and scientists’ role in selecting baricitinib.", "relationship": "Original methods paper from the developers. It adds technical detail, not an independent evaluation of AI’s clinical benefit." }, { "url": "https://europepmc.org/article/PMC/PMC7745180", "contribution": "NIAID-led ACTT-2: recovery time in 1,033 adults. Drug suppliers provided medicines and protocol input but did not fund the trial.", "locator": "Table 2; Trial Oversight; supplementary appendix, pp. 19–23; NCT04401579. Methods, Design, paragraph 2.", "relationship": "NIAID controlled trial design and implementation. Lilly and Gilead supplied medicines and provided protocol input, but did not fund ACTT-2.", "source_refs": [ "AIBD-0042-source-0005" ] }, { "url": "https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19", "contribution": "FDA’s November 2020 authorization and its evidentiary basis. The decision concerns the drug, not the AI discovery method.", "locator": "November 19, 2020 announcement, authorization link and ACTT-2 paragraphs.", "relationship": "Original regulator statement; its efficacy figures derive from ACTT-2.", "source_refs": [ "AIBD-0042-source-0006" ] }, { "url": "https://www.who.int/news/item/14-01-2022-who-recommends-two-new-drugs-to-treat-covid-19", "contribution": "WHO’s January 2022 recommendation. Guidance is not another clinical trial or a measure of worldwide uptake.", "locator": "January 14, 2022 statement, baricitinib recommendation and guideline link.", "relationship": "Original WHO recommendation based on trial synthesis, not another clinical experiment.", "source_refs": [ "AIBD-0042-source-0007" ] }, { "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/", "contribution": "The developer identifies the January 2020 discovery system as the Benevolent Platform.", "locator": "Operational highlights, baricitinib bullet.", "relationship": "Developer’s retrospective identification, not independent verification of clinical benefit.", "source_refs": [ "AIBD-0042-source-0008" ], "display_name": "BenevolentAI" }, { "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "contribution": "BenevolentAI’s London headquarters during the 2020 work.", "locator": "About BenevolentAI, final paragraph: London headquarters.", "relationship": "Original developer statement. Its clinical claims are not counted as additional verification of the trials.", "source_refs": [ "AIBD-0042-source-0009" ], "display_name": "BenevolentAI" }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8487786/", "source_refs": [ "AIBD-0042-source-0010" ], "display_name": "Clinical Therapeutics", "contribution": "A Lilly-funded model of U.S. treatment costs. Its hospital saving depends on the scenario and does not measure savings attributable to AI.", "locator": "Tables IV–V; supplemental table S6; Participants and Methods; Conflicts of Interest.", "relationship": "Economic study funded by Eli Lilly, with company-employed coauthors. Trial inputs and cost assumptions are modeled, not another clinical experiment." } ], "claim_chains": [ { "claim": "Mortality and failure of the primary endpoint", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "Supplementary appendix 6: Statistical analysis, pp. 9–10; Select secondary outcomes, pp. 11–12; Figure S2, p. 14" ], "finding": "The failure of the primary endpoint left no alpha for confirmatory testing of key secondary endpoints. The mortality p-value is nominal." }, { "claim": "Recovery time", "path": [ "https://europepmc.org/article/PMC/PMC7745180", "Table 2; supplementary appendix and original/final protocols" ], "finding": "ACTT-2 compared baricitinib plus remdesivir with placebo plus remdesivir. Its mortality comparison was not statistically conclusive." }, { "claim": "AI contribution", "path": [ "https://europepmc.org/article/PMC/PMC7137985", "Figure and original reference 6: Sorrell et al., Structure 24 (2016):401–411, doi:10.1016/j.str.2015.12.015", "https://pmc.ncbi.nlm.nih.gov/articles/PMC4780864/" ], "finding": "The correspondence is the origin of the AI-assisted prioritization claim. Sorrell et al. (2016), Figure 3B and the ligand-interaction results, supply original laboratory evidence of baricitinib binding to AAK1. That biochemical result does not establish the proposed antiviral mechanism or the clinical contribution of the AI discovery process." }, { "claim": "Regulatory follow-up", "path": [ "https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19", "https://www.fda.gov/media/143822/download", "https://www.who.int/news/item/14-01-2022-who-recommends-two-new-drugs-to-treat-covid-19", "https://iris.who.int/bitstream/handle/10665/351006/WHO-2019-nCoV-therapeutics-2022.1-eng.pdf" ], "finding": "The current FDA letter is a later reissuance with authorization history. The original WHO January 2022 PDF was identified but returned 403; the dated WHO announcement was read." }, { "claim": "System identity", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-unaudited-preliminary-results-year-ended-31-december-2022/" ], "finding": "Benevolent Platform, using its machine-learning-built knowledge graph and AAK1 inhibitor screening" }, { "claim": "Underlying workflow and named component", "path": [ "https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2021.709856/full" ], "finding": "The authors name SVO as a component and describe a workflow that combined computational analysis with expert selection. They do not establish an exact model release." }, { "claim": "Developer jurisdiction and geographic scope", "path": [ "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentais-platform-derived-hypothesis-covid-19-treatment-validated-us-niaid-randomised-control-trial/", "https://pmc.ncbi.nlm.nih.gov/articles/PMC8409066/", "https://europepmc.org/article/PMC/PMC7745180", "https://europepmc.org/article/PMC/PMC7137985" ], "finding": "The original correspondence and company statement identify London, United Kingdom, as the discovery team’s base. COV-BARRIER and ACTT-2 together cover 14 countries, with Puerto Rico included under the United States. These are trial settings, not separately demonstrated benefits in every country. The AI operator is BenevolentAI’s research team; clinical trial investigators evaluated the drug. Specific cross-border relationships are assessed separately." }, { "claim": "Further clinical confirmation", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC9333998/", "Table 2 and Figure 3" ], "finding": "RECOVERY tested baricitinib against usual care. It did not replicate the AI discovery process." }, { "claim": "Economic estimates", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC8487786/", "Tables IV–V", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx", "Supplemental table S6" ], "finding": "The model projects payer costs and hospital net costs. It does not measure cash savings or isolate an AI contribution." }, { "claim": "Historical ownership and control", "path": [ "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "p. 43, note 22", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0" ], "finding": "The accounts identify Kenneth Mulvany as the controller at year-end 2019. A separate AIBD calculation describes his voting-share fraction in the October register." }, { "claim": "Cross-border company funding", "path": [ "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek" ], "finding": "The company and its counsel report investment from Singapore-headquartered Temasek. The amount is company-wide and is not a measured benefit or research budget." }, { "claim": "Cross-border scientific resources", "path": [ "AIBD-0042-source-0004", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949" ], "finding": "Named resource use is documented. The country-to-country description is an AIBD inference from the resource producers and the discovery team." }, { "claim": "AIBD monetary scenarios", "path": [ "AIBD-0042-source-0010", "Tables IV–V", "https://ars.els-cdn.com/content/image/1-s2.0-S0149291821003891-mmc1.docx", "Supplemental table S6" ], "finding": "The return/payback assessment derives net monetary benefit and a full-course cost reference ratio from published inputs. Neither is an observed cash return or an AI-specific return." } ], "limitations": [ "No trial randomized the discovery process to AI versus no AI. The full proprietary graph and ranking run are unavailable.", "COV-BARRIER was sponsor-designed and sponsor-analyzed. Its mortality inference is nominal under the prespecified testing hierarchy.", "The cited recommendation establishes guidance, not measured worldwide adoption or a count of lives saved.", "The original Sorrell et al. article was read. Its linked supplementary Table S1 was identified, but the download returned 403 or a verification page and the supplementary archive timed out; no unavailable table contents were inferred.", "The authors’ measured recovery times do not establish realized hospital staffing or cash savings.", "The FDA source is a news release about an authorization, not a finding about AI effectiveness." ], "excluded_or_consolidated_sources": [ { "url": "https://www.fda.gov/drugs/emergency-preparedness-drugs/coronavirus-covid-19-drugs", "reason": "Generic, changing drug directory; no additional claim in the current case requires it." }, { "url": "https://incidentdatabase.ai/cite/225", "reason": "IBM Watson for Oncology is a different system and a different clinical use. Its incident does not document a harm in this baricitinib discovery or treatment episode." } ], "review_scope": "Reviewed all required fields for this discovery episode. The ten main works establish discovery, clinical effects, institutional decisions, and modeled treatment costs. Additional corporate filings, transaction accounts, and resource histories support ownership and geographic assessment. AIBD calculations and interpretations are labeled separately from reported findings.", "homepage_source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0003" ], "metadata_sources": [ { "url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "citation": "BenevolentAI Limited. Annual Report and Consolidated Financial Statements, 31 December 2019. Filed December 30, 2020.", "locator": "p. 43, note 22; p. 40, note 18.", "date": "2019-12-31", "contribution": "Historical company control and share-class rights immediately before the January 2020 research.", "relationship": "Original statutory company filing. The control statement is from the company’s accounts, not an inference from later ownership.", "access_note": "Original scanned filing inspected, including a visual check of note 22." }, { "url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "citation": "BenevolentAI Limited. Confirmation Statement CS01, October 15, 2019.", "locator": "Share capital, p. 2; shareholder details, pp. 4–6 (unnumbered leaves).", "date": "2019-10-15", "contribution": "The historical voting-share counts used for the labeled AIBD calculation.", "relationship": "Original company filing, with the ordinary and preferred share rights stated explicitly.", "access_note": "Original scanned statement and relevant shareholder pages inspected." }, { "url": "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "citation": "BenevolentAI Limited. Return of Allotment SH01, December 20, 2019. Filed January 8, 2020.", "locator": "pp. 2–3.", "date": "2019-12-20", "contribution": "A capital check showing that the new G2 growth shares did not carry ordinary voting rights before an exit.", "relationship": "Original company filing. This checks share-class rights, not changes in every beneficial owner.", "access_note": "Original scanned return and share-rights pages inspected." }, { "url": "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "citation": "Covington & Burling LLP. “Covington Advises BenevolentAI on $90M Investment from Temasek.” October 15, 2019.", "locator": "¶¶ 1–3.", "date": "2019-10-15", "contribution": "A participant’s confirmation of Singaporean investment in the developer.", "relationship": "The law firm advised BenevolentAI on the transaction. It is a firsthand participant, not an independent financial evaluator.", "access_note": "Original counsel announcement inspected." }, { "url": "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "citation": "BenevolentAI. “BenevolentAI Announces $90 Million Investment from Temasek.” September 17, 2019.", "locator": "Opening paragraph; funding-purpose paragraph; About BenevolentAI.", "date": "2019-09-17", "contribution": "The original funding announcement, its date, and the intended company-wide uses of the capital.", "relationship": "The recipient’s own announcement. It does not allocate funding to the later baricitinib work.", "access_note": "Original developer announcement inspected." }, { "url": "https://www.genome.jp/kegg/kegg1.html", "citation": "Kanehisa Laboratories. “KEGG Database.”", "locator": "KEGG overview and project history.", "contribution": "The Japanese origin of a biomedical resource that the discovery researchers used.", "relationship": "Resource developers’ account of its history. Geographic reuse is inferred by combining it with the baricitinib methods paper.", "access_note": "Original resource overview inspected." }, { "url": "https://doi.org/10.1093/nar/gkz949", "citation": "Luana Licata et al. “SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 Update.” Nucleic Acids Research 48, no. D1 (2020): D504–D510. https://doi.org/10.1093/nar/gkz949.", "locator": "Author affiliations; database access and download description.", "date": "2019-10-29", "contribution": "An Italy-led resource, with U.K. collaborators, that the discovery researchers reused.", "relationship": "Original resource paper. It establishes its producers and access conditions, not server or patient-data routes.", "access_note": "Original resource paper inspected." }, { "url": "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf", "citation": "Temasek Holdings. Temasek Overview 2019.", "locator": "p. 38, “Relating to Our Shareholder.”", "date": "2019", "contribution": "The investor’s government ownership and its stated separation from portfolio-company business decisions.", "relationship": "The investor’s own institutional account. It does not establish government control of BenevolentAI or the research.", "access_note": "Original report downloaded and read after browser access failed." } ], "interpretation_boundary": "Reported findings, direct calculations, and AIBD inferences are distinguished in the affected fields. A completed assessment does not imply that the exact proprietary model or a causal AI contribution is known." } }, "provenance": { "kind": "source_review", "basis": "Traced clinical, discovery, policy, economic, corporate, and geographic statements to their separate origins. Recorded the basis of derived calculations and interpretations.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0002", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0009", "AIBD-0042-source-0010", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI0NjgzNDI0M2FkaXF6a2N4/document?format=pdf&download=0", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI1NDE0MDc3M2FkaXF6a2N4/document?format=pdf&download=0", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949", "https://tr19.temasekreview.com.sg/downloads/Temasek-Review-2019-Overview.pdf" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The FDA and WHO based their conclusions on clinical trials. BenevolentAI’s announcements repeat its discovery account and the trial results." } }, "strategic_assessments[]": { "state": "value_present", "value": { "kind": "structured", "data": { "assessments": [ { "id": "AIBD-0042-strategic-uk-preparedness", "assessment_type": "AIBD qualitative inference", "assessed_on": "2026-10-25", "perspective": "United Kingdom public health preparedness and biomedical research capacity", "domain": "Pandemic preparedness", "reported_status": "The sources document the research network and treatment results. They do not quantify a change in national capability or an advantage attributable to AI.", "documented_basis": "A U.K. discovery team used international biomedical resources after Singaporean investment in the company. Researchers subsequently tested the drug in U.S.-led, multinational, and U.K. trials.", "aibd_inference": "This sequence illustrates a route from existing medicines to clinical tests during a new disease outbreak. Its value for U.K. preparedness depends on access to international knowledge, expert pharmacology, trial capacity, and medicines.", "capability_change": "The researchers produced a testable treatment hypothesis and the trials established a clinical benefit. The record does not identify how much sooner the hypothesis emerged because of AI.", "operational_dependency": "The published trial protocols administer a medicine without using BenevolentAI’s discovery software. AIBD therefore infers that continuing access to that software was not necessary for the treatment regimen that the trials evaluated.", "confidence": "Moderate for this qualitative assessment. No numerical national advantage, time saving, or strategic score is assigned.", "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949" ] } ] } }, "provenance": { "kind": "derivation", "basis": "Prepared a named, dated strategic assessment from the documented institutions and protocols. Marked the capability interpretation as AIBD inference.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0005", "AIBD-0042-source-0001", "AIBD-0042-source-0002", "https://find-and-update.company-information.service.gov.uk/company/09781806/filing-history/MzI4NjgwMDAzNWFkaXF6a2N4/document?format=pdf&download=0", "https://www.benevolent.com/news-and-media/press-releases-and-in-media/benevolentai-announces-90-million-investment-temasek/", "https://www.cov.com/en/news-and-insights/news/2019/10/covington-advises-benevolentai-on-90m-investment-from-temasek", "https://www.genome.jp/kegg/kegg1.html", "https://doi.org/10.1093/nar/gkz949" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "This work may strengthen the United Kingdom’s ability to find treatments during a new outbreak.", "editor_note": "The inference rests on the U.K. team’s January 2020 proposal and the subsequent international trials (references 1–5). Those studies establish a useful treatment, but give no estimate of how much earlier AI made it available." } }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Researchers used the Benevolent Platform to identify baricitinib as a candidate treatment for COVID-19.", "account": "BenevolentAI researchers reported in February 2020 that their knowledge graph had helped them identify baricitinib, an arthritis drug, as a possible treatment for COVID-19. They proposed clinical testing after reviewing its effects on inflammation and proteins involved in viral entry. In ACTT-2, 1,033 hospitalized adults received remdesivir with either baricitinib or a placebo. Median recovery took 7 days with baricitinib and 8 days with the placebo.\n\nCOV-BARRIER enrolled 1,525 adults. By day 28, 8% of patients receiving baricitinib had died, compared with 13% receiving a placebo. Both groups received standard care. Mortality was a secondary outcome. The trial did not meet its primary outcome of reduced disease progression, so its mortality result was not conclusive under the planned procedure for multiple comparisons.\n\nThe subsequent RECOVERY trial enrolled 8,156 patients. Mortality, its primary outcome, was 12% with baricitinib and 14% with usual care alone." } }, "provenance": { "kind": "source_review", "basis": "Separated clinical results from the unmeasured additional contribution of AI.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used the Benevolent Platform to identify baricitinib as a candidate treatment for COVID-19." } }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "structured", "data": { "operating_mode": "Interactive analysis directed by scientists", "selection_authority": "Researchers chose the candidate drug and proposed clinical testing.", "clinical_authority": "No autonomous prescribing or treatment execution is described.", "technical_permissions": "API permissions, access controls, and escalation rules are not reported." } }, "provenance": { "kind": "source_review", "basis": "The documented workflow preserves candidate selection and clinical decisions with people.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Scientists directed the analysis and selected the drug. Clinicians controlled treatment." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "structured", "data": { "roles": [ "Extract biomedical relationships from literature", "Retrieve relationships from a knowledge graph", "Display and analyze protein networks" ], "human_decision": "Scientists selected baricitinib after pharmacological assessment." } }, "provenance": { "kind": "source_review", "basis": "Methods and Author Contributions distinguish automated analysis from scientist selection.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system extracted biomedical relationships, searched the graph, and analyzed networks of proteins." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "period": "January 2020", "workflow": "Coronavirus literature was added to the graph, followed by iterative queries and network analysis.", "unreported": [ "Hardware", "Hosting location", "Model checkpoint", "Exact application release", "Frozen graph snapshot", "Compute budget" ], "reported_status": "The exact model release and frozen graph snapshot are not reported.", "aibd_configuration_proxy": "BenevolentAI’s January 2020 coronavirus-augmented knowledge graph, combined with SVO relationship extraction, graph-pattern queries, and interactive protein-network analysis.", "proxy_basis": "Date and components are documented in the original methods paper. They identify a historical workflow, not an executable version or checkpoint.", "proxy_confidence": "High for the documented period and components; insufficient for exact computational reproduction.", "documented_components": { "relationship_extraction": "SVO extracts relationships from sentences using an unsupervised, rule-based approach.", "network_analysis": "Graph-pattern queries and an interactive protein-network tool with Louvain community detection.", "initial_network": { "proteins": 556, "interactions": 2286, "modules": 16 }, "human_review": "Researchers considered target affinity, free plasma concentration, pharmacokinetics, and dose when selecting baricitinib." } } }, "provenance": { "kind": "source_review", "basis": "Recorded a historically documented configuration proxy while leaving the exact model-version field unreported.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers added relationships from coronavirus papers to the knowledge graph. They used the Louvain algorithm to group connected proteins and examined the networks with interactive tools." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "structured", "data": { "inputs": [ "Biomedical databases", "Scientific literature about coronaviruses, proteins, pathways, and drugs" ], "outputs": [ "Relationships among biological entities", "Protein interaction networks", "Candidate drugs for expert review" ], "language": "English-language search examples are documented; the full language coverage of the corpus is not reported.", "patient_data": "The discovery workflow describes biomedical literature and databases, not individual trial-patient records." } }, "provenance": { "kind": "source_review", "basis": "Read Materials and Methods and Results in the original methods paper.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system drew from biomedical literature and databases to produce relationships and protein networks that researchers used to assess candidate drugs." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "structured", "data": { "named_component": "SVO", "role": "Rule-based extraction of sentence-level relationships", "other_methods": [ "Graph pattern queries", "Louvain community detection", "Protein interaction network analysis" ], "single_model": "No single model represents the entire workflow." } }, "provenance": { "kind": "source_review", "basis": "The methods paper names the component and algorithms.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "SVO, a rule-based model that extracts relationships from sentences." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The original methods paper does not identify an exact model release, checkpoint, or frozen January 2020 graph snapshot.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "reason": "The original methods paper does not identify an exact model release, checkpoint, or frozen January 2020 graph snapshot.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The configuration used in January 2020.", "editor_note": "Smith and colleagues describe the January 2020 work but give no release identifier for SVO (reference 4, p. 4)." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Benevolent Platform" } }, "provenance": { "kind": "source_review", "basis": "The original workflow is identified retrospectively as the Benevolent Platform. This is a product name, not a model release.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0008", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Benevolent Platform" } }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "BenevolentAI", "application_operator": "BenevolentAI research team", "named_component_provider": "BenevolentAI" } }, "provenance": { "kind": "source_review", "basis": "The authors describe their own application and research workflow.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0003", "AIBD-0042-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "BenevolentAI" } }, "taxonomy_crosswalks[]": { "state": "value_present", "value": { "kind": "structured", "data": { "mapping": [ { "taxonomy": "Trustible AI Benefits Framework", "version": "May 1, 2024; AIBD local taxonomy snapshot", "category": "Improved Physical Health", "relationship": "Exact category assignment", "rationale": "Lower mortality and faster recovery concern patients’ physical health." } ], "other_taxonomies": "No crosswalk to an incident or risk taxonomy is asserted." } }, "provenance": { "kind": "curatorial", "basis": "Applied the existing local benefit taxonomy, independently of the depth scale.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The benefit matches Trustible’s “Improved Physical Health” category, published on 1 May 2024." } }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Baricitinib, identified with BenevolentAI, reduced COVID-19 deaths in trials", "headline": "An arthritis drug helped patients with severe COVID-19" } }, "provenance": { "kind": "source_review", "basis": "The title describes the drug benefit and identifies the discovery relationship.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0003", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An arthritis drug helped patients with severe COVID-19" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a8e1b0052ad9c7eff39b20f5389ce8ba29abb827c2271690fcac5264ab7db26f" ], "role": "SHA-256 of normalized case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed after integrating the sourced metadata and labeled estimates.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0006", "AIBD-0042-source-0007", "AIBD-0042-source-0008", "AIBD-0042-source-0004", "AIBD-0042-source-0009", "AIBD-0042-source-0002", "AIBD-0042-source-0010" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Revision a8e1b005, reviewed on 25 October 2026." } }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "BenevolentAI scientists added coronavirus literature to their graph, queried it, examined protein networks, and assessed candidate drugs. Clinical investigators subsequently tested baricitinib in separate trials." }, "provenance": { "kind": "source_review", "basis": "Read the discovery workflow and trial oversight sections.", "record_fields": [], "source_refs": [ "AIBD-0042-source-0001", "AIBD-0042-source-0005", "AIBD-0042-source-0003", "AIBD-0042-source-0004", "AIBD-0042-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Scientists searched the graph, examined protein networks, and assessed medicines. Clinical investigators then tested baricitinib." } } }, "summary": { "total": 91, "addressed": 91, "known": 90, "reviewed": 91, "record_mapped": 0, "not_assessed": 0, "complete": true, "by_state": { "value_present": 90, "not_reported": 1, "unresolved": 0, "not_assessed": 0, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0354", "title": "UN OCHA's CERF anticipatory action framework for Philippine typhoons adopted 510's machine-learning impact model as trigger in 2021; no activation on that trigger documented to 2025", "summary": "OCHA frameworks (2021, 2023, 2025) use 510's XGBoost house-damage model as activation trigger; near-activation Dec 2021 (Rai); the Nov 2025 activation for Uwan ran on the 185 km/h wind trigger.", "date_observed": "2021-09-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "OCHA's Anticipatory Action (AA) Framework for Philippine typhoons was posted on ReliefWeb on 15 September 2021. It set up a US$7.5 million CERF pilot for about 270,500 people in Regions 5 and 8 with FAO, IOM, UNFPA, UNICEF and WFP. It has a two-stage trigger. The readiness trigger is PAGASA and 510 forecasts of a category 4 or stronger cyclone. The activation trigger, within 72 hours of landfall, is the IFRC/Netherlands Red Cross 510 probabilistic typhoon impact prediction model's predicted number of totally damaged houses. The framework says that model partially uses a machine learning model relating wind speed to housing damage. 510's 2024 NHESS paper (vendor-authored) states the XGBoost model served in 2021 as the trigger model for the UN OCHA AA pilot. OCHA's After Action Review of 31 March 2022 records that Typhoon Rai (Odette) in December 2021 rapidly intensified and did not meet the activation criteria. There was a near activation with staff pre-deployed. The 2023 revision retained the 510 model. The framework endorsed on 19 October 2025 covers US$6 million CERF and about 955,507 people in Regions 5, 8 and 13. OCHA and its Centre for Humanitarian Data compute predicted totally damaged buildings with the 510 model every 6–12 hours. It adds an observational trigger for super typhoons of 185 km/h or more reported by PAGASA. OCHA's June 2025 report says the readiness trigger was met for Super Typhoon Pepito (Man-yi) in its November 2024 to April 2025 reporting period. Activation thresholds were not reached and CERF AA resources were reallocated to the response. On 6 November 2025 CERF AA was activated for Super Typhoon Fung-Wong (Uwan) after the observational wind-speed threshold was triggered. OCHA reports nearly US$6 million released and WFP alone reaching 42,100 families. No cited document records an activation produced by the 510 model's output.", "category": "general benefit", "unexpected": false, "purpose": "Forecast the number of totally damaged houses from typhoon track, wind and rainfall forecasts so that CERF-funded early actions can be triggered before landfall. The benefit claimed (AI-triggered anticipatory payouts) is that purpose, but no activation on the model's output is documented.", "system": "510 probabilistic typhoon impact model (XGBoost) predicting totally damaged houses, used as the CERF anticipatory action activation trigger", "model_version": "probabilistic version using ECMWF ensemble tracks (revamped from deterministic, 2021)", "developer": "510, an initiative of the Netherlands Red Cross, with IFRC", "deployer": "UN OCHA Philippines with the CERF AA Core Group (FAO, IOM, UNFPA, UNICEF, WFP); impact estimates generated by 510 (2021 framework) and by OCHA with its Centre for Humanitarian Data (2025 framework)", "location": "Philippines (Regions 5, 8 and 13)", "domain": "Humanitarian anticipatory action / typhoon impact forecasting", "segment": "UN-coordinated anticipatory financing (CERF)", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The model supplies impact estimates that decide whether anticipatory funds are released, and no activation attributable to it is documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No activation attributable to the model's output is documented, so no individual-level outcome can be assigned to the AI." }, { "group": "organizational", "depth": null, "reason": "OCHA adopted the model as its trigger and computes estimates each cycle. The only documented activation (6 November 2025) was triggered by the observational wind-speed threshold." }, { "group": "societal", "depth": null, "reason": "Pre-landfall assistance in November 2025 (WFP reports 42,100 families) is documented, but not attributed to the AI model by any cited source." } ], "ai_role": { "status": "assessed", "statement": "OCHA's 2021, 2023 and 2025 frameworks name the IFRC/510 impact model as the activation-trigger model. The 2021 framework describes it as partially a machine learning model. This is documented by the deployer, not only the maker. The model's forecasts were monitored during the December 2021 near activation (Typhoon Rai) without meeting criteria. The 2024 readiness phase for Pepito ended with CERF AA resources reallocated to response. OCHA's flash update attributes the 6 November 2025 activation for Uwan to the observational threshold (forecast peak 195 km/h against the 185 km/h trigger). It does not state that the 510 model's estimates reached the activation matrix. The AI's contribution to any payout is therefore not established. The maker's NHESS paper is the only source describing the algorithm (XGBoost)." }, "evidence": [ { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022. ReliefWeb, posted 15 September 2021 (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-2021-2022", "date": "2021-09-15", "written_by": "deployer", "quote": "The Model includes a trigger mechanism based on the ECMWF forecast and IFRC/ Netherlands Red Cross 510 probabilistic typhoon impact prediction model developed for the Philippines" }, { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022, model checklist and model selection sections (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022 (model selection)", "url": "https://reliefweb.int/attachments/78d0268e-b476-3a55-ab82-94e7478fc408/Anticipatory%20Action%20Framework%20-%20Philippines%20-%20Typhoons%20-%202021-2022.pdf", "date": "2021-09-15", "written_by": "deployer", "quote": "Partially: Uses a machine learning model to determine relationship between wind speed and housing damage." }, { "kind": "report", "citation": "OCHA Philippines (2022). Report on the After Action Review for CERF Anticipatory Action, 31 March 2022. ReliefWeb (PDF dated 22 April 2022).", "title": "After Action Review on the CERF Anticipatory Action for Typhoons", "url": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons", "date": "2022-03-31", "written_by": "deployer", "quote": "While the typhoon at the end did not meet the AA pilot activation criteria, the CERF AA Core Group was closely monitoring the situation" }, { "kind": "report", "citation": "OCHA (2023). Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision. unocha.org, 3 October 2023 (PDF).", "title": "Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision", "url": "https://www.unocha.org/publications/report/philippines/philippines-cerf-aa-anticipatory-action-framework-2023-revision", "date": "2023-10-03", "written_by": "deployer", "quote": "Tropical Cyclone with potential to reach category level 3 or higher" }, { "kind": "report", "citation": "OCHA (2025). Anticipatory Action Framework Philippines - Tropical Cyclones (as of 03 October 2025, endorsed 19 October 2025). ReliefWeb, posted 4 November 2025 (PDF).", "title": "Anticipatory Action Framework Philippines - Tropical Cyclones (As of 03 October 2025)", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-tropical-cyclones-03-october-2025", "date": "2025-10-19", "written_by": "deployer", "quote": "This will be used to compare against 510 model outputs at 72 hours before landfall, in order to account for varying regional vulnerabilities." }, { "kind": "report", "citation": "OCHA (2025). Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1 (as of 07 November, 9 p.m. local time). ReliefWeb.", "title": "Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1", "url": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "date": "2025-11-07", "written_by": "deployer", "quote": "CERF Anticipatory Action (AA) was activated on 06 November after the observational threshold for Tropical Cyclone Fung-won (Uwan) was triggered" }, { "kind": "press release", "citation": "Paulose, H. (2026). How anticipatory action shaped the response to the Philippines' Twin Typhoons. OCHA Financing and Outreach Division, un.org, January 2026.", "title": "How anticipatory action shaped the response to the Philippines' Twin Typhoons", "url": "https://www.un.org/en/delegate/how-anticipatory-action-shaped-response-philippines%E2%80%99-twin-typhoons", "date": "2026-01-19", "written_by": "deployer", "quote": "WFP alone reached 42,100 families through its anticipatory financing mechanism" }, { "kind": "report", "citation": "OCHA (2025). Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report (November 2024 - April 2025). unocha.org, 27 June 2025.", "title": "Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report", "url": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025", "date": "2025-06-27", "written_by": "deployer", "quote": "CERF AA resources were reallocated to support the emergency response following Super Typhoon Pepito (Man-yi)" }, { "kind": "peer-reviewed study", "citation": "Kooshki Forooshani, M., van den Homberg, M., Kalimeri, K., Kaltenbrunner, A., Mejova, Y., Milano, L., et al. (2024). Towards a global impact-based forecasting model for tropical cyclones. Natural Hazards and Earth System Sciences 24, 309-329, 1 February 2024.", "title": "Towards a global impact-based forecasting model for tropical cyclones", "url": "https://nhess.copernicus.org/articles/24/309/2024/", "date": "2024-02-01", "written_by": "makers", "quote": "in 2021 as the trigger model for the UN OCHA AA pilot" } ], "replication": { "produced_by": [ "A pre-arranged CERF allocation with agency action plans ready before the typhoon season", "ECMWF ensemble track, wind and rainfall forecasts fed to the 510 impact model every 6–12 hours", "Historical house-damage data linking hazard, vulnerability and exposure to train the model", "A threshold matrix of predicted totally damaged houses per region with a 1-in-3.5-year return period (2025)" ], "must_hold": [ "Forecast lead time of at least 72 hours; rapid intensification (Rai 2021) shortened lead time below the trigger window", "Model impact estimates reaching the regional threshold matrix, which no read activation record documents", "Agency delivery capacity (financial service providers, data-sharing agreements) in the 72 hours before landfall", "PAGASA and ECMWF data availability" ], "echoes": [ { "date": null, "setting": "Typhoon Rai (Odette), December 2021: forecasts monitored, activation criteria not met, staff pre-deployed (near activation)", "model_version": "2021 probabilistic version", "outcome": "did not recur", "source": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons" }, { "date": null, "setting": "Super Typhoon Pepito (Man-yi), within OCHA's November 2024 to April 2025 reporting period: readiness trigger met, activation thresholds not reached, CERF AA resources reallocated to emergency response", "model_version": null, "outcome": "did not recur", "source": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025" }, { "date": "2025-11-06", "setting": "Super Typhoon Fung-Wong (Uwan): CERF AA activated on the observational 185 km/h threshold; nearly US$6 million released; WFP reports 42,100 families reached; AI model's role not stated", "model_version": null, "outcome": "unknown", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" } ] }, "paired_incident": null, "headline": "OCHA uses 510's model as CERF trigger; no activation documented", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2025-11-06", "note": "The framework stayed in force and CERF anticipatory action was activated for Super Typhoon Fung-Wong (Uwan) on 6 November 2025 with nearly US$6 million, but on the observational 185 km/h wind threshold rather than on the 510 model's output.", "quote": "The CERF Anticipatory Action (AA) was activated on 06 November after the observational threshold for Tropical Cyclone Fung-won (Uwan) was triggered. Nearly US$6 million has been allocated to five United Nations agencies to implement AA and early response efforts.", "url": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" }, "value": null, "developer_country": "Netherlands", "deployer_country": "Philippines", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.rodekruis.nl/contact/; https://www.unocha.org/philippines", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, seven reports from the deployer and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0354", "catalog_version": "1.0.0", "source_fingerprint": "fb2e5c80103070fb65e02114473a292ff7832a3193b97eaae26cfce2e51f4adb", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0354-source-0001", "AIBD-0354-source-0002", "AIBD-0354-source-0003", "AIBD-0354-source-0004", "AIBD-0354-source-0005", "AIBD-0354-source-0006", "AIBD-0354-source-0007", "AIBD-0354-source-0008", "AIBD-0354-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "510, an initiative of the Netherlands Red Cross, with IFRC", "deployer": "UN OCHA Philippines with the CERF AA Core Group (FAO, IOM, UNFPA, UNICEF, WFP); impact estimates generated by 510 (2021 framework) and by OCHA with its Centre for Humanitarian Data (2025 framework)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "OCHA's 2021, 2023 and 2025 frameworks name the IFRC/510 impact model as the activation-trigger model. The 2021 framework describes it as partially a machine learning model. This is documented by the deployer, not only the maker. The model's forecasts were monitored during the December 2021 near activation (Typhoon Rai) without meeting criteria. The 2024 readiness phase for Pepito ended with CERF AA resources reallocated to response. OCHA's flash update attributes the 6 November 2025 activation for Uwan to the observational threshold (forecast peak 195 km/h against the 185 km/h trigger). It does not state that the 510 model's estimates reached the activation matrix. The AI's contribution to any payout is therefore not established. The maker's NHESS paper is the only source describing the algorithm (XGBoost)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "OCHA’s frameworks included the 510 model’s forecasts of damage to housing among the conditions for early action before a typhoon.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "OCHA's 2021, 2023 and 2025 frameworks name the IFRC/510 impact model as the activation-trigger model. The 2021 framework describes it as partially a machine learning model. This is documented by the deployer, not only the maker. The model's forecasts were monitored during the December 2021 near activation (Typhoon Rai) without meeting criteria. The 2024 readiness phase for Pepito ended with CERF AA resources reallocated to response. OCHA's flash update attributes the 6 November 2025 activation for Uwan to the observational threshold (forecast peak 195 km/h against the 185 km/h trigger). It does not state that the 510 model's estimates reached the activation matrix. The AI's contribution to any payout is therefore not established. 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The only documented activation (6 November 2025) was triggered by the observational wind-speed threshold." }, { "group": "societal", "reason": "Pre-landfall assistance in November 2025 (WFP reports 42,100 families) is documented, but not attributed to the AI model by any cited source." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No activation attributable to the model's output is documented, so no individual-level outcome can be assigned to the AI." }, { "group": "organizational", "reason": "OCHA adopted the model as its trigger and computes estimates each cycle. The only documented activation (6 November 2025) was triggered by the observational wind-speed threshold." }, { "group": "societal", "reason": "Pre-landfall assistance in November 2025 (WFP reports 42,100 families) is documented, but not attributed to the AI model by any cited source." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": 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"not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The available accounts do not establish that the model triggered a payment. OCHA attributed the November 2025 activation for Typhoon Uwan to a wind-speed threshold, without saying that the model’s damage estimates met the activation criteria.", "editor_note": "" } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-11-06", "note": "The framework stayed in force and CERF anticipatory action was activated for Super Typhoon Fung-Wong (Uwan) on 6 November 2025 with nearly US$6 million, but on the observational 185 km/h wind threshold rather than on the 510 model's output.", "quote": "The CERF Anticipatory Action (AA) was activated on 06 November after the observational threshold for Tropical Cyclone Fung-won (Uwan) was triggered. Nearly US$6 million has been allocated to five United Nations agencies to implement AA and early response efforts.", "url": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0354" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The model supplies impact estimates that decide whether anticipatory funds are released, and no activation attributable to it is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "OCHA's Anticipatory Action (AA) Framework for Philippine typhoons was posted on ReliefWeb on 15 September 2021. It set up a US$7.5 million CERF pilot for about 270,500 people in Regions 5 and 8 with FAO, IOM, UNFPA, UNICEF and WFP. It has a two-stage trigger. The readiness trigger is PAGASA and 510 forecasts of a category 4 or stronger cyclone. The activation trigger, within 72 hours of landfall, is the IFRC/Netherlands Red Cross 510 probabilistic typhoon impact prediction model's predicted number of totally damaged houses. The framework says that model partially uses a machine learning model relating wind speed to housing damage. 510's 2024 NHESS paper (vendor-authored) states the XGBoost model served in 2021 as the trigger model for the UN OCHA AA pilot. OCHA's After Action Review of 31 March 2022 records that Typhoon Rai (Odette) in December 2021 rapidly intensified and did not meet the activation criteria. There was a near activation with staff pre-deployed. The 2023 revision retained the 510 model. The framework endorsed on 19 October 2025 covers US$6 million CERF and about 955,507 people in Regions 5, 8 and 13. OCHA and its Centre for Humanitarian Data compute predicted totally damaged buildings with the 510 model every 6–12 hours. It adds an observational trigger for super typhoons of 185 km/h or more reported by PAGASA. OCHA's June 2025 report says the readiness trigger was met for Super Typhoon Pepito (Man-yi) in its November 2024 to April 2025 reporting period. Activation thresholds were not reached and CERF AA resources were reallocated to the response. On 6 November 2025 CERF AA was activated for Super Typhoon Fung-Wong (Uwan) after the observational wind-speed threshold was triggered. OCHA reports nearly US$6 million released and WFP alone reaching 42,100 families. No cited document records an activation produced by the 510 model's output.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No activation attributable to the model's output is documented, so no individual-level outcome can be assigned to the AI." }, { "group": "organizational", "reason": "OCHA adopted the model as its trigger and computes estimates each cycle. The only documented activation (6 November 2025) was triggered by the observational wind-speed threshold." }, { "group": "societal", "reason": "Pre-landfall assistance in November 2025 (WFP reports 42,100 families) is documented, but not attributed to the AI model by any cited source." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Forecast the number of totally damaged houses from typhoon track, wind and rainfall forecasts so that CERF-funded early actions can be triggered before landfall. The benefit claimed (AI-triggered anticipatory payouts) is that purpose, but no activation on the model's output is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Philippines (Regions 5, 8 and 13)", "developer_country": "Netherlands", "deployer_country": "Philippines" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Forecast the number of totally damaged houses from typhoon track, wind and rainfall forecasts so that CERF-funded early actions can be triggered before landfall. The benefit claimed (AI-triggered anticipatory payouts) is that purpose, but no activation on the model's output is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-09-15", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.rodekruis.nl/contact/; https://www.unocha.org/philippines", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A pre-arranged CERF allocation with agency action plans ready before the typhoon season", "ECMWF ensemble track, wind and rainfall forecasts fed to the 510 impact model every 6–12 hours", "Historical house-damage data linking hazard, vulnerability and exposure to train the model", "A threshold matrix of predicted totally damaged houses per region with a 1-in-3.5-year return period (2025)" ], "must_hold": [ "Forecast lead time of at least 72 hours; rapid intensification (Rai 2021) shortened lead time below the trigger window", "Model impact estimates reaching the regional threshold matrix, which no read activation record documents", "Agency delivery capacity (financial service providers, data-sharing agreements) in the 72 hours before landfall", "PAGASA and ECMWF data availability" ], "echoes": [ { "setting": "Typhoon Rai (Odette), December 2021: forecasts monitored, activation criteria not met, staff pre-deployed (near activation)", "model_version": "2021 probabilistic version", "outcome": "did not recur", "source": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons" }, { "setting": "Super Typhoon Pepito (Man-yi), within OCHA's November 2024 to April 2025 reporting period: readiness trigger met, activation thresholds not reached, CERF AA resources reallocated to emergency response", "outcome": "did not recur", "source": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025" }, { "date": "2025-11-06", "setting": "Super Typhoon Fung-Wong (Uwan): CERF AA activated on the observational 185 km/h threshold; nearly US$6 million released; WFP reports 42,100 families reached; AI model's role not stated", "outcome": "unknown", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A pre-arranged CERF allocation with agency action plans ready before the typhoon season", "ECMWF ensemble track, wind and rainfall forecasts fed to the 510 impact model every 6–12 hours", "Historical house-damage data linking hazard, vulnerability and exposure to train the model", "A threshold matrix of predicted totally damaged houses per region with a 1-in-3.5-year return period (2025)" ], "must_hold": [ "Forecast lead time of at least 72 hours; rapid intensification (Rai 2021) shortened lead time below the trigger window", "Model impact estimates reaching the regional threshold matrix, which no read activation record documents", "Agency delivery capacity (financial service providers, data-sharing agreements) in the 72 hours before landfall", "PAGASA and ECMWF data availability" ], "echoes": [ { "setting": "Typhoon Rai (Odette), December 2021: forecasts monitored, activation criteria not met, staff pre-deployed (near activation)", "model_version": "2021 probabilistic version", "outcome": "did not recur", "source": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons" }, { "setting": "Super Typhoon Pepito (Man-yi), within OCHA's November 2024 to April 2025 reporting period: readiness trigger met, activation thresholds not reached, CERF AA resources reallocated to emergency response", "outcome": "did not recur", "source": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025" }, { "date": "2025-11-06", "setting": "Super Typhoon Fung-Wong (Uwan): CERF AA activated on the observational 185 km/h threshold; nearly US$6 million released; WFP reports 42,100 families reached; AI model's role not stated", "outcome": "unknown", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.rodekruis.nl/contact/; https://www.unocha.org/philippines", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Humanitarian anticipatory action / typhoon impact forecasting", "segment": "UN-coordinated anticipatory financing (CERF)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022. ReliefWeb, posted 15 September 2021 (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-2021-2022", "date": "2021-09-15", "written_by": "deployer", "quote": "The Model includes a trigger mechanism based on the ECMWF forecast and IFRC/ Netherlands Red Cross 510 probabilistic typhoon impact prediction model developed for the Philippines" }, { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022, model checklist and model selection sections (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022 (model selection)", "url": "https://reliefweb.int/attachments/78d0268e-b476-3a55-ab82-94e7478fc408/Anticipatory%20Action%20Framework%20-%20Philippines%20-%20Typhoons%20-%202021-2022.pdf", "date": "2021-09-15", "written_by": "deployer", "quote": "Partially: Uses a machine learning model to determine relationship between wind speed and housing damage." }, { "kind": "report", "citation": "OCHA Philippines (2022). Report on the After Action Review for CERF Anticipatory Action, 31 March 2022. ReliefWeb (PDF dated 22 April 2022).", "title": "After Action Review on the CERF Anticipatory Action for Typhoons", "url": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons", "date": "2022-03-31", "written_by": "deployer", "quote": "While the typhoon at the end did not meet the AA pilot activation criteria, the CERF AA Core Group was closely monitoring the situation" }, { "kind": "report", "citation": "OCHA (2023). Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision. unocha.org, 3 October 2023 (PDF).", "title": "Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision", "url": "https://www.unocha.org/publications/report/philippines/philippines-cerf-aa-anticipatory-action-framework-2023-revision", "date": "2023-10-03", "written_by": "deployer", "quote": "Tropical Cyclone with potential to reach category level 3 or higher" }, { "kind": "report", "citation": "OCHA (2025). Anticipatory Action Framework Philippines - Tropical Cyclones (as of 03 October 2025, endorsed 19 October 2025). ReliefWeb, posted 4 November 2025 (PDF).", "title": "Anticipatory Action Framework Philippines - Tropical Cyclones (As of 03 October 2025)", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-tropical-cyclones-03-october-2025", "date": "2025-10-19", "written_by": "deployer", "quote": "This will be used to compare against 510 model outputs at 72 hours before landfall, in order to account for varying regional vulnerabilities." }, { "kind": "report", "citation": "OCHA (2025). Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1 (as of 07 November, 9 p.m. local time). ReliefWeb.", "title": "Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1", "url": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "date": "2025-11-07", "written_by": "deployer", "quote": "CERF Anticipatory Action (AA) was activated on 06 November after the observational threshold for Tropical Cyclone Fung-won (Uwan) was triggered" }, { "kind": "press release", "citation": "Paulose, H. (2026). How anticipatory action shaped the response to the Philippines' Twin Typhoons. OCHA Financing and Outreach Division, un.org, January 2026.", "title": "How anticipatory action shaped the response to the Philippines' Twin Typhoons", "url": "https://www.un.org/en/delegate/how-anticipatory-action-shaped-response-philippines%E2%80%99-twin-typhoons", "date": "2026-01-19", "written_by": "deployer", "quote": "WFP alone reached 42,100 families through its anticipatory financing mechanism" }, { "kind": "report", "citation": "OCHA (2025). Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report (November 2024 - April 2025). unocha.org, 27 June 2025.", "title": "Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report", "url": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025", "date": "2025-06-27", "written_by": "deployer", "quote": "CERF AA resources were reallocated to support the emergency response following Super Typhoon Pepito (Man-yi)" }, { "kind": "peer-reviewed study", "citation": "Kooshki Forooshani, M., van den Homberg, M., Kalimeri, K., Kaltenbrunner, A., Mejova, Y., Milano, L., et al. (2024). Towards a global impact-based forecasting model for tropical cyclones. Natural Hazards and Earth System Sciences 24, 309-329, 1 February 2024.", "title": "Towards a global impact-based forecasting model for tropical cyclones", "url": "https://nhess.copernicus.org/articles/24/309/2024/", "date": "2024-02-01", "written_by": "makers", "quote": "in 2021 as the trigger model for the UN OCHA AA pilot" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0354-source-0001", "AIBD-0354-source-0002", "AIBD-0354-source-0003", "AIBD-0354-source-0004", "AIBD-0354-source-0005", "AIBD-0354-source-0006", "AIBD-0354-source-0007", "AIBD-0354-source-0008", "AIBD-0354-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022. ReliefWeb, posted 15 September 2021 (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-2021-2022", "date": "2021-09-15", "written_by": "deployer", "quote": "The Model includes a trigger mechanism based on the ECMWF forecast and IFRC/ Netherlands Red Cross 510 probabilistic typhoon impact prediction model developed for the Philippines" }, { "kind": "report", "citation": "OCHA (2021). Anticipatory Action Framework Philippines - Typhoons - 2021-2022, model checklist and model selection sections (PDF).", "title": "Anticipatory Action Framework Philippines, 2021-2022 (model selection)", "url": "https://reliefweb.int/attachments/78d0268e-b476-3a55-ab82-94e7478fc408/Anticipatory%20Action%20Framework%20-%20Philippines%20-%20Typhoons%20-%202021-2022.pdf", "date": "2021-09-15", "written_by": "deployer", "quote": "Partially: Uses a machine learning model to determine relationship between wind speed and housing damage." }, { "kind": "report", "citation": "OCHA Philippines (2022). Report on the After Action Review for CERF Anticipatory Action, 31 March 2022. ReliefWeb (PDF dated 22 April 2022).", "title": "After Action Review on the CERF Anticipatory Action for Typhoons", "url": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons", "date": "2022-03-31", "written_by": "deployer", "quote": "While the typhoon at the end did not meet the AA pilot activation criteria, the CERF AA Core Group was closely monitoring the situation" }, { "kind": "report", "citation": "OCHA (2023). Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision. unocha.org, 3 October 2023 (PDF).", "title": "Philippines: CERF AA (Anticipatory Action) Framework, 2023 Revision", "url": "https://www.unocha.org/publications/report/philippines/philippines-cerf-aa-anticipatory-action-framework-2023-revision", "date": "2023-10-03", "written_by": "deployer", "quote": "Tropical Cyclone with potential to reach category level 3 or higher" }, { "kind": "report", "citation": "OCHA (2025). Anticipatory Action Framework Philippines - Tropical Cyclones (as of 03 October 2025, endorsed 19 October 2025). ReliefWeb, posted 4 November 2025 (PDF).", "title": "Anticipatory Action Framework Philippines - Tropical Cyclones (As of 03 October 2025)", "url": "https://reliefweb.int/report/philippines/anticipatory-action-framework-philippines-tropical-cyclones-03-october-2025", "date": "2025-10-19", "written_by": "deployer", "quote": "This will be used to compare against 510 model outputs at 72 hours before landfall, in order to account for varying regional vulnerabilities." }, { "kind": "report", "citation": "OCHA (2025). Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1 (as of 07 November, 9 p.m. local time). ReliefWeb.", "title": "Philippines: Tropical Cyclones Kalmaegi/Tino and Fung-Wong/Uwan - Flash Update No. 1", "url": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time", "date": "2025-11-07", "written_by": "deployer", "quote": "CERF Anticipatory Action (AA) was activated on 06 November after the observational threshold for Tropical Cyclone Fung-won (Uwan) was triggered" }, { "kind": "press release", "citation": "Paulose, H. (2026). How anticipatory action shaped the response to the Philippines' Twin Typhoons. OCHA Financing and Outreach Division, un.org, January 2026.", "title": "How anticipatory action shaped the response to the Philippines' Twin Typhoons", "url": "https://www.un.org/en/delegate/how-anticipatory-action-shaped-response-philippines%E2%80%99-twin-typhoons", "date": "2026-01-19", "written_by": "deployer", "quote": "WFP alone reached 42,100 families through its anticipatory financing mechanism" }, { "kind": "report", "citation": "OCHA (2025). Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report (November 2024 - April 2025). unocha.org, 27 June 2025.", "title": "Philippines: Multiple Tropical Cyclones: Humanitarian Needs and Priorities - Response Overview Report", "url": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025", "date": "2025-06-27", "written_by": "deployer", "quote": "CERF AA resources were reallocated to support the emergency response following Super Typhoon Pepito (Man-yi)" }, { "kind": "peer-reviewed study", "citation": "Kooshki Forooshani, M., van den Homberg, M., Kalimeri, K., Kaltenbrunner, A., Mejova, Y., Milano, L., et al. (2024). Towards a global impact-based forecasting model for tropical cyclones. Natural Hazards and Earth System Sciences 24, 309-329, 1 February 2024.", "title": "Towards a global impact-based forecasting model for tropical cyclones", "url": "https://nhess.copernicus.org/articles/24/309/2024/", "date": "2024-02-01", "written_by": "makers", "quote": "in 2021 as the trigger model for the UN OCHA AA pilot" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "OCHA frameworks (2021, 2023, 2025) use 510's XGBoost house-damage model as activation trigger; near-activation Dec 2021 (Rai); the Nov 2025 activation for Uwan ran on the 185 km/h wind trigger.", "account": "OCHA's Anticipatory Action (AA) Framework for Philippine typhoons was posted on ReliefWeb on 15 September 2021. It set up a US$7.5 million CERF pilot for about 270,500 people in Regions 5 and 8 with FAO, IOM, UNFPA, UNICEF and WFP. It has a two-stage trigger. The readiness trigger is PAGASA and 510 forecasts of a category 4 or stronger cyclone. The activation trigger, within 72 hours of landfall, is the IFRC/Netherlands Red Cross 510 probabilistic typhoon impact prediction model's predicted number of totally damaged houses. The framework says that model partially uses a machine learning model relating wind speed to housing damage. 510's 2024 NHESS paper (vendor-authored) states the XGBoost model served in 2021 as the trigger model for the UN OCHA AA pilot. OCHA's After Action Review of 31 March 2022 records that Typhoon Rai (Odette) in December 2021 rapidly intensified and did not meet the activation criteria. There was a near activation with staff pre-deployed. The 2023 revision retained the 510 model. The framework endorsed on 19 October 2025 covers US$6 million CERF and about 955,507 people in Regions 5, 8 and 13. OCHA and its Centre for Humanitarian Data compute predicted totally damaged buildings with the 510 model every 6–12 hours. It adds an observational trigger for super typhoons of 185 km/h or more reported by PAGASA. OCHA's June 2025 report says the readiness trigger was met for Super Typhoon Pepito (Man-yi) in its November 2024 to April 2025 reporting period. Activation thresholds were not reached and CERF AA resources were reallocated to the response. On 6 November 2025 CERF AA was activated for Super Typhoon Fung-Wong (Uwan) after the observational wind-speed threshold was triggered. OCHA reports nearly US$6 million released and WFP alone reaching 42,100 families. No cited document records an activation produced by the 510 model's output." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model estimated how many houses a typhoon might destroy." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The 2021 revision replaced deterministic forecasts with probabilities derived from ECMWF ensemble tracks." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The model converted typhoon forecasts and data on exposed housing into estimates of houses likely to be destroyed." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "XGBoost within the 510 typhoon-impact model." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "probabilistic version using ECMWF ensemble tracks (revamped from deterministic, 2021)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "510 probabilistic typhoon impact model (XGBoost) predicting totally damaged houses, used as the CERF anticipatory action activation trigger" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "510, an initiative of the Netherlands Red Cross, with IFRC" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "UN OCHA's CERF anticipatory action framework for Philippine typhoons adopted 510's machine-learning impact model as trigger in 2021; no activation on that trigger documented to 2025", "headline": "OCHA uses 510's model as CERF trigger; no activation documented" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fb2e5c80103070fb65e02114473a292ff7832a3193b97eaae26cfce2e51f4adb" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "OCHA's Anticipatory Action (AA) Framework for Philippine typhoons was posted on ReliefWeb on 15 September 2021. It set up a US$7.5 million CERF pilot for about 270,500 people in Regions 5 and 8 with FAO, IOM, UNFPA, UNICEF and WFP. It has a two-stage trigger. The readiness trigger is PAGASA and 510 forecasts of a category 4 or stronger cyclone. The activation trigger, within 72 hours of landfall, is the IFRC/Netherlands Red Cross 510 probabilistic typhoon impact prediction model's predicted number of totally damaged houses. The framework says that model partially uses a machine learning model relating wind speed to housing damage. 510's 2024 NHESS paper (vendor-authored) states the XGBoost model served in 2021 as the trigger model for the UN OCHA AA pilot. OCHA's After Action Review of 31 March 2022 records that Typhoon Rai (Odette) in December 2021 rapidly intensified and did not meet the activation criteria. There was a near activation with staff pre-deployed. The 2023 revision retained the 510 model. The framework endorsed on 19 October 2025 covers US$6 million CERF and about 955,507 people in Regions 5, 8 and 13. OCHA and its Centre for Humanitarian Data compute predicted totally damaged buildings with the 510 model every 6–12 hours. It adds an observational trigger for super typhoons of 185 km/h or more reported by PAGASA. OCHA's June 2025 report says the readiness trigger was met for Super Typhoon Pepito (Man-yi) in its November 2024 to April 2025 reporting period. Activation thresholds were not reached and CERF AA resources were reallocated to the response. On 6 November 2025 CERF AA was activated for Super Typhoon Fung-Wong (Uwan) after the observational wind-speed threshold was triggered. OCHA reports nearly US$6 million released and WFP alone reaching 42,100 families. No cited document records an activation produced by the 510 model's output.", "replication": { "produced_by": [ "A pre-arranged CERF allocation with agency action plans ready before the typhoon season", "ECMWF ensemble track, wind and rainfall forecasts fed to the 510 impact model every 6–12 hours", "Historical house-damage data linking hazard, vulnerability and exposure to train the model", "A threshold matrix of predicted totally damaged houses per region with a 1-in-3.5-year return period (2025)" ], "must_hold": [ "Forecast lead time of at least 72 hours; rapid intensification (Rai 2021) shortened lead time below the trigger window", "Model impact estimates reaching the regional threshold matrix, which no read activation record documents", "Agency delivery capacity (financial service providers, data-sharing agreements) in the 72 hours before landfall", "PAGASA and ECMWF data availability" ], "echoes": [ { "setting": "Typhoon Rai (Odette), December 2021: forecasts monitored, activation criteria not met, staff pre-deployed (near activation)", "model_version": "2021 probabilistic version", "outcome": "did not recur", "source": "https://reliefweb.int/report/philippines/after-action-review-cerf-anticipatory-action-typhoons" }, { "setting": "Super Typhoon Pepito (Man-yi), within OCHA's November 2024 to April 2025 reporting period: readiness trigger met, activation thresholds not reached, CERF AA resources reallocated to emergency response", "outcome": "did not recur", "source": "https://www.unocha.org/publications/report/philippines/philippines-multiple-tropical-cyclones-humanitarian-needs-and-priorities-response-overview-report-november-2024-april-2025" }, { "date": "2025-11-06", "setting": "Super Typhoon Fung-Wong (Uwan): CERF AA activated on the observational 185 km/h threshold; nearly US$6 million released; WFP reports 42,100 families reached; AI model's role not stated", "outcome": "unknown", "source": "https://reliefweb.int/report/philippines/philippines-tropical-cyclones-kalmaegitino-and-fung-wonguwan-flash-update-no1-07-november-9-pm-local-time" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0294", "title": "Fitbit Charge 3 oxygen-variation signals precede COVID-19 exacerbation in 4 of 5 cases and reveal severe sleep apnoea in one patient (DEXTERITY pilot, Kanazawa)", "summary": "Kanazawa pilot, 23 COVID-19 patients (2020): Fitbit oxygen-variation signals preceded 4 of 5 exacerbations (sensitivity 80%); one man's persistent signals led to polysomnography showing severe OSAS.", "date_observed": "2021-09-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Yamagami, Nomura and colleagues published the DEXTERITY pilot in JMIR Formative Research on 16 September 2021. They are at Kanazawa University and Japan Community Health Care Organization (JCHO) Kanazawa Hospital. The study ran from August to November 2020. The individual event is undated. Twenty-three patients with PCR-confirmed COVID-19 wore a Fitbit Charge 3 for 30 days. The investigators defined a high “estimated oxygen variation” (EOV) signal as a significant dip and recovery of the oxygen level within the index period. A prediction counted as successful if the signal appeared within two days before an exacerbation. Exacerbation occurred in six patients (seven events). EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%), better than resting-heart-rate signals (50% and 80%). Separately, patient JCHO-023, a 53-year-old man with hypertension recovered from COVID-19, showed “a long-lasting high EOV signal” from days 18 to 29 without symptoms. The team suspected sleep apnea. A portable polysomnogram (Nihon Kohden SAS-2200) gave a 3% oxygen desaturation index (ODI) of 33.6 per hour, severe obstructive sleep apnea syndrome. The paper reports no treatment for him. The authors note the Fitbit's functions and analysis algorithms were not approved as a medical device at the time. They note that baseline data were short and the five exacerbation cases are too few to generalize. The prediction analysis was defined against outcomes after the fact rather than as live alerts.", "category": "benefit created", "unexpected": true, "purpose": "Fitbit's EOV metric summarizes overnight oxygen variation for consumers. The investigators repurposed it to flag COVID-19 deterioration, and the sleep-apnea finding was incidental to that study aim.", "system": "Fitbit Charge 3 estimated oxygen variation (EOV) and resting heart rate, with investigator-defined signal thresholds", "model_version": "Fitbit Charge 3", "developer": "Fitbit (device and EOV algorithm); Kanazawa University investigators (signal definitions)", "deployer": "Kanazawa University and JCHO Kanazawa Hospital (DEXTERITY pilot, UMIN000041421)", "location": "Kanazawa, Japan", "domain": "Healthcare (infectious disease; sleep medicine)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "depth": null, "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ], "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. The paper does not say whether Fitbit's EOV estimation uses machine learning and notes the functions were not approved as a medical device. The COVID-19 prediction figures were computed after the outcomes were known, not from alerts acted on in real time." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Yamagami K, Nomura A, Kometani M, Shimojima M, Sakata K, Usui S, Furukawa K, Takamura M, Okajima M, Watanabe K, Yoneda T (2021). Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation. JMIR Formative Research 5(9):e30819 (PMC8448084).", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals." }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, results.", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%)" }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, representative case 3 (JCHO-023).", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "His 3% oxygen desaturation index was 33.6 per hour, indicating severe OSAS." }, { "kind": "peer-reviewed study", "citation": "Yamagami et al. (2021), JMIR Form Res 5(9):e30819, limitations.", "title": "Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "date": "2021-09-16", "written_by": "makers", "quote": "the Fitbit wearable device, including its functions (eg, EOV) and analysis algorithms, was not yet approved as a medical device at the time of this study" } ], "replication": { "produced_by": [ "A Fitbit Charge 3 worn for 30 days by patients with PCR-confirmed COVID-19, giving EOV and resting heart rate", "An investigator-defined high-EOV signal (a significant dip and recovery of the oxygen level within the index period) reviewed by the study team", "Weekly phone calls to discharged patients and access to portable polysomnography" ], "must_hold": [ "Patients can pair the device with a smartphone app (elderly patients unable to use a smartphone were not enrolled)", "Enough baseline data to separate abnormal signals from normal variation, which the authors list as lacking in the 30-day window" ], "echoes": [] }, "paired_incident": null, "headline": "Fitbit Charge 3 signals precede 4 of 5 COVID-19 exacerbations", "metric": "EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%)", "comparator": { "against": "high resting-heart-rate (RHR) signals from the same Fitbit data", "before": "the sensitivity and specificity of high RHR signals were 50% and 80%, respectively", "after": "4 out of 5 cases (sensitivity=80%, specificity=90%)", "basis": "measured", "quote": "We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/" }, "later": { "status": "unknown", "date": null, "note": "No later DEXTERITY publication and no follow-up on patient JCHO-023 was found in the cited paper.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8448084/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://support.google.com/product-documentation/answer/14816019; https://en.wikipedia.org/wiki/Kanazawa_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0294", "catalog_version": "1.0.0", "source_fingerprint": "1c723e06aa36a32592a37c7e4605951c8f977581c24cf09083e762676a11cecd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0294-source-0001", "AIBD-0294-source-0002", "AIBD-0294-source-0003", "AIBD-0294-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fitbit (device and EOV algorithm); Kanazawa University investigators (signal definitions)", "deployer": "Kanazawa University and JCHO Kanazawa Hospital (DEXTERITY pilot, UMIN000041421)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. The paper does not say whether Fitbit's EOV estimation uses machine learning and notes the functions were not approved as a medical device. The COVID-19 prediction figures were computed after the outcomes were known, not from alerts acted on in real time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The device produced the EOV values. The investigators' own rule flagged high signals, and clinicians decided to order polysomnography for the sleep-apnea patient. The paper does not say whether Fitbit's EOV estimation uses machine learning and notes the functions were not approved as a medical device. The COVID-19 prediction figures were computed after the outcomes were known, not from alerts acted on in real time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One man received a diagnosis of severe obstructive sleep apnea (3% ODI 33.6/h) from an incidental wearable signal. The paper reports no treatment or follow-up for him." }, { "group": "organizational", "reason": "The 80% sensitivity for predicting exacerbation is a retrospective pilot result on five events, which the authors say is too small to generalize. No live alerting or changed care is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", 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A portable polysomnogram (Nihon Kohden SAS-2200) gave a 3% oxygen desaturation index (ODI) of 33.6 per hour, severe obstructive sleep apnea syndrome. The paper reports no treatment for him. The authors note the Fitbit's functions and analysis algorithms were not approved as a medical device at the time. They note that baseline data were short and the five exacerbation cases are too few to generalize. The prediction analysis was defined against outcomes after the fact rather than as live alerts." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used a Fitbit Charge 3." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Fitbit Charge 3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fitbit Charge 3 estimated oxygen variation (EOV) and resting heart rate, with investigator-defined signal thresholds" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Fitbit (device and EOV algorithm); Kanazawa University investigators (signal definitions)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fitbit Charge 3 oxygen-variation signals precede COVID-19 exacerbation in 4 of 5 cases and reveal severe sleep apnoea in one patient (DEXTERITY pilot, Kanazawa)", "headline": "Fitbit Charge 3 signals precede 4 of 5 COVID-19 exacerbations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1c723e06aa36a32592a37c7e4605951c8f977581c24cf09083e762676a11cecd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Yamagami, Nomura and colleagues published the DEXTERITY pilot in JMIR Formative Research on 16 September 2021. They are at Kanazawa University and Japan Community Health Care Organization (JCHO) Kanazawa Hospital. The study ran from August to November 2020. The individual event is undated. Twenty-three patients with PCR-confirmed COVID-19 wore a Fitbit Charge 3 for 30 days. The investigators defined a high “estimated oxygen variation” (EOV) signal as a significant dip and recovery of the oxygen level within the index period. A prediction counted as successful if the signal appeared within two days before an exacerbation. Exacerbation occurred in six patients (seven events). EOV signals preceded four of five analyzed cases (sensitivity 80%, specificity 90%), better than resting-heart-rate signals (50% and 80%). Separately, patient JCHO-023, a 53-year-old man with hypertension recovered from COVID-19, showed “a long-lasting high EOV signal” from days 18 to 29 without symptoms. The team suspected sleep apnea. A portable polysomnogram (Nihon Kohden SAS-2200) gave a 3% oxygen desaturation index (ODI) of 33.6 per hour, severe obstructive sleep apnea syndrome. The paper reports no treatment for him. The authors note the Fitbit's functions and analysis algorithms were not approved as a medical device at the time. They note that baseline data were short and the five exacerbation cases are too few to generalize. The prediction analysis was defined against outcomes after the fact rather than as live alerts.", "replication": { "produced_by": [ "A Fitbit Charge 3 worn for 30 days by patients with PCR-confirmed COVID-19, giving EOV and resting heart rate", "An investigator-defined high-EOV signal (a significant dip and recovery of the oxygen level within the index period) reviewed by the study team", "Weekly phone calls to discharged patients and access to portable polysomnography" ], "must_hold": [ "Patients can pair the device with a smartphone app (elderly patients unable to use a smartphone were not enrolled)", "Enough baseline data to separate abnormal signals from normal variation, which the authors list as lacking in the 30-day window" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0110", "title": "Apple Watch Fall Detection calling an ambulance for a motorcyclist left unconscious by a hit-and-run in Singapore", "summary": "Apple Watch Fall Detection called an ambulance and alerted his girlfriend after a hit-and-run left a Singapore motorcyclist unconscious.", "date_observed": "2021-09-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On the evening of 25 September 2021, Muhammad Fitri, 24, was riding home when a gray van struck his motorcycle. That was at the junction of Ang Mo Kio Avenue 6 and Ang Mo Kio Street 31, Singapore. The driver fled; Fitri lost consciousness on a near-empty road. His Apple Watch's Fall Detection registered the impact. Via the paired phone it automatically called an ambulance and texted and phoned his emergency contact, his girlfriend. The Singapore Civil Defence Force said it was alerted around 8:20pm. Fitri was regaining consciousness as paramedics arrived. He was conveyed, conscious, to Khoo Teck Puat Hospital with abrasions, a neck collar and a suspected bleed at the back of the head. Police confirmed a hit-and-run.", "category": "protective response", "unexpected": false, "purpose": "Fall Detection is built to recognize a hard fall. If the wearer stays immobile for about a minute, it calls emergency services and messages emergency contacts with the location. That is what it did. The trigger was a motorcycle collision rather than a fall from standing. Apple's documentation notes only that high-impact activity may register as a fall.", "system": "Apple Watch Fall Detection", "model_version": "Not reported; Fall Detection requires Apple Watch Series 4 or later (Mothership, citing Apple)", "developer": "Apple", "deployer": null, "location": "Ang Mo Kio, Singapore", "domain": "Emergency response / road traffic injury", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2021-09-29-a99a" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "An unconscious hit-and-run victim on a quiet road at night had an ambulance summoned within what Wanbao calls the golden hour. He had abrasions, a neck injury needing a collar and a suspected bleed at the back of the head. His girlfriend was told where he was. The family and the Wanbao headline call it life-saving. No clinician or official says so and a passer-by did reach him, so life-saving is not established." } ], "ai_role": { "status": "assessed", "statement": "The watch's fall-detection classifier read the collision's impact as a hard fall. With the wearer unresponsive, it placed the automatic ambulance call through the paired phone and sent the location texts and calls to his girlfriend. SCDF paramedics treated and conveyed him. The counterfactual is unproven. A passer-by later picked up his phone and spoke to the girlfriend. The family at first assumed that person had called the ambulance, and Fitri was regaining consciousness as paramedics arrived." }, "evidence": [ { "kind": "news report", "citation": "Lianhe Wanbao, Chen Yujia 陈昱嘉 (2021). 准新郎遭撞后逃昏迷 智能表救一命 [Groom-to-be knocked unconscious in hit-and-run; smart watch saves his life]. zaobao.com.sg, 28 September 2021 (print: Lianhe Wanbao, 28 September 2021).", "title": "准新郎遭撞后逃昏迷 智能表救一命", "url": "https://www.zaobao.com.sg/news/singapore/story20210928-1198175", "date": "2021-09-28", "written_by": "independent", "quote": "菲特里的智能手表检测到不寻常的剧烈震动后立刻启动了救援功能，链接手表的手机也自动召救护车到现场" }, { "kind": "news report", "citation": "Zheng, Z. (2021). Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio. Mothership.sg, 29 September 2021.", "title": "Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio", "url": "https://mothership.sg/2021/09/motorcyclist-apple-watch-saves-life-ang-mo-kio/", "date": "2021-09-29", "written_by": "independent", "quote": "the Singapore Civil Defence Force (SCDF) said that they were alerted to the accident at around 8:20pm. Fitri was conveyed to Khoo Teck Puat Hospital." }, { "kind": "press release", "citation": "Apple (2026). Use Fall Detection with Apple Watch. Apple Support article 108896, last modified 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ], "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch (Series 4 or later) with a connected paired iPhone or cellular service", "A collision throws the wearer down with an impact the classifier reads as a hard fall. The wearer stays immobile for about a minute without dismissing the alert.", "The ambulance service and the emergency contact can act on the automatic call and the shared location" ], "must_hold": [ "The watch and phone keep working and connected after the impact (here the watch screen cracked but still functioned)", "Nobody else present is able to call for help, otherwise the watch's call adds little", "An ambulance can reach the location within the window in which treatment matters" ], "echoes": [] }, "paired_incident": null, "headline": "Apple Watch calls an ambulance for an unconscious motorcyclist", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later report on Fitri's recovery or the hit-and-run case was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-09-29-a99a", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0110", "catalog_version": "1.0.0", "source_fingerprint": "eda5b9b706d6048044c13a42c8e838a81ea8d558c429266c9ba66817f3c217fd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0110-source-0001", "AIBD-0110-source-0002", "AIBD-0110-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's fall-detection classifier read the collision's impact as a hard fall. With the wearer unresponsive, it placed the automatic ambulance call through the paired phone and sent the location texts and calls to his girlfriend. SCDF paramedics treated and conveyed him. The counterfactual is unproven. A passer-by later picked up his phone and spoke to the girlfriend. The family at first assumed that person had called the ambulance, and Fitri was regaining consciousness as paramedics arrived." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The watch's fall-detection classifier read the collision's impact as a hard fall. With the wearer unresponsive, it placed the automatic ambulance call through the paired phone and sent the location texts and calls to his girlfriend. SCDF paramedics treated and conveyed him. The counterfactual is unproven. A passer-by later picked up his phone and spoke to the girlfriend. The family at first assumed that person had called the ambulance, and Fitri was regaining consciousness as paramedics arrived." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An unconscious hit-and-run victim on a quiet road at night had an ambulance summoned within what Wanbao calls the golden hour. He had abrasions, a neck injury needing a collar and a suspected bleed at the back of the head. His girlfriend was told where he was. The family and the Wanbao headline call it life-saving. No clinician or official says so and a passer-by did reach him, so life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and the makers' press release. 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No clinician or official says so and a passer-by did reach him, so life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An unconscious hit-and-run victim on a quiet road at night had an ambulance summoned within what Wanbao calls the golden hour. He had abrasions, a neck injury needing a collar and a suspected bleed at the back of the head. 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}, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2021-09-29-a99a" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later report on Fitri's recovery or the hit-and-run case was found in the cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0110" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the evening of 25 September 2021, Muhammad Fitri, 24, was riding home when a gray van struck his motorcycle. That was at the junction of Ang Mo Kio Avenue 6 and Ang Mo Kio Street 31, Singapore. The driver fled; Fitri lost consciousness on a near-empty road. His Apple Watch's Fall Detection registered the impact. Via the paired phone it automatically called an ambulance and texted and phoned his emergency contact, his girlfriend. The Singapore Civil Defence Force said it was alerted around 8:20pm. Fitri was regaining consciousness as paramedics arrived. He was conveyed, conscious, to Khoo Teck Puat Hospital with abrasions, a neck collar and a suspected bleed at the back of the head. Police confirmed a hit-and-run.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An unconscious hit-and-run victim on a quiet road at night had an ambulance summoned within what Wanbao calls the golden hour. He had abrasions, a neck injury needing a collar and a suspected bleed at the back of the head. His girlfriend was told where he was. The family and the Wanbao headline call it life-saving. No clinician or official says so and a passer-by did reach him, so life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Fall Detection is built to recognize a hard fall. If the wearer stays immobile for about a minute, it calls emergency services and messages emergency contacts with the location. That is what it did. The trigger was a motorcycle collision rather than a fall from standing. Apple's documentation notes only that high-impact activity may register as a fall." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ang Mo Kio, Singapore", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Fall Detection is built to recognize a hard fall. If the wearer stays immobile for about a minute, it calls emergency services and messages emergency contacts with the location. That is what it did. The trigger was a motorcycle collision rather than a fall from standing. Apple's documentation notes only that high-impact activity may register as a fall." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-09-25", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-09-29-a99a", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch (Series 4 or later) with a connected paired iPhone or cellular service", "A collision throws the wearer down with an impact the classifier reads as a hard fall. The wearer stays immobile for about a minute without dismissing the alert.", "The ambulance service and the emergency contact can act on the automatic call and the shared location" ], "must_hold": [ "The watch and phone keep working and connected after the impact (here the watch screen cracked but still functioned)", "Nobody else present is able to call for help, otherwise the watch's call adds little", "An ambulance can reach the location within the window in which treatment matters" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-09-29-a99a", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Emergency response / road traffic injury", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Lianhe Wanbao, Chen Yujia 陈昱嘉 (2021). 准新郎遭撞后逃昏迷 智能表救一命 [Groom-to-be knocked unconscious in hit-and-run; smart watch saves his life]. zaobao.com.sg, 28 September 2021 (print: Lianhe Wanbao, 28 September 2021).", "title": "准新郎遭撞后逃昏迷 智能表救一命", "url": "https://www.zaobao.com.sg/news/singapore/story20210928-1198175", "date": "2021-09-28", "written_by": "independent", "quote": "菲特里的智能手表检测到不寻常的剧烈震动后立刻启动了救援功能，链接手表的手机也自动召救护车到现场" }, { "kind": "news report", "citation": "Zheng, Z. (2021). Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio. Mothership.sg, 29 September 2021.", "title": "Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio", "url": "https://mothership.sg/2021/09/motorcyclist-apple-watch-saves-life-ang-mo-kio/", "date": "2021-09-29", "written_by": "independent", "quote": "the Singapore Civil Defence Force (SCDF) said that they were alerted to the accident at around 8:20pm. Fitri was conveyed to Khoo Teck Puat Hospital." }, { "kind": "press release", "citation": "Apple (2026). Use Fall Detection with Apple Watch. Apple Support article 108896, last modified 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0110-source-0001", "AIBD-0110-source-0002", "AIBD-0110-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Lianhe Wanbao, Chen Yujia 陈昱嘉 (2021). 准新郎遭撞后逃昏迷 智能表救一命 [Groom-to-be knocked unconscious in hit-and-run; smart watch saves his life]. zaobao.com.sg, 28 September 2021 (print: Lianhe Wanbao, 28 September 2021).", "title": "准新郎遭撞后逃昏迷 智能表救一命", "url": "https://www.zaobao.com.sg/news/singapore/story20210928-1198175", "date": "2021-09-28", "written_by": "independent", "quote": "菲特里的智能手表检测到不寻常的剧烈震动后立刻启动了救援功能，链接手表的手机也自动召救护车到现场" }, { "kind": "news report", "citation": "Zheng, Z. (2021). Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio. Mothership.sg, 29 September 2021.", "title": "Motorcyclist's Apple watch alerts girlfriend & calls for ambulance after hit-&-run accident at Ang Mo Kio", "url": "https://mothership.sg/2021/09/motorcyclist-apple-watch-saves-life-ang-mo-kio/", "date": "2021-09-29", "written_by": "independent", "quote": "the Singapore Civil Defence Force (SCDF) said that they were alerted to the accident at around 8:20pm. Fitri was conveyed to Khoo Teck Puat Hospital." }, { "kind": "press release", "citation": "Apple (2026). Use Fall Detection with Apple Watch. Apple Support article 108896, last modified 6 May 2026.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": "If your watch detects that you've been immobile for about a minute, it will make the call automatically." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Apple Watch Fall Detection called an ambulance and alerted his girlfriend after a hit-and-run left a Singapore motorcyclist unconscious.", "account": "On the evening of 25 September 2021, Muhammad Fitri, 24, was riding home when a gray van struck his motorcycle. That was at the junction of Ang Mo Kio Avenue 6 and Ang Mo Kio Street 31, Singapore. The driver fled; Fitri lost consciousness on a near-empty road. His Apple Watch's Fall Detection registered the impact. Via the paired phone it automatically called an ambulance and texted and phoned his emergency contact, his girlfriend. The Singapore Civil Defence Force said it was alerted around 8:20pm. Fitri was regaining consciousness as paramedics arrived. He was conveyed, conscious, to Khoo Teck Puat Hospital with abrasions, a neck collar and a suspected bleed at the back of the head. Police confirmed a hit-and-run." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The watch detected a hard fall and called emergency services when the wearer did not respond." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The reported feature was Apple Watch Fall Detection. The record does not identify the watch generation." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; Fall Detection requires Apple Watch Series 4 or later (Mothership, citing Apple)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Fall Detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Fall Detection calling an ambulance for a motorcyclist left unconscious by a hit-and-run in Singapore", "headline": "Apple Watch calls an ambulance for an unconscious motorcyclist" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "eda5b9b706d6048044c13a42c8e838a81ea8d558c429266c9ba66817f3c217fd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the evening of 25 September 2021, Muhammad Fitri, 24, was riding home when a gray van struck his motorcycle. That was at the junction of Ang Mo Kio Avenue 6 and Ang Mo Kio Street 31, Singapore. The driver fled; Fitri lost consciousness on a near-empty road. His Apple Watch's Fall Detection registered the impact. Via the paired phone it automatically called an ambulance and texted and phoned his emergency contact, his girlfriend. The Singapore Civil Defence Force said it was alerted around 8:20pm. Fitri was regaining consciousness as paramedics arrived. He was conveyed, conscious, to Khoo Teck Puat Hospital with abrasions, a neck collar and a suspected bleed at the back of the head. Police confirmed a hit-and-run.", "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch (Series 4 or later) with a connected paired iPhone or cellular service", "A collision throws the wearer down with an impact the classifier reads as a hard fall. The wearer stays immobile for about a minute without dismissing the alert.", "The ambulance service and the emergency contact can act on the automatic call and the shared location" ], "must_hold": [ "The watch and phone keep working and connected after the impact (here the watch screen cracked but still functioned)", "Nobody else present is able to call for help, otherwise the watch's call adds little", "An ambulance can reach the location within the window in which treatment matters" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0074", "title": "Machine-learning color reconstruction of Klimt's destroyed Faculty Paintings, made with the Belvedere and later exhibited by it", "summary": "ML color reconstruction of Klimt's destroyed Faculty Paintings launched 7 October 2021 with the Belvedere, shown in its 2025 exhibition", "date_observed": "2021-10-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Gustav Klimt's Faculty Paintings (Philosophy, Medicine and Jurisprudence) were made for the ceiling of the University of Vienna's Great Hall. Fire destroyed them in 1945; only black-and-white photographs survive. The online exhibition Klimt vs. Klimt – The Man of Contradictions was unveiled by Google Arts & Culture with the Belvedere on 7 October 2021. For it, Google Arts & Culture Lab resident Emil Wallner trained a colorization model on 91,749 artworks and then on Klimt's color paintings. Curator Franz Smola's compilation of contemporary descriptions of the colors guided him. The Belvedere describes the result as an attempt to reconstruct the original colors in which artificial intelligence played an essential role. It showed the color reconstructions at original size in its exhibition Gustav Klimt – Pigment & Pixel (20 February to 7 September 2025).", "category": "benefit created", "unexpected": false, "purpose": "Colorize black-and-white photographs of destroyed paintings in the artist's style, guided by archival color descriptions", "system": "The Klimt Color Enigma colourisation model (Google Arts & Culture Lab)", "model_version": null, "developer": "Google (Emil Wallner)", "deployer": "Belvedere, Vienna, with Google Arts & Culture", "location": "Vienna, Austria", "domain": "Art", "segment": "Museums and art history", "benefit_type": "Increased Creativity", "taxonomy_note": "The colorization is a reconstruction hypothesis for destroyed paintings rather than a new creative work.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: the Belvedere adopted and exhibited the reconstructions in 2025, per its exhibition page" }, { "group": "societal", "depth": 1, "reason": "Small: the public can view a color hypothesis of lost works; Smola himself called the result surprising where no color knowledge existed (Jing Daily)" } ], "ai_role": { "status": "assessed", "statement": "The model proposed colors for the monochrome photographs. Known colors from Smola's archival research were added directly, so the output mixes documented evidence with learned statistical guesses. The Belvedere calls it an attempt at reconstruction, and no source claims the colors are verified." }, "evidence": [ { "kind": "press release", "citation": "Belvedere (2025). Gustav Klimt – Pigment & Pixel, exhibition page, 20 February – 7 September 2025. belvedere.at.", "title": "Gustav Klimt – Pigment & Pixel", "url": "https://www.belvedere.at/en/gustav-klimt-pigment-pixel", "date": "2025-02-20", "written_by": "deployer", "quote": "Now for the first time, the Ceiling Paintings can be viewed in color in their original size and arrangement on the ceiling." }, { "kind": "news report", "citation": "Chen, M. (2021). Google Arts & Culture And Belvedere Museum Trained An AI To Color Like Klimt. Jing Daily Culture, 7 October 2021.", "title": "Google Arts & Culture And Belvedere Museum Trained An AI To Color Like Klimt", "url": "https://jingdailyculture.com/google-arts-and-culture-klimt-ai/", "date": "2021-10-07", "written_by": "independent", "quote": "on October 7, Google Arts & Culture unveiled Klimt vs. Klimt – The Man of Contradictions" }, { "kind": "news report", "citation": "I Programmer (2022). Google AI Recreates Lost Klimt Artworks. i-programmer.info.", "title": "Google AI Recreates Lost Klimt Artworks", "url": "https://www.i-programmer.info/news/105-artificial-intelligence/14928-google-ai-recreates-lost-klimt-artworks-.html", "date": "2022-01-03", "written_by": "independent", "quote": "was trained on 91749 artworks from Google Arts & Culture to enable it to learn object boundaries, textures, and frequent compositions in artworks" }, { "kind": "press release", "citation": "Google Arts & Culture (2021). 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Gustav Klimt – Pigment & Pixel, exhibition page, 20 February – 7 September 2025. belvedere.at.", "title": "Gustav Klimt – Pigment & Pixel", "url": "https://www.belvedere.at/en/gustav-klimt-pigment-pixel", "date": "2025-02-20", "written_by": "deployer", "quote": "Now for the first time, the Ceiling Paintings can be viewed in color in their original size and arrangement on the ceiling." }, { "kind": "news report", "citation": "Chen, M. (2021). Google Arts & Culture And Belvedere Museum Trained An AI To Color Like Klimt. Jing Daily Culture, 7 October 2021.", "title": "Google Arts & Culture And Belvedere Museum Trained An AI To Color Like Klimt", "url": "https://jingdailyculture.com/google-arts-and-culture-klimt-ai/", "date": "2021-10-07", "written_by": "independent", "quote": "on October 7, Google Arts & Culture unveiled Klimt vs. Klimt – The Man of Contradictions" }, { "kind": "news report", "citation": "I Programmer (2022). Google AI Recreates Lost Klimt Artworks. i-programmer.info.", "title": "Google AI Recreates Lost Klimt Artworks", "url": "https://www.i-programmer.info/news/105-artificial-intelligence/14928-google-ai-recreates-lost-klimt-artworks-.html", "date": "2022-01-03", "written_by": "independent", "quote": "was trained on 91749 artworks from Google Arts & Culture to enable it to learn object boundaries, textures, and frequent compositions in artworks" }, { "kind": "press release", "citation": "Google Arts & Culture (2021). 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Fire destroyed them in 1945; only black-and-white photographs survive. The online exhibition Klimt vs. Klimt – The Man of Contradictions was unveiled by Google Arts & Culture with the Belvedere on 7 October 2021. For it, Google Arts & Culture Lab resident Emil Wallner trained a colorization model on 91,749 artworks and then on Klimt's color paintings. Curator Franz Smola's compilation of contemporary descriptions of the colors guided him. The Belvedere describes the result as an attempt to reconstruct the original colors in which artificial intelligence played an essential role. It showed the color reconstructions at original size in its exhibition Gustav Klimt – Pigment & Pixel (20 February to 7 September 2025)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "The Klimt Color Enigma colourisation model (Google Arts & Culture Lab)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google (Emil Wallner)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Machine-learning color reconstruction of Klimt's destroyed Faculty Paintings, made with the Belvedere and later exhibited by it", "headline": "Google Arts & Culture Lab recolours Klimt's destroyed paintings" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "96c3a11a391bf3fe05578856cb1ba97ee51dd1c061005d785de6334b66203dc8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Gustav Klimt's Faculty Paintings (Philosophy, Medicine and Jurisprudence) were made for the ceiling of the University of Vienna's Great Hall. Fire destroyed them in 1945; only black-and-white photographs survive. The online exhibition Klimt vs. Klimt – The Man of Contradictions was unveiled by Google Arts & Culture with the Belvedere on 7 October 2021. For it, Google Arts & Culture Lab resident Emil Wallner trained a colorization model on 91,749 artworks and then on Klimt's color paintings. Curator Franz Smola's compilation of contemporary descriptions of the colors guided him. The Belvedere describes the result as an attempt to reconstruct the original colors in which artificial intelligence played an essential role. It showed the color reconstructions at original size in its exhibition Gustav Klimt – Pigment & Pixel (20 February to 7 September 2025).", "replication": { "produced_by": [ "Surviving black-and-white photographs of the destroyed paintings", "A colorization model pre-trained on 91,749 artworks and fine-tuned on Klimt's color paintings", "Curator-compiled written color testimony injected as fixed colors" ], "must_hold": [ "Monochrome photographs of adequate quality exist", "Written color descriptions exist for key areas", "An institutional partner validates and displays the result" ], "echoes": [ { "date": "2025-02-20", "setting": "Belvedere exhibition Gustav Klimt – Pigment & Pixel shows the color reconstructions at original size and ceiling arrangement", "outcome": "recurred", "source": "https://www.belvedere.at/en/gustav-klimt-pigment-pixel" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0073", "title": "AI-completed Beethoven Tenth Symphony premiered by the Beethoven Orchester Bonn on 9 October 2021", "summary": "AI-completed Beethoven Tenth premiered 9 October 2021 by Beethoven Orchester Bonn under Dirk Kaftan at the Telekom Forum, Bonn", "date_observed": "2021-10-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 9 October 2021 the Beethoven Orchester Bonn under Dirk Kaftan gave the world premiere of a Tenth Symphony completed with artificial intelligence. It was at the Telekom Forum in Bonn. Deutsche Telekom funded the project and organized the premiere, for Beethoven's 250th anniversary. Beethoven left only sketches for the work. A team led by musicologist Matthias Röder, with AI researcher Ahmed Elgammal and Mark Gotham, trained a model on Beethoven's output. It generated sketch continuations. Composer Walter Werzowa and musicologists chose and arranged the generated themes. Euronews reported on 13 October 2021 that the premiere had taken place in Bonn on 9 October. The benefit is a performed and recorded cultural artifact; the sources do not claim the result is Beethoven's.", "category": "benefit created", "unexpected": false, "purpose": "Generate a completion of Beethoven's unfinished Tenth Symphony from his sketches in his style", "system": "Beethoven X AI generative music model (Elgammal/Playform AI team)", "model_version": null, "developer": "Ahmed Elgammal (Rutgers University / Playform AI) with Mark Gotham", "deployer": "Deutsche Telekom (funder and concert organizer) with Beethoven Orchester Bonn", "location": "Bonn, Germany", "domain": "Music", "segment": "Classical music performance", "benefit_type": "Increased Creativity", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: a sponsor-funded premiere programmed by the orchestra and broadcast live, per the orchestra's concert page" }, { "group": "societal", "depth": 1, "reason": "Small: one new performance and recording of a hypothetical completion; Euronews states humans chose and arranged the generated themes" } ], "ai_role": { "status": "assessed", "statement": "The model generated candidate continuations of Beethoven's sketches. Humans (Werzowa and the musicologists) selected, arranged and orchestrated them, so the AI contribution was generative input within a human-curated process. The vendor-side accounts (Elgammal in The Conversation; Telekom) and the orchestra's own program page agree on the premiere." }, "evidence": [ { "kind": "press release", "citation": "Beethoven Orchester Bonn (2021). Beethoven X, concert page, 9 October 2021, Telekom Forum. beethoven-orchester.de.", "title": "Beethoven X The AI Project", "url": "https://www.beethoven-orchester.de/konzerte/beethoven-x", "date": "2021-10-09", "written_by": "deployer", "quote": "Sa 09/10/2021 19:00 Telekom Forum … Sinfonie Nr. 10 c-Moll (Uraufführung der durch Künstliche Intelligenz (KI) vollendeten 10. Sinfonie)" }, { "kind": "news report", "citation": "Euronews (2021). Artificial intelligence helps complete Beethoven symphony. Euronews.", "title": "Artificial intelligence helps complete Beethoven symphony", "url": "https://www.euronews.com/video/2021/10/13/artificial-intelligence-helps-complete-beethoven-symphony", "date": "2021-10-13", "written_by": "independent", "quote": "The world premiere was presented last Saturday (9 October) in Bonn, Germany, the birth city of the legendary composer." }, { "kind": "report", "citation": "Elgammal, A. (2021). How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony. The Conversation.", "title": "How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony", "url": "https://theconversation.com/how-a-team-of-musicologists-and-computer-scientists-completed-beethovens-unfinished-10th-symphony-168160", "date": "2021-09-24", "written_by": "makers", "quote": "set to be released on Oct. 9, 2021, the same day as the world premiere performance scheduled to take place in Bonn, Germany" }, { "kind": "press release", "citation": "Magyar Telekom (2021). Algorithms fine-tuned - The digital journey taken by Beethoven's unfinished Tenth Symphony. 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external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Beethoven Orchester Bonn (2021). Beethoven X, concert page, 9 October 2021, Telekom Forum. beethoven-orchester.de.", "title": "Beethoven X The AI Project", "url": "https://www.beethoven-orchester.de/konzerte/beethoven-x", "date": "2021-10-09", "written_by": "deployer", "quote": "Sa 09/10/2021 19:00 Telekom Forum … Sinfonie Nr. 10 c-Moll (Uraufführung der durch Künstliche Intelligenz (KI) vollendeten 10. Sinfonie)" }, { "kind": "news report", "citation": "Euronews (2021). Artificial intelligence helps complete Beethoven symphony. Euronews.", "title": "Artificial intelligence helps complete Beethoven symphony", "url": "https://www.euronews.com/video/2021/10/13/artificial-intelligence-helps-complete-beethoven-symphony", "date": "2021-10-13", "written_by": "independent", "quote": "The world premiere was presented last Saturday (9 October) in Bonn, Germany, the birth city of the legendary composer." }, { "kind": "report", "citation": "Elgammal, A. (2021). How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony. The Conversation.", "title": "How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony", "url": "https://theconversation.com/how-a-team-of-musicologists-and-computer-scientists-completed-beethovens-unfinished-10th-symphony-168160", "date": "2021-09-24", "written_by": "makers", "quote": "set to be released on Oct. 9, 2021, the same day as the world premiere performance scheduled to take place in Bonn, Germany" }, { "kind": "press release", "citation": "Magyar Telekom (2021). Algorithms fine-tuned - The digital journey taken by Beethoven's unfinished Tenth Symphony. Telekom Hungary press release; issued by the project's funder, not by the model's developer.", "title": "Algorithms fine-tuned - The digital journey taken by Beethoven's unfinished Tenth Symphony", "url": "https://www.telekom.hu/about_us/press_room/press_releases/2021/october_1", "date": "2021-10-01", "written_by": "deployer", "quote": "The symphony created as a result of the unique cooperation between man and AI will premiere in Beethoven's birthplace, Bonn, Germany." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0073-source-0001", "AIBD-0073-source-0002", "AIBD-0073-source-0003", "AIBD-0073-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Beethoven Orchester Bonn (2021). Beethoven X, concert page, 9 October 2021, Telekom Forum. beethoven-orchester.de.", "title": "Beethoven X The AI Project", "url": "https://www.beethoven-orchester.de/konzerte/beethoven-x", "date": "2021-10-09", "written_by": "deployer", "quote": "Sa 09/10/2021 19:00 Telekom Forum … Sinfonie Nr. 10 c-Moll (Uraufführung der durch Künstliche Intelligenz (KI) vollendeten 10. Sinfonie)" }, { "kind": "news report", "citation": "Euronews (2021). Artificial intelligence helps complete Beethoven symphony. Euronews.", "title": "Artificial intelligence helps complete Beethoven symphony", "url": "https://www.euronews.com/video/2021/10/13/artificial-intelligence-helps-complete-beethoven-symphony", "date": "2021-10-13", "written_by": "independent", "quote": "The world premiere was presented last Saturday (9 October) in Bonn, Germany, the birth city of the legendary composer." }, { "kind": "report", "citation": "Elgammal, A. (2021). How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony. The Conversation.", "title": "How a team of musicologists and computer scientists completed Beethoven's unfinished 10th Symphony", "url": "https://theconversation.com/how-a-team-of-musicologists-and-computer-scientists-completed-beethovens-unfinished-10th-symphony-168160", "date": "2021-09-24", "written_by": "makers", "quote": "set to be released on Oct. 9, 2021, the same day as the world premiere performance scheduled to take place in Bonn, Germany" }, { "kind": "press release", "citation": "Magyar Telekom (2021). Algorithms fine-tuned - The digital journey taken by Beethoven's unfinished Tenth Symphony. Telekom Hungary press release; issued by the project's funder, not by the model's developer.", "title": "Algorithms fine-tuned - The digital journey taken by Beethoven's unfinished Tenth Symphony", "url": "https://www.telekom.hu/about_us/press_room/press_releases/2021/october_1", "date": "2021-10-01", "written_by": "deployer", "quote": "The symphony created as a result of the unique cooperation between man and AI will premiere in Beethoven's birthplace, Bonn, Germany." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI-completed Beethoven Tenth premiered 9 October 2021 by Beethoven Orchester Bonn under Dirk Kaftan at the Telekom Forum, Bonn", "account": "On 9 October 2021 the Beethoven Orchester Bonn under Dirk Kaftan gave the world premiere of a Tenth Symphony completed with artificial intelligence. It was at the Telekom Forum in Bonn. Deutsche Telekom funded the project and organized the premiere, for Beethoven's 250th anniversary. Beethoven left only sketches for the work. A team led by musicologist Matthias Röder, with AI researcher Ahmed Elgammal and Mark Gotham, trained a model on Beethoven's output. It generated sketch continuations. Composer Walter Werzowa and musicologists chose and arranged the generated themes. Euronews reported on 13 October 2021 that the premiere had taken place in Bonn on 9 October. The benefit is a performed and recorded cultural artifact; the sources do not claim the result is Beethoven's." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Beethoven X AI generative music model (Elgammal/Playform AI team)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Ahmed Elgammal (Rutgers University / Playform AI) with Mark Gotham" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-completed Beethoven Tenth Symphony premiered by the Beethoven Orchester Bonn on 9 October 2021", "headline": "Beethoven X AI completes the Tenth Symphony; premiered in Bonn" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ebde78442c0bab57705858ad7212e1f16bc652cd48f496bb73fda3a155a75dc2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 9 October 2021 the Beethoven Orchester Bonn under Dirk Kaftan gave the world premiere of a Tenth Symphony completed with artificial intelligence. It was at the Telekom Forum in Bonn. Deutsche Telekom funded the project and organized the premiere, for Beethoven's 250th anniversary. Beethoven left only sketches for the work. A team led by musicologist Matthias Röder, with AI researcher Ahmed Elgammal and Mark Gotham, trained a model on Beethoven's output. It generated sketch continuations. Composer Walter Werzowa and musicologists chose and arranged the generated themes. Euronews reported on 13 October 2021 that the premiere had taken place in Bonn on 9 October. The benefit is a performed and recorded cultural artifact; the sources do not claim the result is Beethoven's.", "replication": { "produced_by": [ "Beethoven's surviving sketches for the Tenth Symphony", "A generative model trained on Beethoven's complete works", "Human selection, arrangement and orchestration by Werzowa and the musicologists", "A sponsor and a professional orchestra willing to premiere the result" ], "must_hold": [ "Enough sketch material and corpus to condition the model", "Human curation of generated material", "A performing institution programs the work" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0310", "title": "VA's REACH VET suicide-risk model is associated with fewer documented suicide attempts, admissions and ED visits among top-0.1%-risk veterans; no change in mortality", "summary": "VA-authored triple-difference cohort study (173,313 veterans): REACH VET inclusion linked to more completed visits and safety plans and fewer admissions, ED visits and attempts; no mortality effect.", "date_observed": "2021-10-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Department of Veterans Affairs (VA) announced REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) on 3 April 2017. It had begun as a pilot the previous October and was fully implemented across VA. It uses a predictive model on veterans' health records to identify those at statistically elevated risk of suicide and other adverse outcomes. Once a veteran is identified, a VA mental health or primary care provider reaches out. The provider reviews the condition and treatment plan and decides if enhanced care is needed. Nextgov/FCW (17 July 2025) says the model scans records monthly for the top 0.1% risk tier. It says the variable set was cut from 381 to 61 and about 30,000 veterans were identified in the first year. Nextgov (18 October 2024) gives about 6,700 veterans a month. McCarthy and colleagues published the evaluation in JAMA Network Open on 18 October 2021. They are at the VA Office of Mental Health and Suicide Prevention, which built and runs the program. It covered 173,313 individuals, 40,816 of them in the top 0.1% tier during REACH VET (March 2017 to December 2018). The pre-period (March 2014 to December 2015) had 36,604. Triple-difference analyses found REACH VET associated with more completed outpatient appointments (adjusted triple difference 0.31; 95% CI 0.06 to 0.55). The proportion with new safety plans rose (0.08; 0.06 to 0.10). Mental health admissions (-0.08; -0.10 to -0.05), emergency department (ED) visits (-0.03; -0.06 to -0.01) and documented suicide attempts (-0.05; -0.06 to -0.03) fell. Subcohort analyses found no difference in suicide or all-cause mortality. Care evaluations of identified veterans rose from 46.1% to 87.5% over the period. A 2022 Psychiatric Services paper reports that by October 2020, 98% of identified veterans (N=6,579) were contacted and had care evaluated. Dent, Cooper and McCarthy (JAMA Network Open, 8 July 2025; 266,246 observations) again found no association with suicide, external-cause or all-cause mortality. The 6-month suicide hazard ratio was 1.18 (95% CI 0.83–1.69). Nextgov (2024) reports research finding the model “considered being a white man more of an indicator of potential self-harm than other factors”. The model omitted military sexual trauma; a REACH VET 2.0 adding such factors was planned for early 2025. The program's benefit is a cohort-level association over 2017–2018, not a dated event.", "category": "general benefit", "unexpected": false, "purpose": "Built to identify veterans in the top 0.1% of predicted suicide risk each month so that clinicians re-evaluate and enhance their care. The measured associations are that purpose.", "system": "REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) suicide-risk predictive model and care-enhancement program", "model_version": "Original 2017 model (381 variables reduced to 61, per Nextgov); REACH VET 2.0 announced for 2025", "developer": "US Department of Veterans Affairs, Office of Mental Health and Suicide Prevention", "deployer": "Veterans Health Administration, all facilities", "location": "United States", "domain": "Suicide prevention / mental health care", "segment": "Health-system predictive risk modeling and outreach", "benefit_type": "Improved Physical Health", "taxonomy_note": "The outcomes are mental-health care results (fewer attempts, admissions and ED visits) with no effect on deaths, from a VA-authored cohort study.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The 2021 study reports population-level reductions in documented suicide attempts, admissions and ED visits for identified veterans. No individual veteran's outcome is documented, and mortality did not differ in 2021 or 2025." }, { "group": "organizational", "depth": null, "reason": "Care evaluations rose from 46.1% to 87.5% of identified veterans and 98% were contacted by October 2020, per VA-authored papers. No independent audit was found." }, { "group": "societal", "depth": null, "reason": "Nextgov notes the top 0.1% tier covers only 2–3% of VA suicides and the model under-identified women; no population suicide-rate effect is shown." } ], "ai_role": { "status": "assessed", "statement": "The predictive model selects the monthly top 0.1% risk tier. Coordinators and providers then re-evaluate care and reach out, so the clinical response, not the model alone, produces any change. The evaluation is observational, uses a triple-difference design to handle non-parallel trends, and is authored by the VA office that built and runs REACH VET. It found no mortality association, replicated in 2025 by the same group. Independent reporting documents that the original model weighted being a white man heavily and omitted military sexual trauma." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "McCarthy JF, Cooper SA, Dent KR, Eagan AE, Matarazzo BB, Hannemann CM, Reger MA, Landes SJ, Trafton JA, Schoenbaum M, Katz IR (2021). Evaluation of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration. JAMA Network Open 4(10):e2129900 (PMC8524305). Authors at the VA office that runs the program.", "title": "Evaluation of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8524305/", "date": "2021-10-18", "written_by": "makers", "quote": "REACH VET implementation was associated with greater treatment engagement and new safety plan documentation and fewer mental health admissions, emergency department visits, and suicide attempts." }, { "kind": "peer-reviewed study", "citation": "Dent KR, Cooper S, McCarthy JF (2025). The REACH VET Program and Mortality Outcomes Among Veterans at High Risk of Suicide. JAMA Network Open, 8 July 2025 (PMC12238888). VA-authored.", "title": "The REACH VET Program and Mortality Outcomes Among Veterans at High Risk of Suicide", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12238888/", "date": "2025-07-08", "written_by": "makers", "quote": "inclusion in the REACH VET program was not associated with suicide mortality (6-month hazards ratio [HR], 1.18 [95% CI, 0.83-1.69]" }, { "kind": "peer-reviewed study", "citation": "Matarazzo BB, Eagan A, Landes SJ, et al. (2022/2023). The Veterans Health Administration REACH VET Program: Suicide Predictive Modeling in Practice. Psychiatric Services (first published 30 August 2022). VA-authored.", "title": "The Veterans Health Administration REACH VET Program: Suicide Predictive Modeling in Practice", "url": "https://europepmc.org/article/MED/36039552", "date": "2022-08-30", "written_by": "makers", "quote": "By October 2020, 98% of veterans identified (N=6,579) were contacted by providers and had their care evaluated." }, { "kind": "press release", "citation": "US Department of Veterans Affairs (2017). VA REACH VET Initiative Helps Save Veterans Lives: Program Signals When More Help Is Needed for At-risk Veterans. Press release, 3 April 2017.", "title": "VA REACH VET Initiative Helps Save Veterans Lives: Program Signals When More Help Is Needed for At-risk Veterans", "url": "https://news.va.gov/press-room/va-reach-vet-initiative-helps-save-veterans-lives-program-signals-when-more-help-is-needed-for-at-risk-veterans/", "date": "2017-04-03", "written_by": "makers", "quote": "Using a new predictive model, REACH VET analyzes existing data from Veterans' health records to identify those at a statistically elevated risk for suicide, hospitalization, illness or other adverse outcomes." }, { "kind": "news report", "citation": "Graham E (2025). Inside VA's yearslong AI effort to uncover veterans at high risk of suicide. Nextgov/FCW, 17 July 2025.", "title": "Inside VA's yearslong AI effort to uncover veterans at high risk of suicide", "url": "https://www.nextgov.com/artificial-intelligence/2025/07/inside-vas-yearslong-ai-effort-uncover-veterans-high-risk-suicide/406781/", "date": "2025-07-17", "written_by": "independent", "quote": "It's going to go something like, 'you've been identified as being at elevated risk for suicide at the present time; we'd like to offer you resources.'" }, { "kind": "news report", "citation": "Graham E (2024). VA is updating its AI suicide risk model to reach more women. Nextgov/FCW, 18 October 2024.", "title": "VA is updating its AI suicide risk model to reach more women", "url": "https://www.nextgov.com/artificial-intelligence/2024/10/va-updating-its-ai-suicide-risk-model-reach-more-women/400377/", "date": "2024-10-18", "written_by": "independent", "quote": "considered being a white man more of an indicator of potential self-harm than other factors" } ], "replication": { "produced_by": [ "A predictive model run monthly on VHA electronic health records to rank patients and select the top 0.1% risk tier", "Facility REACH VET coordinators and providers who acknowledge the list, evaluate care, document safety plans and attempt outreach", "A national health system with the data, dashboards and metrics to implement the program at every facility" ], "must_hold": [ "Providers act on the list: care evaluations rose from 46.1% to 87.5% of identified veterans between March 2017 and December 2018", "The model's variables fit the population; the original model under-weighted factors relevant to women veterans, per Nextgov", "Outcome ascertainment is comparable across periods; the authors note that closer attention may increase recorded attempts" ], "echoes": [ { "date": "2025-07-08", "setting": "VA-authored cohort study of 266,246 observations testing suicide, external-cause and all-cause mortality after REACH VET inclusion; found no association at 6, 12 or 24 months (a different endpoint from the 2021 benefit)", "model_version": "Original REACH VET model", "outcome": "unknown", "source": "Dent KR, Cooper S, McCarthy JF (2025) JAMA Netw Open, https://pmc.ncbi.nlm.nih.gov/articles/PMC12238888/" }, { "date": "2025-01-01", "setting": "REACH VET 2.0 adding military sexual trauma and intimate partner violence as risk factors, planned for early 2025 deployment per Nextgov (date is the start of the planned window); no outcome reported", "model_version": "REACH VET 2.0", "outcome": "unknown", "source": "Nextgov/FCW, 18 October 2024 and 17 July 2025" } ] }, "paired_incident": null, "headline": "REACH VET tied to fewer suicide attempts, not deaths", "metric": "documented suicide attempts (-0.05; 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a VA cohort study published 8 July 2025 found no association between REACH VET inclusion and suicide or all-cause mortality, in line with the 2021 evaluation's mortality subanalyses.", "quote": "Each month, REACH VET uses the 61 variables to scan the electronic health records of veterans engaged with the Veterans Health Administration to identify those who are in the top 0.1% of suicide risk.", "url": "https://www.nextgov.com/artificial-intelligence/2025/07/inside-vas-yearslong-ai-effort-uncover-veterans-high-risk-suicide/406781/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; 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2025 found no association between REACH VET inclusion and suicide or all-cause mortality, in line with the 2021 evaluation's mortality subanalyses.", "quote": "Each month, REACH VET uses the 61 variables to scan the electronic health records of veterans engaged with the Veterans Health Administration to identify those who are in the top 0.1% of suicide risk.", "url": "https://www.nextgov.com/artificial-intelligence/2025/07/inside-vas-yearslong-ai-effort-uncover-veterans-high-risk-suicide/406781/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0310" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The outcomes are mental-health care results (fewer attempts, admissions and ED visits) with no effect on deaths, from a VA-authored cohort study." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Department of Veterans Affairs (VA) announced REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) on 3 April 2017. It had begun as a pilot the previous October and was fully implemented across VA. It uses a predictive model on veterans' health records to identify those at statistically elevated risk of suicide and other adverse outcomes. Once a veteran is identified, a VA mental health or primary care provider reaches out. The provider reviews the condition and treatment plan and decides if enhanced care is needed. Nextgov/FCW (17 July 2025) says the model scans records monthly for the top 0.1% risk tier. It says the variable set was cut from 381 to 61 and about 30,000 veterans were identified in the first year. Nextgov (18 October 2024) gives about 6,700 veterans a month. McCarthy and colleagues published the evaluation in JAMA Network Open on 18 October 2021. They are at the VA Office of Mental Health and Suicide Prevention, which built and runs the program. It covered 173,313 individuals, 40,816 of them in the top 0.1% tier during REACH VET (March 2017 to December 2018). The pre-period (March 2014 to December 2015) had 36,604. Triple-difference analyses found REACH VET associated with more completed outpatient appointments (adjusted triple difference 0.31; 95% CI 0.06 to 0.55). The proportion with new safety plans rose (0.08; 0.06 to 0.10). Mental health admissions (-0.08; -0.10 to -0.05), emergency department (ED) visits (-0.03; -0.06 to -0.01) and documented suicide attempts (-0.05; -0.06 to -0.03) fell. Subcohort analyses found no difference in suicide or all-cause mortality. Care evaluations of identified veterans rose from 46.1% to 87.5% over the period. A 2022 Psychiatric Services paper reports that by October 2020, 98% of identified veterans (N=6,579) were contacted and had care evaluated. Dent, Cooper and McCarthy (JAMA Network Open, 8 July 2025; 266,246 observations) again found no association with suicide, external-cause or all-cause mortality. The 6-month suicide hazard ratio was 1.18 (95% CI 0.83–1.69). Nextgov (2024) reports research finding the model “considered being a white man more of an indicator of potential self-harm than other factors”. The model omitted military sexual trauma; a REACH VET 2.0 adding such factors was planned for early 2025. The program's benefit is a cohort-level association over 2017–2018, not a dated event.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The 2021 study reports population-level reductions in documented suicide attempts, admissions and ED visits for identified veterans. No individual veteran's outcome is documented, and mortality did not differ in 2021 or 2025." }, { "group": "organizational", "reason": "Care evaluations rose from 46.1% to 87.5% of identified veterans and 98% were contacted by October 2020, per VA-authored papers. No independent audit was found." }, { "group": "societal", "reason": "Nextgov notes the top 0.1% tier covers only 2–3% of VA suicides and the model under-identified women; no population suicide-rate effect is shown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to identify veterans in the top 0.1% of predicted suicide risk each month so that clinicians re-evaluate and enhance their care. The measured associations are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to identify veterans in the top 0.1% of predicted suicide risk each month so that clinicians re-evaluate and enhance their care. 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Nextgov/FCW, 17 July 2025.", "title": "Inside VA's yearslong AI effort to uncover veterans at high risk of suicide", "url": "https://www.nextgov.com/artificial-intelligence/2025/07/inside-vas-yearslong-ai-effort-uncover-veterans-high-risk-suicide/406781/", "date": "2025-07-17", "written_by": "independent", "quote": "It's going to go something like, 'you've been identified as being at elevated risk for suicide at the present time; we'd like to offer you resources.'" }, { "kind": "news report", "citation": "Graham E (2024). VA is updating its AI suicide risk model to reach more women. Nextgov/FCW, 18 October 2024.", "title": "VA is updating its AI suicide risk model to reach more women", "url": "https://www.nextgov.com/artificial-intelligence/2024/10/va-updating-its-ai-suicide-risk-model-reach-more-women/400377/", "date": "2024-10-18", "written_by": "independent", "quote": "considered being a white man more of an indicator of potential self-harm than other factors" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0310-source-0001", "AIBD-0310-source-0002", "AIBD-0310-source-0003", "AIBD-0310-source-0004", "AIBD-0310-source-0005", "AIBD-0310-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "McCarthy JF, Cooper SA, Dent KR, Eagan AE, Matarazzo BB, Hannemann CM, Reger MA, Landes SJ, Trafton JA, Schoenbaum M, Katz IR (2021). 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VA-authored.", "title": "The Veterans Health Administration REACH VET Program: Suicide Predictive Modeling in Practice", "url": "https://europepmc.org/article/MED/36039552", "date": "2022-08-30", "written_by": "makers", "quote": "By October 2020, 98% of veterans identified (N=6,579) were contacted by providers and had their care evaluated." }, { "kind": "press release", "citation": "US Department of Veterans Affairs (2017). VA REACH VET Initiative Helps Save Veterans Lives: Program Signals When More Help Is Needed for At-risk Veterans. Press release, 3 April 2017.", "title": "VA REACH VET Initiative Helps Save Veterans Lives: Program Signals When More Help Is Needed for At-risk Veterans", "url": "https://news.va.gov/press-room/va-reach-vet-initiative-helps-save-veterans-lives-program-signals-when-more-help-is-needed-for-at-risk-veterans/", "date": "2017-04-03", "written_by": "makers", "quote": "Using a new predictive model, REACH VET analyzes existing data from Veterans' health records to identify those at a statistically elevated risk for suicide, hospitalization, illness or other adverse outcomes." }, { "kind": "news report", "citation": "Graham E (2025). Inside VA's yearslong AI effort to uncover veterans at high risk of suicide. Nextgov/FCW, 17 July 2025.", "title": "Inside VA's yearslong AI effort to uncover veterans at high risk of suicide", "url": "https://www.nextgov.com/artificial-intelligence/2025/07/inside-vas-yearslong-ai-effort-uncover-veterans-high-risk-suicide/406781/", "date": "2025-07-17", "written_by": "independent", "quote": "It's going to go something like, 'you've been identified as being at elevated risk for suicide at the present time; we'd like to offer you resources.'" }, { "kind": "news report", "citation": "Graham E (2024). VA is updating its AI suicide risk model to reach more women. Nextgov/FCW, 18 October 2024.", "title": "VA is updating its AI suicide risk model to reach more women", "url": "https://www.nextgov.com/artificial-intelligence/2024/10/va-updating-its-ai-suicide-risk-model-reach-more-women/400377/", "date": "2024-10-18", "written_by": "independent", "quote": "considered being a white man more of an indicator of potential self-harm than other factors" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "VA-authored triple-difference cohort study (173,313 veterans): REACH VET inclusion linked to more completed visits and safety plans and fewer admissions, ED visits and attempts; no mortality effect.", "account": "The Department of Veterans Affairs (VA) announced REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) on 3 April 2017. It had begun as a pilot the previous October and was fully implemented across VA. It uses a predictive model on veterans' health records to identify those at statistically elevated risk of suicide and other adverse outcomes. Once a veteran is identified, a VA mental health or primary care provider reaches out. The provider reviews the condition and treatment plan and decides if enhanced care is needed. Nextgov/FCW (17 July 2025) says the model scans records monthly for the top 0.1% risk tier. It says the variable set was cut from 381 to 61 and about 30,000 veterans were identified in the first year. Nextgov (18 October 2024) gives about 6,700 veterans a month. McCarthy and colleagues published the evaluation in JAMA Network Open on 18 October 2021. They are at the VA Office of Mental Health and Suicide Prevention, which built and runs the program. It covered 173,313 individuals, 40,816 of them in the top 0.1% tier during REACH VET (March 2017 to December 2018). The pre-period (March 2014 to December 2015) had 36,604. Triple-difference analyses found REACH VET associated with more completed outpatient appointments (adjusted triple difference 0.31; 95% CI 0.06 to 0.55). The proportion with new safety plans rose (0.08; 0.06 to 0.10). Mental health admissions (-0.08; -0.10 to -0.05), emergency department (ED) visits (-0.03; -0.06 to -0.01) and documented suicide attempts (-0.05; -0.06 to -0.03) fell. Subcohort analyses found no difference in suicide or all-cause mortality. Care evaluations of identified veterans rose from 46.1% to 87.5% over the period. A 2022 Psychiatric Services paper reports that by October 2020, 98% of identified veterans (N=6,579) were contacted and had care evaluated. Dent, Cooper and McCarthy (JAMA Network Open, 8 July 2025; 266,246 observations) again found no association with suicide, external-cause or all-cause mortality. The 6-month suicide hazard ratio was 1.18 (95% CI 0.83–1.69). Nextgov (2024) reports research finding the model “considered being a white man more of an indicator of potential self-harm than other factors”. The model omitted military sexual trauma; a REACH VET 2.0 adding such factors was planned for early 2025. The program's benefit is a cohort-level association over 2017–2018, not a dated event." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model ranked patients by predicted suicide risk for clinical follow-up." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The original 2017 REACH VET model selected 61 variables from 381. The later REACH VET 2.0 announcement concerns a different version." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Original 2017 model (381 variables reduced to 61, per Nextgov); REACH VET 2.0 announced for 2025" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The original model introduced in 2017.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) suicide-risk predictive model and care-enhancement program" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "US Department of Veterans Affairs, Office of Mental Health and Suicide Prevention" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "VA's REACH VET suicide-risk model is associated with fewer documented suicide attempts, admissions and ED visits among top-0.1%-risk veterans; no change in mortality", "headline": "REACH VET tied to fewer suicide attempts, not deaths" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a48d242a22658ffd883e03ccffe0dc3a534a068b283614f69edab5a0e7e95dda" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Department of Veterans Affairs (VA) announced REACH VET (Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment) on 3 April 2017. It had begun as a pilot the previous October and was fully implemented across VA. It uses a predictive model on veterans' health records to identify those at statistically elevated risk of suicide and other adverse outcomes. Once a veteran is identified, a VA mental health or primary care provider reaches out. The provider reviews the condition and treatment plan and decides if enhanced care is needed. Nextgov/FCW (17 July 2025) says the model scans records monthly for the top 0.1% risk tier. It says the variable set was cut from 381 to 61 and about 30,000 veterans were identified in the first year. Nextgov (18 October 2024) gives about 6,700 veterans a month. McCarthy and colleagues published the evaluation in JAMA Network Open on 18 October 2021. They are at the VA Office of Mental Health and Suicide Prevention, which built and runs the program. It covered 173,313 individuals, 40,816 of them in the top 0.1% tier during REACH VET (March 2017 to December 2018). The pre-period (March 2014 to December 2015) had 36,604. Triple-difference analyses found REACH VET associated with more completed outpatient appointments (adjusted triple difference 0.31; 95% CI 0.06 to 0.55). The proportion with new safety plans rose (0.08; 0.06 to 0.10). Mental health admissions (-0.08; -0.10 to -0.05), emergency department (ED) visits (-0.03; -0.06 to -0.01) and documented suicide attempts (-0.05; -0.06 to -0.03) fell. Subcohort analyses found no difference in suicide or all-cause mortality. Care evaluations of identified veterans rose from 46.1% to 87.5% over the period. A 2022 Psychiatric Services paper reports that by October 2020, 98% of identified veterans (N=6,579) were contacted and had care evaluated. Dent, Cooper and McCarthy (JAMA Network Open, 8 July 2025; 266,246 observations) again found no association with suicide, external-cause or all-cause mortality. The 6-month suicide hazard ratio was 1.18 (95% CI 0.83–1.69). Nextgov (2024) reports research finding the model “considered being a white man more of an indicator of potential self-harm than other factors”. The model omitted military sexual trauma; a REACH VET 2.0 adding such factors was planned for early 2025. The program's benefit is a cohort-level association over 2017–2018, not a dated event.", "replication": { "produced_by": [ "A predictive model run monthly on VHA electronic health records to rank patients and select the top 0.1% risk tier", "Facility REACH VET coordinators and providers who acknowledge the list, evaluate care, document safety plans and attempt outreach", "A national health system with the data, dashboards and metrics to implement the program at every facility" ], "must_hold": [ "Providers act on the list: care evaluations rose from 46.1% to 87.5% of identified veterans between March 2017 and December 2018", "The model's variables fit the population; the original model under-weighted factors relevant to women veterans, per Nextgov", "Outcome ascertainment is comparable across periods; the authors note that closer attention may increase recorded attempts" ], "echoes": [ { "date": "2025-07-08", "setting": "VA-authored cohort study of 266,246 observations testing suicide, external-cause and all-cause mortality after REACH VET inclusion; found no association at 6, 12 or 24 months (a different endpoint from the 2021 benefit)", "model_version": "Original REACH VET model", "outcome": "unknown", "source": "Dent KR, Cooper S, McCarthy JF (2025) JAMA Netw Open, https://pmc.ncbi.nlm.nih.gov/articles/PMC12238888/" }, { "date": "2025-01-01", "setting": "REACH VET 2.0 adding military sexual trauma and intimate partner violence as risk factors, planned for early 2025 deployment per Nextgov (date is the start of the planned window); no outcome reported", "model_version": "REACH VET 2.0", "outcome": "unknown", "source": "Nextgov/FCW, 18 October 2024 and 17 July 2025" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0043", "title": "AI-based structure prediction doubled structural coverage of the human nuclear pore complex scaffold", "summary": "Researchers combined AI predictions with electron-microscopy maps to model more than 90% of the human nuclear pore scaffold.", "date_observed": "2021-10-27", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Researchers at EMBL, the Max Planck Institute of Biophysics, and collaborating institutions used AlphaFold and RoseTTAfold to predict structures of nuclear-pore proteins. They used ColabFold to model complexes and fitted the predictions to electron-microscopy maps. Their model covered more than 90% of the scaffold, roughly twice the coverage of the previous model. The authors checked the predictions against existing and new experimental structures. The work appeared as a preprint in 2021 and in Science in June 2022.", "category": "benefit created", "unexpected": false, "purpose": "Predict protein and subcomplex structures to enable integrative modeling of a 120-MDa macromolecular machine that resisted conventional structural biology.", "system": "AlphaFold and RoseTTAfold for protein structures, with ColabFold for protein complexes", "model_version": null, "developer": "DeepMind (AlphaFold); University of Washington and Harvard University researchers (RoseTTAFold)", "deployer": "EMBL Heidelberg, Max Planck Institute of Biophysics, EMBL Hamburg (Beck, Hummer, Kosinski groups)", "location": "Heidelberg, Frankfurt am Main and Hamburg, Germany", "domain": "Structural and cell biology", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The collaborating laboratories obtained a model that roughly doubles structural coverage of the human NPC scaffold. That is a material advance for those groups' research programs." }, { "group": "societal", "depth": 2, "reason": "A 70-MDa atomically resolved model covering over 90% of the scaffold is a durable public resource for nuclear transport research. The source reports no direct patient or population benefit." } ], "ai_role": { "status": "assessed", "statement": "AI structure prediction generated the nucleoporin and subcomplex models that formed the input to integrative modeling. The authors state that the predictions were benchmarked against existing and new experimental structures. The resulting model was validated against earlier and new experimental data, so the AI output was independently checked rather than accepted as given." }, "evidence": [ { "kind": "preprint", "citation": "Mosalaganti S, Obarska-Kosinska A, Siggel M, et al. (2021). Artificial intelligence reveals nuclear pore complexity. bioRxiv 2021.10.26.465776, posted 27 October 2021.", "title": "Artificial intelligence reveals nuclear pore complexity", "url": "https://www.biorxiv.org/content/10.1101/2021.10.26.465776v1.full", "date": "2021-10-27", "written_by": "deployer", "quote": null }, { "kind": "peer-reviewed study", "citation": "Mosalaganti S, Obarska-Kosinska A, Siggel M, et al. (2022). AI-based structure prediction empowers integrative structural analysis of human nuclear pores. Science.", "title": "AI-based structure prediction empowers integrative structural analysis of human nuclear pores", "url": "https://doi.org/10.1126/science.abm9506", "date": "2022-06-10", "written_by": "deployer", "quote": "we used artificial intelligence (AI)-based prediction to generate an extensive repertoire of structural models of human NUPs and their subcomplexes" }, { "kind": "report", "citation": "Google DeepMind. “AlphaFold.” Timeline of a breakthrough, entries for 2020 and 2021.", "title": "AlphaFold", "url": "https://deepmind.google/science/alphafold/", "date": null, "written_by": "makers", "quote": null }, { "kind": "other", "citation": "Baek, Minkyung, Frank DiMaio, Ivan Anishchenko, Justas Dauparas, Sergey Ovchinnikov, Jue Wang, and David Baker. “RoseTTAFold: The First Release of RoseTTAFold.” Version 1.0.0. Zenodo, July 3, 2021. doi:10.5281/zenodo.5068265.", "title": "RoseTTAFold: The first release of RoseTTAFold", "url": "https://zenodo.org/records/5068265", "date": "2021-07-03", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Cryo-electron tomographic maps of the human nuclear pore complex in two states", "AI structure predictions for nucleoporins and subcomplexes, benchmarked against experimental structures", "Integrative modeling by groups holding prior structural data on the complex" ], "must_hold": [ "Cryo-electron tomographic maps of sufficient resolution for fitting", "Nucleoporin sequences and homologues available for prediction", "Independent experimental structures available for benchmarking" ], "echoes": [] }, "paired_incident": null, "headline": "AlphaFold models cover over 90% of the human NPC scaffold", "metric": "covers more than 90% of the NPC scaffold, roughly doubling previous structural coverage", "comparator": { "against": "the previous structural model of the human NPC scaffold", "before": "16 Nups and 35 MDa (46% of the scaffold) of the previous model", "after": "25 out of ~30 Nups, and account for 70 MDa of the molecular weight of the NPC (>90% of the scaffold molecular weight)", "basis": "measured", "quote": "The resulting models (Fig. 1) include 25 out of ~30 Nups, and account for 70 MDa of the molecular weight of the NPC (>90% of the scaffold molecular weight) in comparison to 16 Nups and 35 MDa (46% of the scaffold) of the previous model, and largely account for the EM density observed in the constricted and dilated states.", "url": "https://www.biorxiv.org/content/10.1101/2021.10.26.465776v1.full" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unverified AlphaFold/DeepMind attribution from the title, system, developer and the account's last sentence in favor of the source's own wording “AI-based structure prediction”, because the abstract names no tool and the full text could not be read (science.org returned HTTP 403 and the DESY and Goethe University Frankfurt repository copies were unreadable), and added Hamburg to the location because the Kosinski group's affiliations (EMBL Hamburg, Centre for Structural Systems Biology) are in Hamburg.", "source": "Mosalaganti S, et al. Science 2022, abstract and author affiliations via Europe PMC (PMID 35679397; https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI:10.1126/science.abm9506&resultType=core&format=json)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/European_Molecular_Biology_Laboratory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified AlphaFold, RoseTTAfold, and ColabFold in the authors’ full preprint. Replaced the earlier abstract-only uncertainty and separated model names from software releases. Added original developer documentation for provider attribution.", "source": "https://www.researchgate.net/publication/355709263_Artificial_intelligence_reveals_nuclear_pore_complexity", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Aligned the retained sources with their reviewed lead and confirmed the first preprint publication date from bioRxiv. Preserved the published version and its access limitation.", "source": "https://www.biorxiv.org/content/10.1101/2021.10.26.465776v1", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' report, the makers' other, the deployer's peer-reviewed study and the deployer's preprint. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0043", "catalog_version": "1.0.0", "source_fingerprint": "b7d515a86a02e4f60d9afda67041f64c5750f540c2e81180a85a045ef407ff3f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0043-source-0001", "AIBD-0043-source-0002", "AIBD-0043-source-0003", "AIBD-0043-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "DeepMind developed AlphaFold. 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They used ColabFold to model complexes and fitted the predictions to electron-microscopy maps. Their model covered more than 90% of the scaffold, roughly twice the coverage of the previous model. The authors checked the predictions against existing and new experimental structures. 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It applied Exomiser's phenotype-based prioritization to genomes from 2,183 families in the English National Health Service (NHS). Genetic diagnoses were found in 25% of probands, rising to 35% for monogenic disorders. 92% of the 490 diagnoses came from applied gene panels or Exomiser's top five candidates. Clinicians reported 134 of 533 genetic diagnoses, 25%, were of immediate clinical actionability, including medication changes, surveillance recommendations, clinical trial eligibility and reproductive planning.", "category": "general benefit", "unexpected": false, "purpose": "Score and rank candidate causative variants against patient phenotypes to make genome-scale rare-disease diagnosis tractable for clinical teams.", "system": "Exomiser phenotype-driven variant prioritization (machine-learning-assisted scoring and ranking)", "model_version": null, "developer": "Not named in the cited sources; the pilot's phenotype-based prioritization analysis was led by Damian Smedley's team at Queen Mary University of London and Genomics England.", "deployer": "Genomics England and NHS Genomic Medicine Centers", "location": "England, United Kingdom", "domain": "Clinical genomics / rare disease diagnosis", "segment": "Families with undiagnosed rare disease in a national health system", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Clinicians reported that 134 of 533 genetic diagnoses (25%) were of immediate clinical actionability, including medication changes and surveillance. That is a cohort figure and no individually attributable changed outcome is cited." }, { "group": "organizational", "depth": null, "reason": "Exomiser's top five candidates together with applied panels accounted for 92% of the 490 diagnoses. That is an aggregate reduction in manual interpretation burden across the pilot rather than a discrete organizational event." }, { "group": "societal", "depth": null, "reason": "A 25% diagnostic yield across 2,183 families is reported for a national health-system pilot rather than population-wide deployment." } ], "ai_role": { "status": "assessed", "statement": "Exomiser scored and ranked candidate variants against each proband's phenotype. The pilot reports that diagnoses were detected in 77% of top-ranked candidate variants and that panels and Exomiser's top five were complementary. Clinical confirmation and reporting were performed by NHS diagnostic laboratories and clinicians, not by the software. Neither cited source says who developed Exomiser. The pilot's prioritization analysis was led by Damian Smedley's team at Queen Mary University of London and Genomics England, who are among the paper's authors. An independent evaluation is cited alongside it." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "100,000 Genomes Project Pilot Investigators; Smedley D, Smith KR, Martin A, et al. (2021). 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report. N Engl J Med.", "title": "100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "date": "2021-11-11", "written_by": "deployer", "quote": "With the use of phenotype-based prioritization with the Exomiser to score and rank the most likely causative variants, diagnoses were detected in 77% of the top-ranked candidate variants." }, { "kind": "peer-reviewed study", "citation": "Cooperstein IB, Marwaha S, Ward A, et al. (2025). An optimized variant prioritization process for rare disease diagnostics: recommendations for Exomiser and Genomiser. Genome Med.", "title": "An optimized variant prioritization process for rare disease diagnostics", "url": "https://doi.org/10.1186/s13073-025-01546-1", "date": "2025-10-21", "written_by": "independent", "quote": "the percentage of coding diagnostic variants ranked within the top 10 candidates increased from 49.7% to 85.5%" } ], "replication": { "produced_by": [ "Genome sequencing with family data across a national pilot", "Structured phenotype terms of adequate quality", "Exomiser ranking used alongside applied gene panels, with clinical review before reporting" ], "must_hold": [ "Genome or exome sequencing with family data where available", "Structured HPO phenotype terms of adequate quality", "Clinical review of ranked candidates before reporting" ], "echoes": [ { "date": "2025-10-21", "setting": "Undiagnosed Diseases Network, 386 diagnosed probands, University of Utah and Stanford", "model_version": "Exomiser/Genomiser", "outcome": "recurred", "source": "Cooperstein IB, et al. Genome Med 2025. doi 10.1186/s13073-025-01546-1" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "535", "title": "COVID-19 Detection and Prognostication Models Allegedly Flagged for Methodological Flaws and Underlying Biases", "url": "https://incidentdatabase.ai/cite/535", "severity": null, "group": "societal", "basis": "Both are machine-learning diagnostic decision-support models relied on across health systems; the COVID detection and prognostication models proved unfit for clinical use, harming COVID patients and their healthcare providers." }, "headline": "Exomiser helps diagnose 25% of 2,183 probands in the NHS pilot", "metric": "Genetic diagnoses were found in 25% of probands, rising to 35% for monogenic disorders", "comparator": { "against": "the virtual panel-based pipeline (applied gene panels) alone", "before": "A total of 322 (66%) of the 490 diagnoses that were based on SNVs or indels from the genomes were made with the virtual panel–based pipeline", "after": "diagnoses were detected in 77% of the top-ranked candidate variants, in 86% of the top three candidates, and in 88% of the top five candidates", "basis": "measured", "quote": "With the use of phenotype-based prioritization with the Exomiser to score and rank the most likely causative variants, diagnoses were detected in 77% of the top-ranked candidate variants, in 86% of the top three candidates, and in 88% of the top five candidates (Fig. 2D). Use of the Exomiser and applied panels was complementary — 92% of the 490 diagnoses were made with the applied panels or the Exomizer top five candidates (last blue bar in Fig. 2D).", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/" }, "later": null, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 535 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/535", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the observation and evidence dates to the paper's publication date of 11 November 2021, restored the “Preliminary Report” subtitle to the evidence title, moved the record to general benefit without an event with all three depths unset because everything it reports is aggregate, and stopped naming Exomiser's developer, because neither cited source says who built the tool.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.genomicsengland.co.uk/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study and the deployer's peer-reviewed study. 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diagnosis pilot appeared in the New England Journal of Medicine, 11 November 2021. It applied Exomiser's phenotype-based prioritization to genomes from 2,183 families in the English National Health Service (NHS). Genetic diagnoses were found in 25% of probands, rising to 35% for monogenic disorders. 92% of the 490 diagnoses came from applied gene panels or Exomiser's top five candidates. Clinicians reported 134 of 533 genetic diagnoses, 25%, were of immediate clinical actionability, including medication changes, surveillance recommendations, clinical trial eligibility and reproductive planning.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Clinicians reported that 134 of 533 genetic diagnoses (25%) were of immediate clinical actionability, including medication changes and surveillance. That is a cohort figure and no individually attributable changed outcome is cited." }, { "group": "organizational", "reason": "Exomiser's top five candidates together with applied panels accounted for 92% of the 490 diagnoses. That is an aggregate reduction in manual interpretation burden across the pilot rather than a discrete organizational event." }, { "group": "societal", "reason": "A 25% diagnostic yield across 2,183 families is reported for a national health-system pilot rather than population-wide deployment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Score and rank candidate causative variants against patient phenotypes to make genome-scale rare-disease diagnosis tractable for clinical teams." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "England, United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Score and rank candidate causative variants against patient phenotypes to make genome-scale rare-disease diagnosis tractable for clinical teams." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-11-11", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 535 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/535", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the observation and evidence dates to the paper's publication date of 11 November 2021, restored the “Preliminary Report” subtitle to the evidence title, moved the record to general benefit without an event with all three depths unset because everything it reports is aggregate, and stopped naming Exomiser's developer, because neither cited source says who built the tool.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.genomicsengland.co.uk/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Genome sequencing with family data across a national pilot", "Structured phenotype terms of adequate quality", "Exomiser ranking used alongside applied gene panels, with clinical review before reporting" ], "must_hold": [ "Genome or exome sequencing with family data where available", "Structured HPO phenotype terms of adequate quality", "Clinical review of ranked candidates before reporting" ], "echoes": [ { "date": "2025-10-21", "setting": "Undiagnosed Diseases Network, 386 diagnosed probands, University of Utah and Stanford", "model_version": "Exomiser/Genomiser", "outcome": "recurred", "source": "Cooperstein IB, et al. Genome Med 2025. doi 10.1186/s13073-025-01546-1" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Genome sequencing with family data across a national pilot", "Structured phenotype terms of adequate quality", "Exomiser ranking used alongside applied gene panels, with clinical review before reporting" ], "must_hold": [ "Genome or exome sequencing with family data where available", "Structured HPO phenotype terms of adequate quality", "Clinical review of ranked candidates before reporting" ], "echoes": [ { "date": "2025-10-21", "setting": "Undiagnosed Diseases Network, 386 diagnosed probands, University of Utah and Stanford", "model_version": "Exomiser/Genomiser", "outcome": "recurred", "source": "Cooperstein IB, et al. Genome Med 2025. doi 10.1186/s13073-025-01546-1" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 535 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/535", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the observation and evidence dates to the paper's publication date of 11 November 2021, restored the “Preliminary Report” subtitle to the evidence title, moved the record to general benefit without an event with all three depths unset because everything it reports is aggregate, and stopped naming Exomiser's developer, because neither cited source says who built the tool.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.genomicsengland.co.uk/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Clinical genomics / rare disease diagnosis", "segment": "Families with undiagnosed rare disease in a national health system" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "100,000 Genomes Project Pilot Investigators; Smedley D, Smith KR, Martin A, et al. (2021). 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report. N Engl J Med.", "title": "100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "date": "2021-11-11", "written_by": "deployer", "quote": "With the use of phenotype-based prioritization with the Exomiser to score and rank the most likely causative variants, diagnoses were detected in 77% of the top-ranked candidate variants." }, { "kind": "peer-reviewed study", "citation": "Cooperstein IB, Marwaha S, Ward A, et al. (2025). An optimized variant prioritization process for rare disease diagnostics: recommendations for Exomiser and Genomiser. Genome Med.", "title": "An optimized variant prioritization process for rare disease diagnostics", "url": "https://doi.org/10.1186/s13073-025-01546-1", "date": "2025-10-21", "written_by": "independent", "quote": "the percentage of coding diagnostic variants ranked within the top 10 candidates increased from 49.7% to 85.5%" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0049-source-0001", "AIBD-0049-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "100,000 Genomes Project Pilot Investigators; Smedley D, Smith KR, Martin A, et al. (2021). 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report. N Engl J Med.", "title": "100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7613219/", "date": "2021-11-11", "written_by": "deployer", "quote": "With the use of phenotype-based prioritization with the Exomiser to score and rank the most likely causative variants, diagnoses were detected in 77% of the top-ranked candidate variants." }, { "kind": "peer-reviewed study", "citation": "Cooperstein IB, Marwaha S, Ward A, et al. (2025). An optimized variant prioritization process for rare disease diagnostics: recommendations for Exomiser and Genomiser. Genome Med.", "title": "An optimized variant prioritization process for rare disease diagnostics", "url": "https://doi.org/10.1186/s13073-025-01546-1", "date": "2025-10-21", "written_by": "independent", "quote": "the percentage of coding diagnostic variants ranked within the top 10 candidates increased from 49.7% to 85.5%" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Phenotype-driven ML prioritization helped diagnose 25% of 2,183 probands in the NHS pilot; a quarter of diagnoses were immediately actionable.", "account": "The 100,000 Genomes Project rare-disease diagnosis pilot appeared in the New England Journal of Medicine, 11 November 2021. It applied Exomiser's phenotype-based prioritization to genomes from 2,183 families in the English National Health Service (NHS). Genetic diagnoses were found in 25% of probands, rising to 35% for monogenic disorders. 92% of the 490 diagnoses came from applied gene panels or Exomiser's top five candidates. Clinicians reported 134 of 533 genetic diagnoses, 25%, were of immediate clinical actionability, including medication changes, surveillance recommendations, clinical trial eligibility and reproductive planning." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Exomiser phenotype-driven variant prioritization (machine-learning-assisted scoring and ranking)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the cited sources; the pilot's phenotype-based prioritization analysis was led by Damian Smedley's team at Queen Mary University of London and Genomics England." } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Exomiser prioritization contributed to rare-disease diagnoses in the 100,000 Genomes Project pilot", "headline": "Exomiser helps diagnose 25% of 2,183 probands in the NHS pilot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a1b860f3f4af8025dd5dd72250432aae62ef19eadc064e85d7a3d6dbb464a664" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The 100,000 Genomes Project rare-disease diagnosis pilot appeared in the New England Journal of Medicine, 11 November 2021. It applied Exomiser's phenotype-based prioritization to genomes from 2,183 families in the English National Health Service (NHS). Genetic diagnoses were found in 25% of probands, rising to 35% for monogenic disorders. 92% of the 490 diagnoses came from applied gene panels or Exomiser's top five candidates. Clinicians reported 134 of 533 genetic diagnoses, 25%, were of immediate clinical actionability, including medication changes, surveillance recommendations, clinical trial eligibility and reproductive planning.", "replication": { "produced_by": [ "Genome sequencing with family data across a national pilot", "Structured phenotype terms of adequate quality", "Exomiser ranking used alongside applied gene panels, with clinical review before reporting" ], "must_hold": [ "Genome or exome sequencing with family data where available", "Structured HPO phenotype terms of adequate quality", "Clinical review of ranked candidates before reporting" ], "echoes": [ { "date": "2025-10-21", "setting": "Undiagnosed Diseases Network, 386 diagnosed probands, University of Utah and Stanford", "model_version": "Exomiser/Genomiser", "outcome": "recurred", "source": "Cooperstein IB, et al. Genome Med 2025. doi 10.1186/s13073-025-01546-1" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0339", "title": "NHS AI Lab Skunkworks and Faculty build a 14-week proof-of-concept AI bed-allocation tool for Kettering General Hospital; tested and reviewed, released as open source, not deployed", "summary": "14-week NHS AI Skunkworks/Faculty proof of concept (2021) forecasting demand and suggesting beds at Kettering General Hospital; tested by the hospital, open-sourced, not in live use.", "date_observed": "2021-12-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Kettering General Hospital, a National Health Service (NHS) foundation trust, asked the NHS AI Lab Skunkworks team (NHSX) for support exploring AI for bed management. The Skunkworks funded a 14-week project with Faculty, an applied AI supplier selected through the Home Office's Accelerated Capability Environment (ACE). The team used five years of pseudonymized patient administration data and one to two years of patient-flow data. It built a virtual hospital and a Bayesian model forecasting how many patients with given characteristics would present. It compared greedy allocation, Monte Carlo tree search and reinforcement learning for suggesting beds. Only the greedy agent was integrated into the web interface because of performance issues with the tree search. Reinforcement learning was not developed within the project. The resulting proof of concept was tested and reviewed by the hospital. A human scheduler still makes the final bed-allocation decision. It was released as open source on the NHSX GitHub pages. The README places it at Technology Readiness Level 4, not intended for deployment without further development and compliance with the UK Medical Device Regulations 2002. The NHS case study (10 December 2021) says the hospital would work with Faculty to bid for funding to develop and operationalize the system. The GOV.UK ACE case study (12 October 2023) lists potential benefits only. No quantified results and no live use are documented, so this is a general benefit. The GitHub README gives a 12-week initiative launched in May 2021, while the NHS and GOV.UK pages say 14 weeks.", "category": "general benefit", "unexpected": false, "purpose": "Built to forecast bed demand and suggest bed allocations to the hospital's bed-management team. The proof of concept demonstrated that purpose without a measured outcome.", "system": "NHS AI Lab Skunkworks bed-allocation proof of concept (Bayesian demand forecasting with greedy and Monte Carlo tree search allocation agents and a web user interface)", "model_version": null, "developer": "Faculty (applied AI company) with NHS AI Lab Skunkworks (NHSX) and Kettering General Hospital, through the Home Office Accelerated Capability Environment", "deployer": "Kettering General Hospital NHS Foundation Trust (proof-of-concept testing only)", "location": "Kettering, Northamptonshire, England", "domain": "Healthcare operations: hospital bed management", "segment": "NHS acute hospital trust", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The intended good is bed allocation and demand forecasting; the proof of concept was tested but never deployed and reports no result.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No patient outcome is documented." }, { "group": "organizational", "depth": null, "reason": "The proof of concept was tested and reviewed but not used in live bed management." }, { "group": "societal", "depth": null, "reason": "The code is open source but no reuse outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The AI components forecast demand and suggest beds with an explanation, while the scheduler makes the final decision. Only the greedy agent was integrated, and the tool was tested and reviewed by the hospital rather than deployed. All read accounts come from the sponsoring public bodies (NHS AI Lab case study, GOV.UK ACE case study) and the NHSX GitHub README. So this is the deployer side describing its own pilot. No vendor-authored or independent evaluation is among the sources. The NHS page is available only through the Internet Archive because the transform.england.nhs.uk domain no longer resolves." }, "evidence": [ { "kind": "press release", "citation": "NHS Transformation Directorate, NHS AI Lab Skunkworks (2021). Improving hospital bed allocation using AI. Case study, 10 Dec 2021.", "title": "Improving hospital bed allocation using AI", "url": "https://web.archive.org/web/20231123150115/https://transform.england.nhs.uk/ai-lab/explore-all-resources/develop-ai/improving-hospital-bed-allocation-using-ai/", "date": "2021-12-10", "written_by": "makers", "quote": "The resulting proof of concept was then tested and reviewed by Kettering General Hospital." }, { "kind": "press release", "citation": "NHS Transformation Directorate (2021). Improving hospital bed allocation using AI, section 'What next?'.", "title": "Improving hospital bed allocation using AI (What next?)", "url": "https://web.archive.org/web/20231123150115/https://transform.england.nhs.uk/ai-lab/explore-all-resources/develop-ai/improving-hospital-bed-allocation-using-ai/", "date": "2021-12-10", "written_by": "makers", "quote": "Kettering General Hospital will be working with Faculty to bid for further funding to develop and operationalise the bed allocation system." }, { "kind": "press release", "citation": "Accelerated Capability Environment, Home Office (2023). Using AI to improve patient bed allocation decisions in hospital. GOV.UK case study, 12 Oct 2023.", "title": "Using AI to improve patient bed allocation decisions in hospital", "url": "https://www.gov.uk/government/case-studies/using-ai-to-improve-patient-bed-allocation-decisions-in-hospital", "date": "2023-10-12", "written_by": "makers", "quote": "schedulers to make the final bed allocation decision" }, { "kind": "other", "citation": "NHSX / NHS AI Lab Skunkworks (n.d.). skunkworks-bed-allocation README. 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The Skunkworks funded a 14-week project with Faculty, an applied AI supplier selected through the Home Office's Accelerated Capability Environment (ACE). The team used five years of pseudonymized patient administration data and one to two years of patient-flow data. It built a virtual hospital and a Bayesian model forecasting how many patients with given characteristics would present. It compared greedy allocation, Monte Carlo tree search and reinforcement learning for suggesting beds. Only the greedy agent was integrated into the web interface because of performance issues with the tree search. Reinforcement learning was not developed within the project. The resulting proof of concept was tested and reviewed by the hospital. A human scheduler still makes the final bed-allocation decision. It was released as open source on the NHSX GitHub pages. The README places it at Technology Readiness Level 4, not intended for deployment without further development and compliance with the UK Medical Device Regulations 2002. The NHS case study (10 December 2021) says the hospital would work with Faculty to bid for funding to develop and operationalize the system. The GOV.UK ACE case study (12 October 2023) lists potential benefits only. No quantified results and no live use are documented, so this is a general benefit. The GitHub README gives a 12-week initiative launched in May 2021, while the NHS and GOV.UK pages say 14 weeks.", "replication": { "produced_by": [ "Five years of pseudonymized patient administration data and one to two years of patient-flow data under an information governance process", "A virtual hospital modeled on key wards with a Bayesian demand forecast", "A greedy allocation agent integrated into a web interface with explainable suggestions", "Skunkworks funding and an ACE-procured supplier for a 14-week build" ], "must_hold": [ "Centralized, real-time patient-flow and admissions data across all specialties, which the hospital lacked", "Reconfigurability by staff for changes in beds, ward layouts and admission peaks", "Compliance with the UK Medical Device Regulations 2002 before any deployment", "Funding to develop and operationalize the system beyond the proof of concept" ], "echoes": [ { "setting": "Planned bid by Kettering General Hospital with Faculty for funding to develop and operationalize the system (NHS case study, “What next?”); no later outcome read", "outcome": "unknown", "source": "https://web.archive.org/web/20231123150115/https://transform.england.nhs.uk/ai-lab/explore-all-resources/develop-ai/improving-hospital-bed-allocation-using-ai/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0365", "title": "WeChat Pay's “anti-fraud customer service reminder” interrupts a Yunnan man's 190,000 yuan transfer to a suspected romance scammer, and he cancels the payment (14 December 2021)", "summary": "WeChat says its anti-fraud reminder, with Tencent Cloud online service, led a Yunnan man to cancel a 190,000 yuan transfer to a “goddess” he had met online; reported by ChinaZ, 14 December 2021.", "date_observed": "2021-12-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "According to WeChat (ChinaZ, 14 December 2021; ZOL, 16 December 2021), WeChat Pay launched an “anti-fraud customer service reminder”. When a payment is flagged as a risky transaction, the screen shows an “answer the reminder” button and the system connects automatically. Tencent Cloud Zhifu then provides online customer service to help judge the risk. ChinaZ reports that a Mr. Zhang in Yunnan had met a woman on a video platform. Within a week she asked to borrow 190,000 yuan for medical treatment. As he initiated the transfer, a WeChat Pay voice reminder appeared. The customer service, judging from experience that this looked like a dating scam, explained the pattern and advised him to cancel. He avoided a loss of 190,000 yuan. The Monitor bundles this with Shanghai police figures for 2021 (115,000 scam calls blocked daily; 510 million yuan directly recovered). Xinmin attributes those to police, the communications administration and carriers without naming AI.", "category": "harm prevented", "unexpected": false, "purpose": "The reminder was built to warn WeChat Pay users during risky transactions and connect them to online customer service that helps judge the risk. Stopping a transfer to a suspected scammer was that purpose.", "system": "WeChat Pay 'anti-fraud customer service reminder' (防骗客服提醒) with Tencent Cloud Zhifu (腾讯云智服) online customer service", "model_version": null, "developer": "Tencent (WeChat Pay and Tencent Cloud)", "deployer": "WeChat Pay", "location": "Yunnan, China", "domain": "Payments fraud prevention", "segment": "Consumer mobile payments", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2021-12-15-3cd7" }, "ratings": [ { "group": "personal", "depth": 4, "reason": "A 190,000-yuan transfer to a suspected romance scammer was canceled on the reminder, a serious financial loss for one person averted on WeChat's account. The man is identified only by surname and province, no police or bank confirmation is reported, and the case date is not given." } ], "ai_role": { "status": "assessed", "statement": "The automated part the sources describe is the flagging of a risky transaction. That triggers the on-screen reminder and connects the payer to Tencent Cloud Zhifu, a service the Monitor calls AI. ChinaZ says the WeChat Pay customer service judged “from experience” that this was a dating scam, which reads as a human agent. Neither report says how the transaction was flagged or whether any model was involved. The advice, not the flag alone, led Zhang to cancel." }, "evidence": [ { "kind": "news report", "citation": "ChinaZ (2021). 微信支付上线“防骗客服提醒”功能 为一男子保住19万元. 站长之家, 14 December 2021.", "title": "微信支付上线“防骗客服提醒”功能 为一男子保住19万元", "url": "https://www.chinaz.com/2021/1214/1341135.shtml", "date": "2021-12-14", "written_by": "independent", "quote": "凭借经验判断张先生可能陷入了交友诈骗的骗局" }, { "kind": "news report", "citation": "ZOL (2021). 年底了 微信支付正式上线“防骗客服提醒”功能. 中关村在线, 16 December 2021.", "title": "年底了 微信支付正式上线“防骗客服提醒”功能", "url": "https://mobile.zol.com.cn/783/7832465.html", "date": "2021-12-16", "written_by": "independent", "quote": "腾讯云智服提供实时在线客服，协助大家判断当前交易风险" }, { "kind": "news report", "citation": "Yang J (2021). 上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元. 新民晚报 / 新民网, 17 December 2021.", "title": "上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元", "url": "http://newsxmwb.xinmin.cn/shizheng/szt/2021/12/17/32082134.html", "date": "2021-12-17", "written_by": "independent", "quote": "今年以来，日均阻断诈骗电话11.5万通，较去年同比增加6倍" }, { "kind": "registry label", "citation": "OECD.AI (2021). AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud. OECD AI Incidents and Hazards Monitor, entry 2021-12-15-3cd7.", "title": "AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud", "url": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "date": null, "written_by": "independent", "quote": "AI-based risk detection in banks and WeChat Pay helped identify suspects and stop fraudulent transactions, safeguarding users' financial assets." } ], "replication": { "produced_by": [ "A WeChat Pay transfer flagged as a risky transaction. This shows an “answer the reminder” button and connects the payer to Tencent Cloud Zhifu online customer service.", "A customer-service exchange in which the agent asks about the transaction context and recognizes a known scam pattern" ], "must_hold": [ "The flag fires before the transfer completes", "The payer answers the reminder and accepts the advice to cancel", "The scam matches a pattern the service recognizes; here a week-old online acquaintance asking for medical money" ], "echoes": [] }, "paired_incident": null, "headline": "WeChat Pay reminder stops a 190,000 yuan romance-scam transfer", "metric": "avoided a loss of 190,000 yuan", "comparator": null, "later": null, "value": null, "developer_country": "China", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.tencent.com/en-us/about.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0365", "catalog_version": "1.0.0", "source_fingerprint": "b8e436804e34cb9b917c3559cd62e5fc210aaec49a628459e11f18a6d559816a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0365-source-0001", "AIBD-0365-source-0002", "AIBD-0365-source-0003", "AIBD-0365-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tencent (WeChat Pay and Tencent Cloud)", "deployer": "WeChat Pay" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The automated part the sources describe is the flagging of a risky transaction. That triggers the on-screen reminder and connects the payer to Tencent Cloud Zhifu, a service the Monitor calls AI. ChinaZ says the WeChat Pay customer service judged “from experience” that this was a dating scam, which reads as a human agent. Neither report says how the transaction was flagged or whether any model was involved. The advice, not the flag alone, led Zhang to cancel." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The automated part the sources describe is the flagging of a risky transaction. That triggers the on-screen reminder and connects the payer to Tencent Cloud Zhifu, a service the Monitor calls AI. ChinaZ says the WeChat Pay customer service judged “from experience” that this was a dating scam, which reads as a human agent. Neither report says how the transaction was flagged or whether any model was involved. 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "avoided a loss of 190,000 yuan", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2021-12-15-3cd7" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0365" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "According to WeChat (ChinaZ, 14 December 2021; ZOL, 16 December 2021), WeChat Pay launched an “anti-fraud customer service reminder”. When a payment is flagged as a risky transaction, the screen shows an “answer the reminder” button and the system connects automatically. Tencent Cloud Zhifu then provides online customer service to help judge the risk. ChinaZ reports that a Mr. Zhang in Yunnan had met a woman on a video platform. Within a week she asked to borrow 190,000 yuan for medical treatment. As he initiated the transfer, a WeChat Pay voice reminder appeared. The customer service, judging from experience that this looked like a dating scam, explained the pattern and advised him to cancel. He avoided a loss of 190,000 yuan. The Monitor bundles this with Shanghai police figures for 2021 (115,000 scam calls blocked daily; 510 million yuan directly recovered). Xinmin attributes those to police, the communications administration and carriers without naming AI.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "A 190,000-yuan transfer to a suspected romance scammer was canceled on the reminder, a serious financial loss for one person averted on WeChat's account. The man is identified only by surname and province, no police or bank confirmation is reported, and the case date is not given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The reminder was built to warn WeChat Pay users during risky transactions and connect them to online customer service that helps judge the risk. Stopping a transfer to a suspected scammer was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Yunnan, China", "developer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The reminder was built to warn WeChat Pay users during risky transactions and connect them to online customer service that helps judge the risk. Stopping a transfer to a suspected scammer was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2021-12-14", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.tencent.com/en-us/about.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A WeChat Pay transfer flagged as a risky transaction. This shows an “answer the reminder” button and connects the payer to Tencent Cloud Zhifu online customer service.", "A customer-service exchange in which the agent asks about the transaction context and recognizes a known scam pattern" ], "must_hold": [ "The flag fires before the transfer completes", "The payer answers the reminder and accepts the advice to cancel", "The scam matches a pattern the service recognizes; here a week-old online acquaintance asking for medical money" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.tencent.com/en-us/about.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Payments fraud prevention", "segment": "Consumer mobile payments" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ChinaZ (2021). 微信支付上线“防骗客服提醒”功能 为一男子保住19万元. 站长之家, 14 December 2021.", "title": "微信支付上线“防骗客服提醒”功能 为一男子保住19万元", "url": "https://www.chinaz.com/2021/1214/1341135.shtml", "date": "2021-12-14", "written_by": "independent", "quote": "凭借经验判断张先生可能陷入了交友诈骗的骗局" }, { "kind": "news report", "citation": "ZOL (2021). 年底了 微信支付正式上线“防骗客服提醒”功能. 中关村在线, 16 December 2021.", "title": "年底了 微信支付正式上线“防骗客服提醒”功能", "url": "https://mobile.zol.com.cn/783/7832465.html", "date": "2021-12-16", "written_by": "independent", "quote": "腾讯云智服提供实时在线客服，协助大家判断当前交易风险" }, { "kind": "news report", "citation": "Yang J (2021). 上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元. 新民晚报 / 新民网, 17 December 2021.", "title": "上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元", "url": "http://newsxmwb.xinmin.cn/shizheng/szt/2021/12/17/32082134.html", "date": "2021-12-17", "written_by": "independent", "quote": "今年以来，日均阻断诈骗电话11.5万通，较去年同比增加6倍" }, { "kind": "registry label", "citation": "OECD.AI (2021). AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud. OECD AI Incidents and Hazards Monitor, entry 2021-12-15-3cd7.", "title": "AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud", "url": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "written_by": "independent", "quote": "AI-based risk detection in banks and WeChat Pay helped identify suspects and stop fraudulent transactions, safeguarding users' financial assets." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0365-source-0001", "AIBD-0365-source-0002", "AIBD-0365-source-0003", "AIBD-0365-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ChinaZ (2021). 微信支付上线“防骗客服提醒”功能 为一男子保住19万元. 站长之家, 14 December 2021.", "title": "微信支付上线“防骗客服提醒”功能 为一男子保住19万元", "url": "https://www.chinaz.com/2021/1214/1341135.shtml", "date": "2021-12-14", "written_by": "independent", "quote": "凭借经验判断张先生可能陷入了交友诈骗的骗局" }, { "kind": "news report", "citation": "ZOL (2021). 年底了 微信支付正式上线“防骗客服提醒”功能. 中关村在线, 16 December 2021.", "title": "年底了 微信支付正式上线“防骗客服提醒”功能", "url": "https://mobile.zol.com.cn/783/7832465.html", "date": "2021-12-16", "written_by": "independent", "quote": "腾讯云智服提供实时在线客服，协助大家判断当前交易风险" }, { "kind": "news report", "citation": "Yang J (2021). 上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元. 新民晚报 / 新民网, 17 December 2021.", "title": "上海日均阻断诈骗电话11.5万通 今年以来直接挽损5.1亿余元", "url": "http://newsxmwb.xinmin.cn/shizheng/szt/2021/12/17/32082134.html", "date": "2021-12-17", "written_by": "independent", "quote": "今年以来，日均阻断诈骗电话11.5万通，较去年同比增加6倍" }, { "kind": "registry label", "citation": "OECD.AI (2021). AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud. OECD AI Incidents and Hazards Monitor, entry 2021-12-15-3cd7.", "title": "AI Systems in Shanghai and Banking Sector Prevent Large-Scale Financial Fraud", "url": "https://oecd.ai/en/incidents/2021-12-15-3cd7", "written_by": "independent", "quote": "AI-based risk detection in banks and WeChat Pay helped identify suspects and stop fraudulent transactions, safeguarding users' financial assets." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "WeChat says its anti-fraud reminder, with Tencent Cloud online service, led a Yunnan man to cancel a 190,000 yuan transfer to a “goddess” he had met online; reported by ChinaZ, 14 December 2021.", "account": "According to WeChat (ChinaZ, 14 December 2021; ZOL, 16 December 2021), WeChat Pay launched an “anti-fraud customer service reminder”. When a payment is flagged as a risky transaction, the screen shows an “answer the reminder” button and the system connects automatically. Tencent Cloud Zhifu then provides online customer service to help judge the risk. ChinaZ reports that a Mr. Zhang in Yunnan had met a woman on a video platform. Within a week she asked to borrow 190,000 yuan for medical treatment. As he initiated the transfer, a WeChat Pay voice reminder appeared. The customer service, judging from experience that this looked like a dating scam, explained the pattern and advised him to cancel. He avoided a loss of 190,000 yuan. The Monitor bundles this with Shanghai police figures for 2021 (115,000 scam calls blocked daily; 510 million yuan directly recovered). Xinmin attributes those to police, the communications administration and carriers without naming AI." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "WeChat Pay 'anti-fraud customer service reminder' (防骗客服提醒) with Tencent Cloud Zhifu (腾讯云智服) online customer service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tencent (WeChat Pay and Tencent Cloud)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "WeChat Pay's “anti-fraud customer service reminder” interrupts a Yunnan man's 190,000 yuan transfer to a suspected romance scammer, and he cancels the payment (14 December 2021)", "headline": "WeChat Pay reminder stops a 190,000 yuan romance-scam transfer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b8e436804e34cb9b917c3559cd62e5fc210aaec49a628459e11f18a6d559816a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "According to WeChat (ChinaZ, 14 December 2021; ZOL, 16 December 2021), WeChat Pay launched an “anti-fraud customer service reminder”. When a payment is flagged as a risky transaction, the screen shows an “answer the reminder” button and the system connects automatically. Tencent Cloud Zhifu then provides online customer service to help judge the risk. ChinaZ reports that a Mr. Zhang in Yunnan had met a woman on a video platform. Within a week she asked to borrow 190,000 yuan for medical treatment. As he initiated the transfer, a WeChat Pay voice reminder appeared. The customer service, judging from experience that this looked like a dating scam, explained the pattern and advised him to cancel. He avoided a loss of 190,000 yuan. The Monitor bundles this with Shanghai police figures for 2021 (115,000 scam calls blocked daily; 510 million yuan directly recovered). Xinmin attributes those to police, the communications administration and carriers without naming AI.", "replication": { "produced_by": [ "A WeChat Pay transfer flagged as a risky transaction. This shows an “answer the reminder” button and connects the payer to Tencent Cloud Zhifu online customer service.", "A customer-service exchange in which the agent asks about the transaction context and recognizes a known scam pattern" ], "must_hold": [ "The flag fires before the transfer completes", "The payer answers the reminder and accepts the advice to cancel", "The scam matches a pattern the service recognizes; here a week-old online acquaintance asking for medical money" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0050", "title": "Coapt pattern-recognition myoelectric prostheses attached to transulnar osseointegration implants restore daily-living control in two patients", "summary": "Two transulnar amputees given Coapt pattern-recognition prostheses on osseointegration implants regained activities of daily living.", "date_observed": "2021-12-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A JBJS Case Connector report published 15 December 2021 (Jaime, Reif, Kafedzic, Garrison, Dhawan and Rozbruch) describes two people with traumatic transulnar amputations. Both underwent osseointegration implantation. After surgery a myoelectric prosthesis fitted with Coapt pattern-recognition software was attached directly to the implant. The software classifies electromyographic (EMG) signal patterns to drive a multiarticulating hand and wrist. Both trained with the software. At the most recent follow-ups of 18 months and 2 years the implants showed no loosening. The authors state that prosthetic control gradually improved to allow activities of daily living. Surgery dates are not given in the abstract.", "category": "benefit created", "unexpected": false, "purpose": "Pattern-recognition control of a multiarticulating myoelectric hand and wrist for people with upper-limb amputation", "system": "Coapt pattern recognition myoelectric control (Coapt, Chicago, IL) on a multiarticulating hand and wrist", "model_version": null, "developer": "Coapt LLC", "deployer": "Hospital for Special Surgery, New York (Department of Limb Lengthening and Complex Reconstruction; the affiliation is given for the first author)", "location": "New York, New York, United States", "domain": "Rehabilitation medicine / upper-limb prosthetics", "segment": "Amputee prosthetic care", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable patients gained prosthetic control enough for daily living activities, documented at 18-month and 2-year follow-up. The abstract has no validated functional scores, so life-changing is unsupported." }, { "group": "societal", "depth": 1, "reason": "A two-patient case report demonstrating feasibility of combining osseointegration with pattern-recognition control; no population-level effect shown." } ], "ai_role": { "status": "assessed", "statement": "The Coapt software is a machine-learning pattern-recognition controller that maps electromyographic patterns to hand and wrist motions. The report attributes improved control to training with this software on an osseointegrated attachment. So the AI contribution is entangled with the surgical attachment and cannot be isolated." }, "evidence": [ { "kind": "case report", "citation": "Jaime KM, Reif TJ, Kafedzic H, Garrison G, Dhawan J, Rozbruch SR (2021). Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study. JBJS Case Connector 11(4).", "title": "Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study", "url": "https://europepmc.org/abstract/MED/34910710", "date": "2021-12-15", "written_by": "deployer", "quote": "After surgery, a myoelectric prosthetic equipped with Coapt (Chicago, IL) recognition software was attached directly to the implant." }, { "kind": "peer-reviewed study", "citation": "Simon AM, Turner KL, Miller LA, Potter BK, Beachler MD, Dumanian GA, Hargrove LJ, Kuiken TA (2023). User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use. IEEE Trans Neural Syst Rehabil Eng.", "title": "User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use", "url": "https://europepmc.org/abstract/MED/36355739", "date": "2023-01-31", "written_by": "makers", "quote": "they showed significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control" } ], "replication": { "produced_by": [ "Stable implanted attachment delivering consistent electrode contact", "Pattern-recognition classifier trained on the patient's own EMG patterns", "Structured training with the software after surgery" ], "must_hold": [ "Sufficient residual muscle signals to separate grip and wrist classes", "Osseointegration without loosening over the follow-up period", "Clinician-supervised calibration and training" ], "echoes": [ { "date": "2023-01-31", "setting": "Randomized 8-week home trials of pattern recognition versus direct control with the Coapt system in transradial amputees (cohort)", "model_version": "Coapt COMPLETE CONTROL with Ossur i-Limb Ultra Revolution", "outcome": "recurred", "source": "Simon et al. (2023) IEEE Trans Neural Syst Rehabil Eng, PMID 36355739" } ] }, "paired_incident": null, "headline": "Coapt pattern recognition restores daily living for two amputees", "metric": null, "comparator": { "against": "direct myoelectric control", "before": null, "after": "significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control", "basis": "measured", "quote": "After the home trial, they showed significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control; other outcome measures showed no differences between control styles.", "url": "https://europepmc.org/abstract/MED/36355739" }, "later": { "status": "persisted", "date": "2023-01-31", "note": "A later randomized home-use study of transradial amputees confirmed broader grip use and better myoelectric control with Coapt pattern recognition than with direct control.", "quote": "While at home, participants demonstrated broader usage of grips in pattern recognition compared to direct control.", "url": "https://europepmc.org/abstract/MED/36355739" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Named the deployer and location from the first author's affiliation in the cited Europe PMC record, the Department of Limb Lengthening and Complex Reconstruction at Hospital for Special Surgery in New York, which the record had said was not given.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:34910710&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/abstract/MED/36355739; https://europepmc.org/abstract/MED/36355739", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://coaptengineering.com/lti-acquisition; https://en.wikipedia.org/wiki/Hospital_for_Special_Surgery", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0050", "catalog_version": "1.0.0", "source_fingerprint": "a39530618e073fea1374938745b7eadf7d04d6e78b93306046e3fcc6488d718a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0050-source-0001", "AIBD-0050-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Coapt LLC", "deployer": "Hospital for Special Surgery, New York (Department of Limb Lengthening and Complex Reconstruction; the affiliation is given for the first author)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The Coapt software is a machine-learning pattern-recognition controller that maps electromyographic patterns to hand and wrist motions. The report attributes improved control to training with this software on an osseointegrated attachment. So the AI contribution is entangled with the surgical attachment and cannot be isolated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The Coapt software is a machine-learning pattern-recognition controller that maps electromyographic patterns to hand and wrist motions. The report attributes improved control to training with this software on an osseointegrated attachment. So the AI contribution is entangled with the surgical attachment and cannot be isolated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable patients gained prosthetic control enough for daily living activities, documented at 18-month and 2-year follow-up. The abstract has no validated functional scores, so life-changing is unsupported." }, { "group": "societal", "depth": 1, "reason": "A two-patient case report demonstrating feasibility of combining osseointegration with pattern-recognition control; no population-level effect shown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study and the deployer's case report. 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Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study. JBJS Case Connector 11(4).", "title": "Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study", "url": "https://europepmc.org/abstract/MED/34910710", "date": "2021-12-15", "written_by": "deployer", "quote": "After surgery, a myoelectric prosthetic equipped with Coapt (Chicago, IL) recognition software was attached directly to the implant." }, { "kind": "peer-reviewed study", "citation": "Simon AM, Turner KL, Miller LA, Potter BK, Beachler MD, Dumanian GA, Hargrove LJ, Kuiken TA (2023). User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use. 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Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study. JBJS Case Connector 11(4).", "title": "Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study", "url": "https://europepmc.org/abstract/MED/34910710", "date": "2021-12-15", "written_by": "deployer", "quote": "After surgery, a myoelectric prosthetic equipped with Coapt (Chicago, IL) recognition software was attached directly to the implant." }, { "kind": "peer-reviewed study", "citation": "Simon AM, Turner KL, Miller LA, Potter BK, Beachler MD, Dumanian GA, Hargrove LJ, Kuiken TA (2023). User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use. IEEE Trans Neural Syst Rehabil Eng.", "title": "User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use", "url": "https://europepmc.org/abstract/MED/36355739", "date": "2023-01-31", "written_by": "makers", "quote": "they showed significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Two transulnar amputees given Coapt pattern-recognition prostheses on osseointegration implants regained activities of daily living.", "account": "A JBJS Case Connector report published 15 December 2021 (Jaime, Reif, Kafedzic, Garrison, Dhawan and Rozbruch) describes two people with traumatic transulnar amputations. Both underwent osseointegration implantation. After surgery a myoelectric prosthesis fitted with Coapt pattern-recognition software was attached directly to the implant. The software classifies electromyographic (EMG) signal patterns to drive a multiarticulating hand and wrist. Both trained with the software. At the most recent follow-ups of 18 months and 2 years the implants showed no loosening. The authors state that prosthetic control gradually improved to allow activities of daily living. Surgery dates are not given in the abstract." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Coapt pattern recognition myoelectric control (Coapt, Chicago, IL) on a multiarticulating hand and wrist" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Coapt LLC" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Coapt pattern-recognition myoelectric prostheses attached to transulnar osseointegration implants restore daily-living control in two patients", "headline": "Coapt pattern recognition restores daily living for two amputees" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a39530618e073fea1374938745b7eadf7d04d6e78b93306046e3fcc6488d718a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A JBJS Case Connector report published 15 December 2021 (Jaime, Reif, Kafedzic, Garrison, Dhawan and Rozbruch) describes two people with traumatic transulnar amputations. Both underwent osseointegration implantation. After surgery a myoelectric prosthesis fitted with Coapt pattern-recognition software was attached directly to the implant. The software classifies electromyographic (EMG) signal patterns to drive a multiarticulating hand and wrist. Both trained with the software. At the most recent follow-ups of 18 months and 2 years the implants showed no loosening. The authors state that prosthetic control gradually improved to allow activities of daily living. Surgery dates are not given in the abstract.", "replication": { "produced_by": [ "Stable implanted attachment delivering consistent electrode contact", "Pattern-recognition classifier trained on the patient's own EMG patterns", "Structured training with the software after surgery" ], "must_hold": [ "Sufficient residual muscle signals to separate grip and wrist classes", "Osseointegration without loosening over the follow-up period", "Clinician-supervised calibration and training" ], "echoes": [ { "date": "2023-01-31", "setting": "Randomized 8-week home trials of pattern recognition versus direct control with the Coapt system in transradial amputees (cohort)", "model_version": "Coapt COMPLETE CONTROL with Ossur i-Limb Ultra Revolution", "outcome": "recurred", "source": "Simon et al. (2023) IEEE Trans Neural Syst Rehabil Eng, PMID 36355739" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0096", "title": "CAD4TB on ultra-portable X-rays screened 94,694 people in eight Nigerian states and diagnosed 2,337 TB cases (2022)", "summary": "KNCV/USAID deployment Jan–Sep 2022: CAD4TB v7 screened 94,694 people in eight Nigerian states; 2,337 TB cases diagnosed, 97% treated", "date_observed": "2022-01-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "KNCV Tuberculosis Foundation Nigeria and the Institute of Human Virology Nigeria (IHVN), funded by USAID, deployed ten ultra-portable digital X-ray units. This was under the Stop TB Partnership's Introducing New Tools Project. They ran CAD4TB version 7 (threshold 50) for community active case finding in eight states (Katsina, Kano, Nasarawa, Benue, Delta, Cross River, Osun, Oyo). The period was January to September 2022 (day not given; first day of month used). Under a parallel algorithm, every client had both symptom and chest X-ray screening. Anyone positive on either (a CAD4TB score of 50 or above) was classified as presumptive TB and sent for Xpert testing and/or clinical assessment. Of those diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The program screened 94,694 people aged four and over and identified 10,236 presumptive cases. It diagnosed 2,337 TB cases (920 bacteriologically confirmed, 1,386 clinically diagnosed, 31 rifampicin-resistant). 97.3% started treatment, and the average number needed to screen (NNS) was 38. The paper's tables tally 2,481 diagnoses (986 bacteriologically confirmed, 1,466 clinically diagnosed, 29 rifampicin-resistant) with 2,414 (97.3%) started on treatment. They derive the NNS of 38 from that tally; its text gives 2,337 diagnoses. A companion six-state analysis reported 85,910 screened, 1,915 diagnosed and 1,869 treated.", "category": "general benefit", "unexpected": false, "purpose": "Triage chest X-rays to select presumptive TB cases for molecular testing during community active case finding.", "system": "CAD4TB computer-aided detection on ultra-portable digital chest X-ray", "model_version": "CAD4TB version 7, threshold score 50 or above", "developer": "Delft Imaging", "deployer": "KNCV Tuberculosis Foundation Nigeria and Institute of Human Virology Nigeria with the National TB and Leprosy Control Program, funded by USAID", "location": "Eight states, Nigeria", "domain": "Global health: tuberculosis case finding", "segment": "Public health program", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate screening yield; the sources do not document any individual's outcome attributable to the software." }, { "group": "organizational", "depth": null, "reason": "Efficiency figures (NNS 38, NNT 4) are program aggregates without a discrete attributable event." }, { "group": "societal", "depth": null, "reason": "2,337 diagnoses are an aggregate program result." } ], "ai_role": { "status": "assessed", "statement": "A parallel algorithm classified anyone positive on symptom screening or with a CAD4TB score of 50 or above as presumptive TB. They went for Xpert testing and/or clinical assessment, so the AI score was one of two gates to testing, not the sole gate. Of the 2,337 diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The TB yield also depends on X-ray reach, Xpert availability and treatment linkage. Both papers are authored by implementing organizations (KNCV Nigeria, IHVN, USAID, NTBLCP), not the vendor." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Alege, A., Useni, S., Ihesie, A., Eneogu, R., Agbaje, A., et al. (2025). Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria. Frontiers in Digital Health.", "title": "Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12257310/", "date": "2025-06-30", "written_by": "deployer", "quote": "A total of 94,694 subjects aged 4 years and above were screened for TB" }, { "kind": "peer-reviewed study", "citation": "Useni, S., Odume, B., Tukur, M., et al. (2025). Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria. Public Health Action 15(1), 17–20.", "title": "Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/", "date": "2025-03-01", "written_by": "deployer", "quote": "Screened 85,910 persons and identified 8,416 presumptive TB cases. Among these, 1,915 TB cases were diagnosed, and 1,869 patients were put on treatment." }, { "kind": "report", "citation": "KNCV Nigeria (2026). 2025 Annual Report. Knowledge Network for disease Control and Vigilance, Abuja (PDF posted March 2026; day not given, first day of month used).", "title": "Knowledge Network for disease Control and Vigilance 2025 Annual Report", "url": "https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf", "date": "2026-03-01", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Ultra-portable X-ray units with CAD4TB v7 at threshold 50", "Community mobilization and same-day Xpert testing", "USAID funding through the iNTP project" ], "must_hold": [ "Threshold calibrated to local prevalence", "Xpert cartridge supply and sample transport", "Treatment linkage within days" ], "echoes": [ { "date": "2022-01-01", "setting": "Six-state analysis of the same deployment (Benue, Cross River, Delta, Kano, Katsina, Nasarawa)", "model_version": "CAD4TB v7", "outcome": "recurred", "source": "Useni et al. (2025) Public Health Action, https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/" }, { "date": null, "setting": "Routine active case finding with digital X-ray and CAD4TB in Nigerian penitentiary institutions", "model_version": null, "outcome": "unknown", "source": "Chukwuogo et al. (2026) BMC Infectious Diseases, DOI 10.1186/s12879-026-12627-w (Europe PMC listing only)" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "81", "title": "Researchers find evidence of racial, gender, and socioeconomic bias in chest X-ray classifiers", "url": "https://incidentdatabase.ai/cite/81", "severity": null, "group": "personal", "basis": "Chest X-ray classification systems, the same kind as CAD4TB, underdiagnosed economically vulnerable, female and Hispanic patients because of biased training data." }, "headline": "CAD4TB triage of 94,694 people in Nigeria yields 2,337 TB cases", "metric": "2,337 TB cases diagnosed, 97% treated", "comparator": { "against": "KNCV Nigeria's other 2022 case-finding strategies in the same states without portable X-ray (intensified case finding in public and private facilities, medicine vendors and community pharmacists, contact investigation, community active case finding)", "before": "NNS 205.6 (public facilities), 179.0 (private facilities), 127.8 (medicine vendors and community pharmacists), 49.0 (contact investigation), 388.5 (community active case-finding)", "after": "NNS 44.9 with PDX-CAD", "basis": "measured", "quote": "During the same period, 3,867,059 persons were screened for TB in public and private health facilities, 19,140 TB cases were detected, and 18,625 (97.3%) were successfully placed on treatment. The NNS was 205.6 and 127.8, respectively. The NNS was quite high compared to 44.9 in the PDX-CAD system.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/" }, "later": { "status": "scaled", "date": "2025-09-30", "note": "KNCV Nigeria's 2025 annual report says the IMPACT project completed deployment of 390 portable digital X-ray units with AI across all 36 states and the FCT, adding 266 units in 2025, and screened over 780,000 people with over 23,000 TB cases diagnosed in January to September 2025.", "quote": "In 2025, a total of 266 additional PDX platforms were deployed for use across all geo-political zones of the country. In the first three quarters of 2025 (January - September), over 780 thousand persons were screened for TB using the portable digital X-rays, and over 23 thousand TB cases diagnosed using this tool.", "url": "https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf" }, "value": null, "developer_country": "Netherlands", "deployer_country": "Nigeria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 81 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/81", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the AI-role statement and the account so that the CAD4TB score is one of two gates in the paper's parallel algorithm (symptom screen or CAD score of 50 or above) rather than the sole gate to Xpert testing, added the split of diagnosed patients by CAD score (1,614 at 50 or above, 723 below), and noted that the 97.3% treatment rate and the NNS of 38 come from the tables' tally of 2,481 diagnoses while the text gives 2,337.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12257310/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/; https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://delftimaging.com/contact/; https://kncvnigeria.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: two peer-reviewed studies from the deployer and the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0096", "catalog_version": "1.0.0", "source_fingerprint": "ceffb7ad68c5d4fcc0c7eba5b208ba4b42e015ce6a5523caedff0421dba02726", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0096-source-0001", "AIBD-0096-source-0002", "AIBD-0096-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Delft Imaging", "deployer": "KNCV Tuberculosis Foundation Nigeria and Institute of Human Virology Nigeria with the National TB and Leprosy Control Program, funded by USAID" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "A parallel algorithm classified anyone positive on symptom screening or with a CAD4TB score of 50 or above as presumptive TB. They went for Xpert testing and/or clinical assessment, so the AI score was one of two gates to testing, not the sole gate. Of the 2,337 diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The TB yield also depends on X-ray reach, Xpert availability and treatment linkage. Both papers are authored by implementing organizations (KNCV Nigeria, IHVN, USAID, NTBLCP), not the vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "A parallel algorithm classified anyone positive on symptom screening or with a CAD4TB score of 50 or above as presumptive TB. They went for Xpert testing and/or clinical assessment, so the AI score was one of two gates to testing, not the sole gate. Of the 2,337 diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The TB yield also depends on X-ray reach, Xpert availability and treatment linkage. Both papers are authored by implementing organizations (KNCV Nigeria, IHVN, USAID, NTBLCP), not the vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: two peer-reviewed studies from the deployer and the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate screening yield; the sources do not document any individual's outcome attributable to the software." }, { "group": "organizational", "reason": "Efficiency figures (NNS 38, NNT 4) are program aggregates without a discrete attributable event." }, { "group": "societal", "reason": "2,337 diagnoses are an aggregate program result." } ] } }, "provenance": { "kind": "legacy_record", "basis": 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In the first three quarters of 2025 (January - September), over 780 thousand persons were screened for TB using the portable digital X-rays, and over 23 thousand TB cases diagnosed using this tool.", "url": "https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0096" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "KNCV Tuberculosis Foundation Nigeria and the Institute of Human Virology Nigeria (IHVN), funded by USAID, deployed ten ultra-portable digital X-ray units. This was under the Stop TB Partnership's Introducing New Tools Project. They ran CAD4TB version 7 (threshold 50) for community active case finding in eight states (Katsina, Kano, Nasarawa, Benue, Delta, Cross River, Osun, Oyo). The period was January to September 2022 (day not given; first day of month used). Under a parallel algorithm, every client had both symptom and chest X-ray screening. Anyone positive on either (a CAD4TB score of 50 or above) was classified as presumptive TB and sent for Xpert testing and/or clinical assessment. Of those diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The program screened 94,694 people aged four and over and identified 10,236 presumptive cases. It diagnosed 2,337 TB cases (920 bacteriologically confirmed, 1,386 clinically diagnosed, 31 rifampicin-resistant). 97.3% started treatment, and the average number needed to screen (NNS) was 38. The paper's tables tally 2,481 diagnoses (986 bacteriologically confirmed, 1,466 clinically diagnosed, 29 rifampicin-resistant) with 2,414 (97.3%) started on treatment. They derive the NNS of 38 from that tally; its text gives 2,337 diagnoses. A companion six-state analysis reported 85,910 screened, 1,915 diagnosed and 1,869 treated.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate screening yield; the sources do not document any individual's outcome attributable to the software." }, { "group": "organizational", "reason": "Efficiency figures (NNS 38, NNT 4) are program aggregates without a discrete attributable event." }, { "group": "societal", "reason": "2,337 diagnoses are an aggregate program result." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Triage chest X-rays to select presumptive TB cases for molecular testing during community active case finding." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Eight states, Nigeria", "developer_country": "Netherlands", "deployer_country": "Nigeria" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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(2025) Public Health Action, https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/" }, { "setting": "Routine active case finding with digital X-ray and CAD4TB in Nigerian penitentiary institutions", "outcome": "unknown", "source": "Chukwuogo et al. (2026) BMC Infectious Diseases, DOI 10.1186/s12879-026-12627-w (Europe PMC listing only)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Ultra-portable X-ray units with CAD4TB v7 at threshold 50", "Community mobilization and same-day Xpert testing", "USAID funding through the iNTP project" ], "must_hold": [ "Threshold calibrated to local prevalence", "Xpert cartridge supply and sample transport", "Treatment linkage within days" ], "echoes": [ { "date": "2022-01-01", "setting": "Six-state analysis of the same deployment (Benue, Cross River, Delta, Kano, Katsina, Nasarawa)", "model_version": "CAD4TB v7", "outcome": "recurred", "source": "Useni et al. 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(2025). Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria. Frontiers in Digital Health.", "title": "Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12257310/", "date": "2025-06-30", "written_by": "deployer", "quote": "A total of 94,694 subjects aged 4 years and above were screened for TB" }, { "kind": "peer-reviewed study", "citation": "Useni, S., Odume, B., Tukur, M., et al. (2025). Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria. Public Health Action 15(1), 17–20.", "title": "Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/", "date": "2025-03-01", "written_by": "deployer", "quote": "Screened 85,910 persons and identified 8,416 presumptive TB cases. Among these, 1,915 TB cases were diagnosed, and 1,869 patients were put on treatment." }, { "kind": "report", "citation": "KNCV Nigeria (2026). 2025 Annual Report. Knowledge Network for disease Control and Vigilance, Abuja (PDF posted March 2026; day not given, first day of month used).", "title": "Knowledge Network for disease Control and Vigilance 2025 Annual Report", "url": "https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf", "date": "2026-03-01", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0096-source-0001", "AIBD-0096-source-0002", "AIBD-0096-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Alege, A., Useni, S., Ihesie, A., Eneogu, R., Agbaje, A., et al. (2025). Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria. Frontiers in Digital Health.", "title": "Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12257310/", "date": "2025-06-30", "written_by": "deployer", "quote": "A total of 94,694 subjects aged 4 years and above were screened for TB" }, { "kind": "peer-reviewed study", "citation": "Useni, S., Odume, B., Tukur, M., et al. (2025). Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria. Public Health Action 15(1), 17–20.", "title": "Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/", "date": "2025-03-01", "written_by": "deployer", "quote": "Screened 85,910 persons and identified 8,416 presumptive TB cases. Among these, 1,915 TB cases were diagnosed, and 1,869 patients were put on treatment." }, { "kind": "report", "citation": "KNCV Nigeria (2026). 2025 Annual Report. Knowledge Network for disease Control and Vigilance, Abuja (PDF posted March 2026; day not given, first day of month used).", "title": "Knowledge Network for disease Control and Vigilance 2025 Annual Report", "url": "https://kncvnigeria.org/wp-content/uploads/2026/03/2026-KNCV-Nigeria-Annual-Report.pdf", "date": "2026-03-01", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "KNCV/USAID deployment Jan–Sep 2022: CAD4TB v7 screened 94,694 people in eight Nigerian states; 2,337 TB cases diagnosed, 97% treated", "account": "KNCV Tuberculosis Foundation Nigeria and the Institute of Human Virology Nigeria (IHVN), funded by USAID, deployed ten ultra-portable digital X-ray units. This was under the Stop TB Partnership's Introducing New Tools Project. They ran CAD4TB version 7 (threshold 50) for community active case finding in eight states (Katsina, Kano, Nasarawa, Benue, Delta, Cross River, Osun, Oyo). The period was January to September 2022 (day not given; first day of month used). Under a parallel algorithm, every client had both symptom and chest X-ray screening. Anyone positive on either (a CAD4TB score of 50 or above) was classified as presumptive TB and sent for Xpert testing and/or clinical assessment. Of those diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The program screened 94,694 people aged four and over and identified 10,236 presumptive cases. It diagnosed 2,337 TB cases (920 bacteriologically confirmed, 1,386 clinically diagnosed, 31 rifampicin-resistant). 97.3% started treatment, and the average number needed to screen (NNS) was 38. The paper's tables tally 2,481 diagnoses (986 bacteriologically confirmed, 1,466 clinically diagnosed, 29 rifampicin-resistant) with 2,414 (97.3%) started on treatment. They derive the NNS of 38 from that tally; its text gives 2,337 diagnoses. A companion six-state analysis reported 85,910 screened, 1,915 diagnosed and 1,869 treated." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "CAD4TB scored chest X-rays for signs of tuberculosis." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used CAD4TB version 7 with a threshold score of 50." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "CAD4TB version 7, threshold score 50 or above" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "CAD4TB version 7.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "CAD4TB computer-aided detection on ultra-portable digital chest X-ray" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Delft Imaging" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CAD4TB on ultra-portable X-rays screened 94,694 people in eight Nigerian states and diagnosed 2,337 TB cases (2022)", "headline": "CAD4TB triage of 94,694 people in Nigeria yields 2,337 TB cases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ceffb7ad68c5d4fcc0c7eba5b208ba4b42e015ce6a5523caedff0421dba02726" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "KNCV Tuberculosis Foundation Nigeria and the Institute of Human Virology Nigeria (IHVN), funded by USAID, deployed ten ultra-portable digital X-ray units. This was under the Stop TB Partnership's Introducing New Tools Project. They ran CAD4TB version 7 (threshold 50) for community active case finding in eight states (Katsina, Kano, Nasarawa, Benue, Delta, Cross River, Osun, Oyo). The period was January to September 2022 (day not given; first day of month used). Under a parallel algorithm, every client had both symptom and chest X-ray screening. Anyone positive on either (a CAD4TB score of 50 or above) was classified as presumptive TB and sent for Xpert testing and/or clinical assessment. Of those diagnosed, 1,614 (69.1%) scored 50 or above and 723 (30.9%) scored below 50. The program screened 94,694 people aged four and over and identified 10,236 presumptive cases. It diagnosed 2,337 TB cases (920 bacteriologically confirmed, 1,386 clinically diagnosed, 31 rifampicin-resistant). 97.3% started treatment, and the average number needed to screen (NNS) was 38. The paper's tables tally 2,481 diagnoses (986 bacteriologically confirmed, 1,466 clinically diagnosed, 29 rifampicin-resistant) with 2,414 (97.3%) started on treatment. They derive the NNS of 38 from that tally; its text gives 2,337 diagnoses. A companion six-state analysis reported 85,910 screened, 1,915 diagnosed and 1,869 treated.", "replication": { "produced_by": [ "Ultra-portable X-ray units with CAD4TB v7 at threshold 50", "Community mobilization and same-day Xpert testing", "USAID funding through the iNTP project" ], "must_hold": [ "Threshold calibrated to local prevalence", "Xpert cartridge supply and sample transport", "Treatment linkage within days" ], "echoes": [ { "date": "2022-01-01", "setting": "Six-state analysis of the same deployment (Benue, Cross River, Delta, Kano, Katsina, Nasarawa)", "model_version": "CAD4TB v7", "outcome": "recurred", "source": "Useni et al. (2025) Public Health Action, https://pmc.ncbi.nlm.nih.gov/articles/PMC11841120/" }, { "setting": "Routine active case finding with digital X-ray and CAD4TB in Nigerian penitentiary institutions", "outcome": "unknown", "source": "Chukwuogo et al. (2026) BMC Infectious Diseases, DOI 10.1186/s12879-026-12627-w (Europe PMC listing only)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0290", "title": "Smartwatch alert for an irregular rate above 180 bpm leads to a ventricular tachycardia diagnosis, an ICD, and the incidental discovery and resection of a lung adenocarcinoma", "summary": "A 58-year-old's smartwatch flagged an irregular rate over 180 bpm; NSVT was diagnosed from watch data, an ICD placed, and the post-procedure X-ray found a 28 mm lung adenocarcinoma, resected.", "date_observed": "2022-01-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Cole, Kar, Nimako and Smelt reported a case in JRSM Open (4 January 2022; event dates not reported). They are of St George's Healthcare NHS Trust (thoracic surgery) and East Surrey Hospital (respiratory medicine) in England's National Health Service (NHS). A previously well 58-year-old non-smoker's smartwatch alerted him that his heart rate was irregular and exceeding 180 beats per minute while he felt nothing. His GP's 12-lead electrocardiogram (ECG) showed tachycardia without arrhythmia and he was admitted. Inpatient ECGs showed incomplete right bundle branch block and intermittent first-degree AV block but captured no significant arrhythmia. From the smartwatch results, the cardiologist diagnosed non-sustained ventricular tachycardia (NSVT) and an implantable cardioverter-defibrillator (ICD) was inserted. The post-procedure chest X-ray, taken to exclude pneumothorax, incidentally showed a right upper zone abnormality. Computed tomography (CT) found a 28 mm lesion, PET showed FDG-avid nodes, and biopsy showed lepidic adenocarcinoma, staged cT1c N0 M0. He had a video-assisted right upper lobectomy with node dissection and was discharged on day 10. The 35 mm tumor was staged pT2a pN0 M0 with clear margins. The nodes showed sarcoidosis and cardiac magnetic resonance imaging (MRI) found no cardiac sarcoid. The authors call this the first reported case of a smartwatch assisting the diagnosis of both NSVT and lung adenocarcinoma. The watch's brand and model are not stated.", "category": "benefit created", "unexpected": true, "purpose": "The watch's heart-rate alert was its intended function. The lung cancer diagnosis was an incidental consequence of the ICD procedure the alert set in motion, outside anything the device was built to do.", "system": "Smartwatch heart-rate and irregular-rhythm alert (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "United Kingdom (authors at St George's Healthcare NHS Trust, London, and East Surrey Hospital, Redhill; the treating hospitals are not named)", "domain": "Healthcare (cardiology; thoracic oncology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "One man received an ICD for ventricular tachycardia and curative resection of a lung adenocarcinoma found at stage pT2a pN0. The authors judge that without the watch the cancer would likely have grown undetected and curative surgery might not have been an option. That counterfactual is their judgment." } ], "ai_role": { "status": "assessed", "statement": "The watch's alert in an asymptomatic man started the chain. Its stored data were what the cardiologist used to diagnose NSVT when hospital tracings captured nothing. The lung cancer was found by a routine post-ICD X-ray, not by the device. The brand is unknown, so the alerting algorithm cannot be identified. The authors describe smartwatch rhythm monitoring generically as photoplethysmography." }, "evidence": [ { "kind": "case report", "citation": "Cole APC, Kar A, Nimako K, Smelt J (2022). Smartwatch helps detects lung cancer: Using personal technology to advance healthcare. JRSM Open 13(1):20542704211068651. doi:10.1177/20542704211068651 (PMC8733372).", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "was alerted by his smartwatch that his heart rate was irregular and exceeding 180 beats-per-minute, he remained asymptomatic throughout" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, cardiac diagnosis.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "Using the results from his smartwatch, the cardiologist diagnosed non-sustained ventricular tachycardia and he subsequently had an Implantable Cardiac Defibrillator inserted." }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, incidental finding.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "A post procedure Chest X-ray ruled out iatrogenic pneumothorax but this incidentally showed an abnormality in his right upper lung zone" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, conclusions.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "it is likely without his smartwatch his lung adenocarcinoma would have continued to grow undetected, curative surgery may not have been an option" } ], "replication": { "produced_by": [ "An asymptomatic wearer whose smartwatch alerted to an irregular rate above 180 bpm and who took it to his GP", "A cardiologist willing to diagnose from the watch's stored data when hospital tracings were silent", "A procedure (ICD insertion) whose routine follow-up imaging happened to cover the lung" ], "must_hold": [ "The arrhythmia is one the watch records while hospital monitoring misses it", "The incidental finding is in the field of the post-procedure X-ray and caught early enough for curative surgery. The authors cite an estimated 1 in 25 cancers diagnosed incidentally." ], "echoes": [] }, "paired_incident": null, "headline": "Smartwatch alert leads to an ICD and finds a lung adenocarcinoma", "metric": "found a 28 mm lung adenocarcinoma, resected", "comparator": { "against": "no smartwatch (the authors' counterfactual for the same patient)", "before": "his lung adenocarcinoma would have continued to grow undetected, curative surgery may not have been an option", "after": "The upper lobe adenocarcinoma measured 35 mm and was staged as pT2a pN0 M0 with clear resection margins.", "basis": "assumed", "quote": "For the patient described, it is likely without his smartwatch his lung adenocarcinoma would have continued to grow undetected, curative surgery may not have been an option, and the prognosis for him would have undoubtable been poorer.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/" }, "later": { "status": "unknown", "date": null, "note": "Nothing later than the January 2022 case report was found; the paper reports no follow-up beyond discharge on the tenth postoperative day and an outpatient cardiac MRI.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0290", "catalog_version": "1.0.0", "source_fingerprint": "edfbcdfdd559c6924d94147f530a4360f28243862f36b7b6080c175d330e770e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0290-source-0001", "AIBD-0290-source-0002", "AIBD-0290-source-0003", "AIBD-0290-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's alert in an asymptomatic man started the chain. Its stored data were what the cardiologist used to diagnose NSVT when hospital tracings captured nothing. The lung cancer was found by a routine post-ICD X-ray, not by the device. The brand is unknown, so the alerting algorithm cannot be identified. The authors describe smartwatch rhythm monitoring generically as photoplethysmography." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's alert in an asymptomatic man started the chain. Its stored data were what the cardiologist used to diagnose NSVT when hospital tracings captured nothing. The lung cancer was found by a routine post-ICD X-ray, not by the device. The brand is unknown, so the alerting algorithm cannot be identified. The authors describe smartwatch rhythm monitoring generically as photoplethysmography." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One man received an ICD for ventricular tachycardia and curative resection of a lung adenocarcinoma found at stage pT2a pN0. The authors judge that without the watch the cancer would likely have grown undetected and curative surgery might not have been an option. That counterfactual is their judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One man received an ICD for ventricular tachycardia and curative resection of a lung adenocarcinoma found at stage pT2a pN0. The authors judge that without the watch the cancer would likely have grown undetected and curative surgery might not have been an option. That counterfactual is their judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One man received an ICD for ventricular tachycardia and curative resection of a lung adenocarcinoma found at stage pT2a pN0. The authors judge that without the watch the cancer would likely have grown undetected and curative surgery might not have been an option. That counterfactual is their judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": 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"not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Nothing later than the January 2022 case report was found; the paper reports no follow-up beyond discharge on the tenth postoperative day and an outpatient cardiac MRI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", 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"legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Cole, Kar, Nimako and Smelt reported a case in JRSM Open (4 January 2022; event dates not reported). They are of St George's Healthcare NHS Trust (thoracic surgery) and East Surrey Hospital (respiratory medicine) in England's National Health Service (NHS). A previously well 58-year-old non-smoker's smartwatch alerted him that his heart rate was irregular and exceeding 180 beats per minute while he felt nothing. His GP's 12-lead electrocardiogram (ECG) showed tachycardia without arrhythmia and he was admitted. Inpatient ECGs showed incomplete right bundle branch block and intermittent first-degree AV block but captured no significant arrhythmia. From the smartwatch results, the cardiologist diagnosed non-sustained ventricular tachycardia (NSVT) and an implantable cardioverter-defibrillator (ICD) was inserted. The post-procedure chest X-ray, taken to exclude pneumothorax, incidentally showed a right upper zone abnormality. Computed tomography (CT) found a 28 mm lesion, PET showed FDG-avid nodes, and biopsy showed lepidic adenocarcinoma, staged cT1c N0 M0. He had a video-assisted right upper lobectomy with node dissection and was discharged on day 10. The 35 mm tumor was staged pT2a pN0 M0 with clear margins. The nodes showed sarcoidosis and cardiac magnetic resonance imaging (MRI) found no cardiac sarcoid. The authors call this the first reported case of a smartwatch assisting the diagnosis of both NSVT and lung adenocarcinoma. The watch's brand and model are not stated.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One man received an ICD for ventricular tachycardia and curative resection of a lung adenocarcinoma found at stage pT2a pN0. The authors judge that without the watch the cancer would likely have grown undetected and curative surgery might not have been an option. That counterfactual is their judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "The watch's heart-rate alert was its intended function. The lung cancer diagnosis was an incidental consequence of the ICD procedure the alert set in motion, outside anything the device was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom (authors at St George's Healthcare NHS Trust, London, and East Surrey Hospital, Redhill; the treating hospitals are not named)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The watch's heart-rate alert was its intended function. The lung cancer diagnosis was an incidental consequence of the ICD procedure the alert set in motion, outside anything the device was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-01-04", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An asymptomatic wearer whose smartwatch alerted to an irregular rate above 180 bpm and who took it to his GP", "A cardiologist willing to diagnose from the watch's stored data when hospital tracings were silent", "A procedure (ICD insertion) whose routine follow-up imaging happened to cover the lung" ], "must_hold": [ "The arrhythmia is one the watch records while hospital monitoring misses it", "The incidental finding is in the field of the post-procedure X-ray and caught early enough for curative surgery. The authors cite an estimated 1 in 25 cancers diagnosed incidentally." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; thoracic oncology)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Cole APC, Kar A, Nimako K, Smelt J (2022). Smartwatch helps detects lung cancer: Using personal technology to advance healthcare. JRSM Open 13(1):20542704211068651. doi:10.1177/20542704211068651 (PMC8733372).", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "was alerted by his smartwatch that his heart rate was irregular and exceeding 180 beats-per-minute, he remained asymptomatic throughout" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, cardiac diagnosis.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "Using the results from his smartwatch, the cardiologist diagnosed non-sustained ventricular tachycardia and he subsequently had an Implantable Cardiac Defibrillator inserted." }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, incidental finding.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "A post procedure Chest X-ray ruled out iatrogenic pneumothorax but this incidentally showed an abnormality in his right upper lung zone" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, conclusions.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "it is likely without his smartwatch his lung adenocarcinoma would have continued to grow undetected, curative surgery may not have been an option" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0290-source-0001", "AIBD-0290-source-0002", "AIBD-0290-source-0003", "AIBD-0290-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Cole APC, Kar A, Nimako K, Smelt J (2022). Smartwatch helps detects lung cancer: Using personal technology to advance healthcare. JRSM Open 13(1):20542704211068651. doi:10.1177/20542704211068651 (PMC8733372).", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "was alerted by his smartwatch that his heart rate was irregular and exceeding 180 beats-per-minute, he remained asymptomatic throughout" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, cardiac diagnosis.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "Using the results from his smartwatch, the cardiologist diagnosed non-sustained ventricular tachycardia and he subsequently had an Implantable Cardiac Defibrillator inserted." }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, incidental finding.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "A post procedure Chest X-ray ruled out iatrogenic pneumothorax but this incidentally showed an abnormality in his right upper lung zone" }, { "kind": "case report", "citation": "Cole APC et al. (2022), JRSM Open 13(1):20542704211068651, conclusions.", "title": "Smartwatch helps detects lung cancer: Using personal technology to advance healthcare", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8733372/", "date": "2022-01-04", "written_by": "independent", "quote": "it is likely without his smartwatch his lung adenocarcinoma would have continued to grow undetected, curative surgery may not have been an option" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 58-year-old's smartwatch flagged an irregular rate over 180 bpm; NSVT was diagnosed from watch data, an ICD placed, and the post-procedure X-ray found a 28 mm lung adenocarcinoma, resected.", "account": "Cole, Kar, Nimako and Smelt reported a case in JRSM Open (4 January 2022; event dates not reported). They are of St George's Healthcare NHS Trust (thoracic surgery) and East Surrey Hospital (respiratory medicine) in England's National Health Service (NHS). A previously well 58-year-old non-smoker's smartwatch alerted him that his heart rate was irregular and exceeding 180 beats per minute while he felt nothing. His GP's 12-lead electrocardiogram (ECG) showed tachycardia without arrhythmia and he was admitted. Inpatient ECGs showed incomplete right bundle branch block and intermittent first-degree AV block but captured no significant arrhythmia. From the smartwatch results, the cardiologist diagnosed non-sustained ventricular tachycardia (NSVT) and an implantable cardioverter-defibrillator (ICD) was inserted. The post-procedure chest X-ray, taken to exclude pneumothorax, incidentally showed a right upper zone abnormality. Computed tomography (CT) found a 28 mm lesion, PET showed FDG-avid nodes, and biopsy showed lepidic adenocarcinoma, staged cT1c N0 M0. He had a video-assisted right upper lobectomy with node dissection and was discharged on day 10. The 35 mm tumor was staged pT2a pN0 M0 with clear margins. The nodes showed sarcoidosis and cardiac magnetic resonance imaging (MRI) found no cardiac sarcoid. The authors call this the first reported case of a smartwatch assisting the diagnosis of both NSVT and lung adenocarcinoma. The watch's brand and model are not stated." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartwatch heart-rate and irregular-rhythm alert (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Smartwatch alert for an irregular rate above 180 bpm leads to a ventricular tachycardia diagnosis, an ICD, and the incidental discovery and resection of a lung adenocarcinoma", "headline": "Smartwatch alert leads to an ICD and finds a lung adenocarcinoma" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "edfbcdfdd559c6924d94147f530a4360f28243862f36b7b6080c175d330e770e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Cole, Kar, Nimako and Smelt reported a case in JRSM Open (4 January 2022; event dates not reported). They are of St George's Healthcare NHS Trust (thoracic surgery) and East Surrey Hospital (respiratory medicine) in England's National Health Service (NHS). A previously well 58-year-old non-smoker's smartwatch alerted him that his heart rate was irregular and exceeding 180 beats per minute while he felt nothing. His GP's 12-lead electrocardiogram (ECG) showed tachycardia without arrhythmia and he was admitted. Inpatient ECGs showed incomplete right bundle branch block and intermittent first-degree AV block but captured no significant arrhythmia. From the smartwatch results, the cardiologist diagnosed non-sustained ventricular tachycardia (NSVT) and an implantable cardioverter-defibrillator (ICD) was inserted. The post-procedure chest X-ray, taken to exclude pneumothorax, incidentally showed a right upper zone abnormality. Computed tomography (CT) found a 28 mm lesion, PET showed FDG-avid nodes, and biopsy showed lepidic adenocarcinoma, staged cT1c N0 M0. He had a video-assisted right upper lobectomy with node dissection and was discharged on day 10. The 35 mm tumor was staged pT2a pN0 M0 with clear margins. The nodes showed sarcoidosis and cardiac magnetic resonance imaging (MRI) found no cardiac sarcoid. The authors call this the first reported case of a smartwatch assisting the diagnosis of both NSVT and lung adenocarcinoma. The watch's brand and model are not stated.", "replication": { "produced_by": [ "An asymptomatic wearer whose smartwatch alerted to an irregular rate above 180 bpm and who took it to his GP", "A cardiologist willing to diagnose from the watch's stored data when hospital tracings were silent", "A procedure (ICD insertion) whose routine follow-up imaging happened to cover the lung" ], "must_hold": [ "The arrhythmia is one the watch records while hospital monitoring misses it", "The incidental finding is in the field of the post-procedure X-ray and caught early enough for curative surgery. The authors cite an estimated 1 in 25 cancers diagnosed incidentally." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0111", "title": "Google's Android Earthquake Alerts reached Alanya phones seconds before the 5 January 2022 M5.1 (AFAD 5.3) Mediterranean quake", "summary": "Android users near Alanya, Turkey, got Google's earthquake alert seconds before a M5.1 (AFAD 5.3) offshore quake on 5 January 2022.", "date_observed": "2022-01-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At 06:21 local time on 5 January 2022 a magnitude 5.1 (USGS; AFAD 5.3) earthquake struck the Mediterranean about 57 km off Alanya, Antalya, Turkey. Depth: roughly 40 km. Yeni Şafak and DonanımHaber reported the same day on Google's Android Earthquake Alerts System, introduced in Turkey in June 2021. It sent an audible and visual alert for a magnitude 5.3 quake to Android users seconds before the shaking. Hürriyet put the lead at about 10 seconds, while NTV and İndigo Dergisi claimed about a minute. AFAD and the Alanya district governor reported no damage or injuries. On 3 February 2022 Google said the system had alerted users to two January quakes centered on Alanya and Balıkesir.", "category": "protective response", "unexpected": false, "purpose": "Built to detect earthquakes from Android phones' accelerometers and alert users in the expected shaking zone seconds before the slower destructive waves arrive. It covers quakes of magnitude 4.5 and above. This alert was that intended function.", "system": "Android Earthquake Alerts System (crowdsourced phone-accelerometer detection; alerts for magnitude 4.5 and above)", "model_version": null, "developer": "Google", "deployer": "Google", "location": "Alanya, Turkey", "domain": "Disaster risk reduction / earthquake early warning", "segment": "Consumer smartphones (Android)", "benefit_type": "Increased Product Safety", "taxonomy_note": "The alert arrived seconds before shaking, but no protective action by a recipient and no harm are documented.", "registry_ids": { "oecd_aim": "2022-01-18-136b" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "An unstated number of Android users near Alanya received a few seconds' audible and visual notice of the quake. AFAD and the district governor said it caused no damage or injuries. No protective action by a recipient is documented. Hürriyet reported on 7 January 2022 that most users who posted about the alert said they panicked." } ], "ai_role": { "status": "assessed", "statement": "The alert was produced end to end by Google's system. Accelerometer triggers from many phones were combined on Google's servers to detect the quake and estimate its size. Alerts were pushed to phones in the expected shaking zone ahead of the slower S-waves. Google's own descriptions of this process do not use the words AI or machine learning. The OECD Monitor classifies it as an AI system doing event detection and forecasting, and the 2025 Science paper calls it smartphone-based earthquake detection algorithms. The reported lead time varies by outlet (seconds, about 10 seconds, about one minute); Google promises seconds." }, "evidence": [ { "kind": "news report", "citation": "Yeni Şafak (2022). Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı. Yeni Şafak, 5 January 2022.", "title": "Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı", "url": "https://www.yenisafak.com/teknoloji/google-android-deprem-uyari-sistemi-nasil-acilir-deprem-uyari-sistemi-nedir-deprem-uyari-sistemi-hangi-telefonlarda-acilir-3728848", "date": "2022-01-05", "written_by": "independent", "quote": "Depremden saniyeler önce bazı Android kullanıcıları, Google Android’in deprem erken uyarı sisteminden depreme dair telefonlarına 5.3 büyüklüğünde bir depremin olacağına dair sesli ve görsel bir uyarı mesajı gönderildi." }, { "kind": "news report", "citation": "DonanımHaber (2022). Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi. DonanımHaber, 5 January 2022.", "title": "Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi", "url": "https://www.donanimhaber.com/google-erken-uyari-sistemi-alanya-depremini-onceden-bildi--143452", "date": "2022-01-05", "written_by": "independent", "quote": "Google deprem uyarı sistemi, erken saatlerde meydana gelen depremden saniyeler önce, o bölgede oturan kullanıcılara deprem uyarı sistemi aracılığıyla bir uyarı mesajı gönderdi." }, { "kind": "news report", "citation": "Öztürk T (2022). Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi? Hürriyet, 7 January 2022.", "title": "Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi?", "url": "https://www.hurriyet.com.tr/gundem/erken-uyari-sistemi-tartismasi-depremin-olacagini-10-saniye-onceden-bilmek-guvenli-mi-41976168", "date": "2022-01-07", "written_by": "independent", "quote": "Depremden yaklaşık 10 saniye önce, cep telefonlarına 'deprem olacak' bildirimi gitti." }, { "kind": "news report", "citation": "Hürriyet (2022). Google, Android Deprem Uyarı Sistemi’ni tanıttı. Hürriyet, 3 February 2022.", "title": "Google, Android Deprem Uyarı Sistemi’ni tanıttı", "url": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996", "date": "2022-02-03", "written_by": "independent", "quote": "Ocak ayında ülkemizde merkezi Alanya ve Balıkesir olmak üzere 4.5 büyüklüğü üzeri iki depreme dair Android kullanıcılarına uyarı bildirisi gönderen Android Deprem Uyarı Sistemi" }, { "kind": "news report", "citation": "İndigo Dergisi (2022). Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi? İndigo Dergisi, 5 January 2022.", "title": "Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi?", "url": "https://indigodergisi.com/2022/01/google-deprem-uyari-sistemi-nasil-ailir/", "date": "2022-01-05", "written_by": "independent", "quote": "AFAD’dan yapılan açıklamada “Akdeniz’de Antalya’nın Alanya ilçesi açıklarında saat 06.21’de 5,3 büyüklüğünde bir deprem meydana geldi. Gelişmeleri takip ediyoruz” denildi." }, { "kind": "news report", "citation": "NTV (2022). Deprem uyarı sistemi nedir, nasıl çalışır? NTV, 18 January 2022.", "title": "Deprem uyarı sistemi nedir, nasıl çalışır?", "url": "https://www.ntv.com.tr/turkiye/deprem-uyari-sistemi-nedir-nasil-calisir,PtR3VF38DUOdDzApupgnQQ", "date": "2022-01-18", "written_by": "independent", "quote": "Geçtiğimiz haftalarda Google'ın sunduğu deprem uyarı sistemi, Alanya açıklarında meydana gelen 5.3'lük depremi 1 dakika öncesinden tahmin ederek kullanıcılarına sesli uyarı göndermişti." }, { "kind": "news report", "citation": "Yeni Akit (2022). Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır? Yeni Akit, 18 January 2022.", "title": "Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır?", "url": "https://www.yeniakit.com.tr/haber/android-deprem-uyari-sistemi-nedir-nasil-yapilir-nasil-kullanilir-1618101.html", "date": "2022-01-18", "written_by": "independent", "quote": "Android deprem uyarı sistemi sayesinde 5 Ocak 2022 sabahı Antalya’da meydana gelen depremin kısa süre öncesinde vatandaşlara uyarı yollandı." }, { "kind": "news report", "citation": "Hürriyet (2022). Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları. Hürriyet, 18 January 2022.", "title": "Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları", "url": "https://www.hurriyet.com.tr/galeri-deprem-uyari-sistemi-nasil-yapilir-nedir-android-erken-deprem-uyari-sistemi-kullanim-detaylari-41984292", "date": "2022-01-18", "written_by": "independent", "quote": "Olası bir depremi 10 saniye önceden haber verebilen deprem uyarı sistemi Alanya'da yaşanan depremi gerçekleşmeden 1 dakika kadar önce bölgede oturanlara Google tarafından bildirilmişti." }, { "kind": "dataset", "citation": "U.S. Geological Survey (2022). M 5.1 - 67 km SSW of Okurcalar, Turkey (event us7000g94d). USGS Earthquake Hazards Program.", "title": "M 5.1 - 67 km SSW of Okurcalar, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000g94d", "date": "2022-01-05", "written_by": "independent", "quote": "M 5.1 - 67 km SSW of Okurcalar, Turkey" }, { "kind": "news report", "citation": "Duckett C (2021). Android opens up earthquake alerts and end-to-end encrypted messages. ZDNet, 16 June 2021.", "title": "Android opens up earthquake alerts and end-to-end encrypted messages", "url": "https://www.zdnet.com/article/android-opens-up-earthquake-alerts-and-end-to-end-encrypted-messages/", "date": "2021-06-16", "written_by": "independent", "quote": "The system is already live in New Zealand and Greece, with Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan coming on board." }, { "kind": "press release", "citation": "Lee F (2021). 6 new features on Android this summer. Google, The Keyword, 15 June 2021.", "title": "6 new features on Android this summer", "url": "https://blog.google/products-and-platforms/platforms/android/new-features-summer-2021/", "date": "2021-06-15", "written_by": "makers", "quote": "Today, we're introducing the Android Earthquake Alerts System in Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan." }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "date": null, "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "User feedback shows that 85% of people receiving an alert felt shaking, and 36, 28, and 23% received the alert before, during, and after shaking, respectively." } ], "replication": { "produced_by": [ "A magnitude 5.1 (AFAD 5.3) quake above the 4.5 alert threshold, centered about 57 km offshore and roughly 40 km deep. So the push alert could outrun the slower S-waves to the coast.", "Enough Android phones near the epicenter with Earthquake Alerts on to trigger Google's server-side detection. Per Google's 3 February 2022 presentation it runs on Android 5.0 and later and users can switch it off.", "Crowdsourced phone detection was the only input: Google partners with the ShakeAlert seismic network only in California, Oregon and Washington" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. Hürriyet reported on 7 January 2022 that most users who posted about the Alanya alert said they panicked", "The phone must have location and the Earthquake Alerts setting enabled" ], "echoes": [] }, "paired_incident": null, "headline": "Google alerts Alanya phones seconds before a M5.1 quake", "metric": "Hürriyet put the lead at about 10 seconds", "comparator": null, "later": { "status": "persisted", "date": "2022-02-03", "note": "At a 3 February 2022 press event Google said the Android system had alerted users to the two January quakes centered on Alanya and Balıkesir.", "quote": "Ocak ayında ülkemizde merkezi Alanya ve Balıkesir olmak üzere 4.5 büyüklüğü üzeri iki depreme dair Android kullanıcılarına uyarı bildirisi gönderen Android Deprem Uyarı Sistemi hakkında detaylı bilgi vermek ve depremde saniyelerin önemini tekrar vurgulamak üzere Google bir basın toplantısı düzenledi.", "url": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-01-18-136b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: nine independent news reports, one independent dataset, the makers' peer-reviewed study and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0111", "catalog_version": "1.0.0", "source_fingerprint": "65b16e850751b1199c57592eb6bfa2df4ce99dc8579627ff3f0d2be754b77e98", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0111-source-0001", "AIBD-0111-source-0002", "AIBD-0111-source-0003", "AIBD-0111-source-0004", "AIBD-0111-source-0005", "AIBD-0111-source-0006", "AIBD-0111-source-0007", "AIBD-0111-source-0008", "AIBD-0111-source-0009", "AIBD-0111-source-0010", "AIBD-0111-source-0011", "AIBD-0111-source-0012", "AIBD-0111-source-0013", "AIBD-0111-source-0014" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google", "deployer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The alert was produced end to end by Google's system. 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"At a 3 February 2022 press event Google said the Android system had alerted users to the two January quakes centered on Alanya and Balıkesir.", "quote": "Ocak ayında ülkemizde merkezi Alanya ve Balıkesir olmak üzere 4.5 büyüklüğü üzeri iki depreme dair Android kullanıcılarına uyarı bildirisi gönderen Android Deprem Uyarı Sistemi hakkında detaylı bilgi vermek ve depremde saniyelerin önemini tekrar vurgulamak üzere Google bir basın toplantısı düzenledi.", "url": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": 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Depth: roughly 40 km. Yeni Şafak and DonanımHaber reported the same day on Google's Android Earthquake Alerts System, introduced in Turkey in June 2021. It sent an audible and visual alert for a magnitude 5.3 quake to Android users seconds before the shaking. Hürriyet put the lead at about 10 seconds, while NTV and İndigo Dergisi claimed about a minute. AFAD and the Alanya district governor reported no damage or injuries. 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So the push alert could outrun the slower S-waves to the coast.", "Enough Android phones near the epicenter with Earthquake Alerts on to trigger Google's server-side detection. Per Google's 3 February 2022 presentation it runs on Android 5.0 and later and users can switch it off.", "Crowdsourced phone detection was the only input: Google partners with the ShakeAlert seismic network only in California, Oregon and Washington" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. Hürriyet reported on 7 January 2022 that most users who posted about the Alanya alert said they panicked", "The phone must have location and the Earthquake Alerts setting enabled" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-01-18-136b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Disaster risk reduction / earthquake early warning", "segment": "Consumer smartphones (Android)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Yeni Şafak (2022). Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı. Yeni Şafak, 5 January 2022.", "title": "Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı", "url": "https://www.yenisafak.com/teknoloji/google-android-deprem-uyari-sistemi-nasil-acilir-deprem-uyari-sistemi-nedir-deprem-uyari-sistemi-hangi-telefonlarda-acilir-3728848", "date": "2022-01-05", "written_by": "independent", "quote": "Depremden saniyeler önce bazı Android kullanıcıları, Google Android’in deprem erken uyarı sisteminden depreme dair telefonlarına 5.3 büyüklüğünde bir depremin olacağına dair sesli ve görsel bir uyarı mesajı gönderildi." }, { "kind": "news report", "citation": "DonanımHaber (2022). Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi. DonanımHaber, 5 January 2022.", "title": "Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi", "url": "https://www.donanimhaber.com/google-erken-uyari-sistemi-alanya-depremini-onceden-bildi--143452", "date": "2022-01-05", "written_by": "independent", "quote": "Google deprem uyarı sistemi, erken saatlerde meydana gelen depremden saniyeler önce, o bölgede oturan kullanıcılara deprem uyarı sistemi aracılığıyla bir uyarı mesajı gönderdi." }, { "kind": "news report", "citation": "Öztürk T (2022). Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi? Hürriyet, 7 January 2022.", "title": "Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi?", "url": "https://www.hurriyet.com.tr/gundem/erken-uyari-sistemi-tartismasi-depremin-olacagini-10-saniye-onceden-bilmek-guvenli-mi-41976168", "date": "2022-01-07", "written_by": "independent", "quote": "Depremden yaklaşık 10 saniye önce, cep telefonlarına 'deprem olacak' bildirimi gitti." }, { "kind": "news report", "citation": "Hürriyet (2022). Google, Android Deprem Uyarı Sistemi’ni tanıttı. Hürriyet, 3 February 2022.", "title": "Google, Android Deprem Uyarı Sistemi’ni tanıttı", "url": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996", "date": "2022-02-03", "written_by": "independent", "quote": "Ocak ayında ülkemizde merkezi Alanya ve Balıkesir olmak üzere 4.5 büyüklüğü üzeri iki depreme dair Android kullanıcılarına uyarı bildirisi gönderen Android Deprem Uyarı Sistemi" }, { "kind": "news report", "citation": "İndigo Dergisi (2022). Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi? İndigo Dergisi, 5 January 2022.", "title": "Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi?", "url": "https://indigodergisi.com/2022/01/google-deprem-uyari-sistemi-nasil-ailir/", "date": "2022-01-05", "written_by": "independent", "quote": "AFAD’dan yapılan açıklamada “Akdeniz’de Antalya’nın Alanya ilçesi açıklarında saat 06.21’de 5,3 büyüklüğünde bir deprem meydana geldi. Gelişmeleri takip ediyoruz” denildi." }, { "kind": "news report", "citation": "NTV (2022). Deprem uyarı sistemi nedir, nasıl çalışır? NTV, 18 January 2022.", "title": "Deprem uyarı sistemi nedir, nasıl çalışır?", "url": "https://www.ntv.com.tr/turkiye/deprem-uyari-sistemi-nedir-nasil-calisir,PtR3VF38DUOdDzApupgnQQ", "date": "2022-01-18", "written_by": "independent", "quote": "Geçtiğimiz haftalarda Google'ın sunduğu deprem uyarı sistemi, Alanya açıklarında meydana gelen 5.3'lük depremi 1 dakika öncesinden tahmin ederek kullanıcılarına sesli uyarı göndermişti." }, { "kind": "news report", "citation": "Yeni Akit (2022). Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır? Yeni Akit, 18 January 2022.", "title": "Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır?", "url": "https://www.yeniakit.com.tr/haber/android-deprem-uyari-sistemi-nedir-nasil-yapilir-nasil-kullanilir-1618101.html", "date": "2022-01-18", "written_by": "independent", "quote": "Android deprem uyarı sistemi sayesinde 5 Ocak 2022 sabahı Antalya’da meydana gelen depremin kısa süre öncesinde vatandaşlara uyarı yollandı." }, { "kind": "news report", "citation": "Hürriyet (2022). Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları. Hürriyet, 18 January 2022.", "title": "Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları", "url": "https://www.hurriyet.com.tr/galeri-deprem-uyari-sistemi-nasil-yapilir-nedir-android-erken-deprem-uyari-sistemi-kullanim-detaylari-41984292", "date": "2022-01-18", "written_by": "independent", "quote": "Olası bir depremi 10 saniye önceden haber verebilen deprem uyarı sistemi Alanya'da yaşanan depremi gerçekleşmeden 1 dakika kadar önce bölgede oturanlara Google tarafından bildirilmişti." }, { "kind": "dataset", "citation": "U.S. Geological Survey (2022). M 5.1 - 67 km SSW of Okurcalar, Turkey (event us7000g94d). USGS Earthquake Hazards Program.", "title": "M 5.1 - 67 km SSW of Okurcalar, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000g94d", "date": "2022-01-05", "written_by": "independent", "quote": "M 5.1 - 67 km SSW of Okurcalar, Turkey" }, { "kind": "news report", "citation": "Duckett C (2021). Android opens up earthquake alerts and end-to-end encrypted messages. ZDNet, 16 June 2021.", "title": "Android opens up earthquake alerts and end-to-end encrypted messages", "url": "https://www.zdnet.com/article/android-opens-up-earthquake-alerts-and-end-to-end-encrypted-messages/", "date": "2021-06-16", "written_by": "independent", "quote": "The system is already live in New Zealand and Greece, with Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan coming on board." }, { "kind": "press release", "citation": "Lee F (2021). 6 new features on Android this summer. Google, The Keyword, 15 June 2021.", "title": "6 new features on Android this summer", "url": "https://blog.google/products-and-platforms/platforms/android/new-features-summer-2021/", "date": "2021-06-15", "written_by": "makers", "quote": "Today, we're introducing the Android Earthquake Alerts System in Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan." }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "User feedback shows that 85% of people receiving an alert felt shaking, and 36, 28, and 23% received the alert before, during, and after shaking, respectively." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0111-source-0001", "AIBD-0111-source-0002", "AIBD-0111-source-0003", "AIBD-0111-source-0004", "AIBD-0111-source-0005", "AIBD-0111-source-0006", "AIBD-0111-source-0007", "AIBD-0111-source-0008", "AIBD-0111-source-0009", "AIBD-0111-source-0010", "AIBD-0111-source-0011", "AIBD-0111-source-0012", "AIBD-0111-source-0013", "AIBD-0111-source-0014" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Yeni Şafak (2022). Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı. Yeni Şafak, 5 January 2022.", "title": "Google depremi önceden bildi: Antalya depremi hissedilmeden kullanıcılarını uyardı", "url": "https://www.yenisafak.com/teknoloji/google-android-deprem-uyari-sistemi-nasil-acilir-deprem-uyari-sistemi-nedir-deprem-uyari-sistemi-hangi-telefonlarda-acilir-3728848", "date": "2022-01-05", "written_by": "independent", "quote": "Depremden saniyeler önce bazı Android kullanıcıları, Google Android’in deprem erken uyarı sisteminden depreme dair telefonlarına 5.3 büyüklüğünde bir depremin olacağına dair sesli ve görsel bir uyarı mesajı gönderildi." }, { "kind": "news report", "citation": "DonanımHaber (2022). Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi. DonanımHaber, 5 January 2022.", "title": "Google erken uyarı sistemi, Alanya depremini saniyeler öncesinden bildi", "url": "https://www.donanimhaber.com/google-erken-uyari-sistemi-alanya-depremini-onceden-bildi--143452", "date": "2022-01-05", "written_by": "independent", "quote": "Google deprem uyarı sistemi, erken saatlerde meydana gelen depremden saniyeler önce, o bölgede oturan kullanıcılara deprem uyarı sistemi aracılığıyla bir uyarı mesajı gönderdi." }, { "kind": "news report", "citation": "Öztürk T (2022). Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi? Hürriyet, 7 January 2022.", "title": "Erken uyarı sistemi tartışması! Depremin olacağını 10 saniye önceden bilmek güvenli mi?", "url": "https://www.hurriyet.com.tr/gundem/erken-uyari-sistemi-tartismasi-depremin-olacagini-10-saniye-onceden-bilmek-guvenli-mi-41976168", "date": "2022-01-07", "written_by": "independent", "quote": "Depremden yaklaşık 10 saniye önce, cep telefonlarına 'deprem olacak' bildirimi gitti." }, { "kind": "news report", "citation": "Hürriyet (2022). Google, Android Deprem Uyarı Sistemi’ni tanıttı. Hürriyet, 3 February 2022.", "title": "Google, Android Deprem Uyarı Sistemi’ni tanıttı", "url": "https://www.hurriyet.com.tr/teknoloji/google-android-deprem-uyari-sistemini-tanitti-41995996", "date": "2022-02-03", "written_by": "independent", "quote": "Ocak ayında ülkemizde merkezi Alanya ve Balıkesir olmak üzere 4.5 büyüklüğü üzeri iki depreme dair Android kullanıcılarına uyarı bildirisi gönderen Android Deprem Uyarı Sistemi" }, { "kind": "news report", "citation": "İndigo Dergisi (2022). Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi? İndigo Dergisi, 5 January 2022.", "title": "Google Deprem Uyarı Sistemi nasıl açılır? Alanya depremini 1 dakika önceden nasıl haber verdi?", "url": "https://indigodergisi.com/2022/01/google-deprem-uyari-sistemi-nasil-ailir/", "date": "2022-01-05", "written_by": "independent", "quote": "AFAD’dan yapılan açıklamada “Akdeniz’de Antalya’nın Alanya ilçesi açıklarında saat 06.21’de 5,3 büyüklüğünde bir deprem meydana geldi. Gelişmeleri takip ediyoruz” denildi." }, { "kind": "news report", "citation": "NTV (2022). Deprem uyarı sistemi nedir, nasıl çalışır? NTV, 18 January 2022.", "title": "Deprem uyarı sistemi nedir, nasıl çalışır?", "url": "https://www.ntv.com.tr/turkiye/deprem-uyari-sistemi-nedir-nasil-calisir,PtR3VF38DUOdDzApupgnQQ", "date": "2022-01-18", "written_by": "independent", "quote": "Geçtiğimiz haftalarda Google'ın sunduğu deprem uyarı sistemi, Alanya açıklarında meydana gelen 5.3'lük depremi 1 dakika öncesinden tahmin ederek kullanıcılarına sesli uyarı göndermişti." }, { "kind": "news report", "citation": "Yeni Akit (2022). Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır? Yeni Akit, 18 January 2022.", "title": "Android deprem uyarı sistemi nedir, nasıl yapılır, nasıl kullanılır?", "url": "https://www.yeniakit.com.tr/haber/android-deprem-uyari-sistemi-nedir-nasil-yapilir-nasil-kullanilir-1618101.html", "date": "2022-01-18", "written_by": "independent", "quote": "Android deprem uyarı sistemi sayesinde 5 Ocak 2022 sabahı Antalya’da meydana gelen depremin kısa süre öncesinde vatandaşlara uyarı yollandı." }, { "kind": "news report", "citation": "Hürriyet (2022). Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları. Hürriyet, 18 January 2022.", "title": "Deprem uyarı sistemi nasıl yapılır, nedir? Android erken deprem uyarı sistemi kullanım detayları", "url": "https://www.hurriyet.com.tr/galeri-deprem-uyari-sistemi-nasil-yapilir-nedir-android-erken-deprem-uyari-sistemi-kullanim-detaylari-41984292", "date": "2022-01-18", "written_by": "independent", "quote": "Olası bir depremi 10 saniye önceden haber verebilen deprem uyarı sistemi Alanya'da yaşanan depremi gerçekleşmeden 1 dakika kadar önce bölgede oturanlara Google tarafından bildirilmişti." }, { "kind": "dataset", "citation": "U.S. Geological Survey (2022). M 5.1 - 67 km SSW of Okurcalar, Turkey (event us7000g94d). USGS Earthquake Hazards Program.", "title": "M 5.1 - 67 km SSW of Okurcalar, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000g94d", "date": "2022-01-05", "written_by": "independent", "quote": "M 5.1 - 67 km SSW of Okurcalar, Turkey" }, { "kind": "news report", "citation": "Duckett C (2021). Android opens up earthquake alerts and end-to-end encrypted messages. ZDNet, 16 June 2021.", "title": "Android opens up earthquake alerts and end-to-end encrypted messages", "url": "https://www.zdnet.com/article/android-opens-up-earthquake-alerts-and-end-to-end-encrypted-messages/", "date": "2021-06-16", "written_by": "independent", "quote": "The system is already live in New Zealand and Greece, with Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan coming on board." }, { "kind": "press release", "citation": "Lee F (2021). 6 new features on Android this summer. Google, The Keyword, 15 June 2021.", "title": "6 new features on Android this summer", "url": "https://blog.google/products-and-platforms/platforms/android/new-features-summer-2021/", "date": "2021-06-15", "written_by": "makers", "quote": "Today, we're introducing the Android Earthquake Alerts System in Turkey, the Philippines, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan." }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "User feedback shows that 85% of people receiving an alert felt shaking, and 36, 28, and 23% received the alert before, during, and after shaking, respectively." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Android users near Alanya, Turkey, got Google's earthquake alert seconds before a M5.1 (AFAD 5.3) offshore quake on 5 January 2022.", "account": "At 06:21 local time on 5 January 2022 a magnitude 5.1 (USGS; AFAD 5.3) earthquake struck the Mediterranean about 57 km off Alanya, Antalya, Turkey. Depth: roughly 40 km. Yeni Şafak and DonanımHaber reported the same day on Google's Android Earthquake Alerts System, introduced in Turkey in June 2021. It sent an audible and visual alert for a magnitude 5.3 quake to Android users seconds before the shaking. Hürriyet put the lead at about 10 seconds, while NTV and İndigo Dergisi claimed about a minute. AFAD and the Alanya district governor reported no damage or injuries. On 3 February 2022 Google said the system had alerted users to two January quakes centered on Alanya and Balıkesir." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Android Earthquake Alerts System (crowdsourced phone-accelerometer detection; alerts for magnitude 4.5 and above)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Google's Android Earthquake Alerts reached Alanya phones seconds before the 5 January 2022 M5.1 (AFAD 5.3) Mediterranean quake", "headline": "Google alerts Alanya phones seconds before a M5.1 quake" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "65b16e850751b1199c57592eb6bfa2df4ce99dc8579627ff3f0d2be754b77e98" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At 06:21 local time on 5 January 2022 a magnitude 5.1 (USGS; AFAD 5.3) earthquake struck the Mediterranean about 57 km off Alanya, Antalya, Turkey. Depth: roughly 40 km. Yeni Şafak and DonanımHaber reported the same day on Google's Android Earthquake Alerts System, introduced in Turkey in June 2021. It sent an audible and visual alert for a magnitude 5.3 quake to Android users seconds before the shaking. Hürriyet put the lead at about 10 seconds, while NTV and İndigo Dergisi claimed about a minute. AFAD and the Alanya district governor reported no damage or injuries. On 3 February 2022 Google said the system had alerted users to two January quakes centered on Alanya and Balıkesir.", "replication": { "produced_by": [ "A magnitude 5.1 (AFAD 5.3) quake above the 4.5 alert threshold, centered about 57 km offshore and roughly 40 km deep. So the push alert could outrun the slower S-waves to the coast.", "Enough Android phones near the epicenter with Earthquake Alerts on to trigger Google's server-side detection. Per Google's 3 February 2022 presentation it runs on Android 5.0 and later and users can switch it off.", "Crowdsourced phone detection was the only input: Google partners with the ShakeAlert seismic network only in California, Oregon and Washington" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. Hürriyet reported on 7 January 2022 that most users who posted about the Alanya alert said they panicked", "The phone must have location and the Earthquake Alerts setting enabled" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0289", "title": "Smartwatch low-heart-rate alert (<40 bpm) sends a 32-year-old woman to hospital, where ciprofloxacin is identified as the cause of her bradycardia and replaced", "summary": "A smartwatch alert for a heart rate under 40 bpm two days after discharge on ciprofloxacin led to an ED visit; telemetry showed 30–50 bpm, the antibiotic was switched and the rate normalized.", "date_observed": "2022-01-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Cordova Sanchez, Chohan, Olatunde and White of SUNY Upstate Medical University, Syracuse, reported a case in the Journal of Investigative Medicine High Impact Case Reports. It was published 24 January 2022; the event date is not given. A 32-year-old woman was seen two days after discharge from a hospital stay for cholangitis, during which she had an ERCP. She was sent home on ciprofloxacin and metronidazole. She developed dizziness on minimal exertion, and her smartwatch triggered an alert for a sustained heart rate below 40 beats per minute. She attended an outside emergency department, where telemetry confirmed 30–50 bpm. She was transferred to the authors' hospital for cardiology review. Her electrocardiogram (ECG) showed sinus bradycardia at 51 bpm, against 66 bpm before the antibiotics. The procedural drugs given two days earlier have short half-lives. Other work-up (blood tests, thyroid function, Lyme serology, drug screen, echocardiogram) was unremarkable. Ciprofloxacin was replaced with ceftriaxone; by the next day her heart rate was 60–70 bpm. She was discharged on cefpodoxime and metronidazole. The authors conclude ciprofloxacin was the likely cause and early recognition of the bradycardia prevented a potential adverse event. The watch's brand and model are not stated; the authors describe wearable heart-rate detection generically as photoplethysmography.", "category": "benefit created", "unexpected": false, "purpose": "Smartwatch low-heart-rate alerts are built to prompt the wearer to seek review; this alert was that purpose. The authors add that consumer wearables may surface less commonly reported medication side effects.", "system": "Smartwatch low-heart-rate alert (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "Syracuse, United States", "domain": "Healthcare (cardiology; adverse drug reaction)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The alert led to recognition of symptomatic drug-induced bradycardia and a change of antibiotic, after which her heart rate normalized. The authors say a potential adverse event was prevented but document no event that was imminent." } ], "ai_role": { "status": "assessed", "statement": "The watch's sustained low-heart-rate alert, combined with her symptoms, is what the authors say prompted the hospital visit. Telemetry confirmed the rate and clinicians identified ciprofloxacin by exclusion and re-challenge-free withdrawal. The threshold alert is a simple rule on a photoplethysmographic heart-rate estimate, and the brand is unknown, so no learned model can be credited." }, "evidence": [ { "kind": "case report", "citation": "Cordova Sanchez A, Chohan M, Olatunde O, White C (2022). A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch. Journal of Investigative Medicine High Impact Case Reports 10:23247096211069761. doi:10.1177/23247096211069761 (PMC8793425).", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "Her smartwatch had triggered an alert for a sustained heart rate of less than 40 beats per minute (bpm), prompting her to present to the Emergency Department" }, { "kind": "case report", "citation": "Cordova Sanchez A et al. (2022), J Investig Med High Impact Case Rep 10:23247096211069761, management.", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "She was placed on continuous telemetry and ciprofloxacin was replaced with ceftriaxone." }, { "kind": "case report", "citation": "Cordova Sanchez A et al. (2022), J Investig Med High Impact Case Rep 10:23247096211069761, discussion.", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "Early recognition of bradycardia prevented a potential adverse event." } ], "replication": { "produced_by": [ "A wearer on a newly prescribed drug whose smartwatch has a low-heart-rate alert enabled", "Symptoms vague enough that the alert, not the symptoms alone, prompted presentation", "Clinicians who excluded other causes and withdrew the suspected drug" ], "must_hold": [ "The bradycardia is sustained long enough to trip the watch's threshold", "The wearer treats the alert as a reason to seek care" ], "echoes": [] }, "paired_incident": null, "headline": "Smartwatch alert under 40 bpm reveals ciprofloxacin bradycardia", "metric": "by the next day her heart rate was 60–70 bpm", "comparator": { "against": "presentation without the smartwatch alert", "before": "a potential adverse event", "after": "Early recognition of bradycardia", "basis": "assumed", "quote": "The combination of symptoms and smartwatch notification prompted her presentation to the hospital. Early recognition of bradycardia prevented a potential adverse event.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/" }, "later": { "status": "unknown", "date": null, "note": "Nothing after discharge on cefpodoxime and metronidazole was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0289", "catalog_version": "1.0.0", "source_fingerprint": "ca30118c9445cffda91367ed70564a00d8ec711083d178a0146dec52169c92b8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0289-source-0001", "AIBD-0289-source-0002", "AIBD-0289-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's sustained low-heart-rate alert, combined with her symptoms, is what the authors say prompted the hospital visit. Telemetry confirmed the rate and clinicians identified ciprofloxacin by exclusion and re-challenge-free withdrawal. The threshold alert is a simple rule on a photoplethysmographic heart-rate estimate, and the brand is unknown, so no learned model can be credited." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's sustained low-heart-rate alert, combined with her symptoms, is what the authors say prompted the hospital visit. Telemetry confirmed the rate and clinicians identified ciprofloxacin by exclusion and re-challenge-free withdrawal. 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It was published 24 January 2022; the event date is not given. A 32-year-old woman was seen two days after discharge from a hospital stay for cholangitis, during which she had an ERCP. She was sent home on ciprofloxacin and metronidazole. She developed dizziness on minimal exertion, and her smartwatch triggered an alert for a sustained heart rate below 40 beats per minute. She attended an outside emergency department, where telemetry confirmed 30–50 bpm. She was transferred to the authors' hospital for cardiology review. Her electrocardiogram (ECG) showed sinus bradycardia at 51 bpm, against 66 bpm before the antibiotics. The procedural drugs given two days earlier have short half-lives. Other work-up (blood tests, thyroid function, Lyme serology, drug screen, echocardiogram) was unremarkable. Ciprofloxacin was replaced with ceftriaxone; by the next day her heart rate was 60–70 bpm. She was discharged on cefpodoxime and metronidazole. The authors conclude ciprofloxacin was the likely cause and early recognition of the bradycardia prevented a potential adverse event. 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A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch. Journal of Investigative Medicine High Impact Case Reports 10:23247096211069761. doi:10.1177/23247096211069761 (PMC8793425).", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "Her smartwatch had triggered an alert for a sustained heart rate of less than 40 beats per minute (bpm), prompting her to present to the Emergency Department" }, { "kind": "case report", "citation": "Cordova Sanchez A et al. (2022), J Investig Med High Impact Case Rep 10:23247096211069761, management.", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "She was placed on continuous telemetry and ciprofloxacin was replaced with ceftriaxone." }, { "kind": "case report", "citation": "Cordova Sanchez A et al. 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A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch. Journal of Investigative Medicine High Impact Case Reports 10:23247096211069761. doi:10.1177/23247096211069761 (PMC8793425).", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "Her smartwatch had triggered an alert for a sustained heart rate of less than 40 beats per minute (bpm), prompting her to present to the Emergency Department" }, { "kind": "case report", "citation": "Cordova Sanchez A et al. (2022), J Investig Med High Impact Case Rep 10:23247096211069761, management.", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "She was placed on continuous telemetry and ciprofloxacin was replaced with ceftriaxone." }, { "kind": "case report", "citation": "Cordova Sanchez A et al. (2022), J Investig Med High Impact Case Rep 10:23247096211069761, discussion.", "title": "A Rare Case of Ciprofloxacin-Induced Bradycardia Recognized by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8793425/", "date": "2022-01-24", "written_by": "independent", "quote": "Early recognition of bradycardia prevented a potential adverse event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A smartwatch alert for a heart rate under 40 bpm two days after discharge on ciprofloxacin led to an ED visit; telemetry showed 30–50 bpm, the antibiotic was switched and the rate normalized.", "account": "Cordova Sanchez, Chohan, Olatunde and White of SUNY Upstate Medical University, Syracuse, reported a case in the Journal of Investigative Medicine High Impact Case Reports. It was published 24 January 2022; the event date is not given. A 32-year-old woman was seen two days after discharge from a hospital stay for cholangitis, during which she had an ERCP. She was sent home on ciprofloxacin and metronidazole. She developed dizziness on minimal exertion, and her smartwatch triggered an alert for a sustained heart rate below 40 beats per minute. She attended an outside emergency department, where telemetry confirmed 30–50 bpm. She was transferred to the authors' hospital for cardiology review. Her electrocardiogram (ECG) showed sinus bradycardia at 51 bpm, against 66 bpm before the antibiotics. The procedural drugs given two days earlier have short half-lives. Other work-up (blood tests, thyroid function, Lyme serology, drug screen, echocardiogram) was unremarkable. Ciprofloxacin was replaced with ceftriaxone; by the next day her heart rate was 60–70 bpm. She was discharged on cefpodoxime and metronidazole. The authors conclude ciprofloxacin was the likely cause and early recognition of the bradycardia prevented a potential adverse event. The watch's brand and model are not stated; the authors describe wearable heart-rate detection generically as photoplethysmography." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartwatch low-heart-rate alert (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Smartwatch low-heart-rate alert (<40 bpm) sends a 32-year-old woman to hospital, where ciprofloxacin is identified as the cause of her bradycardia and replaced", "headline": "Smartwatch alert under 40 bpm reveals ciprofloxacin bradycardia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ca30118c9445cffda91367ed70564a00d8ec711083d178a0146dec52169c92b8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Cordova Sanchez, Chohan, Olatunde and White of SUNY Upstate Medical University, Syracuse, reported a case in the Journal of Investigative Medicine High Impact Case Reports. It was published 24 January 2022; the event date is not given. A 32-year-old woman was seen two days after discharge from a hospital stay for cholangitis, during which she had an ERCP. She was sent home on ciprofloxacin and metronidazole. She developed dizziness on minimal exertion, and her smartwatch triggered an alert for a sustained heart rate below 40 beats per minute. She attended an outside emergency department, where telemetry confirmed 30–50 bpm. She was transferred to the authors' hospital for cardiology review. Her electrocardiogram (ECG) showed sinus bradycardia at 51 bpm, against 66 bpm before the antibiotics. The procedural drugs given two days earlier have short half-lives. Other work-up (blood tests, thyroid function, Lyme serology, drug screen, echocardiogram) was unremarkable. Ciprofloxacin was replaced with ceftriaxone; by the next day her heart rate was 60–70 bpm. She was discharged on cefpodoxime and metronidazole. The authors conclude ciprofloxacin was the likely cause and early recognition of the bradycardia prevented a potential adverse event. The watch's brand and model are not stated; the authors describe wearable heart-rate detection generically as photoplethysmography.", "replication": { "produced_by": [ "A wearer on a newly prescribed drug whose smartwatch has a low-heart-rate alert enabled", "Symptoms vague enough that the alert, not the symptoms alone, prompted presentation", "Clinicians who excluded other causes and withdrew the suspected drug" ], "must_hold": [ "The bradycardia is sustained long enough to trip the watch's threshold", "The wearer treats the alert as a reason to seek care" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0581", "title": "AI-assisted aneurysm detection supports Sophia Chan's emergency treatment and recovery at Mayo Clinic", "summary": "Sophia Chan survived a ruptured aneurysm after AI-assisted diagnosis and emergency treatment at Mayo Clinic.", "date_observed": "2022-02-01", "date_basis": "event", "date_precision": "month", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "In February 2022, Sophia Chan became unresponsive after an aneurysm ruptured. At Mayo Clinic in Jacksonville, AI helped clinicians locate it within minutes. She underwent surgery, although her husband was initially told that she was unlikely to survive. After weeks of stabilization, she recovered. Mayo reports that she had resumed an active family life two years later.", "category": "harm prevented", "unexpected": false, "purpose": "Accelerate stroke diagnosis and treatment.", "system": "AI analysis of brain CT images", "model_version": null, "developer": null, "deployer": "Mayo Clinic", "location": "Jacksonville, Florida, United States", "domain": "Stroke care", "segment": "Emergency patients with brain hemorrhage", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "Chan survived a critical hemorrhage and regained an active life. Mayo credits AI with aiding diagnosis." } ], "ai_role": { "status": "assessed", "statement": "AI helped locate the aneurysm. Clinicians provided treatment. The software and its separate effect on survival are unspecified." }, "evidence": [ { "kind": "report", "citation": "Mayo Clinic Magazine, January 2025.", "title": "Transforming Stroke Care and Outcomes Using AI", "url": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "date": null, "written_by": "deployer", "quote": "the AI algorithms that allowed the care team to find her aneurysm in minutes" } ], "replication": { "produced_by": [ "AI-assisted imaging, surgery, and intensive care." ], "must_hold": [ "Timely imaging, clinical review, and access to emergency treatment." ], "echoes": [] }, "paired_incident": null, "headline": "AI helps locate Sophia Chan's aneurysm before emergency treatment", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Mayo Clinic's original patient account and its embedded material. Kept it as one institutional source. Distinguished Sophia Chan's recovery from the page's general ischemic-stroke illustration, which does not measure her treatment time or neurons saved.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0581", "catalog_version": "1.0.0", "source_fingerprint": "1350009d81d5e22362617e6836f10066be92ecee61e8f6f5f2d5167587e9ad40", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0581-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Mayo Clinic" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AI helped locate the aneurysm. Clinicians provided treatment. The software and its separate effect on survival are unspecified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "AI helped locate the aneurysm. Clinicians provided treatment. 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"state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In February 2022, Sophia Chan became unresponsive after an aneurysm ruptured. At Mayo Clinic in Jacksonville, AI helped clinicians locate it within minutes. She underwent surgery, although her husband was initially told that she was unlikely to survive. After weeks of stabilization, she recovered. Mayo reports that she had resumed an active family life two years later.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Chan survived a critical hemorrhage and regained an active life. Mayo credits AI with aiding diagnosis." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Accelerate stroke diagnosis and treatment." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Jacksonville, Florida, United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Accelerate stroke diagnosis and treatment." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-02-01", "date_basis": "event", "date_precision": "month", "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Mayo Clinic's original patient account and its embedded material. Kept it as one institutional source. Distinguished Sophia Chan's recovery from the page's general ischemic-stroke illustration, which does not measure her treatment time or neurons saved.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0581-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "AI-assisted imaging, surgery, and intensive care." ], "must_hold": [ "Timely imaging, clinical review, and access to emergency treatment." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Mayo Clinic's original patient account and its embedded material. Kept it as one institutional source. Distinguished Sophia Chan's recovery from the page's general ischemic-stroke illustration, which does not measure her treatment time or neurons saved.", "source": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0581-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Stroke care", "segment": "Emergency patients with brain hemorrhage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "versions_and_access": [ { "source_url": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "version": "January 2025 magazine article; no exact publication day used." } ], "limitations": [ "The AI product and model version are unnamed.", "The contribution of AI to survival is not isolated from proximity to the hospital and clinical treatment.", "The DISCOVERY study mentioned in follow-up concerns later cognitive outcomes, not validation of the original AI-assisted rescue." ] } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0581-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The account leaves the AI product unnamed and does not separate its contribution from rapid access to hospital treatment. The later DISCOVERY study concerns cognition rather than verification of this rescue.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Mayo Clinic Magazine, January 2025.", "title": "Transforming Stroke Care and Outcomes Using AI", "url": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "written_by": "deployer", "quote": "the AI algorithms that allowed the care team to find her aneurysm in minutes" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0581-source-0001" ], "role": "Retained evidence sources in reviewed order" }, "provenance": { "kind": "curatorial", "basis": "Updated identifiers after consolidating duplicate excerpts and reviewing original sources.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0581-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Mayo Clinic Magazine, January 2025.", "title": "Transforming Stroke Care and Outcomes Using AI", "url": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "written_by": "deployer", "quote": "the AI algorithms that allowed the care team to find her aneurysm in minutes" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "lead_source_ref": "AIBD-0581-source-0001", "retained_source_order": [ "AIBD-0581-source-0001" ], "origins": [ { "url": "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "contribution": "Patient, husband and care-team accounts describe the February 2022 emergency, AI-assisted localization and recovery.", "locator": "A Ticking Clock; Accelerating Diagnosis and Intervention; The Difference a Minute Can Make.", "relationship": "Original reporting by the treating institution; no independent clinical publication is linked.", "source_refs": [ "AIBD-0581-source-0001" ] } ], "claim_chains": [ { "claim": "Sophia's treatment and recovery", "path": [ "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/" ], "finding": "The original source is Mayo's patient and care-team account. The page does not link a case paper, scan report, alert log or device specification." }, { "claim": "Background timing and neuron figures", "path": [ "https://mayomagazine.mayoclinic.org/2025/01/ai-in-stroke-care/", "42 Million Neurons Saved With AI Intervention infographic" ], "finding": "The 22-minute and 42-million-neuron figures concern an illustrative ischemic-stroke pathway. They are not patient-specific measurements and are not imported into this case." } ], "limitations": [ "The AI product and model version are unnamed.", "The contribution of AI to survival is not isolated from proximity to the hospital and clinical treatment.", "The DISCOVERY study mentioned in follow-up concerns later cognitive outcomes, not validation of the original AI-assisted rescue." ], "excluded_or_consolidated_sources": [], "review_scope": "Traced the claims in this case through accessible original publications and relevant embedded references, tables, appendices, corrections, and supplements. The stated access limits remain unresolved." } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0581-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Mayo Clinic’s magazine interviews Chan, her husband, and her care team. It links no independent clinical report of the episode.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Sophia Chan survived a ruptured aneurysm after AI-assisted diagnosis and emergency treatment at Mayo Clinic.", "account": "In February 2022, Sophia Chan became unresponsive after an aneurysm ruptured. At Mayo Clinic in Jacksonville, AI helped clinicians locate it within minutes. She underwent surgery, although her husband was initially told that she was unlikely to survive. After weeks of stabilization, she recovered. Mayo reports that she had resumed an active family life two years later." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI analysis of brain CT images" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-assisted aneurysm detection supports Sophia Chan's emergency treatment and recovery at Mayo Clinic", "headline": "AI helps locate Sophia Chan's aneurysm before emergency treatment" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1350009d81d5e22362617e6836f10066be92ecee61e8f6f5f2d5167587e9ad40" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Updated the fingerprint after this targeted source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In February 2022, Sophia Chan became unresponsive after an aneurysm ruptured. At Mayo Clinic in Jacksonville, AI helped clinicians locate it within minutes. She underwent surgery, although her husband was initially told that she was unlikely to survive. After weeks of stabilization, she recovered. Mayo reports that she had resumed an active family life two years later.", "replication": { "produced_by": [ "AI-assisted imaging, surgery, and intensive care." ], "must_hold": [ "Timely imaging, clinical review, and access to emergency treatment." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 6, "record_mapped": 24, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0164", "title": "DeepMind reinforcement-learning controller shapes TCV plasmas, including sustained twin “droplets”", "summary": "A deep RL controller commanding all 19 TCV coils produced and held elongated, negative-triangularity, snowflake and twin-droplet plasmas at EPFL's Swiss Plasma Center (Nature, 16 February 2022).", "date_observed": "2022-02-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Degrave et al. (Nature, published 16 February 2022; received 14 July 2021) describe a single deep neural network controller. It learns in simulation to command all 19 magnetic control coils of the Tokamak à Configuration Variable (TCV). TCV is a research tokamak at the Swiss Plasma Center, EPFL. Deployed on the real device, the controller produced and controlled elongated conventional shapes and advanced configurations such as negative triangularity and “snowflake” plasmas. It tracked location, current and shape. In one demonstration it established a snowflake with X-points 34 cm apart and narrowed the separation to 6.6 cm, combined RMSE 3.7 cm. It also sustained “droplets”, two separate plasmas maintained simultaneously in the vessel. MIT Technology Review (16 February 2022) reported that the AI controlled the real reactor without additional fine-tuning. It quoted independent expert Jonathan Citrin of the Dutch Institute for Fundamental Energy Research and Swiss Plasma Center director Ambrogio Fasoli. The experiment dates are not given.", "category": "benefit created", "unexpected": false, "purpose": "The controller was built to shape and maintain plasmas in TCV from high-level objectives; the configurations produced, including droplets, were its intended use.", "system": "DeepMind deep reinforcement learning magnetic controller for TCV (MLP policy commanding 19 coils)", "model_version": null, "developer": "DeepMind, with the Swiss Plasma Center, EPFL", "deployer": "Swiss Plasma Center, EPFL (TCV)", "location": "Lausanne, Switzerland", "domain": "Energy research (magnetic confinement fusion)", "segment": "Tokamak plasma control", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The result is a control capability on a research tokamak rather than an accuracy gain over a baseline.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 3, "reason": "The Swiss Plasma Center gained a controller the paper calls a notable advance for tokamak feedback control. It brought less design effort for new configurations and new droplet experiments." }, { "group": "societal", "depth": null, "reason": "No societal outcome beyond research progress is documented." } ], "ai_role": { "status": "assessed", "statement": "The reinforcement learning policy directly issued the coil voltage commands during the discharges, so the configurations are its output. The evidence is the peer-reviewed paper by the maker (DeepMind) and the operator (EPFL) plus an independent news report quoting an outside expert. Developer and deployer collaborated on the paper." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Degrave, J., Felici, F., Buchli, J. et al., 'Magnetic control of tokamak plasmas through deep reinforcement learning', Nature 602, 414–419 (2022), doi:10.1038/s41586-021-04301-9", "title": "Magnetic control of tokamak plasmas through deep reinforcement learning", "url": "https://www.nature.com/articles/s41586-021-04301-9", "date": "2022-02-16", "written_by": "makers", "quote": "We also demonstrate sustained ‘droplets’ on TCV, in which two separate plasmas are maintained simultaneously within the vessel." }, { "kind": "news report", "citation": "Will Douglas Heaven, 'DeepMind's AI can control superheated plasma inside a fusion reactor', MIT Technology Review, 16 February 2022", "title": "DeepMind's AI can control superheated plasma inside a fusion reactor", "url": "https://www.technologyreview.com/2022/02/16/1045470/deepminds-ai-can-control-superheated-plasma-inside-a-fusion-reactor/", "date": "2022-02-16", "written_by": "independent", "quote": "the researchers gave it control of the magnets in the Variable Configuration Tokamak (TCV), an experimental reactor in Lausanne." }, { "kind": "news report", "citation": "MIT Technology Review, 16 February 2022 (Jonathan Citrin, Dutch Institute for Fundamental Energy Research)", "title": "DeepMind's AI can control superheated plasma inside a fusion reactor", "url": "https://www.technologyreview.com/2022/02/16/1045470/deepminds-ai-can-control-superheated-plasma-inside-a-fusion-reactor/", "date": "2022-02-16", "written_by": "independent", "quote": "It's an incredibly powerful method. It's an important first step in a very exciting direction." }, { "kind": "preprint", "citation": "Tracey, B. D., Michi, A., Chervonyi, Y., et al. (2023). Towards practical reinforcement learning for tokamak magnetic control. arXiv:2307.11546, 21 July 2023 (v2 5 October 2023).", "title": "Towards practical reinforcement learning for tokamak magnetic control", "url": "https://arxiv.org/abs/2307.11546", "date": "2023-07-21", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A high-fidelity simulator (FGE) and equilibrium reconstruction (LIUQE) of the target tokamak available for training", "A flexible research tokamak with 19 independently actuated coils", "A real-time control system able to run a neural network policy at the required rate" ], "must_hold": [ "A simulator accurate enough for zero-shot transfer to the device", "Operator-specified targets within the device's physical and operational constraints", "Access to machine time on a research tokamak" ], "echoes": [ { "date": "2024-02-21", "setting": "DIII-D tokamak, San Diego; deep RL controller for tearing-instability avoidance (different objective)", "model_version": null, "outcome": "recurred", "source": "https://www.nature.com/articles/s41586-024-07024-9" } ] }, "paired_incident": null, "headline": "DeepMind RL controller shapes TCV plasmas and sustains droplets", "metric": "narrowed the separation to 6.6 cm with a combined RMSE of 3.7 cm", "comparator": null, "later": { "status": "persisted", "date": "2023-07-21", "note": "DeepMind and the Swiss Plasma Center reported upgraded RL controllers with up to 65% better shape accuracy in simulation and new validating experiments on TCV.", "quote": "We present simulation results that show up to 65\\% improvement in shape accuracy, achieve substantial reduction in the long-term bias of the plasma current, and additionally reduce the training time required to learn new tasks by a factor of 3 or more.", "url": "https://arxiv.org/abs/2307.11546" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "Switzerland", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://arxiv.org/abs/2307.11546", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://www.epfl.ch/research/domains/swiss-plasma-center/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study and the makers' preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0164", "catalog_version": "1.0.0", "source_fingerprint": "067f32980f20d353aff915cf6761f2d4e63e74512577a32df918c8220d5821b7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0164-source-0001", "AIBD-0164-source-0002", "AIBD-0164-source-0003", "AIBD-0164-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepMind, with the Swiss Plasma Center, EPFL", "deployer": "Swiss Plasma Center, EPFL (TCV)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The reinforcement learning policy directly issued the coil voltage commands during the discharges, so the configurations are its output. 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Towards practical reinforcement learning for tokamak magnetic control. arXiv:2307.11546, 21 July 2023 (v2 5 October 2023).", "title": "Towards practical reinforcement learning for tokamak magnetic control", "url": "https://arxiv.org/abs/2307.11546", "date": "2023-07-21", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A deep RL controller commanding all 19 TCV coils produced and held elongated, negative-triangularity, snowflake and twin-droplet plasmas at EPFL's Swiss Plasma Center (Nature, 16 February 2022).", "account": "Degrave et al. (Nature, published 16 February 2022; received 14 July 2021) describe a single deep neural network controller. It learns in simulation to command all 19 magnetic control coils of the Tokamak à Configuration Variable (TCV). TCV is a research tokamak at the Swiss Plasma Center, EPFL. Deployed on the real device, the controller produced and controlled elongated conventional shapes and advanced configurations such as negative triangularity and “snowflake” plasmas. It tracked location, current and shape. In one demonstration it established a snowflake with X-points 34 cm apart and narrowed the separation to 6.6 cm, combined RMSE 3.7 cm. It also sustained “droplets”, two separate plasmas maintained simultaneously in the vessel. MIT Technology Review (16 February 2022) reported that the AI controlled the real reactor without additional fine-tuning. It quoted independent expert Jonathan Citrin of the Dutch Institute for Fundamental Energy Research and Swiss Plasma Center director Ambrogio Fasoli. The experiment dates are not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DeepMind deep reinforcement learning magnetic controller for TCV (MLP policy commanding 19 coils)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind, with the Swiss Plasma Center, EPFL" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "DeepMind reinforcement-learning controller shapes TCV plasmas, including sustained twin “droplets”", "headline": "DeepMind RL controller shapes TCV plasmas and sustains droplets" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "067f32980f20d353aff915cf6761f2d4e63e74512577a32df918c8220d5821b7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Degrave et al. (Nature, published 16 February 2022; received 14 July 2021) describe a single deep neural network controller. It learns in simulation to command all 19 magnetic control coils of the Tokamak à Configuration Variable (TCV). TCV is a research tokamak at the Swiss Plasma Center, EPFL. Deployed on the real device, the controller produced and controlled elongated conventional shapes and advanced configurations such as negative triangularity and “snowflake” plasmas. It tracked location, current and shape. In one demonstration it established a snowflake with X-points 34 cm apart and narrowed the separation to 6.6 cm, combined RMSE 3.7 cm. It also sustained “droplets”, two separate plasmas maintained simultaneously in the vessel. MIT Technology Review (16 February 2022) reported that the AI controlled the real reactor without additional fine-tuning. It quoted independent expert Jonathan Citrin of the Dutch Institute for Fundamental Energy Research and Swiss Plasma Center director Ambrogio Fasoli. The experiment dates are not given.", "replication": { "produced_by": [ "A high-fidelity simulator (FGE) and equilibrium reconstruction (LIUQE) of the target tokamak available for training", "A flexible research tokamak with 19 independently actuated coils", "A real-time control system able to run a neural network policy at the required rate" ], "must_hold": [ "A simulator accurate enough for zero-shot transfer to the device", "Operator-specified targets within the device's physical and operational constraints", "Access to machine time on a research tokamak" ], "echoes": [ { "date": "2024-02-21", "setting": "DIII-D tokamak, San Diego; deep RL controller for tearing-instability avoidance (different objective)", "outcome": "recurred", "source": "https://www.nature.com/articles/s41586-024-07024-9" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0027", "title": "Fitbit Alta HR resting heart rate trend leading to early diagnosis and treatment of large vessel vasculitis", "summary": "Fitbit Alta HR resting-heart-rate rise from 55 to 75 bpm led to early diagnosis and treatment of large vessel vasculitis (Zurich).", "date_observed": "2022-02-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case report appeared in BMJ Case Reports on 28 February 2022 (event dates not reported). A 57-year-old woman in Zurich, Switzerland, noticed in her Fitbit Alta HR application a persistent rise in resting heart rate. It went from about 55 to about 75 beats per minute over three months, alongside non-specific constitutional symptoms. The elevated resting heart rate led her to seek advice at University Hospital Zurich. FDG-PET with computed tomography (CT) showed inflammation of the aorta and both subclavian and axillary arteries, consistent with large vessel vasculitis. Treatment with prednisone 50 mg daily and tocilizumab produced rapid improvement. Her resting heart rate normalized within 10 days and inflammatory markers within two weeks.", "category": "benefit created", "unexpected": true, "purpose": "The Fitbit Alta HR computes resting heart rate for fitness tracking; it was not built to detect vasculitis, so this benefit was not its purpose.", "system": "Fitbit Alta HR resting heart rate (Fitbit app)", "model_version": "Fitbit Alta HR", "developer": "Fitbit (Google)", "deployer": null, "location": "Zurich, Switzerland", "domain": "Healthcare (rheumatology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "One woman obtained an earlier diagnosis of giant cell arteritis with large vessel involvement and prompt immunosuppressive treatment that resolved her symptoms. A material benefit to one person." } ], "ai_role": { "status": "assessed", "statement": "The device's resting-heart-rate algorithm produced the trend the patient noticed; there was no alert, and the patient and clinicians drew the inference. The authors credit the elevated resting heart rate with an earlier diagnosis." }, "evidence": [ { "kind": "case report", "citation": "Gkikopoulos N, Wenger M, Distler O, Becker M (2022). Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis. BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8886383/", "date": "2022-02-28", "written_by": "independent", "quote": "The persistently elevated RHR led the patient to seek medical advice and contributed to an earlier diagnosis of a potentially severe disease." }, { "kind": "case report", "citation": "Gkikopoulos N et al. (2022). BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://doi.org/10.1136/bcr-2021-245021", "date": "2022-02-28", "written_by": "independent", "quote": "Treatment with glucocorticoids and tocilizumab led to a significant improvement of her symptoms and decrease in inflammatory parameters." } ], "replication": { "produced_by": [ "The wearer tracks resting heart rate over months with a Fitbit", "A systemic inflammatory illness raises resting heart rate persistently", "The wearer brings the trend to a clinician who pursues imaging" ], "must_hold": [ "A stable personal baseline exists", "The clinician treats the trend as a signal rather than noise", "Diagnostic imaging and immunosuppressive therapy are available" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1666", "title": "Oura Smart Ring Purchaser in California Alleged Company Overstated AI Sleep-Tracking Accuracy, Leading to Overpayment", "url": "https://incidentdatabase.ai/cite/1666", "severity": null, "group": "personal", "basis": "Consumer wearable health metric read in its app: a Fitbit resting-heart-rate trend proved true, while Oura's inferred sleep stages were allegedly less accurate than marketed, harming ring purchasers who relied on them." }, "headline": "Fitbit Alta HR heart-rate rise leads to vasculitis diagnosis", "metric": "resting heart rate had risen persistently from about 55 to about 75 beats per minute", "comparator": null, "later": { "status": "unknown", "date": null, "note": "Both cited entries are the same case report; no later development was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1666 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1666", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://support.google.com/product-documentation/answer/14816019", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent case reports. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0027", "catalog_version": "1.0.0", "source_fingerprint": "eeda0aac83a83a6d1cf0582ba329fde1920299f343bbb75b4ebf22380d42f449", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0027-source-0001", "AIBD-0027-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fitbit (Google)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The device's resting-heart-rate algorithm produced the trend the patient noticed; there was no alert, and the patient and clinicians drew the inference. 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A material benefit to one person." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Consumer wearable health metric read in its app: a Fitbit resting-heart-rate trend proved true, while Oura's inferred sleep stages were allegedly less accurate than marketed, harming ring purchasers who relied on them.", "links": [ { "database": "AI Incident Database", "identifier": "1666", "title": "Oura Smart Ring 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Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis. BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8886383/", "date": "2022-02-28", "written_by": "independent", "quote": "The persistently elevated RHR led the patient to seek medical advice and contributed to an earlier diagnosis of a potentially severe disease." }, { "kind": "case report", "citation": "Gkikopoulos N et al. (2022). BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://doi.org/10.1136/bcr-2021-245021", "date": "2022-02-28", "written_by": "independent", "quote": "Treatment with glucocorticoids and tocilizumab led to a significant improvement of her symptoms and decrease in inflammatory parameters." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0027-source-0001", "AIBD-0027-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Gkikopoulos N, Wenger M, Distler O, Becker M (2022). Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis. BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8886383/", "date": "2022-02-28", "written_by": "independent", "quote": "The persistently elevated RHR led the patient to seek medical advice and contributed to an earlier diagnosis of a potentially severe disease." }, { "kind": "case report", "citation": "Gkikopoulos N et al. (2022). BMJ Case Reports 15(2):e245021.", "title": "Self-monitoring of the resting heart rate using a fitness tracker smartwatch application leads to an early diagnosis of large vessel vasculitis", "url": "https://doi.org/10.1136/bcr-2021-245021", "date": "2022-02-28", "written_by": "independent", "quote": "Treatment with glucocorticoids and tocilizumab led to a significant improvement of her symptoms and decrease in inflammatory parameters." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Fitbit Alta HR resting-heart-rate rise from 55 to 75 bpm led to early diagnosis and treatment of large vessel vasculitis (Zurich).", "account": "A case report appeared in BMJ Case Reports on 28 February 2022 (event dates not reported). A 57-year-old woman in Zurich, Switzerland, noticed in her Fitbit Alta HR application a persistent rise in resting heart rate. It went from about 55 to about 75 beats per minute over three months, alongside non-specific constitutional symptoms. The elevated resting heart rate led her to seek advice at University Hospital Zurich. FDG-PET with computed tomography (CT) showed inflammation of the aorta and both subclavian and axillary arteries, consistent with large vessel vasculitis. Treatment with prednisone 50 mg daily and tocilizumab produced rapid improvement. Her resting heart rate normalized within 10 days and inflammatory markers within two weeks." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The device calculated resting heart rate over time." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used a Fitbit Alta HR." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Fitbit Alta HR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fitbit Alta HR resting heart rate (Fitbit app)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Fitbit (Google)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fitbit Alta HR resting heart rate trend leading to early diagnosis and treatment of large vessel vasculitis", "headline": "Fitbit Alta HR heart-rate rise leads to vasculitis diagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "eeda0aac83a83a6d1cf0582ba329fde1920299f343bbb75b4ebf22380d42f449" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report appeared in BMJ Case Reports on 28 February 2022 (event dates not reported). A 57-year-old woman in Zurich, Switzerland, noticed in her Fitbit Alta HR application a persistent rise in resting heart rate. It went from about 55 to about 75 beats per minute over three months, alongside non-specific constitutional symptoms. The elevated resting heart rate led her to seek advice at University Hospital Zurich. FDG-PET with computed tomography (CT) showed inflammation of the aorta and both subclavian and axillary arteries, consistent with large vessel vasculitis. Treatment with prednisone 50 mg daily and tocilizumab produced rapid improvement. Her resting heart rate normalized within 10 days and inflammatory markers within two weeks.", "replication": { "produced_by": [ "The wearer tracks resting heart rate over months with a Fitbit", "A systemic inflammatory illness raises resting heart rate persistently", "The wearer brings the trend to a clinician who pursues imaging" ], "must_hold": [ "A stable personal baseline exists", "The clinician treats the trend as a signal rather than noise", "Diagnostic imaging and immunosuppressive therapy are available" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0369", "title": "Westchester County police use Rekor plate-reader pattern analysis to stop David Zayas in Scarsdale; crack cocaine, cash and a pistol found and he is convicted", "summary": "Westchester County PD's Rekor system flagged David Zayas's driving pattern across 480 cameras; a March 2022 stop in Scarsdale found crack cocaine, cash and a pistol; he was convicted (Carscoops).", "date_observed": "2022-03-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Carscoops reports that the Westchester County Police Department, New York, used technology provided by Rekor. It examined the driving patterns of anyone passing its 480 license-plate-reader cameras over a two-year period. It determined that David Zayas had made several trips along routes typically used by drug traffickers and turned around quickly to go home. In March 2022 Zayas was driving a gray Chevrolet in Scarsdale. Officers pulled him over, searched the car and found crack cocaine, cash and a pistol. The case ended in his conviction (Carscoops, 18 July 2023, drawing on Forbes). The Star's AFP Relaxnews item adds that police took an interest in a vehicle registered to Zayas in March 2022. The OECD Monitor summary says the system analyzed billions of plate records and lists rights and public-interest harms. Carscoops quotes ACLU lawyer Brett Max Kaufman and defense attorney Ben Gold criticizing the surveillance. Only the month is given, so 1 March 2022 is used.", "category": "benefit created", "unexpected": false, "purpose": "Carscoops describes Rekor's Public Safety Network as aggregating vehicle location data from its customers so police can examine driving patterns. Flagging a pattern associated with drug trafficking for a stop is that function, not a side effect.", "system": "Rekor license-plate-reader pattern analysis (Rekor Public Safety Network data) used by the Westchester County Police Department", "model_version": null, "developer": "Rekor", "deployer": "Westchester County Police Department", "location": "Scarsdale, United States", "domain": "Policing / drug trafficking", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-07-17-994a" }, "ratings": [ { "group": "societal", "depth": 2, "reason": "A driver found with crack cocaine, cash and a pistol was convicted after the AI-flagged stop, per Carscoops. The quantities, the charges and the sentence are not in the sources on record, which do not include the Forbes report that cited court documents." } ], "ai_role": { "status": "assessed", "statement": "Per Carscoops, Rekor-supplied analysis over 480 cameras and two years of reads produced the ground for the stop. That was several trips on routes typically used by drug traffickers with quick turnarounds. Everything after the flag was police work; the conviction rested on what the search found. The original Forbes report, which cited court filings, is not among the sources. The sources on record give no accuracy figure, no count of other flagged drivers and no court ruling on the stop. Carscoops quotes Ben Gold calling avoidance of the system unfeasible and Brett Max Kaufman calling the surveillance's scale massive." }, "evidence": [ { "kind": "news report", "citation": "Bell, S. (2023). Police Use AI To Analyze Driving Patterns And Surveil All Drivers. Carscoops, 18 July 2023.", "title": "Police Use AI To Analyze Driving Patterns And Surveil All Drivers", "url": "https://www.carscoops.com/2023/07/police-use-ai-to-analyze-driving-patterns-and-surveil-all-drivers", "date": "2023-07-18", "written_by": "independent", "quote": "Westchester PD was able to determine that Zayas made several trips along routes typically used by drug traffickers, and turned around quickly to go home." }, { "kind": "news report", "citation": "Bell, S. (2023). Police Use AI To Analyze Driving Patterns And Surveil All Drivers. Carscoops, 18 July 2023 (second quotation).", "title": "Police Use AI To Analyze Driving Patterns And Surveil All Drivers", "url": "https://www.carscoops.com/2023/07/police-use-ai-to-analyze-driving-patterns-and-surveil-all-drivers", "date": "2023-07-18", "written_by": "independent", "quote": "Westchester PD pulled him over and searched his car and found crack cocaine, cash, and a pistol." }, { "kind": "news report", "citation": "AFP Relaxnews (2023). How AI helped catch a drug trafficker. The Star (Malaysia), 20 July 2023.", "title": "How AI helped catch a drug trafficker", "url": "https://www.thestar.com.my/tech/tech-news/2023/07/20/how-ai-helped-catch-a-drug-trafficker", "date": "2023-07-20", "written_by": "independent", "quote": "In March 2022, the police took an interest in the behaviour of a vehicle registered to a certain David Zayas." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2023). AI-Powered License Plate Surveillance Leads to Drug Trafficker Arrest in New York. 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Carscoops, 18 July 2023 (second quotation).", "title": "Police Use AI To Analyze Driving Patterns And Surveil All Drivers", "url": "https://www.carscoops.com/2023/07/police-use-ai-to-analyze-driving-patterns-and-surveil-all-drivers", "date": "2023-07-18", "written_by": "independent", "quote": "Westchester PD pulled him over and searched his car and found crack cocaine, cash, and a pistol." }, { "kind": "news report", "citation": "AFP Relaxnews (2023). How AI helped catch a drug trafficker. The Star (Malaysia), 20 July 2023.", "title": "How AI helped catch a drug trafficker", "url": "https://www.thestar.com.my/tech/tech-news/2023/07/20/how-ai-helped-catch-a-drug-trafficker", "date": "2023-07-20", "written_by": "independent", "quote": "In March 2022, the police took an interest in the behaviour of a vehicle registered to a certain David Zayas." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2023). AI-Powered License Plate Surveillance Leads to Drug Trafficker Arrest in New York. OECD.AI, 17 July 2023.", "title": "AI-Powered License Plate Surveillance Leads to Drug Trafficker Arrest in New York", "url": "https://oecd.ai/en/incidents/2023-07-17-994a", "date": "2023-07-17", "written_by": "independent", "quote": "This led to the stop and arrest of David Zayas, who was found with drugs, cash, and a weapon." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0369-source-0001", "AIBD-0369-source-0002", "AIBD-0369-source-0003", "AIBD-0369-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Bell, S. (2023). Police Use AI To Analyze Driving Patterns And Surveil All Drivers. Carscoops, 18 July 2023.", "title": "Police Use AI To Analyze Driving Patterns And Surveil All Drivers", "url": "https://www.carscoops.com/2023/07/police-use-ai-to-analyze-driving-patterns-and-surveil-all-drivers", "date": "2023-07-18", "written_by": "independent", "quote": "Westchester PD was able to determine that Zayas made several trips along routes typically used by drug traffickers, and turned around quickly to go home." }, { "kind": "news report", "citation": "Bell, S. (2023). Police Use AI To Analyze Driving Patterns And Surveil All Drivers. Carscoops, 18 July 2023 (second quotation).", "title": "Police Use AI To Analyze Driving Patterns And Surveil All Drivers", "url": "https://www.carscoops.com/2023/07/police-use-ai-to-analyze-driving-patterns-and-surveil-all-drivers", "date": "2023-07-18", "written_by": "independent", "quote": "Westchester PD pulled him over and searched his car and found crack cocaine, cash, and a pistol." }, { "kind": "news report", "citation": "AFP Relaxnews (2023). How AI helped catch a drug trafficker. The Star (Malaysia), 20 July 2023.", "title": "How AI helped catch a drug trafficker", "url": "https://www.thestar.com.my/tech/tech-news/2023/07/20/how-ai-helped-catch-a-drug-trafficker", "date": "2023-07-20", "written_by": "independent", "quote": "In March 2022, the police took an interest in the behaviour of a vehicle registered to a certain David Zayas." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2023). AI-Powered License Plate Surveillance Leads to Drug Trafficker Arrest in New York. OECD.AI, 17 July 2023.", "title": "AI-Powered License Plate Surveillance Leads to Drug Trafficker Arrest in New York", "url": "https://oecd.ai/en/incidents/2023-07-17-994a", "date": "2023-07-17", "written_by": "independent", "quote": "This led to the stop and arrest of David Zayas, who was found with drugs, cash, and a weapon." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Westchester County PD's Rekor system flagged David Zayas's driving pattern across 480 cameras; a March 2022 stop in Scarsdale found crack cocaine, cash and a pistol; he was convicted (Carscoops).", "account": "Carscoops reports that the Westchester County Police Department, New York, used technology provided by Rekor. It examined the driving patterns of anyone passing its 480 license-plate-reader cameras over a two-year period. It determined that David Zayas had made several trips along routes typically used by drug traffickers and turned around quickly to go home. In March 2022 Zayas was driving a gray Chevrolet in Scarsdale. Officers pulled him over, searched the car and found crack cocaine, cash and a pistol. The case ended in his conviction (Carscoops, 18 July 2023, drawing on Forbes). The Star's AFP Relaxnews item adds that police took an interest in a vehicle registered to Zayas in March 2022. The OECD Monitor summary says the system analyzed billions of plate records and lists rights and public-interest harms. Carscoops quotes ACLU lawyer Brett Max Kaufman and defense attorney Ben Gold criticizing the surveillance. Only the month is given, so 1 March 2022 is used." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Rekor license-plate-reader pattern analysis (Rekor Public Safety Network data) used by the Westchester County Police Department" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rekor" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Westchester County police use Rekor plate-reader pattern analysis to stop David Zayas in Scarsdale; crack cocaine, cash and a pistol found and he is convicted", "headline": "Rekor plate-pattern analysis leads to a Scarsdale drug stop" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d6b8af6c234b5590e85d31593bf1abe48e30ebfbbeabb5bb0fbf7aea9258142a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Carscoops reports that the Westchester County Police Department, New York, used technology provided by Rekor. It examined the driving patterns of anyone passing its 480 license-plate-reader cameras over a two-year period. It determined that David Zayas had made several trips along routes typically used by drug traffickers and turned around quickly to go home. In March 2022 Zayas was driving a gray Chevrolet in Scarsdale. Officers pulled him over, searched the car and found crack cocaine, cash and a pistol. The case ended in his conviction (Carscoops, 18 July 2023, drawing on Forbes). The Star's AFP Relaxnews item adds that police took an interest in a vehicle registered to Zayas in March 2022. The OECD Monitor summary says the system analyzed billions of plate records and lists rights and public-interest harms. Carscoops quotes ACLU lawyer Brett Max Kaufman and defense attorney Ben Gold criticizing the surveillance. Only the month is given, so 1 March 2022 is used.", "replication": { "produced_by": [ "A county network of 480 license-plate-reader cameras feeding Rekor's aggregated vehicle-location data", "Pattern analysis over two years of reads that flags routes and quick turnarounds associated with drug trafficking", "A traffic stop and vehicle search by officers acting on the flag" ], "must_hold": [ "The flagged pattern must be a lawful basis for a stop and search, which defense counsel contested", "Officers must corroborate the pattern with evidence found at the stop", "Retention and analysis of plate data over years must be permitted" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0275", "title": "Google deep-learning DR screening in Thailand's national program: 7,651 patients, specialist-level accuracy", "summary": "At nine primary-care sites (Dec 2018-Mar 2020) Google's deep-learning system graded fundus photos in real time, 94.7% accuracy for vision-threatening DR, 2,412 referrals; a fifth of images rejected.", "date_observed": "2022-03-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Ruamviboonsuk et al. (Lancet Digital Health, 7 March 2022) report a prospective interventional cohort study funded by Google and Rajavithi Hospital with Google Health co-authors. It deployed a deep-learning system at nine primary-care sites of Thailand's national diabetic retinopathy screening program between 12 December 2018 and 29 March 2020. Of 7,940 patients screened, 7,651 were analyzed and 2,412 (31.5%) were referred for retinopathy, macular edema, ungradable images or low acuity. For vision-threatening retinopathy the system's accuracy was 94.7%, sensitivity 91.4% and specificity 95.4%. The retina-specialist over-readers scored 93.5%, 84.8% and 95.5%. MIT Technology Review (27 April 2020) reported Google's own field study of the deployment in 11 clinics. Over a fifth of images were rejected, nurses were frustrated by rejections and slow internet, and when it worked the system sped screening. The Nation Thailand (10 February 2025) reported Google and Perceptra planning AI screening for about 1 million people in Thailand over a decade. It cited over 600,000 patients screened with the model globally. The paper's abstract is among the sources.", "category": "benefit created", "unexpected": false, "purpose": "Real-time automated grading of fundus photographs for diabetic retinopathy in a national screening program", "system": "Google Health deep-learning diabetic retinopathy screening system", "model_version": "ARDA", "developer": "Google (Google Health)", "deployer": "Thailand national diabetic retinopathy screening program (Ministry of Public Health guidelines) with Rajavithi Hospital, Bangkok", "location": "Thailand (nine primary-care sites)", "domain": "Health; ophthalmology", "segment": "People with diabetes due for retinopathy screening", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "7,651 patients received real-time grading with specialist-level accuracy and 2,412 were referred." }, { "group": "organizational", "depth": 1, "reason": "Real-time results in primary care; field reporting notes speed gains when the system worked and rejections and connectivity problems when it did not." }, { "group": "societal", "depth": null, "reason": "No population-level vision outcome reported." } ], "ai_role": { "status": "assessed", "statement": "The deep-learning grades and referral recommendations were delivered in real time with specialist over-reading as a safety net. Accuracy figures come from the vendor-funded, vendor co-authored prospective study. An independent news account of Google's field study records substantial image rejection and nurse frustration." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Ruamviboonsuk P, Tiwari R, Sayres R, et al. Lancet Digit Health 4(4):e235-e244 (2022)", "title": "Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study", "url": "https://doi.org/10.1016/s2589-7500(22)00017-6", "date": "2022-03-07", "written_by": "makers", "quote": "A deep-learning system can deliver real-time diabetic retinopathy detection capability similar to retina specialists in community-based screening settings." }, { "kind": "news report", "citation": "Heaven WD. MIT Technology Review, 27 Apr 2020", "title": "Google's medical AI was super accurate in a lab. Real life was a different story.", "url": "https://www.technologyreview.com/2020/04/27/1000658/google-medical-ai-accurate-lab-real-life-clinic-covid-diabetes-retina-disease/", "date": "2020-04-27", "written_by": "independent", "quote": "Nurses felt frustrated, especially when they believed the rejected scans showed no signs of disease and the follow-up appointments were unnecessary." }, { "kind": "news report", "citation": "The Nation Thailand, 10 Feb 2025", "title": "Google, Perceptra offer AI-powered diabetic retinopathy screening", "url": "https://www.nationthailand.com/business/tech/40046121", "date": "2025-02-10", "written_by": "independent", "quote": "From initial research to the first patient screening in Thailand, we are committed to translating the potential of AI into meaningful change." }, { "kind": "other", "citation": "Nature Medicine 32:3525-3527 (23 Sep 2026). Comment by Google and partner-site authors on scaling deep-learning diabetic retinopathy screening across India, Thailand and Australia.", "title": "Nature Medicine comment on scaling a deep learning diabetic retinopathy tool across India, Thailand and Australia", "url": "https://www.nature.com/articles/s41591-026-04643-9", "date": "2026-09-23", "written_by": "makers", "quote": null }, { "kind": "other", "citation": "AI Weekly (6 Oct 2026). Google ARDA eye AI tops a million patients in three countries.", "title": "Google ARDA eye AI tops a million patients in three countries", "url": "https://aiweekly.co/alerts/google-arda-eye-ai-tops-a-million-patients-in-three-countries", "date": "2026-10-06", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Fundus photography at primary-care sites", "Real-time deep-learning grading with referral recommendations", "Retina-specialist over-reading as a safety mechanism" ], "must_hold": [ "Image quality sufficient for grading (a fifth of images were rejected in the 2020 field study)", "Reliable connectivity", "Referral pathways able to absorb referrals" ], "echoes": [ { "date": "2025-02-10", "setting": "Google-Perceptra program to screen about 1 million people in Thailand over a decade (announcement)", "model_version": null, "outcome": "unknown", "source": "https://www.nationthailand.com/business/tech/40046121" }, { "date": "2022-10-15", "setting": "Same Thai community-based national screening program, 4,852 participants and eight non-mydriatic camera types: the deep-learning algorithm showed better sensitivity, specificity and kappa than human graders (Srinivasan et al., Life)", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.3390/life12101610" } ] }, "paired_incident": null, "headline": "Google DR screening in Thailand matches specialists at 94.7%", "metric": "94.7% accuracy for vision-threatening DR, 2,412 referrals", "comparator": { "against": "regional retina specialist over-readers, measured against an adjudicated reference standard from fellowship-trained retina specialists", "before": "an accuracy of 93·5 (91·7-95·0; p=0·17), a sensitivity of 84·8% (79·4-90·0; p=0·024), and specificity of 95·5% (94·1-96·7; p=0·98)", "after": "an accuracy of 94·7% (95% CI 93·0-96·2), sensitivity of 91·4% (87·1-95·0), and specificity of 95·4% (94·1-96·7)", "basis": "measured", "quote": "For vision-threatening diabetic retinopathy, the deep-learning system had an accuracy of 94·7% (95% CI 93·0-96·2), sensitivity of 91·4% (87·1-95·0), and specificity of 95·4% (94·1-96·7). The retina specialist over-readers had an accuracy of 93·5 (91·7-95·0; p=0·17), a sensitivity of 84·8% (79·4-90·0; p=0·024), and specificity of 95·5% (94·1-96·7; p=0·98).", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=TITLE:%22Real-time%20diabetic%20retinopathy%20screening%20by%20deep%20learning%20in%20a%20multisite%20national%20screening%20programme%22&resultType=core&format=json" }, "later": { "status": "scaled", "date": "2026-09-23", "note": "A Nature Medicine comment of 23 September 2026 by the Google and partner-site authors describes scaling the same deep-learning screening tool across India, Thailand and Australia; an October 2026 AI Weekly alert summarizing it says the model, ARDA, has now screened more than one million patients, with Perceptra licensed to run screening in Thailand.", "quote": "Scaling a successful deep learning tool across three highly distinct settings – in India, Thailand and Australia — offers cross-cutting insights that may inform the expansion of healthcare artificial intelligence globally.", "url": "https://www.nature.com/articles/s41591-026-04643-9" }, "value": null, "developer_country": "United States", "deployer_country": "Thailand", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged a second write-up of the same study: added the 2022 Life replication in the same Thai program.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=TITLE:%22Real-time%20diabetic%20retinopathy%20screening%20by%20deep%20learning%20in%20a%20multisite%20national%20screening%20programme%22&resultType=core&format=json; https://www.nature.com/articles/s41591-026-04643-9; https://aiweekly.co/alerts/google-arda-eye-ai-tops-a-million-patients-in-three-countries", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Ministry_of_Public_Health_(Thailand)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, one other independent source, the makers' peer-reviewed study and the makers' other. 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(Lancet Digital Health, 7 March 2022) report a prospective interventional cohort study funded by Google and Rajavithi Hospital with Google Health co-authors. It deployed a deep-learning system at nine primary-care sites of Thailand's national diabetic retinopathy screening program between 12 December 2018 and 29 March 2020. Of 7,940 patients screened, 7,651 were analyzed and 2,412 (31.5%) were referred for retinopathy, macular edema, ungradable images or low acuity. For vision-threatening retinopathy the system's accuracy was 94.7%, sensitivity 91.4% and specificity 95.4%. The retina-specialist over-readers scored 93.5%, 84.8% and 95.5%. MIT Technology Review (27 April 2020) reported Google's own field study of the deployment in 11 clinics. Over a fifth of images were rejected, nurses were frustrated by rejections and slow internet, and when it worked the system sped screening. The Nation Thailand (10 February 2025) reported Google and Perceptra planning AI screening for about 1 million people in Thailand over a decade. It cited over 600,000 patients screened with the model globally. The paper's abstract is among the sources.", "replication": { "produced_by": [ "Fundus photography at primary-care sites", "Real-time deep-learning grading with referral recommendations", "Retina-specialist over-reading as a safety mechanism" ], "must_hold": [ "Image quality sufficient for grading (a fifth of images were rejected in the 2020 field study)", "Reliable connectivity", "Referral pathways able to absorb referrals" ], "echoes": [ { "date": "2025-02-10", "setting": "Google-Perceptra program to screen about 1 million people in Thailand over a decade (announcement)", "outcome": "unknown", "source": "https://www.nationthailand.com/business/tech/40046121" }, { "date": "2022-10-15", "setting": "Same Thai community-based national screening program, 4,852 participants and eight non-mydriatic camera types: the deep-learning algorithm showed better sensitivity, specificity and kappa than human graders (Srinivasan et al., Life)", "outcome": "recurred", "source": "https://doi.org/10.3390/life12101610" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0017", "title": "Ithaca: deep neural network for restoring, placing and dating ancient Greek inscriptions (capability study)", "summary": "Ithaca restores and dates Greek inscriptions with measured accuracy gains; no specific accepted restoration verified.", "date_observed": "2022-03-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 9 March 2022 Nature published Ithaca, a deep neural network built by DeepMind with the Universities of Venice Ca' Foscari, Oxford and Athens. Authors include Assael, Sommerschield, Prag and de Freitas. It restores missing text in damaged ancient Greek inscriptions and attributes them to place and date. Ithaca restored text with 62 percent accuracy alone and raised historians' accuracy from 25 to 72 percent when they worked with it. It attributed inscriptions geographically with 71 percent accuracy and dated them to within about 30 years. Its average date of 421 BC for a group of disputed Athenian decrees agreed with recent independent re-dating. 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University news.", "title": "AI to aid historians in restoring, placing and dating ancient texts", "url": "https://www.unive.it/pag/16584/?tx_news_pi1%5Bnews%5D=12037", "date": "2022-03-09", "written_by": "makers", "quote": "have already used the model to shed light on current disputes in Greek history" }, { "kind": "report", "citation": "Roueché, C. (2022). AI minds the gap and fills in missing Greek inscriptions. Nature, News & Views, 9 March 2022. doi:10.1038/d41586-022-00641-2", "title": "AI minds the gap and fills in missing Greek inscriptions", "url": "https://www.nature.com/articles/d41586-022-00641-2", "date": "2022-03-09", "written_by": "independent", "quote": "A new AI tool helps to fill in missing text and estimate the timeframe and geographical origin of ancient inscriptions." }, { "kind": "news report", "citation": "Google DeepMind's new AI can help historians understand ancient Latin inscriptions. MIT Technology Review, 23 July 2025.", "title": "Google DeepMind's new AI can help historians understand ancient Latin inscriptions", "url": "https://www.technologyreview.com/2025/07/23/1120574/deepmind-ai-aeneas-helps-historians-interpret-latin-inscriptions/", "date": "2025-07-23", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A large digitized corpus of inscriptions with known provenance and date", "A neural network trained on artificially damaged text", "Evaluation against held-out inscriptions and with historians in the loop" ], "must_hold": [ "A verified event of a benefit created or restored would require an epigrapher-accepted restoration or re-dating attributable to the model and documented in a non-vendor source" ], "echoes": [] }, "paired_incident": null, "headline": "Ithaca raises historians' accuracy from 25 to 72 percent", "metric": "raised historians' accuracy from 25 to 72 percent when they worked with it", "comparator": { "against": "historians restoring damaged texts without the tool", "before": "25%", "after": "72% (historians using Ithaca); 62% for Ithaca alone", "basis": "measured", "quote": "While Ithaca alone achieves 62% accuracy when restoring damaged texts, the use of Ithaca by historians improved their accuracy from 25% to 72%, confirming the synergistic effect of this research tool.", "url": "https://europepmc.org/article/PMC/PMC8907065" }, "later": { "status": "scaled", "date": "2025-07-23", "note": "DeepMind followed Ithaca with Aeneas, a successor model for Latin inscriptions published in Nature on 23 July 2025, extending the approach to a second language and to retrieval of parallel texts.", "quote": "It follows Google's previous archaeological tool Ithaca, which also used deep learning to reconstruct and contextualize ancient text, in its case Greek. But while Ithaca and Aeneas use some similar systems, Aeneas also promises to give researchers jumping-off points for further analysis.", "url": "https://www.technologyreview.com/2025/07/23/1120574/deepmind-ai-aeneas-helps-historians-interpret-latin-inscriptions/" }, "value": null, "developer_country": "United Kingdom", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Verification sweep: both sources were written by Ithaca's developers (DeepMind and Ca' Foscari), so the Ca' Foscari page is now marked vendor-authored and a Nature News & Views by Charlotte Roueché, who is not an author of the paper, is added as the independent source.", "source": "https://www.nature.com/articles/d41586-022-00641-2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC8907065; https://www.technologyreview.com/2025/07/23/1120574/deepmind-ai-aeneas-helps-historians-interpret-latin-inscriptions/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, one independent news report, the makers' peer-reviewed study and the makers' press release. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Ithaca (2022)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Ithaca (transformer-based deep neural network for epigraphic restoration and attribution)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind with Ca' Foscari University of Venice, University of Oxford and Athens University of Economics and Business" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Ithaca: deep neural network for restoring, placing and dating ancient Greek inscriptions (capability study)", "headline": "Ithaca raises historians' accuracy from 25 to 72 percent" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "302890ae1f7d56f3ea61c181dd07fed38ed62453610ee0492cdfece78ec510bf" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 9 March 2022 Nature published Ithaca, a deep neural network built by DeepMind with the Universities of Venice Ca' Foscari, Oxford and Athens. Authors include Assael, Sommerschield, Prag and de Freitas. It restores missing text in damaged ancient Greek inscriptions and attributes them to place and date. Ithaca restored text with 62 percent accuracy alone and raised historians' accuracy from 25 to 72 percent when they worked with it. It attributed inscriptions geographically with 71 percent accuracy and dated them to within about 30 years. Its average date of 421 BC for a group of disputed Athenian decrees agreed with recent independent re-dating. The cited sources report accuracy studies and a public interface, not a specific inscription whose restoration epigraphers have since accepted.", "replication": { "produced_by": [ "A large digitized corpus of inscriptions with known provenance and date", "A neural network trained on artificially damaged text", "Evaluation against held-out inscriptions and with historians in the loop" ], "must_hold": [ "A verified event of a benefit created or restored would require an epigrapher-accepted restoration or re-dating attributable to the model and documented in a non-vendor source" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0366", "title": "Xuanwu Hospital implants China's first closed-loop responsive neurostimulator, Epilcure, with an on-skull AI chip in a man with drug-resistant bilateral temporal lobe epilepsy (9 Mar 2022)", "summary": "9 Mar 2022: Xuanwu Hospital, Beijing, implanted Epilcure, a closed-loop neurostimulator whose on-skull AI chip monitors EEG and stimulates on predicted seizures, in a man with drug-resistant epilepsy.", "date_observed": "2022-03-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 9 March 2022 a team at Xuanwu Hospital, Capital Medical University, Beijing, implanted the Epilcure closed-loop responsive neurostimulation system. Hospital president Zhao Guoguang and neurosurgeon Shan Yongzhi led it. The patient, a man with drug-resistant bilateral temporal lobe epilepsy, was the first enrollee in a hospital-led NMPA registration clinical trial. Sources: cnBeta and Kuai Keji (12 March 2022), both citing the neurosurgery department's WeChat account. The reports describe an AI chip implanted in the skull, with intracranial electrodes monitoring electroencephalography (EEG) rhythms around the clock. On predicting an imminent seizure, it delivers an interfering rhythm to block seizure formation at the focus. Bilateral temporal lobe epilepsy is called a relative contraindication for open surgery. The operation went smoothly and the stimulator's indicators worked normally during surgery. Post-operative reconstruction showed precise electrode placement and clear EEG signals (cnBeta). No seizure outcome, patient age or follow-up is reported; the device's maker is not named.", "category": "benefit created", "unexpected": false, "purpose": "Epilcure was built to detect the onset of seizures from continuously monitored intracranial EEG and deliver stimulation to abort them in people with drug-resistant epilepsy. Implanting it for that purpose was the intended use, though no seizure outcome is yet reported.", "system": "Epilcure closed-loop responsive neurostimulation system (brain-computer interface)", "model_version": null, "developer": null, "deployer": "Xuanwu Hospital, Capital Medical University, Beijing", "location": "Beijing, China", "domain": "Healthcare (epilepsy; responsive neurostimulation)", "segment": "Implanted neuromodulation device in a registration clinical trial", "benefit_type": "Improved Physical Health", "taxonomy_note": "The documented outcome is a successful implantation with the device working, not seizure reduction.", "registry_ids": { "oecd_aim": "2022-03-11-af88" }, "ratings": [ { "group": "personal", "depth": null, "reason": "The reports establish a successful implantation with the stimulator working normally and electrodes precisely placed. No reduction in seizures, follow-up or patient-reported outcome is given, so the benefit to the patient's health is not yet established." } ], "ai_role": { "status": "unassessed", "statement": "The hospital, as relayed by the reports, describes the AI element as an on-skull chip. It monitors intracranial EEG continuously and predicts imminent seizures to trigger interfering stimulation. The read reports establish only that the implant functioned during surgery and that electrodes were placed precisely. No detection or stimulation event, seizure count or follow-up is reported. What the AI contributed to the patient cannot be assessed from these sources." }, "evidence": [ { "kind": "news report", "citation": "cnBeta (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功. cnBeta.COM, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功", "url": "https://www.cnbeta.com.tw/articles/tech/1246089.htm", "date": "2022-03-12", "written_by": "independent", "quote": "术中刺激器各项指标均工作正常，术后重建显示电极位置精准" }, { "kind": "news report", "citation": "Jian J (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑. 快科技 (MyDrivers), 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑", "url": "https://news.mydrivers.com/1/819/819786.htm", "date": "2022-03-12", "written_by": "independent", "quote": "通过将人工智能芯片植入颅骨，颅内电极植入脑内" }, { "kind": "news report", "citation": "Phoenix Technology (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑. 凤凰网科技, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑", "url": "https://tech.ifeng.com/c/8EJq2tqI1TE", "date": "2022-03-12", "written_by": "independent", "quote": "一旦预测到即将发生的癫痫，即启动外源性干扰节律" }, { "kind": "registry label", "citation": "OECD.AI (2022). China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures. OECD AI Incidents and Hazards Monitor, entry 2022-03-11-af88.", "title": "China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures", "url": "https://oecd.ai/en/incidents/2022-03-11-af88", "date": null, "written_by": "independent", "quote": "The AI chip continuously monitors brain activity and intervenes to prevent seizures, marking a significant clinical application of AI in healthcare with direct positive impact on patient health." } ], "replication": { "produced_by": [ "Intracranial electrodes at the epileptic focus feeding continuous EEG to a chip implanted in the skull", "A seizure-prediction routine on the chip that triggers an interfering stimulation rhythm when it predicts an imminent seizure", "Enrollment in the hospital-led NMPA registration trial for patients whose epilepsy is drug-resistant and unsuited to open surgery" ], "must_hold": [ "Electrode placement is precise and signals are clear, as the post-operative reconstruction reported here", "The prediction fires early enough and specifically enough to abort seizures, which no cited source yet documents" ], "echoes": [] }, "paired_incident": null, "headline": "Xuanwu Hospital implants China's first responsive neurostimulator", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-11-af88", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0366", "catalog_version": "1.0.0", "source_fingerprint": "8763a5d15e0002a555a5ed84b4f2f4b3510344b175cf687169aa839ec3157f27", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0366-source-0001", "AIBD-0366-source-0002", "AIBD-0366-source-0003", "AIBD-0366-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Xuanwu Hospital, Capital Medical University, Beijing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "The hospital, as relayed by the reports, describes the AI element as an on-skull chip. It monitors intracranial EEG continuously and predicts imminent seizures to trigger interfering stimulation. The read reports establish only that the implant functioned during surgery and that electrodes were placed precisely. No detection or stimulation event, seizure count or follow-up is reported. What the AI contributed to the patient cannot be assessed from these sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports establish a successful implantation with the stimulator working normally and electrodes precisely placed. No reduction in seizures, follow-up or patient-reported outcome is given, so the benefit to the patient's health is not yet established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports establish a successful implantation with the stimulator working normally and electrodes precisely placed. No reduction in seizures, follow-up or patient-reported outcome is given, so the benefit to the patient's health is not yet established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2022-03-11-af88" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0366" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The documented outcome is a successful implantation with the device working, not seizure reduction." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 9 March 2022 a team at Xuanwu Hospital, Capital Medical University, Beijing, implanted the Epilcure closed-loop responsive neurostimulation system. Hospital president Zhao Guoguang and neurosurgeon Shan Yongzhi led it. The patient, a man with drug-resistant bilateral temporal lobe epilepsy, was the first enrollee in a hospital-led NMPA registration clinical trial. Sources: cnBeta and Kuai Keji (12 March 2022), both citing the neurosurgery department's WeChat account. The reports describe an AI chip implanted in the skull, with intracranial electrodes monitoring electroencephalography (EEG) rhythms around the clock. On predicting an imminent seizure, it delivers an interfering rhythm to block seizure formation at the focus. Bilateral temporal lobe epilepsy is called a relative contraindication for open surgery. The operation went smoothly and the stimulator's indicators worked normally during surgery. Post-operative reconstruction showed precise electrode placement and clear EEG signals (cnBeta). No seizure outcome, patient age or follow-up is reported; the device's maker is not named.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports establish a successful implantation with the stimulator working normally and electrodes precisely placed. No reduction in seizures, follow-up or patient-reported outcome is given, so the benefit to the patient's health is not yet established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Epilcure was built to detect the onset of seizures from continuously monitored intracranial EEG and deliver stimulation to abort them in people with drug-resistant epilepsy. Implanting it for that purpose was the intended use, though no seizure outcome is yet reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Beijing, China", "deployer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Epilcure was built to detect the onset of seizures from continuously monitored intracranial EEG and deliver stimulation to abort them in people with drug-resistant epilepsy. Implanting it for that purpose was the intended use, though no seizure outcome is yet reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-03-09", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-11-af88", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Intracranial electrodes at the epileptic focus feeding continuous EEG to a chip implanted in the skull", "A seizure-prediction routine on the chip that triggers an interfering stimulation rhythm when it predicts an imminent seizure", "Enrollment in the hospital-led NMPA registration trial for patients whose epilepsy is drug-resistant and unsuited to open surgery" ], "must_hold": [ "Electrode placement is precise and signals are clear, as the post-operative reconstruction reported here", "The prediction fires early enough and specifically enough to abort seizures, which no cited source yet documents" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-11-af88", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (epilepsy; responsive neurostimulation)", "segment": "Implanted neuromodulation device in a registration clinical trial" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "cnBeta (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功. cnBeta.COM, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功", "url": "https://www.cnbeta.com.tw/articles/tech/1246089.htm", "date": "2022-03-12", "written_by": "independent", "quote": "术中刺激器各项指标均工作正常，术后重建显示电极位置精准" }, { "kind": "news report", "citation": "Jian J (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑. 快科技 (MyDrivers), 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑", "url": "https://news.mydrivers.com/1/819/819786.htm", "date": "2022-03-12", "written_by": "independent", "quote": "通过将人工智能芯片植入颅骨，颅内电极植入脑内" }, { "kind": "news report", "citation": "Phoenix Technology (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑. 凤凰网科技, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑", "url": "https://tech.ifeng.com/c/8EJq2tqI1TE", "date": "2022-03-12", "written_by": "independent", "quote": "一旦预测到即将发生的癫痫，即启动外源性干扰节律" }, { "kind": "registry label", "citation": "OECD.AI (2022). China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures. OECD AI Incidents and Hazards Monitor, entry 2022-03-11-af88.", "title": "China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures", "url": "https://oecd.ai/en/incidents/2022-03-11-af88", "written_by": "independent", "quote": "The AI chip continuously monitors brain activity and intervenes to prevent seizures, marking a significant clinical application of AI in healthcare with direct positive impact on patient health." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0366-source-0001", "AIBD-0366-source-0002", "AIBD-0366-source-0003", "AIBD-0366-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "cnBeta (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功. cnBeta.COM, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功", "url": "https://www.cnbeta.com.tw/articles/tech/1246089.htm", "date": "2022-03-12", "written_by": "independent", "quote": "术中刺激器各项指标均工作正常，术后重建显示电极位置精准" }, { "kind": "news report", "citation": "Jian J (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑. 快科技 (MyDrivers), 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：人工智能芯片直连大脑", "url": "https://news.mydrivers.com/1/819/819786.htm", "date": "2022-03-12", "written_by": "independent", "quote": "通过将人工智能芯片植入颅骨，颅内电极植入脑内" }, { "kind": "news report", "citation": "Phoenix Technology (2022). 中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑. 凤凰网科技, 12 March 2022.", "title": "中国首例“脑机接口”反应性闭环神经刺激系统植入成功：AI芯片直连大脑", "url": "https://tech.ifeng.com/c/8EJq2tqI1TE", "date": "2022-03-12", "written_by": "independent", "quote": "一旦预测到即将发生的癫痫，即启动外源性干扰节律" }, { "kind": "registry label", "citation": "OECD.AI (2022). China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures. OECD AI Incidents and Hazards Monitor, entry 2022-03-11-af88.", "title": "China's First AI-Powered Brain-Computer Interface Implanted to Prevent Epileptic Seizures", "url": "https://oecd.ai/en/incidents/2022-03-11-af88", "written_by": "independent", "quote": "The AI chip continuously monitors brain activity and intervenes to prevent seizures, marking a significant clinical application of AI in healthcare with direct positive impact on patient health." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "9 Mar 2022: Xuanwu Hospital, Beijing, implanted Epilcure, a closed-loop neurostimulator whose on-skull AI chip monitors EEG and stimulates on predicted seizures, in a man with drug-resistant epilepsy.", "account": "On 9 March 2022 a team at Xuanwu Hospital, Capital Medical University, Beijing, implanted the Epilcure closed-loop responsive neurostimulation system. Hospital president Zhao Guoguang and neurosurgeon Shan Yongzhi led it. The patient, a man with drug-resistant bilateral temporal lobe epilepsy, was the first enrollee in a hospital-led NMPA registration clinical trial. Sources: cnBeta and Kuai Keji (12 March 2022), both citing the neurosurgery department's WeChat account. The reports describe an AI chip implanted in the skull, with intracranial electrodes monitoring electroencephalography (EEG) rhythms around the clock. On predicting an imminent seizure, it delivers an interfering rhythm to block seizure formation at the focus. Bilateral temporal lobe epilepsy is called a relative contraindication for open surgery. The operation went smoothly and the stimulator's indicators worked normally during surgery. Post-operative reconstruction showed precise electrode placement and clear EEG signals (cnBeta). No seizure outcome, patient age or follow-up is reported; the device's maker is not named." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Epilcure closed-loop responsive neurostimulation system (brain-computer interface)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Xuanwu Hospital implants China's first closed-loop responsive neurostimulator, Epilcure, with an on-skull AI chip in a man with drug-resistant bilateral temporal lobe epilepsy (9 Mar 2022)", "headline": "Xuanwu Hospital implants China's first responsive neurostimulator" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8763a5d15e0002a555a5ed84b4f2f4b3510344b175cf687169aa839ec3157f27" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 9 March 2022 a team at Xuanwu Hospital, Capital Medical University, Beijing, implanted the Epilcure closed-loop responsive neurostimulation system. Hospital president Zhao Guoguang and neurosurgeon Shan Yongzhi led it. The patient, a man with drug-resistant bilateral temporal lobe epilepsy, was the first enrollee in a hospital-led NMPA registration clinical trial. Sources: cnBeta and Kuai Keji (12 March 2022), both citing the neurosurgery department's WeChat account. The reports describe an AI chip implanted in the skull, with intracranial electrodes monitoring electroencephalography (EEG) rhythms around the clock. On predicting an imminent seizure, it delivers an interfering rhythm to block seizure formation at the focus. Bilateral temporal lobe epilepsy is called a relative contraindication for open surgery. The operation went smoothly and the stimulator's indicators worked normally during surgery. Post-operative reconstruction showed precise electrode placement and clear EEG signals (cnBeta). No seizure outcome, patient age or follow-up is reported; the device's maker is not named.", "replication": { "produced_by": [ "Intracranial electrodes at the epileptic focus feeding continuous EEG to a chip implanted in the skull", "A seizure-prediction routine on the chip that triggers an interfering stimulation rhythm when it predicts an imminent seizure", "Enrollment in the hospital-led NMPA registration trial for patients whose epilepsy is drug-resistant and unsuited to open surgery" ], "must_hold": [ "Electrode placement is precise and signals are clear, as the post-operative reconstruction reported here", "The prediction fires early enough and specifically enough to abort seizures, which no cited source yet documents" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 25, "reviewed": 0, "record_mapped": 25, "not_assessed": 66, "complete": false, "by_state": { "value_present": 25, "not_reported": 0, "unresolved": 0, "not_assessed": 66, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0112", "title": "ASENA analysis program flags a car at Yüksekova carrying 52.5 kg of explosives bound for Istanbul", "summary": "Police analysis software flagged a car at Yüksekova on 20 March 2022; it held 52.5 kg of explosives officials said were bound for Istanbul.", "date_observed": "2022-03-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 20 March 2022 at about 19:00, officers of the Hakkari Provincial Police Directorate stopped a car at the Yüksekova-Van checkpoint exit in Yüksekova, Turkey. Work on the directorate's ASENA analysis program had flagged it as suspicious, initially as a suspected drug shipment. A search of a hidden compartment under the spare-wheel well found 133 packets, 52.5 kg, of factory-made explosive assessed as PETN-RDX. The driver, A.K., a police officer posted in Istanbul, was remanded on 22 March 2022. Interior Minister Süleyman Soylu said on 21 March that the target was Istanbul. On 20 November 2023 the Hakkari 2nd Heavy Penal Court gave A.K. 21 years for supplying weapons to a terrorist organization. Four co-defendants got 17.5 years each.", "category": "harm prevented", "unexpected": true, "purpose": "ASENA (Analiz Sistemleri Narkotik Ağı) is the Turkish National Police's narcotics analysis software, in service since March 2021. Built to flag and investigate drug crime from integrated police and justice databases. The Hakkari flag was worked as a suspected drug shipment and the search found explosives instead, so this benefit was outside the system's design purpose.", "system": "ASENA (Analiz Sistemleri Narkotik Ağı), Turkish National Police narcotics analysis software", "model_version": null, "developer": "Turkish National Police (Emniyet Genel Müdürlüğü), Narcotics Crimes Department; described as written by Turkish engineers, no contractor named", "deployer": "Hakkari Provincial Police Directorate, Turkish National Police", "location": "Yüksekova, Turkey", "domain": "Public safety and counter-terrorism policing", "segment": "Government, security, and defense", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2022-03-21-22fd" }, "ratings": [ { "group": "societal", "depth": 4, "reason": "52.5 kg of explosive assessed as PETN-RDX was seized before use. The minister said the target was Istanbul and the court convicted five men of supplying weapons to a terrorist organization. So the averted harm was potentially mass-casualty, though the specific plan was not established in the reporting." }, { "group": "organizational", "depth": 2, "reason": "The Hakkari police obtained a lead that produced a seizure, five arrests and five convictions. The minister counted it among 15 similar actions stopped that year." } ], "ai_role": { "status": "assessed", "statement": "The program supplied the lead and nothing more. The minister said the analysis programs, “what they call artificial intelligence”, had identified a suspicious vehicle thought to be carrying drugs. The Hakkari police chief called him on the evening of 20 March. Officers then stopped the car at a fixed checkpoint, searched the concealed compartment and arrested the driver; prosecutors and the court did the rest. No source describes the program's inputs, the data it matched, or whether an analyst reviewed the flag before the stop. The defendant spoke in court of “those who informed”, but no source reports an informant." }, "evidence": [ { "kind": "news report", "citation": "Cumhuriyet (2022). Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı. Cumhuriyet.", "title": "Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı", "url": "https://www.cumhuriyet.com.tr/siyaset/goruntuler-ortaya-cikti-aracinda-52-kilo-patlayici-cikan-polis-tutuklandi-1918432", "date": "2022-03-22", "written_by": "independent", "quote": "20 Mart 2022 günü saat 19.00 sıralarında Yüksekova ilçesi Yüksekova-Van Uygulama Noktası çıkışında bir araç durdurulduğu belirtildi" }, { "kind": "news report", "citation": "Hürriyet (2022). Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du. Hürriyet.", "title": "Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du", "url": "https://www.hurriyet.com.tr/gundem/son-dakika-bakan-soyludan-onemli-aciklamalar-42027018", "date": "2022-03-21", "written_by": "independent", "quote": "Bu yapay zeka dedikleri ve birçok bilgiyi üst üste koyarak oluşturdukları programlar. Buradan şüpheli bir aracı tespit ettiklerini söylediler. Uyuşturucu sevkiyatı olduğunu söylediler." }, { "kind": "news report", "citation": "Son Dakika (2022). Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du. Sondakika.com.", "title": "Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du", "url": "https://www.sondakika.com/haber/haber-polis-memurunun-52-kilo-patlayiciyla-yakalanmasi-14811802", "date": "2022-03-21", "written_by": "independent", "quote": "Hakkari İl Emniyet Müdürlüğünce Asena analiz programı üzerinden yapılan çalışmalar neticesinde, bir polis memurunun sürücülüğünü yaptığı araçta 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirilmişti." }, { "kind": "news report", "citation": "NTV (2022). Polis memuru 52,5 kilo patlayıcıyla yakalandı. NTV Haber.", "title": "Polis memuru 52,5 kilo patlayıcıyla yakalandı", "url": "https://www.ntv.com.tr/turkiye/polis-memuru-52-5-kilo-patlayiciyla-yakalandi,FnN59Nq0G0GEzin9tpURRQ", "date": "2022-03-21", "written_by": "independent", "quote": "stepne havuzunun alt kısmına yapılmış zula içerisine gizlenmiş vaziyette 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirildi" }, { "kind": "news report", "citation": "Duvar English (2022). Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari. Duvar English.", "title": "Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari", "url": "https://www.duvarenglish.com/opposition-mp-ahmet-sik-inquires-about-police-officer-caught-with-52kg-of-explosives-in-hakkari-news-60703", "date": "2022-03-23", "written_by": "independent", "quote": "The police found 133 pieces of 52 kilograms and 500 grams of explosives in the spare wheel carrier of the car." }, { "kind": "news report", "citation": "Anadolu Ajansı, Bulur, S. (2022). Yapay zeka ASENA uyuşturucunun izini sürüyor. Anadolu Ajansı.", "title": "Yapay zeka ASENA uyuşturucunun izini sürüyor", "url": "https://www.aa.com.tr/tr/gundem/yapay-zeka-asena-uyusturucunun-izini-suruyor/2603769", "date": "2022-06-02", "written_by": "independent", "quote": "e-Devlet ve UYAP ile İçişleri ve Adalet bakanlıklarının veri tabanlarıyla entegre çalışabilen yapay zeka formatında bir yazılım olan ASENA, yaklaşık 14 ay önce faaliyete geçirildi" }, { "kind": "news report", "citation": "Demirören Haber Ajansı, Özkan, M. (2023). 52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun. DHA.", "title": "52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun", "url": "https://www.dha.com.tr/yerel-haberler/hakkari/52-kilo-patlayiciyla-yakalanan-polis-memuru-ih-2208374", "date": "2023-02-17", "written_by": "independent", "quote": "Hakkari'de İl Emniyet Müdürlüğü'nce Asena analiz programı üzerinden yapılan çalışmalar ile İstanbul'da görev yapan polis memurunun kullandığı otomobil, 20 Mart'ta Yüksekova çıkışındaki polis kontrol noktasında durduruldu." }, { "kind": "news report", "citation": "Kısa Dalga, from DHA (2023). Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası. Kısa Dalga.", "title": "Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası", "url": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "date": "2023-11-20", "written_by": "independent", "quote": "Savunmaları dinleyen mahkeme heyeti, \"terör örgütüne silah sağlamak\" suçundan polis memuru A.K. için 21 yıl, diğer 4 sanık için de 17 yıl 6'şar ay hapis cezası verdi." } ], "replication": { "produced_by": [ "A police analysis program integrated with national identity, justice and interior databases that ranks vehicles or persons for interdiction", "A fixed checkpoint on the Yüksekova-Van road at which a flagged car could be stopped and searched the same evening", "Officers prepared to search a concealed compartment on a narcotics lead rather than a terrorism lead" ], "must_hold": [ "The flag must be followed by a lawful stop and physical search; the software only prioritizes", "Seized material must be forensically assessed and the case prosecuted, as here with a 2023 conviction, for the counterfactual to stand", "Analytic leads must be checked before a stop; the sources do not report the program's false-positive rate" ], "echoes": [] }, "paired_incident": null, "headline": "ASENA flags a car at Yüksekova carrying 52.5 kg of explosives", "metric": "133 packets, 52.5 kg, of factory-made explosive", "comparator": null, "later": { "status": "litigated", "date": "2023-11-20", "note": "On 20 November 2023 the Hakkari 2nd Heavy Penal Court sentenced the police officer A.K. to 21 years in prison and the four co-defendants to 17 years 6 months each.", "quote": "Sanık polis A.K. 21 yıl, diğer 4 sanık ise 17 yıl 6'şar ay hapis cezasına çarptırıldı.", "url": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842" }, "value": null, "developer_country": "Turkey", "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-21-22fd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey); https://en.wikipedia.org/wiki/Hakk%C3%A2ri_Province", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: eight independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0112", "catalog_version": "1.0.0", "source_fingerprint": "00409ff3142ba7d3d534b52a19f5ab154a50c3cad385e94162da4361e0c4870a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0112-source-0001", "AIBD-0112-source-0002", "AIBD-0112-source-0003", "AIBD-0112-source-0004", "AIBD-0112-source-0005", "AIBD-0112-source-0006", "AIBD-0112-source-0007", "AIBD-0112-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Turkish National Police (Emniyet Genel Müdürlüğü), Narcotics Crimes Department; described as written by Turkish engineers, no contractor named", "deployer": "Hakkari Provincial Police Directorate, Turkish National Police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The program supplied the lead and nothing more. The minister said the analysis programs, “what they call artificial intelligence”, had identified a suspicious vehicle thought to be carrying drugs. The Hakkari police chief called him on the evening of 20 March. Officers then stopped the car at a fixed checkpoint, searched the concealed compartment and arrested the driver; prosecutors and the court did the rest. No source describes the program's inputs, the data it matched, or whether an analyst reviewed the flag before the stop. The defendant spoke in court of “those who informed”, but no source reports an informant." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The program supplied the lead and nothing more. The minister said the analysis programs, “what they call artificial intelligence”, had identified a suspicious vehicle thought to be carrying drugs. The Hakkari police chief called him on the evening of 20 March. Officers then stopped the car at a fixed checkpoint, searched the concealed compartment and arrested the driver; prosecutors and the court did the rest. No source describes the program's inputs, the data it matched, or whether an analyst reviewed the flag before the stop. The defendant spoke in court of “those who informed”, but no source reports an informant." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "52.5 kg of explosive assessed as PETN-RDX was seized before use. The minister said the target was Istanbul and the court convicted five men of supplying weapons to a terrorist organization. So the averted harm was potentially mass-casualty, though the specific plan was not established in the reporting." }, { "group": "organizational", "depth": 2, "reason": "The Hakkari police obtained a lead that produced a seizure, five arrests and five convictions. The minister counted it among 15 similar actions stopped that year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: eight independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "52.5 kg of explosive assessed as PETN-RDX was seized before use. The minister said the target was Istanbul and the court convicted five men of supplying weapons to a terrorist organization. So the averted harm was potentially mass-casualty, though the specific plan was not established in the reporting." }, { "group": "organizational", "depth": 2, "reason": "The Hakkari police obtained a lead that produced a seizure, five arrests and five convictions. The minister counted it among 15 similar actions stopped that year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "52.5 kg of explosive assessed as PETN-RDX was seized before use. The minister said the target was Istanbul and the court convicted five men of supplying weapons to a terrorist organization. So the averted harm was potentially mass-casualty, though the specific plan was not established in the reporting." }, { "group": "organizational", "depth": 2, "reason": "The Hakkari police obtained a lead that produced a seizure, five arrests and five convictions. The minister counted it among 15 similar actions stopped that year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "133 packets, 52.5 kg, of factory-made explosive", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2022-03-21-22fd" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "litigated", "date": "2023-11-20", "note": "On 20 November 2023 the Hakkari 2nd Heavy Penal Court sentenced the police officer A.K. to 21 years in prison and the four co-defendants to 17 years 6 months each.", "quote": "Sanık polis A.K. 21 yıl, diğer 4 sanık ise 17 yıl 6'şar ay hapis cezasına çarptırıldı.", "url": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0112" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 20 March 2022 at about 19:00, officers of the Hakkari Provincial Police Directorate stopped a car at the Yüksekova-Van checkpoint exit in Yüksekova, Turkey. Work on the directorate's ASENA analysis program had flagged it as suspicious, initially as a suspected drug shipment. A search of a hidden compartment under the spare-wheel well found 133 packets, 52.5 kg, of factory-made explosive assessed as PETN-RDX. The driver, A.K., a police officer posted in Istanbul, was remanded on 22 March 2022. Interior Minister Süleyman Soylu said on 21 March that the target was Istanbul. On 20 November 2023 the Hakkari 2nd Heavy Penal Court gave A.K. 21 years for supplying weapons to a terrorist organization. Four co-defendants got 17.5 years each.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "52.5 kg of explosive assessed as PETN-RDX was seized before use. The minister said the target was Istanbul and the court convicted five men of supplying weapons to a terrorist organization. So the averted harm was potentially mass-casualty, though the specific plan was not established in the reporting." }, { "group": "organizational", "depth": 2, "reason": "The Hakkari police obtained a lead that produced a seizure, five arrests and five convictions. The minister counted it among 15 similar actions stopped that year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "ASENA (Analiz Sistemleri Narkotik Ağı) is the Turkish National Police's narcotics analysis software, in service since March 2021. Built to flag and investigate drug crime from integrated police and justice databases. The Hakkari flag was worked as a suspected drug shipment and the search found explosives instead, so this benefit was outside the system's design purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Yüksekova, Turkey", "developer_country": "Turkey", "deployer_country": "Turkey" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ASENA (Analiz Sistemleri Narkotik Ağı) is the Turkish National Police's narcotics analysis software, in service since March 2021. Built to flag and investigate drug crime from integrated police and justice databases. The Hakkari flag was worked as a suspected drug shipment and the search found explosives instead, so this benefit was outside the system's design purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-03-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-21-22fd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey); https://en.wikipedia.org/wiki/Hakk%C3%A2ri_Province", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A police analysis program integrated with national identity, justice and interior databases that ranks vehicles or persons for interdiction", "A fixed checkpoint on the Yüksekova-Van road at which a flagged car could be stopped and searched the same evening", "Officers prepared to search a concealed compartment on a narcotics lead rather than a terrorism lead" ], "must_hold": [ "The flag must be followed by a lawful stop and physical search; the software only prioritizes", "Seized material must be forensically assessed and the case prosecuted, as here with a 2023 conviction, for the counterfactual to stand", "Analytic leads must be checked before a stop; the sources do not report the program's false-positive rate" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-03-21-22fd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey); https://en.wikipedia.org/wiki/Hakk%C3%A2ri_Province", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public safety and counter-terrorism policing", "segment": "Government, security, and defense" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Cumhuriyet (2022). Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı. Cumhuriyet.", "title": "Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı", "url": "https://www.cumhuriyet.com.tr/siyaset/goruntuler-ortaya-cikti-aracinda-52-kilo-patlayici-cikan-polis-tutuklandi-1918432", "date": "2022-03-22", "written_by": "independent", "quote": "20 Mart 2022 günü saat 19.00 sıralarında Yüksekova ilçesi Yüksekova-Van Uygulama Noktası çıkışında bir araç durdurulduğu belirtildi" }, { "kind": "news report", "citation": "Hürriyet (2022). Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du. Hürriyet.", "title": "Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du", "url": "https://www.hurriyet.com.tr/gundem/son-dakika-bakan-soyludan-onemli-aciklamalar-42027018", "date": "2022-03-21", "written_by": "independent", "quote": "Bu yapay zeka dedikleri ve birçok bilgiyi üst üste koyarak oluşturdukları programlar. Buradan şüpheli bir aracı tespit ettiklerini söylediler. Uyuşturucu sevkiyatı olduğunu söylediler." }, { "kind": "news report", "citation": "Son Dakika (2022). Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du. Sondakika.com.", "title": "Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du", "url": "https://www.sondakika.com/haber/haber-polis-memurunun-52-kilo-patlayiciyla-yakalanmasi-14811802", "date": "2022-03-21", "written_by": "independent", "quote": "Hakkari İl Emniyet Müdürlüğünce Asena analiz programı üzerinden yapılan çalışmalar neticesinde, bir polis memurunun sürücülüğünü yaptığı araçta 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirilmişti." }, { "kind": "news report", "citation": "NTV (2022). Polis memuru 52,5 kilo patlayıcıyla yakalandı. NTV Haber.", "title": "Polis memuru 52,5 kilo patlayıcıyla yakalandı", "url": "https://www.ntv.com.tr/turkiye/polis-memuru-52-5-kilo-patlayiciyla-yakalandi,FnN59Nq0G0GEzin9tpURRQ", "date": "2022-03-21", "written_by": "independent", "quote": "stepne havuzunun alt kısmına yapılmış zula içerisine gizlenmiş vaziyette 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirildi" }, { "kind": "news report", "citation": "Duvar English (2022). Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari. Duvar English.", "title": "Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari", "url": "https://www.duvarenglish.com/opposition-mp-ahmet-sik-inquires-about-police-officer-caught-with-52kg-of-explosives-in-hakkari-news-60703", "date": "2022-03-23", "written_by": "independent", "quote": "The police found 133 pieces of 52 kilograms and 500 grams of explosives in the spare wheel carrier of the car." }, { "kind": "news report", "citation": "Anadolu Ajansı, Bulur, S. (2022). Yapay zeka ASENA uyuşturucunun izini sürüyor. Anadolu Ajansı.", "title": "Yapay zeka ASENA uyuşturucunun izini sürüyor", "url": "https://www.aa.com.tr/tr/gundem/yapay-zeka-asena-uyusturucunun-izini-suruyor/2603769", "date": "2022-06-02", "written_by": "independent", "quote": "e-Devlet ve UYAP ile İçişleri ve Adalet bakanlıklarının veri tabanlarıyla entegre çalışabilen yapay zeka formatında bir yazılım olan ASENA, yaklaşık 14 ay önce faaliyete geçirildi" }, { "kind": "news report", "citation": "Demirören Haber Ajansı, Özkan, M. (2023). 52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun. DHA.", "title": "52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun", "url": "https://www.dha.com.tr/yerel-haberler/hakkari/52-kilo-patlayiciyla-yakalanan-polis-memuru-ih-2208374", "date": "2023-02-17", "written_by": "independent", "quote": "Hakkari'de İl Emniyet Müdürlüğü'nce Asena analiz programı üzerinden yapılan çalışmalar ile İstanbul'da görev yapan polis memurunun kullandığı otomobil, 20 Mart'ta Yüksekova çıkışındaki polis kontrol noktasında durduruldu." }, { "kind": "news report", "citation": "Kısa Dalga, from DHA (2023). Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası. Kısa Dalga.", "title": "Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası", "url": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "date": "2023-11-20", "written_by": "independent", "quote": "Savunmaları dinleyen mahkeme heyeti, \"terör örgütüne silah sağlamak\" suçundan polis memuru A.K. için 21 yıl, diğer 4 sanık için de 17 yıl 6'şar ay hapis cezası verdi." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0112-source-0001", "AIBD-0112-source-0002", "AIBD-0112-source-0003", "AIBD-0112-source-0004", "AIBD-0112-source-0005", "AIBD-0112-source-0006", "AIBD-0112-source-0007", "AIBD-0112-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Cumhuriyet (2022). Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı. Cumhuriyet.", "title": "Görüntüler ortaya çıktı: Aracında 52 kilo patlayıcı çıkan polis tutuklandı, Valilik açıklama yaptı", "url": "https://www.cumhuriyet.com.tr/siyaset/goruntuler-ortaya-cikti-aracinda-52-kilo-patlayici-cikan-polis-tutuklandi-1918432", "date": "2022-03-22", "written_by": "independent", "quote": "20 Mart 2022 günü saat 19.00 sıralarında Yüksekova ilçesi Yüksekova-Van Uygulama Noktası çıkışında bir araç durdurulduğu belirtildi" }, { "kind": "news report", "citation": "Hürriyet (2022). Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du. Hürriyet.", "title": "Bakan Soylu'dan polis aracında bulunan patlayıcıyla ilgili flaş açıklama: Hedef İstanbul'du", "url": "https://www.hurriyet.com.tr/gundem/son-dakika-bakan-soyludan-onemli-aciklamalar-42027018", "date": "2022-03-21", "written_by": "independent", "quote": "Bu yapay zeka dedikleri ve birçok bilgiyi üst üste koyarak oluşturdukları programlar. Buradan şüpheli bir aracı tespit ettiklerini söylediler. Uyuşturucu sevkiyatı olduğunu söylediler." }, { "kind": "news report", "citation": "Son Dakika (2022). Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du. Sondakika.com.", "title": "Polis memurunun 52 kilo patlayıcıyla yakalanması hakkında konuşan Bakan Soylu: Hedef İstanbul'du", "url": "https://www.sondakika.com/haber/haber-polis-memurunun-52-kilo-patlayiciyla-yakalanmasi-14811802", "date": "2022-03-21", "written_by": "independent", "quote": "Hakkari İl Emniyet Müdürlüğünce Asena analiz programı üzerinden yapılan çalışmalar neticesinde, bir polis memurunun sürücülüğünü yaptığı araçta 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirilmişti." }, { "kind": "news report", "citation": "NTV (2022). Polis memuru 52,5 kilo patlayıcıyla yakalandı. NTV Haber.", "title": "Polis memuru 52,5 kilo patlayıcıyla yakalandı", "url": "https://www.ntv.com.tr/turkiye/polis-memuru-52-5-kilo-patlayiciyla-yakalandi,FnN59Nq0G0GEzin9tpURRQ", "date": "2022-03-21", "written_by": "independent", "quote": "stepne havuzunun alt kısmına yapılmış zula içerisine gizlenmiş vaziyette 133 parça halinde 52 kilo 500 gram patlayıcı madde ele geçirildi" }, { "kind": "news report", "citation": "Duvar English (2022). Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari. Duvar English.", "title": "Opposition MP Ahmet Şık inquires about police officer caught with 52kg of explosives in Hakkari", "url": "https://www.duvarenglish.com/opposition-mp-ahmet-sik-inquires-about-police-officer-caught-with-52kg-of-explosives-in-hakkari-news-60703", "date": "2022-03-23", "written_by": "independent", "quote": "The police found 133 pieces of 52 kilograms and 500 grams of explosives in the spare wheel carrier of the car." }, { "kind": "news report", "citation": "Anadolu Ajansı, Bulur, S. (2022). Yapay zeka ASENA uyuşturucunun izini sürüyor. Anadolu Ajansı.", "title": "Yapay zeka ASENA uyuşturucunun izini sürüyor", "url": "https://www.aa.com.tr/tr/gundem/yapay-zeka-asena-uyusturucunun-izini-suruyor/2603769", "date": "2022-06-02", "written_by": "independent", "quote": "e-Devlet ve UYAP ile İçişleri ve Adalet bakanlıklarının veri tabanlarıyla entegre çalışabilen yapay zeka formatında bir yazılım olan ASENA, yaklaşık 14 ay önce faaliyete geçirildi" }, { "kind": "news report", "citation": "Demirören Haber Ajansı, Özkan, M. (2023). 52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun. DHA.", "title": "52 kilo patlayıcıyla yakalanan polis memuru: İhbar edenlerden Allah razı olsun", "url": "https://www.dha.com.tr/yerel-haberler/hakkari/52-kilo-patlayiciyla-yakalanan-polis-memuru-ih-2208374", "date": "2023-02-17", "written_by": "independent", "quote": "Hakkari'de İl Emniyet Müdürlüğü'nce Asena analiz programı üzerinden yapılan çalışmalar ile İstanbul'da görev yapan polis memurunun kullandığı otomobil, 20 Mart'ta Yüksekova çıkışındaki polis kontrol noktasında durduruldu." }, { "kind": "news report", "citation": "Kısa Dalga, from DHA (2023). Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası. Kısa Dalga.", "title": "Aracında 52 kilo patlayıcı bulunan polise 21 yıl hapis cezası", "url": "https://kisadalga.net/haber/detay/aracinda-52-kilo-patlayici-bulunan-polise-21-yil-hapis-cezasi_86842", "date": "2023-11-20", "written_by": "independent", "quote": "Savunmaları dinleyen mahkeme heyeti, \"terör örgütüne silah sağlamak\" suçundan polis memuru A.K. için 21 yıl, diğer 4 sanık için de 17 yıl 6'şar ay hapis cezası verdi." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Police analysis software flagged a car at Yüksekova on 20 March 2022; it held 52.5 kg of explosives officials said were bound for Istanbul.", "account": "On 20 March 2022 at about 19:00, officers of the Hakkari Provincial Police Directorate stopped a car at the Yüksekova-Van checkpoint exit in Yüksekova, Turkey. Work on the directorate's ASENA analysis program had flagged it as suspicious, initially as a suspected drug shipment. A search of a hidden compartment under the spare-wheel well found 133 packets, 52.5 kg, of factory-made explosive assessed as PETN-RDX. The driver, A.K., a police officer posted in Istanbul, was remanded on 22 March 2022. Interior Minister Süleyman Soylu said on 21 March that the target was Istanbul. On 20 November 2023 the Hakkari 2nd Heavy Penal Court gave A.K. 21 years for supplying weapons to a terrorist organization. Four co-defendants got 17.5 years each." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ASENA (Analiz Sistemleri Narkotik Ağı), Turkish National Police narcotics analysis software" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Turkish National Police (Emniyet Genel Müdürlüğü), Narcotics Crimes Department; described as written by Turkish engineers, no contractor named" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ASENA analysis program flags a car at Yüksekova carrying 52.5 kg of explosives bound for Istanbul", "headline": "ASENA flags a car at Yüksekova carrying 52.5 kg of explosives" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "00409ff3142ba7d3d534b52a19f5ab154a50c3cad385e94162da4361e0c4870a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 20 March 2022 at about 19:00, officers of the Hakkari Provincial Police Directorate stopped a car at the Yüksekova-Van checkpoint exit in Yüksekova, Turkey. Work on the directorate's ASENA analysis program had flagged it as suspicious, initially as a suspected drug shipment. A search of a hidden compartment under the spare-wheel well found 133 packets, 52.5 kg, of factory-made explosive assessed as PETN-RDX. The driver, A.K., a police officer posted in Istanbul, was remanded on 22 March 2022. Interior Minister Süleyman Soylu said on 21 March that the target was Istanbul. On 20 November 2023 the Hakkari 2nd Heavy Penal Court gave A.K. 21 years for supplying weapons to a terrorist organization. Four co-defendants got 17.5 years each.", "replication": { "produced_by": [ "A police analysis program integrated with national identity, justice and interior databases that ranks vehicles or persons for interdiction", "A fixed checkpoint on the Yüksekova-Van road at which a flagged car could be stopped and searched the same evening", "Officers prepared to search a concealed compartment on a narcotics lead rather than a terrorism lead" ], "must_hold": [ "The flag must be followed by a lawful stop and physical search; the software only prioritizes", "Seized material must be forensically assessed and the case prosecuted, as here with a 2023 conviction, for the counterfactual to stand", "Analytic leads must be checked before a stop; the sources do not report the program's false-positive rate" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0317", "title": "Vyntra's (formerly NetGuardians) AI risk models may have blocked fraudulent payments at unnamed banks, including a USD 500,000 ATM scheme", "summary": "Vendor “Fraud Cases” page lists blocked payments from CHF 19,990 to USD 850,000 and a USD 500,000 (KSh 58 million) ATM fraud ending in arrests; customers, banks and dates are not given.", "date_observed": "2022-04-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Vyntra's “Fraud Cases” page was published 4 April 2022 per its page metadata; the cases themselves are undated. It states that “Our solutions stop the fraud before the money leaves the bank” and lists about two dozen short case studies at unnamed banks. One is an account takeover after pharming stopped before a CHF 19,990 payment. Another is an impersonation that led a bank employee to validate a CHF 1,000,000 transaction, blocked because the beneficiary was unusual at bank level. There are vishing, tech-support, CEO-fraud, business-email-compromise, romance and invoice-redirection cases. Their payments of EUR 22,114, EUR 33,170, USD 7,500, GBP 21,000, EUR 125,000, EUR 170,000, USD 100,000, USD 170,000 and USD 850,000 were stopped. Transaction or e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language) did not match the customer's or bank's usual profile. There are two internal-fraud cases. In one case “fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs”. The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. The page is the vendor's own account.", "category": "harm prevented", "unexpected": false, "purpose": "The risk models are built to score payments and e-banking sessions against customer and bank profiles in real time and block fraudulent transfers. Each case is that intended use.", "system": "Vyntra (NetGuardians) AI risk models for real-time payment and e-banking fraud detection", "model_version": null, "developer": "Vyntra (NetGuardians SA, merged with Intix in June 2025)", "deployer": "Unnamed client banks", "location": "Not stated; amounts are given in Swiss francs, euros, pounds, US dollars and Kenyan shillings", "domain": "Banking fraud prevention", "segment": "Retail and corporate payment fraud at client banks", "benefit_type": "Reduced Risk", "taxonomy_note": "The blocked payments and the ATM fraud are described only on the vendor's page, with no named bank, customer or date.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "The vendor describes customers whose social-engineering transfers of EUR 125,000 and USD 170,000 were blocked, a loss averted for each. No customer is named or independently documented." }, { "group": "organizational", "depth": 4, "reason": "The vendor states that a USD 500,000 (KSh 58 million) ATM fraud was stopped with arrests. It says payments up to USD 850,000 were blocked before funds left client banks. Serious losses averted if the account holds. Customers, banks and dates are not given." }, { "group": "societal", "depth": null, "reason": "No aggregate verified by a regulator is given." } ], "ai_role": { "status": "unassessed", "statement": "The evidence is limited to the maker's account. Vyntra's page attributes each block to its AI risk models detecting variables outside the customer's or bank's usual profile. No customer, bank, date or official record is available to assess whether the models, rather than staff or other controls, produced the outcome. The AI's contribution is not established." }, "evidence": [ { "kind": "press release", "citation": "Vyntra (2022). Fraud Cases. vyntra.com (vendor case-study page; page metadata gives 4 April 2022; cases undated).", "title": "Fraud Cases - Vyntra", "url": "https://www.vyntra.com/fraud-cases/", "date": "2022-04-04", "written_by": "makers", "quote": "Vyntra's AI risk models prevented the fraud due to the unusual timing and frequency of ATM withdrawals." }, { "kind": "press release", "citation": "Vyntra (2022). Fraud Cases, same page, ATM case.", "title": "Fraud Cases - Vyntra", "url": "https://www.vyntra.com/fraud-cases/", "date": "2022-04-04", "written_by": "makers", "quote": "fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs." }, { "kind": "news report", "citation": "FinTech Global (2025). Vyntra launched by NetGuardians and Intix to boost banking intelligence. 19 June 2025.", "title": "Vyntra launched by NetGuardians and Intix to boost banking intelligence", "url": "https://fintech.global/2025/06/19/vyntra-launched-by-netguardians-and-intix-to-boost-banking-intelligence/", "date": "2025-06-19", "written_by": "independent", "quote": "NetGuardians brings its advanced artificial intelligence tools to detect and prevent financial crime, while Intix contributes its expertise in transaction data analysis and visibility." } ], "replication": { "produced_by": [ "Behavioral profiles of each customer's and the bank's usual transaction and e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language)", "Real-time scoring before a payment is released" ], "must_hold": [ "The fraudulent transaction departs from the profile on several variables; the vendor notes cases with little customer history relied on bank-level anomalies", "The bank acts on the alert before the money leaves" ], "echoes": [] }, "paired_incident": null, "headline": "Vyntra's AI risk models may have stopped a USD 500,000 ATM fraud", "metric": "fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million)", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No dated follow-up to any of the cases was found; the June 2025 merger of NetGuardians and Intix into Vyntra concerns the vendor, not the cases.", "quote": null, "url": null }, "value": { "amount": "USD 500,000 (KSh 58 million)", "what": "fraudulent ATM withdrawal detected and stopped, with arrests", "who": "the second bank, an unnamed client bank (the page labels the case 'Kenya')", "estimate": false, "quote": "The fraud was detected in real time and the fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank’s ATMs. Vyntra's AI risk models prevented the fraud due to the unusual timing and frequency of ATM withdrawals.", "url": "https://www.vyntra.com/fraud-cases/" }, "developer_country": "Switzerland", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 3 for personal and 4 for organizational on the documented outcome, with the reason stated on each rating.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://www.vyntra.com/fraud-cases/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.vyntra.com/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0317", "catalog_version": "1.0.0", "source_fingerprint": "0242cb63702bd620f893f6be7eb51974757fa5552e2abf436018f8573cdcbf56", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0317-source-0001", "AIBD-0317-source-0002", "AIBD-0317-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0317-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Vyntra (NetGuardians SA, merged with Intix in June 2025)", "deployer": "Unnamed client banks" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "unassessed", "statement": "The evidence is limited to the maker's account. Vyntra's page attributes each block to its AI risk models detecting variables outside the customer's or bank's usual profile. No customer, bank, date or official record is available to assess whether the models, rather than staff or other controls, produced the outcome. The AI's contribution is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The vendor describes customers whose social-engineering transfers of EUR 125,000 and USD 170,000 were blocked, a loss averted for each. No customer is named or independently documented." }, { "group": "organizational", "depth": 4, "reason": "The vendor states that a USD 500,000 (KSh 58 million) ATM fraud was stopped with arrests. It says payments up to USD 850,000 were blocked before funds left client banks. Serious losses averted if the account holds. Customers, banks and dates are not given." }, { "group": "societal", "reason": "No aggregate verified by a regulator is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The vendor describes customers whose social-engineering transfers of EUR 125,000 and USD 170,000 were blocked, a loss averted for each. No customer is named or independently documented." }, { "group": "organizational", "depth": 4, "reason": "The vendor states that a USD 500,000 (KSh 58 million) ATM fraud was stopped with arrests. It says payments up to USD 850,000 were blocked before funds left client banks. Serious losses averted if the account holds. Customers, banks and dates are not given." }, { "group": "societal", "reason": "No aggregate verified by a regulator is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The vendor describes customers whose social-engineering transfers of EUR 125,000 and USD 170,000 were blocked, a loss averted for each. No customer is named or independently documented." }, { "group": "organizational", "depth": 4, "reason": "The vendor states that a USD 500,000 (KSh 58 million) ATM fraud was stopped with arrests. It says payments up to USD 850,000 were blocked before funds left client banks. Serious losses averted if the account holds. Customers, banks and dates are not given." }, { "group": "societal", "reason": "No aggregate verified by a regulator is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "USD 500,000 (KSh 58 million)", "what": "fraudulent ATM withdrawal detected and stopped, with arrests", "who": "the second bank, an unnamed client bank (the page labels the case 'Kenya')", "estimate": false, "quote": "The fraud was detected in real time and the fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank’s ATMs. Vyntra's AI risk models prevented the fraud due to the unusual timing and frequency of ATM withdrawals.", "url": "https://www.vyntra.com/fraud-cases/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. 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Vyntra launched by NetGuardians and Intix to boost banking intelligence. 19 June 2025.", "title": "Vyntra launched by NetGuardians and Intix to boost banking intelligence", "url": "https://fintech.global/2025/06/19/vyntra-launched-by-netguardians-and-intix-to-boost-banking-intelligence/", "date": "2025-06-19", "written_by": "independent", "quote": "NetGuardians brings its advanced artificial intelligence tools to detect and prevent financial crime, while Intix contributes its expertise in transaction data analysis and visibility." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Vendor “Fraud Cases” page lists blocked payments from CHF 19,990 to USD 850,000 and a USD 500,000 (KSh 58 million) ATM fraud ending in arrests; customers, banks and dates are not given.", "account": "Vyntra's “Fraud Cases” page was published 4 April 2022 per its page metadata; the cases themselves are undated. It states that “Our solutions stop the fraud before the money leaves the bank” and lists about two dozen short case studies at unnamed banks. One is an account takeover after pharming stopped before a CHF 19,990 payment. Another is an impersonation that led a bank employee to validate a CHF 1,000,000 transaction, blocked because the beneficiary was unusual at bank level. There are vishing, tech-support, CEO-fraud, business-email-compromise, romance and invoice-redirection cases. Their payments of EUR 22,114, EUR 33,170, USD 7,500, GBP 21,000, EUR 125,000, EUR 170,000, USD 100,000, USD 170,000 and USD 850,000 were stopped. Transaction or e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language) did not match the customer's or bank's usual profile. There are two internal-fraud cases. In one case “fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs”. The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. The page is the vendor's own account." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Vyntra (NetGuardians) AI risk models for real-time payment and e-banking fraud detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Vyntra (NetGuardians SA, merged with Intix in June 2025)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Vyntra's (formerly NetGuardians) AI risk models may have blocked fraudulent payments at unnamed banks, including a USD 500,000 ATM scheme", "headline": "Vyntra's AI risk models may have stopped a USD 500,000 ATM fraud" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0242cb63702bd620f893f6be7eb51974757fa5552e2abf436018f8573cdcbf56" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Vyntra's “Fraud Cases” page was published 4 April 2022 per its page metadata; the cases themselves are undated. It states that “Our solutions stop the fraud before the money leaves the bank” and lists about two dozen short case studies at unnamed banks. One is an account takeover after pharming stopped before a CHF 19,990 payment. Another is an impersonation that led a bank employee to validate a CHF 1,000,000 transaction, blocked because the beneficiary was unusual at bank level. There are vishing, tech-support, CEO-fraud, business-email-compromise, romance and invoice-redirection cases. Their payments of EUR 22,114, EUR 33,170, USD 7,500, GBP 21,000, EUR 125,000, EUR 170,000, USD 100,000, USD 170,000 and USD 850,000 were stopped. Transaction or e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language) did not match the customer's or bank's usual profile. There are two internal-fraud cases. In one case “fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs”. The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. The page is the vendor's own account.", "replication": { "produced_by": [ "Behavioral profiles of each customer's and the bank's usual transaction and e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language)", "Real-time scoring before a payment is released" ], "must_hold": [ "The fraudulent transaction departs from the profile on several variables; the vendor notes cases with little customer history relied on bank-level anomalies", "The bank acts on the alert before the money leaves" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0352", "title": "EasyScan GO machine-learning malaria microscopy reaches 91.1% sensitivity and 75.6% specificity against expert microscopy at 11 sites; accuracy study only, manufacturer-funded", "summary": "Das et al. 2022: 2,250 blood films at 11 sites in 11 countries (2018–2019); EasyScan GO sensitivity 91.1%, specificity 75.6% vs expert microscopy; no patient outcome; Global Good funded.", "date_observed": "2022-04-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A multi-center observational study was published in Malaria Journal on 12 April 2022 (Das et al.). The fieldwork is dated only to 2018 and 2019. It evaluated the EasyScan GO, a digital microscopy device whose convolutional-neural-network software was developed by Intellectual Ventures' Global Good Fund. Motic built its production prototype. The 11 sites were in 11 countries: Burkina Faso, Kenya, Republic of the Congo, Senegal, South Africa, Uganda, Bangladesh, Cambodia, Nepal, Thailand and Brazil. In total 2,250 Giemsa-stained blood films were read independently by expert microscopists and by the device. Diagnostic sensitivity was 91.1% (95% CI 88.9–92.7) and specificity 75.6% (73.1–78.0); with good-quality slides specificity rose to 85.1%. Species were identified accurately in 93% of P. falciparum and 92% of P. vivax samples. Parasite density estimates were within 25% of the reference in 23% of slides. The authors conclude the device meets WHO-TDR level 2 criteria for detection and species identification and level 4 for quantification and false-positive rate. They say all parameters were significantly affected by slide quality, and the study did not evaluate performance under routine field operation. The study was funded by the Global Good Fund, which donated the devices; six co-authors were its employees. No patient-management outcome was measured.", "category": "general benefit", "unexpected": false, "purpose": "Automated detection, species identification and quantification of malaria parasites in blood films to replace or support expert microscopy. The evaluated benefit (diagnostic accuracy) is that purpose.", "system": "EasyScan GO digital malaria microscopy device with convolutional-neural-network image analysis of thick blood films", "model_version": "version1.15.17b", "developer": "Intellectual Ventures' Global Good Fund (software and original hardware); Motic (production prototype device, software licensed to Motic)", "deployer": "Research sites in 11 countries under a multi-center study with University of Oxford / Mahidol-Oxford Tropical Medicine Research Unit-affiliated investigators (research use, not routine service)", "location": "11 sites in Burkina Faso, Kenya, Republic of the Congo, Senegal, South Africa, Uganda, Bangladesh, Cambodia, Nepal, Thailand and Brazil", "domain": "Malaria diagnostics / digital microscopy", "segment": "Global-health diagnostic research", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The device matched rather than exceeded expert microscopy (91.1% sensitivity, 75.6% specificity), and no patient outcome was tracked.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No patient-management or clinical outcome was measured." }, { "group": "organizational", "depth": null, "reason": "Laboratory-level accuracy was measured under study conditions, not routine field operation." }, { "group": "societal", "depth": null, "reason": "No deployment at program scale is documented." } ], "ai_role": { "status": "assessed", "statement": "The machine-learning device produced the readings compared against expert microscopy, so the measured accuracy is the AI's own performance. The evidence is a single peer-reviewed study funded by the maker (Global Good Fund) with maker-employed co-authors who provided inputs to study design and training. The authors state the study did not evaluate performance under routine field operation and that all parameters were significantly affected by slide quality. No independent or outcome-level evidence was found." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Das, D., Vongpromek, R., Assawariyathipat, T., et al. (2022). Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning. Malaria Journal 21, 122. doi:10.1186/s12936-022-04146-1.", "title": "Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning", "url": "https://doi.org/10.1186/s12936-022-04146-1", "date": "2022-04-12", "written_by": "makers", "quote": "The diagnostic sensitivity of EasyScan Go was 91.1% (95% CI 88.9-92.7), and specificity 75.6% (95% CI 73.1-78.0)." }, { "kind": "peer-reviewed study", "citation": "Das, D., et al. (2022). Same article, full text (methods and limitations). Europe PMC PMC9004086.", "title": "Field evaluation of the diagnostic performance of EasyScan GO (full text)", "url": "https://europepmc.org/article/PMC/PMC9004086", "date": "2022-04-12", "written_by": "makers", "quote": "In addition, the study did not evaluate the performance of the EasyScan Go under routine field operation." }, { "kind": "peer-reviewed study", "citation": "Das, D., et al. (2022). Same article, competing interests statement. Europe PMC PMC9004086.", "title": "Field evaluation of the diagnostic performance of EasyScan GO (competing interests)", "url": "https://europepmc.org/article/PMC/PMC9004086", "date": "2022-04-12", "written_by": "makers", "quote": "MPH, SKM, CM, SB, CBD and CB were employees of the Global Good Fund, Intellectual Ventures at the time of study implementation" }, { "kind": "peer-reviewed study", "citation": "Das, D., Vongpromek, R., Assawariyathipat, T., et al. (2022). Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning. Malaria Journal 21, 122. doi:10.1186/s12936-022-04146-1. Full text as served by the Europe PMC REST API (PMC9004086).", "title": "Field evaluation of the diagnostic performance of EasyScan GO (Europe PMC full text XML)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9004086/fullTextXML", "date": "2022-04-12", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "EasyScan GO devices donated and set up with manufacturer training at each site", "Giemsa-stained thick blood films read in parallel by two expert microscopists as reference", "STARD-reported multi-center observational design across 11 countries (ClinicalTrials.gov NCT03512678)" ], "must_hold": [ "Good slide quality, which the authors found significantly affected all performance parameters", "Parasitemia above about 200 parasites/uL, below which sensitivity fell to 57%", "Thick-film-only software (the tested version did not separate non-falciparum species)" ], "echoes": [ { "date": null, "setting": "Earlier field test of the first thick-film version in Thailand, 2014–2015, reported in the same article's background", "model_version": "first thick-film algorithm", "outcome": "recurred", "source": "https://europepmc.org/article/PMC/PMC9004086" }, { "date": null, "setting": "Thailand and Indonesia, 2016–2017: the article reports sensitivity 89% and specificity 97% for the second thick-film algorithm against expert microscopy", "model_version": "second thick-film algorithm", "outcome": "recurred", "source": "https://europepmc.org/article/PMC/PMC9004086" } ] }, "paired_incident": null, "headline": "EasyScan GO reaches 91.1% sensitivity for malaria at 11 sites", "metric": "Diagnostic sensitivity was 91.1% (95% CI 88.9–92.7) and specificity 75.6% (73.1–78.0)", "comparator": { "against": "expert microscopy", "before": null, "after": "diagnostic sensitivity of the EasyScan Go device was 91.1% (95% CI 88.9–92.7) and specificity was 75.6% (95% CI 73.1–78.0)", "basis": "measured", "quote": "Compared to reference microscopy, the diagnostic sensitivity of the EasyScan Go device was 91.1% (95% CI 88.9–92.7) and specificity was 75.6% (95% CI 73.1–78.0) (Table 1).", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9004086/fullTextXML" }, "later": { "status": "unknown", "date": null, "note": "No later evaluation, approval or deployment is reported in the article.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9004086/fullTextXML; https://www.ebi.ac.uk/europepmc/webservices/rest/PMC9004086/fullTextXML", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Intellectual_Ventures", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: three peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0352", "catalog_version": "1.0.0", "source_fingerprint": "165d995b2ec7578feda05d5f3990957643789fa9131b19484d3c70473c63db0f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0352-source-0001", "AIBD-0352-source-0002", "AIBD-0352-source-0003", "AIBD-0352-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Intellectual Ventures' Global Good Fund (software and original hardware); Motic (production prototype device, software licensed to Motic)", "deployer": "Research sites in 11 countries under a multi-center study with University of Oxford / Mahidol-Oxford Tropical Medicine Research Unit-affiliated investigators (research use, not routine service)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The machine-learning device produced the readings compared against expert microscopy, so the measured accuracy is the AI's own performance. 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The fieldwork is dated only to 2018 and 2019. It evaluated the EasyScan GO, a digital microscopy device whose convolutional-neural-network software was developed by Intellectual Ventures' Global Good Fund. Motic built its production prototype. The 11 sites were in 11 countries: Burkina Faso, Kenya, Republic of the Congo, Senegal, South Africa, Uganda, Bangladesh, Cambodia, Nepal, Thailand and Brazil. In total 2,250 Giemsa-stained blood films were read independently by expert microscopists and by the device. Diagnostic sensitivity was 91.1% (95% CI 88.9–92.7) and specificity 75.6% (73.1–78.0); with good-quality slides specificity rose to 85.1%. Species were identified accurately in 93% of P. falciparum and 92% of P. vivax samples. Parasite density estimates were within 25% of the reference in 23% of slides. The authors conclude the device meets WHO-TDR level 2 criteria for detection and species identification and level 4 for quantification and false-positive rate. They say all parameters were significantly affected by slide quality, and the study did not evaluate performance under routine field operation. The study was funded by the Global Good Fund, which donated the devices; six co-authors were its employees. 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The fieldwork is dated only to 2018 and 2019. It evaluated the EasyScan GO, a digital microscopy device whose convolutional-neural-network software was developed by Intellectual Ventures' Global Good Fund. Motic built its production prototype. The 11 sites were in 11 countries: Burkina Faso, Kenya, Republic of the Congo, Senegal, South Africa, Uganda, Bangladesh, Cambodia, Nepal, Thailand and Brazil. In total 2,250 Giemsa-stained blood films were read independently by expert microscopists and by the device. Diagnostic sensitivity was 91.1% (95% CI 88.9–92.7) and specificity 75.6% (73.1–78.0); with good-quality slides specificity rose to 85.1%. Species were identified accurately in 93% of P. falciparum and 92% of P. vivax samples. Parasite density estimates were within 25% of the reference in 23% of slides. The authors conclude the device meets WHO-TDR level 2 criteria for detection and species identification and level 4 for quantification and false-positive rate. They say all parameters were significantly affected by slide quality, and the study did not evaluate performance under routine field operation. The study was funded by the Global Good Fund, which donated the devices; six co-authors were its employees. No patient-management outcome was measured." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The network analyzed microscope images for malaria parasites." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used software version 1.15.17b." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. 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The fieldwork is dated only to 2018 and 2019. It evaluated the EasyScan GO, a digital microscopy device whose convolutional-neural-network software was developed by Intellectual Ventures' Global Good Fund. Motic built its production prototype. The 11 sites were in 11 countries: Burkina Faso, Kenya, Republic of the Congo, Senegal, South Africa, Uganda, Bangladesh, Cambodia, Nepal, Thailand and Brazil. In total 2,250 Giemsa-stained blood films were read independently by expert microscopists and by the device. Diagnostic sensitivity was 91.1% (95% CI 88.9–92.7) and specificity 75.6% (73.1–78.0); with good-quality slides specificity rose to 85.1%. Species were identified accurately in 93% of P. falciparum and 92% of P. vivax samples. Parasite density estimates were within 25% of the reference in 23% of slides. The authors conclude the device meets WHO-TDR level 2 criteria for detection and species identification and level 4 for quantification and false-positive rate. They say all parameters were significantly affected by slide quality, and the study did not evaluate performance under routine field operation. The study was funded by the Global Good Fund, which donated the devices; six co-authors were its employees. No patient-management outcome was measured.", "replication": { "produced_by": [ "EasyScan GO devices donated and set up with manufacturer training at each site", "Giemsa-stained thick blood films read in parallel by two expert microscopists as reference", "STARD-reported multi-center observational design across 11 countries (ClinicalTrials.gov NCT03512678)" ], "must_hold": [ "Good slide quality, which the authors found significantly affected all performance parameters", "Parasitemia above about 200 parasites/uL, below which sensitivity fell to 57%", "Thick-film-only software (the tested version did not separate non-falciparum species)" ], "echoes": [ { "setting": "Earlier field test of the first thick-film version in Thailand, 2014–2015, reported in the same article's background", "model_version": "first thick-film algorithm", "outcome": "recurred", "source": "https://europepmc.org/article/PMC/PMC9004086" }, { "setting": "Thailand and Indonesia, 2016–2017: the article reports sensitivity 89% and specificity 97% for the second thick-film algorithm against expert microscopy", "model_version": "second thick-film algorithm", "outcome": "recurred", "source": "https://europepmc.org/article/PMC/PMC9004086" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0045", "title": "FAST-PETase, a machine-learning-engineered enzyme, depolymerised post-consumer PET and was reused by an independent lab", "summary": "A 3D-CNN ensemble engineered FAST-PETase, which degraded 51 post-consumer PET products in a week; Texas A&M later reported complete depolymerisation using it with MHETase.", "date_observed": "2022-04-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In a Nature paper of 27 April 2022, researchers at the University of Texas at Austin used a structure-based machine-learning algorithm. The algorithm, an ensemble of three three-dimensional convolutional neural networks, selected stabilizing mutations in a polyethylene terephthalate (PET) hydrolase, producing FAST-PETase. They reported that untreated post-consumer PET from 51 different thermoformed products was almost completely degraded within one week at 50 degrees Celsius. The enzyme outperformed wild-type and engineered alternatives between 30 and 50 degrees Celsius. They closed the loop by resynthesizing PET from the recovered monomers. An independent group at Texas A&M University used FAST-PETase together with MHETase in a yeast whole-cell biocatalyst (Environmental Science and Technology Letters, 19 March 2025). It reported complete depolymerization of a PET film in seven days at 30 degrees Celsius.", "category": "benefit created", "unexpected": false, "purpose": "Use a structure-based machine-learning model to predict stabilizing mutations that make a PET hydrolase active and robust at moderate temperatures.", "system": "Structure-based machine-learning mutation predictor (ensemble of three 3D convolutional neural networks) applied to PETase engineering", "model_version": "MutCompute", "developer": "University of Texas at Austin (Alper and Ellington groups)", "deployer": "University of Texas at Austin; subsequently Texas A&M University", "location": "Austin, Texas, United States", "domain": "Enzyme engineering / plastic degradation", "segment": null, "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "A laboratory-scale enzyme that an independent group could pick up and reuse successfully; the sources report bench work, not production deployment." }, { "group": "societal", "depth": 1, "reason": "Complete depolymerization of untreated post-consumer PET was shown only in the laboratory in both the original and the independent study. 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Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst. Environ Sci Technol Lett.", "title": "Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/", "date": "2025-03-19", "written_by": "deployer", "quote": "a TPA yield of 4.95 mM was obtained after incubation with the PET film for 7 days" } ], "replication": { "produced_by": [ "A structure-based machine-learning model trained to predict stabilizing mutations", "A wild-type PET hydrolase as the starting scaffold", "Untreated post-consumer PET tested at moderate temperatures" ], "must_hold": [ "Moderate reaction temperatures (roughly 30–50 degrees Celsius)", "Amorphous or thermoformed PET substrate", "Enzyme expressed and purified or displayed at sufficient activity" ], "echoes": [ { "date": "2025-03-19", "setting": "Texas A&M University, FAST-PETase co-immobilised on a scaffoldin in a yeast whole-cell biocatalyst", "model_version": null, "outcome": "recurred", "source": "Gulati S, Sun Q. 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Nature 2022 (https://www.nature.com/articles/s41586-022-04599-z); Gulati S, Sun Q. Environ Sci Technol Lett 2025 (https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.nature.com/articles/s41586-022-04599-z; https://www.nature.com/articles/s41586-022-04599-z", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Texas_at_Austin; https://en.wikipedia.org/wiki/University_of_Texas_at_Austin", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A structure-based machine-learning model trained to predict stabilizing mutations", "A wild-type PET hydrolase as the starting scaffold", "Untreated post-consumer PET tested at moderate temperatures" ], "must_hold": [ "Moderate reaction temperatures (roughly 30–50 degrees Celsius)", "Amorphous or thermoformed PET substrate", "Enzyme expressed and purified or displayed at sufficient activity" ], "echoes": [ { "date": "2025-03-19", "setting": "Texas A&M University, FAST-PETase co-immobilised on a scaffoldin in a yeast whole-cell biocatalyst", "outcome": "recurred", "source": "Gulati S, Sun Q. Environ Sci Technol Lett 2025. https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A structure-based machine-learning model trained to predict stabilizing mutations", "A wild-type PET hydrolase as the starting scaffold", "Untreated post-consumer PET tested at moderate temperatures" ], "must_hold": [ "Moderate reaction temperatures (roughly 30–50 degrees Celsius)", "Amorphous or thermoformed PET substrate", "Enzyme expressed and purified or displayed at sufficient activity" ], "echoes": [ { "date": "2025-03-19", "setting": "Texas A&M University, FAST-PETase co-immobilised on a scaffoldin in a yeast whole-cell biocatalyst", "outcome": "recurred", "source": "Gulati S, Sun Q. Environ Sci Technol Lett 2025. https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the temperature of the 51-product degradation experiment to 50 degrees Celsius (30 to 50 degrees Celsius is the range over which FAST-PETase outperformed alternatives, a different claim), credited the complete depolymerisation to FAST-PETase co-immobilised with MHETase rather than to FAST-PETase alone, and used the exact title of the ESTL paper.", "source": "Lu H, et al. Nature 2022 (https://www.nature.com/articles/s41586-022-04599-z); Gulati S, Sun Q. Environ Sci Technol Lett 2025 (https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.nature.com/articles/s41586-022-04599-z; https://www.nature.com/articles/s41586-022-04599-z", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Texas_at_Austin; https://en.wikipedia.org/wiki/University_of_Texas_at_Austin", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Enzyme engineering / plastic degradation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Lu H, Diaz DJ, Czarnecki NJ, et al. (2022). Machine learning-aided engineering of hydrolases for PET depolymerization. Nature.", "title": "Machine learning-aided engineering of hydrolases for PET depolymerization", "url": "https://www.nature.com/articles/s41586-022-04599-z", "date": "2022-04-27", "written_by": "makers", "quote": "untreated, postconsumer-PET from 51 different thermoformed products can all be almost completely degraded by FAST-PETase in 1 week" }, { "kind": "peer-reviewed study", "citation": "Gulati S, Sun Q (2025). Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst. Environ Sci Technol Lett.", "title": "Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/", "date": "2025-03-19", "written_by": "deployer", "quote": "a TPA yield of 4.95 mM was obtained after incubation with the PET film for 7 days" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0045-source-0001", "AIBD-0045-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Lu H, Diaz DJ, Czarnecki NJ, et al. (2022). Machine learning-aided engineering of hydrolases for PET depolymerization. Nature.", "title": "Machine learning-aided engineering of hydrolases for PET depolymerization", "url": "https://www.nature.com/articles/s41586-022-04599-z", "date": "2022-04-27", "written_by": "makers", "quote": "untreated, postconsumer-PET from 51 different thermoformed products can all be almost completely degraded by FAST-PETase in 1 week" }, { "kind": "peer-reviewed study", "citation": "Gulati S, Sun Q (2025). Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst. Environ Sci Technol Lett.", "title": "Complete Enzymatic Depolymerization of Polyethylene Terephthalate (PET) Plastic Using a Saccharomyces cerevisiae-Based Whole-Cell Biocatalyst", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/", "date": "2025-03-19", "written_by": "deployer", "quote": "a TPA yield of 4.95 mM was obtained after incubation with the PET film for 7 days" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 3D-CNN ensemble engineered FAST-PETase, which degraded 51 post-consumer PET products in a week; Texas A&M later reported complete depolymerisation using it with MHETase.", "account": "In a Nature paper of 27 April 2022, researchers at the University of Texas at Austin used a structure-based machine-learning algorithm. The algorithm, an ensemble of three three-dimensional convolutional neural networks, selected stabilizing mutations in a polyethylene terephthalate (PET) hydrolase, producing FAST-PETase. They reported that untreated post-consumer PET from 51 different thermoformed products was almost completely degraded within one week at 50 degrees Celsius. The enzyme outperformed wild-type and engineered alternatives between 30 and 50 degrees Celsius. They closed the loop by resynthesizing PET from the recovered monomers. An independent group at Texas A&M University used FAST-PETase together with MHETase in a yeast whole-cell biocatalyst (Environmental Science and Technology Letters, 19 March 2025). It reported complete depolymerization of a PET film in seven days at 30 degrees Celsius." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model selected candidate mutations for enzyme experiments." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "MutCompute." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "MutCompute" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Structure-based machine-learning mutation predictor (ensemble of three 3D convolutional neural networks) applied to PETase engineering" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Texas at Austin (Alper and Ellington groups)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FAST-PETase, a machine-learning-engineered enzyme, depolymerised post-consumer PET and was reused by an independent lab", "headline": "FAST-PETase degrades 51 post-consumer PET products in a week" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d86cb258dc3a92e131233909ca6e1de0f131fae1027df04847983abbe5e9d70d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In a Nature paper of 27 April 2022, researchers at the University of Texas at Austin used a structure-based machine-learning algorithm. The algorithm, an ensemble of three three-dimensional convolutional neural networks, selected stabilizing mutations in a polyethylene terephthalate (PET) hydrolase, producing FAST-PETase. They reported that untreated post-consumer PET from 51 different thermoformed products was almost completely degraded within one week at 50 degrees Celsius. The enzyme outperformed wild-type and engineered alternatives between 30 and 50 degrees Celsius. They closed the loop by resynthesizing PET from the recovered monomers. An independent group at Texas A&M University used FAST-PETase together with MHETase in a yeast whole-cell biocatalyst (Environmental Science and Technology Letters, 19 March 2025). It reported complete depolymerization of a PET film in seven days at 30 degrees Celsius.", "replication": { "produced_by": [ "A structure-based machine-learning model trained to predict stabilizing mutations", "A wild-type PET hydrolase as the starting scaffold", "Untreated post-consumer PET tested at moderate temperatures" ], "must_hold": [ "Moderate reaction temperatures (roughly 30–50 degrees Celsius)", "Amorphous or thermoformed PET substrate", "Enzyme expressed and purified or displayed at sufficient activity" ], "echoes": [ { "date": "2025-03-19", "setting": "Texas A&M University, FAST-PETase co-immobilised on a scaffoldin in a yeast whole-cell biocatalyst", "outcome": "recurred", "source": "Gulati S, Sun Q. Environ Sci Technol Lett 2025. https://pmc.ncbi.nlm.nih.gov/articles/PMC11984091/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0079", "title": "RapidAI automated LVO detection alerts Memorial Neuroscience Institute's stroke team; 29-year-old firefighter's artery reopened within 60 minutes of arrival", "summary": "RapidAI's automated LVO alert mobilized the stroke team for Eric, 29; thrombectomy restored flow under 60 minutes from arrival; no deficits.", "date_observed": "2022-05-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Eric, a 29-year-old firefighter and paramedic, felt unwell after a workout. He tried to send a text and could not move his left thumb, then his left leg went numb. His trainer noticed he was slurring and called 9-1-1. Emergency medical services (EMS) took him to Memorial Hospital West's Comprehensive Stroke Center. Under the Memorial stroke protocol the paramedics had already alerted the hospital. The neurointerventional surgery team was ready to do a computed tomography (CT) scan and treat in the catheterization laboratory. As soon as scan results were available, Dr Brijesh Mehta received the RapidAI alert on his smartphone and smartwatch. It showed the software's automated detection of a large vessel occlusion (LVO). That prompted him to mobilize the cath lab team and fast-track Eric for mechanical thrombectomy. The blocked artery was fully opened and blood flow restored under 60 minutes from his arrival. Eric described himself as alive with no deficits. The hospital published the account on 12 May 2022; the stroke date and its city are not given.", "category": "protective response", "unexpected": false, "purpose": "RapidAI's platform is built to detect large vessel occlusion on imaging and push alerts to the stroke team so that thrombectomy can start sooner. This is its intended function.", "system": "RapidAI imaging platform (automated LVO detection)", "model_version": null, "developer": "RapidAI", "deployer": "Memorial Healthcare System / Memorial Neuroscience Institute (Memorial Hospital West)", "location": null, "domain": "Healthcare - acute stroke care", "segment": "Comprehensive stroke center AI triage", "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's part was faster team mobilization, and EMS had already pre-notified the hospital, so the counterfactual is unproven.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A 29-year-old had his occluded artery reopened within 60 minutes of arrival and reports being alive with no deficits. The AI's share is the time saved in fast-tracking the cath lab team after EMS had already pre-notified the hospital and the team was ready. The thrombectomy was the treatment." }, { "group": "organizational", "depth": 2, "reason": "Dr Mehta states that the platform streamlines workflow and cuts time compared with the previous need to open scans at workstations." } ], "ai_role": { "status": "assessed", "statement": "RapidAI's automated LVO detection delivered the alert that prompted Dr Mehta to mobilize the cath lab team and fast-track thrombectomy. Under the Memorial stroke protocol EMS had already pre-notified the hospital and the neurointerventional team was ready before imaging. The occlusion would have been identified on the CT scan regardless. So the AI's contribution is speed at the point of care, and its share of the time saved cannot be separated from the pre-notification. The only counterfactual offered is Dr Mehta's general description of the pre-RapidAI workflow." }, "evidence": [ { "kind": "press release", "citation": "Memorial Healthcare System (2022). Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients. Hospital news release, 12 May 2022, quoting Dr Brijesh P. Mehta, medical director of the Comprehensive Stroke Program and Neurointerventional Surgery at Memorial Neuroscience Institute, and the patient.", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "He received the RapidAI alert on his smartphone and smartwatch, showing the software's automated detection of LVO (large vessel occlusion)" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (second quotation).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "the blocked artery was fully opened, and blood flow restored after the thrombectomy procedure in under 60 minutes from his arrival" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (quotation from Dr Brijesh P. Mehta).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "The value of artificial intelligence is that it streamlines our workflow, cuts down time and allows us to make decisions quickly and effectively at the point of care to benefit our patients." } ], "replication": { "produced_by": [ "RapidAI LVO detection pushing alerts to the on-call neurointerventionalist's phone and watch", "A comprehensive stroke center with an in-house thrombectomy team" ], "must_hold": [ "Rapid recognition of stroke signs and EMS transport to a thrombectomy-capable center", "Team mobilization on the AI alert rather than after a formal radiology read" ], "echoes": [] }, "paired_incident": null, "headline": "RapidAI LVO alert gets Eric's artery reopened within 60 minutes", "metric": "thrombectomy restored flow under 60 minutes from arrival; no deficits", "comparator": { "against": "the hospital's workflow before RapidAI, with scans viewed at workstations", "before": "tethered to our workstations and had to take multiple steps to open the software to view the scans", "after": "RapidAI alert on his smartphone and smartwatch; artery opened in under 60 minutes from arrival", "basis": "assumed", "quote": "Before RapidAI, we were tethered to our workstations and had to take multiple steps to open the software to view the scans. 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This is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-05-12", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected Eric's symptoms to the source's wording (could not move his left thumb, then his left leg went numb, trainer noticed slurring), added that EMS had pre-notified the hospital and the team was ready before imaging so that the alert's role is fast-tracking the cath lab team, changed “CT angiogram” to “CT scan”, quoted Dr Mehta's sentence in full, and moved the category from specific harm prevented to protective response with prevention unproven because the source offers no individual counterfactual for the AI's share of the time saved.", "source": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected Eric's symptoms to the source's wording (could not move his left thumb, then his left leg went numb, trainer noticed slurring), added that EMS had pre-notified the hospital and the team was ready before imaging so that the alert's role is fast-tracking the cath lab team, changed “CT angiogram” to “CT scan”, quoted Dr Mehta's sentence in full, and moved the category from specific harm prevented to protective response with prevention unproven because the source offers no individual counterfactual for the AI's share of the time saved.", "source": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.rapidai.com/privacy-policy; https://www.mhs.net/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - acute stroke care", "segment": "Comprehensive stroke center AI triage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Memorial Healthcare System (2022). Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients. Hospital news release, 12 May 2022, quoting Dr Brijesh P. Mehta, medical director of the Comprehensive Stroke Program and Neurointerventional Surgery at Memorial Neuroscience Institute, and the patient.", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "He received the RapidAI alert on his smartphone and smartwatch, showing the software's automated detection of LVO (large vessel occlusion)" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (second quotation).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "the blocked artery was fully opened, and blood flow restored after the thrombectomy procedure in under 60 minutes from his arrival" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (quotation from Dr Brijesh P. Mehta).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "The value of artificial intelligence is that it streamlines our workflow, cuts down time and allows us to make decisions quickly and effectively at the point of care to benefit our patients." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0079-source-0001", "AIBD-0079-source-0002", "AIBD-0079-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Memorial Healthcare System (2022). Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients. Hospital news release, 12 May 2022, quoting Dr Brijesh P. Mehta, medical director of the Comprehensive Stroke Program and Neurointerventional Surgery at Memorial Neuroscience Institute, and the patient.", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "He received the RapidAI alert on his smartphone and smartwatch, showing the software's automated detection of LVO (large vessel occlusion)" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (second quotation).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "the blocked artery was fully opened, and blood flow restored after the thrombectomy procedure in under 60 minutes from his arrival" }, { "kind": "press release", "citation": "Memorial Healthcare System (2022). Hospital news release, 12 May 2022 (quotation from Dr Brijesh P. Mehta).", "title": "Memorial Neuroscience Institute Uses AI to Optimize Care and Positive Outcomes for Stroke Patients", "url": "https://www.mhs.net/news/2022/05/memorial-neuroscience-institute-uses-ai-to-optimize-care-and-positive-outcomes-for-stroke-patients", "date": "2022-05-12", "written_by": "deployer", "quote": "The value of artificial intelligence is that it streamlines our workflow, cuts down time and allows us to make decisions quickly and effectively at the point of care to benefit our patients." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "RapidAI's automated LVO alert mobilized the stroke team for Eric, 29; thrombectomy restored flow under 60 minutes from arrival; no deficits.", "account": "Eric, a 29-year-old firefighter and paramedic, felt unwell after a workout. He tried to send a text and could not move his left thumb, then his left leg went numb. His trainer noticed he was slurring and called 9-1-1. Emergency medical services (EMS) took him to Memorial Hospital West's Comprehensive Stroke Center. Under the Memorial stroke protocol the paramedics had already alerted the hospital. The neurointerventional surgery team was ready to do a computed tomography (CT) scan and treat in the catheterization laboratory. As soon as scan results were available, Dr Brijesh Mehta received the RapidAI alert on his smartphone and smartwatch. It showed the software's automated detection of a large vessel occlusion (LVO). That prompted him to mobilize the cath lab team and fast-track Eric for mechanical thrombectomy. The blocked artery was fully opened and blood flow restored under 60 minutes from his arrival. Eric described himself as alive with no deficits. The hospital published the account on 12 May 2022; the stroke date and its city are not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "RapidAI imaging platform (automated LVO detection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "RapidAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "RapidAI automated LVO detection alerts Memorial Neuroscience Institute's stroke team; 29-year-old firefighter's artery reopened within 60 minutes of arrival", "headline": "RapidAI LVO alert gets Eric's artery reopened within 60 minutes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1067971966d0f02e27b9747935cc762ce4a7715429d236e1b8344bb89c6ee12b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Eric, a 29-year-old firefighter and paramedic, felt unwell after a workout. He tried to send a text and could not move his left thumb, then his left leg went numb. His trainer noticed he was slurring and called 9-1-1. Emergency medical services (EMS) took him to Memorial Hospital West's Comprehensive Stroke Center. Under the Memorial stroke protocol the paramedics had already alerted the hospital. The neurointerventional surgery team was ready to do a computed tomography (CT) scan and treat in the catheterization laboratory. As soon as scan results were available, Dr Brijesh Mehta received the RapidAI alert on his smartphone and smartwatch. It showed the software's automated detection of a large vessel occlusion (LVO). That prompted him to mobilize the cath lab team and fast-track Eric for mechanical thrombectomy. The blocked artery was fully opened and blood flow restored under 60 minutes from his arrival. Eric described himself as alive with no deficits. The hospital published the account on 12 May 2022; the stroke date and its city are not given.", "replication": { "produced_by": [ "RapidAI LVO detection pushing alerts to the on-call neurointerventionalist's phone and watch", "A comprehensive stroke center with an in-house thrombectomy team" ], "must_hold": [ "Rapid recognition of stroke signs and EMS transport to a thrombectomy-capable center", "Team mobilization on the AI alert rather than after a formal radiology read" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0113", "title": "Meta threat alert, relayed through the FBI, brings Paraguayan police and psychologists to a bullied 17-year-old who praised the Uvalde shooter", "summary": "Meta flagged a Paraguayan teen's post praising the Uvalde shooter; the FBI relayed it and police, prosecutors and psychologists intervened.", "date_observed": "2022-05-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Thursday 26 May 2022, two days after the Uvalde school shooting, Paraguay's Policía Nacional and Ministerio Público received an alert. It came from Meta's platform and the FBI office in Buenos Aires. A user in Paraguay had tagged the shooter, called himself his “fan” and said something similar could happen in Paraguay with more victims. Comisario Diosnel Alarcón's cybercrime department identified the Instagram profile as a 17-year-old in the “zona central”. He lived with a relative and was treated as a bullying victim. Police, prosecutors, the children's defender and psychologists visited the home and recommended urgent psychological support, and also visited a friend who knew of the posts. No weapon or plan was reported.", "category": "protective response", "unexpected": false, "purpose": "Meta's content-detection and law-enforcement referral process exists to find posts that threaten violence or self-harm. It passes credible threats to the authorities of the user's country. Flagging this post and alerting the police was that purpose.", "system": "Meta (Facebook/Instagram) violence-threat detection and law-enforcement referral process", "model_version": null, "developer": "Meta Platforms", "deployer": "Meta Platforms", "location": null, "domain": "Online safety and threat referral to law enforcement", "segment": "Media, social platforms, and marketing", "benefit_type": "Reduced Violence", "taxonomy_note": "A threat of a copycat shooting was checked and the minor given psychological support, but no weapon or plan was found and the detection is not shown to be automated.", "registry_ids": { "oecd_aim": "2022-05-27-1b09" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "The 17-year-old, a bullying victim living with a relative, was seen by prosecutors' psychologists, who recommended urgent support (“contención”). The sources report no coercive outcome beyond a planned review of his phone." }, { "group": "societal", "depth": 1, "reason": "A public statement that a school shooting could be repeated in Paraguay was checked within a day, after local media had reported threats in schools. Police said many such alerts prove to be jokes, so no prevented harm is shown." } ], "ai_role": { "status": "unassessed", "statement": "Officials said the network detected the comment, classified it as dangerous and reported it. It went to the FBI and a 24/7 channel shared by prosecutors and the cybercrime police. Alarcón also spoke of corroborating “datos de analítica artificial” before the visit. No source says the flag was automated. Meta documents that its technology proactively detects most violating content before anyone reports it, but its referrals to law enforcement also pass through human review. Identifying the user, the home visit and the psychological support were the work of Paraguayan police, prosecutors and the child-protection office." }, "evidence": [ { "kind": "news report", "citation": "La Nación, Paraguay (2022). Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor. La Nación.", "title": "Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor", "url": "https://www.lanacion.com.py/pais/2022/05/26/atentado-en-texas-fbi-alerta-sobre-intencion-de-replicar-el-hecho-en-paraguay-por-parte-de-un-menor/", "date": "2022-05-26", "written_by": "independent", "quote": "eso detecta la red social y reporta al FBI como también a una red 24/7 en el que está tanto el Ministerio Público como la Policía de Delitos Informáticos" }, { "kind": "news report", "citation": "Última Hora, Glezcu, M. (2022). FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio. Última Hora.", "title": "FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio", "url": "https://www.ultimahora.com/fbi-alerta-la-policia-paraguaya-una-amenaza-tiroteo-un-colegio-n3003665.html", "date": "2022-05-26", "written_by": "independent", "quote": "las alertas llegan constantemente cuando las redes sociales detectan conductas de personas que quieren atentar contra su vida o también de otros tipos de hechos punibles graves" }, { "kind": "news report", "citation": "Diario Hoy (2022). Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó. Hoy.", "title": "Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó", "url": "https://www.hoy.com.py/nacionales/joven-paraguayo-alento-por-redes-a-tiroteo-en-texas-delitos-informaticos-ya-lo-ubico", "date": "2022-05-27", "written_by": "independent", "quote": "Fuimos alertados a través de la red social involucrada y el FBI de Buenos Aires, luego hicimos lo propio en el Departamento de Cibercrimen para identificar al usuario" }, { "kind": "news report", "citation": "Última Hora (2022). Caso alertado por FBI involucra a una víctima del bullying, señalan. Última Hora.", "title": "Caso alertado por FBI involucra a una víctima del bullying, señalan", "url": "https://www.ultimahora.com/caso-alertado-fbi-involucra-una-victima-del-bullying-segun-fiscalia-n3003798.html", "date": "2022-05-27", "written_by": "independent", "quote": "El Ministerio Público también recibió la misma alerta que recibió la Policía Nacional el jueves por parte de la agencia federal de investigación e inteligencia FBI" }, { "kind": "news report", "citation": "Última Hora (2022). Policía Nacional señala que reciben alertas periódicas de redes sociales. Última Hora.", "title": "Policía Nacional señala que reciben alertas periódicas de redes sociales", "url": "https://www.ultimahora.com/delitos-informaticos-senala-que-reciben-alertas-periodicas-redes-sociales-n3003985.html", "date": "2022-05-28", "written_by": "independent", "quote": "una vez corroborados los datos de analítica artificial, nos constituimos en la casa del adolescente" }, { "kind": "news report", "citation": "EFE, via Vanguardia (2022). Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas. Vanguardia.", "title": "Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas", "url": "https://www.vanguardia.com/tecnologia/menor-paraguayo-activa-alerta-de-facebook-tras-mensaje-sobre-masacre-de-texas-XA5244671", "date": "2022-05-27", "written_by": "independent", "quote": "publicó un comentario que la red social catalogó como peligroso" }, { "kind": "press release", "citation": "Meta (n.d.). Detecting violations. Meta Transparency Center.", "title": "Detecting violations", "url": "https://transparency.meta.com/enforcement/detecting-violations/", "date": null, "written_by": "makers", "quote": "Our technology proactively detects and removes the vast majority of violating content before anyone reports it" } ], "replication": { "produced_by": [ "A platform practice of reporting threats of violence to law enforcement in the user's country. Here, via the FBI's Buenos Aires office and a 24/7 police-prosecutor channel.", "A cybercrime unit able to identify an account holder from the platform's primary data within hours", "A welfare rather than punitive response, with prosecutors, the children's defender and psychologists attending" ], "must_hold": [ "The referral must carry enough account data to identify a real person; police said many flagged profiles are fake or jokes", "The response must stay proportionate for a minor; the Monitor flags rights, psychological and reputational risks to the child", "The platform's detection and referral thresholds, which are not public for this case, must stay in place for the alert to recur" ], "echoes": [] }, "paired_incident": null, "headline": "Meta alert brings police and psychologists to a Paraguayan teen", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "Follow-up reports on 27 and 28 May 2022 described the police visit with psychologists and said the cybercrime unit receives such platform alerts routinely, but no later development in this case was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-05-27-1b09", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports and the makers' press release. 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It went to the FBI and a 24/7 channel shared by prosecutors and the cybercrime police. Alarcón also spoke of corroborating “datos de analítica artificial” before the visit. No source says the flag was automated. Meta documents that its technology proactively detects most violating content before anyone reports it, but its referrals to law enforcement also pass through human review. 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Flagging this post and alerting the police was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Meta's content-detection and law-enforcement referral process exists to find posts that threaten violence or self-harm. It passes credible threats to the authorities of the user's country. Flagging this post and alerting the police was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-05-26", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-05-27-1b09", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A platform practice of reporting threats of violence to law enforcement in the user's country. Here, via the FBI's Buenos Aires office and a 24/7 police-prosecutor channel.", "A cybercrime unit able to identify an account holder from the platform's primary data within hours", "A welfare rather than punitive response, with prosecutors, the children's defender and psychologists attending" ], "must_hold": [ "The referral must carry enough account data to identify a real person; police said many flagged profiles are fake or jokes", "The response must stay proportionate for a minor; the Monitor flags rights, psychological and reputational risks to the child", "The platform's detection and referral thresholds, which are not public for this case, must stay in place for the alert to recur" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-05-27-1b09", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Online safety and threat referral to law enforcement", "segment": "Media, social platforms, and marketing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "La Nación, Paraguay (2022). Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor. La Nación.", "title": "Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor", "url": "https://www.lanacion.com.py/pais/2022/05/26/atentado-en-texas-fbi-alerta-sobre-intencion-de-replicar-el-hecho-en-paraguay-por-parte-de-un-menor/", "date": "2022-05-26", "written_by": "independent", "quote": "eso detecta la red social y reporta al FBI como también a una red 24/7 en el que está tanto el Ministerio Público como la Policía de Delitos Informáticos" }, { "kind": "news report", "citation": "Última Hora, Glezcu, M. (2022). FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio. Última Hora.", "title": "FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio", "url": "https://www.ultimahora.com/fbi-alerta-la-policia-paraguaya-una-amenaza-tiroteo-un-colegio-n3003665.html", "date": "2022-05-26", "written_by": "independent", "quote": "las alertas llegan constantemente cuando las redes sociales detectan conductas de personas que quieren atentar contra su vida o también de otros tipos de hechos punibles graves" }, { "kind": "news report", "citation": "Diario Hoy (2022). Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó. Hoy.", "title": "Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó", "url": "https://www.hoy.com.py/nacionales/joven-paraguayo-alento-por-redes-a-tiroteo-en-texas-delitos-informaticos-ya-lo-ubico", "date": "2022-05-27", "written_by": "independent", "quote": "Fuimos alertados a través de la red social involucrada y el FBI de Buenos Aires, luego hicimos lo propio en el Departamento de Cibercrimen para identificar al usuario" }, { "kind": "news report", "citation": "Última Hora (2022). Caso alertado por FBI involucra a una víctima del bullying, señalan. Última Hora.", "title": "Caso alertado por FBI involucra a una víctima del bullying, señalan", "url": "https://www.ultimahora.com/caso-alertado-fbi-involucra-una-victima-del-bullying-segun-fiscalia-n3003798.html", "date": "2022-05-27", "written_by": "independent", "quote": "El Ministerio Público también recibió la misma alerta que recibió la Policía Nacional el jueves por parte de la agencia federal de investigación e inteligencia FBI" }, { "kind": "news report", "citation": "Última Hora (2022). Policía Nacional señala que reciben alertas periódicas de redes sociales. Última Hora.", "title": "Policía Nacional señala que reciben alertas periódicas de redes sociales", "url": "https://www.ultimahora.com/delitos-informaticos-senala-que-reciben-alertas-periodicas-redes-sociales-n3003985.html", "date": "2022-05-28", "written_by": "independent", "quote": "una vez corroborados los datos de analítica artificial, nos constituimos en la casa del adolescente" }, { "kind": "news report", "citation": "EFE, via Vanguardia (2022). Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas. Vanguardia.", "title": "Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas", "url": "https://www.vanguardia.com/tecnologia/menor-paraguayo-activa-alerta-de-facebook-tras-mensaje-sobre-masacre-de-texas-XA5244671", "date": "2022-05-27", "written_by": "independent", "quote": "publicó un comentario que la red social catalogó como peligroso" }, { "kind": "press release", "citation": "Meta (n.d.). Detecting violations. Meta Transparency Center.", "title": "Detecting violations", "url": "https://transparency.meta.com/enforcement/detecting-violations/", "written_by": "makers", "quote": "Our technology proactively detects and removes the vast majority of violating content before anyone reports it" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0113-source-0001", "AIBD-0113-source-0002", "AIBD-0113-source-0003", "AIBD-0113-source-0004", "AIBD-0113-source-0005", "AIBD-0113-source-0006", "AIBD-0113-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "La Nación, Paraguay (2022). Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor. La Nación.", "title": "Atentado en Texas: FBI alerta sobre intención de replicar el hecho en Paraguay por parte de un menor", "url": "https://www.lanacion.com.py/pais/2022/05/26/atentado-en-texas-fbi-alerta-sobre-intencion-de-replicar-el-hecho-en-paraguay-por-parte-de-un-menor/", "date": "2022-05-26", "written_by": "independent", "quote": "eso detecta la red social y reporta al FBI como también a una red 24/7 en el que está tanto el Ministerio Público como la Policía de Delitos Informáticos" }, { "kind": "news report", "citation": "Última Hora, Glezcu, M. (2022). FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio. Última Hora.", "title": "FBI alerta a la Policía paraguaya de una amenaza de tiroteo en un colegio", "url": "https://www.ultimahora.com/fbi-alerta-la-policia-paraguaya-una-amenaza-tiroteo-un-colegio-n3003665.html", "date": "2022-05-26", "written_by": "independent", "quote": "las alertas llegan constantemente cuando las redes sociales detectan conductas de personas que quieren atentar contra su vida o también de otros tipos de hechos punibles graves" }, { "kind": "news report", "citation": "Diario Hoy (2022). Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó. Hoy.", "title": "Joven paraguayo alentó por redes a tiroteo en Texas: FBI alertó y la Policía ya lo ubicó", "url": "https://www.hoy.com.py/nacionales/joven-paraguayo-alento-por-redes-a-tiroteo-en-texas-delitos-informaticos-ya-lo-ubico", "date": "2022-05-27", "written_by": "independent", "quote": "Fuimos alertados a través de la red social involucrada y el FBI de Buenos Aires, luego hicimos lo propio en el Departamento de Cibercrimen para identificar al usuario" }, { "kind": "news report", "citation": "Última Hora (2022). Caso alertado por FBI involucra a una víctima del bullying, señalan. Última Hora.", "title": "Caso alertado por FBI involucra a una víctima del bullying, señalan", "url": "https://www.ultimahora.com/caso-alertado-fbi-involucra-una-victima-del-bullying-segun-fiscalia-n3003798.html", "date": "2022-05-27", "written_by": "independent", "quote": "El Ministerio Público también recibió la misma alerta que recibió la Policía Nacional el jueves por parte de la agencia federal de investigación e inteligencia FBI" }, { "kind": "news report", "citation": "Última Hora (2022). Policía Nacional señala que reciben alertas periódicas de redes sociales. Última Hora.", "title": "Policía Nacional señala que reciben alertas periódicas de redes sociales", "url": "https://www.ultimahora.com/delitos-informaticos-senala-que-reciben-alertas-periodicas-redes-sociales-n3003985.html", "date": "2022-05-28", "written_by": "independent", "quote": "una vez corroborados los datos de analítica artificial, nos constituimos en la casa del adolescente" }, { "kind": "news report", "citation": "EFE, via Vanguardia (2022). Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas. Vanguardia.", "title": "Menor paraguayo activa alerta de Facebook tras mensaje sobre masacre de Texas", "url": "https://www.vanguardia.com/tecnologia/menor-paraguayo-activa-alerta-de-facebook-tras-mensaje-sobre-masacre-de-texas-XA5244671", "date": "2022-05-27", "written_by": "independent", "quote": "publicó un comentario que la red social catalogó como peligroso" }, { "kind": "press release", "citation": "Meta (n.d.). Detecting violations. Meta Transparency Center.", "title": "Detecting violations", "url": "https://transparency.meta.com/enforcement/detecting-violations/", "written_by": "makers", "quote": "Our technology proactively detects and removes the vast majority of violating content before anyone reports it" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Meta flagged a Paraguayan teen's post praising the Uvalde shooter; the FBI relayed it and police, prosecutors and psychologists intervened.", "account": "On Thursday 26 May 2022, two days after the Uvalde school shooting, Paraguay's Policía Nacional and Ministerio Público received an alert. It came from Meta's platform and the FBI office in Buenos Aires. A user in Paraguay had tagged the shooter, called himself his “fan” and said something similar could happen in Paraguay with more victims. Comisario Diosnel Alarcón's cybercrime department identified the Instagram profile as a 17-year-old in the “zona central”. He lived with a relative and was treated as a bullying victim. Police, prosecutors, the children's defender and psychologists visited the home and recommended urgent psychological support, and also visited a friend who knew of the posts. No weapon or plan was reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Meta (Facebook/Instagram) violence-threat detection and law-enforcement referral process" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meta Platforms" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Meta threat alert, relayed through the FBI, brings Paraguayan police and psychologists to a bullied 17-year-old who praised the Uvalde shooter", "headline": "Meta alert brings police and psychologists to a Paraguayan teen" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "976c61ad62f482e970abb49b78777dfcbf43fa9ab0c98c75a6d47b93f4d3989c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Thursday 26 May 2022, two days after the Uvalde school shooting, Paraguay's Policía Nacional and Ministerio Público received an alert. It came from Meta's platform and the FBI office in Buenos Aires. A user in Paraguay had tagged the shooter, called himself his “fan” and said something similar could happen in Paraguay with more victims. Comisario Diosnel Alarcón's cybercrime department identified the Instagram profile as a 17-year-old in the “zona central”. He lived with a relative and was treated as a bullying victim. Police, prosecutors, the children's defender and psychologists visited the home and recommended urgent psychological support, and also visited a friend who knew of the posts. No weapon or plan was reported.", "replication": { "produced_by": [ "A platform practice of reporting threats of violence to law enforcement in the user's country. Here, via the FBI's Buenos Aires office and a 24/7 police-prosecutor channel.", "A cybercrime unit able to identify an account holder from the platform's primary data within hours", "A welfare rather than punitive response, with prosecutors, the children's defender and psychologists attending" ], "must_hold": [ "The referral must carry enough account data to identify a real person; police said many flagged profiles are fake or jokes", "The response must stay proportionate for a minor; the Monitor flags rights, psychological and reputational risks to the child", "The platform's detection and referral thresholds, which are not public for this case, must stay in place for the alert to recur" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0321", "title": "ABAIR's Irish synthetic voices power an NVDA screenreader plugin for visually impaired pupils, “extensively tested with visually-impaired school children”", "summary": "SLPAT 2022 paper by the ABAIR team (Trinity College Dublin): Irish NVDA plugin with Braille output, NCBI-funded, built with a blind researcher, tested with visually impaired pupils; no dated outcome.", "date_observed": "2022-05-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Ní Chasaide, Barnes, Ní Chiaráin, McGuirk, Morrin, Nic Corcráin and Cummins of the ABAIR initiative described three assistive applications of ABAIR's Irish speech technology. This was at the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022, 27 May 2022). The first is “A screenreading facility for Irish has been developed as a plugin for the NVDA screenreader, prompted by urgent pleas from parents and grandparents of visually impaired children in the Gaeltacht or attending Irish-medium schools”. Only three books existed in Irish Braille for them. “With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin”. It adds Braille output through the Liblouis translator and lets users choose a male or female voice and the reading speed. The paper states “The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)”. The reference list has McGuirk 2015, an M.Phil. dissertation. It names no child, school, date or measured result and describes the voices as text-to-speech synthesis without stating the synthesis method. No source independent of the developers was found.", "category": "general benefit", "unexpected": false, "purpose": "Built so that blind and visually impaired pupils can hear and read Irish text through a screenreader with Braille output. Use by school children was that intended purpose.", "system": "ABAIR Irish-language synthetic voices (abair.ie) delivered through an NVDA screenreader plugin with Liblouis Braille output", "model_version": null, "developer": "ABAIR project, Phonetics and Speech Laboratory, Trinity College Dublin (Ní Chasaide et al.), with a blind researcher funded by the National Council for the Blind of Ireland", "deployer": "Visually impaired pupils in Gaeltacht and Irish-medium schools, per the paper", "location": "Ireland", "domain": "Accessibility / assistive technology for an endangered language", "segment": "Blind and low-vision school pupils learning through Irish", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The paper reports extensive testing with visually impaired school children and the motivating need (three Irish Braille books). No identified pupil, date or measured gain." }, { "group": "societal", "depth": null, "reason": "Access to written Irish for the 4,701 school-age blind or visually impaired people cited from the 2016 census is the stated aim. No uptake figure is given." } ], "ai_role": { "status": "unassessed", "statement": "The evidence is limited to the developers' account. The ABAIR team's SLPAT 2022 paper says the Irish NVDA plugin with their synthetic voices was built with a blind researcher. It was extensively tested with visually impaired school children, without any outcome data. The paper does not describe the synthesis method. So neither the system's AI character nor its contribution to any pupil's reading can be assessed from cited sources." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Ní Chasaide A, Barnes E, Ní Chiaráin N, McGuirk R, Morrin O, Nic Corcráin M, Cummins J (2022). Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective. Proceedings of the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022), pp. 80-87, doi:10.18653/v1/2022.slpat-1.10 (authored by the system's developers).", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10/", "date": "2022-05-27", "written_by": "makers", "quote": "The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)." }, { "kind": "peer-reviewed study", "citation": "Ní Chasaide et al. (2022), same paper, section 4.", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10.pdf", "date": "2022-05-27", "written_by": "makers", "quote": "With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin." } ], "replication": { "produced_by": [ "Multidialect Irish text-to-speech voices from the ABAIR initiative, funded under the 20-Year Strategy for the Irish Language", "A blind researcher co-developing the NVDA plugin with NCBI funding, with Liblouis Braille output" ], "must_hold": [ "Users and their support networks (teachers, family) are involved in design and testing, which the authors state as a guiding principle", "The free NVDA screenreader is the pupil's platform" ], "echoes": [] }, "paired_incident": null, "headline": "ABAIR's Irish voices power an NVDA screenreader for blind pupils", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No source dated after 27 May 2022 reports deployment, uptake or review of the NVDA plugin; abair.ie's undated 'Léitheoir Scáileáin + Braille' page gives setup instructions only,.", "quote": null, "url": null }, "value": null, "developer_country": "Ireland", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.abair.ie/en/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0321", "catalog_version": "1.0.0", "source_fingerprint": "1f6db98b74a15ad6fae2921bdf0de524a744c89936ca94eea19498fde4e40e3f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0321-source-0001", "AIBD-0321-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ABAIR project, Phonetics and Speech Laboratory, Trinity College Dublin (Ní Chasaide et al.), with a blind researcher funded by the National Council for the Blind of Ireland", "deployer": "Visually impaired pupils in Gaeltacht and Irish-medium schools, per the paper" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The evidence is limited to the developers' account. The ABAIR team's SLPAT 2022 paper says the Irish NVDA plugin with their synthetic voices was built with a blind researcher. It was extensively tested with visually impaired school children, without any outcome data. The paper does not describe the synthesis method. So neither the system's AI character nor its contribution to any pupil's reading can be assessed from cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: two peer-reviewed studies from the makers. 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No uptake figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The paper reports extensive testing with visually impaired school children and the motivating need (three Irish Braille books). No identified pupil, date or measured gain." }, { "group": "societal", "reason": "Access to written Irish for the 4,701 school-age blind or visually impaired people cited from the 2016 census is the stated aim. No uptake figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No source dated after 27 May 2022 reports deployment, uptake or review of the NVDA plugin; abair.ie's undated 'Léitheoir Scáileáin + Braille' page gives setup instructions only,." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0321" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Ní Chasaide, Barnes, Ní Chiaráin, McGuirk, Morrin, Nic Corcráin and Cummins of the ABAIR initiative described three assistive applications of ABAIR's Irish speech technology. This was at the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022, 27 May 2022). The first is “A screenreading facility for Irish has been developed as a plugin for the NVDA screenreader, prompted by urgent pleas from parents and grandparents of visually impaired children in the Gaeltacht or attending Irish-medium schools”. Only three books existed in Irish Braille for them. “With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin”. It adds Braille output through the Liblouis translator and lets users choose a male or female voice and the reading speed. The paper states “The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)”. The reference list has McGuirk 2015, an M.Phil. dissertation. It names no child, school, date or measured result and describes the voices as text-to-speech synthesis without stating the synthesis method. No source independent of the developers was found.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The paper reports extensive testing with visually impaired school children and the motivating need (three Irish Braille books). No identified pupil, date or measured gain." }, { "group": "societal", "reason": "Access to written Irish for the 4,701 school-age blind or visually impaired people cited from the 2016 census is the stated aim. No uptake figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built so that blind and visually impaired pupils can hear and read Irish text through a screenreader with Braille output. Use by school children was that intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ireland", "developer_country": "Ireland" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built so that blind and visually impaired pupils can hear and read Irish text through a screenreader with Braille output. Use by school children was that intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-05-27", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.abair.ie/en/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Multidialect Irish text-to-speech voices from the ABAIR initiative, funded under the 20-Year Strategy for the Irish Language", "A blind researcher co-developing the NVDA plugin with NCBI funding, with Liblouis Braille output" ], "must_hold": [ "Users and their support networks (teachers, family) are involved in design and testing, which the authors state as a guiding principle", "The free NVDA screenreader is the pupil's platform" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.abair.ie/en/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Accessibility / assistive technology for an endangered language", "segment": "Blind and low-vision school pupils learning through Irish" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Ní Chasaide A, Barnes E, Ní Chiaráin N, McGuirk R, Morrin O, Nic Corcráin M, Cummins J (2022). Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective. Proceedings of the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022), pp. 80-87, doi:10.18653/v1/2022.slpat-1.10 (authored by the system's developers).", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10/", "date": "2022-05-27", "written_by": "makers", "quote": "The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)." }, { "kind": "peer-reviewed study", "citation": "Ní Chasaide et al. (2022), same paper, section 4.", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10.pdf", "date": "2022-05-27", "written_by": "makers", "quote": "With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0321-source-0001", "AIBD-0321-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Ní Chasaide A, Barnes E, Ní Chiaráin N, McGuirk R, Morrin O, Nic Corcráin M, Cummins J (2022). Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective. Proceedings of the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022), pp. 80-87, doi:10.18653/v1/2022.slpat-1.10 (authored by the system's developers).", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10/", "date": "2022-05-27", "written_by": "makers", "quote": "The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)." }, { "kind": "peer-reviewed study", "citation": "Ní Chasaide et al. (2022), same paper, section 4.", "title": "Challenges in assistive technology development for an endangered language: an Irish (Gaelic) perspective", "url": "https://aclanthology.org/2022.slpat-1.10.pdf", "date": "2022-05-27", "written_by": "makers", "quote": "With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SLPAT 2022 paper by the ABAIR team (Trinity College Dublin): Irish NVDA plugin with Braille output, NCBI-funded, built with a blind researcher, tested with visually impaired pupils; no dated outcome.", "account": "Ní Chasaide, Barnes, Ní Chiaráin, McGuirk, Morrin, Nic Corcráin and Cummins of the ABAIR initiative described three assistive applications of ABAIR's Irish speech technology. This was at the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022, 27 May 2022). The first is “A screenreading facility for Irish has been developed as a plugin for the NVDA screenreader, prompted by urgent pleas from parents and grandparents of visually impaired children in the Gaeltacht or attending Irish-medium schools”. Only three books existed in Irish Braille for them. “With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin”. It adds Braille output through the Liblouis translator and lets users choose a male or female voice and the reading speed. The paper states “The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)”. The reference list has McGuirk 2015, an M.Phil. dissertation. It names no child, school, date or measured result and describes the voices as text-to-speech synthesis without stating the synthesis method. No source independent of the developers was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ABAIR Irish-language synthetic voices (abair.ie) delivered through an NVDA screenreader plugin with Liblouis Braille output" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ABAIR project, Phonetics and Speech Laboratory, Trinity College Dublin (Ní Chasaide et al.), with a blind researcher funded by the National Council for the Blind of Ireland" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ABAIR's Irish synthetic voices power an NVDA screenreader plugin for visually impaired pupils, “extensively tested with visually-impaired school children”", "headline": "ABAIR's Irish voices power an NVDA screenreader for blind pupils" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1f6db98b74a15ad6fae2921bdf0de524a744c89936ca94eea19498fde4e40e3f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Ní Chasaide, Barnes, Ní Chiaráin, McGuirk, Morrin, Nic Corcráin and Cummins of the ABAIR initiative described three assistive applications of ABAIR's Irish speech technology. This was at the Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022, 27 May 2022). The first is “A screenreading facility for Irish has been developed as a plugin for the NVDA screenreader, prompted by urgent pleas from parents and grandparents of visually impaired children in the Gaeltacht or attending Irish-medium schools”. Only three books existed in Irish Braille for them. “With funding from the National Council for the Blind in Ireland (NCBI) a blind researcher worked with the ABAIR team to develop the NVDA screenreader plugin”. It adds Braille output through the Liblouis translator and lets users choose a male or female voice and the reading speed. The paper states “The system was extensively tested with visually-impaired school children and a full technical description is available in McGuirk (2005)”. The reference list has McGuirk 2015, an M.Phil. dissertation. It names no child, school, date or measured result and describes the voices as text-to-speech synthesis without stating the synthesis method. No source independent of the developers was found.", "replication": { "produced_by": [ "Multidialect Irish text-to-speech voices from the ABAIR initiative, funded under the 20-Year Strategy for the Irish Language", "A blind researcher co-developing the NVDA plugin with NCBI funding, with Liblouis Braille output" ], "must_hold": [ "Users and their support networks (teachers, family) are involved in design and testing, which the authors state as a guiding principle", "The free NVDA screenreader is the pupil's platform" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0031", "title": "Randomized evaluation of Google AI flood alerts with community dissemination in Bihar, India (2022–2023 monsoons)", "summary": "Bihar RCT, 319 panchayats: households relayed Google flood alerts reported 16.6% fewer illness symptoms and about 30% lower medical costs.", "date_observed": "2022-06-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Google's AI flood-forecasting system, run with India's Central Water Commission (CWC), issues riverine flood alerts as Android push notifications. In Bihar, India, economists Maulik Jagnani (Tufts) and Rohini Pande (Yale) ran a randomized evaluation across 319 panchayats in 12 flood-prone districts. It covered the 2022 and 2023 monsoon seasons (June to October). The non-governmental organization Yuganter trained community volunteers to relay the alerts. Treatment households got 2.41 more alerts in 2022 and were 46.5% more likely to get an alert before water reached their area. They reported 16.56% fewer illness symptoms and about 30% lower medical spending than controls. No specific evacuation tied to an alert is documented.", "category": "general benefit", "unexpected": false, "purpose": "The forecasting system was built to warn people of riverine floods before water arrives so they can prepare or evacuate. The measured preparedness and health effects are that intended benefit, but only at cohort level.", "system": "Google flood forecasting with Android push alerts (Google Public Alerts), plus community dissemination by Yuganter volunteers", "model_version": null, "developer": "Google", "deployer": "Central Water Commission of India with Google; last-mile dissemination by Yuganter (NGO) under the Jagnani-Pande evaluation", "location": "Bihar (twelve flood-prone districts), India", "domain": "Disaster risk reduction / flood early warning", "segment": "Rural households in riverine flood zones", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Effects are cohort averages across roughly 3.6 million people's communities (fewer illness symptoms, lower medical spending). No identifiable household with an attributable changed outcome is documented." }, { "group": "societal", "depth": null, "reason": "The study estimates population-level preparedness and health effects from a randomized design. It reports no discrete event such as a named evacuation." } ], "ai_role": { "status": "assessed", "statement": "The AI forecast generated the alerts. The randomized contrast, however, is between community dissemination of those alerts and alerts alone. So the measured effect is attributable to the dissemination of AI forecasts rather than to forecast accuracy itself. A 2019 pilot in which the only added treatment was raising alert awareness with a single local leader found no treatment impact." }, "evidence": [ { "kind": "preprint", "citation": "Jagnani M, Pande R (2024). Forecasting Fate: Experimental Evaluation of a Flood Early Warning System. Working paper, Tufts University and Yale University (Economic Growth Center), 3 April 2024.", "title": "Forecasting Fate: Experimental Evaluation of a Flood Early Warning System", "url": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "date": "2024-04-03", "written_by": "independent", "quote": "treatment households exhibiting higher adaptation and health scores and a 30% reduction in medical costs compared to control communities" }, { "kind": "report", "citation": "Abdul Latif Jameel Poverty Action Lab (J-PAL) (n.d.). Disseminating Flood Warnings to Increase Disaster Preparedness in India. Evaluation summary (PDF).", "title": "Disseminating Flood Warnings to Increase Disaster Preparedness in India", "url": "https://www.povertyactionlab.org/print/pdf/node/8026750", "date": null, "written_by": "independent", "quote": "households in treatment communities received 2.37 more alerts (a 290 percent increase) on average during the 2022 flood season (June-October)" } ], "replication": { "produced_by": [ "Google/CWC flood alerts available to all 319 study panchayats (both arms); the randomized element was volunteer dissemination", "Trained community volunteers relaying smartphone alerts in villages with low literacy and limited location-services use", "Repeated flood seasons (2022 was more intense than 2023) allowing effects to be measured" ], "must_hold": [ "Alerts reach households before water arrives (46.5% more likely in treatment communities in 2022)", "Households trust alerts despite more false positives (8.09% vs 3.64%)", "Dissemination capacity is maintained. From 2023 two volunteers per panchayat replaced three, supplemented by direct WhatsApp/SMS messages to treatment households enrolled in the 2022 endline survey." ], "echoes": [ { "date": "2023-06-01", "setting": "2023 monsoon season in the same 319 Bihar panchayats: treatment households received 4.35 more alerts and were 88% more likely to receive an alert before water reached their panchayat", "model_version": null, "outcome": "recurred", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "severity": null, "group": "societal", "basis": "Same developer and channel: Google's Android hazard alerts; flood alerts cut illness in Bihar, while the Android Earthquake Alerts system underestimated the Kahramanmaraş quake and failed to warn millions of Android users in Turkey." }, "headline": "Google flood alerts in Bihar cut reported illness by 16.6%", "metric": "16.56% fewer illness symptoms and about 30% lower medical expenditure", "comparator": { "against": "control communities, where households had access to the smartphone alerts but no community volunteers relaying them", "before": "control households (reference group)", "after": "0.36 fewer illness symptoms (a 16.56% decrease); roughly INR 6,500 less on illness treatment (a 32.87% decrease)", "basis": "measured", "quote": "Overall, treatment households observed 0.36 fewer illness symptoms (a 16.56% decrease) compared to control households (Table 4). As a result, households in treatment areas incurred roughly INR 6,500 less on illness treatment (a 32.87% decrease).", "url": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" }, "later": { "status": "unknown", "date": null, "note": "Neither cited source reports a development after the 2022-2023 evaluation seasons.", "quote": null, "url": null }, "value": { "amount": "INR 6,500", "what": "less spent on illness treatment per household over the flood season", "who": "treatment households in the Bihar study panchayats", "estimate": false, "quote": "As a result, households in treatment areas incurred roughly INR 6,500 less on illness treatment (a 32.87% decrease). In fact, based on the estimated reduction in medical expenditures alone, we estimate that for every $1 spent on the program, the intervention would generate a minimum benefit of $30 during a severe flooding season.", "url": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" }, "developer_country": "United States", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed “Flood Hub”, “Google Research” and the Kosi-river claim because neither cited source states them, and reworded the 2023 volunteer change and the 2019 pilot to match the working paper, which adds direct WhatsApp/SMS messaging in 2023 and describes the pilot's treatment as amplifying alert awareness to a single local leader.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf; https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Central_Water_Commission", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report and one independent preprint. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0031", "catalog_version": "1.0.0", "source_fingerprint": "1bfab83fdd45a0a55bd8861c4524bc8554fc9c682ab1f94bcf4c48375513c3f8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0031-source-0001", "AIBD-0031-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0031-legacy-value", "DIV-0010" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0031-legacy-value", "DIV-0010" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google", "deployer": "Central Water Commission of India with Google; last-mile dissemination by Yuganter (NGO) under the Jagnani-Pande evaluation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI forecast generated the alerts. The randomized contrast, however, is between community dissemination of those alerts and alerts alone. So the measured effect is attributable to the dissemination of AI forecasts rather than to forecast accuracy itself. A 2019 pilot in which the only added treatment was raising alert awareness with a single local leader found no treatment impact." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The AI forecast generated the alerts. The randomized contrast, however, is between community dissemination of those alerts and alerts alone. So the measured effect is attributable to the dissemination of AI forecasts rather than to forecast accuracy itself. A 2019 pilot in which the only added treatment was raising alert awareness with a single local leader found no treatment impact." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report and one independent preprint. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Effects are cohort averages across roughly 3.6 million people's communities (fewer illness symptoms, lower medical spending). No identifiable household with an attributable changed outcome is documented." }, { "group": "societal", "reason": "The study estimates population-level preparedness and health effects from a randomized design. It reports no discrete event such as a named evacuation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Effects are cohort averages across roughly 3.6 million people's communities (fewer illness symptoms, lower medical spending). No identifiable household with an attributable changed outcome is documented." }, { "group": "societal", "reason": "The study estimates population-level preparedness and health effects from a randomized design. 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The measured preparedness and health effects are that intended benefit, but only at cohort level." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Bihar (twelve flood-prone districts), India", "developer_country": "United States", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The forecasting system was built to warn people of riverine floods before water arrives so they can prepare or evacuate. The measured preparedness and health effects are that intended benefit, but only at cohort level." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-06-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed “Flood Hub”, “Google Research” and the Kosi-river claim because neither cited source states them, and reworded the 2023 volunteer change and the 2019 pilot to match the working paper, which adds direct WhatsApp/SMS messaging in 2023 and describes the pilot's treatment as amplifying alert awareness to a single local leader.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf; https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Central_Water_Commission", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Google/CWC flood alerts available to all 319 study panchayats (both arms); the randomized element was volunteer dissemination", "Trained community volunteers relaying smartphone alerts in villages with low literacy and limited location-services use", "Repeated flood seasons (2022 was more intense than 2023) allowing effects to be measured" ], "must_hold": [ "Alerts reach households before water arrives (46.5% more likely in treatment communities in 2022)", "Households trust alerts despite more false positives (8.09% vs 3.64%)", "Dissemination capacity is maintained. From 2023 two volunteers per panchayat replaced three, supplemented by direct WhatsApp/SMS messages to treatment households enrolled in the 2022 endline survey." ], "echoes": [ { "date": "2023-06-01", "setting": "2023 monsoon season in the same 319 Bihar panchayats: treatment households received 4.35 more alerts and were 88% more likely to receive an alert before water reached their panchayat", "outcome": "recurred", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Google/CWC flood alerts available to all 319 study panchayats (both arms); the randomized element was volunteer dissemination", "Trained community volunteers relaying smartphone alerts in villages with low literacy and limited location-services use", "Repeated flood seasons (2022 was more intense than 2023) allowing effects to be measured" ], "must_hold": [ "Alerts reach households before water arrives (46.5% more likely in treatment communities in 2022)", "Households trust alerts despite more false positives (8.09% vs 3.64%)", "Dissemination capacity is maintained. From 2023 two volunteers per panchayat replaced three, supplemented by direct WhatsApp/SMS messages to treatment households enrolled in the 2022 endline survey." ], "echoes": [ { "date": "2023-06-01", "setting": "2023 monsoon season in the same 319 Bihar panchayats: treatment households received 4.35 more alerts and were 88% more likely to receive an alert before water reached their panchayat", "outcome": "recurred", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed “Flood Hub”, “Google Research” and the Kosi-river claim because neither cited source states them, and reworded the 2023 volunteer change and the 2019 pilot to match the working paper, which adds direct WhatsApp/SMS messaging in 2023 and describes the pilot's treatment as amplifying alert awareness to a single local leader.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf; https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Central_Water_Commission", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Disaster risk reduction / flood early warning", "segment": "Rural households in riverine flood zones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Jagnani M, Pande R (2024). Forecasting Fate: Experimental Evaluation of a Flood Early Warning System. Working paper, Tufts University and Yale University (Economic Growth Center), 3 April 2024.", "title": "Forecasting Fate: Experimental Evaluation of a Flood Early Warning System", "url": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "date": "2024-04-03", "written_by": "independent", "quote": "treatment households exhibiting higher adaptation and health scores and a 30% reduction in medical costs compared to control communities" }, { "kind": "report", "citation": "Abdul Latif Jameel Poverty Action Lab (J-PAL) (n.d.). Disseminating Flood Warnings to Increase Disaster Preparedness in India. Evaluation summary (PDF).", "title": "Disseminating Flood Warnings to Increase Disaster Preparedness in India", "url": "https://www.povertyactionlab.org/print/pdf/node/8026750", "written_by": "independent", "quote": "households in treatment communities received 2.37 more alerts (a 290 percent increase) on average during the 2022 flood season (June-October)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0031-source-0001", "AIBD-0031-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Jagnani M, Pande R (2024). Forecasting Fate: Experimental Evaluation of a Flood Early Warning System. Working paper, Tufts University and Yale University (Economic Growth Center), 3 April 2024.", "title": "Forecasting Fate: Experimental Evaluation of a Flood Early Warning System", "url": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf", "date": "2024-04-03", "written_by": "independent", "quote": "treatment households exhibiting higher adaptation and health scores and a 30% reduction in medical costs compared to control communities" }, { "kind": "report", "citation": "Abdul Latif Jameel Poverty Action Lab (J-PAL) (n.d.). Disseminating Flood Warnings to Increase Disaster Preparedness in India. Evaluation summary (PDF).", "title": "Disseminating Flood Warnings to Increase Disaster Preparedness in India", "url": "https://www.povertyactionlab.org/print/pdf/node/8026750", "written_by": "independent", "quote": "households in treatment communities received 2.37 more alerts (a 290 percent increase) on average during the 2022 flood season (June-October)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Bihar RCT, 319 panchayats: households relayed Google flood alerts reported 16.6% fewer illness symptoms and about 30% lower medical costs.", "account": "Google's AI flood-forecasting system, run with India's Central Water Commission (CWC), issues riverine flood alerts as Android push notifications. In Bihar, India, economists Maulik Jagnani (Tufts) and Rohini Pande (Yale) ran a randomized evaluation across 319 panchayats in 12 flood-prone districts. It covered the 2022 and 2023 monsoon seasons (June to October). The non-governmental organization Yuganter trained community volunteers to relay the alerts. Treatment households got 2.41 more alerts in 2022 and were 46.5% more likely to get an alert before water reached their area. They reported 16.56% fewer illness symptoms and about 30% lower medical spending than controls. No specific evacuation tied to an alert is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Google flood forecasting with Android push alerts (Google Public Alerts), plus community dissemination by Yuganter volunteers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Randomized evaluation of Google AI flood alerts with community dissemination in Bihar, India (2022–2023 monsoons)", "headline": "Google flood alerts in Bihar cut reported illness by 16.6%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1bfab83fdd45a0a55bd8861c4524bc8554fc9c682ab1f94bcf4c48375513c3f8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Google's AI flood-forecasting system, run with India's Central Water Commission (CWC), issues riverine flood alerts as Android push notifications. In Bihar, India, economists Maulik Jagnani (Tufts) and Rohini Pande (Yale) ran a randomized evaluation across 319 panchayats in 12 flood-prone districts. It covered the 2022 and 2023 monsoon seasons (June to October). The non-governmental organization Yuganter trained community volunteers to relay the alerts. Treatment households got 2.41 more alerts in 2022 and were 46.5% more likely to get an alert before water reached their area. They reported 16.56% fewer illness symptoms and about 30% lower medical spending than controls. No specific evacuation tied to an alert is documented.", "replication": { "produced_by": [ "Google/CWC flood alerts available to all 319 study panchayats (both arms); the randomized element was volunteer dissemination", "Trained community volunteers relaying smartphone alerts in villages with low literacy and limited location-services use", "Repeated flood seasons (2022 was more intense than 2023) allowing effects to be measured" ], "must_hold": [ "Alerts reach households before water arrives (46.5% more likely in treatment communities in 2022)", "Households trust alerts despite more false positives (8.09% vs 3.64%)", "Dissemination capacity is maintained. From 2023 two volunteers per panchayat replaced three, supplemented by direct WhatsApp/SMS messages to treatment households enrolled in the 2022 endline survey." ], "echoes": [ { "date": "2023-06-01", "setting": "2023 monsoon season in the same 319 Bihar panchayats: treatment households received 4.35 more alerts and were 88% more likely to receive an alert before water reached their panchayat", "outcome": "recurred", "source": "https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/2986/files/2024/04/Google_Floods-bcdf49042e23059a.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 38, "reviewed": 0, "record_mapped": 38, "not_assessed": 53, "complete": false, "by_state": { "value_present": 38, "not_reported": 0, "unresolved": 0, "not_assessed": 53, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0069", "title": "From Numbers to Names facial recognition identifies Geddy Lee's mother in a Bergen-Belsen DP-camp photograph", "summary": "N2N face search found Geddy Lee's mother in a Bergen-Belsen DP-camp photo; Lee confirmed it and found more family photos at Yad Vashem", "date_observed": "2022-06-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "From Numbers to Names (N2N) is a facial-recognition search built by software engineer Daniel Patt. It indexes roughly half a million digitized Holocaust-era photographs from the US Holocaust Memorial Museum (USHMM) and Yad Vashem. The Times of Israel reported on 26 June 2022 (report date; identification date not given) that the tool surfaced a photograph of Mary Weinrib. She was an Auschwitz survivor and mother of Rush musician Geddy Lee, at the Bergen-Belsen displaced-persons camp. Lee confirmed the identification and then located further photographs of his mother's extended family in the Yad Vashem collection (Jerusalem Post, 28 June 2022). On 19 December 2022 NPR reported a second case: survivor Blanche Fixler recognized herself, her aunt and her cousin in photographs found with the tool.", "category": "benefit created", "unexpected": false, "purpose": "Identify unnamed faces in Holocaust-era photo and video archives and help descendants find images of relatives", "system": "From Numbers to Names (N2N) facial-recognition search", "model_version": null, "developer": "Daniel Patt (independent project; N2N volunteer team)", "deployer": "From Numbers to Names (numberstonames.org)", "location": null, "domain": "History and archives", "segment": "Holocaust archives and family history", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Material to a family: Lee confirmed a previously unknown photograph of his mother at Bergen-Belsen. He found photographs of her extended family (Times of Israel, Jerusalem Post). Fixler found images of herself, her aunt and cousin (NPR)" }, { "group": "organizational", "depth": 1, "reason": "Small gain for archives: an anonymous Yad Vashem photograph acquired an identification, but the sources record no formal archival update" }, { "group": "societal", "depth": 1, "reason": "Small: two documented identifications among millions of unidentified faces indexed, per the sources" } ], "ai_role": { "status": "assessed", "statement": "The face-similarity search surfaced the candidate photograph. The identification was confirmed by a family member (Lee) or by the survivor herself (Fixler), not by the archive. The further Yad Vashem family photographs were found by Lee following the lead. No archive statement confirming the identification is among the sources." }, "evidence": [ { "kind": "news report", "citation": "The Times of Israel (2022). Google engineer identifies anonymous faces in WWII photos with AI facial recognition. The Times of Israel.", "title": "Google engineer identifies anonymous faces in WWII photos with AI facial recognition", "url": "https://www.timesofisrael.com/google-engineer-identifies-anonymous-faces-in-wwii-photos-with-ai-facial-recognition/", "date": "2022-06-26", "written_by": "independent", "quote": "He was able to confirm this was indeed a photo of her at the displaced persons camp at Bergen-Belsen" }, { "kind": "news report", "citation": "The Jerusalem Post (2022). AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos. The Jerusalem Post.", "title": "AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos", "url": "https://www.jpost.com/business-and-innovation/tech-and-start-ups/article-710634", "date": "2022-06-28", "written_by": "independent", "quote": "researchers of the AI technology, From Numbers to Names, managed to find a photo of Weinrib from her time at the displaced person camp in Bergen-Belsen" }, { "kind": "news report", "citation": "NPR (2022). Artificial Intelligence helped connect a Holocaust survivor with photos of her past. NPR.", "title": "Artificial Intelligence helped connect a Holocaust survivor with photos of her past", "url": "https://text.npr.org/1144230135", "date": "2022-12-19", "written_by": "independent", "quote": "I recognized myself. And my aunt was there and my cousin and a few other people that I recognized." }, { "kind": "press release", "citation": "From Numbers to Names (n.d.). Home page. numberstonames.org.", "title": "From Numbers to Names", "url": "https://numberstonames.org/", "date": null, "written_by": "makers", "quote": "From Numbers to Names provides a new way to explore Holocaust photo and video archives through AI." } ], "replication": { "produced_by": [ "Face-embedding similarity search over about half a million digitized USHMM and Yad Vashem photographs", "A reference photograph of the relative supplied by the family", "Human confirmation by a family member or the survivor" ], "must_hold": [ "The archive photographs are digitized and indexed by the tool", "The relative's face appears in an indexed photograph", "A living relative or survivor can recognize and confirm the match" ], "echoes": [ { "date": "2022-12-19", "setting": "Holocaust survivor Blanche Fixler, photographs found via N2N after Patt searched using a photo from Twitter", "model_version": null, "outcome": "recurred", "source": "https://text.npr.org/1144230135" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "109", "title": "PimEyes's Facial Recognition AI Allegedly Lacked Safeguards to Prevent Itself from Being Abused", "url": "https://incidentdatabase.ai/cite/109", "severity": null, "group": "personal", "basis": "Same kind of system and task, a public facial-image search engine matching a face across a photo corpus: PimEyes lacked safeguards against misuse such as stalking, harming private individuals and their privacy." }, "headline": "N2N face search finds Geddy Lee's mother in Bergen-Belsen photo", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2022-12-19", "note": "Six months after the Geddy Lee identification, NPR reported a further identification made with the tool: survivor Blanche Fixler recognized herself, her aunt and her cousin.", "quote": "I recognized myself. 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severity not given by the source.", "source": "https://incidentdatabase.ai/cite/109", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://text.npr.org/1144230135", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://numberstonames.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Face-embedding similarity search over about half a million digitized USHMM and Yad Vashem photographs", "A reference photograph of the relative supplied by the family", "Human confirmation by a family member or the survivor" ], "must_hold": [ "The archive photographs are digitized and indexed by the tool", "The relative's face appears in an indexed photograph", "A living relative or survivor can recognize and confirm the match" ], "echoes": [ { "date": "2022-12-19", "setting": "Holocaust survivor Blanche Fixler, photographs found via N2N after Patt searched using a photo from Twitter", "outcome": "recurred", "source": "https://text.npr.org/1144230135" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 109 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/109", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://text.npr.org/1144230135", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://numberstonames.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "History and archives", "segment": "Holocaust archives and family history" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Times of Israel (2022). Google engineer identifies anonymous faces in WWII photos with AI facial recognition. The Times of Israel.", "title": "Google engineer identifies anonymous faces in WWII photos with AI facial recognition", "url": "https://www.timesofisrael.com/google-engineer-identifies-anonymous-faces-in-wwii-photos-with-ai-facial-recognition/", "date": "2022-06-26", "written_by": "independent", "quote": "He was able to confirm this was indeed a photo of her at the displaced persons camp at Bergen-Belsen" }, { "kind": "news report", "citation": "The Jerusalem Post (2022). AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos. The Jerusalem Post.", "title": "AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos", "url": "https://www.jpost.com/business-and-innovation/tech-and-start-ups/article-710634", "date": "2022-06-28", "written_by": "independent", "quote": "researchers of the AI technology, From Numbers to Names, managed to find a photo of Weinrib from her time at the displaced person camp in Bergen-Belsen" }, { "kind": "news report", "citation": "NPR (2022). Artificial Intelligence helped connect a Holocaust survivor with photos of her past. NPR.", "title": "Artificial Intelligence helped connect a Holocaust survivor with photos of her past", "url": "https://text.npr.org/1144230135", "date": "2022-12-19", "written_by": "independent", "quote": "I recognized myself. And my aunt was there and my cousin and a few other people that I recognized." }, { "kind": "press release", "citation": "From Numbers to Names (n.d.). Home page. numberstonames.org.", "title": "From Numbers to Names", "url": "https://numberstonames.org/", "written_by": "makers", "quote": "From Numbers to Names provides a new way to explore Holocaust photo and video archives through AI." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0069-source-0001", "AIBD-0069-source-0002", "AIBD-0069-source-0003", "AIBD-0069-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Times of Israel (2022). Google engineer identifies anonymous faces in WWII photos with AI facial recognition. The Times of Israel.", "title": "Google engineer identifies anonymous faces in WWII photos with AI facial recognition", "url": "https://www.timesofisrael.com/google-engineer-identifies-anonymous-faces-in-wwii-photos-with-ai-facial-recognition/", "date": "2022-06-26", "written_by": "independent", "quote": "He was able to confirm this was indeed a photo of her at the displaced persons camp at Bergen-Belsen" }, { "kind": "news report", "citation": "The Jerusalem Post (2022). AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos. The Jerusalem Post.", "title": "AI facial recognition tech identifies rocker Geddy Lee's mother in anonymous Holocaust photos", "url": "https://www.jpost.com/business-and-innovation/tech-and-start-ups/article-710634", "date": "2022-06-28", "written_by": "independent", "quote": "researchers of the AI technology, From Numbers to Names, managed to find a photo of Weinrib from her time at the displaced person camp in Bergen-Belsen" }, { "kind": "news report", "citation": "NPR (2022). Artificial Intelligence helped connect a Holocaust survivor with photos of her past. NPR.", "title": "Artificial Intelligence helped connect a Holocaust survivor with photos of her past", "url": "https://text.npr.org/1144230135", "date": "2022-12-19", "written_by": "independent", "quote": "I recognized myself. And my aunt was there and my cousin and a few other people that I recognized." }, { "kind": "press release", "citation": "From Numbers to Names (n.d.). Home page. numberstonames.org.", "title": "From Numbers to Names", "url": "https://numberstonames.org/", "written_by": "makers", "quote": "From Numbers to Names provides a new way to explore Holocaust photo and video archives through AI." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "N2N face search found Geddy Lee's mother in a Bergen-Belsen DP-camp photo; Lee confirmed it and found more family photos at Yad Vashem", "account": "From Numbers to Names (N2N) is a facial-recognition search built by software engineer Daniel Patt. It indexes roughly half a million digitized Holocaust-era photographs from the US Holocaust Memorial Museum (USHMM) and Yad Vashem. The Times of Israel reported on 26 June 2022 (report date; identification date not given) that the tool surfaced a photograph of Mary Weinrib. She was an Auschwitz survivor and mother of Rush musician Geddy Lee, at the Bergen-Belsen displaced-persons camp. Lee confirmed the identification and then located further photographs of his mother's extended family in the Yad Vashem collection (Jerusalem Post, 28 June 2022). On 19 December 2022 NPR reported a second case: survivor Blanche Fixler recognized herself, her aunt and her cousin in photographs found with the tool." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "From Numbers to Names (N2N) facial-recognition search" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Daniel Patt (independent project; N2N volunteer team)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "From Numbers to Names facial recognition identifies Geddy Lee's mother in a Bergen-Belsen DP-camp photograph", "headline": "N2N face search finds Geddy Lee's mother in Bergen-Belsen photo" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3f74741e64fe998f85884f4f38a5ee3dae3d3f0b198676c747cd2f3d8a8f1792" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "From Numbers to Names (N2N) is a facial-recognition search built by software engineer Daniel Patt. It indexes roughly half a million digitized Holocaust-era photographs from the US Holocaust Memorial Museum (USHMM) and Yad Vashem. The Times of Israel reported on 26 June 2022 (report date; identification date not given) that the tool surfaced a photograph of Mary Weinrib. She was an Auschwitz survivor and mother of Rush musician Geddy Lee, at the Bergen-Belsen displaced-persons camp. Lee confirmed the identification and then located further photographs of his mother's extended family in the Yad Vashem collection (Jerusalem Post, 28 June 2022). On 19 December 2022 NPR reported a second case: survivor Blanche Fixler recognized herself, her aunt and her cousin in photographs found with the tool.", "replication": { "produced_by": [ "Face-embedding similarity search over about half a million digitized USHMM and Yad Vashem photographs", "A reference photograph of the relative supplied by the family", "Human confirmation by a family member or the survivor" ], "must_hold": [ "The archive photographs are digitized and indexed by the tool", "The relative's face appears in an indexed photograph", "A living relative or survivor can recognize and confirm the match" ], "echoes": [ { "date": "2022-12-19", "setting": "Holocaust survivor Blanche Fixler, photographs found via N2N after Patt searched using a photo from Twitter", "outcome": "recurred", "source": "https://text.npr.org/1144230135" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0182", "title": "Italy's Agenzia delle Entrate activates the VeRa risk-analysis algorithm under a June 2022 decree", "summary": "VeRa (Verifica dei Rapporti Finanziari) cross-matches the financial-relationships archive with tax data under pseudonymisation to build selective lists of high-risk taxpayers; no realized outcome f...", "date_observed": "2022-06-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Agenda Digitale (Denaura Bordandini and Massimo Borgobello, 29 July 2022) described VeRa, “verifica dei rapporti finanziari”. It called it a new AI-based application to help Agenzia delle Entrate officials fight tax evasion. It cross-matches the Archivio dei Rapporti Finanziari with other tax-registry information. The Garante per la protezione dei dati personali required anonymized preliminary analysis, data minimization and deletion after the second year following assessment. Fiscomania (Elisa Migliorini, 15 May 2026) states that the algorithm became operative under the ministerial decree of 28 June 2022. The decree was adopted after hearing the Garante and the Agenzia. Its legal basis is Law 160/2019 article 1 paragraphs 681–686. It is run by the Settore Analisi del rischio of the Divisione Contribuenti. It produces selective lists of taxpayers at higher fiscal risk by crossing financial-relationship, declaration, asset and electronic-payment data. Taxpayers are handled under an anonymous code during the preliminary phase. Fiscomania gives only PNRR targets for 2022 (2,581,090 communications, 2.45 billion euro expected receipts, 5% fewer false positives than 2019), not results.", "category": "general benefit", "unexpected": false, "purpose": "Build selective lists of taxpayers at higher fiscal risk by cross-matching financial-relationship data with tax declarations.", "system": "Ve.R.A. (Verifica dei Rapporti Finanziari)", "model_version": null, "developer": "Agenzia delle Entrate, Settore Analisi del rischio, Divisione Contribuenti (no vendor named)", "deployer": "Agenzia delle Entrate", "location": null, "domain": "Tax compliance", "segment": "Risk analysis for tax evasion", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The announcement describes audit targeting, with no flagged positions or sums recovered documented.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No realized output of the algorithm is documented." }, { "group": "societal", "depth": null, "reason": "No recovered revenue attributable to VeRa is documented." } ], "ai_role": { "status": "unassessed", "statement": "Agenda Digitale calls the application AI-based and Fiscomania describes risk analysis over cross-matched data. Neither gives the technique or any result, so the algorithm's contribution cannot be assessed. The Agenzia both runs and, as far as the sources show, operates the system in-house." }, "evidence": [ { "kind": "news report", "citation": "Denaura Bordandini and Massimo Borgobello, Agenda Digitale, 29 July 2022", "title": "Vera, l'AI al servizio dell'Agenzia delle entrate: come funziona l'algoritmo anti evasione", "url": "https://www.agendadigitale.eu/documenti/vera-lai-al-servizio-dellagenzia-delle-entrate-come-funziona-lalgoritmo-anti-evasione/", "date": "2022-07-29", "written_by": "independent", "quote": "un nuovo applicativo, basato sull'intelligenza artificiale, che coadiuverà i funzionari dell'Agenzia delle Entrate (ADE) nella lotta all'evasione fiscale." }, { "kind": "other", "citation": "Elisa Migliorini, Fiscomania, 15 May 2026", "title": "Ve.R.A.: come funziona il sistema di analisi del rischio fiscale dell'Agenzia delle Entrate", "url": "https://fiscomania.com/algoritmo-anti-evasione/", "date": "2026-05-15", "written_by": "independent", "quote": "liste selettive di contribuenti a più elevato rischio fiscale" } ], "replication": { "produced_by": [ "A legal basis (Law 160/2019 and the decree of 28 June 2022) permitting cross-matching of the financial-relationships archive with tax data under Garante safeguards" ], "must_hold": [ "Access to the Archivio dei Rapporti Finanziari", "Pseudonymization during preliminary analysis and retention limits set by the Garante" ], "echoes": [] }, "paired_incident": null, "headline": "Agenzia delle Entrate activates VeRa to list high-risk taxpayers", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The May 2026 Fiscomania guide describes Ve.R.A. as operative under the June 2022 decree but reports no results or later decree; no dated development was found.", "quote": null, "url": null }, "value": null, "developer_country": "Italy", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Agenzia_delle_Entrate; https://en.wikipedia.org/wiki/Agenzia_delle_Entrate", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0182", "catalog_version": "1.0.0", "source_fingerprint": "dc2f5d85d5c068fc267c44d3eeff4e3d5ac0000a4ad39dd5a90668b16bf71c32", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0182-source-0001", "AIBD-0182-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Agenzia delle Entrate, Settore Analisi del rischio, Divisione Contribuenti (no vendor named)", "deployer": "Agenzia delle Entrate" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Agenda Digitale calls the application AI-based and Fiscomania describes risk analysis over cross-matched data. Neither gives the technique or any result, so the algorithm's contribution cannot be assessed. The Agenzia both runs and, as far as the sources show, operates the system in-house." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No realized output of the algorithm is documented." }, { "group": "societal", "reason": "No recovered revenue attributable to VeRa is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No realized output of the algorithm is documented." }, { "group": "societal", "reason": "No recovered revenue attributable to VeRa is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The May 2026 Fiscomania guide describes Ve.R.A. as operative under the June 2022 decree but reports no results or later decree; no dated development was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0182" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The announcement describes audit targeting, with no flagged positions or sums recovered documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Agenda Digitale (Denaura Bordandini and Massimo Borgobello, 29 July 2022) described VeRa, “verifica dei rapporti finanziari”. It called it a new AI-based application to help Agenzia delle Entrate officials fight tax evasion. It cross-matches the Archivio dei Rapporti Finanziari with other tax-registry information. The Garante per la protezione dei dati personali required anonymized preliminary analysis, data minimization and deletion after the second year following assessment. Fiscomania (Elisa Migliorini, 15 May 2026) states that the algorithm became operative under the ministerial decree of 28 June 2022. The decree was adopted after hearing the Garante and the Agenzia. Its legal basis is Law 160/2019 article 1 paragraphs 681–686. It is run by the Settore Analisi del rischio of the Divisione Contribuenti. It produces selective lists of taxpayers at higher fiscal risk by crossing financial-relationship, declaration, asset and electronic-payment data. Taxpayers are handled under an anonymous code during the preliminary phase. Fiscomania gives only PNRR targets for 2022 (2,581,090 communications, 2.45 billion euro expected receipts, 5% fewer false positives than 2019), not results.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No realized output of the algorithm is documented." }, { "group": "societal", "reason": "No recovered revenue attributable to VeRa is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Build selective lists of taxpayers at higher fiscal risk by cross-matching financial-relationship data with tax declarations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Italy", "deployer_country": "Italy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Build selective lists of taxpayers at higher fiscal risk by cross-matching financial-relationship data with tax declarations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-06-28", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Agenzia_delle_Entrate; https://en.wikipedia.org/wiki/Agenzia_delle_Entrate", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A legal basis (Law 160/2019 and the decree of 28 June 2022) permitting cross-matching of the financial-relationships archive with tax data under Garante safeguards" ], "must_hold": [ "Access to the Archivio dei Rapporti Finanziari", "Pseudonymization during preliminary analysis and retention limits set by the Garante" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Agenzia_delle_Entrate; https://en.wikipedia.org/wiki/Agenzia_delle_Entrate", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Tax compliance", "segment": "Risk analysis for tax evasion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Denaura Bordandini and Massimo Borgobello, Agenda Digitale, 29 July 2022", "title": "Vera, l'AI al servizio dell'Agenzia delle entrate: come funziona l'algoritmo anti evasione", "url": "https://www.agendadigitale.eu/documenti/vera-lai-al-servizio-dellagenzia-delle-entrate-come-funziona-lalgoritmo-anti-evasione/", "date": "2022-07-29", "written_by": "independent", "quote": "un nuovo applicativo, basato sull'intelligenza artificiale, che coadiuverà i funzionari dell'Agenzia delle Entrate (ADE) nella lotta all'evasione fiscale." }, { "kind": "other", "citation": "Elisa Migliorini, Fiscomania, 15 May 2026", "title": "Ve.R.A.: come funziona il sistema di analisi del rischio fiscale dell'Agenzia delle Entrate", "url": "https://fiscomania.com/algoritmo-anti-evasione/", "date": "2026-05-15", "written_by": "independent", "quote": "liste selettive di contribuenti a più elevato rischio fiscale" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0182-source-0001", "AIBD-0182-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Denaura Bordandini and Massimo Borgobello, Agenda Digitale, 29 July 2022", "title": "Vera, l'AI al servizio dell'Agenzia delle entrate: come funziona l'algoritmo anti evasione", "url": "https://www.agendadigitale.eu/documenti/vera-lai-al-servizio-dellagenzia-delle-entrate-come-funziona-lalgoritmo-anti-evasione/", "date": "2022-07-29", "written_by": "independent", "quote": "un nuovo applicativo, basato sull'intelligenza artificiale, che coadiuverà i funzionari dell'Agenzia delle Entrate (ADE) nella lotta all'evasione fiscale." }, { "kind": "other", "citation": "Elisa Migliorini, Fiscomania, 15 May 2026", "title": "Ve.R.A.: come funziona il sistema di analisi del rischio fiscale dell'Agenzia delle Entrate", "url": "https://fiscomania.com/algoritmo-anti-evasione/", "date": "2026-05-15", "written_by": "independent", "quote": "liste selettive di contribuenti a più elevato rischio fiscale" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "VeRa (Verifica dei Rapporti Finanziari) cross-matches the financial-relationships archive with tax data under pseudonymisation to build selective lists of high-risk taxpayers; no realized outcome f...", "account": "Agenda Digitale (Denaura Bordandini and Massimo Borgobello, 29 July 2022) described VeRa, “verifica dei rapporti finanziari”. It called it a new AI-based application to help Agenzia delle Entrate officials fight tax evasion. It cross-matches the Archivio dei Rapporti Finanziari with other tax-registry information. The Garante per la protezione dei dati personali required anonymized preliminary analysis, data minimization and deletion after the second year following assessment. Fiscomania (Elisa Migliorini, 15 May 2026) states that the algorithm became operative under the ministerial decree of 28 June 2022. The decree was adopted after hearing the Garante and the Agenzia. Its legal basis is Law 160/2019 article 1 paragraphs 681–686. It is run by the Settore Analisi del rischio of the Divisione Contribuenti. It produces selective lists of taxpayers at higher fiscal risk by crossing financial-relationship, declaration, asset and electronic-payment data. Taxpayers are handled under an anonymous code during the preliminary phase. Fiscomania gives only PNRR targets for 2022 (2,581,090 communications, 2.45 billion euro expected receipts, 5% fewer false positives than 2019), not results." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Ve.R.A. (Verifica dei Rapporti Finanziari)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Agenzia delle Entrate, Settore Analisi del rischio, Divisione Contribuenti (no vendor named)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Italy's Agenzia delle Entrate activates the VeRa risk-analysis algorithm under a June 2022 decree", "headline": "Agenzia delle Entrate activates VeRa to list high-risk taxpayers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "dc2f5d85d5c068fc267c44d3eeff4e3d5ac0000a4ad39dd5a90668b16bf71c32" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Agenda Digitale (Denaura Bordandini and Massimo Borgobello, 29 July 2022) described VeRa, “verifica dei rapporti finanziari”. It called it a new AI-based application to help Agenzia delle Entrate officials fight tax evasion. It cross-matches the Archivio dei Rapporti Finanziari with other tax-registry information. The Garante per la protezione dei dati personali required anonymized preliminary analysis, data minimization and deletion after the second year following assessment. Fiscomania (Elisa Migliorini, 15 May 2026) states that the algorithm became operative under the ministerial decree of 28 June 2022. The decree was adopted after hearing the Garante and the Agenzia. Its legal basis is Law 160/2019 article 1 paragraphs 681–686. It is run by the Settore Analisi del rischio of the Divisione Contribuenti. It produces selective lists of taxpayers at higher fiscal risk by crossing financial-relationship, declaration, asset and electronic-payment data. Taxpayers are handled under an anonymous code during the preliminary phase. Fiscomania gives only PNRR targets for 2022 (2,581,090 communications, 2.45 billion euro expected receipts, 5% fewer false positives than 2019), not results.", "replication": { "produced_by": [ "A legal basis (Law 160/2019 and the decree of 28 June 2022) permitting cross-matching of the financial-relationships archive with tax data under Garante safeguards" ], "must_hold": [ "Access to the Archivio dei Rapporti Finanziari", "Pseudonymization during preliminary analysis and retention limits set by the Garante" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0068", "title": "Imagene AI infers EGFR mutation from an H&E slide, letting a woman with leptomeningeal lung cancer start osimertinib two days after biopsy and avoid neuraxis radiotherapy", "summary": "Imagene AI predicted EGFR from an H&E slide in <48 h; rapid PCR confirmed; osimertinib began 2 days post-biopsy, no neuraxis radiotherapy.", "date_observed": "2022-07-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In July 2022 a healthy woman in her early 40s was admitted to Tel Aviv Sourasky Medical Center, Israel. She had a month of worsening headaches. Imaging showed a 2.6 cm left apical lung adenocarcinoma with leptomeningeal spread; biopsy tissue was scarce. To guide gene testing without exhausting tissue, the team ran Imagene's deep-learning algorithm on the H&E slide. Within 48 hours of biopsy it inferred EGFR mutation positivity. A rapid Idylla PCR assay confirmed the L858R exon 21 mutation; osimertinib started two days after biopsy. The authors say that was one week earlier than routine practice and avoided whole-neuraxis radiotherapy. Magnetic resonance imaging (MRI) at two months showed the enhancement gone.", "category": "benefit created", "unexpected": false, "purpose": "Imagene's algorithm is built to infer genomic alteration status from routine pathology slides in order to direct molecular testing; this benefit is its intended function.", "system": "Imagene AI (H&E-based molecular inference)", "model_version": null, "developer": "Imagene", "deployer": "Tel Aviv Sourasky Medical Center", "location": "Tel Aviv, Israel", "domain": "Healthcare - oncology / molecular pathology", "segment": "AI-guided biomarker testing in non-small-cell lung cancer", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Targeted therapy for leptomeningeal disease started a week earlier and whole-neuraxis radiotherapy was avoided, with MRI improvement at two months. Survival benefit is not reported." }, { "group": "organizational", "depth": 1, "reason": "The slide-based inference let the team choose a single rapid PCR test instead of waiting for sequencing on limited tissue." } ], "ai_role": { "status": "assessed", "statement": "The AI inference directed which rapid test to run; treatment began only after PCR confirmation. The AI therefore changed the sequence and speed of testing rather than the final diagnosis. Authors are Tel Aviv Sourasky / Tel Aviv University clinicians declaring no competing interests. A second patient in the report (February 2023) followed the same path." }, "evidence": [ { "kind": "case report", "citation": "Waissengrin B, Garasimov A, Bainhoren O, Merimsky O, Shamai S, Erental A, Wolf I, Hershkovitz D (2023). Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report. Journal of Clinical Pathology 76(11):790-792.", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "date": null, "written_by": "deployer", "quote": "The algorithmic inference identified positivity for EGFR mutation." }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (second quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "date": null, "written_by": "deployer", "quote": "The incorporation of the AI solution not only enabled targeted treatment 1 week earlier than in the routine practice" }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (third quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "date": null, "written_by": "deployer", "quote": "resulted in avoiding altogether whole neuroaxis radiotherapy" } ], "replication": { "produced_by": [ "Scanning the diagnostic H&E slide and running the inference within 48 hours of biopsy", "A rapid single-gene PCR assay available for confirmation" ], "must_hold": [ "PCR or sequencing confirmation before treatment", "A tumor with a targetable driver the model can infer" ], "echoes": [ { "date": "2023-02-01", "setting": "Second woman in her early 40s with EGFR-mutant NSCLC at the same center, February 2023; same AI-guided path, MRI improvement at two months", "model_version": null, "outcome": "recurred", "source": "Waissengrin B et al. (2023) J Clin Pathol 76(11):790-792, https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "225", "title": "IBM Watson for Oncology Criticized by Customers for Allegedly Unsafe and Inaccurate Cancer Treatment Recommendations", "url": "https://incidentdatabase.ai/cite/225", "severity": null, "group": "personal", "basis": "Same domain and task, AI decision support steering cancer treatment: Watson for Oncology gave allegedly unsafe and incorrect treatment recommendations, harming cancer patients and oncologists, the groups Imagene's EGFR inference served." }, "headline": "Imagene AI infers EGFR from H&E; osimertinib 2 days post-biopsy", "metric": "one week earlier than routine practice and avoided whole-neuraxis radiotherapy", "comparator": { "against": "routine practice, in which comprehensive genomic profiling precedes targeted therapy", "before": "CGP is time-consuming, with the time for diagnosis reaching up to 4 weeks", "after": "targeted treatment 1 week earlier than in the routine practice; osimertinib given 2 days after the biopsy", "basis": "assumed", "quote": "The incorporation of the AI solution not only enabled targeted treatment 1 week earlier than in the routine practice but also resulted in avoiding altogether whole neuroaxis radiotherapy.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" }, "later": { "status": "persisted", "date": null, "note": "MRI two months after osimertinib began (exact date not given) showed disappearance of the leptomeningeal enhancement in this patient and in the second patient.", "quote": "Both patients' MRI scans after 2 months of TKI showed significant improvement with disappearance of the enhancement.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" }, "value": null, "developer_country": "Israel", "deployer_country": "Israel", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 225 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/225", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/; https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://imagene-ai.com/privacy-policy/; https://en.wikipedia.org/wiki/Tel_Aviv_Sourasky_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0068", "catalog_version": "1.0.0", "source_fingerprint": "f95325356bf6185ad2551e47258c9cbba0b69a755721dbb9d46c0bafd1aac5bd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0068-source-0001", "AIBD-0068-source-0002", "AIBD-0068-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Imagene", "deployer": "Tel Aviv Sourasky Medical Center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI inference directed which rapid test to run; treatment began only after PCR confirmation. The AI therefore changed the sequence and speed of testing rather than the final diagnosis. Authors are Tel Aviv Sourasky / Tel Aviv University clinicians declaring no competing interests. A second patient in the report (February 2023) followed the same path." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI inference directed which rapid test to run; treatment began only after PCR confirmation. The AI therefore changed the sequence and speed of testing rather than the final diagnosis. Authors are Tel Aviv Sourasky / Tel Aviv University clinicians declaring no competing interests. A second patient in the report (February 2023) followed the same path." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Targeted therapy for leptomeningeal disease started a week earlier and whole-neuraxis radiotherapy was avoided, with MRI improvement at two months. Survival benefit is not reported." }, { "group": "organizational", "depth": 1, "reason": "The slide-based inference let the team choose a single rapid PCR test instead of waiting for sequencing on limited tissue." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Targeted therapy for leptomeningeal disease started a week earlier and whole-neuraxis radiotherapy was avoided, with MRI improvement at two months. Survival benefit is not reported." }, { "group": "organizational", "depth": 1, "reason": "The slide-based inference let the team choose a single rapid PCR test instead of waiting for sequencing on limited tissue." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Targeted therapy for leptomeningeal disease started a week earlier and whole-neuraxis radiotherapy was avoided, with MRI improvement at two months. Survival benefit is not reported." }, { "group": "organizational", "depth": 1, "reason": "The slide-based inference let the team choose a single rapid PCR test instead of waiting for sequencing on limited tissue." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same domain and task, AI decision support steering cancer treatment: Watson for Oncology gave allegedly unsafe and incorrect treatment 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"coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "one week earlier than routine practice and avoided whole-neuraxis radiotherapy", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "225", "title": "IBM Watson for Oncology Criticized by Customers for Allegedly Unsafe and Inaccurate Cancer Treatment Recommendations", "url": "https://incidentdatabase.ai/cite/225", "group": "personal", "basis": "Same domain and task, AI decision support steering cancer treatment: Watson for Oncology gave allegedly unsafe and incorrect treatment recommendations, harming cancer patients and oncologists, the groups Imagene's EGFR inference served." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "note": "MRI two months after osimertinib began (exact date not given) showed disappearance of the leptomeningeal enhancement in this patient and in the second patient.", "quote": "Both patients' MRI scans after 2 months of TKI showed significant improvement with disappearance of the enhancement.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0068" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In July 2022 a healthy woman in her early 40s was admitted to Tel Aviv Sourasky Medical Center, Israel. She had a month of worsening headaches. Imaging showed a 2.6 cm left apical lung adenocarcinoma with leptomeningeal spread; biopsy tissue was scarce. To guide gene testing without exhausting tissue, the team ran Imagene's deep-learning algorithm on the H&E slide. Within 48 hours of biopsy it inferred EGFR mutation positivity. A rapid Idylla PCR assay confirmed the L858R exon 21 mutation; osimertinib started two days after biopsy. The authors say that was one week earlier than routine practice and avoided whole-neuraxis radiotherapy. Magnetic resonance imaging (MRI) at two months showed the enhancement gone.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Targeted therapy for leptomeningeal disease started a week earlier and whole-neuraxis radiotherapy was avoided, with MRI improvement at two months. Survival benefit is not reported." }, { "group": "organizational", "depth": 1, "reason": "The slide-based inference let the team choose a single rapid PCR test instead of waiting for sequencing on limited tissue." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Imagene's algorithm is built to infer genomic alteration status from routine pathology slides in order to direct molecular testing; this benefit is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Tel Aviv, Israel", "developer_country": "Israel", "deployer_country": "Israel" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Imagene's algorithm is built to infer genomic alteration status from routine pathology slides in order to direct molecular testing; this benefit is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-07-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 225 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/225", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/; https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://imagene-ai.com/privacy-policy/; https://en.wikipedia.org/wiki/Tel_Aviv_Sourasky_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Scanning the diagnostic H&E slide and running the inference within 48 hours of biopsy", "A rapid single-gene PCR assay available for confirmation" ], "must_hold": [ "PCR or sequencing confirmation before treatment", "A tumor with a targetable driver the model can infer" ], "echoes": [ { "date": "2023-02-01", "setting": "Second woman in her early 40s with EGFR-mutant NSCLC at the same center, February 2023; same AI-guided path, MRI improvement at two months", "outcome": "recurred", "source": "Waissengrin B et al. (2023) J Clin Pathol 76(11):790-792, https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Scanning the diagnostic H&E slide and running the inference within 48 hours of biopsy", "A rapid single-gene PCR assay available for confirmation" ], "must_hold": [ "PCR or sequencing confirmation before treatment", "A tumor with a targetable driver the model can infer" ], "echoes": [ { "date": "2023-02-01", "setting": "Second woman in her early 40s with EGFR-mutant NSCLC at the same center, February 2023; same AI-guided path, MRI improvement at two months", "outcome": "recurred", "source": "Waissengrin B et al. (2023) J Clin Pathol 76(11):790-792, https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 225 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/225", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/; https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://imagene-ai.com/privacy-policy/; https://en.wikipedia.org/wiki/Tel_Aviv_Sourasky_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - oncology / molecular pathology", "segment": "AI-guided biomarker testing in non-small-cell lung cancer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Waissengrin B, Garasimov A, Bainhoren O, Merimsky O, Shamai S, Erental A, Wolf I, Hershkovitz D (2023). Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report. Journal of Clinical Pathology 76(11):790-792.", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "The algorithmic inference identified positivity for EGFR mutation." }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (second quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "The incorporation of the AI solution not only enabled targeted treatment 1 week earlier than in the routine practice" }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (third quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "resulted in avoiding altogether whole neuroaxis radiotherapy" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0068-source-0001", "AIBD-0068-source-0002", "AIBD-0068-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Waissengrin B, Garasimov A, Bainhoren O, Merimsky O, Shamai S, Erental A, Wolf I, Hershkovitz D (2023). Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report. Journal of Clinical Pathology 76(11):790-792.", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "The algorithmic inference identified positivity for EGFR mutation." }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (second quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "The incorporation of the AI solution not only enabled targeted treatment 1 week earlier than in the routine practice" }, { "kind": "case report", "citation": "Waissengrin B et al. (2023). J Clin Pathol 76(11):790-792 (third quotation).", "title": "Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/", "written_by": "deployer", "quote": "resulted in avoiding altogether whole neuroaxis radiotherapy" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Imagene AI predicted EGFR from an H&E slide in <48 h; rapid PCR confirmed; osimertinib began 2 days post-biopsy, no neuraxis radiotherapy.", "account": "In July 2022 a healthy woman in her early 40s was admitted to Tel Aviv Sourasky Medical Center, Israel. She had a month of worsening headaches. Imaging showed a 2.6 cm left apical lung adenocarcinoma with leptomeningeal spread; biopsy tissue was scarce. To guide gene testing without exhausting tissue, the team ran Imagene's deep-learning algorithm on the H&E slide. Within 48 hours of biopsy it inferred EGFR mutation positivity. A rapid Idylla PCR assay confirmed the L858R exon 21 mutation; osimertinib started two days after biopsy. The authors say that was one week earlier than routine practice and avoided whole-neuraxis radiotherapy. Magnetic resonance imaging (MRI) at two months showed the enhancement gone." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Imagene AI (H&E-based molecular inference)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Imagene" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Imagene AI infers EGFR mutation from an H&E slide, letting a woman with leptomeningeal lung cancer start osimertinib two days after biopsy and avoid neuraxis radiotherapy", "headline": "Imagene AI infers EGFR from H&E; osimertinib 2 days post-biopsy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f95325356bf6185ad2551e47258c9cbba0b69a755721dbb9d46c0bafd1aac5bd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In July 2022 a healthy woman in her early 40s was admitted to Tel Aviv Sourasky Medical Center, Israel. She had a month of worsening headaches. Imaging showed a 2.6 cm left apical lung adenocarcinoma with leptomeningeal spread; biopsy tissue was scarce. To guide gene testing without exhausting tissue, the team ran Imagene's deep-learning algorithm on the H&E slide. Within 48 hours of biopsy it inferred EGFR mutation positivity. A rapid Idylla PCR assay confirmed the L858R exon 21 mutation; osimertinib started two days after biopsy. The authors say that was one week earlier than routine practice and avoided whole-neuraxis radiotherapy. Magnetic resonance imaging (MRI) at two months showed the enhancement gone.", "replication": { "produced_by": [ "Scanning the diagnostic H&E slide and running the inference within 48 hours of biopsy", "A rapid single-gene PCR assay available for confirmation" ], "must_hold": [ "PCR or sequencing confirmation before treatment", "A tumor with a targetable driver the model can infer" ], "echoes": [ { "date": "2023-02-01", "setting": "Second woman in her early 40s with EGFR-mutant NSCLC at the same center, February 2023; same AI-guided path, MRI improvement at two months", "outcome": "recurred", "source": "Waissengrin B et al. (2023) J Clin Pathol 76(11):790-792, https://pmc.ncbi.nlm.nih.gov/articles/PMC10646899/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0114", "title": "An early resistance warning helped doctors change a woman’s antibiotic", "summary": "An early resistance warning from CMUH’s Intelligent Anti-Microbial System helped doctors change a 78-year-old woman’s antibiotic before she recovered.", "date_observed": "2022-07-01", "date_basis": "event", "date_precision": "month", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "A 78-year-old woman at China Medical University Hospital developed severe pneumonia during a prolonged admission. The hospital’s Intelligent Anti-Microbial System predicted within an hour that her Stenotrophomonas maltophilia isolate resisted ceftazidime and suggested levofloxacin. Clinicians changed the antibiotic. The hospital reported that she recovered and went home in late July 2022. The account concerns one patient. More than 100,000 platform uses and projected changes in hospital mortality concern the wider service, not 100,000 demonstrated recoveries.", "category": "harm prevented", "unexpected": false, "purpose": "Help clinicians select an effective antibiotic sooner by predicting resistance from routine mass spectra.", "system": "智抗菌平台 / Intelligent Anti-Microbial System (i.A.M.S)", "model_version": null, "developer": "China Medical University Hospital, Taichung (team of superintendent Der-Yang Cho 周德陽, Po-Ren Hsueh 薛博仁 of the Department of Laboratory Medicine, and Jiaxin Yu 游家鑫)", "deployer": "China Medical University Hospital, Taichung", "location": "Taichung, Taiwan", "domain": "Healthcare - clinical microbiology and antibiotic therapy", "segment": "Hospital laboratory AI (antibiotic-resistance prediction from MALDI-TOF spectra)", "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's part was turnaround time, a resistance prediction in one hour instead of days.", "registry_ids": { "oecd_aim": "2022-10-25-1879" }, "ratings": [ { "group": "personal", "depth": 4, "reason": "The treating hospital described timely treatment of a severe infection, followed by recovery and discharge. The account does not establish a counterfactual life saved." } ], "ai_role": { "status": "assessed", "statement": "The platform analyzed a bacterial mass spectrum to predict resistance and suggest an alternative antibiotic. Clinicians selected and administered treatment. The hospital attributes earlier selection to the system, but the available account cannot isolate its effect on survival." }, "evidence": [ { "kind": "press release", "citation": "China Medical University Hospital, “78歲婦人感染超級細菌昏迷 ! AI質譜儀1小時找出有效抗生素 《智抗菌》平臺累積十萬人以上使用 刊登頂尖醫學期刊《Journal of Infection》,” October 31, 2022. Original treating-hospital account, patient narrative and figure captions.", "title": "78歲婦人感染超級細菌昏迷 ! AI質譜儀1小時找出有效抗生素", "url": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8151", "date": "2022-10-31", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "中央社 (Central News Agency), 記者郝雪卿 (2022). 78歲婦人感染超級細菌命危 AI質譜儀輔助治療. CNA, Taichung, 26 October 2022, reporting the hospital's press conference and quoting superintendent 周德陽 and vice-superintendent 薛博仁.", "title": "78歲婦人感染超級細菌命危 AI質譜儀輔助治療", "url": "https://www.cna.com.tw/news/ahel/202210260324.aspx", "date": "2022-10-26", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "自由健康網 (Liberty Times), 記者蔡淑媛 (2022). 7旬嬤感染超級細菌命危 AI預測有抗藥性趕緊換藥救命. Liberty Times, Taichung, 26 October 2022, quoting 周德陽 and 薛博仁.", "title": "7旬嬤感染超級細菌命危 AI預測有抗藥性趕緊換藥救命", "url": "https://health.ltn.com.tw/article/breakingnews/4102412", "date": "2022-10-26", "written_by": "deployer", "quote": null }, { "kind": "peer-reviewed study", "citation": "Yu J, Lin HH, Tseng KH, Tien N, Hsueh PR, Cho DY (2023). Direct prediction of ceftazidime-resistant Stenotrophomonas maltophilia from routine MALDI-TOF mass spectra using machine learning. Journal of Infection 86(2): e58-e60, letter, online 9 September 2022, doi:10.1016/j.jinf.2022.09.005. All authors at China Medical University Hospital; the letter has no abstract, so its keywords are quoted.", "title": "Direct prediction of ceftazidime-resistant Stenotrophomonas maltophilia from routine MALDI-TOF mass spectra using machine learning", "url": "https://doi.org/10.1016/j.jinf.2022.09.005", "date": "2022-09-09", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "China Medical University Hospital, 2022 Corporate Sustainability Report, 37, “預測抗藥細菌，醫療數位轉型.” The report identifies i.A.M.S and compares inpatient drug spending with the corresponding period of 2021.", "title": "中國醫藥大學附設醫院 2022 永續報告書", "url": "https://www.cmuh.org.tw/FileUploads/FileUpload/2022%E4%B8%AD%E5%9C%8B%E9%86%ABCSR%28ESG%29_PDF.pdf", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The hospital's own laboratory identifies isolates by MALDI-TOF, so a spectrum exists as soon as a culture grows", "A machine-learning classifier trained on the hospital's spectra and susceptibility records for Stenotrophomonas maltophilia and ceftazidime, one of nine species the platform covers", "The platform returns the resistance prediction and a suggested alternative to the treating team within an hour" ], "must_hold": [ "The organism and antibiotic are ones the model was trained for", "Clinicians act on the prediction before the conventional susceptibility result arrives", "An effective alternative antibiotic is available and tolerated by the patient" ], "echoes": [] }, "paired_incident": null, "headline": "An early resistance warning helped doctors change a woman’s antibiotic", "metric": "flagged ceftazidime resistance in 1 hour", "comparator": { "against": "The two to three days that hospital clinicians said conventional susceptibility testing required", "before": "Two to three days", "after": "A prediction within one hour", "basis": "assumed", "quote": "中國附醫驗醫學中心副院長薛博仁說，由於菌嗜麥芽窄食單胞菌抗藥性強，一般臨床檢驗抗藥性要2、3天，透過AI大數據分析細菌質譜儀圖譜，1小時能快速預測有抗藥性，準確率達92%，醫療團隊發現原先用藥有抗藥性，立刻換上無抗藥性的抗生素，1週後就肺部感染大幅好轉，之後順利拔管出院返家。", "url": "https://health.ltn.com.tw/article/breakingnews/4102412" }, "later": { "status": "persisted", "date": "2022-10-31", "note": "The hospital reported more than 100,000 platform uses since rollout. Its five-year mortality and medication-error figures were projections, not observed results.", "quote": null, "url": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8151" }, "value": null, "developer_country": "Taiwan", "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-10-25-1879", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://health.ltn.com.tw/article/breakingnews/4102412; https://www.top1health.com/Article/240/90334", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/China_Medical_University_(Taiwan); https://en.wikipedia.org/wiki/China_Medical_University_(Taiwan)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8151", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the deployer's report, two news reports from the deployer and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0114", "catalog_version": "1.0.0", "source_fingerprint": "60e0410e98964a3c30cb0ae8f5c4e28c43bc3fc69209a8b348bedb8d77c1ae09", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0114-source-0001", "AIBD-0114-source-0002", "AIBD-0114-source-0003", "AIBD-0114-source-0004", "AIBD-0114-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "CMUH clinical account, NewsArticle 8151" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The evaluation described in the cited original sources." }, "record_ids": [ "CMUH clinical account, NewsArticle 8151" ] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0114-platform-drug-spending" ], "role": "monetary observations" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Platform-wide spending figures, separate from the patient’s recovery." }, "record_ids": [ "AIBD-0114-platform-drug-spending" ] }, "institutional decisions": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "CMUH i.A.M.S rollout 2022" ], "role": "institutional decisions" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospital adoption of the clinical platform." }, "record_ids": [ "CMUH i.A.M.S rollout 2022" ] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "China Medical University Hospital developed and deployed the platform. 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The patient account does not establish public or commercial access to that version." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "A treating hospital’s account of one patient, with separate information about the wider platform." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A treating hospital’s account of one patient, with separate information about the wider platform." } }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "patient_recovery": { "url": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8151", "locator": "Patient narrative and clinical-image captions" }, "early_July_extubation": { "url": "https://www.cna.com.tw/news/ahel/202210260324.aspx", "locator": "Paragraph quoting superintendent Cho" }, "drug_spending": { "url": "https://www.cmuh.org.tw/FileUploads/FileUpload/2022%E4%B8%AD%E5%9C%8B%E9%86%ABCSR%28ESG%29_PDF.pdf", "locator": "p. 37" }, "model_publication": { "url": "https://doi.org/10.1016/j.jinf.2022.09.005", "locator": "Bibliographic metadata only; full text inaccessible" } } }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0002", "AIBD-0114-source-0004", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital supports the clinical account. Its report provides separate figures about the wider platform." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "text", "text": "A firsthand hospital account, supplemented by reporting from its press conference. The clinical outcome has not been independently verified in the reviewed materials." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A firsthand hospital account, supplemented by reporting from its press conference. The clinical outcome has not been independently verified in the reviewed materials." } }, "claims[].missingness": { "state": "value_present", "value": { "kind": "text", "text": "The exact deployed model, release, configuration, and patient-level treatment record remain unavailable. The source does not quantify this woman’s financial benefit." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The exact deployed model, release, configuration, and patient-level treatment record remain unavailable. The source does not quantify this woman’s financial benefit." } }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "The platform predicted antibiotic resistance before clinicians changed treatment, after which the patient recovered." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The platform predicted antibiotic resistance before clinicians changed treatment, after which the patient recovered." } }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not document international transfers of patient data or quantify cross-border financial flows.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not document international transfers of patient data or quantify cross-border financial flows." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "text", "text": "The hospital introduced the platform in 2022 and reported more than 100,000 uses by October. Its publications differ on whether rollout began in January or February." }, "provenance": { "kind": "source_review", "basis": "Hospital rollout and projection paragraphs; 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital introduced the platform in 2022 and reported more than 100,000 uses by October. Its publications differ on whether rollout began in January or February." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "text", "text": "Hospital leaders described delayed susceptibility results and the consequences of inappropriate treatment." }, "provenance": { "kind": "source_review", "basis": "Hospital rollout and projection paragraphs; 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Hospital leaders described delayed susceptibility results and the consequences of inappropriate treatment." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "text", "text": "China Medical University Hospital sought faster resistance predictions and earlier selection of antibiotics." }, "provenance": { "kind": "source_review", "basis": "Hospital rollout and projection paragraphs; 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "China Medical University Hospital sought faster resistance predictions and earlier selection of antibiotics." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "text", "text": "The hospital described faster laboratory results and reduced drug spending. Its five-year mortality and medication-error figures were forecasts." }, "provenance": { "kind": "source_review", "basis": "Hospital rollout and projection paragraphs; 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital described faster laboratory results and reduced drug spending. Its five-year mortality and medication-error figures were forecasts." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "Clinical use at China Medical University Hospital in 2022." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Clinical use at China Medical University Hospital in 2022." } }, "economics[].amount": { "state": "value_present", "value": { "kind": "structured", "data": { "hospital_report": { "inpatient_drug_spending_reduction_percent": [ 30, 40 ], "comparison": "Corresponding period of 2021" }, "press_quote": { "annual_antibiotic_spending_reduction_raw": "千萬", "numeric_reading": 10000000, "currency_explicitly_stated": false, "realization_uncertain": true }, "scope": "Entire platform, not this patient", "fructus_status_recommendation": "context or review queue pending monetary base, currency, and attribution review" } }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital reports 30–40% lower inpatient drug spending. A news report quotes annual savings of “10 million,” without stating a currency or calculation." } }, "economics[].costs[]": { "state": "value_present", "value": { "kind": "text", "text": "Implementation and operating costs are not reported alongside the savings." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Implementation and operating costs are not reported alongside the savings." } }, "economics[].counterfactual": { "state": "value_present", "value": { "kind": "text", "text": "The hospital report uses the corresponding period of 2021. It does not describe adjustment for changes in patients or treatment." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital report uses the corresponding period of 2021. It does not describe adjustment for changes in patients or treatment." } }, "economics[].currency_price_basis": { "state": "unresolved", "provenance": { "kind": "source_review", "basis": "Liberty Times, final paragraph; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "reason": "The annual figure does not state its currency or price year. The hospital report gives only percentages.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The annual figure does not state its currency or price year. The hospital report gives only percentages.", "editor_note": "New Taiwan dollars are a plausible reading because the report concerns a Taiwanese hospital’s domestic drug spending. The cited sentence does not name the currency, so no conversion has been applied." } }, "economics[].gross_net": { "state": "value_present", "value": { "kind": "text", "text": "The figures concern drug spending. They do not subtract development, equipment, staffing, or operating costs." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The figures concern drug spending. They do not subtract development, equipment, staffing, or operating costs." } }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "text", "text": "Reported reductions in drug spending across the hospital’s platform." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Reported reductions in drug spending across the hospital’s platform." } }, "economics[].period_unit": { "state": "value_present", "value": { "kind": "text", "text": "The hospital compared the period after rollout in 2022 with the corresponding period in 2021. A separate news account gives an annual figure." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital compared the period after rollout in 2022 with the corresponding period in 2021. A separate news account gives an annual figure." } }, "economics[].realization": { "state": "value_present", "value": { "kind": "text", "text": "The sustainability report presents the spending reduction as observed. The annual figure’s calculation and period of observation are unclear." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sustainability report presents the spending reduction as observed. The annual figure’s calculation and period of observation are unclear." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "The hospital describes lower inpatient drug spending. It does not allocate the saving between the insurer, hospital, and patients." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital describes lower inpatient drug spending. It does not allocate the saving between the insurer, hospital, and patients." } }, "economics[].return_payback": { "state": "value_present", "value": { "kind": "text", "text": "The sources do not calculate net return or a payback period." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources do not calculate net return or a payback period." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "The report states a percentage reduction without publishing the underlying spending amounts, denominators, or calculation." }, "provenance": { "kind": "source_review", "basis": "CMUH 2022 sustainability report, p. 37; Liberty Times, final platform paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0003", "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The report states a percentage reduction without publishing the underlying spending amounts, denominators, or calculation." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The evidence supports the system’s role in selecting treatment earlier. It does not establish what would have happened without that warning." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The evidence supports the system’s role in selecting treatment earlier. It does not establish what would have happened without that warning." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "The hospital’s stated turnaround for conventional susceptibility testing. There was no controlled comparison of this patient’s recovery." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital’s stated turnaround for conventional susceptibility testing. There was no controlled comparison of this patient’s recovery." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "A single-patient clinical account without a control. The hospital also reported separate, aggregate observations about its platform." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A single-patient clinical account without a control. The hospital also reported separate, aggregate observations about its platform." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "The resistance prediction was available within an hour. Clinicians changed the antibiotic, and the patient later recovered and was discharged." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The resistance prediction was available within an hour. Clinicians changed the antibiotic, and the patient later recovered and was discharged." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "The admission began in April 2022, pneumonia developed in late May, and discharge occurred in late July. The exact date of the AI warning is not established." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The admission began in April 2022, pneumonia developed in late May, and discharge occurred in late July. The exact date of the AI warning is not established." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "CMUH clinical account, NewsArticle 8151" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "CMUH clinical account, NewsArticle 8151" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "The hospital described the laboratory warning, antibiotic change, improvement, extubation, and discharge. Public reports do not include the full medical record." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital described the laboratory warning, antibiotic change, improvement, extubation, and discharge. Public reports do not include the full medical record." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Time to a resistance prediction and the patient’s subsequent clinical recovery." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Time to a resistance prediction and the patient’s subsequent clinical recovery." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The hospital reproduces a figure from its resistance-model letter. The reviewed public materials do not provide model code, weights, or patient-level data." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital reproduces a figure from its resistance-model letter. The reviewed public materials do not provide model code, weights, or patient-level data." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "One patient at China Medical University Hospital. The hospital separately reported more than 100,000 uses of its platform." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "One patient at China Medical University Hospital. The hospital separately reported more than 100,000 uses of its platform." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The clinical evidence comes from the treating hospital. News reports repeat its account. The original resistance-model letter could be identified but not read in full." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The clinical evidence comes from the treating hospital. News reports repeat its account. The original resistance-model letter could be identified but not read in full." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2022-10-25-1879" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "The hospital’s 2022 report describes lower inpatient drug spending across the platform. It provides no later follow-up on this woman." }, "provenance": { "kind": "source_review", "basis": "2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital’s 2022 report describes lower inpatient drug spending across the platform. It provides no later follow-up on this woman." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Laboratory staff prepared and identified the isolate. Physicians interpreted the warning and made the treatment decision." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Laboratory staff prepared and identified the isolate. Physicians interpreted the warning and made the treatment decision." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0114" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The service depended on a microbiology laboratory, MALDI-TOF mass spectrometry, susceptibility records, clinical staff, and an available alternative antibiotic." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The service depended on a microbiology laboratory, MALDI-TOF mass spectrometry, susceptibility records, clinical staff, and an available alternative antibiotic." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "One 78-year-old woman with severe pneumonia, diabetes, hypertension, and chronic kidney disease." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "One 78-year-old woman with severe pneumonia, diabetes, hypertension, and chronic kidney disease." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "structured", "data": { "documented_patients": 1, "platform_uses_lower_bound": 100000, "uses_are_not_unique_beneficiaries": true, "patient_name": "Pseudonym in the source; no legal name recorded." } }, "provenance": { "kind": "source_review", "basis": "Hospital patient narrative and rollout paragraph.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "One reported recovery. The hospital’s figure of more than 100,000 platform uses is not a count of distinct beneficiaries." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's part was turnaround time, a resistance prediction in one hour instead of days." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "The hospital reported that an early resistance warning helped clinicians change the antibiotic before the woman recovered." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital reported that an early resistance warning helped clinicians change the antibiotic before the woman recovered." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "The reported clinical result concerns one patient at one hospital. Platform-wide usage does not count confirmed individual benefits." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reported clinical result concerns one patient at one hospital. Platform-wide usage does not count confirmed individual benefits." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "The woman went home in late July 2022. The sources do not report her subsequent health." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The woman went home in late July 2022. The sources do not report her subsequent health." } }, "outcomes[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0114-outcome-01" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0114-outcome-01" } }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "structured", "data": { "groups": [ "personal" ] } }, "provenance": { "kind": "curatorial", "basis": "The beneficiary groups correspond to the reviewed depth assessments.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "People." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Recovery was reported by the treating hospital. The platform’s five-year mortality forecasts were intended benefits." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Recovery was reported by the treating hospital. 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Direct prediction of ceftazidime-resistant Stenotrophomonas maltophilia from routine MALDI-TOF mass spectra using machine learning. Journal of Infection 86(2): e58-e60, letter, online 9 September 2022, doi:10.1016/j.jinf.2022.09.005. 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Clinicians chose and administered the antibiotic." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The system supplied a prediction and treatment suggestion. Clinicians chose and administered the antibiotic." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The resistance-prediction component analyzed the bacterial spectrum. The broader platform supported antibiotic selection." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The resistance-prediction component analyzed the bacterial spectrum. The broader platform supported antibiotic selection." } }, "systems[].deployment_configuration": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Hospital account; full model letter inaccessible.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0004" ], "reviewed_on": "2026-10-25" }, "reason": "The exact instrument model, software settings, and prediction threshold are not reported in the accessible patient account.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The exact instrument model, software settings, and prediction threshold are not reported in the accessible patient account." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "A routine MALDI-TOF mass spectrum informed a prediction of ceftazidime resistance and a suggestion to consider levofloxacin." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A routine MALDI-TOF mass spectrum informed a prediction of ceftazidime resistance and a suggestion to consider levofloxacin." } }, "systems[].model_name": { "state": "unresolved", "provenance": { "kind": "source_review", "basis": "Hospital account; cited letter, doi:10.1016/j.jinf.2022.09.005. The full letter was inaccessible.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0004" ], "reviewed_on": "2026-10-25" }, "reason": "The sources identify a machine-learning model for resistance prediction but do not establish its exact architecture.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources identify a machine-learning model for resistance prediction but do not establish its exact architecture." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Hospital account and public letter metadata.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001", "AIBD-0114-source-0004" ], "reviewed_on": "2026-10-25" }, "reason": "The hospital account does not report a model release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital account does not report a model release." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "智抗菌平台, also called the Intelligent Anti-Microbial System or i.A.M.S." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "智抗菌平台, also called the Intelligent Anti-Microbial System or i.A.M.S." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "China Medical University Hospital, Taichung, Taiwan." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "China Medical University Hospital, Taichung, Taiwan." } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "An early resistance warning helped doctors change a woman’s antibiotic" }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An early resistance warning helped doctors change a woman’s antibiotic" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "60e0410e98964a3c30cb0ae8f5c4e28c43bc3fc69209a8b348bedb8d77c1ae09" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Content fingerprint refreshed after the October 25, 2026 source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "The laboratory cultured the organism and obtained its mass spectrum. The system predicted resistance, and the treating team changed the antibiotic." }, "provenance": { "kind": "source_review", "basis": "CMUH, hospital account of 31 October 2022, patient narrative and figure captions; CNA and Liberty Times, 26 October 2022; CMUH 2022 sustainability report, p. 37.", "record_fields": [], "source_refs": [ "AIBD-0114-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The laboratory cultured the organism and obtained its mass spectrum. The system predicted resistance, and the treating team changed the antibiotic." } } }, "summary": { "total": 91, "addressed": 91, "known": 80, "reviewed": 78, "record_mapped": 9, "not_assessed": 4, "complete": false, "by_state": { "value_present": 80, "not_reported": 5, "unresolved": 2, "not_assessed": 4, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0066", "title": "TREWS machine-learning sepsis early warning system: provider-confirmed alerts within 3 hours associated with lower in-hospital mortality across five hospitals", "summary": "Prospective five-hospital study: sepsis alerts confirmed within 3 h had 3.3% absolute lower in-hospital mortality (CI 1.7–5.1).", "date_observed": "2022-07-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Targeted Real-time Early Warning System (TREWS) is a machine-learning sepsis alert developed at Johns Hopkins University. It was deployed in the electronic health record (EHR) at five US hospitals including Johns Hopkins, Howard County General Hospital and Suburban Hospital. A prospective multi-site cohort study (Nature Medicine, 21 July 2022) monitored 590,736 patients. The analysis focused on 6,877 patients with sepsis identified by the alert before antibiotics were started. After adjustment for presentation and severity, patients whose alert a provider confirmed within three hours had 3.3% absolute (18.7% relative) lower in-hospital mortality. They had less organ failure and shorter stays than patients whose alert was not confirmed within three hours. No individual patient is described.", "category": "general benefit", "unexpected": false, "purpose": "TREWS was built to identify patients developing sepsis early so that treatment can start sooner; the mortality association is its intended benefit.", "system": "TREWS (Targeted Real-time Early Warning System)", "model_version": null, "developer": "Johns Hopkins University (Suchi Saria's group)", "deployer": "Johns Hopkins Medicine (five hospitals)", "location": "Baltimore, United States", "domain": "Healthcare - sepsis / critical care", "segment": "EHR-integrated early warning system", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Cohort-level association (mortality, organ failure, length of stay) without an individually attributable event." }, { "group": "societal", "depth": null, "reason": "The study reports adjusted associations across 590,736 monitored patients, not a discrete population-level event." } ], "ai_role": { "status": "assessed", "statement": "The study is observational. It compares patients whose TREWS alert was confirmed within 3 hours with those confirmed later or not at all, adjusting for presentation and severity. It supports an association, not causation. A medRxiv critique titled “Randomized Clinical Trials or Convenient Controls: TREWS or FALSE?” (Nemati et al., 2022) questions the comparison design. The sources include only the paper's abstract, not its competing-interests statement." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Adams R, Henry KE, Sridharan A, et al. (2022). Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis. Nature Medicine 28(7):1455-1460. doi:10.1038/s41591-022-01894-0.", "title": "Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis", "url": "https://europepmc.org/abstract/MED/35864252", "date": "2022-07-21", "written_by": "makers", "quote": "During the study, 590,736 patients were monitored by TREWS across five hospitals." }, { "kind": "peer-reviewed study", "citation": "Adams R et al. (2022). Nature Medicine 28(7):1455-1460 (second quotation from abstract).", "title": "Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis", "url": "https://europepmc.org/abstract/MED/35864252", "date": "2022-07-21", "written_by": "makers", "quote": "whose alert was confirmed by a provider within 3 h of the alert had a reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction" } ], "replication": { "produced_by": [ "EHR-integrated deployment with alerts presented to bedside providers", "A provider confirmation workflow linked to sepsis treatment" ], "must_hold": [ "Providers evaluate alerts promptly (the benefit was seen only for alerts confirmed within 3 hours)", "Comparable patient mix and alert thresholds" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "123", "title": "Epic Systems’s Sepsis Prediction Algorithms Revealed to Have High Error Rates on Seriously Ill Patients", "url": "https://incidentdatabase.ai/cite/123", "severity": null, "group": "personal", "basis": "Same system class and task, EHR-integrated machine-learning sepsis prediction: Epic's model showed high false-positive and false-negative rates on seriously ill patients, the sepsis-patient cohort TREWS's confirmed alerts benefited." }, "headline": "Confirmed TREWS sepsis alerts are linked to 3.3% lower mortality", "metric": "3.3% absolute (18.7% relative) reduction in in-hospital mortality", "comparator": { "against": "alerted sepsis patients whose alert was not confirmed by a provider within 3 h", "before": "patients whose alert was not confirmed by a provider within 3 h", "after": "reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction, and 18.7%, CI 9.4, 27.0%, adjusted relative reduction)", "basis": "measured", "quote": "Adjusting for patient presentation and severity, patients in this group whose alert was confirmed by a provider within 3 h of the alert had a reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction, and 18.7%, CI 9.4, 27.0%, adjusted relative reduction), organ failure and length of stay compared with patients whose alert was not confirmed by a provider within 3 h.", "url": "https://europepmc.org/abstract/MED/35864252" }, "later": { "status": "unknown", "date": null, "note": "No later development appears in the cited source.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 123 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/123", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Verification sweep: the Nature Medicine study is written by TREWS's developers at Johns Hopkins; those sources are now marked as written by the makers. The record is admitted on its peer-reviewed or independent source.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/abstract/MED/35864252", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Johns_Hopkins_University; https://en.wikipedia.org/wiki/Johns_Hopkins_Medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Johns Hopkins Medicine.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0066", "catalog_version": "1.0.0", "source_fingerprint": "185690fa4197527956053e0cbf3f73df70fd0c5530d6616ea774a007afe949ac", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0066-source-0001", "AIBD-0066-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Johns Hopkins University (Suchi Saria's group)", "deployer": "Johns Hopkins Medicine (five hospitals)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The study is observational. It compares patients whose TREWS alert was confirmed within 3 hours with those confirmed later or not at all, adjusting for presentation and severity. It supports an association, not causation. A medRxiv critique titled “Randomized Clinical Trials or Convenient Controls: TREWS or FALSE?” (Nemati et al., 2022) questions the comparison design. The sources include only the paper's abstract, not its competing-interests statement." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The study is observational. It compares patients whose TREWS alert was confirmed within 3 hours with those confirmed later or not at all, adjusting for presentation and severity. It supports an association, not causation. A medRxiv critique titled “Randomized Clinical Trials or Convenient Controls: TREWS or FALSE?” (Nemati et al., 2022) questions the comparison design. The sources include only the paper's abstract, not its competing-interests statement." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Cohort-level association (mortality, organ failure, length of stay) without an individually attributable event." }, { "group": "societal", "reason": "The study reports adjusted associations across 590,736 monitored patients, not a discrete population-level event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not 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model showed high false-positive and false-negative rates on seriously ill patients, the sepsis-patient cohort TREWS's confirmed alerts benefited.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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It was deployed in the electronic health record (EHR) at five US hospitals including Johns Hopkins, Howard County General Hospital and Suburban Hospital. A prospective multi-site cohort study (Nature Medicine, 21 July 2022) monitored 590,736 patients. The analysis focused on 6,877 patients with sepsis identified by the alert before antibiotics were started. After adjustment for presentation and severity, patients whose alert a provider confirmed within three hours had 3.3% absolute (18.7% relative) lower in-hospital mortality. They had less organ failure and shorter stays than patients whose alert was not confirmed within three hours. No individual patient is described." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "TREWS (Targeted Real-time Early Warning System)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Johns Hopkins University (Suchi Saria's group)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TREWS machine-learning sepsis early warning system: provider-confirmed alerts within 3 hours associated with lower in-hospital mortality across five hospitals", "headline": "Confirmed TREWS sepsis alerts are linked to 3.3% lower mortality" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "185690fa4197527956053e0cbf3f73df70fd0c5530d6616ea774a007afe949ac" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Targeted Real-time Early Warning System (TREWS) is a machine-learning sepsis alert developed at Johns Hopkins University. It was deployed in the electronic health record (EHR) at five US hospitals including Johns Hopkins, Howard County General Hospital and Suburban Hospital. A prospective multi-site cohort study (Nature Medicine, 21 July 2022) monitored 590,736 patients. The analysis focused on 6,877 patients with sepsis identified by the alert before antibiotics were started. After adjustment for presentation and severity, patients whose alert a provider confirmed within three hours had 3.3% absolute (18.7% relative) lower in-hospital mortality. They had less organ failure and shorter stays than patients whose alert was not confirmed within three hours. No individual patient is described.", "replication": { "produced_by": [ "EHR-integrated deployment with alerts presented to bedside providers", "A provider confirmation workflow linked to sepsis treatment" ], "must_hold": [ "Providers evaluate alerts promptly (the benefit was seen only for alerts confirmed within 3 hours)", "Comparable patient mix and alert thresholds" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0004", "title": "Intracortical speech neuroprosthesis decodes attempted speech at 62 words per minute for a woman with ALS (Stanford)", "summary": "Four 64-electrode microelectrode arrays and an RNN with a 125,000-word language model let Pat Bennett (ALS) produce text at 62 wpm, 23.8% word error rate", "date_observed": "2022-08-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date.", "category": "benefit created", "unexpected": false, "purpose": "Built to restore communication by decoding attempted speech from intracortical recordings into text; large-vocabulary text communication was the intended benefit and is what occurred.", "system": "Stanford intracortical speech neuroprosthesis (BrainGate2 trial)", "model_version": "Four 64-electrode microelectrode arrays in area 6v and area 44; five-layer gated recurrent-unit RNN with a 125,000-word trigram language model", "developer": "Stanford Neural Prosthetics Translational Laboratory (Willett, Henderson, Shenoy) with the BrainGate consortium", "deployer": "Stanford Medicine", "location": "Stanford, United States", "domain": "Healthcare / assistive communication", "segment": "ALS with loss of intelligible speech", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Material benefit to one identifiable person: large-vocabulary communication at conversational pace in research sessions. The team itself called it a proof of concept rather than an everyday device." } ], "ai_role": { "status": "assessed", "statement": "An RNN decoder plus an n-gram language model is the mechanism translating neural activity into text. The Stanford neurosurgeon describes the language model as “a sophisticated auto-correct”. The benefit is attributable to the decoding system." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Willett FR, Kunz EM, Fan C, et al. (2023). A high-performance speech neuroprosthesis. Nature.", "title": "A high-performance speech neuroprosthesis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/", "date": "2023-08-23", "written_by": "makers", "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)." }, { "kind": "news report", "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).", "title": "These experimental brain implants can restore speech to paralyzed patients", "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients", "date": "2023-08-23", "written_by": "independent", "quote": "For Pat Bennett, 68, every spoken word is a struggle." }, { "kind": "press release", "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. 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(2023). A high-performance speech neuroprosthesis. Nature.", "title": "A high-performance speech neuroprosthesis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/", "date": "2023-08-23", "written_by": "makers", "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)." }, { "kind": "news report", "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).", "title": "These experimental brain implants can restore speech to paralyzed patients", "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients", "date": "2023-08-23", "written_by": "independent", "quote": "For Pat Bennett, 68, every spoken word is a struggle." }, { "kind": "press release", "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. Stanford Medicine News (developer institution release).", "title": "Brain implants, software guide speech-disabled person's intended words to computer screen", "url": "https://med.stanford.edu/news/all-news/2023/08/brain-implant-speech-als.html", "date": "2023-08-23", "written_by": "makers", "quote": "On March 29, 2022, a Stanford Medicine neurosurgeon placed two tiny sensors apiece in two separate regions - both implicated in speech production - along the surface of Bennett's brain." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0004-source-0001", "AIBD-0004-source-0002", "AIBD-0004-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Willett FR, Kunz EM, Fan C, et al. (2023). A high-performance speech neuroprosthesis. Nature.", "title": "A high-performance speech neuroprosthesis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468393/", "date": "2023-08-23", "written_by": "makers", "quote": "T12 spoke at an average pace of 62 words per minute, which more than triples the speed of the previous state of the art for any type of BCI (18 words per minute for a handwriting BCI)." }, { "kind": "news report", "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).", "title": "These experimental brain implants can restore speech to paralyzed patients", "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients", "date": "2023-08-23", "written_by": "independent", "quote": "For Pat Bennett, 68, every spoken word is a struggle." }, { "kind": "press release", "citation": "Goldman B (2023). Brain implants, software guide speech-disabled person's intended words to computer screen. 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They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The decoder and language model converted neural activity into text." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Four arrays, each with 64 electrodes, recorded activity in cortical areas 6v and 44. The language model used a vocabulary of 125,000 words." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The system converted cortical recordings into words." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A five-layer recurrent neural network with gated recurrent units, combined with a trigram language model." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Four 64-electrode microelectrode arrays in area 6v and area 44; five-layer gated recurrent-unit RNN with a 125,000-word trigram language model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Stanford intracortical speech neuroprosthesis (BrainGate2 trial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Stanford Neural Prosthetics Translational Laboratory (Willett, Henderson, Shenoy) with the BrainGate consortium" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Intracortical speech neuroprosthesis decodes attempted speech at 62 words per minute for a woman with ALS (Stanford)", "headline": "Stanford neuroprosthesis decodes Pat Bennett's speech at 62 wpm" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9faa389e1dc7813970aa77e80fe1a8cc1517cf5f30fd77ec735e588b98695403" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At Stanford University, a participant with bulbar-onset amyotrophic lateral sclerosis (identified in news reports as Pat Bennett, 68) had four 64-electrode arrays implanted. They went into ventral premotor cortex (area 6v) and area 44 under the BrainGate2 trial. Stanford's release dates the surgery to 29 March 2022. A recurrent neural network (RNN) converted her neural activity into phoneme probabilities and a 125,000-word language model assembled sentences. She produced text at 62 words per minute (Willett et al., Nature, 23 August 2023). The word error rate was 9.1% on a 50-word vocabulary and 23.8% on the full vocabulary. The work was described as a proof of concept in research sessions. The paper dates sessions by post-implant day (119, 136 and 141 for the reported data), not calendar date. The Stanford release says research sessions began about a month after the 29 March 2022 surgery. It says 62 words per minute came after four months. That places the result in about August 2022, so 1 August 2022 is used as the observation date.", "replication": { "produced_by": [ "Preserved articulatory code for phonemes in ventral premotor cortex years after loss of speech", "Four intracortical arrays in speech-related cortex", "RNN decoder plus large-vocabulary language model trained on the participant's attempted speech", "Regulated trial setting (BrainGate2) with research support" ], "must_hold": [ "Array signal quality remains adequate", "Participant can attempt speech and tolerate recording sessions", "Decoder retraining available across sessions" ], "echoes": [ { "date": "2024-08-15", "setting": "UC Davis, a different participant (45-year-old man with ALS), same intracortical phoneme-decoding approach with Willett as co-author; 97.5% accuracy over 248 hours of conversation", "model_version": "256 electrodes; phoneme decoder with 125,000-word language models", "outcome": "recurred", "source": "Card NS, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med. https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0100", "title": "PROMPTS improves pregnant women’s knowledge and reported care in Kenya", "summary": "Women invited to PROMPTS improved several measures of knowledge, preparation for childbirth, and reported care by 0.06–0.09 standard deviations.", "date_observed": "2022-08-24", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Researchers studied PROMPTS at 40 Kenyan health facilities. The platform combined health information, reminders, and a helpdesk that classified questions for automated replies or clinical review. The trial enrolled 6,139 pregnant women between November and December 2021 and followed them through August 2022. Women at facilities assigned to introduce PROMPTS had improvements of 0.06–0.09 standard deviations across five measures of knowledge, preparation, and reported care. Care-seeking for danger signs did not improve significantly. The trial evaluated the whole platform and was not powered for clinical outcomes. The NLP system changed during this period: the technical paper dates TRIM-AI deployment to June 2022.", "category": "general benefit", "unexpected": false, "purpose": "Deliver pregnancy and postpartum information by SMS and triage incoming questions to a clinical helpdesk by intent and priority.", "system": "PROMPTS, an SMS health platform with automated message classification and a clinical helpdesk; TRIM-AI was introduced in June 2022", "model_version": null, "developer": "Jacaranda Health", "deployer": "Jacaranda Health with Kenyan county health facilities", "location": "Eight counties (Kajiado, Kilifi, Kirinyaga, Kisii, Meru, Narok, Nyeri, Siaya), Kenya", "domain": "Maternal and newborn health", "segment": "Non-profit digital health", "benefit_type": "Improved Physical Health", "taxonomy_note": "The trial measured health knowledge and reported care practices, not clinical outcomes.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Women had measurable improvements in knowledge and reported care practices." } ], "ai_role": { "status": "assessed", "statement": "The helpdesk classified questions and directed messages to automated responses or clinicians. The trial evaluated the whole platform, so the NLP system’s separate effect was not measured." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Vatsa, Rajet, et al. PLOS Medicine 22, no. 2 (2025): e1004527. https://doi.org/10.1371/journal.pmed.1004527.", "title": "Impact Evaluation of a Digital Health Platform Empowering Kenyan Women across the Pregnancy-Postpartum Care Continuum: A Cluster Randomized Controlled Trial", "url": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004527", "date": "2025-02-03", "written_by": "evaluator", "quote": null }, { "kind": "peer-reviewed study", "citation": "Zhang, Wenbo, et al. Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 12 (2023): 14620–27. https://doi.org/10.1609/aaai.v37i12.26709.", "title": "A Continual Pre-Training Approach to Tele-Triaging Pregnant Women in Kenya", "url": "https://ojs.aaai.org/index.php/AAAI/article/view/26709", "date": "2023-06-26", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Jacaranda Health. PROMPTS. Program brochure, n.d.", "title": "PROMPTS", "url": "https://jacarandahealth.org/ypoagriw/2023/11/PROMPTS-BROCHURE-V4.pdf", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Jacaranda Health. Q3 Impact Report: July–September 2025.", "title": "Q3 Impact Report 2025", "url": "https://jacarandahealth.org/ypoagriw/2025/11/Q3-2025-Impact-Report-1.pdf", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Scheduled information and reminders", "An NLP helpdesk that sorted questions for replies or clinical review", "Facility enrollment and county partnerships" ], "must_hold": [ "Access to a phone that can receive text messages", "Clinical staff for escalated questions", "Facilities that support enrollment" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "545", "title": "Chatbot Tessa gives unauthorized diet advice to users seeking help for eating disorders", "url": "https://incidentdatabase.ai/cite/545", "severity": null, "group": "personal", "basis": "Both programs used automated health-message support. 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Subtracting US$632 from US$819 gives US$187 per month." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "The evaluation did not separate automated triage from information, reminders, or clinician support." }, "provenance": { "kind": "source_review", "basis": "Design and limitations.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The evaluation did not separate automated triage from information, reminders, or clinician support." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Women at control facilities were not systematically introduced to PROMPTS, although they could join independently." }, "provenance": { "kind": "source_review", "basis": "Intervention and design.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women at control facilities were not systematically introduced to PROMPTS, although they could join independently." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Twenty facilities introduced PROMPTS and twenty continued usual care. Assignment was stratified within counties." }, "provenance": { "kind": "source_review", "basis": "Methods and S1 Text.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Twenty facilities introduced PROMPTS and twenty continued usual care. Assignment was stratified within counties." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "Five indices improved by 0.06–0.09 standard deviations. Care-seeking for danger signs did not differ significantly." }, "provenance": { "kind": "source_review", "basis": "Abstract and Tables 2–6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Five indices improved by 0.06–0.09 standard deviations. Care-seeking for danger signs did not differ significantly." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Among treatment participants surveyed during pregnancy, 1,453 of 1,700 reported joining PROMPTS." }, "provenance": { "kind": "source_review", "basis": "Results, uptake.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Among treatment participants surveyed during pregnancy, 1,453 of 1,700 reported joining PROMPTS." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0100-E01", "AIBD-0100-E02" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Identifiers assigned to the evaluations described here.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0100-E01, AIBD-0100-E02" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Telephone surveys measured knowledge and reported care. Analysis compared assigned groups and accounted for clustering by facility." }, "provenance": { "kind": "source_review", "basis": "Methods.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Telephone surveys measured knowledge and reported care. Analysis compared assigned groups and accounted for clustering by facility." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Knowledge, birth preparation, routine and danger-sign care, newborn care, and postpartum care content." }, "provenance": { "kind": "source_review", "basis": "Outcome definitions; Tables 2–6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Knowledge, birth preparation, routine and danger-sign care, newborn care, and postpartum care content." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The public repository contains analysis code and documentation. Participant data remain restricted under the study’s approvals." }, "provenance": { "kind": "source_review", "basis": "Data availability; repository README at https://github.com/RVatsa96/prompts-evaluation.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The public repository contains analysis code and documentation. Participant data remain restricted under the study’s approvals." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "There were 6,139 participants at 40 facilities. Researchers completed 5,509 of 6,128 eligible postpartum interviews." }, "provenance": { "kind": "source_review", "basis": "Flow diagram; pp. 12–13.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "There were 6,139 participants at 40 facilities. Researchers completed 5,509 of 6,128 eligible postpartum interviews." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "Outcomes were self-reported. The study was not powered for clinical outcomes, and a parallel nurse-training program could have influenced care." }, "provenance": { "kind": "source_review", "basis": "Strengths and limitations.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Outcomes were self-reported. The study was not powered for clinical outcomes, and a parallel nurse-training program could have influenced care." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "545", "title": "Chatbot Tessa gives unauthorized diet advice to users seeking help for eating disorders", "url": "https://incidentdatabase.ai/cite/545", "group": "personal", "basis": "Both programs used automated health-message support. This is an editorial comparison of a shared function, not evidence that their systems or clinical safeguards were equivalent." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "For July–September 2025, Jacaranda reported cumulative reach of 3,580,095 mothers across 23 Kenyan counties and 1,500 facilities." }, "provenance": { "kind": "source_review", "basis": "Opening scale figures.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "For July–September 2025, Jacaranda reported cumulative reach of 3,580,095 mothers across 23 Kenyan counties and 1,500 facilities." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Clinical staff prepared responses and handled escalated messages. The technical evaluation asked users whether automated answers were helpful." }, "provenance": { "kind": "source_review", "basis": "Deployment section and online appendix.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Clinical staff prepared responses and handled escalated messages. The technical evaluation asked users whether automated answers were helpful." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0100" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "Women needed access to a phone that could receive texts. The service also needed mobile networks, facility enrollment, and clinical helpdesk staff." }, "provenance": { "kind": "source_review", "basis": "Eligibility and intervention.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women needed access to a phone that could receive texts. The service also needed mobile networks, facility enrollment, and clinical helpdesk staff." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Women attending participating facilities who had access to a mobile phone." }, "provenance": { "kind": "source_review", "basis": "Eligibility.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women attending participating facilities who had access to a mobile phone." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "The trial enrolled 6,139 women: 3,140 at treatment facilities and 2,999 at control facilities." }, "provenance": { "kind": "source_review", "basis": "Results and flow diagram.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial enrolled 6,139 women: 3,140 at treatment facilities and 2,999 at control facilities." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved health knowledge and use of recommended maternal and newborn care." }, "provenance": { "kind": "source_review", "basis": "Tables 2–6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Improved health knowledge and use of recommended maternal and newborn care." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "The invitation to use PROMPTS improved several measures of knowledge, preparation, and care." }, "provenance": { "kind": "source_review", "basis": "Tables 2–6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The invitation to use PROMPTS improved several measures of knowledge, preparation, and care." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "The trial covered public and faith-based facilities in eight counties. It excluded women without phone access." }, "provenance": { "kind": "source_review", "basis": "Setting and eligibility.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial covered public and faith-based facilities in eight counties. It excluded women without phone access." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Researchers followed participants from pregnancy into the early postpartum period." }, "provenance": { "kind": "source_review", "basis": "Follow-up methods.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers followed participants from pregnancy into the early postpartum period." } }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Pregnant and postpartum women and their newborns." }, "provenance": { "kind": "source_review", "basis": "Study population.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Pregnant and postpartum women and their newborns." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Observed in a randomized evaluation." }, "provenance": { "kind": "source_review", "basis": "Methods and results.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Observed in a randomized evaluation." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "The service depended on phone access and did not replace clinical care. The trial did not establish effects on deaths or serious illness." }, "provenance": { "kind": "source_review", "basis": "Eligibility and limitations.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The service depended on phone access and did not replace clinical care. The trial did not establish effects on deaths or serious illness." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Better knowledge and care were the intended benefits." }, "provenance": { "kind": "source_review", "basis": "Study objectives.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Better knowledge and care were the intended benefits." } }, "places[]": { "state": "value_present", "value": { "kind": "text", "text": "Forty facilities participated across Kajiado, Kilifi, Kirinyaga, Kisii, Meru, Narok, Nyeri, and Siaya counties in Kenya." }, "provenance": { "kind": "source_review", "basis": "Study setting and Table 1.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Forty facilities participated across Kajiado, Kilifi, Kirinyaga, Kisii, Meru, Narok, Nyeri, and Siaya counties in Kenya." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "PROMPTS provided pregnancy information, reminders, and help with questions through text messages." }, "provenance": { "kind": "source_review", "basis": "Intervention description, pp. 5–6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "PROMPTS provided pregnancy information, reminders, and help with questions through text messages." } }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "start": "2021-11-08", "end": "2022-08-24", "precision": "day", "display": "8 November 2021–24 August 2022", "refs": [ "AIBD-0100-source-0001" ], "current_date_observed": "2021-11-08", "instruction": "Use the observed result period for the case date. Keep the full study period separately; the normalized sort date does not imply a more precise observation.", "observed_result_period": "2022-08-24", "observed_result_precision": "day", "observed_result_basis": "Last day of trial follow-up." } }, "provenance": { "kind": "source_review", "basis": "Original study timing.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Recruitment ran from 8 November to 10 December 2021. Follow-up continued through 24 August 2022." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "text", "text": "The later report documents expansion, rather than a new randomized test of the Kenyan trial result." }, "provenance": { "kind": "source_review", "basis": "Scale and expansion sections.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The later report documents expansion, rather than a new randomized test of the Kenyan trial result." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "Women need access to SMS, facilities must support enrollment, and clinicians must be available for escalated questions." }, "provenance": { "kind": "source_review", "basis": "Intervention and eligibility.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women need access to SMS, facilities must support enrollment, and clinicians must be available for escalated questions." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 545 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/545", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the helpdesk description so that roughly 86% of messages receive automated guidance and only escalations reach clinical agents, and restated authorship so that Harvard holds the first and joint senior authorships, the IPA authors did data curation, investigation and supervision, five authors are Jacaranda Health employees, and the USAID DIV and Gates grants were awarded to the Jacaranda Health team.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11835334/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Learning among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11835334/; https://jacarandahealth.org/ypoagriw/2025/11/Q3-2025-Impact-Report-1.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.jacarandahealth.org/; https://www.jacarandahealth.org/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004527", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Maternal and newborn health." }, "provenance": { "kind": "source_review", "basis": "Introduction.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Maternal and newborn health." } }, "sources[].access_version": { "state": "value_present", "value": { "kind": "text", "text": "Original papers, relevant supplements, technical appendix, and provider reports were inspected. Model exposure by trial participant remains unresolved." }, "provenance": { "kind": "source_review", "basis": "Methods, Tables 1–6, discussion, and S1–S2 Text.; pp. 14621–26 and online appendix.; p. 2, costs; p. 3, helpdesk and AI.; Opening scale figures and Ghana expansion section.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Original papers, relevant supplements, technical appendix, and provider reports were inspected. Model exposure by trial participant remains unresolved." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "text", "text": "The trial provides the benefit findings. Its references lead to the original NLP paper and provider cost estimate. A later provider report covers expansion." }, "provenance": { "kind": "source_review", "basis": "Methods, Tables 1–6, discussion, and S1–S2 Text.; pp. 14621–26 and online appendix.; p. 2, costs; p. 3, helpdesk and AI.; Opening scale figures and Ghana expansion section.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial provides the benefit findings. Its references lead to the original NLP paper and provider cost estimate. A later provider report covers expansion." } }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "role": "retained evidence" }, "provenance": { "kind": "source_review", "basis": "Retained evidence in the reviewed order.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0100-source-0001, AIBD-0100-source-0002, AIBD-0100-source-0003, AIBD-0100-source-0004" } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "English." }, "provenance": { "kind": "source_review", "basis": "Methods, Tables 1–6, discussion, and S1–S2 Text.; pp. 14621–26 and online appendix.; p. 2, costs; p. 3, helpdesk and AI.; Opening scale figures and Ghana expansion section.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The benefit study includes both outside researchers and Jacaranda. The technical and cost claims come from the developer partnership and provider." }, "provenance": { "kind": "source_review", "basis": "Methods, Tables 1–6, discussion, and S1–S2 Text.; pp. 14621–26 and online appendix.; p. 2, costs; p. 3, helpdesk and AI.; Opening scale figures and Ghana expansion section.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The benefit study includes both outside researchers and Jacaranda. The technical and cost claims come from the developer partnership and provider." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0100-source-0001", "retained_source_order": [ "AIBD-0100-source-0001", "AIBD-0100-source-0002", "AIBD-0100-source-0003", "AIBD-0100-source-0004" ], "origins": [ { "url": "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004527", "title": "Impact Evaluation of a Digital Health Platform Empowering Kenyan Women across the Pregnancy-Postpartum Care Continuum: A Cluster Randomized Controlled Trial", "locator": "Methods, Tables 1–6, discussion, and S1–S2 Text.", "contribution": "Original trial of the complete platform, with sample, methods, outcomes, and limitations.", "relationship": "Primary study by researchers from Harvard, the World Bank, Innovations for Poverty Action, and Jacaranda Health. 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This is the source that R1 cites for cost and some platform details.", "source_refs": [ "AIBD-0100-source-0003" ], "access": "Original PDF downloaded. Cost, helpdesk, and expansion sections were read. The publication day and price-base year are not established by the URL." }, { "url": "https://jacarandahealth.org/ypoagriw/2025/11/Q3-2025-Impact-Report-1.pdf", "title": "Q3 Impact Report 2025", "locator": "Opening scale figures and Ghana expansion section.", "contribution": "Later cumulative enrollment and service expansion, distinct from the trial’s measured effects.", "relationship": "Original provider report. Enrollment totals are reach, not counts of people with a measured benefit.", "source_refs": [ "AIBD-0100-source-0004" ], "access": "Original PDF downloaded. The title, scale figures, and Ghana expansion section were read. 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The platform classified their intent and urgency, then provided guidance or routed the message to clinicians." }, "provenance": { "kind": "source_review", "basis": "Intervention description, p. 6.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women sent questions by SMS. The platform classified their intent and urgency, then provided guidance or routed the message to clinicians." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "An earlier Google Cloud classifier preceded TRIM-AI. The later system adapted XLM-RoBERTa-large as XLM-RoBERTa-JH." }, "provenance": { "kind": "source_review", "basis": "pp. 14621–24, 14626.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An earlier Google Cloud classifier preceded TRIM-AI. 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Its use during the latter part of follow-up is plausible, but the trial does not report participants’ exposure by model." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "PROMPTS." }, "provenance": { "kind": "source_review", "basis": "Intervention description.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "PROMPTS." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Jacaranda Health." }, "provenance": { "kind": "source_review", "basis": "Intervention description.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Jacaranda Health." } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "PROMPTS improves pregnant women’s knowledge and reported care in Kenya" }, "provenance": { "kind": "source_review", "basis": "Methods, Tables 1–6, discussion, and S1–S2 Text.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "PROMPTS improves pregnant women’s knowledge and reported care in Kenya" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "aa41a37d6114e406c7a3592aa2a249aae44081f7b10e950be64d19da67f2f189" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Women received scheduled messages and reminders and could text the helpdesk. Clinicians handled questions that required human review." }, "provenance": { "kind": "source_review", "basis": "Intervention description.", "record_fields": [], "source_refs": [ "AIBD-0100-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Women received scheduled messages and reminders and could text the helpdesk. Clinicians handled questions that required human review." } } }, "summary": { "total": 91, "addressed": 91, "known": 76, "reviewed": 74, "record_mapped": 5, "not_assessed": 12, "complete": false, "by_state": { "value_present": 76, "not_reported": 2, "unresolved": 1, "not_assessed": 12, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0003", "title": "ECoG speech neuroprosthesis with avatar restores 78-words-per-minute communication after brainstem stroke (UCSF)", "summary": "253-electrode ECoG and deep-learning decoder let Ann Johnson, mute since a 2005 stroke, produce text, synthesized speech and an avatar", "date_observed": "2022-09-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At UCSF Medical Center, a 47-year-old woman with quadriplegia and anarthria from a pontine infarct in 2005 was in the BRAVO trial (NCT03698149). News reports name her Ann Johnson. A 253-channel electrocorticography (ECoG) array was implanted over speech cortical areas in September 2022. Deep-learning recurrent neural networks trained on her attempted silent speech decoded text at a median 78 words per minute. Median word error rate was 25% over a 1,024-word vocabulary. They synthesized speech personalized to her pre-injury voice and animated a facial avatar (Metzger et al., Nature, 23 August 2023). She had earlier communicated by letterboard. The paper ties the text-decoding result to 14 days of data collection shortly after the September 2022 implant and gives no calendar session dates. So the implant month (1 September 2022) is the observation date.", "category": "benefit created", "unexpected": false, "purpose": "Built to restore communication by decoding attempted speech from cortical surface recordings into text, synthesized speech and avatar animation. That was the intended benefit and is what occurred.", "system": "UCSF multimodal speech neuroprosthesis (BRAVO trial)", "model_version": "253-channel high-density ECoG array; bidirectional RNN decoders with CTC loss producing text, synthesized speech and avatar gestures; 1,024-word vocabulary", "developer": "UCSF Chang Lab with UC Berkeley", "deployer": "UCSF Medical Center", "location": "San Francisco, United States", "domain": "Healthcare / assistive communication", "segment": "Post-stroke anarthria", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Material benefit to one identifiable person: fast text, synthesized voice and avatar communication demonstrated in research sessions (run at her residence). The paper reports no independent use outside those sessions." } ], "ai_role": { "status": "assessed", "statement": "Deep-learning decoders are the mechanism. They map cortical activity during attempted speech to phonemes, speech units and articulatory gestures, and every output (text, voice, avatar) depends on them." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Metzger SL, Littlejohn KT, Silva AB, et al. (2023). A high-performance neuroprosthesis for speech decoding and avatar control. Nature.", "title": "A high-performance neuroprosthesis for speech decoding and avatar control", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10826467/", "date": "2023-08-23", "written_by": "makers", "quote": "median rate of 78 words per minute and median word error rate of 25%" }, { "kind": "news report", "citation": "Bendix A (2023). Woman with paralysis speaks through an avatar 18 years after a stroke, thanks to a brain implant. NBC News (via Yahoo News).", "title": "Woman with paralysis speaks through an avatar 18 years after a stroke, thanks to a brain implant", "url": "https://www.yahoo.com/news/woman-paralysis-speaks-avatar-18-004307945.html", "date": "2023-08-24", "written_by": "independent", "quote": "In 2005, Ann Johnson suffered a stroke that left her severely paralyzed and unable to speak. She was 30." }, { "kind": "news report", "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).", "title": "These experimental brain implants can restore speech to paralyzed patients", "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients", "date": "2023-08-23", "written_by": "independent", "quote": "There is this aspect to it that is, to some degree, restoring identity and personhood." }, { "kind": "press release", "citation": "Ellery M. Brain-to-voice neuroprosthesis restores naturalistic speech. Berkeley Engineering, 31 March 2025.", "title": "Brain-to-voice neuroprosthesis restores naturalistic speech", "url": "https://engineering.berkeley.edu/news/2025/03/brain-to-voice-neuroprosthesis-restores-naturalistic-speech/", "date": "2025-03-31", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Preserved articulatory representations in speech sensorimotor cortex 18 years after paralysis", "High-density ECoG coverage of speech cortex", "Deep-learning decoders trained on the participant's attempted speech in under two weeks" ], "must_hold": [ "Participant can attempt speech and retains cortical speech representations", "Array remains stable with adequate signal quality", "Research infrastructure available for training and real-time decoding" ], "echoes": [ { "date": "2024-05-20", "setting": "UCSF, a different participant (a 36-year-old Spanish-English bilingual with anarthria and severe spastic quadriparesis after a bilateral pontine stroke, 128-electrode ECoG array, BRAVO trial NCT03698149; verified against the full text at PMC11554235): sentences decoded in either language", "model_version": "ECoG with deep-learning and bilingual natural-language models", "outcome": "recurred", "source": "Silva AB, Liu JR, Metzger SL, et al. (2024). A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages. Nature Biomedical Engineering. doi:10.1038/s41551-024-01207-5" }, { "date": "2025-03-31", "setting": "UCSF, a clinical trial participant with severe paralysis and anarthria (the accessible abstract does not say whether this is the same participant and the full text is behind a login wall, so the identity is unverified): continuously streaming speech synthesis personalized to the participant's pre-injury voice in 80 ms increments", "model_version": "Deep-learning recurrent neural network transducer models", "outcome": "recurred", "source": "Littlejohn KT, Cho CJ, Liu JR, et al. (2025). A streaming brain-to-voice neuroprosthesis to restore naturalistic communication. Nature Neuroscience. doi:10.1038/s41593-025-01905-6" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "732", "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations", "url": "https://incidentdatabase.ai/cite/732", "severity": null, "group": "personal", "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech." }, "headline": "UCSF neuroprosthesis lets Ann Johnson speak through an avatar", "metric": "decoded text at a median 78 words per minute with 25% median word error rate", "comparator": null, "later": { "status": "persisted", "date": "2025-03-31", "note": "The same participant went on to use a streaming synthesis approach, reported in Nature Neuroscience, that cut the decoding delay from about eight seconds per sentence to under a second.", "quote": "Ann, who also participated in the 2023 study, shared with researchers how her experience with the new streaming synthesis approach compared to the earlier study's text-to-speech decoding method.", "url": "https://engineering.berkeley.edu/news/2025/03/brain-to-voice-neuroprosthesis-restores-naturalistic-speech/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/732", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Moved the date observed from the publication date to the September 2022 implant month to which the paper anchors its 14-day data-collection results, noted that the sessions ran at the participant's residence, added a taxonomy note on why a research-session demonstration is filed as a benefit created or restored, verified the Silva 2024 echo participant as a different person against the PMC full text, and marked the Littlejohn 2025 echo participant as unverified.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10826467/; https://pmc.ncbi.nlm.nih.gov/articles/PMC11554235/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://engineering.berkeley.edu/news/2025/03/brain-to-voice-neuroprosthesis-restores-naturalistic-speech/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://changlab.ucsf.edu/; https://en.wikipedia.org/wiki/UCSF_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0003", "catalog_version": "1.0.0", "source_fingerprint": "7d83466f3a2af8b31dfc5d8a4394bf129f9ed3fb9cb522733b589adb34a526dc", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0003-source-0001", "AIBD-0003-source-0002", "AIBD-0003-source-0003", "AIBD-0003-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UCSF Chang Lab with UC Berkeley", "deployer": "UCSF Medical Center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Deep-learning decoders are the mechanism. They map cortical activity during attempted speech to phonemes, speech units and articulatory gestures, and every output (text, voice, avatar) depends on them." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Deep-learning decoders are the mechanism. They map cortical activity during attempted speech to phonemes, speech units and articulatory gestures, and every output (text, voice, avatar) depends on them." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Material benefit to one identifiable person: fast text, synthesized voice and avatar communication demonstrated in research sessions (run at her residence). 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(2023). A high-performance neuroprosthesis for speech decoding and avatar control. Nature.", "title": "A high-performance neuroprosthesis for speech decoding and avatar control", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10826467/", "date": "2023-08-23", "written_by": "makers", "quote": "median rate of 78 words per minute and median word error rate of 25%" }, { "kind": "news report", "citation": "Bendix A (2023). Woman with paralysis speaks through an avatar 18 years after a stroke, thanks to a brain implant. NBC News (via Yahoo News).", "title": "Woman with paralysis speaks through an avatar 18 years after a stroke, thanks to a brain implant", "url": "https://www.yahoo.com/news/woman-paralysis-speaks-avatar-18-004307945.html", "date": "2023-08-24", "written_by": "independent", "quote": "In 2005, Ann Johnson suffered a stroke that left her severely paralyzed and unable to speak. She was 30." }, { "kind": "news report", "citation": "Hamilton J (2023). These experimental brain implants can restore speech to paralyzed patients. NPR (via BPR).", "title": "These experimental brain implants can restore speech to paralyzed patients", "url": "https://www.bpr.org/2023-08-23/these-experimental-brain-implants-can-restore-speech-to-paralyzed-patients", "date": "2023-08-23", "written_by": "independent", "quote": "There is this aspect to it that is, to some degree, restoring identity and personhood." }, { "kind": "press release", "citation": "Ellery M. Brain-to-voice neuroprosthesis restores naturalistic speech. Berkeley Engineering, 31 March 2025.", "title": "Brain-to-voice neuroprosthesis restores naturalistic speech", "url": "https://engineering.berkeley.edu/news/2025/03/brain-to-voice-neuroprosthesis-restores-naturalistic-speech/", "date": "2025-03-31", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "253-electrode ECoG and deep-learning decoder let Ann Johnson, mute since a 2005 stroke, produce text, synthesized speech and an avatar", "account": "At UCSF Medical Center, a 47-year-old woman with quadriplegia and anarthria from a pontine infarct in 2005 was in the BRAVO trial (NCT03698149). News reports name her Ann Johnson. A 253-channel electrocorticography (ECoG) array was implanted over speech cortical areas in September 2022. Deep-learning recurrent neural networks trained on her attempted silent speech decoded text at a median 78 words per minute. Median word error rate was 25% over a 1,024-word vocabulary. They synthesized speech personalized to her pre-injury voice and animated a facial avatar (Metzger et al., Nature, 23 August 2023). She had earlier communicated by letterboard. The paper ties the text-decoding result to 14 days of data collection shortly after the September 2022 implant and gives no calendar session dates. 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No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "Bidirectional recurrent neural networks trained with connectionist temporal classification loss." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. 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News reports name her Ann Johnson. A 253-channel electrocorticography (ECoG) array was implanted over speech cortical areas in September 2022. Deep-learning recurrent neural networks trained on her attempted silent speech decoded text at a median 78 words per minute. Median word error rate was 25% over a 1,024-word vocabulary. They synthesized speech personalized to her pre-injury voice and animated a facial avatar (Metzger et al., Nature, 23 August 2023). She had earlier communicated by letterboard. The paper ties the text-decoding result to 14 days of data collection shortly after the September 2022 implant and gives no calendar session dates. So the implant month (1 September 2022) is the observation date.", "replication": { "produced_by": [ "Preserved articulatory representations in speech sensorimotor cortex 18 years after paralysis", "High-density ECoG coverage of speech cortex", "Deep-learning decoders trained on the participant's attempted speech in under two weeks" ], "must_hold": [ "Participant can attempt speech and retains cortical speech representations", "Array remains stable with adequate signal quality", "Research infrastructure available for training and real-time decoding" ], "echoes": [ { "date": "2024-05-20", "setting": "UCSF, a different participant (a 36-year-old Spanish-English bilingual with anarthria and severe spastic quadriparesis after a bilateral pontine stroke, 128-electrode ECoG array, BRAVO trial NCT03698149; verified against the full text at PMC11554235): sentences decoded in either language", "model_version": "ECoG with deep-learning and bilingual natural-language models", "outcome": "recurred", "source": "Silva AB, Liu JR, Metzger SL, et al. (2024). A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages. Nature Biomedical Engineering. doi:10.1038/s41551-024-01207-5" }, { "date": "2025-03-31", "setting": "UCSF, a clinical trial participant with severe paralysis and anarthria (the accessible abstract does not say whether this is the same participant and the full text is behind a login wall, so the identity is unverified): continuously streaming speech synthesis personalized to the participant's pre-injury voice in 80 ms increments", "model_version": "Deep-learning recurrent neural network transducer models", "outcome": "recurred", "source": "Littlejohn KT, Cho CJ, Liu JR, et al. (2025). A streaming brain-to-voice neuroprosthesis to restore naturalistic communication. Nature Neuroscience. doi:10.1038/s41593-025-01905-6" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0019", "title": "AI-guided survey confirms 303 new figurative Nazca geoglyphs in Peru", "summary": "An IBM–Yamagata deep-learning survey guided fieldwork that confirmed 303 new Nazca geoglyphs, published in PNAS (Sep 2024).", "date_observed": "2022-09-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Between September 2022 and February 2023 (sources give only months, so the first day of September is used) archaeologists surveyed the Nazca Pampa in Peru. Masato Sakai of Yamagata University's Institute of Nasca led them. They used candidate locations proposed by a deep-learning model developed with IBM Research. It screened aerial photographs at 10-centimeter resolution over more than 600 square kilometers. Field verification confirmed 303 previously unknown figurative relief-type geoglyphs, almost doubling the known total. 178 were individually suggested by the model and 125 were found during the AI-guided survey without an individual suggestion. The team screened about 36 AI suggestions per promising candidate and reports a sixteen-fold increase in discovery rate. The results appeared in PNAS on 23 September 2024.", "category": "benefit created", "unexpected": false, "purpose": "Built to flag candidate geoglyph locations in aerial imagery so that archaeologists could prioritize ground survey; the discoveries were that purpose.", "system": "Geoglyph classifier developed by IBM and Yamagata University: an ImageNet-pretrained ResNet50 with a two-layer classifier, applied to aerial imagery through IBM PAIRS", "model_version": null, "developer": "IBM Research (IBM T.J. Watson Research Center) with Yamagata University and DLR", "deployer": "Yamagata University (Institute of Nasca field team)", "location": "Nazca, Peru", "domain": "Archaeology", "segment": "Academic research with industry partner", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Yamagata University's Institute of Nasca reports a sixteen-fold increase in discovery rate, achieving in six months what DLR says previously took decades." }, { "group": "societal", "depth": 3, "reason": "The known corpus of figurative geoglyphs at a UNESCO World Heritage site nearly doubled, with 303 confirmed sites added to Peru's archaeological record." } ], "ai_role": { "status": "assessed", "statement": "The model proposed candidate locations that directed fieldwork. 178 of the 303 confirmed geoglyphs were individually suggested by the AI. Of the remaining 125, 66 were found as part of an AI-discovered group. The other 59 were found without any help from AI or in screening outside the AI-suggested boxes. Confirmation was by ground survey, not by the model." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Sakai, M., Sakurai, A., Lu, S., Olano, J., Albrecht, C. M., Hamann, H. F. and Freitag, M. (2024). AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose. PNAS 121(40), e2407652121 (PMC11459208).", "title": "AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/", "date": "2024-09-23", "written_by": "makers", "quote": "303 new figurative relief-type geoglyphs, almost doubling the amount of known relief-type geoglyphs." }, { "kind": "press release", "citation": "Yamagata University (2024). AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose. University news.", "title": "AI-accelerated Nazca survey nearly doubles the number of known figurative geoglyphs and sheds light on their purpose", "url": "https://www.yamagata-u.ac.jp/en/information/info/20240924/", "date": "2024-09-24", "written_by": "makers", "quote": "This represents a 16 fold increase in the rate of discovery by using IBM's AI." }, { "kind": "press release", "citation": "German Aerospace Center DLR, Earth Observation Center (2024). Accelerated Discovery of Nasca Geoglyphs Guided by AI.", "title": "Accelerated Discovery of Nasca Geoglyphs Guided by AI", "url": "https://www.dlr.de/en/eoc/latest/news/2024/accelerated-discovery-nasca-geoglyphs-by-ai", "date": "2024-10-09", "written_by": "makers", "quote": "The AI system revealed the distribution of candidate geoglyphs from aerial photographs, drawing the archaeologists' attention to areas where to take a closer look at the ground on site." }, { "kind": "news report", "citation": "Archaeology Magazine, Archaeological Institute of America (2024). More Than 300 Geoglyphs Discovered in Peru.", "title": "More Than 300 Geoglyphs Discovered in Peru", "url": "https://archaeology.org/news/2024/09/27/more-than-300-geoglyphs-discovered-in-peru/", "date": "2024-09-27", "written_by": "independent", "quote": "The use of AI in research has allowed us to map the distribution of geoglyphs more quickly and accurately." }, { "kind": "news report", "citation": "del Río ML. More than 200 geoglyphs discovered in Nazca Desert with help of AI. The Art Newspaper, 14 August 2025.", "title": "More than 200 geoglyphs discovered in Nazca Desert with help of AI", "url": "https://www.theartnewspaper.com/2025/08/14/248-nazca-lines-discovered-artificial-intelligence-peru", "date": "2025-08-14", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "High-resolution aerial imagery of the whole survey area", "A detector trained with limited labeled examples of relief-type geoglyphs", "Archaeologist screening of candidates followed by ground verification" ], "must_hold": [ "Targets must be visible at the imagery resolution (about 10 cm)", "Each candidate must be confirmed on the ground before being counted" ], "echoes": [] }, "paired_incident": null, "headline": "IBM–Yamagata AI survey confirms 303 new Nazca geoglyphs in Peru", "metric": "303 previously unknown figurative relief-type geoglyphs, almost doubling the known total", "comparator": { "against": "the discovery rate with remotely sensed high-resolution imagery but without AI (2004 to 2020)", "before": "18.7/y from 2004 to 2020", "after": "303 new figurative geoglyphs during the 2022/23 season of field work (a 16-fold acceleration)", "basis": "measured", "quote": "It has accelerated due to the availability of remotely sensed high-resolution imagery to 18.7/y from 2004 to 2020. Our current work represents another 16-fold acceleration (303 new figurative geoglyphs during the 2022/23 season of field work) using big geospatial data technologies and data mining with the aid of AI.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/" }, "later": { "status": "scaled", "date": "2025-08-14", "note": "The same Yamagata-IBM team announced 248 further AI-assisted geoglyph finds at Expo 2025 Osaka, bringing the total to 893, of which 781 came from AI and aerial-image analysis.", "quote": "An international team led by Japan's Yamagata University and IBM, in collaboration with Peruvian researchers, has announced the discovery of 248 new geoglyphs among the famous Nazca Lines.", "url": "https://www.theartnewspaper.com/2025/08/14/248-nazca-lines-discovered-artificial-intelligence-peru" }, "value": null, "developer_country": "United States", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the statement of the system's part to follow the PNAS breakdown, because the earlier wording credited all 125 non-individually-suggested geoglyphs to AI-prioritized areas when the paper attributes 66 to an AI-discovered group and 59 to finds made without AI help or outside the AI-suggested boxes.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/; https://www.theartnewspaper.com/2025/08/14/248-nazca-lines-discovered-artificial-intelligence-peru", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/IBM_Research; https://www.yamagata-u.ac.jp/en/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Yamagata University.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified the AI model, software, configuration, and human controls from the original paper, supplement, or author documentation.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' peer-reviewed study and two press releases from the makers. 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More than 200 geoglyphs discovered in Nazca Desert with help of AI. The Art Newspaper, 14 August 2025.", "title": "More than 200 geoglyphs discovered in Nazca Desert with help of AI", "url": "https://www.theartnewspaper.com/2025/08/14/248-nazca-lines-discovered-artificial-intelligence-peru", "date": "2025-08-14", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11459208/", "source_refs": [ "AIBD-0019-source-0001" ], "locator": "Results; Materials and Methods, Data Preparation", "contribution": "Describes imagery, candidate generation, human review, and field confirmation.", "relationship": "Original research or documentation from the system’s researchers. This supports identity and methods, not independent verification of benefits." }, { "url": "https://www.pnas.org/doi/suppl/10.1073/pnas.2407652121/suppl_file/pnas.2407652121.sapp.pdf", "source_refs": [ "AIBD-0019-source-0001" ], "locator": "Details of the artificial neural network, pp. 2–3; Postprocessing, pp. 3–4", "contribution": "Names ResNet50 and its classifier and documents threshold settings. This is the original paper’s supplement.", "relationship": "Original research or documentation from the system’s researchers. This supports identity and methods, not independent verification of benefits." } ], "retained_source_order": [ "AIBD-0019-source-0001", "AIBD-0019-source-0002", "AIBD-0019-source-0003", "AIBD-0019-source-0004", "AIBD-0019-source-0005" ], "lead_source_ref": "AIBD-0019-source-0001", "review_scope": "AI identity and operation; existing benefit and source-independence assessments are retained." } }, "provenance": { "kind": "source_review", "basis": "Reviewed the original materials for AI identity and operation. Other source assessments remain unchanged.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The original paper and supplement describe the classifier, image processing, and archaeological fieldwork." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "An IBM–Yamagata deep-learning survey guided fieldwork that confirmed 303 new Nazca geoglyphs, published in PNAS (Sep 2024).", "account": "Between September 2022 and February 2023 (sources give only months, so the first day of September is used) archaeologists surveyed the Nazca Pampa in Peru. Masato Sakai of Yamagata University's Institute of Nasca led them. They used candidate locations proposed by a deep-learning model developed with IBM Research. It screened aerial photographs at 10-centimeter resolution over more than 600 square kilometers. Field verification confirmed 303 previously unknown figurative relief-type geoglyphs, almost doubling the known total. 178 were individually suggested by the model and 125 were found during the AI-guided survey without an individual suggestion. The team screened about 36 AI suggestions per promising candidate and reports a sixteen-fold increase in discovery rate. The results appeared in PNAS on 23 September 2024." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "Archaeologists screened the candidates and visited selected locations to confirm the geoglyphs." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The classifier estimated where relief-type geoglyphs might appear in aerial images." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The model analyzed 112 × 112-pixel images at 5-meter intervals. Candidate selection used probability threshold 0.55 and at least two adjoining image patches." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The classifier analyzed aerial photographs and returned a map of probabilities and candidate locations." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "ResNet50 with a two-layer classifier, adapted from ImageNet training." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not give a release or checkpoint identifier.", "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The study does not give a release or checkpoint identifier." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "The geoglyph classifier developed by IBM and Yamagata University, with IBM PAIRS for imagery." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "IBM Research and Yamagata University, with the German Aerospace Center." }, "provenance": { "kind": "source_review", "basis": "Read the original paper and SI Appendix, “Details of the artificial neural network,” pp. 2–3, and “Postprocessing of the modeled probability map,” pp. 3–4.", "record_fields": [], "source_refs": [ "AIBD-0019-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-guided survey confirms 303 new figurative Nazca geoglyphs in Peru", "headline": "IBM–Yamagata AI survey confirms 303 new Nazca geoglyphs in Peru" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "199358dd8dd5cf6a0df989eb1748dbbb10aca72413bdcd649ee588881e64495f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Between September 2022 and February 2023 (sources give only months, so the first day of September is used) archaeologists surveyed the Nazca Pampa in Peru. Masato Sakai of Yamagata University's Institute of Nasca led them. They used candidate locations proposed by a deep-learning model developed with IBM Research. It screened aerial photographs at 10-centimeter resolution over more than 600 square kilometers. Field verification confirmed 303 previously unknown figurative relief-type geoglyphs, almost doubling the known total. 178 were individually suggested by the model and 125 were found during the AI-guided survey without an individual suggestion. The team screened about 36 AI suggestions per promising candidate and reports a sixteen-fold increase in discovery rate. The results appeared in PNAS on 23 September 2024.", "replication": { "produced_by": [ "High-resolution aerial imagery of the whole survey area", "A detector trained with limited labeled examples of relief-type geoglyphs", "Archaeologist screening of candidates followed by ground verification" ], "must_hold": [ "Targets must be visible at the imagery resolution (about 10 cm)", "Each candidate must be confirmed on the ground before being counted" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 10, "record_mapped": 26, "not_assessed": 55, "complete": false, "by_state": { "value_present": 35, "not_reported": 1, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0022", "title": "Apple Watch Blood Oxygen reading leading to diagnosis and treatment of pulmonary embolism", "summary": "Apple Watch Series 7 SpO2 of 88% prompted CT angiography that found pulmonary embolism; anticoagulated and discharged (Japan).", "date_observed": "2022-09-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case appeared online on 5 September 2022 in QJM (event date not reported). A 50-year-old woman who recently had COVID-19 was referred to the authors' hospital (Oita University, Yufu, Japan) for assessment of dyspnea. Hospital pulse oximetry read 97%, but her Apple Watch Series 7 had shown 88% oxygen saturation in the early morning. Prompted by the watch reading, clinicians did emergent computed tomography (CT) angiography. It showed filling defects in multiple pulmonary artery branches, confirming pulmonary embolism with bilateral deep venous thrombosis (DVT). She was treated with a direct oral anticoagulant, oxygen was stopped on day 6 and she was discharged on day 15. The authors state the watch's low reading led to the diagnosis.", "category": "benefit created", "unexpected": true, "purpose": "The Blood Oxygen app measures oxygen saturation for general wellness and is not intended for medical diagnosis. Detecting a pulmonary embolism was not what it was built to do.", "system": "Apple Watch Blood Oxygen app", "model_version": "Apple Watch Series 7 (event); Series 6 in echo", "developer": "Apple", "deployer": null, "location": "Yufu, Oita Prefecture, Japan", "domain": "Healthcare (emergency and respiratory medicine)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A pulmonary embolism with bilateral DVT was diagnosed and anticoagulated after hospital oximetry had been normal. A life-changing benefit, though the source does not establish that death was imminent." } ], "ai_role": { "status": "assessed", "statement": "The watch's pulse-oximetry algorithm produced the 88% reading on the patient's watch. The letter does not say who reported it to the clinicians and describes no automatic alert. Clinicians chose to perform CT angiography because of that reading and state that it led to the diagnosis." }, "evidence": [ { "kind": "case report", "citation": "Shiota S, Horinouchi Y, Doi E, Miyazaki E (2022). Suspicion of pulmonary embolism after COVID-19 infection raised by a smartwatch. QJM, hcac217 (online 5 Sep 2022; issue 2023).", "title": "Suspicion of pulmonary embolism after COVID-19 infection raised by a smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9494381/", "date": "2022-09-05", "written_by": "independent", "quote": "The smartwatch correctly recognized a low SpO2, which led to the diagnosis of PE in our case." }, { "kind": "case report", "citation": "Tulisiak LN, Loesing ME, Ljungberg A, Kaczor EE (2025). Smartwatch Detection of Refractory Hypoxemia in Phenazopyridine-Induced Methemoglobinemia: A Case Report. Journal of Medical Toxicology 21(4):430-433.", "title": "Smartwatch Detection of Refractory Hypoxemia in Phenazopyridine-Induced Methemoglobinemia", "url": "https://europepmc.org/article/PMC/PMC12511463", "date": "2025-08-04", "written_by": "independent", "quote": "The day before presentation, she was walking in the mall when she was notified by her Series 6 Apple Watch© (version 9.6.3) that her oxygen level was low." } ], "replication": { "produced_by": [ "The wearer has an Apple Watch with the Blood Oxygen app and reviews its readings", "A hypoxemic condition produces a persistently low reading at home", "The wearer reports the reading and a clinician acts on it despite normal spot oximetry" ], "must_hold": [ "The reading is not dismissed as artifact", "Confirmatory testing (CT angiography, co-oximetry) is available", "Effective treatment exists for the condition found" ], "echoes": [ { "date": "2025-08-04", "setting": "71-year-old woman, emergency department, USA (authors' institution: University at Buffalo); her watch notified her of low oxygen and read 73–86% over the next 24 hours, but she ignored the alert and sought care only when her family saw blue discoloration of her skin; hospital pulse oximetry itself read 84% and venous methaemoglobin was 19.8% from phenazopyridine; methylene blue, discharged after about 24 hours; the watch readings corroborated the hospital finding rather than bringing her to care, so the index mechanism did not repeat (publication date)", "model_version": "Apple Watch Series 6", "outcome": "did not recur", "source": "Tulisiak et al. (2025). J Med Toxicol 21(4):430-433. https://europepmc.org/article/PMC/PMC12511463" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "severity": null, "group": "personal", "basis": "Same device, Apple Watch: a sensor-driven alert that was false (Crash Detection dialed 911 for skiers) mirrors a sensor reading that was true (88% SpO2 prompting CT); harmed were Apple Watch users and dispatchers." }, "headline": "Apple Watch SpO2 of 88% prompts CT that finds pulmonary embolism", "metric": "Apple Watch Series 7 had shown an oxygen saturation of 88% in the early morning", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No development after the 2022 case report was found; the 2025 methemoglobinemia report involved a different patient and mechanism.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored “(version 9.6.3)” to the Tulisiak quote, re-recorded the Tulisiak echo as “did not recur” because the patient ignored the watch alert and hospital oximetry itself read 84%, replaced “Buffalo” and “Oita” with the authors' institutions as the sources state them (University at Buffalo; Oita University, Yufu), dropped the unsupported claim that the patient reported the 88% reading, and changed the kind of event from a specific harm prevented to a benefit created or restored because the source shows a changed diagnostic course rather than an averted specified harm, in line with AIBD-0021 and AIBD-0025.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9494381/ ; https://europepmc.org/article/PMC/PMC12511463", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent case reports. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0022", "catalog_version": "1.0.0", "source_fingerprint": "37aad5184fa2ebfaedddf37a1f064ea271a76fecfb119919ae17d8d00138ffef", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0022-source-0001", "AIBD-0022-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's pulse-oximetry algorithm produced the 88% reading on the patient's watch. The letter does not say who reported it to the clinicians and describes no automatic alert. Clinicians chose to perform CT angiography because of that reading and state that it led to the diagnosis." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's pulse-oximetry algorithm produced the 88% reading on the patient's watch. The letter does not say who reported it to the clinicians and describes no automatic alert. Clinicians chose to perform CT angiography because of that reading and state that it led to the diagnosis." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A pulmonary embolism with bilateral DVT was diagnosed and anticoagulated after hospital oximetry had been normal. A life-changing benefit, though the source does not establish that death was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: two independent case reports. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A pulmonary embolism with bilateral DVT was diagnosed and anticoagulated after hospital oximetry had been normal. A life-changing benefit, though the source does not establish that death was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A pulmonary embolism with bilateral DVT was diagnosed and anticoagulated after hospital oximetry had been normal. A life-changing benefit, though the source does not establish that death was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same device, Apple Watch: a sensor-driven alert that was false (Crash Detection dialed 911 for skiers) mirrors a sensor reading that was true (88% SpO2 prompting CT); harmed were Apple Watch users and dispatchers.", "links": [ { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "group": "personal", "basis": "Same device, Apple Watch: a sensor-driven alert that was false (Crash Detection dialed 911 for skiers) mirrors a sensor reading that was true (88% SpO2 prompting CT); harmed were Apple Watch users and dispatchers.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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A 50-year-old woman who recently had COVID-19 was referred to the authors' hospital (Oita University, Yufu, Japan) for assessment of dyspnea. Hospital pulse oximetry read 97%, but her Apple Watch Series 7 had shown 88% oxygen saturation in the early morning. Prompted by the watch reading, clinicians did emergent computed tomography (CT) angiography. It showed filling defects in multiple pulmonary artery branches, confirming pulmonary embolism with bilateral deep venous thrombosis (DVT). She was treated with a direct oral anticoagulant, oxygen was stopped on day 6 and she was discharged on day 15. The authors state the watch's low reading led to the diagnosis.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A pulmonary embolism with bilateral DVT was diagnosed and anticoagulated after hospital oximetry had been normal. A life-changing benefit, though the source does not establish that death was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "The Blood Oxygen app measures oxygen saturation for general wellness and is not intended for medical diagnosis. Detecting a pulmonary embolism was not what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Yufu, Oita Prefecture, Japan", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The Blood Oxygen app measures oxygen saturation for general wellness and is not intended for medical diagnosis. Detecting a pulmonary embolism was not what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-09-05", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored “(version 9.6.3)” to the Tulisiak quote, re-recorded the Tulisiak echo as “did not recur” because the patient ignored the watch alert and hospital oximetry itself read 84%, replaced “Buffalo” and “Oita” with the authors' institutions as the sources state them (University at Buffalo; Oita University, Yufu), dropped the unsupported claim that the patient reported the 88% reading, and changed the kind of event from a specific harm prevented to a benefit created or restored because the source shows a changed diagnostic course rather than an averted specified harm, in line with AIBD-0021 and AIBD-0025.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9494381/ ; https://europepmc.org/article/PMC/PMC12511463", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer has an Apple Watch with the Blood Oxygen app and reviews its readings", "A hypoxemic condition produces a persistently low reading at home", "The wearer reports the reading and a clinician acts on it despite normal spot oximetry" ], "must_hold": [ "The reading is not dismissed as artifact", "Confirmatory testing (CT angiography, co-oximetry) is available", "Effective treatment exists for the condition found" ], "echoes": [ { "date": "2025-08-04", "setting": "71-year-old woman, emergency department, USA (authors' institution: University at Buffalo); her watch notified her of low oxygen and read 73–86% over the next 24 hours, but she ignored the alert and sought care only when her family saw blue discoloration of her skin; hospital pulse oximetry itself read 84% and venous methaemoglobin was 19.8% from phenazopyridine; methylene blue, discharged after about 24 hours; the watch readings corroborated the hospital finding rather than bringing her to care, so the index mechanism did not repeat (publication date)", "model_version": "Apple Watch Series 6", "outcome": "did not recur", "source": "Tulisiak et al. (2025). J Med Toxicol 21(4):430-433. https://europepmc.org/article/PMC/PMC12511463" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer has an Apple Watch with the Blood Oxygen app and reviews its readings", "A hypoxemic condition produces a persistently low reading at home", "The wearer reports the reading and a clinician acts on it despite normal spot oximetry" ], "must_hold": [ "The reading is not dismissed as artifact", "Confirmatory testing (CT angiography, co-oximetry) is available", "Effective treatment exists for the condition found" ], "echoes": [ { "date": "2025-08-04", "setting": "71-year-old woman, emergency department, USA (authors' institution: University at Buffalo); her watch notified her of low oxygen and read 73–86% over the next 24 hours, but she ignored the alert and sought care only when her family saw blue discoloration of her skin; hospital pulse oximetry itself read 84% and venous methaemoglobin was 19.8% from phenazopyridine; methylene blue, discharged after about 24 hours; the watch readings corroborated the hospital finding rather than bringing her to care, so the index mechanism did not repeat (publication date)", "model_version": "Apple Watch Series 6", "outcome": "did not recur", "source": "Tulisiak et al. 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J Med Toxicol 21(4):430-433. https://europepmc.org/article/PMC/PMC12511463" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored “(version 9.6.3)” to the Tulisiak quote, re-recorded the Tulisiak echo as “did not recur” because the patient ignored the watch alert and hospital oximetry itself read 84%, replaced “Buffalo” and “Oita” with the authors' institutions as the sources state them (University at Buffalo; Oita University, Yufu), dropped the unsupported claim that the patient reported the 88% reading, and changed the kind of event from a specific harm prevented to a benefit created or restored because the source shows a changed diagnostic course rather than an averted specified harm, in line with AIBD-0021 and AIBD-0025.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9494381/ ; https://europepmc.org/article/PMC/PMC12511463", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (emergency and respiratory medicine)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Shiota S, Horinouchi Y, Doi E, Miyazaki E (2022). 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Journal of Medical Toxicology 21(4):430-433.", "title": "Smartwatch Detection of Refractory Hypoxemia in Phenazopyridine-Induced Methemoglobinemia", "url": "https://europepmc.org/article/PMC/PMC12511463", "date": "2025-08-04", "written_by": "independent", "quote": "The day before presentation, she was walking in the mall when she was notified by her Series 6 Apple Watch© (version 9.6.3) that her oxygen level was low." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0022-source-0001", "AIBD-0022-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Shiota S, Horinouchi Y, Doi E, Miyazaki E (2022). Suspicion of pulmonary embolism after COVID-19 infection raised by a smartwatch. QJM, hcac217 (online 5 Sep 2022; issue 2023).", "title": "Suspicion of pulmonary embolism after COVID-19 infection raised by a smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9494381/", "date": "2022-09-05", "written_by": "independent", "quote": "The smartwatch correctly recognized a low SpO2, which led to the diagnosis of PE in our case." }, { "kind": "case report", "citation": "Tulisiak LN, Loesing ME, Ljungberg A, Kaczor EE (2025). Smartwatch Detection of Refractory Hypoxemia in Phenazopyridine-Induced Methemoglobinemia: A Case Report. Journal of Medical Toxicology 21(4):430-433.", "title": "Smartwatch Detection of Refractory Hypoxemia in Phenazopyridine-Induced Methemoglobinemia", "url": "https://europepmc.org/article/PMC/PMC12511463", "date": "2025-08-04", "written_by": "independent", "quote": "The day before presentation, she was walking in the mall when she was notified by her Series 6 Apple Watch© (version 9.6.3) that her oxygen level was low." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Apple Watch Series 7 SpO2 of 88% prompted CT angiography that found pulmonary embolism; anticoagulated and discharged (Japan).", "account": "A case appeared online on 5 September 2022 in QJM (event date not reported). A 50-year-old woman who recently had COVID-19 was referred to the authors' hospital (Oita University, Yufu, Japan) for assessment of dyspnea. Hospital pulse oximetry read 97%, but her Apple Watch Series 7 had shown 88% oxygen saturation in the early morning. Prompted by the watch reading, clinicians did emergent computed tomography (CT) angiography. It showed filling defects in multiple pulmonary artery branches, confirming pulmonary embolism with bilateral deep venous thrombosis (DVT). She was treated with a direct oral anticoagulant, oxygen was stopped on day 6 and she was discharged on day 15. The authors state the watch's low reading led to the diagnosis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The watch estimated blood-oxygen saturation from optical measurements." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The initial event involved an Apple Watch Series 7. A later report involved a Series 6." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Apple Watch Series 7 (event); Series 6 in echo" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Blood Oxygen app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Blood Oxygen reading leading to diagnosis and treatment of pulmonary embolism", "headline": "Apple Watch SpO2 of 88% prompts CT that finds pulmonary embolism" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "37aad5184fa2ebfaedddf37a1f064ea271a76fecfb119919ae17d8d00138ffef" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case appeared online on 5 September 2022 in QJM (event date not reported). A 50-year-old woman who recently had COVID-19 was referred to the authors' hospital (Oita University, Yufu, Japan) for assessment of dyspnea. Hospital pulse oximetry read 97%, but her Apple Watch Series 7 had shown 88% oxygen saturation in the early morning. Prompted by the watch reading, clinicians did emergent computed tomography (CT) angiography. It showed filling defects in multiple pulmonary artery branches, confirming pulmonary embolism with bilateral deep venous thrombosis (DVT). She was treated with a direct oral anticoagulant, oxygen was stopped on day 6 and she was discharged on day 15. The authors state the watch's low reading led to the diagnosis.", "replication": { "produced_by": [ "The wearer has an Apple Watch with the Blood Oxygen app and reviews its readings", "A hypoxemic condition produces a persistently low reading at home", "The wearer reports the reading and a clinician acts on it despite normal spot oximetry" ], "must_hold": [ "The reading is not dismissed as artifact", "Confirmatory testing (CT angiography, co-oximetry) is available", "Effective treatment exists for the condition found" ], "echoes": [ { "date": "2025-08-04", "setting": "71-year-old woman, emergency department, USA (authors' institution: University at Buffalo); her watch notified her of low oxygen and read 73–86% over the next 24 hours, but she ignored the alert and sought care only when her family saw blue discoloration of her skin; hospital pulse oximetry itself read 84% and venous methaemoglobin was 19.8% from phenazopyridine; methylene blue, discharged after about 24 hours; the watch readings corroborated the hospital finding rather than bringing her to care, so the index mechanism did not repeat (publication date)", "model_version": "Apple Watch Series 6", "outcome": "did not recur", "source": "Tulisiak et al. (2025). J Med Toxicol 21(4):430-433. https://europepmc.org/article/PMC/PMC12511463" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0172", "title": "Germany deploys IdentiFlight cameras to slow turbines for lesser spotted eagles", "summary": "The OECD AI Incidents Monitor records Germany's deployment of IdentiFlight AI cameras to detect lesser spotted eagles near wind turbines and slow the blades (September 2022); no German outcome data.", "date_observed": "2022-09-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry summarizes press coverage of 20 and 21 September 2022 (The Guardian, Mother Jones, The Register and others, not among the sources). It says Germany is deploying AI-powered camera systems developed by IdentiFlight to detect endangered lesser spotted eagles near wind turbines. They slow the blades to prevent fatal collisions, as wind-farm expansion raises the risk to the species. The monitor's rationale cites the 82% reduction reported from the Wyoming study rather than any German measurement. Only the registry page is among the sources; the sites, operators and any fatality data in Germany are not documented.", "category": "general benefit", "unexpected": false, "purpose": "IdentiFlight is built to detect eagles and curtail turbines; protecting lesser spotted eagles at German wind farms is the intended use.", "system": "IdentiFlight automated eagle detection and turbine curtailment", "model_version": null, "developer": "IdentiFlight", "deployer": null, "location": "Germany", "domain": "Energy", "segment": "Wind power wildlife mitigation", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No German fatality data are documented." }, { "group": "organizational", "depth": null, "reason": "No operator or site outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The deployment is reported through a registry summary of press coverage. No evaluation of the system's effect in Germany was found, and the only effect size cited is the contested Wyoming estimate." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2022-09-20-caeb, 'Germany Deploys AI to Protect Endangered Eagles from Wind Turbine Collisions'", "title": "Germany Deploys AI to Protect Endangered Eagles from Wind Turbine Collisions", "url": "https://oecd.ai/en/incidents/2022-09-20-caeb", "date": "2022-09-20", "written_by": "independent", "quote": "Germany is deploying AI-powered camera systems, developed by IdentiFlight, to detect endangered lesser spotted eagles near wind turbines and slow the blades to prevent fatal collisions." }, { "kind": "other", "citation": "OekoFor GbR (undated, news entries to September 2025). IdentiFlight. OekoFor portfolio page on the German validation of IdentiFlight.", "title": "IdentiFlight", "url": "http://www.oekofor.de/en/portfolio/idf_en/", "date": null, "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Wind-farm expansion into lesser spotted eagle habitat creating a regulatory need for mitigation", "Availability of the IdentiFlight system already evaluated in the United States" ], "must_hold": [ "Site-specific monitoring of eagle fatalities before and after installation", "Operators accepting curtailment losses" ], "echoes": [ { "date": "2021-01-28", "setting": "Top of the World Windpower Facility, Wyoming; BACI study of IdentiFlight curtailment", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1111/1365-2664.13831" } ] }, "paired_incident": null, "headline": "Germany deploys IdentiFlight to protect lesser spotted eagles", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2025-09-01", "note": "OekoFor's validation page reports, in an entry dated September 2025 (day not given), that the latest IdentiFlight version is under evaluation in Germany and its recognition model is still being trained, after training on further species in April 2024.", "quote": "The latest version of the IdentiFlight system is being evaluated. At the same time, the underlying AI recognition model is being continuously trained and optimised.", "url": "http://www.oekofor.de/en/portfolio/idf_en/" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "http://www.oekofor.de/en/portfolio/idf_en/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.identiflight.com/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "Listed, not verified", "claim_basis": "Sources: a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0172", "catalog_version": "1.0.0", "source_fingerprint": "d681e6db13db4697d9388094d32b787ef2bd96acf429df05405aae7a98d10f6d", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0172-source-0001", "AIBD-0172-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "IdentiFlight" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The deployment is reported through a registry summary of press coverage. No evaluation of the system's effect in Germany was found, and the only effect size cited is the contested Wyoming estimate." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "Listed, not verified", "basis": "Sources: a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No German fatality data are documented." }, { "group": "organizational", "reason": "No operator or site outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No German fatality data are documented." }, { "group": "organizational", "reason": "No operator or site outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-09-01", "note": "OekoFor's validation page reports, in an entry dated September 2025 (day not given), that the latest IdentiFlight version is under evaluation in Germany and its recognition model is still being trained, after training on further species in April 2024.", "quote": "The latest version of the IdentiFlight system is being evaluated. At the same time, the underlying AI recognition model is being continuously trained and optimised.", "url": "http://www.oekofor.de/en/portfolio/idf_en/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0172" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry summarizes press coverage of 20 and 21 September 2022 (The Guardian, Mother Jones, The Register and others, not among the sources). It says Germany is deploying AI-powered camera systems developed by IdentiFlight to detect endangered lesser spotted eagles near wind turbines. They slow the blades to prevent fatal collisions, as wind-farm expansion raises the risk to the species. The monitor's rationale cites the 82% reduction reported from the Wyoming study rather than any German measurement. Only the registry page is among the sources; the sites, operators and any fatality data in Germany are not documented.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No German fatality data are documented." }, { "group": "organizational", "reason": "No operator or site outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "IdentiFlight is built to detect eagles and curtail turbines; protecting lesser spotted eagles at German wind farms is the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Germany", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Only the registry page is among the sources; the sites, operators and any fatality data in Germany are not documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "IdentiFlight automated eagle detection and turbine curtailment" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "IdentiFlight" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Germany deploys IdentiFlight cameras to slow turbines for lesser spotted eagles", "headline": "Germany deploys IdentiFlight to protect lesser spotted eagles" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d681e6db13db4697d9388094d32b787ef2bd96acf429df05405aae7a98d10f6d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry summarizes press coverage of 20 and 21 September 2022 (The Guardian, Mother Jones, The Register and others, not among the sources). It says Germany is deploying AI-powered camera systems developed by IdentiFlight to detect endangered lesser spotted eagles near wind turbines. They slow the blades to prevent fatal collisions, as wind-farm expansion raises the risk to the species. The monitor's rationale cites the 82% reduction reported from the Wyoming study rather than any German measurement. Only the registry page is among the sources; the sites, operators and any fatality data in Germany are not documented.", "replication": { "produced_by": [ "Wind-farm expansion into lesser spotted eagle habitat creating a regulatory need for mitigation", "Availability of the IdentiFlight system already evaluated in the United States" ], "must_hold": [ "Site-specific monitoring of eagle fatalities before and after installation", "Operators accepting curtailment losses" ], "echoes": [ { "date": "2021-01-28", "setting": "Top of the World Windpower Facility, Wyoming; BACI study of IdentiFlight curtailment", "outcome": "recurred", "source": "https://doi.org/10.1111/1365-2664.13831" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0117", "title": "Gazi University's Turkish Brain Project algorithm flags a glioma on a 46-year-old woman's brain MRI while she is still in the scanner; physicians alerted at once, stereotactic biopsy the next day", "summary": "Real-time MRI algorithm at Gazi University Hospital alerted doctors to a 46-year-old woman's glioma mid-scan; biopsy next day, Oct 2022.", "date_observed": "2022-10-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In October 2022, a 46-year-old woman with a nonspecific headache had brain magnetic resonance imaging (MRI). This was at Gazi University Faculty of Medicine Hospital, Ankara. A region-based convolutional neural network algorithm, built within the Turkish Brain Project and running on the hospital network in real time, detected an intraparenchymal mass. It alerted the research team while she was still in the scanner. Physicians read the images, judged the finding consistent with a diffuse glioma and admitted her. A stereotactic biopsy next day confirmed an isocitrate dehydrogenase wild-type diffuse glioma; she was referred to oncology for immediate treatment. The case was published 8 May 2023 and reported by Anadolu Agency 22 May 2023.", "category": "protective response", "unexpected": false, "purpose": "The Turkish Brain Project algorithm was built to detect abnormalities on brain MRI as images are acquired and warn the responsible physicians at once. So the days the authors say radiology typically needs to report, and the longer wait before treatment, are cut to days. Anadolu Agency reports it was trained on stroke, hemorrhage and tumor cases. Flagging this patient's tumor mid-scan is that intended use.", "system": "Turkish Brain Project real-time brain MRI alert system at Gazi University: a region-based convolutional neural network object-detection algorithm integrated into the hospital network, which processes MRI images in real time; Anadolu Agency reports that it evaluates a brain MRI within 5-10 seconds while the patient is still in the scanner and sends the physicians' mobile phones a message with the abnormal regions segmented, through a GSM operator's picture-message service", "model_version": null, "developer": "Gazi University, Ankara (Department of Neurosurgery and Department of Computer Engineering), within the Turkish Brain Project funded by the Presidency of the Republic of Türkiye, with the Presidency's Digital Transformation Office credited for the model's development", "deployer": "Gazi University, Department of Neurosurgery, Ankara", "location": "Ankara, Turkey", "domain": "Healthcare - neurosurgery / brain MRI", "segment": "Hospital real-time MRI anomaly alerting (academic, non-commercial)", "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's part was turnaround, an alert mid-scan and a biopsy the next day where reporting typically takes days.", "registry_ids": { "oecd_aim": "2023-05-20-a638" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "One identifiable patient had a diffuse glioma found during her scan, was biopsied the next day and referred for immediate oncological treatment. That was instead of the days the authors say radiology typically needs and the longer wait before treatment. The paper reports no follow-up and no changed outcome. The “saved a life” wording is Anadolu Agency's headline, not the authors' claim." } ], "ai_role": { "status": "assessed", "statement": "The algorithm detected the mass on the real-time MRI data and raised the alert while the patient was still in the scanner. Physicians then read the images, judged the finding consistent with a diffuse glioma and admitted her. The diagnosis itself came from the pathology report after the stereotactic biopsy. What the AI contributed is detection and speed, not a different diagnosis or treatment. The counterfactual is unproven. The authors say radiology would typically take days to report and that further investigations are needed on the advantages of earlier treatment. They give no evidence of what delay this patient would otherwise have faced. The case is reported by the team that built and deployed the algorithm, and the Anadolu Agency coverage carries that team's account. No independent clinical review is cited." }, "evidence": [ { "kind": "case report", "citation": "Sozer A, Borcek AO, Sagiroglu S, Poshtkouh A, Demirtas Z, Karaaslan MM, Kuzucu P, Celtikci E (2023). The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case. Journal of Neurosurgery: Case Lessons 5(19): CASE22536, published 8 May 2023, doi:10.3171/CASE22536, PMID 37158388, PMCID PMC10550689, CC BY-NC-ND 4.0. All authors at Gazi University; their team built and deployed the algorithm, so marked as maker-authored.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://doi.org/10.3171/CASE22536", "date": "2023-05-08", "written_by": "makers", "quote": "detected by an AI algorithm running on real-time patient data while the patient was still in the MRI scanner" }, { "kind": "case report", "citation": "Sozer A et al. (2023). Journal of Neurosurgery: Case Lessons 5(19): CASE22536 (second quotation, on the operation; the case narrative dates the alert to October 2022, the biopsy to the following day, and the pathology to an isocitrate dehydrogenase wild-type diffuse glioma). Open-access copy at PubMed Central.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10550689/", "date": "2023-05-08", "written_by": "makers", "quote": "The day after MRI, a stereotactic biopsy was performed." }, { "kind": "news report", "citation": "TRT Haber, from Anadolu Agency (2023). Tıp tarihinde ilk: Yapay zeka hayat kurtardı [A first in medical history: artificial intelligence saved a life]. TRT Haber, Health, 22 May 2023, source credited as AA; quotes Assoc. Prof. Emrah Çeltikçi and Prof. Şeref Sağıroğlu of Gazi University on the 5-10 second evaluation, the phone alerts and the six-month training.", "title": "Tıp tarihinde ilk: Yapay zeka hayat kurtardı", "url": "https://www.trthaber.com/haber/saglik/tip-tarihinde-ilk-yapay-zeka-hayat-kurtardi-769140.html", "date": "2023-05-22", "written_by": "independent", "quote": "yapay zeka algoritmasının hasta daha MR cihazındayken 5-10 saniye arasında değişen sürelerde çekilen beyin MR'ında anormal bir durum içerip içermediğini değerlendirmeyi başardığını" }, { "kind": "news report", "citation": "Habertürk, from Anadolu Ajansı (2023). Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti [Patient whose life was saved by AI's early warning enters medical history]. Habertürk, Health, 23 May 2023, byline Anadolu Ajansı; identifies the patient as a 46-year-old woman, quotes Çeltikçi on the phone alert and Sağıroğlu on over 1,000 abnormal findings reported from the hospital's three MRI scanners and a pledge to install the system free in all public hospitals.", "title": "Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti", "url": "https://www.haberturk.com/yapay-zekanin-erken-uyariyla-hayatini-kurtardigi-hasta-3593925", "date": "2023-05-23", "written_by": "independent", "quote": "Telefona baktığımızda yapay zekanın hastamızın beyninin ciddi bir kısmında beyin ödemi ve tümör tespiti yaptığına dair mesaj gördük. Doktorlarımız hemen harekete geçti ve gerekli önlemleri aldı." } ], "replication": { "produced_by": [ "A region-based convolutional neural network object-detection algorithm trained on a brain MRI data set built within the Turkish Brain Project. Anadolu Agency: six months of training on stroke, hemorrhage and tumor cases.", "Integration into the hospital network so MRI images are processed as they are acquired. Anadolu Agency reports evaluation within 5–10 seconds on the hospital's three MRI scanners.", "An alert channel to the physicians' mobile phones, reported by Anadolu Agency as a GSM operator's picture-message service carrying the segmented abnormal regions", "A neurosurgery team that reads the alert at once and can admit and biopsy the patient within a day" ], "must_hold": [ "The lesion is of a kind the model was trained on (the team names stroke, hemorrhage and tumor)", "The alert reaches a physician who acts on it before the routine radiology report", "The hospital can schedule a biopsy or operation promptly", "False alerts stay low enough that physicians keep trusting the messages. Anadolu Agency quotes Sağıroğlu that the system had reported over 1,000 abnormal findings and physicians work closely with it because they trust it." ], "echoes": [] }, "paired_incident": null, "headline": "Turkish Brain Project algorithm flags a glioma mid-scan at Gazi", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The May 2023 Turkish press coverage reported the published case; no later development in the patient's treatment or the algorithm's deployment was found.", "quote": null, "url": null }, "value": null, "developer_country": "Turkey", "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-05-20-a638", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Gazi_University; https://en.wikipedia.org/wiki/Gazi_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Gazi University.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and two case reports from the makers. 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Flagging this patient's tumor mid-scan is that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-10-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-05-20-a638", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Gazi_University; https://en.wikipedia.org/wiki/Gazi_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Gazi University.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A region-based convolutional neural network object-detection algorithm trained on a brain MRI data set built within the Turkish Brain Project. 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Anadolu Agency quotes Sağıroğlu that the system had reported over 1,000 abnormal findings and physicians work closely with it because they trust it." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-05-20-a638", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Gazi_University; https://en.wikipedia.org/wiki/Gazi_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Gazi University.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - neurosurgery / brain MRI", "segment": "Hospital real-time MRI anomaly alerting (academic, non-commercial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Sozer A, Borcek AO, Sagiroglu S, Poshtkouh A, Demirtas Z, Karaaslan MM, Kuzucu P, Celtikci E (2023). The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case. Journal of Neurosurgery: Case Lessons 5(19): CASE22536, published 8 May 2023, doi:10.3171/CASE22536, PMID 37158388, PMCID PMC10550689, CC BY-NC-ND 4.0. All authors at Gazi University; their team built and deployed the algorithm, so marked as maker-authored.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://doi.org/10.3171/CASE22536", "date": "2023-05-08", "written_by": "makers", "quote": "detected by an AI algorithm running on real-time patient data while the patient was still in the MRI scanner" }, { "kind": "case report", "citation": "Sozer A et al. (2023). Journal of Neurosurgery: Case Lessons 5(19): CASE22536 (second quotation, on the operation; the case narrative dates the alert to October 2022, the biopsy to the following day, and the pathology to an isocitrate dehydrogenase wild-type diffuse glioma). Open-access copy at PubMed Central.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10550689/", "date": "2023-05-08", "written_by": "makers", "quote": "The day after MRI, a stereotactic biopsy was performed." }, { "kind": "news report", "citation": "TRT Haber, from Anadolu Agency (2023). Tıp tarihinde ilk: Yapay zeka hayat kurtardı [A first in medical history: artificial intelligence saved a life]. TRT Haber, Health, 22 May 2023, source credited as AA; quotes Assoc. Prof. Emrah Çeltikçi and Prof. Şeref Sağıroğlu of Gazi University on the 5-10 second evaluation, the phone alerts and the six-month training.", "title": "Tıp tarihinde ilk: Yapay zeka hayat kurtardı", "url": "https://www.trthaber.com/haber/saglik/tip-tarihinde-ilk-yapay-zeka-hayat-kurtardi-769140.html", "date": "2023-05-22", "written_by": "independent", "quote": "yapay zeka algoritmasının hasta daha MR cihazındayken 5-10 saniye arasında değişen sürelerde çekilen beyin MR'ında anormal bir durum içerip içermediğini değerlendirmeyi başardığını" }, { "kind": "news report", "citation": "Habertürk, from Anadolu Ajansı (2023). Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti [Patient whose life was saved by AI's early warning enters medical history]. Habertürk, Health, 23 May 2023, byline Anadolu Ajansı; identifies the patient as a 46-year-old woman, quotes Çeltikçi on the phone alert and Sağıroğlu on over 1,000 abnormal findings reported from the hospital's three MRI scanners and a pledge to install the system free in all public hospitals.", "title": "Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti", "url": "https://www.haberturk.com/yapay-zekanin-erken-uyariyla-hayatini-kurtardigi-hasta-3593925", "date": "2023-05-23", "written_by": "independent", "quote": "Telefona baktığımızda yapay zekanın hastamızın beyninin ciddi bir kısmında beyin ödemi ve tümör tespiti yaptığına dair mesaj gördük. Doktorlarımız hemen harekete geçti ve gerekli önlemleri aldı." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0117-source-0001", "AIBD-0117-source-0002", "AIBD-0117-source-0003", "AIBD-0117-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Sozer A, Borcek AO, Sagiroglu S, Poshtkouh A, Demirtas Z, Karaaslan MM, Kuzucu P, Celtikci E (2023). The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case. Journal of Neurosurgery: Case Lessons 5(19): CASE22536, published 8 May 2023, doi:10.3171/CASE22536, PMID 37158388, PMCID PMC10550689, CC BY-NC-ND 4.0. All authors at Gazi University; their team built and deployed the algorithm, so marked as maker-authored.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://doi.org/10.3171/CASE22536", "date": "2023-05-08", "written_by": "makers", "quote": "detected by an AI algorithm running on real-time patient data while the patient was still in the MRI scanner" }, { "kind": "case report", "citation": "Sozer A et al. (2023). Journal of Neurosurgery: Case Lessons 5(19): CASE22536 (second quotation, on the operation; the case narrative dates the alert to October 2022, the biopsy to the following day, and the pathology to an isocitrate dehydrogenase wild-type diffuse glioma). Open-access copy at PubMed Central.", "title": "The first case of glioma detected by an artificial intelligence algorithm running on real-time data in neurosurgery: illustrative case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10550689/", "date": "2023-05-08", "written_by": "makers", "quote": "The day after MRI, a stereotactic biopsy was performed." }, { "kind": "news report", "citation": "TRT Haber, from Anadolu Agency (2023). Tıp tarihinde ilk: Yapay zeka hayat kurtardı [A first in medical history: artificial intelligence saved a life]. TRT Haber, Health, 22 May 2023, source credited as AA; quotes Assoc. Prof. Emrah Çeltikçi and Prof. Şeref Sağıroğlu of Gazi University on the 5-10 second evaluation, the phone alerts and the six-month training.", "title": "Tıp tarihinde ilk: Yapay zeka hayat kurtardı", "url": "https://www.trthaber.com/haber/saglik/tip-tarihinde-ilk-yapay-zeka-hayat-kurtardi-769140.html", "date": "2023-05-22", "written_by": "independent", "quote": "yapay zeka algoritmasının hasta daha MR cihazındayken 5-10 saniye arasında değişen sürelerde çekilen beyin MR'ında anormal bir durum içerip içermediğini değerlendirmeyi başardığını" }, { "kind": "news report", "citation": "Habertürk, from Anadolu Ajansı (2023). Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti [Patient whose life was saved by AI's early warning enters medical history]. Habertürk, Health, 23 May 2023, byline Anadolu Ajansı; identifies the patient as a 46-year-old woman, quotes Çeltikçi on the phone alert and Sağıroğlu on over 1,000 abnormal findings reported from the hospital's three MRI scanners and a pledge to install the system free in all public hospitals.", "title": "Yapay zekanın erken uyarıyla hayatını kurtardığı hasta tıp tarihine geçti", "url": "https://www.haberturk.com/yapay-zekanin-erken-uyariyla-hayatini-kurtardigi-hasta-3593925", "date": "2023-05-23", "written_by": "independent", "quote": "Telefona baktığımızda yapay zekanın hastamızın beyninin ciddi bir kısmında beyin ödemi ve tümör tespiti yaptığına dair mesaj gördük. Doktorlarımız hemen harekete geçti ve gerekli önlemleri aldı." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Real-time MRI algorithm at Gazi University Hospital alerted doctors to a 46-year-old woman's glioma mid-scan; biopsy next day, Oct 2022.", "account": "In October 2022, a 46-year-old woman with a nonspecific headache had brain magnetic resonance imaging (MRI). This was at Gazi University Faculty of Medicine Hospital, Ankara. A region-based convolutional neural network algorithm, built within the Turkish Brain Project and running on the hospital network in real time, detected an intraparenchymal mass. It alerted the research team while she was still in the scanner. Physicians read the images, judged the finding consistent with a diffuse glioma and admitted her. A stereotactic biopsy next day confirmed an isocitrate dehydrogenase wild-type diffuse glioma; she was referred to oncology for immediate treatment. The case was published 8 May 2023 and reported by Anadolu Agency 22 May 2023." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Turkish Brain Project real-time brain MRI alert system at Gazi University: a region-based convolutional neural network object-detection algorithm integrated into the hospital network, which processes MRI images in real time; Anadolu Agency reports that it evaluates a brain MRI within 5-10 seconds while the patient is still in the scanner and sends the physicians' mobile phones a message with the abnormal regions segmented, through a GSM operator's picture-message service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Gazi University, Ankara (Department of Neurosurgery and Department of Computer Engineering), within the Turkish Brain Project funded by the Presidency of the Republic of Türkiye, with the Presidency's Digital Transformation Office credited for the model's development" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Gazi University's Turkish Brain Project algorithm flags a glioma on a 46-year-old woman's brain MRI while she is still in the scanner; physicians alerted at once, stereotactic biopsy the next day", "headline": "Turkish Brain Project algorithm flags a glioma mid-scan at Gazi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f2fd1ed0ddbe798b29eb836010ea3eb5a85f89930bbcca87cfd07756f879965d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In October 2022, a 46-year-old woman with a nonspecific headache had brain magnetic resonance imaging (MRI). This was at Gazi University Faculty of Medicine Hospital, Ankara. A region-based convolutional neural network algorithm, built within the Turkish Brain Project and running on the hospital network in real time, detected an intraparenchymal mass. It alerted the research team while she was still in the scanner. Physicians read the images, judged the finding consistent with a diffuse glioma and admitted her. A stereotactic biopsy next day confirmed an isocitrate dehydrogenase wild-type diffuse glioma; she was referred to oncology for immediate treatment. The case was published 8 May 2023 and reported by Anadolu Agency 22 May 2023.", "replication": { "produced_by": [ "A region-based convolutional neural network object-detection algorithm trained on a brain MRI data set built within the Turkish Brain Project. Anadolu Agency: six months of training on stroke, hemorrhage and tumor cases.", "Integration into the hospital network so MRI images are processed as they are acquired. Anadolu Agency reports evaluation within 5–10 seconds on the hospital's three MRI scanners.", "An alert channel to the physicians' mobile phones, reported by Anadolu Agency as a GSM operator's picture-message service carrying the segmented abnormal regions", "A neurosurgery team that reads the alert at once and can admit and biopsy the patient within a day" ], "must_hold": [ "The lesion is of a kind the model was trained on (the team names stroke, hemorrhage and tumor)", "The alert reaches a physician who acts on it before the routine radiology report", "The hospital can schedule a biopsy or operation promptly", "False alerts stay low enough that physicians keep trusting the messages. Anadolu Agency quotes Sağıroğlu that the system had reported over 1,000 abnormal findings and physicians work closely with it because they trust it." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0020", "title": "AlphaTensor discovers faster matrix multiplication algorithms over GF(2), immediately built upon by independent mathematicians", "summary": "AlphaTensor found a 47-multiplication 4x4 scheme over GF(2) and a 96 for 5x5; Kauers and Moosbauer improved the latter to 95.", "date_observed": "2022-10-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 5 October 2022 Nature published AlphaTensor, a reinforcement-learning system from DeepMind (Fawzi, Balog, Huang, Hubert, Romera-Paredes and others). It treats the search for matrix multiplication algorithms as a one-player game, TensorGame. A deep neural network guides a planning procedure derived from AlphaZero. It found an algorithm multiplying two 4x4 matrices over the field with two elements in 47 multiplications. That beat Strassen's two-level algorithm for the first time in about 50 years. It also found a 96-multiplication scheme for 5x5 matrices over that field. On 8 October 2022 Manuel Kauers and Jakob Moosbauer posted a preprint, revised on 13 October. It started from the published 5x5 scheme and improved it to 95 multiplications.", "category": "benefit created", "unexpected": false, "purpose": "Built to discover matrix multiplication algorithms by searching for low-rank tensor decompositions; the new schemes were that purpose.", "system": "AlphaTensor (AlphaZero-derived reinforcement learning for tensor decomposition)", "model_version": null, "developer": "DeepMind", "deployer": "DeepMind", "location": "London, United Kingdom", "domain": "Mathematics / algorithmic complexity", "segment": "Industrial research laboratory", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "Researchers in algebraic complexity gained new explicit decompositions that were improved upon within a week by Kauers and Moosbauer. The gains are field-restricted. Nature reports the 4x4 improvement for matrices “in a finite field” and Kauers and Moosbauer give the 5x5 record of 96 multiplications over Z2." } ], "ai_role": { "status": "assessed", "statement": "The reinforcement-learning agent found the decompositions, which are explicit and checkable. The independent preprint treats the 96-multiplication 5x5 result as established and improves it, which corroborates the result's existence. The 47-multiplication 4x4 scheme rests on the vendor paper's published decomposition." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Fawzi, A. et al. (2022). Discovering faster matrix multiplication algorithms with reinforcement learning. 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The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story. arXiv:2210.04045.", "title": "The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story", "url": "https://arxiv.org/abs/2210.04045", "date": "2022-10-08", "written_by": "independent", "quote": "In response to a recent Nature article which announced an algorithm for multiplying 5×5-matrices over ℤ₂ with only 96 multiplications, two fewer than the previous record" } ], "replication": { "produced_by": [ "Formulation of algorithm discovery as a tensor-decomposition game", "Neural-network-guided search with exact verification of each decomposition", "Publication of explicit decompositions that others can check and extend" ], "must_hold": [ "Decompositions must be verified exactly over the stated ring or field", "Independent reproduction or extension by researchers outside the vendor" ], "echoes": [ { "date": "2025-05-14", "setting": "AlphaEvolve (Google DeepMind) found a scheme multiplying 4x4 complex-valued matrices in 48 scalar multiplications; Dumas, Pernet and Sedoglavic (arXiv:2506.13242, submitted 16 June 2025) derived a 48-multiplication scheme with rational coefficients from AlphaEvolve's complex-valued decomposition, valid over any ring except characteristic 2", "model_version": "AlphaEvolve", "outcome": "recurred", "source": "https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/ ; https://arxiv.org/abs/2506.13242" } ] }, "paired_incident": null, "headline": "AlphaTensor finds a 47-multiplication 4x4 scheme over GF(2)", "metric": "multiplying two 4x4 matrices over the field with two elements in 47 multiplications", "comparator": null, "later": { "status": "persisted", "date": "2022-10-08", "note": "Three days after publication, Kauers and Moosbauer took AlphaTensor's 96-multiplication 5x5 scheme over Z2 as a starting point and improved it to 95, confirming and extending the result.", "quote": "In response to a recent Nature article which announced an algorithm for multiplying 5×5-matrices over ℤ2 with only 96 multiplications, two fewer than the previous record, we present an algorithm that does the job with only 95 multiplications.", "url": "https://arxiv.org/abs/2210.04045" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced the stitched Nature quote with the abstract sentence as printed, corrected the AlphaEvolve echo to say that the rational 48-multiplication scheme was projected from AlphaEvolve's complex-valued decomposition rather than derived independently, and confined the societal rating reason to what the cited sources state.", "source": "https://www.nature.com/articles/s41586-022-05172-4 ; https://arxiv.org/abs/2506.13242 ; https://arxiv.org/abs/2210.04045", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://arxiv.org/abs/2210.04045", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://en.wikipedia.org/wiki/Google_DeepMind", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent preprint and the makers' peer-reviewed study. 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https://arxiv.org/abs/2506.13242 ; https://arxiv.org/abs/2210.04045", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://arxiv.org/abs/2210.04045", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://en.wikipedia.org/wiki/Google_DeepMind", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Mathematics / algorithmic complexity", "segment": "Industrial research laboratory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story. arXiv:2210.04045.", "title": "The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story", "url": "https://arxiv.org/abs/2210.04045", "date": "2022-10-08", "written_by": "independent", "quote": "In response to a recent Nature article which announced an algorithm for multiplying 5×5-matrices over ℤ₂ with only 96 multiplications, two fewer than the previous record" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0020-source-0001", "AIBD-0020-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Fawzi, A. et al. 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The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story. arXiv:2210.04045.", "title": "The FBHHRBNRSSSHK-Algorithm for Multiplication in Z2^(5x5) is still not the end of the story", "url": "https://arxiv.org/abs/2210.04045", "date": "2022-10-08", "written_by": "independent", "quote": "In response to a recent Nature article which announced an algorithm for multiplying 5×5-matrices over ℤ₂ with only 96 multiplications, two fewer than the previous record" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AlphaTensor found a 47-multiplication 4x4 scheme over GF(2) and a 96 for 5x5; Kauers and Moosbauer improved the latter to 95.", "account": "On 5 October 2022 Nature published AlphaTensor, a reinforcement-learning system from DeepMind (Fawzi, Balog, Huang, Hubert, Romera-Paredes and others). It treats the search for matrix multiplication algorithms as a one-player game, TensorGame. A deep neural network guides a planning procedure derived from AlphaZero. It found an algorithm multiplying two 4x4 matrices over the field with two elements in 47 multiplications. That beat Strassen's two-level algorithm for the first time in about 50 years. It also found a 96-multiplication scheme for 5x5 matrices over that field. On 8 October 2022 Manuel Kauers and Jakob Moosbauer posted a preprint, revised on 13 October. It started from the published 5x5 scheme and improved it to 95 multiplications." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AlphaTensor (AlphaZero-derived reinforcement learning for tensor decomposition)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AlphaTensor discovers faster matrix multiplication algorithms over GF(2), immediately built upon by independent mathematicians", "headline": "AlphaTensor finds a 47-multiplication 4x4 scheme over GF(2)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "36e53663ce0d1cbad7bd182ff4516c9b74755751a816e98423dbf0c57bf9a160" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 5 October 2022 Nature published AlphaTensor, a reinforcement-learning system from DeepMind (Fawzi, Balog, Huang, Hubert, Romera-Paredes and others). It treats the search for matrix multiplication algorithms as a one-player game, TensorGame. A deep neural network guides a planning procedure derived from AlphaZero. It found an algorithm multiplying two 4x4 matrices over the field with two elements in 47 multiplications. That beat Strassen's two-level algorithm for the first time in about 50 years. It also found a 96-multiplication scheme for 5x5 matrices over that field. On 8 October 2022 Manuel Kauers and Jakob Moosbauer posted a preprint, revised on 13 October. It started from the published 5x5 scheme and improved it to 95 multiplications.", "replication": { "produced_by": [ "Formulation of algorithm discovery as a tensor-decomposition game", "Neural-network-guided search with exact verification of each decomposition", "Publication of explicit decompositions that others can check and extend" ], "must_hold": [ "Decompositions must be verified exactly over the stated ring or field", "Independent reproduction or extension by researchers outside the vendor" ], "echoes": [ { "date": "2025-05-14", "setting": "AlphaEvolve (Google DeepMind) found a scheme multiplying 4x4 complex-valued matrices in 48 scalar multiplications; Dumas, Pernet and Sedoglavic (arXiv:2506.13242, submitted 16 June 2025) derived a 48-multiplication scheme with rational coefficients from AlphaEvolve's complex-valued decomposition, valid over any ring except characteristic 2", "model_version": "AlphaEvolve", "outcome": "recurred", "source": "https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/ ; https://arxiv.org/abs/2506.13242" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0228", "title": "INEC's Automated Biometric Identification System invalidates 2,780,756 ineligible voter registrations (22.6%) before Nigeria's 2023 election", "summary": "INEC chairman Mahmood Yakubu reported on 26 Oct 2022 that ABIS cleaning of 2021–22 registrations identified 2,780,756 (22.6%) double, underage or fake entries, leaving 9,518,188 valid new registrants.", "date_observed": "2022-10-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The date is that of Professor Mahmood Yakubu's address to political parties in Abuja, reproduced by the Nigerian Democratic Report. He said the Continuous Voter Registration data (28 June 2021 to 31 July 2022) was cleaned with the Automated Biometric Identification System (ABIS). This identified 2,780,756 registrations (22.6%) as ineligible and invalidated them. Among them were double or multiple registrants, underage persons and fake registrations failing INEC's business rules. That left 9,518,188 valid post-ABIS registrations; 23 registration officers were identified for sanctions. On 12 September 2022, INEC commissioner Festus Okoye said 1,126,359 of 2,523,458 registrants (28 June 2021 to 14 January 2022) were found invalid and delisted. ABIS processing of later registrations was ongoing (Punch). BusinessDay later argued that some fake and underage registrants evaded ABIS and that invalidation rates were regionally lopsided. The vendor of ABIS is not named in the sources.", "category": "benefit created", "unexpected": false, "purpose": "De-duplicate and validate biometric voter registrations (fingerprints and faces) to remove double, multiple, underage and fake entries from the national register.", "system": "Automated Biometric Identification System (ABIS)", "model_version": null, "developer": "Not named in the sources", "deployer": "Independent National Electoral Commission (INEC), Nigeria", "location": null, "domain": "Electoral integrity / voter registration", "segment": "Government", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 3, "reason": "2,780,756 ineligible entries (22.6% of new registrations) were removed from the register used for the 2023 general election, per INEC's chairman. BusinessDay disputes completeness and regional balance." }, { "group": "organizational", "depth": 2, "reason": "INEC obtained a cleaned register and identified 23 of its own officers for sanctions over multiple registrations." } ], "ai_role": { "status": "assessed", "statement": "The figures come from INEC's own statements (the deployer) relayed by two Nigerian outlets, not from an audit. INEC's website could not be searched. ABIS's matching method, error rates and the share of invalidations due to biometrics versus business rules are not stated. BusinessDay's critique (registrants evading ABIS; 49.3% of invalidations from two regions) is included as a limit." }, "evidence": [ { "kind": "news report", "citation": "Akindele Orimolade, Nigerian Democratic Report, 26 Oct 2022 (reproducing INEC chairman's address)", "title": "Nigeria’s Voter Register Hits 93.5 million as 12m New Registrants Are Added", "url": "https://www.ndr.org.ng/nigerias-voter-register-hits-93-5-million-as-12m-new-registrants-are-added/", "date": "2022-10-26", "written_by": "independent", "quote": "a total of 2,780,756 (22.6%) were identified as ineligible registrants and invalidated from the record" }, { "kind": "news report", "citation": "Donatus Anichukwueze, Punch, 13 Sep 2022", "title": "Double registration: INEC delists 1.1m newly registered voters", "url": "https://punchng.com/double-registration-inec-delists-1-1m-newly-registered-voters/", "date": "2022-09-13", "written_by": "independent", "quote": "cleaning up of the register of voters using the Automated Biometric Identification System (ABIS) is ongoing" }, { "kind": "news report", "citation": "BusinessDay, 20 Jan 2023", "title": "Eight questions INEC must answer Before the first ballot is cast", "url": "https://businessday.ng/uncategorized/article/eight-questions-inec-must-answer-before-the-first-ballot-is-cast/", "date": "2023-01-20", "written_by": "independent", "quote": "Yet, those registrants found a way to evade the prying eyes of the ABIS and made it successfully to the voter register." } ], "replication": { "produced_by": [ "Biometric capture (fingerprints, face) at registration with a central de-duplication pass", "Business rules defining ineligible entries applied after matching", "Public display of the register for claims and objections" ], "must_hold": [ "Biometric capture quality adequate for matching", "Independent audit of matching accuracy (absent here)", "Officers unable to bypass capture protocols" ], "echoes": [ { "date": "2022-09-12", "setting": "Earlier CVR phase (28 Jun 2021 to 14 Jan 2022): 1,126,359 of 2,523,458 registrations invalidated", "model_version": null, "outcome": "recurred", "source": "https://punchng.com/double-registration-inec-delists-1-1m-newly-registered-voters/" } ] }, "paired_incident": null, "headline": "INEC's ABIS invalidates 2,780,756 ineligible voter registrations", "metric": "2,780,756 registrations (22.6%) were identified as ineligible and invalidated", "comparator": { "against": "the raw Continuous Voter Registration data before ABIS cleaning", "before": "12,298,944 Nigerians successfully completed the registration as new voters", "after": "the number of valid registrations (post-ABIS) is 9,518,188", "basis": "measured", "quote": "After a rigorous cleaning-up of the data using the Automated Biometric Identification System (ABIS), a total of 2,780,756 (22.6%) were identified as ineligible registrants and invalidated from the record", "url": "https://www.ndr.org.ng/nigerias-voter-register-hits-93-5-million-as-12m-new-registrants-are-added/" }, "later": { "status": "reversed", "date": "2023-01-20", "note": "A BusinessDay analysis argued that fake and underage registrants had nonetheless reached the final register and that invalidation rates were lopsided by region, a press critique rather than an official reversal.", "quote": "Yet, those registrants found a way to evade the prying eyes of the ABIS and made it successfully to the voter register.", "url": "https://businessday.ng/uncategorized/article/eight-questions-inec-must-answer-before-the-first-ballot-is-cast/" }, "value": null, "developer_country": null, "deployer_country": "Nigeria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.ndr.org.ng/nigerias-voter-register-hits-93-5-million-as-12m-new-registrants-are-added/; https://businessday.ng/uncategorized/article/eight-questions-inec-must-answer-before-the-first-ballot-is-cast/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Independent_National_Electoral_Commission_(Nigeria)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0228", "catalog_version": "1.0.0", "source_fingerprint": "5a044b42ea970ffac0e746064eb4422c05448688f59ddb7a4c03ba5cbc9d0a68", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0228-source-0001", "AIBD-0228-source-0002", "AIBD-0228-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not named in the sources", "deployer": "Independent National Electoral Commission (INEC), Nigeria" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The figures come from INEC's own statements (the deployer) relayed by two Nigerian outlets, not from an audit. INEC's website could not be searched. ABIS's matching method, error rates and the share of invalidations due to biometrics versus business rules are not stated. BusinessDay's critique (registrants evading ABIS; 49.3% of invalidations from two regions) is included as a limit." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The figures come from INEC's own statements (the deployer) relayed by two Nigerian outlets, not from an audit. INEC's website could not be searched. ABIS's matching method, error rates and the share of invalidations due to biometrics versus business rules are not stated. BusinessDay's critique (registrants evading ABIS; 49.3% of invalidations from two regions) is included as a limit." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "2,780,756 ineligible entries (22.6% of new registrations) were removed from the register used for the 2023 general election, per INEC's chairman. 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "INEC chairman Mahmood Yakubu reported on 26 Oct 2022 that ABIS cleaning of 2021–22 registrations identified 2,780,756 (22.6%) double, underage or fake entries, leaving 9,518,188 valid new registrants.", "account": "The date is that of Professor Mahmood Yakubu's address to political parties in Abuja, reproduced by the Nigerian Democratic Report. He said the Continuous Voter Registration data (28 June 2021 to 31 July 2022) was cleaned with the Automated Biometric Identification System (ABIS). This identified 2,780,756 registrations (22.6%) as ineligible and invalidated them. Among them were double or multiple registrants, underage persons and fake registrations failing INEC's business rules. That left 9,518,188 valid post-ABIS registrations; 23 registration officers were identified for sanctions. On 12 September 2022, INEC commissioner Festus Okoye said 1,126,359 of 2,523,458 registrants (28 June 2021 to 14 January 2022) were found invalid and delisted. ABIS processing of later registrations was ongoing (Punch). BusinessDay later argued that some fake and underage registrants evaded ABIS and that invalidation rates were regionally lopsided. The vendor of ABIS is not named in the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Automated Biometric Identification System (ABIS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "INEC's Automated Biometric Identification System invalidates 2,780,756 ineligible voter registrations (22.6%) before Nigeria's 2023 election", "headline": "INEC's ABIS invalidates 2,780,756 ineligible voter registrations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5a044b42ea970ffac0e746064eb4422c05448688f59ddb7a4c03ba5cbc9d0a68" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The date is that of Professor Mahmood Yakubu's address to political parties in Abuja, reproduced by the Nigerian Democratic Report. He said the Continuous Voter Registration data (28 June 2021 to 31 July 2022) was cleaned with the Automated Biometric Identification System (ABIS). This identified 2,780,756 registrations (22.6%) as ineligible and invalidated them. Among them were double or multiple registrants, underage persons and fake registrations failing INEC's business rules. That left 9,518,188 valid post-ABIS registrations; 23 registration officers were identified for sanctions. On 12 September 2022, INEC commissioner Festus Okoye said 1,126,359 of 2,523,458 registrants (28 June 2021 to 14 January 2022) were found invalid and delisted. ABIS processing of later registrations was ongoing (Punch). BusinessDay later argued that some fake and underage registrants evaded ABIS and that invalidation rates were regionally lopsided. The vendor of ABIS is not named in the sources.", "replication": { "produced_by": [ "Biometric capture (fingerprints, face) at registration with a central de-duplication pass", "Business rules defining ineligible entries applied after matching", "Public display of the register for claims and objections" ], "must_hold": [ "Biometric capture quality adequate for matching", "Independent audit of matching accuracy (absent here)", "Officers unable to bypass capture protocols" ], "echoes": [ { "date": "2022-09-12", "setting": "Earlier CVR phase (28 Jun 2021 to 14 Jan 2022): 1,126,359 of 2,523,458 registrations invalidated", "outcome": "recurred", "source": "https://punchng.com/double-registration-inec-delists-1-1m-newly-registered-voters/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0098", "title": "Philippine Red Cross activated its typhoon Early Action Protocol on 510's machine-learning impact forecast before Storm Nalgae (October 2022)", "summary": "510 ML impact forecast hit the trigger on 27 October 2022; PRC installed shelter kits for 78 Aurora households before Storm Nalgae", "date_observed": "2022-10-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Philippine Red Cross (PRC) approved its Early Action Protocol (EAP) for typhoons in December 2019. Its impact-based forecasting (IBF) model, developed with 510 (Netherlands Red Cross), applies machine learning (ML) to predict housing damage per municipality from typhoon forecasts. As Tropical Storm Paeng (Nalgae) approached on 27 October 2022, the 510/IBF forecast projected up to 10 percent shelter damage in priority municipalities. That hit the trigger at 56 hours' lead time. With IFRC anticipatory DREF funds, PRC activated it in Aurora Province. On 27 to 29 October, 40 workers distributed and installed shelter strengthening kits for 78 of 100 planned households in Dipaculao before landfall. PRC's post-storm survey reports all 78 kits installed, 390 people reached. CHF 7,002 of the CHF 117,555 budget was spent.", "category": "protective response", "unexpected": false, "purpose": "Forecast typhoon housing damage per municipality to trigger pre-agreed early actions before landfall.", "system": "510 impact-based forecasting (IBF) model for typhoons in the Philippines, operated through the 510 dashboard with PAGASA forecasts", "model_version": "eXtreme Gradient Boosting (XGBoost)", "developer": "510, an initiative of the Netherlands Red Cross, with the Philippine Red Cross and German Red Cross", "deployer": "Philippine Red Cross, with IFRC anticipatory DREF funding", "location": "Dipaculao, Aurora Province, Philippines", "domain": "Disaster risk reduction and forecast-based financing", "segment": "Red Cross National Society", "benefit_type": "Reduced Risk", "taxonomy_note": "Shelter reinforcement before the storm reduces potential harm, but the post-storm survey gives no counterfactual.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "78 households had roofs and walls reinforced before landfall. PRC reports they mitigated wind impact (implementer survey, no counterfactual)." }, { "group": "organizational", "depth": 1, "reason": "First completed activation of the Philippine typhoon EAP. Lessons on lead time and weather constraints documented in the final report." }, { "group": "societal", "depth": 1, "reason": "Small scale: 390 people reached in one municipality." } ], "ai_role": { "status": "assessed", "statement": "The ML impact forecast was the trigger. Under the EAP, early actions fire on the forecast wind impact on housing 72 hours before landfall. The trigger: at least 10% of houses totally damaged in more than three municipalities. The notification records the Aurora municipalities as “Met (More than 10%)”. The 72-hour lead-time condition was not met. The final report says the 56-hour lead time was exceptionally granted. The notification says the projection came from the 510/IBF forecast incorporating PAGASA data. PRC staff confirmed chapter capacity and chose municipalities. The outcome claim is PRC's own post-storm survey. The NHESS paper and EGU abstract on the model have 510 staff as co-authors, not lead authors." }, "evidence": [ { "kind": "report", "citation": "IFRC and Philippine Red Cross (2022). Early Action Protocol Activation Notification: Philippines - Typhoons (EAP2019PH01, MDRPH049).", "title": "EAP Activation Notification, Philippines Typhoons (EAP2019PH01)", "url": "https://adore.ifrc.org/Download.aspx?FileId=590819", "date": "2022-10-27", "written_by": "deployer", "quote": "shelter damages are projected up to 10 per cent in different municipalities in the priority areas under the Early Action Protocol (EAP) for typhoon" }, { "kind": "report", "citation": "IFRC and Philippine Red Cross (2023). Early Action Protocol Activation Final Report: Philippines, Typhoon Paeng (MDRPH049). Dated 30 June 2023; PDF file timestamp 18 January 2024.", "title": "Early Action Protocol Activation Final Report, Philippines Typhoon Paeng", "url": "https://go-api.ifrc.org/api/DownloadFile/67581/MDRPH049eapfr", "date": "2023-06-30", "written_by": "deployer", "quote": "Despite of the challenges, 100 percent of 78 households who received the kits were successfully installed/reinforced." }, { "kind": "peer-reviewed study", "citation": "Kooshki Forooshani, M., van den Homberg, M., Kalimeri, K., Kaltenbrunner, A., Mejova, Y., Milano, L., et al. (2024). Towards a global impact-based forecasting model for tropical cyclones. Natural Hazards and Earth System Sciences 24, 309–329.", "title": "Towards a global impact-based forecasting model for tropical cyclones", "url": "https://nhess.copernicus.org/articles/24/309/2024/", "date": "2024-02-01", "written_by": "makers", "quote": "In 2019, the 510 model was approved as the trigger model for the early action protocol for typhoons" }, { "kind": "other", "citation": "Free, R., van den Homberg, M., Sperna Weiland, F., Teklesadik, A., Melillo, M., Bogaard, T. (2022). Extending a ML impact-based forecasting model for typhoons in the Philippines with a rainfall threshold for consecutive landslide events. EGU General Assembly 2022, EGU22-10474.", "title": "Extending a ML impact-based forecasting model for typhoons in the Philippines with a rainfall threshold for consecutive landslide events", "url": "https://meetingorganizer.copernicus.org/EGU22/EGU22-10474.html", "date": "2022-05-23", "written_by": "makers", "quote": "An impact-based forecasting model for typhoons currently operational in the Philippines predicts impact due to the high wind speeds associated with typhoons" } ], "replication": { "produced_by": [ "510 IBF damage model fed by PAGASA typhoon forecasts", "Pre-approved EAP with a 10% projected-damage trigger", "IFRC anticipatory DREF funds released on trigger", "Pre-positioned shelter kits, trained carpenters and pre-identified households" ], "must_hold": [ "Lead time near 72 hours", "Forecast track and intensity accuracy", "Weather permitting installation before landfall", "Local government authorization in no-build zones" ], "echoes": [ { "date": "2019-11-30", "setting": "Typhoon Kammuri 2019: EAP newly approved; IFRC DREF noted the forecast-based trigger might not yet be reached", "model_version": null, "outcome": "unknown", "source": "IFRC DREF MDRPH037, https://adore.ifrc.org/Download.aspx?FileId=271567" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "536", "title": "NJ Transit's Use of Modeling Software Miscalculated Storm Surge Threat Level", "url": "https://incidentdatabase.ai/cite/536", "severity": null, "group": "organizational", "basis": "Storm-impact model used for pre-landfall operational decisions underestimated Sandy's surge and NJ Transit lost equipment; 510's typhoon impact model triggers Red Cross action the same way." }, "headline": "510's ML forecast triggers PRC shelter kits before Storm Nalgae", "metric": "installed shelter kits for 78 Aurora households before Storm Nalgae", "comparator": null, "later": { "status": "persisted", "date": "2023-06-30", "note": "The IFRC final report of 30 June 2023 records all 78 households served and houses reinforced before impact, but a PRC lessons-learned workshop judged the trigger high and recommended reviewing the typhoon EAP.", "quote": "In addition, the trigger was considered high according to the solicited lessons from Paeng Lesson learned Workshop conducted by PRC with the support IFRC. Thus, one of the recommendations gathered is to review and revisit the Typhoon EAP.", "url": "https://go-api.ifrc.org/api/DownloadFile/67581/MDRPH049eapfr" }, "value": null, "developer_country": "Netherlands", "deployer_country": "Philippines", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 536 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/536", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the final report's date to its cover date of 30 June 2023 (18 January 2024 was the PDF file timestamp) and the notification's date to its launch date of 27 October 2022, marked the NHESS paper and EGU abstract independent because 510 staff are co-authors rather than lead authors, and restated the EAP trigger as at least 10% of houses totally damaged in more than three municipalities 72 hours before landfall, with the lead-time condition waived at 56 hours.", "source": "https://go-api.ifrc.org/api/DownloadFile/67581/MDRPH049eapfr; https://adore.ifrc.org/Download.aspx?FileId=590819; https://adore.ifrc.org/Download.aspx?FileId=271567", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://go-api.ifrc.org/api/DownloadFile/67581/MDRPH049eapfr; https://nhess.copernicus.org/articles/24/309/2024/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.rodekruis.nl/contact/; https://en.wikipedia.org/wiki/Philippine_Red_Cross", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' other and two reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0098", "catalog_version": "1.0.0", "source_fingerprint": "4d27685232098c66182082682b2e51601106d680d084eeb7882325e3cdc5c1ac", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0098-source-0001", "AIBD-0098-source-0002", "AIBD-0098-source-0003", "AIBD-0098-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "510, an initiative of the Netherlands Red Cross, with the Philippine Red Cross and German Red Cross", "deployer": "Philippine Red Cross, with IFRC anticipatory DREF funding" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ML impact forecast was the trigger. Under the EAP, early actions fire on the forecast wind impact on housing 72 hours before landfall. The trigger: at least 10% of houses totally damaged in more than three municipalities. The notification records the Aurora municipalities as “Met (More than 10%)”. The 72-hour lead-time condition was not met. The final report says the 56-hour lead time was exceptionally granted. The notification says the projection came from the 510/IBF forecast incorporating PAGASA data. PRC staff confirmed chapter capacity and chose municipalities. The outcome claim is PRC's own post-storm survey. The NHESS paper and EGU abstract on the model have 510 staff as co-authors, not lead authors." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The 510 model forecast that damage to housing would exceed the threshold for early action in Aurora. Its forecasts incorporated data from PAGASA.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The ML impact forecast was the trigger. Under the EAP, early actions fire on the forecast wind impact on housing 72 hours before landfall. The trigger: at least 10% of houses totally damaged in more than three municipalities. The notification records the Aurora municipalities as “Met (More than 10%)”. The 72-hour lead-time condition was not met. The final report says the 56-hour lead time was exceptionally granted. The notification says the projection came from the 510/IBF forecast incorporating PAGASA data. PRC staff confirmed chapter capacity and chose municipalities. The outcome claim is PRC's own post-storm survey. The NHESS paper and EGU abstract on the model have 510 staff as co-authors, not lead authors." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "78 households had roofs and walls reinforced before landfall. PRC reports they mitigated wind impact (implementer survey, no counterfactual)." }, { "group": "organizational", "depth": 1, "reason": "First completed activation of the Philippine typhoon EAP. Lessons on lead time and weather constraints documented in the final report." }, { "group": "societal", "depth": 1, "reason": "Small scale: 390 people reached in one municipality." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study, the makers' other and two reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "78 households had roofs and walls reinforced before landfall. PRC reports they mitigated wind impact (implementer survey, no counterfactual)." }, { "group": "organizational", "depth": 1, "reason": "First completed activation of the Philippine typhoon EAP. Lessons on lead time and weather constraints documented in the final report." }, { "group": "societal", "depth": 1, "reason": "Small scale: 390 people reached in one municipality." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "78 households had roofs and walls reinforced before landfall. PRC reports they mitigated wind impact (implementer survey, no counterfactual)." }, { "group": "organizational", "depth": 1, "reason": "First completed activation of the Philippine typhoon EAP. Lessons on lead time and weather constraints documented in the final report." }, { "group": "societal", "depth": 1, "reason": "Small scale: 390 people reached in one municipality." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Storm-impact model used for pre-landfall operational decisions underestimated Sandy's surge and NJ Transit lost equipment; 510's typhoon impact model triggers Red Cross action the 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The Philippine Red Cross’s own survey supplies the reported benefits after the storm.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "536", "title": "NJ Transit's Use of Modeling Software Miscalculated Storm Surge Threat Level", "url": "https://incidentdatabase.ai/cite/536", "group": "organizational", "basis": "Storm-impact model used for pre-landfall operational decisions underestimated Sandy's surge and NJ Transit lost equipment; 510's typhoon impact model triggers Red Cross action the same way." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2023-06-30", "note": "The IFRC final report of 30 June 2023 records all 78 households served and houses reinforced before impact, but a PRC lessons-learned workshop judged the trigger high and recommended reviewing the typhoon EAP.", "quote": "In addition, the trigger was considered high according to the solicited lessons from Paeng Lesson learned Workshop conducted by PRC with the support IFRC. 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Dated 30 June 2023; PDF file timestamp 18 January 2024.", "title": "Early Action Protocol Activation Final Report, Philippines Typhoon Paeng", "url": "https://go-api.ifrc.org/api/DownloadFile/67581/MDRPH049eapfr", "date": "2023-06-30", "written_by": "deployer", "quote": "Despite of the challenges, 100 percent of 78 households who received the kits were successfully installed/reinforced." }, { "kind": "peer-reviewed study", "citation": "Kooshki Forooshani, M., van den Homberg, M., Kalimeri, K., Kaltenbrunner, A., Mejova, Y., Milano, L., et al. (2024). Towards a global impact-based forecasting model for tropical cyclones. Natural Hazards and Earth System Sciences 24, 309–329.", "title": "Towards a global impact-based forecasting model for tropical cyclones", "url": "https://nhess.copernicus.org/articles/24/309/2024/", "date": "2024-02-01", "written_by": "makers", "quote": "In 2019, the 510 model was approved as the trigger model for the early action protocol for typhoons" }, { "kind": "other", "citation": "Free, R., van den Homberg, M., Sperna Weiland, F., Teklesadik, A., Melillo, M., Bogaard, T. (2022). Extending a ML impact-based forecasting model for typhoons in the Philippines with a rainfall threshold for consecutive landslide events. EGU General Assembly 2022, EGU22-10474.", "title": "Extending a ML impact-based forecasting model for typhoons in the Philippines with a rainfall threshold for consecutive landslide events", "url": "https://meetingorganizer.copernicus.org/EGU22/EGU22-10474.html", "date": "2022-05-23", "written_by": "makers", "quote": "An impact-based forecasting model for typhoons currently operational in the Philippines predicts impact due to the high wind speeds associated with typhoons" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "510 ML impact forecast hit the trigger on 27 October 2022; PRC installed shelter kits for 78 Aurora households before Storm Nalgae", "account": "The Philippine Red Cross (PRC) approved its Early Action Protocol (EAP) for typhoons in December 2019. Its impact-based forecasting (IBF) model, developed with 510 (Netherlands Red Cross), applies machine learning (ML) to predict housing damage per municipality from typhoon forecasts. As Tropical Storm Paeng (Nalgae) approached on 27 October 2022, the 510/IBF forecast projected up to 10 percent shelter damage in priority municipalities. That hit the trigger at 56 hours' lead time. With IFRC anticipatory DREF funds, PRC activated it in Aurora Province. On 27 to 29 October, 40 workers distributed and installed shelter strengthening kits for 78 of 100 planned households in Dipaculao before landfall. PRC's post-storm survey reports all 78 kits installed, 390 people reached. CHF 7,002 of the CHF 117,555 budget was spent." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model forecast damage to housing before a typhoon." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "XGBoost." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "eXtreme Gradient Boosting (XGBoost)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "510 impact-based forecasting (IBF) model for typhoons in the Philippines, operated through the 510 dashboard with PAGASA forecasts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "510, an initiative of the Netherlands Red Cross, with the Philippine Red Cross and German Red Cross" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Philippine Red Cross activated its typhoon Early Action Protocol on 510's machine-learning impact forecast before Storm Nalgae (October 2022)", "headline": "510's ML forecast triggers PRC shelter kits before Storm Nalgae" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4d27685232098c66182082682b2e51601106d680d084eeb7882325e3cdc5c1ac" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Philippine Red Cross (PRC) approved its Early Action Protocol (EAP) for typhoons in December 2019. Its impact-based forecasting (IBF) model, developed with 510 (Netherlands Red Cross), applies machine learning (ML) to predict housing damage per municipality from typhoon forecasts. As Tropical Storm Paeng (Nalgae) approached on 27 October 2022, the 510/IBF forecast projected up to 10 percent shelter damage in priority municipalities. That hit the trigger at 56 hours' lead time. With IFRC anticipatory DREF funds, PRC activated it in Aurora Province. On 27 to 29 October, 40 workers distributed and installed shelter strengthening kits for 78 of 100 planned households in Dipaculao before landfall. PRC's post-storm survey reports all 78 kits installed, 390 people reached. CHF 7,002 of the CHF 117,555 budget was spent.", "replication": { "produced_by": [ "510 IBF damage model fed by PAGASA typhoon forecasts", "Pre-approved EAP with a 10% projected-damage trigger", "IFRC anticipatory DREF funds released on trigger", "Pre-positioned shelter kits, trained carpenters and pre-identified households" ], "must_hold": [ "Lead time near 72 hours", "Forecast track and intensity accuracy", "Weather permitting installation before landfall", "Local government authorization in no-build zones" ], "echoes": [ { "date": "2019-11-30", "setting": "Typhoon Kammuri 2019: EAP newly approved; IFRC DREF noted the forecast-based trigger might not yet be reached", "outcome": "unknown", "source": "IFRC DREF MDRPH037, https://adore.ifrc.org/Download.aspx?FileId=271567" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 35, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0367", "title": "The Palantir-based DAR software identifies the author of an emailed amok threat against Siegen's city administration in fractions of a second and 51 of about 100 participants in a Duisburg shooting (28 October 2022)", "summary": "NRW Interior Ministry, 28 Oct 2022: Palantir-based DAR resolved an amok-threat email against Siegen's city administration in seconds and identified 51 of about 100 people at a Duisburg clan shooting.", "date_observed": "2022-10-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 28 October 2022 North Rhine-Westphalia's (NRW) Interior Ministry said DAR, the police's Palantir software, was central in several recent cases (WELT; RP Online). In October someone had emailed the Siegen city administration announcing an amok attack. The threat was over the city's “topless” permission for swimming pools. The ministry said the email address revealed the suspect via Palantir in fractions of a second. A shooting in Duisburg-Hamborn between a Turkish-Arab clan and the Hells Angels injured four people. A Duisburg investigator said police quickly identified 51 of the roughly 100 participants, about 20 minutes each (RP Online; WELT). 49 of them were assigned to rival groups. Interior Minister Herbert Reul addressed the Landtag's interior committee on 27 October. He said DAR links the weapons register, residents' registration, the police case system and the wanted-persons portal. The ministry puts the 2019–2025 cost at about 39 million euros. The opposition attacks it on data-protection and cost grounds (WELT).", "category": "benefit created", "unexpected": false, "purpose": "DAR was procured to let North Rhine-Westphalia police search and link entries across police and administrative databases during investigations. Identifying suspects from an email address or from a nickname and phone number was that purpose.", "system": "DAR (Datenbankübergreifende Recherche und Analyse), Palantir software used by North Rhine-Westphalia police", "model_version": null, "developer": "Palantir Technologies", "deployer": "North Rhine-Westphalia police, under the NRW Ministry of the Interior (contract since 2019)", "location": "Siegen, Germany", "domain": "Policing / criminal investigation", "segment": "Cross-database analysis for state police", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2022-10-28-8649" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "NRW police resolved an amok-threat email address to a person in fractions of a second. They identified 51 of about 100 shooting participants at about 20 minutes each, per the ministry and a Duisburg investigator. No comparison with conventional methods and no charges or convictions are reported." }, { "group": "societal", "depth": null, "reason": "Siegen's administration and public had the author of a threatened amok attack identified. The sources do not say whether the threat was credible, whether the person was charged, or what harm was averted." } ], "ai_role": { "status": "assessed", "statement": "The reports describe DAR as software that links entries across the weapons register, residents' registration data, the police case system and the wanted-persons portal. None mentions machine learning. The minister himself describes plain linking, while the OECD AI Incidents Monitor calls it an AI system. On the ministry's account the software's contribution was speed of identification. That was an email address in fractions of a second and about 20 minutes per shooting participant. Whether manual queries would have reached the same people more slowly is not addressed. The claims come from the deploying ministry and an unnamed investigator." }, "evidence": [ { "kind": "news report", "citation": "WELT (2022). Ministerium: «Palantir» klärte unter anderem Amokdrohung auf. WELT, 28 October 2022.", "title": "Ministerium: «Palantir» klärte unter anderem Amokdrohung auf", "url": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die E-Mail-Adresse habe via «Palantir» in Sekundenbruchteilen die verdächtige Person enthüllt, hieß es aus dem Innenministerium." }, { "kind": "news report", "citation": "Corman T, Triesch A (2022). Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf. RP Online, 28 October 2022.", "title": "Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf", "url": "https://rp-online.de/nrw/panorama/duesseldorf-palantir-klaert-amokdrohung-und-schiesserei-in-duisburg-auf_aid-79054087", "date": "2022-10-28", "written_by": "independent", "quote": "Wie ein Duisburger Ermittler sagte, konnte man schnell 51 der rund 100 Beteiligten identifizieren." }, { "kind": "news report", "citation": "Westfalenpost (2022). Siegen: Amokdrohung gegen Stadtverwaltung. WP.de, 28 October 2022.", "title": "Siegen: Amokdrohung gegen Stadtverwaltung", "url": "https://www.wp.de/staedte/siegerland/article236775413/Siegen-Amokdrohung-gegen-Stadtverwaltung.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die Stadtverwaltung gerät in den Fokus eines Verdächtigen. Er schickt eine Amokdrohung." }, { "kind": "registry label", "citation": "OECD.AI (2022). AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations. OECD AI Incidents and Hazards Monitor, entry 2022-10-28-8649.", "title": "AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations", "url": "https://oecd.ai/en/incidents/2022-10-28-8649", "date": null, "written_by": "independent", "quote": "a mass shooting in Duisburg and an emailed amok threat to Siegen city administration" } ], "replication": { "produced_by": [ "Police and administrative databases (weapons register, residents' registration, case-processing system, wanted-persons portal) linked in one Palantir-based search", "An identifier from the case, such as an email address, a nickname or a phone number, that matches an entry somewhere in the linked data" ], "must_hold": [ "The person already appears in one of the linked databases. The system links records and does not generate new ones", "Investigators have lawful access to the linked registers. The opposition contests the arrangement on data-protection grounds", "Licensing continues. The ministry puts the 2019–2025 cost at about 39 million euros" ], "echoes": [ { "date": null, "setting": "August 2022, North Rhine-Westphalia: per the ministry, DAR led from one burglar to a whole gang", "model_version": null, "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" }, { "date": null, "setting": "August 2022, North Rhine-Westphalia: DAR identified a man suspected of abusing a 13-year-old girl from only a nickname and a phone number with fake owner data", "model_version": null, "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" } ] }, "paired_incident": null, "headline": "Palantir-based DAR identifies the author of a Siegen amok threat", "metric": "51 of the roughly 100 participants", "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-10-28-8649", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Palantir_Technologies; https://de.wikipedia.org/wiki/Polizei_Nordrhein-Westfalen", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0367", "catalog_version": "1.0.0", "source_fingerprint": "f8bb557bc7f642dcd2c31905ee08cd079662a321cced3883eaae0125429f4a68", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0367-source-0001", "AIBD-0367-source-0002", "AIBD-0367-source-0003", "AIBD-0367-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Palantir Technologies", "deployer": "North Rhine-Westphalia police, under the NRW Ministry of the Interior (contract since 2019)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The reports describe DAR as software that links entries across the weapons register, residents' registration data, the police case system and the wanted-persons portal. None mentions machine learning. The minister himself describes plain linking, while the OECD AI Incidents Monitor calls it an AI system. On the ministry's account the software's contribution was speed of identification. That was an email address in fractions of a second and about 20 minutes per shooting participant. Whether manual queries would have reached the same people more slowly is not addressed. The claims come from the deploying ministry and an unnamed investigator." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The reports describe DAR as software that links entries across the weapons register, residents' registration data, the police case system and the wanted-persons portal. None mentions machine learning. The minister himself describes plain linking, while the OECD AI Incidents Monitor calls it an AI system. On the ministry's account the software's contribution was speed of identification. That was an email address in fractions of a second and about 20 minutes per shooting participant. Whether manual queries would have reached the same people more slowly is not addressed. The claims come from the deploying ministry and an unnamed investigator." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NRW police resolved an amok-threat email address to a person in fractions of a second. They identified 51 of about 100 shooting participants at about 20 minutes each, per the ministry and a Duisburg investigator. No comparison with conventional methods and no charges or convictions are reported." }, { "group": "societal", "reason": "Siegen's administration and public had the author of a threatened amok attack identified. The sources do not say whether the threat was credible, whether the person was charged, or what harm was averted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NRW police resolved an amok-threat email address to a person in fractions of a second. They identified 51 of about 100 shooting participants at about 20 minutes each, per the ministry and a Duisburg investigator. No comparison with conventional methods and no charges or convictions are reported." }, { "group": "societal", "reason": "Siegen's administration and public had the author of a threatened amok attack identified. The sources do not say whether the threat was credible, whether the person was charged, or what harm was averted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NRW police resolved an amok-threat email address to a person in fractions of a second. They identified 51 of about 100 shooting participants at about 20 minutes each, per the ministry and a Duisburg investigator. No comparison with conventional methods and no charges or convictions are reported." }, { "group": "societal", "reason": "Siegen's administration and public had the author of a threatened amok attack identified. The sources do not say whether the threat was credible, whether the person was charged, or what harm was averted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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In October someone had emailed the Siegen city administration announcing an amok attack. The threat was over the city's “topless” permission for swimming pools. The ministry said the email address revealed the suspect via Palantir in fractions of a second. A shooting in Duisburg-Hamborn between a Turkish-Arab clan and the Hells Angels injured four people. A Duisburg investigator said police quickly identified 51 of the roughly 100 participants, about 20 minutes each (RP Online; WELT). 49 of them were assigned to rival groups. Interior Minister Herbert Reul addressed the Landtag's interior committee on 27 October. He said DAR links the weapons register, residents' registration, the police case system and the wanted-persons portal. The ministry puts the 2019–2025 cost at about 39 million euros. The opposition attacks it on data-protection and cost grounds (WELT).", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NRW police resolved an amok-threat email address to a person in fractions of a second. 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The sources do not say whether the threat was credible, whether the person was charged, or what harm was averted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "DAR was procured to let North Rhine-Westphalia police search and link entries across police and administrative databases during investigations. Identifying suspects from an email address or from a nickname and phone number was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Siegen, Germany", "developer_country": "United States", "deployer_country": "Germany" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "DAR was procured to let North Rhine-Westphalia police search and link entries across police and administrative databases during investigations. 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The ministry puts the 2019–2025 cost at about 39 million euros" ], "echoes": [ { "setting": "August 2022, North Rhine-Westphalia: per the ministry, DAR led from one burglar to a whole gang", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" }, { "setting": "August 2022, North Rhine-Westphalia: DAR identified a man suspected of abusing a 13-year-old girl from only a nickname and a phone number with fake owner data", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Police and administrative databases (weapons register, residents' registration, case-processing system, wanted-persons portal) linked in one Palantir-based search", "An identifier from the case, such as an email address, a nickname or a phone number, that matches an entry somewhere in the linked data" ], "must_hold": [ "The person already appears in one of the linked databases. The system links records and does not generate new ones", "Investigators have lawful access to the linked registers. The opposition contests the arrangement on data-protection grounds", "Licensing continues. The ministry puts the 2019–2025 cost at about 39 million euros" ], "echoes": [ { "setting": "August 2022, North Rhine-Westphalia: per the ministry, DAR led from one burglar to a whole gang", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" }, { "setting": "August 2022, North Rhine-Westphalia: DAR identified a man suspected of abusing a 13-year-old girl from only a nickname and a phone number with fake owner data", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-10-28-8649", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Palantir_Technologies; https://de.wikipedia.org/wiki/Polizei_Nordrhein-Westfalen", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / criminal investigation", "segment": "Cross-database analysis for state police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "WELT (2022). Ministerium: «Palantir» klärte unter anderem Amokdrohung auf. WELT, 28 October 2022.", "title": "Ministerium: «Palantir» klärte unter anderem Amokdrohung auf", "url": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die E-Mail-Adresse habe via «Palantir» in Sekundenbruchteilen die verdächtige Person enthüllt, hieß es aus dem Innenministerium." }, { "kind": "news report", "citation": "Corman T, Triesch A (2022). Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf. RP Online, 28 October 2022.", "title": "Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf", "url": "https://rp-online.de/nrw/panorama/duesseldorf-palantir-klaert-amokdrohung-und-schiesserei-in-duisburg-auf_aid-79054087", "date": "2022-10-28", "written_by": "independent", "quote": "Wie ein Duisburger Ermittler sagte, konnte man schnell 51 der rund 100 Beteiligten identifizieren." }, { "kind": "news report", "citation": "Westfalenpost (2022). Siegen: Amokdrohung gegen Stadtverwaltung. WP.de, 28 October 2022.", "title": "Siegen: Amokdrohung gegen Stadtverwaltung", "url": "https://www.wp.de/staedte/siegerland/article236775413/Siegen-Amokdrohung-gegen-Stadtverwaltung.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die Stadtverwaltung gerät in den Fokus eines Verdächtigen. Er schickt eine Amokdrohung." }, { "kind": "registry label", "citation": "OECD.AI (2022). AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations. OECD AI Incidents and Hazards Monitor, entry 2022-10-28-8649.", "title": "AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations", "url": "https://oecd.ai/en/incidents/2022-10-28-8649", "written_by": "independent", "quote": "a mass shooting in Duisburg and an emailed amok threat to Siegen city administration" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0367-source-0001", "AIBD-0367-source-0002", "AIBD-0367-source-0003", "AIBD-0367-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "WELT (2022). Ministerium: «Palantir» klärte unter anderem Amokdrohung auf. WELT, 28 October 2022.", "title": "Ministerium: «Palantir» klärte unter anderem Amokdrohung auf", "url": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die E-Mail-Adresse habe via «Palantir» in Sekundenbruchteilen die verdächtige Person enthüllt, hieß es aus dem Innenministerium." }, { "kind": "news report", "citation": "Corman T, Triesch A (2022). Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf. RP Online, 28 October 2022.", "title": "Düsseldorf: „Palantir“ klärt Amokdrohung und Schießerei in Duisburg auf", "url": "https://rp-online.de/nrw/panorama/duesseldorf-palantir-klaert-amokdrohung-und-schiesserei-in-duisburg-auf_aid-79054087", "date": "2022-10-28", "written_by": "independent", "quote": "Wie ein Duisburger Ermittler sagte, konnte man schnell 51 der rund 100 Beteiligten identifizieren." }, { "kind": "news report", "citation": "Westfalenpost (2022). Siegen: Amokdrohung gegen Stadtverwaltung. WP.de, 28 October 2022.", "title": "Siegen: Amokdrohung gegen Stadtverwaltung", "url": "https://www.wp.de/staedte/siegerland/article236775413/Siegen-Amokdrohung-gegen-Stadtverwaltung.html", "date": "2022-10-28", "written_by": "independent", "quote": "Die Stadtverwaltung gerät in den Fokus eines Verdächtigen. Er schickt eine Amokdrohung." }, { "kind": "registry label", "citation": "OECD.AI (2022). AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations. OECD AI Incidents and Hazards Monitor, entry 2022-10-28-8649.", "title": "AI System 'Palantir' Enables Rapid Suspect Identification in NRW Police Investigations", "url": "https://oecd.ai/en/incidents/2022-10-28-8649", "written_by": "independent", "quote": "a mass shooting in Duisburg and an emailed amok threat to Siegen city administration" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "NRW Interior Ministry, 28 Oct 2022: Palantir-based DAR resolved an amok-threat email against Siegen's city administration in seconds and identified 51 of about 100 people at a Duisburg clan shooting.", "account": "On 28 October 2022 North Rhine-Westphalia's (NRW) Interior Ministry said DAR, the police's Palantir software, was central in several recent cases (WELT; RP Online). In October someone had emailed the Siegen city administration announcing an amok attack. The threat was over the city's “topless” permission for swimming pools. The ministry said the email address revealed the suspect via Palantir in fractions of a second. A shooting in Duisburg-Hamborn between a Turkish-Arab clan and the Hells Angels injured four people. A Duisburg investigator said police quickly identified 51 of the roughly 100 participants, about 20 minutes each (RP Online; WELT). 49 of them were assigned to rival groups. Interior Minister Herbert Reul addressed the Landtag's interior committee on 27 October. He said DAR links the weapons register, residents' registration, the police case system and the wanted-persons portal. The ministry puts the 2019–2025 cost at about 39 million euros. The opposition attacks it on data-protection and cost grounds (WELT)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DAR (Datenbankübergreifende Recherche und Analyse), Palantir software used by North Rhine-Westphalia police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Palantir Technologies" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "The Palantir-based DAR software identifies the author of an emailed amok threat against Siegen's city administration in fractions of a second and 51 of about 100 participants in a Duisburg shooting (28 October 2022)", "headline": "Palantir-based DAR identifies the author of a Siegen amok threat" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f8bb557bc7f642dcd2c31905ee08cd079662a321cced3883eaae0125429f4a68" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 28 October 2022 North Rhine-Westphalia's (NRW) Interior Ministry said DAR, the police's Palantir software, was central in several recent cases (WELT; RP Online). In October someone had emailed the Siegen city administration announcing an amok attack. The threat was over the city's “topless” permission for swimming pools. The ministry said the email address revealed the suspect via Palantir in fractions of a second. A shooting in Duisburg-Hamborn between a Turkish-Arab clan and the Hells Angels injured four people. A Duisburg investigator said police quickly identified 51 of the roughly 100 participants, about 20 minutes each (RP Online; WELT). 49 of them were assigned to rival groups. Interior Minister Herbert Reul addressed the Landtag's interior committee on 27 October. He said DAR links the weapons register, residents' registration, the police case system and the wanted-persons portal. The ministry puts the 2019–2025 cost at about 39 million euros. The opposition attacks it on data-protection and cost grounds (WELT).", "replication": { "produced_by": [ "Police and administrative databases (weapons register, residents' registration, case-processing system, wanted-persons portal) linked in one Palantir-based search", "An identifier from the case, such as an email address, a nickname or a phone number, that matches an entry somewhere in the linked data" ], "must_hold": [ "The person already appears in one of the linked databases. The system links records and does not generate new ones", "Investigators have lawful access to the linked registers. The opposition contests the arrangement on data-protection grounds", "Licensing continues. The ministry puts the 2019–2025 cost at about 39 million euros" ], "echoes": [ { "setting": "August 2022, North Rhine-Westphalia: per the ministry, DAR led from one burglar to a whole gang", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" }, { "setting": "August 2022, North Rhine-Westphalia: DAR identified a man suspected of abusing a 13-year-old girl from only a nickname and a phone number with fake owner data", "outcome": "recurred", "source": "https://www.welt.de/regionales/nrw/article241830977/Ministerium-Palantir-klaerte-unter-anderem-Amokdrohung-auf.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0311", "title": "Cerebral's CMD-1 NLP crisis-message detector cuts median time to crisis-specialist triage from about 9 hours to 8–13 minutes in a prospective October 2022 deployment", "summary": "Two-stage NLP (keyword filter plus logistic regression) screened 102,471 chat messages in October 2022 (AUC 0.98, sensitivity 0.98); daily median receipt-to-triage time 8–13 min versus 9 h before.", "date_observed": "2022-10-31", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Swaminathan, López and colleagues published in npj Digital Medicine on 21 November 2023. They are at Cerebral Inc., a national tele-mental-health provider, and Stanford University School of Medicine. They described developing and deploying Crisis Message Detector 1 (CMD-1). CMD-1 is a two-stage natural-language-processing system: key-word filtering, then logistic regression. It flags patient chat messages indicating possible suicidal or homicidal ideation, domestic violence or non-suicidal self-injury. It surfaces them to Cerebral's crisis specialists via a Slack interface. The model was trained on 721 messages (32% potential crises) sent between 1 April 2021 and 1 April 2022. It was evaluated on a retrospective test set of 481 messages: AUC 0.82, sensitivity 0.99, PPV 0.35. A prospective test set had 102,471 messages from 1 to 31 October 2022 (AUC 0.98; sensitivity 0.98; PPV 0.66). 9,795 of these passed the key-word filter. In the prospective period the daily median time from message receipt to crisis-specialist triage was 8 to 13 minutes. Before deployment it averaged more than 9 hours, per Cerebral's internal analysis. False negatives reached specialists through usual channels. Seven authors report salary and equity in Cerebral and three part-time employment there. Stanford HAI's account (8 January 2024) gives the reduction as “from 10 hours to under 10 minutes” with 97% sensitivity and specificity. Those figures differ slightly from the paper's. No downstream patient outcome (hospitalization, emergency department (ED) use, attempts) is reported.", "category": "general benefit", "unexpected": false, "purpose": "Built to detect and surface crisis chat messages so that crisis specialists triage them sooner. The measured triage-time reduction is that purpose.", "system": "CMD-1 (Crisis Message Detector 1): key-word filter followed by a logistic-regression classifier on chat messages", "model_version": "CMD-1", "developer": "Cerebral Inc. with Stanford University School of Medicine collaborators", "deployer": "Cerebral Inc.", "location": "United States", "domain": "Mental health crisis response / telehealth", "segment": "Tele-mental-health chat message triage", "benefit_type": "Reduced Task Time", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Patients in crisis were triaged within minutes rather than hours on median. The paper reports no clinical outcome for any patient." }, { "group": "organizational", "depth": null, "reason": "The 9-hour baseline comes from Cerebral's internal analysis. The 8–13 minute figure is from the company-authored evaluation. No independent measurement exists." } ], "ai_role": { "status": "assessed", "statement": "The classifier decides which messages are surfaced to crisis specialists, who then triage them. Humans labeled the outcomes. False negatives still reached specialists through usual channels. The effect is reported by the company that built and runs the system, with Stanford co-authors. The pre-deployment baseline is an internal figure. Stanford HAI's summary gives slightly different numbers (10 hours to under 10 minutes; 97%)." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Swaminathan A, López I, Garcia Mar RA, Heist T, McClintock T, Caoili K, Grace M, Rubashkin M, Boggs M, Chen JH, Gevaert O, Lorigo D, Nock MK, Williams PA, Ahuja M, et al. (2023). Natural language processing system for rapid detection and intervention of mental health crisis chat messages. npj Digital Medicine 6 (PMC10663535). Lead authors employed by Cerebral Inc.", "title": "Natural language processing system for rapid detection and intervention of mental health crisis chat messages", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10663535/", "date": "2023-11-21", "written_by": "makers", "quote": "The daily median time from message receipt to crisis specialist triage ranges from 8 to 13 min, compared to 9 h before the deployment of the system." }, { "kind": "peer-reviewed study", "citation": "Swaminathan A, et al. (2023), competing-interests statement of the same paper.", "title": "Natural language processing system for rapid detection and intervention of mental health crisis chat messages", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10663535/", "date": "2023-11-21", "written_by": "makers", "quote": "The following authors report receiving a salary and owning equity in Cerebral Inc.: A.S., T.H., T.M., M.G., M.R., M.B., D.M." }, { "kind": "press release", "citation": "Kannan P (2024). Using NLP to Detect Mental Health Crises. Stanford HAI, 8 January 2024 (Stanford researchers co-authored the paper).", "title": "Using NLP to Detect Mental Health Crises", "url": "https://hai.stanford.edu/news/using-nlp-detect-mental-health-crises", "date": "2024-01-08", "written_by": "makers", "quote": "The compelling system developed here demonstrates not just an analytical result, but the much harder work of integrating that into a real workflow" } ], "replication": { "produced_by": [ "Thousands of daily patient chat messages on a telehealth platform with a crisis response team already in place", "A key-word filter followed by a logistic-regression classifier trained on 721 labeled messages", "A Slack-based workflow in which crisis specialists review and label surfaced messages" ], "must_hold": [ "Crisis specialists available to act on surfaced messages within minutes", "A high-recall filter stage, since messages that do not pass it are classified as non-crises automatically", "Message volume and language similar to the training data. The authors note the prospective PPV was 0.66" ], "echoes": [] }, "paired_incident": null, "headline": "CMD-1 cuts crisis triage from 9 hours to 8–13 minutes", "metric": "daily median receipt-to-triage time 8–13 min versus 9 h before", "comparator": { "against": "response times to patient chat messages before CMD-1 was deployed, per Cerebral's internal analysis", "before": "over 9 h on average", "after": "8 to 13 min", "basis": "measured", "quote": "The daily median time from message receipt to crisis specialist triage ranges from 8 to 13 min, compared to 9 h before the deployment of the system.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10663535/" }, "later": { "status": "unknown", "date": null, "note": "No source dated after the October 2022 prospective deployment reports whether CMD-1 kept running or was adopted elsewhere; the January 2024 Stanford HAI piece only restates the paper's results.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10663535/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://cerebral.com/privacy-policy; https://www.sec.gov/Archives/edgar/data/2083019/000208301926000001/xslFormDX01/primary_doc.xml", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Cerebral Inc..", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0311", "catalog_version": "1.0.0", "source_fingerprint": "b99c2969249e6164fb497e6bf41575005746a3f4135743469b97719999e0b0f0", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0311-source-0001", "AIBD-0311-source-0002", "AIBD-0311-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Cerebral Inc. with Stanford University School of Medicine collaborators", "deployer": "Cerebral Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The classifier decides which messages are surfaced to crisis specialists, who then triage them. Humans labeled the outcomes. False negatives still reached specialists through usual channels. The effect is reported by the company that built and runs the system, with Stanford co-authors. The pre-deployment baseline is an internal figure. Stanford HAI's summary gives slightly different numbers (10 hours to under 10 minutes; 97%)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The classifier decides which messages are surfaced to crisis specialists, who then triage them. Humans labeled the outcomes. False negatives still reached specialists through usual channels. The effect is reported by the company that built and runs the system, with Stanford co-authors. The pre-deployment baseline is an internal figure. Stanford HAI's summary gives slightly different numbers (10 hours to under 10 minutes; 97%)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Patients in crisis were triaged within minutes rather than hours on median. The paper reports no clinical outcome for any patient." }, { "group": "organizational", "reason": "The 9-hour baseline comes from Cerebral's internal analysis. The 8–13 minute figure is from the company-authored evaluation. No independent measurement exists." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Patients in crisis were triaged within minutes rather than hours on median. The paper reports no clinical outcome for any patient." }, { "group": "organizational", "reason": "The 9-hour baseline comes from Cerebral's internal analysis. The 8–13 minute figure is from the company-authored evaluation. No independent measurement exists." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": 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The paper documents no use of the system for the patient's real communication." }, { "group": "societal", "depth": null, "reason": "Single-case proof of concept with a 13-word vocabulary." } ], "ai_role": { "status": "assessed", "statement": "The personalized network is the entire intervention. Its 72.65% word accuracy exceeded the 56.75% mean of familiar listeners. The comparison used a 13-word closed set. The authors state the single-case design and limited vocabulary constrain generalization." }, "evidence": [ { "kind": "case report", "citation": "University of Messina and IRCCS Centro Neurolesi Bonino-Pulejo authors (2026). Case Report: Tailored automatic speech recognition in global aphasia with dysarthria - a single case proof of concept. 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The record is admitted on its peer-reviewed or independent source.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13271983/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Messina; https://en.wikipedia.org/wiki/University_of_Messina", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to University of Messina.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' case report. 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The record is admitted on its peer-reviewed or independent source.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13271983/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Messina; https://en.wikipedia.org/wiki/University_of_Messina", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to University of Messina.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Speech-language rehabilitation / augmentative communication", "segment": "Adults with post-stroke aphasia and dysarthria" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "University of Messina and IRCCS Centro Neurolesi Bonino-Pulejo authors (2026). Case Report: Tailored automatic speech recognition in global aphasia with dysarthria - a single case proof of concept. Frontiers in Rehabilitation Sciences.", "title": "Case Report: Tailored automatic speech recognition in global aphasia with dysarthria - a single case proof of concept", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13271983/", "written_by": "makers", "quote": "The tailored ASR correctly identified 680 of 936 test utterances, yielding an overall word-level accuracy of 72.65%" }, { "kind": "case report", "citation": "Same article (listener benchmark).", "title": "Case Report: Tailored automatic speech recognition in global aphasia with dysarthria (listener benchmark)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13271983/", "written_by": "makers", "quote": "Individual listener accuracy ranged from 38.5% to 73.1% (mean = 56.75%, SD = 12.91%)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0059-source-0001", "AIBD-0059-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "University of Messina and IRCCS Centro Neurolesi Bonino-Pulejo authors (2026). Case Report: Tailored automatic speech recognition in global aphasia with dysarthria - a single case proof of concept. 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It appears in Frontiers in Rehabilitation Sciences (2026). She has right hemiparesis, global aphasia and dysarthria from a massive left-hemisphere hemorrhage at age 19. A compact convolutional neural network in the CapisciAMe voice-input communication app was trained only on her voice. Training used 1,120 utterances of 13 Italian target words from 33 sessions in one month in a therapy room. Utterances from November 2022 (day not given, so 1 November is used) were the held-out test set. The tailored recognizer identified 680 of 936 test utterances (72.65%). 12 rehabilitation professionals who knew her averaged 56.75%. No real-world communication use is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The personalized network recognized spoken words for a communication aid." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The speech-recognition model was trained on 1,120 patient utterances." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "cnn-trad-fpool3." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "cnn-trad-fpool3 trained on 1,120 patient utterances" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "CapisciAMe speaker-dependent ASR (compact convolutional neural network, cnn-trad-fpool3) in a voice-input voice-output communication aid" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Messina and IRCCS Centro Neurolesi Bonino-Pulejo research team (CapisciAMe app developed in Italy as a research tool)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Speaker-tailored neural speech recognition outperforms familiar listeners for a woman with global aphasia and dysarthria (single case)", "headline": "CapisciAMe CNN outperforms familiar listeners on impaired speech" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c7c5373cc7590c15dcc7b12260b15cf3eac2429c628820d9673fde2fe87c98be" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 34-year-old right-handed woman took part in a single-case proof of concept at the University of Messina and IRCCS Centro Neurolesi Bonino-Pulejo. It appears in Frontiers in Rehabilitation Sciences (2026). She has right hemiparesis, global aphasia and dysarthria from a massive left-hemisphere hemorrhage at age 19. A compact convolutional neural network in the CapisciAMe voice-input communication app was trained only on her voice. Training used 1,120 utterances of 13 Italian target words from 33 sessions in one month in a therapy room. Utterances from November 2022 (day not given, so 1 November is used) were the held-out test set. The tailored recognizer identified 680 of 936 test utterances (72.65%). 12 rehabilitation professionals who knew her averaged 56.75%. No real-world communication use is documented.", "replication": { "produced_by": [ "Speaker-dependent training on hundreds of the patient's own utterances", "Closed, small target vocabulary", "Multiple prompting modalities during recording" ], "must_hold": [ "Patient can produce consistent vocalizations for each target word", "Quiet recording environment with a headset microphone", "Clinician time to collect and label training data" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0368", "title": "Instagram self-harm alert to Madhya Pradesh cyber police leads Satna officers to a 17-year-old within about an hour; she is counseled and sent home (3 November 2022)", "summary": "3 November 2022, about 5 pm: Instagram emailed MP cyber police a self-harm alert; Bhopal and Indore teams traced a 17-year-old to Satna in about an hour; she was counseled and sent home.", "date_observed": "2022-11-03", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 3 November 2022 at about 5 pm, Madhya Pradesh's state cyber police received an alert emailed by Instagram's US office. It said a user in the state had suffered a body injury. The Indore cyber-crime unit shared the “self-harm” alert with the cyber headquarters in Bhopal (ANI, 5 November 2022; Times of India, 4 November 2022). The girl, 17, had uploaded two videos. In one, a packet of poison lay beside her as she acted as if drunk. In the other she appeared to cut a vein (ANI). The Times of India notes a small cut on her wrist. State Cyber SP Vaibhav Shrivastava said: “After an effort of one hour, we traced the location of the girl”. She was in Satna district, whose police were informed (ANI). Satna SP Ashutosh Gupta said officers located her and called her in with her mother. She said she only wanted to scare her boyfriend and was sent home after counseling (Times of India).", "category": "protective response", "unexpected": false, "purpose": "Instagram's self-harm detection was built to flag content indicating self-harm or suicide risk and route alerts to agencies that can intervene. An alert that brought police to a girl posting self-harm videos was that purpose.", "system": "Instagram self-harm content detection and alert routing", "model_version": null, "developer": "Meta Platforms (Instagram)", "deployer": "Instagram; alert acted on by the Madhya Pradesh State Cyber Police (Bhopal headquarters and Indore unit) and Satna Police", "location": "Satna, India", "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police", "benefit_type": "Improved Physical Health", "taxonomy_note": "The good is a welfare check and counseling for a teen flagged for self-harm, with only a minor injury documented.", "registry_ids": { "oecd_aim": "2022-11-04-76c5" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "A 17-year-old had posted videos with poison and an apparent cut. She was reached and counseled within about an hour of the alert and sent home with a small cut on her wrist. By her own account she wanted to scare her boyfriend. An averted suicide rests on the police's framing and is not established." } ], "ai_role": { "status": "assessed", "statement": "Police say the alert came by email from Instagram's US office after the videos were posted. An ASP described the platform's AI algorithms as flagging non-graphic self-harm content such as scars, search words and hashtags. No source says whether a classifier or a user report started the alert, or whether Instagram staff reviewed it. Everything after the email was human work. Bhopal and Indore technical teams traced the location in about an hour. Satna police found and counseled her." }, "evidence": [ { "kind": "news report", "citation": "TNN (2022). Instagram alert helps cops prevent a suicide in Madhya Pradesh. The Times of India (Bhopal), 4 November 2022.", "title": "Instagram alert helps cops prevent a suicide in Madhya Pradesh", "url": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms", "date": "2022-11-04", "written_by": "independent", "quote": "She told us that she only wanted to scare her boyfriend as he was not talking to her for five days. She was sent home after a session of counseling" }, { "kind": "news report", "citation": "ANI (2022). Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna. Asian News International, 5 November 2022.", "title": "Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna", "url": "https://www.aninews.in/news/national/general-news/madhya-pradesh-instagrams-timely-alert-to-cyber-police-helps-save-minor-girls-life-in-satna20221105161736", "date": "2022-11-05", "written_by": "independent", "quote": "After an effort of one hour, we traced the location of the girl. We find that she is a resident of the Satna district of Madhya Pradesh" }, { "kind": "news report", "citation": "Team Latestly (2022). Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life. LatestLY, 4 November 2022.", "title": "Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life", "url": "https://www.latestly.com/india/news/madhya-pradesh-instagram-timely-alert-to-indore-cyber-cops-saves-satna-girl-from-ending-life-4417111.html", "date": "2022-11-04", "written_by": "independent", "quote": "AI algorithms on Instagram don't allow any graphic images of self-harm, and any non-graphic, self-harm related content, such as scars, or search words and hashtags, trigger alerts" }, { "kind": "registry label", "citation": "OECD.AI (2022). Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh. OECD AI Incidents and Hazards Monitor, entry 2022-11-04-76c5.", "title": "Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh", "url": "https://oecd.ai/en/incidents/2022-11-04-76c5", "date": null, "written_by": "independent", "quote": "Instagram's AI system detected self-harm content posted by a 17-year-old girl in Satna, Madhya Pradesh, and sent an alert to cyber police." } ], "replication": { "produced_by": [ "Instagram's self-harm detection and alert routing, which per the police flags non-graphic self-harm content and emails state cyber police with account information", "A state cyber police unit (Bhopal headquarters and Indore unit) able to trace the account's location from the emailed information, here in about an hour", "District police able to reach the person and hold a counseling session with a parent present" ], "must_hold": [ "The account's IP or other details resolve to a reachable district", "The person is found before any act. Here she was found with a small cut on her wrist", "A standing channel exists between Instagram and the state cyber police. This was the unit's second such alert" ], "echoes": [ { "date": null, "setting": "Chhattisgarh, earlier: per ASP Vaibhav Srivastava, a previous Instagram “suicide” alert to the Madhya Pradesh cyber cell led to a girl being traced to Chhattisgarh and saved by local police", "model_version": null, "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms" } ] }, "paired_incident": null, "headline": "Instagram self-harm alert brings Satna police to a 17-year-old", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-11-04-76c5", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. 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This was the unit's second such alert" ], "echoes": [ { "setting": "Chhattisgarh, earlier: per ASP Vaibhav Srivastava, a previous Instagram “suicide” alert to the Madhya Pradesh cyber cell led to a girl being traced to Chhattisgarh and saved by local police", "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-11-04-76c5", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "TNN (2022). Instagram alert helps cops prevent a suicide in Madhya Pradesh. The Times of India (Bhopal), 4 November 2022.", "title": "Instagram alert helps cops prevent a suicide in Madhya Pradesh", "url": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms", "date": "2022-11-04", "written_by": "independent", "quote": "She told us that she only wanted to scare her boyfriend as he was not talking to her for five days. She was sent home after a session of counseling" }, { "kind": "news report", "citation": "ANI (2022). Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna. Asian News International, 5 November 2022.", "title": "Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna", "url": "https://www.aninews.in/news/national/general-news/madhya-pradesh-instagrams-timely-alert-to-cyber-police-helps-save-minor-girls-life-in-satna20221105161736", "date": "2022-11-05", "written_by": "independent", "quote": "After an effort of one hour, we traced the location of the girl. We find that she is a resident of the Satna district of Madhya Pradesh" }, { "kind": "news report", "citation": "Team Latestly (2022). Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life. LatestLY, 4 November 2022.", "title": "Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life", "url": "https://www.latestly.com/india/news/madhya-pradesh-instagram-timely-alert-to-indore-cyber-cops-saves-satna-girl-from-ending-life-4417111.html", "date": "2022-11-04", "written_by": "independent", "quote": "AI algorithms on Instagram don't allow any graphic images of self-harm, and any non-graphic, self-harm related content, such as scars, or search words and hashtags, trigger alerts" }, { "kind": "registry label", "citation": "OECD.AI (2022). Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh. OECD AI Incidents and Hazards Monitor, entry 2022-11-04-76c5.", "title": "Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh", "url": "https://oecd.ai/en/incidents/2022-11-04-76c5", "written_by": "independent", "quote": "Instagram's AI system detected self-harm content posted by a 17-year-old girl in Satna, Madhya Pradesh, and sent an alert to cyber police." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0368-source-0001", "AIBD-0368-source-0002", "AIBD-0368-source-0003", "AIBD-0368-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "TNN (2022). Instagram alert helps cops prevent a suicide in Madhya Pradesh. The Times of India (Bhopal), 4 November 2022.", "title": "Instagram alert helps cops prevent a suicide in Madhya Pradesh", "url": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms", "date": "2022-11-04", "written_by": "independent", "quote": "She told us that she only wanted to scare her boyfriend as he was not talking to her for five days. She was sent home after a session of counseling" }, { "kind": "news report", "citation": "ANI (2022). Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna. Asian News International, 5 November 2022.", "title": "Madhya Pradesh: Instagram's timely alert to cyber police helps save minor girl's life in Satna", "url": "https://www.aninews.in/news/national/general-news/madhya-pradesh-instagrams-timely-alert-to-cyber-police-helps-save-minor-girls-life-in-satna20221105161736", "date": "2022-11-05", "written_by": "independent", "quote": "After an effort of one hour, we traced the location of the girl. We find that she is a resident of the Satna district of Madhya Pradesh" }, { "kind": "news report", "citation": "Team Latestly (2022). Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life. LatestLY, 4 November 2022.", "title": "Madhya Pradesh: Instagram Timely Alert to Indore Cyber Cops Saves Satna Girl From Ending Life", "url": "https://www.latestly.com/india/news/madhya-pradesh-instagram-timely-alert-to-indore-cyber-cops-saves-satna-girl-from-ending-life-4417111.html", "date": "2022-11-04", "written_by": "independent", "quote": "AI algorithms on Instagram don't allow any graphic images of self-harm, and any non-graphic, self-harm related content, such as scars, or search words and hashtags, trigger alerts" }, { "kind": "registry label", "citation": "OECD.AI (2022). Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh. OECD AI Incidents and Hazards Monitor, entry 2022-11-04-76c5.", "title": "Instagram AI Alert Enables Police to Prevent Teen Suicide in Madhya Pradesh", "url": "https://oecd.ai/en/incidents/2022-11-04-76c5", "written_by": "independent", "quote": "Instagram's AI system detected self-harm content posted by a 17-year-old girl in Satna, Madhya Pradesh, and sent an alert to cyber police." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "3 November 2022, about 5 pm: Instagram emailed MP cyber police a self-harm alert; Bhopal and Indore teams traced a 17-year-old to Satna in about an hour; she was counseled and sent home.", "account": "On 3 November 2022 at about 5 pm, Madhya Pradesh's state cyber police received an alert emailed by Instagram's US office. It said a user in the state had suffered a body injury. The Indore cyber-crime unit shared the “self-harm” alert with the cyber headquarters in Bhopal (ANI, 5 November 2022; Times of India, 4 November 2022). The girl, 17, had uploaded two videos. In one, a packet of poison lay beside her as she acted as if drunk. In the other she appeared to cut a vein (ANI). The Times of India notes a small cut on her wrist. State Cyber SP Vaibhav Shrivastava said: “After an effort of one hour, we traced the location of the girl”. She was in Satna district, whose police were informed (ANI). Satna SP Ashutosh Gupta said officers located her and called her in with her mother. She said she only wanted to scare her boyfriend and was sent home after counseling (Times of India)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Instagram self-harm content detection and alert routing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meta Platforms (Instagram)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Instagram self-harm alert to Madhya Pradesh cyber police leads Satna officers to a 17-year-old within about an hour; she is counseled and sent home (3 November 2022)", "headline": "Instagram self-harm alert brings Satna police to a 17-year-old" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "df724059f4e078b0baf3ddb1b276f72659cf7cc9167fb308345002ee63116233" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 3 November 2022 at about 5 pm, Madhya Pradesh's state cyber police received an alert emailed by Instagram's US office. It said a user in the state had suffered a body injury. The Indore cyber-crime unit shared the “self-harm” alert with the cyber headquarters in Bhopal (ANI, 5 November 2022; Times of India, 4 November 2022). The girl, 17, had uploaded two videos. In one, a packet of poison lay beside her as she acted as if drunk. In the other she appeared to cut a vein (ANI). The Times of India notes a small cut on her wrist. State Cyber SP Vaibhav Shrivastava said: “After an effort of one hour, we traced the location of the girl”. She was in Satna district, whose police were informed (ANI). Satna SP Ashutosh Gupta said officers located her and called her in with her mother. She said she only wanted to scare her boyfriend and was sent home after counseling (Times of India).", "replication": { "produced_by": [ "Instagram's self-harm detection and alert routing, which per the police flags non-graphic self-harm content and emails state cyber police with account information", "A state cyber police unit (Bhopal headquarters and Indore unit) able to trace the account's location from the emailed information, here in about an hour", "District police able to reach the person and hold a counseling session with a parent present" ], "must_hold": [ "The account's IP or other details resolve to a reachable district", "The person is found before any act. Here she was found with a small cut on her wrist", "A standing channel exists between Instagram and the state cyber police. This was the unit's second such alert" ], "echoes": [ { "setting": "Chhattisgarh, earlier: per ASP Vaibhav Srivastava, a previous Instagram “suicide” alert to the Madhya Pradesh cyber cell led to a girl being traced to Chhattisgarh and saved by local police", "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhopal/instagram-alert-helps-cops-prevent-a-suicide-in-madhya-pradesh/articleshow/95288119.cms" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0247", "title": "Seibu Railway puts AI and 3D-image crossing anomaly detection into full operation at three crossings from 14 November 2022", "summary": "Response.jp (11 Nov 2022): OKI and Marubeni Network Solutions' AI monitoring and a stereo-camera 3D system detect people or vehicles left in crossings, light special signal lamps for drivers and se...", "date_observed": "2022-11-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Response.jp reported on 11 Nov 2022 that Seibu Railway would begin full operation of a “踏切異常検知システム” on 14 Nov 2022. It combines two technologies. One is an AI monitoring system developed by OKI and Marubeni Network Solutions. It uses skeleton recognition to detect people and objects left in crossings. The other is a 3D image-analysis system from Computer Systems Laboratory that uses stereo-camera depth. When a detection occurs, the special signal lamps that warn drivers of danger operate. Live video of the site is sent to the operations control center. Operation started at three crossings on the Ikebukuro and Shinjuku lines, with two more planned within fiscal 2022. The trial that began in December 2021 was reported to have confirmed stable operation. The sources are press-release based. The OECD AI Incidents Monitor lists the deployment as an aggregate benefit. No detection event or accident outcome is documented.", "category": "general benefit", "unexpected": false, "purpose": "The system is built to detect people or vehicles remaining inside a crossing and warn approaching train drivers.", "system": "踏切異常検知システム: 踏切滞留AI監視システム (skeleton-recognition AI) and 3D画像解析踏切監視システム (stereo-camera depth analysis)", "model_version": null, "developer": "OKI and Marubeni Network Solutions (AI system); Computer Systems Laboratory (3D image analysis)", "deployer": "Seibu Railway", "location": null, "domain": "Railway safety", "segment": "Level-crossing obstacle detection", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No outcome is documented." }, { "group": "organizational", "depth": null, "reason": "Only stable operation in trials is reported." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The AI detects and the signal lamps alert human drivers, who brake. No detection statistics are given." }, "evidence": [ { "kind": "news report", "citation": "Response.jp (11 Nov 2022). 西武が踏切異常検知システムを本運用.", "title": "西武が踏切異常検知システムを本運用", "url": "https://response.jp/article/2022/11/11/363968.html", "date": "2022-11-11", "written_by": "independent", "quote": "検知すると運転士へ危険を知らせる特殊信号発光機が作動" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2022-11-09-4a03: Seibu Railway Deploys AI-Based Crossing Detection to Prevent Accidents.", "title": "Seibu Railway Deploys AI-Based Crossing Detection to Prevent Accidents", "url": "https://oecd.ai/en/incidents/2022-11-09-4a03", "date": "2022-11-09", "written_by": "independent", "quote": "These real-time AI systems automatically alert train drivers to potential dangers, aiming to prevent accidents and enhance safety, especially at smaller pedestrian crossings." } ], "replication": { "produced_by": [ "Camera coverage of smaller pedestrian crossings", "Special signal lamps already used to warn drivers", "A year-long trial before full operation" ], "must_hold": [ "Detection remains reliable across weather and lighting", "Drivers can stop in time once the lamp operates" ], "echoes": [ { "date": "2026-06-24", "setting": "Odakyu's AI crossing image analysis at four crossings, linked directly to train braking (ITmedia)", "model_version": null, "outcome": "recurred", "source": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html" } ] }, "paired_incident": null, "headline": "Seibu puts OKI AI crossing anomaly detection into full operation", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No source after 14 November 2022 was available; the pre-launch report only states plans for two more crossings within fiscal 2022.", "quote": null, "url": null }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Oki_Electric_Industry; https://en.wikipedia.org/wiki/Seibu_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0247", "catalog_version": "1.0.0", "source_fingerprint": "56ef2cfbd48eecd3f321afef991947a6df736b6cb1f825be9f355f8bbd351e87", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0247-source-0001", "AIBD-0247-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OKI and Marubeni Network Solutions (AI system); Computer Systems Laboratory (3D image analysis)", "deployer": "Seibu Railway" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The AI detects and the signal lamps alert human drivers, who brake. No detection statistics are given." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and a registry entry. 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No detection event or accident outcome is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "踏切異常検知システム: 踏切滞留AI監視システム (skeleton-recognition AI) and 3D画像解析踏切監視システム (stereo-camera depth analysis)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OKI and Marubeni Network Solutions (AI system); Computer Systems Laboratory (3D image analysis)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Seibu Railway puts AI and 3D-image crossing anomaly detection into full operation at three crossings from 14 November 2022", "headline": "Seibu puts OKI AI crossing anomaly detection into full operation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "56ef2cfbd48eecd3f321afef991947a6df736b6cb1f825be9f355f8bbd351e87" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Response.jp reported on 11 Nov 2022 that Seibu Railway would begin full operation of a “踏切異常検知システム” on 14 Nov 2022. It combines two technologies. One is an AI monitoring system developed by OKI and Marubeni Network Solutions. It uses skeleton recognition to detect people and objects left in crossings. The other is a 3D image-analysis system from Computer Systems Laboratory that uses stereo-camera depth. When a detection occurs, the special signal lamps that warn drivers of danger operate. Live video of the site is sent to the operations control center. Operation started at three crossings on the Ikebukuro and Shinjuku lines, with two more planned within fiscal 2022. The trial that began in December 2021 was reported to have confirmed stable operation. The sources are press-release based. The OECD AI Incidents Monitor lists the deployment as an aggregate benefit. No detection event or accident outcome is documented.", "replication": { "produced_by": [ "Camera coverage of smaller pedestrian crossings", "Special signal lamps already used to warn drivers", "A year-long trial before full operation" ], "must_hold": [ "Detection remains reliable across weather and lighting", "Drivers can stop in time once the lamp operates" ], "echoes": [ { "date": "2026-06-24", "setting": "Odakyu's AI crossing image analysis at four crossings, linked directly to train braking (ITmedia)", "outcome": "recurred", "source": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0259", "title": "FCW with AEB cut front-to-rear crashes 49%; AEB cut pickup rear-end crash rates 43% (November 2022)", "summary": "VOA Learning English (16 Nov 2022): the automaker-NHTSA Partnership for Analytics Research in Traffic Safety analyzed 12 million police-reported crashes in 13 states; IIHS analyzed pickups in 25 st...", "date_observed": "2022-11-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "VOA Learning English reported on 16 Nov 2022, drawing on Associated Press coverage, that two U.S. studies had quantified the effect of front crash prevention. The Partnership for Analytics Research in Traffic Safety (PARTS) is a collaboration between automakers and the National Highway Traffic Safety Administration. It examined more than 12 million police-reported crashes in 13 states involving 93 vehicle models from 2015 to 2020. It found front-to-rear crashes reduced by 49% when the striking vehicle had both forward collision warning and automatic emergency braking. Injury crashes were down 53%. Stellantis executive Tim Czapp of the PARTS board was quoted. The Insurance Institute for Highway Safety (IIHS) used police-reported crashes in 25 states from 2017 to 2020. It found automatic emergency braking reduced rear-end crash rates for pickups by 43%. IIHS researcher Jessica Cicchino urged automakers to fit every pickup with the feature. The PARTS and IIHS reports themselves are not among the sources. The OECD AI Incidents Monitor lists the coverage as an aggregate benefit. These are different studies from the 2017 IIHS analysis.", "category": "general benefit", "unexpected": false, "purpose": "Forward collision warning and automatic emergency braking are built to detect an impending front-to-rear collision and warn or brake.", "system": "Forward collision warning and automatic emergency braking across multiple makers' passenger vehicles and pickups", "model_version": null, "developer": "Multiple automakers", "deployer": "Multiple automakers (factory-fitted systems)", "location": null, "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Aggregate crash-rate findings. No individually attributable outcome." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "Camera and radar perception triggers warnings and braking. The studies compare crash rates of equipped and unequipped vehicles using police-reported crash data. The underlying reports are not among the sources." }, "evidence": [ { "kind": "news report", "citation": "VOA Learning English (16 Nov 2022). Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent (from Associated Press reporting).", "title": "Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent", "url": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html", "date": "2022-11-16", "written_by": "independent", "quote": "Front to rear crashes were reduced by 49 percent when the striking vehicle had both forward collision warning and automatic emergency braking." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2022-11-15-d32d: Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes.", "title": "Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes", "url": "https://oecd.ai/en/incidents/2022-11-15-d32d", "date": "2022-11-15", "written_by": "independent", "quote": "Two U.S. studies found that automatic emergency braking, an AI system that detects imminent collisions and applies brakes, can halve rear-end crashes and reduce pickup truck crashes by over 40%." }, { "kind": "report", "citation": "Partnership for Analytics Research in Traffic Safety (6 Jan 2025). A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems. MITRE Corporation, Public Release Case Number 25-0114.", "title": "A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems", "url": "https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "date": "2025-01-06", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Large multi-state police-reported crash databases linked to vehicle equipment", "Comparison of equipped and unequipped versions of the same models", "Industry-regulator data sharing (PARTS) and an insurer-funded institute (IIHS)" ], "must_hold": [ "Equipment status can be identified per vehicle", "Crash reporting thresholds are comparable across states" ], "echoes": [ { "date": "2017-01-01", "setting": "IIHS 2017 analysis of FCW and AEB on rear-end striking crash rates", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1016/j.aap.2016.11.009" } ] }, "paired_incident": null, "headline": "FCW with AEB cuts front-to-rear crashes 49%", "metric": "front-to-rear crashes reduced by 49%", "comparator": { "against": "striking vehicles without forward collision warning and automatic emergency braking", "before": "not stated", "after": "front to rear crashes were reduced by 49 percent", "basis": "measured", "quote": "The PARTS group’s study found that front to rear crashes were reduced by 49 percent when the striking vehicle had both forward collision warning and automatic emergency braking.", "url": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html" }, "later": { "status": "persisted", "date": "2025-01-06", "note": "PARTS's second study, published 6 January 2025 on model years 2015-2023, again measured a 49% reduction in front-to-rear crashes for AEB-equipped vehicles, with effectiveness rising from 46% for 2015-2017 models to 52% for 2021-2023 models; NHTSA had meanwhile finalized a rule in April 2024 requiring AEB on all new light vehicles by September 2029.", "quote": "The study measured a 49% reduction in front-to-rear crashes for vehicles equipped with AEB across all vehicle segments and model years.", "url": "https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html; https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the makers' report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0259", "catalog_version": "1.0.0", "source_fingerprint": "6b7fa969c9181de347fd16d211016b5b1ecddcaf3cd4a4c1465383f096558c97", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0259-source-0001", "AIBD-0259-source-0002", "AIBD-0259-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Multiple automakers", "deployer": "Multiple automakers (factory-fitted systems)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Camera and radar perception triggers warnings and braking. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Aggregate crash-rate findings. 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"evaluations", "display": { "answer": "front-to-rear crashes reduced by 49%", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-01-06", "note": "PARTS's second study, published 6 January 2025 on model years 2015-2023, again measured a 49% reduction in front-to-rear crashes for AEB-equipped vehicles, with effectiveness rising from 46% for 2015-2017 models to 52% for 2021-2023 models; NHTSA had meanwhile finalized a rule in April 2024 requiring AEB on all new light vehicles by September 2029.", "quote": "The study measured a 49% reduction in front-to-rear crashes for vehicles equipped with AEB across all vehicle segments and model years.", "url": "https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0259" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "VOA Learning English reported on 16 Nov 2022, drawing on Associated Press coverage, that two U.S. studies had quantified the effect of front crash prevention. The Partnership for Analytics Research in Traffic Safety (PARTS) is a collaboration between automakers and the National Highway Traffic Safety Administration. It examined more than 12 million police-reported crashes in 13 states involving 93 vehicle models from 2015 to 2020. It found front-to-rear crashes reduced by 49% when the striking vehicle had both forward collision warning and automatic emergency braking. Injury crashes were down 53%. Stellantis executive Tim Czapp of the PARTS board was quoted. The Insurance Institute for Highway Safety (IIHS) used police-reported crashes in 25 states from 2017 to 2020. It found automatic emergency braking reduced rear-end crash rates for pickups by 43%. IIHS researcher Jessica Cicchino urged automakers to fit every pickup with the feature. The PARTS and IIHS reports themselves are not among the sources. The OECD AI Incidents Monitor lists the coverage as an aggregate benefit. These are different studies from the 2017 IIHS analysis.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Aggregate crash-rate findings. No individually attributable outcome." }, { "group": "organizational", "reason": "No organizational outcome is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Forward collision warning and automatic emergency braking are built to detect an impending front-to-rear collision and warn or brake." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Forward collision warning and automatic emergency braking are built to detect an impending front-to-rear collision and warn or brake." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-11-16", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html; https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Large multi-state police-reported crash databases linked to vehicle equipment", "Comparison of equipped and unequipped versions of the same models", "Industry-regulator data sharing (PARTS) and an insurer-funded institute (IIHS)" ], "must_hold": [ "Equipment status can be identified per vehicle", "Crash reporting thresholds are comparable across states" ], "echoes": [ { "date": "2017-01-01", "setting": "IIHS 2017 analysis of FCW and AEB on rear-end striking crash rates", "outcome": "recurred", "source": "https://doi.org/10.1016/j.aap.2016.11.009" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Large multi-state police-reported crash databases linked to vehicle equipment", "Comparison of equipped and unequipped versions of the same models", "Industry-regulator data sharing (PARTS) and an insurer-funded institute (IIHS)" ], "must_hold": [ "Equipment status can be identified per vehicle", "Crash reporting thresholds are comparable across states" ], "echoes": [ { "date": "2017-01-01", "setting": "IIHS 2017 analysis of FCW and AEB on rear-end striking crash rates", "outcome": "recurred", "source": "https://doi.org/10.1016/j.aap.2016.11.009" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html; https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road vehicle crash avoidance", "segment": "Automotive" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "VOA Learning English (16 Nov 2022). Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent (from Associated Press reporting).", "title": "Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent", "url": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html", "date": "2022-11-16", "written_by": "independent", "quote": "Front to rear crashes were reduced by 49 percent when the striking vehicle had both forward collision warning and automatic emergency braking." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2022-11-15-d32d: Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes.", "title": "Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes", "url": "https://oecd.ai/en/incidents/2022-11-15-d32d", "date": "2022-11-15", "written_by": "independent", "quote": "Two U.S. studies found that automatic emergency braking, an AI system that detects imminent collisions and applies brakes, can halve rear-end crashes and reduce pickup truck crashes by over 40%." }, { "kind": "report", "citation": "Partnership for Analytics Research in Traffic Safety (6 Jan 2025). A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems. MITRE Corporation, Public Release Case Number 25-0114.", "title": "A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems", "url": "https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "date": "2025-01-06", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0259-source-0001", "AIBD-0259-source-0002", "AIBD-0259-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "VOA Learning English (16 Nov 2022). Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent (from Associated Press reporting).", "title": "Study: Vehicle Warning and Braking Systems Cut Crashes by 50 Percent", "url": "https://learningenglish.voanews.com/a/study-vehicle-warning-and-braking-systems-cut-crashes-by-50-percent/6836920.html", "date": "2022-11-16", "written_by": "independent", "quote": "Front to rear crashes were reduced by 49 percent when the striking vehicle had both forward collision warning and automatic emergency braking." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2022-11-15-d32d: Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes.", "title": "Automatic Emergency Braking AI Significantly Reduces Vehicle Crashes", "url": "https://oecd.ai/en/incidents/2022-11-15-d32d", "date": "2022-11-15", "written_by": "independent", "quote": "Two U.S. studies found that automatic emergency braking, an AI system that detects imminent collisions and applies brakes, can halve rear-end crashes and reduce pickup truck crashes by over 40%." }, { "kind": "report", "citation": "Partnership for Analytics Research in Traffic Safety (6 Jan 2025). A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems. MITRE Corporation, Public Release Case Number 25-0114.", "title": "A Study on Real-world Effectiveness of Model Year 2015–2023 Advanced Driver Assistance Systems", "url": "https://www.safetyresearch.net/wp-content/uploads/2025/04/PARTS_Real-World-Effectiveness-ADAS.pdf", "date": "2025-01-06", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "VOA Learning English (16 Nov 2022): the automaker-NHTSA Partnership for Analytics Research in Traffic Safety analyzed 12 million police-reported crashes in 13 states; IIHS analyzed pickups in 25 st...", "account": "VOA Learning English reported on 16 Nov 2022, drawing on Associated Press coverage, that two U.S. studies had quantified the effect of front crash prevention. The Partnership for Analytics Research in Traffic Safety (PARTS) is a collaboration between automakers and the National Highway Traffic Safety Administration. It examined more than 12 million police-reported crashes in 13 states involving 93 vehicle models from 2015 to 2020. It found front-to-rear crashes reduced by 49% when the striking vehicle had both forward collision warning and automatic emergency braking. Injury crashes were down 53%. Stellantis executive Tim Czapp of the PARTS board was quoted. The Insurance Institute for Highway Safety (IIHS) used police-reported crashes in 25 states from 2017 to 2020. It found automatic emergency braking reduced rear-end crash rates for pickups by 43%. IIHS researcher Jessica Cicchino urged automakers to fit every pickup with the feature. The PARTS and IIHS reports themselves are not among the sources. The OECD AI Incidents Monitor lists the coverage as an aggregate benefit. These are different studies from the 2017 IIHS analysis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Forward collision warning and automatic emergency braking across multiple makers' passenger vehicles and pickups" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Multiple automakers" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FCW with AEB cut front-to-rear crashes 49%; AEB cut pickup rear-end crash rates 43% (November 2022)", "headline": "FCW with AEB cuts front-to-rear crashes 49%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6b7fa969c9181de347fd16d211016b5b1ecddcaf3cd4a4c1465383f096558c97" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "VOA Learning English reported on 16 Nov 2022, drawing on Associated Press coverage, that two U.S. studies had quantified the effect of front crash prevention. The Partnership for Analytics Research in Traffic Safety (PARTS) is a collaboration between automakers and the National Highway Traffic Safety Administration. It examined more than 12 million police-reported crashes in 13 states involving 93 vehicle models from 2015 to 2020. It found front-to-rear crashes reduced by 49% when the striking vehicle had both forward collision warning and automatic emergency braking. Injury crashes were down 53%. Stellantis executive Tim Czapp of the PARTS board was quoted. The Insurance Institute for Highway Safety (IIHS) used police-reported crashes in 25 states from 2017 to 2020. It found automatic emergency braking reduced rear-end crash rates for pickups by 43%. IIHS researcher Jessica Cicchino urged automakers to fit every pickup with the feature. The PARTS and IIHS reports themselves are not among the sources. The OECD AI Incidents Monitor lists the coverage as an aggregate benefit. These are different studies from the 2017 IIHS analysis.", "replication": { "produced_by": [ "Large multi-state police-reported crash databases linked to vehicle equipment", "Comparison of equipped and unequipped versions of the same models", "Industry-regulator data sharing (PARTS) and an insurer-funded institute (IIHS)" ], "must_hold": [ "Equipment status can be identified per vehicle", "Crash reporting thresholds are comparable across states" ], "echoes": [ { "date": "2017-01-01", "setting": "IIHS 2017 analysis of FCW and AEB on rear-end striking crash rates", "outcome": "recurred", "source": "https://doi.org/10.1016/j.aap.2016.11.009" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0332", "title": "TCE-MG's Alice audit of 2,297 August 2022 tenders detects 60 irregularities worth R$113.7 million; 53 alerts answered and notices worth R$91.7 million corrected", "summary": "TCE-MG audit with Alice of 2,297 Aug 2022 tenders: 60 irregularities (R$113,713,128.26); 53 alerts answered; notices corrected worth R$91,723,011.31 (TCE-MG, 27 June 2023).", "date_observed": "2022-12-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Tribunal de Contas do Estado de Minas Gerais (TCE-MG) is one of more than ten Brazilian courts of accounts that adopted Alice. Alice is the Análise de Licitações e Editais system created by the CGU and the TCU. In December 2022 it published an audit of 2,297 municipal and state tenders held in a single month, August 2022. The exact day is not given. The court's own news item of 27 June 2023, reproduced by Atricon on 28 June 2023, gives the results. The work detected 60 irregularities involving R$113,713,128.26. 53 of the 60 alerts sent to the audited bodies received answers that allowed control verification. Irregularities were fixed in republished notices or measures adopted for future tenders. The audit achieved corrected notices worth R$91,723,011.31. The figures are aggregates presented by analysts Maria Aparecida Aiko Ikemura and Leonardo Alves Mateus to about 60 people from courts of accounts across Brazil. No individual tender is named.", "category": "protective response", "unexpected": false, "purpose": "Automated identification of tender notices with possible inconsistencies or irregularities so that the court can oversee more tenders. This use was its intended purpose.", "system": "Alice (Análise de Licitações e Editais), the CGU/TCU tender-analysis system as adopted by TCE-MG", "model_version": null, "developer": "Controladoria-Geral da União (CGU) and Tribunal de Contas da União (TCU)", "deployer": "Tribunal de Contas do Estado de Minas Gerais (TCE-MG)", "location": "Minas Gerais, Brazil", "domain": "Public administration: state external audit and procurement control", "segment": "State court of accounts (anti-waste and anti-corruption control)", "benefit_type": "Reduced Risk", "taxonomy_note": "The value corrected is that of the notices, not money saved.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified. Beneficiaries are public bodies and bidders in corrected tenders." }, { "group": "organizational", "depth": 2, "reason": "Material to the audited municipal and state bodies: 53 of 60 alerts answered and notices worth R$91,723,011.31 corrected, per the court's own aggregate figures." }, { "group": "societal", "depth": 1, "reason": "One month of tenders in one state. The statement gives no estimate of money saved, only the value of notices corrected." } ], "ai_role": { "status": "assessed", "statement": "Alice produced the alerts on the 2,297 tenders. TCE-MG analysts forwarded 60 alerts and the audited bodies made the corrections. The AI role was detection and triage. The only sources are the deployer's own news item (TCE-MG, 27 June 2023) and Atricon's reproduction of it the next day. No audit report, tender or court decision is among the sources. TCE-MG did not build the tool (CGU/TCU did), so the statement is not vendor-authored. It is the user describing its own results." }, "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Tribunal mineiro apresenta economia feita com ajuda de Alice. TCE-MG Coordenadoria de Jornalismo e Redação (Fred La Rocca), 27 Jun 2023.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "O trabalho detectou 60 irregularidades, que envolveram o valor de R$ 113.713.128,26." }, { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Same item, result of the alerts.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice (corrections)", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "Com isso, a auditoria conseguiu a correção dos editais no valor equivalente a R$ 91.723.011,31." }, { "kind": "press release", "citation": "Appel, V. (2023). TCE-MG apresenta economia feita com ajuda de robô Alice. Atricon (Associação dos Membros dos Tribunais de Contas do Brasil), 28 Jun 2023, source TCE-MG.", "title": "TCE-MG apresenta economia feita com ajuda de robô Alice", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/", "date": "2023-06-28", "written_by": "deployer", "quote": "Em dezembro de 2022, o TCE publicou o resultado de uma auditória feita em 2.297 licitações municipais e estaduais somente em agosto daquele ano." }, { "kind": "press release", "citation": "Appel V (2024). TCE-MG apresenta robôs Alice e Solaris para o TCE-ES. Atricon, 17 January 2024.", "title": "TCE-MG apresenta robôs Alice e Solaris para o TCE-ES", "url": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "date": "2024-01-17", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Adoption of the CGU/TCU Alice system by a state court of accounts, with its own data acquisition and infrastructure", "Selection of a typology of irregularities and a designed oversight process", "Alerts sent to the audited bodies with a request for response", "Audited bodies republishing corrected notices or adopting measures for future tenders" ], "must_hold": [ "Access to state and municipal tender notices in machine-readable form", "Internal acceptance of the tool by auditors (the court cites internal resistance as a challenge)", "Audited bodies answering alerts (53 of 60 did)", "Typologies kept current so that alerts remain relevant" ], "echoes": [ { "date": "2017-09-27", "setting": "TCU (Goiás unit) use of Alice on DNIT BR-153 notices, tenders blocked by acórdão", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" }, { "date": "2024-01-17", "setting": "TCE-MG presented Alice and Solaris to TCE-ES (Espírito Santo) for adoption; no outcome reported", "model_version": null, "outcome": "unknown", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" } ] }, "paired_incident": null, "headline": "Alice audit at TCE-MG corrects notices worth R$91.7 million", "metric": "the audit achieved corrections of notices worth R$91,723,011.31", "comparator": null, "later": { "status": "persisted", "date": "2024-01-17", "note": "In January 2024 TCE-MG was still running Alice and presented its methodology and results to a TCE-ES auditor who had asked to learn about the robots; adoption by TCE-ES is not reported.", "quote": "Conhecer a metodologia e resultados do TCEMG com a utilização dos robôs Solaris e Alice, bem como as ações implementadas pela Corte de Contas mineira com os dados e informações obtidos com as fiscalizações feitas pelos robôs. Com esses objetivos, o auditor Bruno Fardin Faé, do Tribunal de Contas do Espírito Santos (TCE-ES), solicitou ao TCE-MG uma reunião virtual com a equipe do Suricato, que ocorreu na manhã desta quarta-feira (16).", "url": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" }, "value": { "amount": "R$ 91.723.011,31", "what": "value of the tender notices corrected after Alice's alerts in the audit of August 2022 tenders", "who": "the audited state and municipal bodies in Minas Gerais, which republished corrected notices; the page's title calls the result a saving without saying who saved", "estimate": false, "quote": "Dos 60 alertas encaminhados aos jurisdicionados, 53 apresentaram respostas que permitiram a verificação do controle, alcançando a correção das irregularidades na republicação dos editais ou adoção de providências em futuros procedimentos licitatórios. Com isso, a auditoria conseguiu a correção dos editais equivalente a R$ 91.723.011,31.", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" }, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_do_Estado_de_Minas_Gerais", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: three press releases from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0332", "catalog_version": "1.0.0", "source_fingerprint": "9a17eefb59731218d03d721f97d64c7857a0731029460a856d0ad980c6dd8260", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0332-source-0001", "AIBD-0332-source-0002", "AIBD-0332-source-0003", "AIBD-0332-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0332-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Controladoria-Geral da União (CGU) and Tribunal de Contas da União (TCU)", "deployer": "Tribunal de Contas do Estado de Minas Gerais (TCE-MG)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Alice produced the alerts on the 2,297 tenders. TCE-MG analysts forwarded 60 alerts and the audited bodies made the corrections. The AI role was detection and triage. The only sources are the deployer's own news item (TCE-MG, 27 June 2023) and Atricon's reproduction of it the next day. No audit report, tender or court decision is among the sources. TCE-MG did not build the tool (CGU/TCU did), so the statement is not vendor-authored. It is the user describing its own results." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Alice produced the alerts on the 2,297 tenders. TCE-MG analysts forwarded 60 alerts and the audited bodies made the corrections. The AI role was detection and triage. The only sources are the deployer's own news item (TCE-MG, 27 June 2023) and Atricon's reproduction of it the next day. No audit report, tender or court decision is among the sources. TCE-MG did not build the tool (CGU/TCU did), so the statement is not vendor-authored. It is the user describing its own results." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. Beneficiaries are public bodies and bidders in corrected tenders." }, { "group": "organizational", "depth": 2, "reason": "Material to the audited municipal and state bodies: 53 of 60 alerts answered and notices worth R$91,723,011.31 corrected, per the court's own aggregate figures." }, { "group": "societal", "depth": 1, "reason": "One month of tenders in one state. The statement gives no estimate of money saved, only the value of notices corrected." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: three press releases from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. Beneficiaries are public bodies and bidders in corrected tenders." }, { "group": "organizational", "depth": 2, "reason": "Material to the audited municipal and state bodies: 53 of 60 alerts answered and notices worth R$91,723,011.31 corrected, per the court's own aggregate figures." }, { "group": "societal", "depth": 1, "reason": "One month of tenders in one state. The statement gives no estimate of money saved, only the value of notices corrected." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. Beneficiaries are public bodies and bidders in corrected tenders." }, { "group": "organizational", "depth": 2, "reason": "Material to the audited municipal and state bodies: 53 of 60 alerts answered and notices worth R$91,723,011.31 corrected, per the court's own aggregate figures." }, { "group": "societal", "depth": 1, "reason": "One month of tenders in one state. The statement gives no estimate of money saved, only the value of notices corrected." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 91.723.011,31", "what": "value of the tender notices corrected after Alice's alerts in the audit of August 2022 tenders", "who": "the audited state and municipal bodies in Minas Gerais, which republished corrected notices; the page's title calls the result a saving without saying who saved", "estimate": false, "quote": "Dos 60 alertas encaminhados aos jurisdicionados, 53 apresentaram respostas que permitiram a verificação do controle, alcançando a correção das irregularidades na republicação dos editais ou adoção de providências em futuros procedimentos licitatórios. Com isso, a auditoria conseguiu a correção dos editais equivalente a R$ 91.723.011,31.", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 91.723.011,31", "what": "value of the tender notices corrected after Alice's alerts in the audit of August 2022 tenders", "who": "the audited state and municipal bodies in Minas Gerais, which republished corrected notices; the page's title calls the result a saving without saying who saved", "estimate": false, "quote": "Dos 60 alertas encaminhados aos jurisdicionados, 53 apresentaram respostas que permitiram a verificação do controle, alcançando a correção das irregularidades na republicação dos editais ou adoção de providências em futuros procedimentos licitatórios. Com isso, a auditoria conseguiu a correção dos editais equivalente a R$ 91.723.011,31.", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 91.723.011,31", "what": "value of the tender notices corrected after Alice's alerts in the audit of August 2022 tenders", "who": "the audited state and municipal bodies in Minas Gerais, which republished corrected notices; the page's title calls the result a saving without saying who saved", "estimate": false, "quote": "Dos 60 alertas encaminhados aos jurisdicionados, 53 apresentaram respostas que permitiram a verificação do controle, alcançando a correção das irregularidades na republicação dos editais ou adoção de providências em futuros procedimentos licitatórios. Com isso, a auditoria conseguiu a correção dos editais equivalente a R$ 91.723.011,31.", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "the audit achieved corrections of notices worth R$91,723,011.31", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2024-01-17", "note": "In January 2024 TCE-MG was still running Alice and presented its methodology and results to a TCE-ES auditor who had asked to learn about the robots; adoption by TCE-ES is not reported.", "quote": "Conhecer a metodologia e resultados do TCEMG com a utilização dos robôs Solaris e Alice, bem como as ações implementadas pela Corte de Contas mineira com os dados e informações obtidos com as fiscalizações feitas pelos robôs. Com esses objetivos, o auditor Bruno Fardin Faé, do Tribunal de Contas do Espírito Santos (TCE-ES), solicitou ao TCE-MG uma reunião virtual com a equipe do Suricato, que ocorreu na manhã desta quarta-feira (16).", "url": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0332" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "The value corrected is that of the notices, not money saved." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tribunal de Contas do Estado de Minas Gerais (TCE-MG) is one of more than ten Brazilian courts of accounts that adopted Alice. Alice is the Análise de Licitações e Editais system created by the CGU and the TCU. In December 2022 it published an audit of 2,297 municipal and state tenders held in a single month, August 2022. The exact day is not given. The court's own news item of 27 June 2023, reproduced by Atricon on 28 June 2023, gives the results. The work detected 60 irregularities involving R$113,713,128.26. 53 of the 60 alerts sent to the audited bodies received answers that allowed control verification. Irregularities were fixed in republished notices or measures adopted for future tenders. The audit achieved corrected notices worth R$91,723,011.31. The figures are aggregates presented by analysts Maria Aparecida Aiko Ikemura and Leonardo Alves Mateus to about 60 people from courts of accounts across Brazil. No individual tender is named.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. Beneficiaries are public bodies and bidders in corrected tenders." }, { "group": "organizational", "depth": 2, "reason": "Material to the audited municipal and state bodies: 53 of 60 alerts answered and notices worth R$91,723,011.31 corrected, per the court's own aggregate figures." }, { "group": "societal", "depth": 1, "reason": "One month of tenders in one state. The statement gives no estimate of money saved, only the value of notices corrected." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Automated identification of tender notices with possible inconsistencies or irregularities so that the court can oversee more tenders. This use was its intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Minas Gerais, Brazil", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Automated identification of tender notices with possible inconsistencies or irregularities so that the court can oversee more tenders. This use was its intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-12-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_do_Estado_de_Minas_Gerais", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Adoption of the CGU/TCU Alice system by a state court of accounts, with its own data acquisition and infrastructure", "Selection of a typology of irregularities and a designed oversight process", "Alerts sent to the audited bodies with a request for response", "Audited bodies republishing corrected notices or adopting measures for future tenders" ], "must_hold": [ "Access to state and municipal tender notices in machine-readable form", "Internal acceptance of the tool by auditors (the court cites internal resistance as a challenge)", "Audited bodies answering alerts (53 of 60 did)", "Typologies kept current so that alerts remain relevant" ], "echoes": [ { "date": "2017-09-27", "setting": "TCU (Goiás unit) use of Alice on DNIT BR-153 notices, tenders blocked by acórdão", "outcome": "recurred", "source": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" }, { "date": "2024-01-17", "setting": "TCE-MG presented Alice and Solaris to TCE-ES (Espírito Santo) for adoption; no outcome reported", "outcome": "unknown", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Adoption of the CGU/TCU Alice system by a state court of accounts, with its own data acquisition and infrastructure", "Selection of a typology of irregularities and a designed oversight process", "Alerts sent to the audited bodies with a request for response", "Audited bodies republishing corrected notices or adopting measures for future tenders" ], "must_hold": [ "Access to state and municipal tender notices in machine-readable form", "Internal acceptance of the tool by auditors (the court cites internal resistance as a challenge)", "Audited bodies answering alerts (53 of 60 did)", "Typologies kept current so that alerts remain relevant" ], "echoes": [ { "date": "2017-09-27", "setting": "TCU (Goiás unit) use of Alice on DNIT BR-153 notices, tenders blocked by acórdão", "outcome": "recurred", "source": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" }, { "date": "2024-01-17", "setting": "TCE-MG presented Alice and Solaris to TCE-ES (Espírito Santo) for adoption; no outcome reported", "outcome": "unknown", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Tribunal_de_Contas_do_Estado_de_Minas_Gerais", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: state external audit and procurement control", "segment": "State court of accounts (anti-waste and anti-corruption control)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Tribunal mineiro apresenta economia feita com ajuda de Alice. TCE-MG Coordenadoria de Jornalismo e Redação (Fred La Rocca), 27 Jun 2023.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "O trabalho detectou 60 irregularidades, que envolveram o valor de R$ 113.713.128,26." }, { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Same item, result of the alerts.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice (corrections)", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "Com isso, a auditoria conseguiu a correção dos editais no valor equivalente a R$ 91.723.011,31." }, { "kind": "press release", "citation": "Appel, V. (2023). TCE-MG apresenta economia feita com ajuda de robô Alice. Atricon (Associação dos Membros dos Tribunais de Contas do Brasil), 28 Jun 2023, source TCE-MG.", "title": "TCE-MG apresenta economia feita com ajuda de robô Alice", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/", "date": "2023-06-28", "written_by": "deployer", "quote": "Em dezembro de 2022, o TCE publicou o resultado de uma auditória feita em 2.297 licitações municipais e estaduais somente em agosto daquele ano." }, { "kind": "press release", "citation": "Appel V (2024). TCE-MG apresenta robôs Alice e Solaris para o TCE-ES. Atricon, 17 January 2024.", "title": "TCE-MG apresenta robôs Alice e Solaris para o TCE-ES", "url": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "date": "2024-01-17", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0332-source-0001", "AIBD-0332-source-0002", "AIBD-0332-source-0003", "AIBD-0332-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Tribunal mineiro apresenta economia feita com ajuda de Alice. TCE-MG Coordenadoria de Jornalismo e Redação (Fred La Rocca), 27 Jun 2023.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "O trabalho detectou 60 irregularidades, que envolveram o valor de R$ 113.713.128,26." }, { "kind": "press release", "citation": "Tribunal de Contas do Estado de Minas Gerais (2023). Same item, result of the alerts.", "title": "Tribunal mineiro apresenta economia feita com ajuda de Alice (corrections)", "url": "https://www.tce.mg.gov.br/Tribunal-mineiro-apresenta-economia-feita-com-ajuda-de-Alice.html/Noticia/1111626457", "date": "2023-06-27", "written_by": "deployer", "quote": "Com isso, a auditoria conseguiu a correção dos editais no valor equivalente a R$ 91.723.011,31." }, { "kind": "press release", "citation": "Appel, V. (2023). TCE-MG apresenta economia feita com ajuda de robô Alice. Atricon (Associação dos Membros dos Tribunais de Contas do Brasil), 28 Jun 2023, source TCE-MG.", "title": "TCE-MG apresenta economia feita com ajuda de robô Alice", "url": "https://atricon.org.br/blog/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/", "date": "2023-06-28", "written_by": "deployer", "quote": "Em dezembro de 2022, o TCE publicou o resultado de uma auditória feita em 2.297 licitações municipais e estaduais somente em agosto daquele ano." }, { "kind": "press release", "citation": "Appel V (2024). TCE-MG apresenta robôs Alice e Solaris para o TCE-ES. Atricon, 17 January 2024.", "title": "TCE-MG apresenta robôs Alice e Solaris para o TCE-ES", "url": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/", "date": "2024-01-17", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "TCE-MG audit with Alice of 2,297 Aug 2022 tenders: 60 irregularities (R$113,713,128.26); 53 alerts answered; notices corrected worth R$91,723,011.31 (TCE-MG, 27 June 2023).", "account": "The Tribunal de Contas do Estado de Minas Gerais (TCE-MG) is one of more than ten Brazilian courts of accounts that adopted Alice. Alice is the Análise de Licitações e Editais system created by the CGU and the TCU. In December 2022 it published an audit of 2,297 municipal and state tenders held in a single month, August 2022. The exact day is not given. The court's own news item of 27 June 2023, reproduced by Atricon on 28 June 2023, gives the results. The work detected 60 irregularities involving R$113,713,128.26. 53 of the 60 alerts sent to the audited bodies received answers that allowed control verification. Irregularities were fixed in republished notices or measures adopted for future tenders. The audit achieved corrected notices worth R$91,723,011.31. The figures are aggregates presented by analysts Maria Aparecida Aiko Ikemura and Leonardo Alves Mateus to about 60 people from courts of accounts across Brazil. No individual tender is named." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Alice (Análise de Licitações e Editais), the CGU/TCU tender-analysis system as adopted by TCE-MG" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Controladoria-Geral da União (CGU) and Tribunal de Contas da União (TCU)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TCE-MG's Alice audit of 2,297 August 2022 tenders detects 60 irregularities worth R$113.7 million; 53 alerts answered and notices worth R$91.7 million corrected", "headline": "Alice audit at TCE-MG corrects notices worth R$91.7 million" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9a17eefb59731218d03d721f97d64c7857a0731029460a856d0ad980c6dd8260" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tribunal de Contas do Estado de Minas Gerais (TCE-MG) is one of more than ten Brazilian courts of accounts that adopted Alice. Alice is the Análise de Licitações e Editais system created by the CGU and the TCU. In December 2022 it published an audit of 2,297 municipal and state tenders held in a single month, August 2022. The exact day is not given. The court's own news item of 27 June 2023, reproduced by Atricon on 28 June 2023, gives the results. The work detected 60 irregularities involving R$113,713,128.26. 53 of the 60 alerts sent to the audited bodies received answers that allowed control verification. Irregularities were fixed in republished notices or measures adopted for future tenders. The audit achieved corrected notices worth R$91,723,011.31. The figures are aggregates presented by analysts Maria Aparecida Aiko Ikemura and Leonardo Alves Mateus to about 60 people from courts of accounts across Brazil. No individual tender is named.", "replication": { "produced_by": [ "Adoption of the CGU/TCU Alice system by a state court of accounts, with its own data acquisition and infrastructure", "Selection of a typology of irregularities and a designed oversight process", "Alerts sent to the audited bodies with a request for response", "Audited bodies republishing corrected notices or adopting measures for future tenders" ], "must_hold": [ "Access to state and municipal tender notices in machine-readable form", "Internal acceptance of the tool by auditors (the court cites internal resistance as a challenge)", "Audited bodies answering alerts (53 of 60 did)", "Typologies kept current so that alerts remain relevant" ], "echoes": [ { "date": "2017-09-27", "setting": "TCU (Goiás unit) use of Alice on DNIT BR-153 notices, tenders blocked by acórdão", "outcome": "recurred", "source": "https://web.archive.org/web/20240224093756/https://inforchannel.com.br/2017/09/27/tcu-cria-robo-para-varredura-diaria-de-irregularidades-em-editais/" }, { "date": "2024-01-17", "setting": "TCE-MG presented Alice and Solaris to TCE-ES (Espírito Santo) for adoption; no outcome reported", "outcome": "unknown", "source": "https://atricon.org.br/blog/tce-mg-apresenta-robos-alice-e-solaris-para-o-tce-es/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0067", "title": "An AI eye exam increased screening among young people with diabetes", "summary": "In the ACCESS trial, all 81 young people offered IDx-DR completed an eye exam, compared with 18 of 82 controls referred to an eye-care provider.", "date_observed": "2022-12-06", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "The ACCESS trial enrolled young people with diabetes at two Johns Hopkins clinics in Baltimore. Of 164 participants randomized, one control was excluded after entering another screening study. All 81 participants assigned to an IDx-DR eye exam completed screening, compared with 18 of 82 controls referred to an eye-care provider. The AI marked 25 results as positive, and 16 of those participants attended an eye-care visit within six months. A retina specialist reviewed all AI images for safety because the device was not cleared for this age group. The study measured screening and follow-up, not preserved vision.", "category": "general benefit", "unexpected": false, "purpose": "IDx-DR/LumineticsCore is built to autonomously detect more-than-mild diabetic retinopathy from fundus images at the point of care. Increasing screening completion is its intended benefit.", "system": "IDx-DR (now LumineticsCore)", "model_version": null, "developer": "Digital Diagnostics", "deployer": "Johns Hopkins Pediatric Diabetes Center", "location": "Baltimore, United States", "domain": "Healthcare - diabetic retinopathy screening", "segment": "Autonomous AI screening in pediatric diabetes care", "benefit_type": "Improved Physical Health", "taxonomy_note": "The trial reports exam completion and follow-through, process outcomes, rather than vision outcomes.", "registry_ids": { "clinicaltrials_gov": "NCT05131451" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "The trial measured a substantial increase in completed diabetic eye exams. It did not establish improved vision or prevention of blindness." } ], "ai_role": { "status": "assessed", "statement": "IDx-DR assessed retinal photographs and returned a screening result during the diabetes visit. The trial compared this on-site service with referral elsewhere. A retina specialist also reviewed the images for safety. A coauthor had financial interests in the manufacturer, although he did not have access to the underlying data." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Risa M. Wolf et al., “Autonomous Artificial Intelligence Increases Screening and Follow-up for Diabetic Retinopathy in Youth: The ACCESS Randomized Control Trial,” Nature Communications 15 (2024): 421, doi:10.1038/s41467-023-44676-z. 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The article does not identify the precise paying account." }, "provenance": { "kind": "source_review", "basis": "Methods: Acceptability and satisfaction, last sentence. This payment is study context only.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Study participants received compensation. The article does not identify the precise paying account." } }, "economics[].return_payback": { "state": "value_present", "value": { "kind": "text", "text": "No financial return or payback period was estimated." }, "provenance": { "kind": "source_review", "basis": "Methods: Acceptability and satisfaction, last sentence. This payment is study context only.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "No financial return or payback period was estimated." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "The source states the gift card’s face value. It does not value health outcomes." }, "provenance": { "kind": "source_review", "basis": "Methods: Acceptability and satisfaction, last sentence. This payment is study context only.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The source states the gift card’s face value. It does not value health outcomes." } }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "Randomization supports the effect of offering an immediate AI exam rather than a referral. It does not separate the algorithm from convenience and access at the clinic." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Randomization supports the effect of offering an immediate AI exam rather than a referral. It does not separate the algorithm from convenience and access at the clinic." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Scripted education and referral to an eye-care provider, with a printed handout." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Scripted education and referral to an eye-care provider, with a printed handout." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "An unmasked randomized trial, with allocation concealed until assignment. Randomization used blocks of four or six and was stratified by clinic." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An unmasked randomized trial, with allocation concealed until assignment. 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The abstract gives 83 assigned controls, while the analyzed control denominator is 82.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Screening completion was 100% with AI and 22% with referral, a difference of 78 percentage points (95% CI, 69–87)." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Participants enrolled from 24 November 2021 to 6 June 2022. Follow-up ended on 6 December 2022. An AI exam generally took five to ten minutes." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Participants enrolled from 24 November 2021 to 6 June 2022. Follow-up ended on 6 December 2022. An AI exam generally took five to ten minutes." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "NCT05131451" }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "NCT05131451" } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "The primary outcome was documented completion of a diabetic eye exam within six months. Researchers also tracked referral attendance and participant satisfaction." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The primary outcome was documented completion of a diabetic eye exam within six months. Researchers also tracked referral attendance and participant satisfaction." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Completion of a diabetic eye exam within six months, with referral attendance as a secondary outcome." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Completion of a diabetic eye exam within six months, with referral attendance as a secondary outcome." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The protocol and supplement describe the procedure. De-identified data require an approved proposal and data-use agreement. The commercial diagnostic code is not published." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The protocol and supplement describe the procedure. De-identified data require an approved proposal and data-use agreement. The commercial diagnostic code is not published." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "The trial randomized 164 participants at two Baltimore clinics. After one control was excluded, the analysis included 81 AI participants and 82 controls." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial randomized 164 participants at two Baltimore clinics. After one control was excluded, the analysis included 81 AI participants and 82 controls." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The trial measured access to screening, not later vision. The referral comparison used 25 AI-positive participants versus the entire control group, so those secondary denominators are not equivalent." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial measured access to screening, not later vision. The referral comparison used 25 AI-positive participants versus the entire control group, so those secondary denominators are not equivalent." } }, "external_references[]": { "state": "value_present", "value": { "kind": "structured", "data": { "ClinicalTrials.gov": "NCT05131451" } }, "provenance": { "kind": "source_review", "basis": "Original study registration, inspected through the ClinicalTrials.gov API.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "NCT05131451" } }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The study followed eye-exam completion and referral attendance for six months. It did not report later vision outcomes.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "A board-certified retina specialist reviewed every AI image for safety. An independent monitoring board oversaw the study." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A board-certified retina specialist reviewed every AI image for safety. An independent monitoring board oversaw the study." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0067" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The service required a retinal camera, trained clinic staff, IDx-DR, specialist safety review, and a referral route." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The service required a retinal camera, trained clinic staff, IDx-DR, specialist safety review, and a referral route." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Young people with type 1 or type 2 diabetes who were due for a diabetic eye exam." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Young people with type 1 or type 2 diabetes who were due for a diabetic eye exam." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "structured", "data": { "eligible": 170, "declined": 6, "randomized": 164, "assigned_AI": 81, "assigned_control": 83, "excluded_control": 1, "analyzed": 163, "screened": { "AI": 81, "control": 18 }, "AI_positive_screens": 25, "AI_positive_follow_up_visits": 16 } }, "provenance": { "kind": "source_review", "basis": "Figure 1; Results: Participant flow and Primary and secondary outcomes.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "All 81 AI participants and 18 of 82 controls completed screening. 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It was not large enough to establish equal effects across every subgroup." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial included a racially diverse population, and 47% of participants had Medicaid coverage. It was not large enough to establish equal effects across every subgroup." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Screening and referral attendance were followed for six months." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Screening and referral attendance were followed for six months." } }, "outcomes[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0067-outcome-01" }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0067-outcome-01" } }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "structured", "data": { "groups": [ "personal" ] } }, "provenance": { "kind": "curatorial", "basis": "The beneficiary groups correspond to the reviewed depth assessments.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "People." } }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Observed in a randomized trial." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Observed in a randomized trial." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "The AI produced positive screening results that required further assessment. Its reported specificity was 78.9% against specialist review. A positive screen was not a confirmed diagnosis." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The AI produced positive screening results that required further assessment. Its reported specificity was 78.9% against specialist review. A positive screen was not a confirmed diagnosis." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "IDx-DR/LumineticsCore is built to autonomously detect more-than-mild diabetic retinopathy from fundus images at the point of care. 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The manufacturer was also based in the United States." } }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "IDx-DR/LumineticsCore is built to autonomously detect more-than-mild diabetic retinopathy from fundus images at the point of care. Increasing screening completion is its intended benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "enrollment_start": "2021-11-24", "enrollment_end": "2022-06-06", "follow_up_end": "2022-12-06", "publication": "2024-01-11" } }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Enrollment began on 24 November 2021, and follow-up ended on 6 December 2022." } }, "replication.attempts[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not report an independent repetition of this clinical result.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not report an independent repetition of this clinical result." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "The tested service combined an immediate eye exam, clinic staff, follow-up referrals, and specialist safety review for young participants." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The tested service combined an immediate eye exam, clinic staff, follow-up referrals, and specialist safety review for young participants." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Evidence quote restored to the abstract's verbatim sentence including the group sizes (n = 81) and (n = 83), evidence date set to the 11 January 2024 publication date, and the AI-role statement corrected because second author R. Channa is at the University of Wisconsin rather than Johns Hopkins, with the author-contribution statement that Abramoff had no access to the underlying data added.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.digitaldiagnostics.com/contact/; https://en.wikipedia.org/wiki/Johns_Hopkins_Medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - diabetic retinopathy screening", "segment": "Autonomous AI screening in pediatric diabetes care" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "versions_and_access": [ { "source_ref": "AIBD-0067-source-0001", "source_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "access_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "locator": "Figure 1; Tables 1–4; Methods; Data and Code availability; Author contributions; Competing interests.", "status": "Original text read.", "reviewed_on": "2026-10-25" }, { "source_ref": "AIBD-0067-source-0001", "source_url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41467-023-44676-z/MediaObjects/41467_2023_44676_MOESM1_ESM.docx", "access_url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41467-023-44676-z/MediaObjects/41467_2023_44676_MOESM1_ESM.docx", "locator": "Supplementary Note 3 and supplementary tables.", "status": "Original text read.", "reviewed_on": "2026-10-25" }, { "source_ref": "AIBD-0067-source-0001", "source_url": "https://clinicaltrials.gov/study/NCT05131451", "access_url": "https://clinicaltrials.gov/api/v2/studies/NCT05131451", "locator": "Protocol identification, status, locations, eligibility, and outcomes.", "status": "Original text read.", "reviewed_on": "2026-10-25" } ] } }, "provenance": { "kind": "source_review", "basis": "Access records below distinguish full text, supplements, metadata, and inaccessible material.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Access and version details are listed for each reviewed source." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "structured", "data": { "citations": [ { "source_ref": "AIBD-0067-source-0001", "citation": "Risa M. Wolf et al., “Autonomous Artificial Intelligence Increases Screening and Follow-up for Diabetic Retinopathy in Youth: The ACCESS Randomized Control Trial,” Nature Communications 15 (2024): 421, doi:10.1038/s41467-023-44676-z. Figures 1–2, Methods, and Supplementary Note 3.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "date": "2024-01-11" } ], "locators": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "locator": "Figure 1; Tables 1–4; Methods; Data and Code availability; Author contributions; Competing interests.", "contribution": "Randomized screening results, denominators, age limits, procedures, and conflicts.", "relationship": "Original academic evaluation with a manufacturer-affiliated coauthor.", "source_refs": [ "AIBD-0067-source-0001" ] }, { "url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41467-023-44676-z/MediaObjects/41467_2023_44676_MOESM1_ESM.docx", "locator": "Supplementary Note 3 and supplementary tables.", "contribution": "Image procedure, investigational use, and specialist safety review.", "relationship": "Supplement to the same trial.", "source_refs": [ "AIBD-0067-source-0001" ] }, { "url": "https://clinicaltrials.gov/study/NCT05131451", "locator": "Protocol identification, status, locations, eligibility, and outcomes.", "contribution": "Study registration and ethics identifier.", "relationship": "Sponsor-supplied trial registration.", "source_refs": [ "AIBD-0067-source-0001" ] } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed source metadata and contribution-specific locators.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Original citations and the passages that support each finding." } }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0067-source-0001" ], "role": "Retained sources" }, "provenance": { "kind": "curatorial", "basis": "Identifiers correspond to the retained source order.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "1 retained sources." } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "English. No translation was used." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English. No translation was used." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "Academic investigators conducted the trial. One coauthor was an investor, director, and consultant of Digital Diagnostics, but had no access to the underlying data." }, "provenance": { "kind": "source_review", "basis": "Author contributions and Competing interests.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Academic investigators conducted the trial. One coauthor was an investor, director, and consultant of Digital Diagnostics, but had no access to the underlying data." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0067-source-0001", "retained_source_order": [ "AIBD-0067-source-0001" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10784572/", "locator": "Figure 1; Tables 1–4; Methods; Data and Code availability; Author contributions; Competing interests.", "contribution": "Randomized screening results, denominators, age limits, procedures, and conflicts.", "relationship": "Original academic evaluation with a manufacturer-affiliated coauthor.", "source_refs": [ "AIBD-0067-source-0001" ] }, { "url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41467-023-44676-z/MediaObjects/41467_2023_44676_MOESM1_ESM.docx", "locator": "Supplementary Note 3 and supplementary tables.", "contribution": "Image procedure, investigational use, and specialist safety review.", "relationship": "Supplement to the same trial.", "source_refs": [ "AIBD-0067-source-0001" ] }, { "url": "https://clinicaltrials.gov/study/NCT05131451", "locator": "Protocol identification, status, locations, eligibility, and outcomes.", "contribution": "Study registration and ethics identifier.", "relationship": "Sponsor-supplied trial registration.", "source_refs": [ "AIBD-0067-source-0001" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Methods, results, counts, chronology, AI identity and operation, human responsibilities, limitations, and economic evidence." } }, "provenance": { "kind": "source_review", "basis": "The original materials and exact locators are listed in this assessment.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original studies and their supporting materials are linked to the findings that they support." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "In the ACCESS trial, all 81 young people offered IDx-DR completed an eye exam, compared with 18 of 82 controls referred to an eye-care provider." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "In the ACCESS trial, all 81 young people offered IDx-DR completed an eye exam, compared with 18 of 82 controls referred to an eye-care provider." } }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "The software produced its result without a clinician interpreting the photographs first. The research team nevertheless obtained specialist overreads for safety." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The software produced its result without a clinician interpreting the photographs first. The research team nevertheless obtained specialist overreads for safety." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software checked image quality and assessed photographs for diabetic eye disease." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The software checked image quality and assessed photographs for diabetic eye disease." } }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "algorithm": "locked diagnostic device", "image_fields": [ "fovea", "optic disc" ], "maximum_image_acquisition_attempts": 3, "result_latency": "within 60 seconds", "exam_time_minutes": [ 5, 10 ], "human_overread": "all AI images" } }, "provenance": { "kind": "source_review", "basis": "Supplementary Note 3; Methods; Code availability.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The device used two retinal views and allowed up to three attempts to obtain suitable images. The trial does not name the camera model." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Two color retinal photographs centered on the fovea and optic disc were assessed. The output indicated disease, no disease, or insufficient image quality." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two color retinal photographs centered on the fovea and optic disc were assessed. The output indicated disease, no disease, or insufficient image quality." } }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The locked diagnostic algorithms within IDx-DR. The trial does not name a separate model family or release." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The locked diagnostic algorithms within IDx-DR. The trial does not name a separate model family or release." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Methods and Code availability; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The paper and supplement do not identify the installed software release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The paper and supplement do not identify the installed software release." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "IDx-DR, now sold as LumineticsCore." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "IDx-DR, now sold as LumineticsCore." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Digital Diagnostics, United States." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Digital Diagnostics, United States." } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "An AI eye exam increased screening among young people with diabetes" }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "An AI eye exam increased screening among young people with diabetes" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f6eae30ef3c156d711228cb8bcf5969e1eca2919712de3047d11d854ad4ba314" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Content fingerprint refreshed after the October 25, 2026 source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Clinic staff photographed the retina during the diabetes visit. Participants received the result immediately and were referred for an eye-care visit when indicated." }, "provenance": { "kind": "source_review", "basis": "Wolf et al., Nature Communications (2024), Figure 1; Tables 1–4; Methods; Supplementary Note 3.", "record_fields": [], "source_refs": [ "AIBD-0067-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Clinic staff photographed the retina during the diabetes visit. Participants received the result immediately and were referred for an eye-care visit when indicated." } } }, "summary": { "total": 91, "addressed": 91, "known": 83, "reviewed": 78, "record_mapped": 9, "not_assessed": 4, "complete": false, "by_state": { "value_present": 83, "not_reported": 4, "unresolved": 0, "not_assessed": 4, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0264", "title": "FOX AI cochlear-implant fitting matches or beats manual fitting in a 24-patient crossover RCT in Brussels", "summary": "In a Brussels crossover RCT, newly implanted patients fitted with FOX had better speech intelligibility at 3 and 12 months; all manual-arm patients kept the FOX map; 47 experienced users improved.", "date_observed": "2022-12-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Wathour et al. (Ear and Hearing, published online 21 December 2022) ran a one-year randomized crossover trial. It had 24 newly implanted cochlear-implant patients at Cliniques universitaires Saint-Luc, Brussels. It compared manual fitting with the Fitting to Outcome eXpert (FOX). From 3 months the FOX group showed less variability and better speech intelligibility in quiet and noise. Median phoneme scores were 50%, 70% and 50% at 55, 70 and 85 dB SPL versus 45%, 50% and 40%. After crossover, 100% of the manual group kept the FOX map and 82% performed better with it. 63% of the FOX group preferred their manual map for comfort. A companion study (Otology & Neurotology, 18 January 2023) gave 47 experienced users a FOX map. It found median improvements of 10 dB at 6,000 Hz and 10% in phonemic discrimination and speech scores after 15 days of take-home use. Two 2019 case studies from the same group reported improved word recognition with AI suggestions in one of two adults. Otoconsult's site describes FOX as an outcome-based application assisting audiologists and AI-FOX as the successor of a deterministic first-generation tool. P. J. Govaerts co-authored all three papers. Whether any author is affiliated with Otoconsult could not be verified from the records read.", "category": "benefit created", "unexpected": false, "purpose": "Recommend cochlear-implant MAP settings to audiologists from measured auditory outcomes", "system": "FOX (Fitting to Outcome eXpert) / AI-FOX cochlear-implant fitting software", "model_version": "Generation used in the 2022-2023 studies not stated; Otoconsult describes AI-FOX as successor to a deterministic first-generation FOX", "developer": "Otoconsult (per otoconsult.com)", "deployer": "Cliniques universitaires Saint-Luc, Brussels", "location": "Brussels, Belgium", "domain": "Health; hearing", "segment": "Cochlear-implant recipients", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Better speech intelligibility at 3 and 12 months in newly implanted patients. Median 10% gains in speech scores for experienced users." }, { "group": "organizational", "depth": 1, "reason": "Authors report the FOX approach equivalent or superior in “hearing performance, comfort, and resources”." }, { "group": "societal", "depth": null, "reason": "Single-center studies. No population-level outcome." } ], "ai_role": { "status": "assessed", "statement": "The software proposes MAP settings from measured outcomes. The trials compare it with manual fitting and attribute the measured gains to the FOX maps. All three papers share co-author P. J. Govaerts. The developer's identity is taken from Otoconsult's own site. No record independent of the authors' group is among the sources." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Wathour J, Govaerts PJ, Derue L, et al. Ear Hear 44(3) (2023)", "title": "Prospective Comparison Between Manual and Computer-Assisted (FOX) Cochlear Implant Fitting in Newly Implanted Patients", "url": "https://doi.org/10.1097/aud.0000000000001314", "date": "2022-12-21", "written_by": "makers", "quote": "the AI-FOX approach was equivalent to or even outperformed the manual approach in hearing performance, comfort, and resources" }, { "kind": "peer-reviewed study", "citation": "Wathour J, Govaerts PJ, Lacroix E, Naima D. Otol Neurotol 44(3) (2023)", "title": "Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients", "url": "https://doi.org/10.1097/mao.0000000000003810", "date": "2023-01-18", "written_by": "makers", "quote": "The AI-assisted CI mapping model as a potential assistive tool may improve audiological outcomes for experienced CI patients" }, { "kind": "case report", "citation": "Wathour J, Govaerts PJ, Deggouj N. Cochlear Implants Int (2019)", "title": "From manual to artificial intelligence fitting: Two cochlear implant case studies", "url": "https://doi.org/10.1080/14670100.2019.1667574", "date": "2019-09-17", "written_by": "makers", "quote": "For subject 2, the word recognition scores improved at soft and loud intensities with the AI suggestions." }, { "kind": "press release", "citation": "Otoconsult product page", "title": "AI-FOX", "url": "https://www.otoconsult.com/fox", "date": null, "written_by": "makers", "quote": "AI-FOX is an expert system. It is the successor of the first-generation FOX, which was a deterministic tool." } ], "replication": { "produced_by": [ "Outcome measurements (thresholds, loudness scaling, speech scores) fed to the FOX recommender", "Audiologists applying the recommended MAPs" ], "must_hold": [ "Clinicians accept and apply FOX recommendations", "Patients tolerate the map (63% of FOX-arm patients preferred manual maps for comfort)" ], "echoes": [ { "date": "2019-09-17", "setting": "Two adult case studies, same center", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1080/14670100.2019.1667574" }, { "date": "2023-01-18", "setting": "47 experienced CI users, same center, 15-day take-home comparison", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1097/mao.0000000000003810" } ] }, "paired_incident": null, "headline": "FOX matches or beats manual cochlear-implant fitting in RCT", "metric": "100% of the manual group kept the FOX map and 82% performed better with it", "comparator": null, "later": null, "value": null, "developer_country": "Belgium", "deployer_country": "Belgium", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.otoconsult.com/; https://www.saintluc.be/fr/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two peer-reviewed studies from the makers, the makers' case report and the makers' press release. 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Ear Hear 44(3) (2023)", "title": "Prospective Comparison Between Manual and Computer-Assisted (FOX) Cochlear Implant Fitting in Newly Implanted Patients", "url": "https://doi.org/10.1097/aud.0000000000001314", "date": "2022-12-21", "written_by": "makers", "quote": "the AI-FOX approach was equivalent to or even outperformed the manual approach in hearing performance, comfort, and resources" }, { "kind": "peer-reviewed study", "citation": "Wathour J, Govaerts PJ, Lacroix E, Naima D. Otol Neurotol 44(3) (2023)", "title": "Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients", "url": "https://doi.org/10.1097/mao.0000000000003810", "date": "2023-01-18", "written_by": "makers", "quote": "The AI-assisted CI mapping model as a potential assistive tool may improve audiological outcomes for experienced CI patients" }, { "kind": "case report", "citation": "Wathour J, Govaerts PJ, Deggouj N. Cochlear Implants Int (2019)", "title": "From manual to artificial intelligence fitting: Two cochlear implant case studies", "url": "https://doi.org/10.1080/14670100.2019.1667574", "date": "2019-09-17", "written_by": "makers", "quote": "For subject 2, the word recognition scores improved at soft and loud intensities with the AI suggestions." }, { "kind": "press release", "citation": "Otoconsult product page", "title": "AI-FOX", "url": "https://www.otoconsult.com/fox", "written_by": "makers", "quote": "AI-FOX is an expert system. It is the successor of the first-generation FOX, which was a deterministic tool." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0264-source-0001", "AIBD-0264-source-0002", "AIBD-0264-source-0003", "AIBD-0264-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Wathour J, Govaerts PJ, Derue L, et al. Ear Hear 44(3) (2023)", "title": "Prospective Comparison Between Manual and Computer-Assisted (FOX) Cochlear Implant Fitting in Newly Implanted Patients", "url": "https://doi.org/10.1097/aud.0000000000001314", "date": "2022-12-21", "written_by": "makers", "quote": "the AI-FOX approach was equivalent to or even outperformed the manual approach in hearing performance, comfort, and resources" }, { "kind": "peer-reviewed study", "citation": "Wathour J, Govaerts PJ, Lacroix E, Naima D. Otol Neurotol 44(3) (2023)", "title": "Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients", "url": "https://doi.org/10.1097/mao.0000000000003810", "date": "2023-01-18", "written_by": "makers", "quote": "The AI-assisted CI mapping model as a potential assistive tool may improve audiological outcomes for experienced CI patients" }, { "kind": "case report", "citation": "Wathour J, Govaerts PJ, Deggouj N. Cochlear Implants Int (2019)", "title": "From manual to artificial intelligence fitting: Two cochlear implant case studies", "url": "https://doi.org/10.1080/14670100.2019.1667574", "date": "2019-09-17", "written_by": "makers", "quote": "For subject 2, the word recognition scores improved at soft and loud intensities with the AI suggestions." }, { "kind": "press release", "citation": "Otoconsult product page", "title": "AI-FOX", "url": "https://www.otoconsult.com/fox", "written_by": "makers", "quote": "AI-FOX is an expert system. It is the successor of the first-generation FOX, which was a deterministic tool." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "In a Brussels crossover RCT, newly implanted patients fitted with FOX had better speech intelligibility at 3 and 12 months; all manual-arm patients kept the FOX map; 47 experienced users improved.", "account": "Wathour et al. (Ear and Hearing, published online 21 December 2022) ran a one-year randomized crossover trial. It had 24 newly implanted cochlear-implant patients at Cliniques universitaires Saint-Luc, Brussels. It compared manual fitting with the Fitting to Outcome eXpert (FOX). From 3 months the FOX group showed less variability and better speech intelligibility in quiet and noise. Median phoneme scores were 50%, 70% and 50% at 55, 70 and 85 dB SPL versus 45%, 50% and 40%. After crossover, 100% of the manual group kept the FOX map and 82% performed better with it. 63% of the FOX group preferred their manual map for comfort. A companion study (Otology & Neurotology, 18 January 2023) gave 47 experienced users a FOX map. It found median improvements of 10 dB at 6,000 Hz and 10% in phonemic discrimination and speech scores after 15 days of take-home use. Two 2019 case studies from the same group reported improved word recognition with AI suggestions in one of two adults. Otoconsult's site describes FOX as an outcome-based application assisting audiologists and AI-FOX as the successor of a deterministic first-generation tool. P. J. Govaerts co-authored all three papers. Whether any author is affiliated with Otoconsult could not be verified from the records read." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The studies used FOX fitting software in 2022 and 2023. The sources do not establish whether this was the later AI-FOX generation." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Generation used in the 2022-2023 studies not stated; Otoconsult describes AI-FOX as successor to a deterministic first-generation FOX" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FOX (Fitting to Outcome eXpert) / AI-FOX cochlear-implant fitting software" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Otoconsult (per otoconsult.com)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FOX AI cochlear-implant fitting matches or beats manual fitting in a 24-patient crossover RCT in Brussels", "headline": "FOX matches or beats manual cochlear-implant fitting in RCT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9b7d1293e0fe4b22bb253066405901d889d497590f6ed50bf0b63907f8d46c0b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Wathour et al. (Ear and Hearing, published online 21 December 2022) ran a one-year randomized crossover trial. It had 24 newly implanted cochlear-implant patients at Cliniques universitaires Saint-Luc, Brussels. It compared manual fitting with the Fitting to Outcome eXpert (FOX). From 3 months the FOX group showed less variability and better speech intelligibility in quiet and noise. Median phoneme scores were 50%, 70% and 50% at 55, 70 and 85 dB SPL versus 45%, 50% and 40%. After crossover, 100% of the manual group kept the FOX map and 82% performed better with it. 63% of the FOX group preferred their manual map for comfort. A companion study (Otology & Neurotology, 18 January 2023) gave 47 experienced users a FOX map. It found median improvements of 10 dB at 6,000 Hz and 10% in phonemic discrimination and speech scores after 15 days of take-home use. Two 2019 case studies from the same group reported improved word recognition with AI suggestions in one of two adults. Otoconsult's site describes FOX as an outcome-based application assisting audiologists and AI-FOX as the successor of a deterministic first-generation tool. P. J. Govaerts co-authored all three papers. Whether any author is affiliated with Otoconsult could not be verified from the records read.", "replication": { "produced_by": [ "Outcome measurements (thresholds, loudness scaling, speech scores) fed to the FOX recommender", "Audiologists applying the recommended MAPs" ], "must_hold": [ "Clinicians accept and apply FOX recommendations", "Patients tolerate the map (63% of FOX-arm patients preferred manual maps for comfort)" ], "echoes": [ { "date": "2019-09-17", "setting": "Two adult case studies, same center", "outcome": "recurred", "source": "https://doi.org/10.1080/14670100.2019.1667574" }, { "date": "2023-01-18", "setting": "47 experienced CI users, same center, 15-day take-home comparison", "outcome": "recurred", "source": "https://doi.org/10.1097/mao.0000000000003810" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0115", "title": "China Medical University Hospital's exercise-ECG AI catching a 99% coronary stenosis that manual reading had rated moderate, Taichung, 2022", "summary": "CMUH's exercise-ECG AI put severe-blockage odds at 72% where manual reading said follow-up; angiography found a 99% LAD stenosis, stented.", "date_observed": "2022-12-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 75-year-old man surnamed Chen, with controlled hypertension, woke one day with chest tightness and palpitations first taken for reflux. Liberty Times puts the onset in 2021. At China Medical University Hospital (CMUH), Taichung, his exercise electrocardiogram (ECG) was read manually with a risk score. That gave about 50% blockage, moderate risk, follow-up only. The hospital's own Exercise ECG AI-Assisted Interpretation System, in use since May 2022, put the probability of severe (over 70%) narrowing at 72%. So cardiologist 吳宏彬 ordered angiography, found a 99% stenosis of the left anterior descending artery and stented it at once. He went home, chest tightness resolved. The hospital presented it on 28 December 2022. Test and procedure dates are not reported.", "category": "harm prevented", "unexpected": false, "purpose": "The hospital's AI Center built the system to judge from an exercise ECG whether a patient's coronary arteries are severely narrowed (over 70%). Manual reading of a dozen tracings is slow and, the hospital says, only 40–50% accurate. Flagging this patient's severe stenosis was exactly that purpose.", "system": "運動心電圖AI輔助判讀系統 (Exercise ECG AI-Assisted Interpretation System), China Medical University Hospital", "model_version": "Not reported. The hospital describes a deep-learning model that takes exercise-ECG signals at three time points plus 10 measured and 2 derived features (such as history and maximum workload), trained on nearly 1,000 exercise ECGs matched to catheterization data, accuracy about 80%, sensitivity 88%, in clinical use since May 2022; the authors' 2025 paper describes a convolutional recurrent network with three ECG slices and 12 features, AUC 0.83, sensitivity 0.89, specificity 0.60.", "developer": "China Medical University Hospital (中國醫藥大學附設醫院人工智慧中心), director 許凱程", "deployer": "China Medical University Hospital, Division of Cardiology (心臟血管系), Taichung", "location": "Taichung, Taiwan", "domain": "Healthcare: cardiology diagnostics (exercise stress ECG)", "segment": "Hospital cardiology; in-house clinical AI", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2022-12-28-624f" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A man with a 99% stenosis of the left anterior descending artery had it stented after the AI flagged a 72% probability of severe narrowing. The manual exercise-ECG reading had rated it moderate and left it for drug treatment and follow-up. The cardiologist put his chance of an acute infarction at 8 in 10. He said the stent removed the sudden-death risk. He left hospital, symptoms resolved. The hospital's headlines call it life-saving, but the harm was prospective and the account is the developer-hospital's own, so life-saving is not established." } ], "ai_role": { "status": "assessed", "statement": "The model read the exercise-ECG signals and report features. It returned a 72% probability of severe coronary narrowing, above the moderate-risk verdict of the manual reading and risk score. On that basis the cardiologist ordered angiography, which showed the 99% stenosis, and he stented it. The counterfactual rests on the treating cardiologist's statement, carried by three outlets and the hospital's release. He said the manual reading would have led to drug treatment and follow-up only. The hospital that says so also built the model. The dates of the reading and procedure are not reported. The published model's specificity of 0.60 means such flags are often false positives." }, "evidence": [ { "kind": "news report", "citation": "蔡淑媛 (2022). 胸悶、心悸以為胃食道逆流 竟慢性心肌梗塞99％ [Chest tightness and palpitations taken for reflux turn out to be chronic myocardial infarction, 99% blocked]. 自由健康網 (Liberty Times Health), Taichung, 28 December 2022; print edition 29 December 2022 as 以為胃食道逆流 AI判讀竟是慢性心肌梗塞, https://health.ltn.com.tw/article/paper/1559692.", "title": "胸悶、心悸以為胃食道逆流 竟慢性心肌梗塞99％", "url": "https://health.ltn.com.tw/article/breakingnews/4168516", "date": "2022-12-28", "written_by": "independent", "quote": "同步AI輔助判讀卻發現有嚴重心肌梗塞風險" }, { "kind": "news report", "citation": "寇世菁, 中廣新聞網 (BCC News) (2022). 75歲男起床胸悶心悸 中國附醫運動心電圖AI輔助判讀系統及時救命 [75-year-old man wakes with chest tightness and palpitations; CMUH exercise-ECG AI-assisted interpretation system saves his life in time]. Syndicated on Yahoo奇摩新聞, 28 December 2022.", "title": "75歲男起床胸悶心悸 中國附醫運動心電圖AI輔助判讀系統及時救命", "url": "https://tw.news.yahoo.com/75%E6%AD%B2%E7%94%B7%E8%B5%B7%E5%BA%8A%E8%83%B8%E6%82%B6%E5%BF%83%E6%82%B8-%E4%B8%AD%E5%9C%8B%E9%99%84%E9%86%AB%E9%81%8B%E5%8B%95%E5%BF%83%E9%9B%BB%E5%9C%96ai%E8%BC%94%E5%8A%A9%E5%88%A4%E8%AE%80%E7%B3%BB%E7%B5%B1%E5%8F%8A%E6%99%82%E6%95%91%E5%91%BD-083734634.html", "date": "2022-12-28", "written_by": "independent", "quote": "運動心電圖檢查後，傳統人工判讀，認為追蹤即可" }, { "kind": "news report", "citation": "張雅淳, 周刊王CTWANT (2022). 男子以為胃食道逆流 AI及時判斷「血管堵塞72%」逃過猝死 [Man thought it was reflux; AI judged '72% vessel blockage' in time and he escaped sudden death]. Syndicated on Yahoo奇摩新聞, 28 December 2022.", "title": "男子以為胃食道逆流 AI及時判斷「血管堵塞72%」逃過猝死", "url": "https://tw.news.yahoo.com/%E7%94%B7%E5%AD%90%E4%BB%A5%E7%82%BA%E8%83%83%E9%A3%9F%E9%81%93%E9%80%86%E6%B5%81-ai%E5%8F%8A%E6%99%82%E5%88%A4%E6%96%B7-%E8%A1%80%E7%AE%A1%E5%A0%B5%E5%A1%9E72-%E9%80%83%E9%81%8E%E7%8C%9D%E6%AD%BB-083151068.html", "date": "2022-12-28", "written_by": "independent", "quote": "AI報告顯示：陳伯伯的冠狀動脈血管嚴重阻塞機率已高達72%" }, { "kind": "press release", "citation": "China Medical University Hospital, Public Relations Office 公關室 (2022). 75歲阿伯起床胸悶心悸，冠動脈阻塞高達99％！「運動心電圖AI輔助判讀系統」及時介入治療倖免於難 [75-year-old wakes with chest tightness and palpitations, coronary artery 99% blocked; exercise-ECG AI-assisted interpretation system intervenes in time]. CMUH news no. 8228, 29 December 2022.", "title": "75歲阿伯起床胸悶心悸，冠動脈阻塞高達99％！「運動心電圖AI輔助判讀系統」 及時介入治療倖免於難", "url": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8228", "date": "2022-12-29", "written_by": "makers", "quote": "結果顯示，陳伯伯左前降支狹窄竟已高達99%" }, { "kind": "peer-reviewed study", "citation": "Liang, H.-Y., Hsu, K.-C., Chien, S.-Y., Yeh, C.-Y., Sun, T.-H., Liu, M.-H., & Ng, K. K. (2025). Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease. Frontiers in Artificial Intelligence, 8, 1496109. PMID 40166362; PMC11955648.", "title": "Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease", "url": "https://doi.org/10.3389/frai.2025.1496109", "date": "2025-03-17", "written_by": "makers", "quote": "We retrospectively collected 818 patients who underwent both ExECG and coronary angiography (CAG) within 6 months." } ], "replication": { "produced_by": [ "A patient with atypical symptoms has an exercise ECG at a hospital that runs the AI model alongside the manual reading", "The model's probability of severe (over 70%) stenosis exceeds what the manual reading and risk score suggest. The cardiologist acts on it by ordering angiography", "Angiography confirms a severe stenosis that can be treated at once by stenting" ], "must_hold": [ "The model is run in addition to, not instead of, the clinician's reading. The hospital calls it assisted interpretation and a clinician made every decision", "The clinician is willing to send a patient to invasive angiography on an AI probability score. With the published model's specificity of 0.60, some such patients will have no severe lesion", "The patient is seen at a hospital that has the system. The sources describe it only at CMUH, in use from May 2022" ], "echoes": [] }, "paired_incident": null, "headline": "CMUH's exercise-ECG AI catches a 99% LAD stenosis rated moderate", "metric": "angiography found a 99% LAD stenosis, stented", "comparator": null, "later": { "status": "persisted", "date": "2025-03-17", "note": "The hospital's cardiology group published the algorithm in Frontiers in Artificial Intelligence in March 2025 with external validation on its own patients after February 2022 and at Asia University Hospital.", "quote": "Our study provides an efficient and accurate tool to identify patients with significant CAD by the AI-enhanced ExECG algorithm, which achieved an AUC of 0.83, a sensitivity of 0.89, and a specificity of 0.60, within 1 min.", "url": "https://doi.org/10.3389/frai.2025.1496109" }, "value": null, "developer_country": "Taiwan", "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-12-28-624f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://doi.org/10.3389/frai.2025.1496109", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://zh.wikipedia.org/wiki/%E4%B8%AD%E5%9C%8B%E9%86%AB%E8%97%A5%E5%A4%A7%E5%AD%B8%E9%99%84%E8%A8%AD%E9%86%AB%E9%99%A2; https://en.wikipedia.org/wiki/China_Medical_University_(Taiwan)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to China Medical University Hospital.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' peer-reviewed study and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0115", "catalog_version": "1.0.0", "source_fingerprint": "ada0f6e4bf20d8d0f0d30c3ff523e1b613ca3f8d97c3269834cf564e62df77c8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0115-source-0001", "AIBD-0115-source-0002", "AIBD-0115-source-0003", "AIBD-0115-source-0004", "AIBD-0115-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "China Medical University Hospital (中國醫藥大學附設醫院人工智慧中心), director 許凱程", "deployer": "China Medical University Hospital, Division of Cardiology (心臟血管系), Taichung" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model read the exercise-ECG signals and report features. 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Liberty Times puts the onset in 2021. At China Medical University Hospital (CMUH), Taichung, his exercise electrocardiogram (ECG) was read manually with a risk score. That gave about 50% blockage, moderate risk, follow-up only. The hospital's own Exercise ECG AI-Assisted Interpretation System, in use since May 2022, put the probability of severe (over 70%) narrowing at 72%. So cardiologist 吳宏彬 ordered angiography, found a 99% stenosis of the left anterior descending artery and stented it at once. He went home, chest tightness resolved. The hospital presented it on 28 December 2022. 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Flagging this patient's severe stenosis was exactly that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2022-12-28", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-12-28-624f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://doi.org/10.3389/frai.2025.1496109", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://zh.wikipedia.org/wiki/%E4%B8%AD%E5%9C%8B%E9%86%AB%E8%97%A5%E5%A4%A7%E5%AD%B8%E9%99%84%E8%A8%AD%E9%86%AB%E9%99%A2; https://en.wikipedia.org/wiki/China_Medical_University_(Taiwan)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to China Medical University Hospital.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A patient with atypical symptoms has an exercise ECG at a hospital that runs the AI model alongside the manual reading", "The model's probability of severe (over 70%) stenosis exceeds what the manual reading and risk score suggest. The cardiologist acts on it by ordering angiography", "Angiography confirms a severe stenosis that can be treated at once by stenting" ], "must_hold": [ "The model is run in addition to, not instead of, the clinician's reading. The hospital calls it assisted interpretation and a clinician made every decision", "The clinician is willing to send a patient to invasive angiography on an AI probability score. With the published model's specificity of 0.60, some such patients will have no severe lesion", "The patient is seen at a hospital that has the system. The sources describe it only at CMUH, in use from May 2022" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2022-12-28-624f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://doi.org/10.3389/frai.2025.1496109", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://zh.wikipedia.org/wiki/%E4%B8%AD%E5%9C%8B%E9%86%AB%E8%97%A5%E5%A4%A7%E5%AD%B8%E9%99%84%E8%A8%AD%E9%86%AB%E9%99%A2; https://en.wikipedia.org/wiki/China_Medical_University_(Taiwan)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to China Medical University Hospital.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare: cardiology diagnostics (exercise stress ECG)", "segment": "Hospital cardiology; in-house clinical AI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "蔡淑媛 (2022). 胸悶、心悸以為胃食道逆流 竟慢性心肌梗塞99％ [Chest tightness and palpitations taken for reflux turn out to be chronic myocardial infarction, 99% blocked]. 自由健康網 (Liberty Times Health), Taichung, 28 December 2022; print edition 29 December 2022 as 以為胃食道逆流 AI判讀竟是慢性心肌梗塞, https://health.ltn.com.tw/article/paper/1559692.", "title": "胸悶、心悸以為胃食道逆流 竟慢性心肌梗塞99％", "url": "https://health.ltn.com.tw/article/breakingnews/4168516", "date": "2022-12-28", "written_by": "independent", "quote": "同步AI輔助判讀卻發現有嚴重心肌梗塞風險" }, { "kind": "news report", "citation": "寇世菁, 中廣新聞網 (BCC News) (2022). 75歲男起床胸悶心悸 中國附醫運動心電圖AI輔助判讀系統及時救命 [75-year-old man wakes with chest tightness and palpitations; CMUH exercise-ECG AI-assisted interpretation system saves his life in time]. 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Syndicated on Yahoo奇摩新聞, 28 December 2022.", "title": "男子以為胃食道逆流 AI及時判斷「血管堵塞72%」逃過猝死", "url": "https://tw.news.yahoo.com/%E7%94%B7%E5%AD%90%E4%BB%A5%E7%82%BA%E8%83%83%E9%A3%9F%E9%81%93%E9%80%86%E6%B5%81-ai%E5%8F%8A%E6%99%82%E5%88%A4%E6%96%B7-%E8%A1%80%E7%AE%A1%E5%A0%B5%E5%A1%9E72-%E9%80%83%E9%81%8E%E7%8C%9D%E6%AD%BB-083151068.html", "date": "2022-12-28", "written_by": "independent", "quote": "AI報告顯示：陳伯伯的冠狀動脈血管嚴重阻塞機率已高達72%" }, { "kind": "press release", "citation": "China Medical University Hospital, Public Relations Office 公關室 (2022). 75歲阿伯起床胸悶心悸，冠動脈阻塞高達99％！「運動心電圖AI輔助判讀系統」及時介入治療倖免於難 [75-year-old wakes with chest tightness and palpitations, coronary artery 99% blocked; exercise-ECG AI-assisted interpretation system intervenes in time]. CMUH news no. 8228, 29 December 2022.", "title": "75歲阿伯起床胸悶心悸，冠動脈阻塞高達99％！「運動心電圖AI輔助判讀系統」 及時介入治療倖免於難", "url": "https://www.cmuh.cmu.edu.tw/NewsInfo/NewsArticle?no=8228", "date": "2022-12-29", "written_by": "makers", "quote": "結果顯示，陳伯伯左前降支狹窄竟已高達99%" }, { "kind": "peer-reviewed study", "citation": "Liang, H.-Y., Hsu, K.-C., Chien, S.-Y., Yeh, C.-Y., Sun, T.-H., Liu, M.-H., & Ng, K. K. (2025). Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease. Frontiers in Artificial Intelligence, 8, 1496109. PMID 40166362; PMC11955648.", "title": "Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease", "url": "https://doi.org/10.3389/frai.2025.1496109", "date": "2025-03-17", "written_by": "makers", "quote": "We retrospectively collected 818 patients who underwent both ExECG and coronary angiography (CAG) within 6 months." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CMUH's exercise-ECG AI put severe-blockage odds at 72% where manual reading said follow-up; angiography found a 99% LAD stenosis, stented.", "account": "A 75-year-old man surnamed Chen, with controlled hypertension, woke one day with chest tightness and palpitations first taken for reflux. Liberty Times puts the onset in 2021. At China Medical University Hospital (CMUH), Taichung, his exercise electrocardiogram (ECG) was read manually with a risk score. That gave about 50% blockage, moderate risk, follow-up only. The hospital's own Exercise ECG AI-Assisted Interpretation System, in use since May 2022, put the probability of severe (over 70%) narrowing at 72%. So cardiologist 吳宏彬 ordered angiography, found a 99% stenosis of the left anterior descending artery and stented it at once. He went home, chest tightness resolved. The hospital presented it on 28 December 2022. Test and procedure dates are not reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model estimated the probability of coronary narrowing from exercise ECGs and clinical features." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The model combined exercise ECG recordings from three time points with 12 measured or derived clinical features." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The model analyzed exercise ECG signals and clinical features to assess coronary artery disease." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A deep-learning model that processes exercise ECG recordings and clinical features." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported. The hospital describes a deep-learning model that takes exercise-ECG signals at three time points plus 10 measured and 2 derived features (such as history and maximum workload), trained on nearly 1,000 exercise ECGs matched to catheterization data, accuracy about 80%, sensitivity 88%, in clinical use since May 2022; the authors' 2025 paper describes a convolutional recurrent network with three ECG slices and 12 features, AUC 0.83, sensitivity 0.89, specificity 0.60." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "運動心電圖AI輔助判讀系統 (Exercise ECG AI-Assisted Interpretation System), China Medical University Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "China Medical University Hospital (中國醫藥大學附設醫院人工智慧中心), director 許凱程" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "China Medical University Hospital's exercise-ECG AI catching a 99% coronary stenosis that manual reading had rated moderate, Taichung, 2022", "headline": "CMUH's exercise-ECG AI catches a 99% LAD stenosis rated moderate" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ada0f6e4bf20d8d0f0d30c3ff523e1b613ca3f8d97c3269834cf564e62df77c8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 75-year-old man surnamed Chen, with controlled hypertension, woke one day with chest tightness and palpitations first taken for reflux. Liberty Times puts the onset in 2021. At China Medical University Hospital (CMUH), Taichung, his exercise electrocardiogram (ECG) was read manually with a risk score. That gave about 50% blockage, moderate risk, follow-up only. The hospital's own Exercise ECG AI-Assisted Interpretation System, in use since May 2022, put the probability of severe (over 70%) narrowing at 72%. So cardiologist 吳宏彬 ordered angiography, found a 99% stenosis of the left anterior descending artery and stented it at once. He went home, chest tightness resolved. The hospital presented it on 28 December 2022. Test and procedure dates are not reported.", "replication": { "produced_by": [ "A patient with atypical symptoms has an exercise ECG at a hospital that runs the AI model alongside the manual reading", "The model's probability of severe (over 70%) stenosis exceeds what the manual reading and risk score suggest. The cardiologist acts on it by ordering angiography", "Angiography confirms a severe stenosis that can be treated at once by stenting" ], "must_hold": [ "The model is run in addition to, not instead of, the clinician's reading. The hospital calls it assisted interpretation and a clinician made every decision", "The clinician is willing to send a patient to invasive angiography on an AI probability score. With the published model's specificity of 0.60, some such patients will have no severe lesion", "The patient is seen at a hospital that has the system. The sources describe it only at CMUH, in use from May 2022" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0037", "title": "Face2Gene redirects an 18-year misdiagnosis of Cornelia de Lange syndrome toward DYRK1A-related MRD7 in a 22-year-old man", "summary": "Face2Gene suggested MRD7 for a 22-year-old misdiagnosed with Cornelia de Lange at age 4; exome sequencing confirmed a DYRK1A variant.", "date_observed": "2023-01-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Obara, Abe and Toyoshima of the National Hospital Organization Akita National Hospital, Japan, reported a 22-year-old man in Cureus on 5 January 2023. He had been diagnosed with Cornelia de Lange syndrome at age four based on facial dysmorphism, microcephaly, short stature and intellectual disability. At 22 his Cornelia de Lange clinical diagnostic score was 5 of 19. His frontal facial photograph and clinical features were uploaded to Face2Gene. This “introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7”. The paper gives no ranking or scores for these candidates. Whole-exome sequencing then identified a novel heterozygous DYRK1A variant, c.848dup, p.(Asn283LysfsTer6), confirming MRD7. The 18-year span in the title derives from the ages the paper gives, diagnosed at four and re-evaluated at 22. The paper does not state a duration. The consultation date is not given.", "category": "benefit created", "unexpected": false, "purpose": "Face2Gene is built to suggest candidate syndromes from facial images and clinical features. This suggestion was that purpose.", "system": "Face2Gene (DeepGestalt facial phenotyping)", "model_version": null, "developer": "FDNA", "deployer": "Department of Neurology, National Hospital Organization Akita National Hospital", "location": "Yurihonjo, Japan", "domain": "Healthcare / clinical genetics", "segment": "Rare disease diagnosis", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "A correct molecular diagnosis replaced a misdiagnosis held since age four. The report documents no treatment change, so material rather than life-changing." } ], "ai_role": { "status": "assessed", "statement": "Face2Gene listed MRD7 among four candidates. The paper gives no ranking. Whole-exome sequencing made the diagnosis. The AI redirected the differential after the clinical score undermined the prior diagnosis." }, "evidence": [ { "kind": "case report", "citation": "Obara K, Abe E, Toyoshima I (2023). Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7. Cureus (PMC9822525).", "title": "Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "date": "2023-01-05", "written_by": "deployer", "quote": "As a result, Face2Gene introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7." } ], "replication": { "produced_by": [ "Frontal facial photograph plus clinical features uploaded to Face2Gene", "A prior clinical diagnosis that no longer fit the clinical score", "Access to whole-exome sequencing to confirm" ], "must_hold": [ "The true syndrome is represented in Face2Gene's training data (authors note MRD7 recommendations improve as cases are registered)", "Clinicians pursue a candidate that is one of several suggestions" ], "echoes": [ { "date": "2025-11-01", "setting": "International case series, 17 cases / 19 patients, in which DeepGestalt changed geneticists' testing decisions; American Journal of Medical Genetics Part A vol. 197 issue 11 (issue month, first day used)", "model_version": null, "outcome": "recurred", "source": "Rudy NL, Gomes A, et al. (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time. Am J Med Genet A, https://doi.org/10.1002/ajmg.a.64171 (quote: 'We present 17 cases involving 19 patients')" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "582", "title": "Racial Bias in Lung Function Diagnostic Algorithm Leads to Underdiagnosis in Black Men", "url": "https://incidentdatabase.ai/cite/582", "severity": null, "group": "personal", "basis": "Clinician-facing diagnostic algorithm: Face2Gene redirected an 18-year misdiagnosis, while a race-adjusted lung-function diagnostic algorithm led to inaccurate or delayed diagnoses for Black men at the University of Pennsylvania Health System." }, "headline": "Face2Gene suggests MRD7 after an 18-year misdiagnosis", "metric": null, "comparator": { "against": "the clinical diagnosis of Cornelia de Lange syndrome made at age four", "before": "At four years of age, he was clinically diagnosed with Cornelia de Lange syndrome (CdLS; OMIM 122470, 300590, 300882, 610759, and 614701) due to his facial dysmorphism, microcephaly, short stature, and intellectual disability.", "after": "Face2Gene introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7.", "basis": "measured", "quote": "As a result, Face2Gene introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 582 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/582", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored the OMIM/MIM identifiers to the Face2Gene candidate-list quote in the evidence and the account so that it is verbatim, replaced the unsupported “not ranked first” and “non-top-ranked suggestion” wording with a statement that the paper gives no ranking, and noted in the account that the title's 18-year span is derived from the stated ages of four and 22 because the paper gives no duration.", "source": "Obara K, Abe E, Toyoshima I (2023) Cureus, PMC9822525 (full text checked via Europe PMC): https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fdna.com/privacy-policy/; https://akita.hosp.go.jp/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0037", "catalog_version": "1.0.0", "source_fingerprint": "d5a1a59dc70987ebbc1af9e729b075dc82d3e0c327e586efc7162336512a528e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0037-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "FDNA", "deployer": "Department of Neurology, National Hospital Organization Akita National Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Face2Gene listed MRD7 among four candidates. 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He had been diagnosed with Cornelia de Lange syndrome at age four based on facial dysmorphism, microcephaly, short stature and intellectual disability. At 22 his Cornelia de Lange clinical diagnostic score was 5 of 19. His frontal facial photograph and clinical features were uploaded to Face2Gene. This “introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7”. The paper gives no ranking or scores for these candidates. Whole-exome sequencing then identified a novel heterozygous DYRK1A variant, c.848dup, p.(Asn283LysfsTer6), confirming MRD7. The 18-year span in the title derives from the ages the paper gives, diagnosed at four and re-evaluated at 22. The paper does not state a duration. 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The report documents no treatment change, so material rather than life-changing." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Face2Gene is built to suggest candidate syndromes from facial images and clinical features. This suggestion was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Yurihonjo, Japan", "developer_country": "United States", "deployer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Face2Gene is built to suggest candidate syndromes from facial images and clinical features. This suggestion was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-01-05", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 582 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/582", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored the OMIM/MIM identifiers to the Face2Gene candidate-list quote in the evidence and the account so that it is verbatim, replaced the unsupported “not ranked first” and “non-top-ranked suggestion” wording with a statement that the paper gives no ranking, and noted in the account that the title's 18-year span is derived from the stated ages of four and 22 because the paper gives no duration.", "source": "Obara K, Abe E, Toyoshima I (2023) Cureus, PMC9822525 (full text checked via Europe PMC): https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fdna.com/privacy-policy/; https://akita.hosp.go.jp/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Frontal facial photograph plus clinical features uploaded to Face2Gene", "A prior clinical diagnosis that no longer fit the clinical score", "Access to whole-exome sequencing to confirm" ], "must_hold": [ "The true syndrome is represented in Face2Gene's training data (authors note MRD7 recommendations improve as cases are registered)", "Clinicians pursue a candidate that is one of several suggestions" ], "echoes": [ { "date": "2025-11-01", "setting": "International case series, 17 cases / 19 patients, in which DeepGestalt changed geneticists' testing decisions; American Journal of Medical Genetics Part A vol. 197 issue 11 (issue month, first day used)", "outcome": "recurred", "source": "Rudy NL, Gomes A, et al. (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time. Am J Med Genet A, https://doi.org/10.1002/ajmg.a.64171 (quote: 'We present 17 cases involving 19 patients')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Frontal facial photograph plus clinical features uploaded to Face2Gene", "A prior clinical diagnosis that no longer fit the clinical score", "Access to whole-exome sequencing to confirm" ], "must_hold": [ "The true syndrome is represented in Face2Gene's training data (authors note MRD7 recommendations improve as cases are registered)", "Clinicians pursue a candidate that is one of several suggestions" ], "echoes": [ { "date": "2025-11-01", "setting": "International case series, 17 cases / 19 patients, in which DeepGestalt changed geneticists' testing decisions; American Journal of Medical Genetics Part A vol. 197 issue 11 (issue month, first day used)", "outcome": "recurred", "source": "Rudy NL, Gomes A, et al. (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time. Am J Med Genet A, https://doi.org/10.1002/ajmg.a.64171 (quote: 'We present 17 cases involving 19 patients')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 582 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/582", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored the OMIM/MIM identifiers to the Face2Gene candidate-list quote in the evidence and the account so that it is verbatim, replaced the unsupported “not ranked first” and “non-top-ranked suggestion” wording with a statement that the paper gives no ranking, and noted in the account that the title's 18-year span is derived from the stated ages of four and 22 because the paper gives no duration.", "source": "Obara K, Abe E, Toyoshima I (2023) Cureus, PMC9822525 (full text checked via Europe PMC): https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fdna.com/privacy-policy/; https://akita.hosp.go.jp/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare / clinical genetics", "segment": "Rare disease diagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Obara K, Abe E, Toyoshima I (2023). Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7. Cureus (PMC9822525).", "title": "Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "date": "2023-01-05", "written_by": "deployer", "quote": "As a result, Face2Gene introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0037-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Obara K, Abe E, Toyoshima I (2023). Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7. Cureus (PMC9822525).", "title": "Whole-Exome Sequencing Identified a Novel DYRK1A Variant in a Patient With Intellectual Developmental Disorder, Autosomal Dominant 7", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/", "date": "2023-01-05", "written_by": "deployer", "quote": "As a result, Face2Gene introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Face2Gene suggested MRD7 for a 22-year-old misdiagnosed with Cornelia de Lange at age 4; exome sequencing confirmed a DYRK1A variant.", "account": "Obara, Abe and Toyoshima of the National Hospital Organization Akita National Hospital, Japan, reported a 22-year-old man in Cureus on 5 January 2023. He had been diagnosed with Cornelia de Lange syndrome at age four based on facial dysmorphism, microcephaly, short stature and intellectual disability. At 22 his Cornelia de Lange clinical diagnostic score was 5 of 19. His frontal facial photograph and clinical features were uploaded to Face2Gene. This “introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7”. The paper gives no ranking or scores for these candidates. Whole-exome sequencing then identified a novel heterozygous DYRK1A variant, c.848dup, p.(Asn283LysfsTer6), confirming MRD7. The 18-year span in the title derives from the ages the paper gives, diagnosed at four and re-evaluated at 22. The paper does not state a duration. The consultation date is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Face2Gene (DeepGestalt facial phenotyping)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "FDNA" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Face2Gene redirects an 18-year misdiagnosis of Cornelia de Lange syndrome toward DYRK1A-related MRD7 in a 22-year-old man", "headline": "Face2Gene suggests MRD7 after an 18-year misdiagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d5a1a59dc70987ebbc1af9e729b075dc82d3e0c327e586efc7162336512a528e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Obara, Abe and Toyoshima of the National Hospital Organization Akita National Hospital, Japan, reported a 22-year-old man in Cureus on 5 January 2023. He had been diagnosed with Cornelia de Lange syndrome at age four based on facial dysmorphism, microcephaly, short stature and intellectual disability. At 22 his Cornelia de Lange clinical diagnostic score was 5 of 19. His frontal facial photograph and clinical features were uploaded to Face2Gene. This “introduced the following candidate diseases: Angelman syndrome (AS, OMIM 105833), Witteveen-Kolk syndrome (WKOS; MIM 613406), Rubinstein-Taybi syndrome (RTS; OMIM 180849), and MRD7”. The paper gives no ranking or scores for these candidates. Whole-exome sequencing then identified a novel heterozygous DYRK1A variant, c.848dup, p.(Asn283LysfsTer6), confirming MRD7. The 18-year span in the title derives from the ages the paper gives, diagnosed at four and re-evaluated at 22. The paper does not state a duration. The consultation date is not given.", "replication": { "produced_by": [ "Frontal facial photograph plus clinical features uploaded to Face2Gene", "A prior clinical diagnosis that no longer fit the clinical score", "Access to whole-exome sequencing to confirm" ], "must_hold": [ "The true syndrome is represented in Face2Gene's training data (authors note MRD7 recommendations improve as cases are registered)", "Clinicians pursue a candidate that is one of several suggestions" ], "echoes": [ { "date": "2025-11-01", "setting": "International case series, 17 cases / 19 patients, in which DeepGestalt changed geneticists' testing decisions; American Journal of Medical Genetics Part A vol. 197 issue 11 (issue month, first day used)", "outcome": "recurred", "source": "Rudy NL, Gomes A, et al. (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time. Am J Med Genet A, https://doi.org/10.1002/ajmg.a.64171 (quote: 'We present 17 cases involving 19 patients')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0048", "title": "Fabric GEM AI ranked the causal ANTXR2 variant, diagnosing infantile hyaline fibromatosis in a six-month-old", "summary": "AI-assisted rapid genome sequencing scored a homozygous ANTXR2 variant at 4.7, diagnosing an infant within five days and changing her care plan.", "date_observed": "2023-01-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The report's abstract describes a six-month-old infant with a history of painful extremity contractures. Its case presentation opens with a four-month-old girl referred to the pediatric emergency department at Robert Wood Johnson University Hospital. She was referred for failure to thrive with abdominal distension and global developmental delay. The paper dates her abnormal neurological development to two months of age. It included bilateral upper-extremity hypotonia, a weak palmar grasp, pain with all passive and active extremity movement and bilateral contractures. A bleeding, ulcerated infantile hemangioma in the center of the neck was managed from three months of age. The diminishing appetite and abdominal distension were noted at four months. Rapid whole-genome sequencing at Rady Children's Institute for Genomic Medicine used the Fabric GEM artificial-intelligence analysis tool with Phevor re-ranking. The sample was shipped on 5 January 2023 and preliminary results were returned on 10 January 2023. GEM scored a homozygous ANTXR2 variant, c.652T>C (p.Cys218Arg), at 4.7. That gave a diagnosis of infantile hyaline fibromatosis syndrome. A multidisciplinary meeting held the same day conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. Treating clinicians reported the case in Cureus on 9 June 2024.", "category": "benefit created", "unexpected": false, "purpose": "Rank candidate variants from rapid whole-genome sequencing against the patient's phenotype so that clinicians can reach a molecular diagnosis quickly.", "system": "Fabric GEM artificial-intelligence variant interpretation tool with Phevor phenotype-driven re-ranking", "model_version": null, "developer": "Fabric Genomics, Oakland, California", "deployer": "Rady Children's Institute for Genomic Medicine and Robert Wood Johnson University Hospital", "location": "New Brunswick, New Jersey, United States", "domain": "Clinical genomics / rare disease diagnosis", "segment": "Critically ill infant undergoing rapid whole-genome sequencing", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "An identifiable infant received a definitive molecular diagnosis of a disorder the authors describe as frequently causing early death before age two. This triggered a same-day multidisciplinary meeting that conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. The authors add that extensive genetic counseling is essential for parents desiring future children, given a 25% risk for the offspring of carrier parents. They do not report that counseling was delivered." }, { "group": "organizational", "depth": 1, "reason": "A single case in which preliminary results returned five days after the sample shipped, on 5 January 2023, with results on 10 January 2023. Genomic panels and a microarray sent from the institution were still pending and anticipated to take longer than one month. The report does not say what became of those tests." } ], "ai_role": { "status": "assessed", "statement": "GEM scored and surfaced the homozygous ANTXR2 variant at 4.7. The paper says Bayes factor scores greater than 2 are considered strong support. Phevor also identified the variant but scored it 1. That is below the Phevor score of 5 or above that the paper treats as further guidance on what to prioritize. The clinicians then confirmed and interpreted the finding and made the diagnosis. The report is written by the treating clinicians and a Rady clinical genomics scientist, not by the tool's vendor." }, "evidence": [ { "kind": "case report", "citation": "Ye GX, Ontiveros E, Ivander A, Velinov M, Simotas C (2024). Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using Artificial Intelligence-Assisted Rapid Whole Genome Sequencing. Cureus.", "title": "Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using AI-Assisted Rapid Whole Genome Sequencing", "url": "https://europepmc.org/article/PMC/PMC11234061", "date": "2024-06-09", "written_by": "deployer", "quote": "Variants with a GEM score ≥ 0 were reviewed for this proband leading to the identification of a homozygous c.652T>C (p.Cys218Arg) variant in the ANTXR2 gene" }, { "kind": "peer-reviewed study", "citation": "Owen MJ, Kingsmore SF, et al. (2022). An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases. Nat Commun. Led from Rady Children's Institute for Genomic Medicine, with Fabric Genomics and Illumina staff among the co-authors.", "title": "An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "date": "2022-07-26", "written_by": "makers", "quote": "The average rank of the correct diagnosis was 1, 2 and 1 for MOON, GEM and TSS, respectively" } ], "replication": { "produced_by": [ "Rapid whole-genome sequencing of a critically ill infant", "Structured phenotype terms entered for the patient", "AI ranking of candidate variants reviewed and confirmed by clinicians" ], "must_hold": [ "Rapid whole-genome sequencing of the proband", "Structured phenotype terms entered for the patient", "Clinician review and confirmation of the ranked variant" ], "echoes": [ { "date": "2022-07-26", "setting": "Rady Children's automated 13.5-hour diagnosis system, four retrospective infant cases", "model_version": "GEM (Fabric Genomics)", "outcome": "recurred", "source": "Owen MJ, et al. Nat Commun 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "123", "title": "Epic Systems’s Sepsis Prediction Algorithms Revealed to Have High Error Rates on Seriously Ill Patients", "url": "https://incidentdatabase.ai/cite/123", "severity": null, "group": "personal", "basis": "Both are hospital decision-support systems meant to flag a life-threatening condition in a critically ill patient; Epic's false negatives and false positives left seriously ill inpatients unrecognised by their clinicians." }, "headline": "Fabric GEM flags ANTXR2 and diagnoses an infant in five days", "metric": "scored a homozygous ANTXR2 variant at 4.7, diagnosing an infant within five days", "comparator": { "against": "chromosomal microarray and targeted gene panels", "before": "one to two weeks for much more limited results from chromosomal microarray and four to six weeks for targeted gene panels", "after": "less than five days", "basis": "assumed", "quote": "Using a combination of next-generation sequencing and these novel artificial intelligence methods, Rady has been able to lower the total turnaround time for commercial rWGS to less than five days, compared to one to two weeks for much more limited results from chromosomal microarray and four to six weeks for targeted gene panels", "url": "https://europepmc.org/article/PMC/PMC11234061" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 123 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/123", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Dropped the claim that the diagnosis ended further investigation at the treating hospital, restated the GEM and Phevor thresholds as the paper gives them (greater than 2, and 5 or above), dated the presenting findings as the paper dates them, recast the 25% recurrence risk as the authors' recommendation that counseling is essential rather than counseling delivered, and marked the 13.5-hour Nature Communications paper as not vendor-authored, because each of those statements went further than the sources do.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11234061/ ; https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11234061", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fabricgenomics.com/privacy-policy/; https://radygenomics.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0048", "catalog_version": "1.0.0", "source_fingerprint": "a3075cb0abfb0ae85e7a06197875788a02a454737eaf475f4b55f59abb44644a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0048-source-0001", "AIBD-0048-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fabric Genomics, Oakland, California", "deployer": "Rady Children's Institute for Genomic Medicine and Robert Wood Johnson University Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "GEM scored and surfaced the homozygous ANTXR2 variant at 4.7. 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The report documents a diagnosis and care decisions, without establishing longer survival." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "123", "title": "Epic Systems’s Sepsis Prediction Algorithms Revealed to Have High Error Rates on Seriously Ill Patients", "url": "https://incidentdatabase.ai/cite/123", "group": "personal", "basis": "Both are hospital decision-support systems meant to flag a life-threatening condition in a critically ill patient; Epic's false negatives and false positives left seriously ill inpatients unrecognised by their clinicians." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later development found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0048" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "An infant and the clinicians who investigated her condition." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "An infant and the clinicians who investigated her condition." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "One infant." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "One infant." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The report's abstract describes a six-month-old infant with a history of painful extremity contractures. Its case presentation opens with a four-month-old girl referred to the pediatric emergency department at Robert Wood Johnson University Hospital. She was referred for failure to thrive with abdominal distension and global developmental delay. The paper dates her abnormal neurological development to two months of age. It included bilateral upper-extremity hypotonia, a weak palmar grasp, pain with all passive and active extremity movement and bilateral contractures. A bleeding, ulcerated infantile hemangioma in the center of the neck was managed from three months of age. The diminishing appetite and abdominal distension were noted at four months. Rapid whole-genome sequencing at Rady Children's Institute for Genomic Medicine used the Fabric GEM artificial-intelligence analysis tool with Phevor re-ranking. The sample was shipped on 5 January 2023 and preliminary results were returned on 10 January 2023. GEM scored a homozygous ANTXR2 variant, c.652T>C (p.Cys218Arg), at 4.7. That gave a diagnosis of infantile hyaline fibromatosis syndrome. A multidisciplinary meeting held the same day conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. 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This triggered a same-day multidisciplinary meeting that conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. The authors add that extensive genetic counseling is essential for parents desiring future children, given a 25% risk for the offspring of carrier parents. They do not report that counseling was delivered." }, { "group": "organizational", "depth": 1, "reason": "A single case in which preliminary results returned five days after the sample shipped, on 5 January 2023, with results on 10 January 2023. Genomic panels and a microarray sent from the institution were still pending and anticipated to take longer than one month. The report does not say what became of those tests." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Rank candidate variants from rapid whole-genome sequencing against the patient's phenotype so that clinicians can reach a molecular diagnosis quickly." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "New Brunswick, New Jersey, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Rank candidate variants from rapid whole-genome sequencing against the patient's phenotype so that clinicians can reach a molecular diagnosis quickly." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-01-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 123 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/123", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Dropped the claim that the diagnosis ended further investigation at the treating hospital, restated the GEM and Phevor thresholds as the paper gives them (greater than 2, and 5 or above), dated the presenting findings as the paper dates them, recast the 25% recurrence risk as the authors' recommendation that counseling is essential rather than counseling delivered, and marked the 13.5-hour Nature Communications paper as not vendor-authored, because each of those statements went further than the sources do.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11234061/ ; https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11234061", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fabricgenomics.com/privacy-policy/; https://radygenomics.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Rapid whole-genome sequencing of a critically ill infant", "Structured phenotype terms entered for the patient", "AI ranking of candidate variants reviewed and confirmed by clinicians" ], "must_hold": [ "Rapid whole-genome sequencing of the proband", "Structured phenotype terms entered for the patient", "Clinician review and confirmation of the ranked variant" ], "echoes": [ { "date": "2022-07-26", "setting": "Rady Children's automated 13.5-hour diagnosis system, four retrospective infant cases", "model_version": "GEM (Fabric Genomics)", "outcome": "recurred", "source": "Owen MJ, et al. Nat Commun 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Rapid whole-genome sequencing of a critically ill infant", "Structured phenotype terms entered for the patient", "AI ranking of candidate variants reviewed and confirmed by clinicians" ], "must_hold": [ "Rapid whole-genome sequencing of the proband", "Structured phenotype terms entered for the patient", "Clinician review and confirmation of the ranked variant" ], "echoes": [ { "date": "2022-07-26", "setting": "Rady Children's automated 13.5-hour diagnosis system, four retrospective infant cases", "model_version": "GEM (Fabric Genomics)", "outcome": "recurred", "source": "Owen MJ, et al. Nat Commun 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Rapid genome sequencing, detailed symptoms, and clinicians who can review and confirm the suggested variant are needed." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 123 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/123", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Dropped the claim that the diagnosis ended further investigation at the treating hospital, restated the GEM and Phevor thresholds as the paper gives them (greater than 2, and 5 or above), dated the presenting findings as the paper dates them, recast the 25% recurrence risk as the authors' recommendation that counseling is essential rather than counseling delivered, and marked the 13.5-hour Nature Communications paper as not vendor-authored, because each of those statements went further than the sources do.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11234061/ ; https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11234061", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fabricgenomics.com/privacy-policy/; https://radygenomics.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Clinical genomics / rare disease diagnosis", "segment": "Critically ill infant undergoing rapid whole-genome sequencing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Ye GX, Ontiveros E, Ivander A, Velinov M, Simotas C (2024). Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using Artificial Intelligence-Assisted Rapid Whole Genome Sequencing. Cureus.", "title": "Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using AI-Assisted Rapid Whole Genome Sequencing", "url": "https://europepmc.org/article/PMC/PMC11234061", "date": "2024-06-09", "written_by": "deployer", "quote": "Variants with a GEM score ≥ 0 were reviewed for this proband leading to the identification of a homozygous c.652T>C (p.Cys218Arg) variant in the ANTXR2 gene" }, { "kind": "peer-reviewed study", "citation": "Owen MJ, Kingsmore SF, et al. (2022). An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases. Nat Commun. Led from Rady Children's Institute for Genomic Medicine, with Fabric Genomics and Illumina staff among the co-authors.", "title": "An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "date": "2022-07-26", "written_by": "makers", "quote": "The average rank of the correct diagnosis was 1, 2 and 1 for MOON, GEM and TSS, respectively" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0048-source-0001", "AIBD-0048-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Ye GX, Ontiveros E, Ivander A, Velinov M, Simotas C (2024). Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using Artificial Intelligence-Assisted Rapid Whole Genome Sequencing. Cureus.", "title": "Autosomal Recessive Infantile Hyaline Fibromatosis Identified Using AI-Assisted Rapid Whole Genome Sequencing", "url": "https://europepmc.org/article/PMC/PMC11234061", "date": "2024-06-09", "written_by": "deployer", "quote": "Variants with a GEM score ≥ 0 were reviewed for this proband leading to the identification of a homozygous c.652T>C (p.Cys218Arg) variant in the ANTXR2 gene" }, { "kind": "peer-reviewed study", "citation": "Owen MJ, Kingsmore SF, et al. (2022). An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases. Nat Commun. Led from Rady Children's Institute for Genomic Medicine, with Fabric Genomics and Illumina staff among the co-authors.", "title": "An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/", "date": "2022-07-26", "written_by": "makers", "quote": "The average rank of the correct diagnosis was 1, 2 and 1 for MOON, GEM and TSS, respectively" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI-assisted rapid genome sequencing scored a homozygous ANTXR2 variant at 4.7, diagnosing an infant within five days and changing her care plan.", "account": "The report's abstract describes a six-month-old infant with a history of painful extremity contractures. Its case presentation opens with a four-month-old girl referred to the pediatric emergency department at Robert Wood Johnson University Hospital. She was referred for failure to thrive with abdominal distension and global developmental delay. The paper dates her abnormal neurological development to two months of age. It included bilateral upper-extremity hypotonia, a weak palmar grasp, pain with all passive and active extremity movement and bilateral contractures. A bleeding, ulcerated infantile hemangioma in the center of the neck was managed from three months of age. The diminishing appetite and abdominal distension were noted at four months. Rapid whole-genome sequencing at Rady Children's Institute for Genomic Medicine used the Fabric GEM artificial-intelligence analysis tool with Phevor re-ranking. The sample was shipped on 5 January 2023 and preliminary results were returned on 10 January 2023. GEM scored a homozygous ANTXR2 variant, c.652T>C (p.Cys218Arg), at 4.7. That gave a diagnosis of infantile hyaline fibromatosis syndrome. A multidisciplinary meeting held the same day conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. Treating clinicians reported the case in Cureus on 9 June 2024." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fabric GEM artificial-intelligence variant interpretation tool with Phevor phenotype-driven re-ranking" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Fabric Genomics, Oakland, California" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fabric GEM AI ranked the causal ANTXR2 variant, diagnosing infantile hyaline fibromatosis in a six-month-old", "headline": "Fabric GEM flags ANTXR2 and diagnoses an infant in five days" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a3075cb0abfb0ae85e7a06197875788a02a454737eaf475f4b55f59abb44644a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The report's abstract describes a six-month-old infant with a history of painful extremity contractures. Its case presentation opens with a four-month-old girl referred to the pediatric emergency department at Robert Wood Johnson University Hospital. She was referred for failure to thrive with abdominal distension and global developmental delay. The paper dates her abnormal neurological development to two months of age. It included bilateral upper-extremity hypotonia, a weak palmar grasp, pain with all passive and active extremity movement and bilateral contractures. A bleeding, ulcerated infantile hemangioma in the center of the neck was managed from three months of age. The diminishing appetite and abdominal distension were noted at four months. Rapid whole-genome sequencing at Rady Children's Institute for Genomic Medicine used the Fabric GEM artificial-intelligence analysis tool with Phevor re-ranking. The sample was shipped on 5 January 2023 and preliminary results were returned on 10 January 2023. GEM scored a homozygous ANTXR2 variant, c.652T>C (p.Cys218Arg), at 4.7. That gave a diagnosis of infantile hyaline fibromatosis syndrome. A multidisciplinary meeting held the same day conveyed the implications, coordinated gastrostomy tube placement and discussed long-term goals. Treating clinicians reported the case in Cureus on 9 June 2024.", "replication": { "produced_by": [ "Rapid whole-genome sequencing of a critically ill infant", "Structured phenotype terms entered for the patient", "AI ranking of candidate variants reviewed and confirmed by clinicians" ], "must_hold": [ "Rapid whole-genome sequencing of the proband", "Structured phenotype terms entered for the patient", "Clinician review and confirmation of the ranked variant" ], "echoes": [ { "date": "2022-07-26", "setting": "Rady Children's automated 13.5-hour diagnosis system, four retrospective infant cases", "model_version": "GEM (Fabric Genomics)", "outcome": "recurred", "source": "Owen MJ, et al. Nat Commun 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9325884/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Clinicians submitted the infant’s genome and symptoms for analysis. They reviewed the variants that GEM ranked and confirmed an ANTXR2 variant as the cause of her condition." } } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0217", "title": "Rising Academies' WhatsApp math tutor Rori: school-assigned trial in 11 Ghanaian schools finds a 0.36 effect size over about eight months (arXiv 2024)", "summary": "Preprint by Oxford, Rising Academies and J-PAL North America authors: students using Rori one hour a week in study hall gained 0.36 SD more in math (637 baseline, 477 endline) than controls in 2023.", "date_observed": "2023-02-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Rori is an AI-powered conversational math tutor on WhatsApp created by Rising Academies, an educational network based in Ghana. Henkel (University of Oxford), Horne-Robinson (Rising Academies), Kozhakhmetova and Lee (J-PAL North America) report a preliminary evaluation in 11 Rising Academies schools in Ghana. Students in grades 3–8 took a 35-question math assessment in early February 2023 (baseline) and late August 2023 (endline). 637 students (336 treatment, 301 control) took the baseline and 477 the endline. Treated students were given a phone for one hour a week during study hall to study math with Rori. Controls continued regular instruction. The May 2024 PDF (v2) reports an effect size of 0.36 (Cohen's d, p < 0.001) and a marginal cost of about $5 per student. The arXiv abstract still describes approximately 1,000 students in grades 3–9, two 30-minute sessions a week over 8 months and an effect size of 0.37. That does not match the v2 body.", "category": "general benefit", "unexpected": false, "purpose": "Rori was built to give extra math practice and feedback through chat. The math gain is that purpose.", "system": "Rori, AI-powered conversational math tutor on WhatsApp", "model_version": null, "developer": "Rising Academies", "deployer": "Rising Academies (11 schools)", "location": null, "domain": "Education", "segment": "Primary and junior-secondary math (chat-based tutoring)", "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Treated students' math growth exceeded controls' by 0.36 SD (v2 PDF)." }, { "group": "organizational", "depth": null, "reason": "The deploying network reports a marginal cost of about $5 per student (v2 PDF)." } ], "ai_role": { "status": "assessed", "statement": "Rori delivered the extra practice hour itself, so the comparison is Rori time versus a normal study hall. The authors call the result preliminary, year 1 only. The vendor co-authored the preprint." }, "evidence": [ { "kind": "preprint", "citation": "Henkel O, Horne-Robinson H, Kozhakhmetova N, Lee A (2024). Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana. arXiv:2402.09809 (abstract page; v1 15 Feb 2024, v2 5 May 2024).", "title": "Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana", "url": "https://arxiv.org/abs/2402.09809", "date": "2024-02-15", "written_by": "makers", "quote": "We find that the math growth scores were substantially higher for the treatment group with an effect size of 0.37, and that the results were statistically significant (p < 0.001)." }, { "kind": "preprint", "citation": "Henkel O et al. arXiv:2402.09809v2 PDF (5 May 2024; affiliations Oxford, Rising Academies, J-PAL North America).", "title": "Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI- Math Tutor in Ghana (v2 PDF)", "url": "https://arxiv.org/pdf/2402.09809v2", "date": "2024-05-05", "written_by": "makers", "quote": "The baseline was taken by 637 students in grades 3-8 (336 in Treatment, 301 in Control), of which 477 took the endline and 160 did not." }, { "kind": "press release", "citation": "Sawyers C. Evolving Partnerships in Ghana. Rising Academies news, 6 May 2026.", "title": "Evolving Partnerships in Ghana", "url": "https://www.risingacademies.com/risingnews/deepening-government-partnerships-and-responding-to-demand-in-ghana-1", "date": "2026-05-06", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A chat tutor that runs on basic phones over low-bandwidth networks", "One scheduled hour a week of independent use during study hall with a provided phone", "A control group kept on the normal timetable in the same school network" ], "must_hold": [ "Phone and WhatsApp access during school time", "Schools accustomed to routine testing (the authors cite this against a Hawthorne effect)", "Replication outside the Rising Academies network, which the authors say is still needed" ], "echoes": [] }, "paired_incident": null, "headline": "Rising Academies' WhatsApp tutor Rori lifts math scores 0.36 SD", "metric": "an effect size of 0.36 (Cohen's d, p < 0.001)", "comparator": { "against": "control-group students at schools without Rori access who continued regular math instruction", "before": "control group growth score M = 2.12 (SD = 6.30) between baseline and endline", "after": "treatment group growth score M = 5.13 (SD = 7.03), an effect size of 0.36 (Cohen's d)", "basis": "measured", "quote": "An independent samples t-test between the control (M = 2.12, SD = 6.30) and the treatment group (M = 5.13, SD = 7.03) revealed that the 3.01 difference in growth scores was highly statistically significant (p < 0.001).", "url": "https://arxiv.org/pdf/2402.09809v2" }, "later": { "status": "scaled", "date": "2026-05-06", "note": "By May 2026 Rising Academies was piloting Rori in government schools in Ghana's Eastern Region with World Bank support, had extended the pilot by six months, and was preparing a larger randomized trial in more than 100 public schools from September 2026.", "quote": "With World Bank support, Rising is piloting Rori, our AI-enabled virtual maths tutor, in government schools in Ghana’s Eastern Region. 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Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana. arXiv:2402.09809 (abstract page; v1 15 Feb 2024, v2 5 May 2024).", "title": "Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana", "url": "https://arxiv.org/abs/2402.09809", "date": "2024-02-15", "written_by": "makers", "quote": "We find that the math growth scores were substantially higher for the treatment group with an effect size of 0.37, and that the results were statistically significant (p < 0.001)." }, { "kind": "preprint", "citation": "Henkel O et al. arXiv:2402.09809v2 PDF (5 May 2024; affiliations Oxford, Rising Academies, J-PAL North America).", "title": "Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI- Math Tutor in Ghana (v2 PDF)", "url": "https://arxiv.org/pdf/2402.09809v2", "date": "2024-05-05", "written_by": "makers", "quote": "The baseline was taken by 637 students in grades 3-8 (336 in Treatment, 301 in Control), of which 477 took the endline and 160 did not." }, { "kind": "press release", "citation": "Sawyers C. Evolving Partnerships in Ghana. Rising Academies news, 6 May 2026.", "title": "Evolving Partnerships in Ghana", "url": "https://www.risingacademies.com/risingnews/deepening-government-partnerships-and-responding-to-demand-in-ghana-1", "date": "2026-05-06", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0217-source-0001", "AIBD-0217-source-0002", "AIBD-0217-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Henkel O, Horne-Robinson H, Kozhakhmetova N, Lee A (2024). Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana. arXiv:2402.09809 (abstract page; v1 15 Feb 2024, v2 5 May 2024).", "title": "Effective and Scalable Math Support: Evidence on the Impact of an AI-Tutor on Math Achievement in Ghana", "url": "https://arxiv.org/abs/2402.09809", "date": "2024-02-15", "written_by": "makers", "quote": "We find that the math growth scores were substantially higher for the treatment group with an effect size of 0.37, and that the results were statistically significant (p < 0.001)." }, { "kind": "preprint", "citation": "Henkel O et al. arXiv:2402.09809v2 PDF (5 May 2024; affiliations Oxford, Rising Academies, J-PAL North America).", "title": "Effective and Scalable Math Support: Experimental Evidence on the Impact of an AI- Math Tutor in Ghana (v2 PDF)", "url": "https://arxiv.org/pdf/2402.09809v2", "date": "2024-05-05", "written_by": "makers", "quote": "The baseline was taken by 637 students in grades 3-8 (336 in Treatment, 301 in Control), of which 477 took the endline and 160 did not." }, { "kind": "press release", "citation": "Sawyers C. Evolving Partnerships in Ghana. Rising Academies news, 6 May 2026.", "title": "Evolving Partnerships in Ghana", "url": "https://www.risingacademies.com/risingnews/deepening-government-partnerships-and-responding-to-demand-in-ghana-1", "date": "2026-05-06", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Preprint by Oxford, Rising Academies and J-PAL North America authors: students using Rori one hour a week in study hall gained 0.36 SD more in math (637 baseline, 477 endline) than controls in 2023.", "account": "Rori is an AI-powered conversational math tutor on WhatsApp created by Rising Academies, an educational network based in Ghana. Henkel (University of Oxford), Horne-Robinson (Rising Academies), Kozhakhmetova and Lee (J-PAL North America) report a preliminary evaluation in 11 Rising Academies schools in Ghana. Students in grades 3–8 took a 35-question math assessment in early February 2023 (baseline) and late August 2023 (endline). 637 students (336 treatment, 301 control) took the baseline and 477 the endline. Treated students were given a phone for one hour a week during study hall to study math with Rori. Controls continued regular instruction. The May 2024 PDF (v2) reports an effect size of 0.36 (Cohen's d, p < 0.001) and a marginal cost of about $5 per student. The arXiv abstract still describes approximately 1,000 students in grades 3–9, two 30-minute sessions a week over 8 months and an effect size of 0.37. That does not match the v2 body." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Rori, AI-powered conversational math tutor on WhatsApp" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rising Academies" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rising Academies' WhatsApp math tutor Rori: school-assigned trial in 11 Ghanaian schools finds a 0.36 effect size over about eight months (arXiv 2024)", "headline": "Rising Academies' WhatsApp tutor Rori lifts math scores 0.36 SD" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a43fdb482c8e399ee79647cb2a3b4e26d00c379ec0121d42ecc64fb4152439f5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Rori is an AI-powered conversational math tutor on WhatsApp created by Rising Academies, an educational network based in Ghana. Henkel (University of Oxford), Horne-Robinson (Rising Academies), Kozhakhmetova and Lee (J-PAL North America) report a preliminary evaluation in 11 Rising Academies schools in Ghana. Students in grades 3–8 took a 35-question math assessment in early February 2023 (baseline) and late August 2023 (endline). 637 students (336 treatment, 301 control) took the baseline and 477 the endline. Treated students were given a phone for one hour a week during study hall to study math with Rori. Controls continued regular instruction. The May 2024 PDF (v2) reports an effect size of 0.36 (Cohen's d, p < 0.001) and a marginal cost of about $5 per student. The arXiv abstract still describes approximately 1,000 students in grades 3–9, two 30-minute sessions a week over 8 months and an effect size of 0.37. That does not match the v2 body.", "replication": { "produced_by": [ "A chat tutor that runs on basic phones over low-bandwidth networks", "One scheduled hour a week of independent use during study hall with a provided phone", "A control group kept on the normal timetable in the same school network" ], "must_hold": [ "Phone and WhatsApp access during school time", "Schools accustomed to routine testing (the authors cite this against a Hawthorne effect)", "Replication outside the Rising Academies network, which the authors say is still needed" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0353", "title": "AI-assisted RapiD mapping in HOT's February 2023 Türkiye earthquake activation was up to 12.4% slower and was disabled; OSM data still reached AKUT and AFAD", "summary": "OSM wiki: University of Colorado Boulder/Indiana University research found RapiD AI-assisted contributors up to 12.4% slower; RapiD disabled; OSM data used by AKUT and AFAD. No AI benefit documented.", "date_observed": "2023-02-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "After the M7.8 earthquake in Türkiye on 6 February 2023, the Humanitarian OpenStreetMap Team (HOT) activated, led by the Turkish community Yer Çizenler. It ran Tasking Manager projects for roads and buildings in Türkiye and Syria. The OpenStreetMap (OSM) wiki page for the response is community-authored and was last modified 5 June 2026. It states that, because of the large project areas, AI-assisted mapping with the RapiD editor was originally encouraged. It proved counter-productive and was then disabled. Research from the University of Colorado Boulder and Indiana University, shared with HOT in August 2023, compared 1,650 Tasking Manager contributors before and during it. Contributors using RapiD mapped tasks up to 12.4% slower than those not using AI-assisted mapping. Validators reported many data-quality issues from RapiD contributors, which led to RapiD being disabled on all activation projects. The same page records that OSM data supported rescue coordination by the AKUT Search and Rescue Association and AFAD. It also supported public-health programming in the Kahramanmaraş tent city and the World Bank's GRADE damage report. HOT's own activation and size-up pages (Internet Archive captures of 7 February and 29 May 2023) mention no AI tool and list no partner requests. No cited source documents Microsoft building footprints, HOT's fAIr or Meta maps here, nor any AI role in HOT's 2022 Pakistan floods activation. Cyclone Idai material was not found.", "category": "general benefit", "unexpected": false, "purpose": "AI-assisted mapping was encouraged to speed building and road mapping over large areas for responders. The evidence shows it slowed mapping and lowered quality in this activation. The claimed benefit was not delivered.", "system": "RapiD editor (AI-assisted mapping) used on HOT Tasking Manager projects; the sources do not name its developer", "model_version": null, "developer": null, "deployer": "Humanitarian OpenStreetMap Team with Yer Çizenler (activation lead)", "location": "Türkiye (Kahramanmaraş earthquakes) and northern Syria", "domain": "Humanitarian mapping / disaster response", "segment": "Volunteer humanitarian mapping", "benefit_type": "Reduced Task Time", "taxonomy_note": "The claimed good was faster mapping per contributor; the only independent study found contributors up to 12.4% slower and the tool was disabled.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No AI-attributable outcome: the AI-assisted editor was found slower and was disabled." }, { "group": "organizational", "depth": null, "reason": "No AI-attributable outcome: responders' use of OSM data is documented, but not tied to AI-derived features. The AI tool reduced mapping speed." }, { "group": "societal", "depth": null, "reason": "No AI-attributable outcome documented." } ], "ai_role": { "status": "assessed", "statement": "The AI component (RapiD AI-assisted mapping) is documented by the community-authored OSM wiki as counter-productive. It was up to 12.4% slower at task mapping, with validator-reported quality problems, and was then disabled on all activation projects. Use of OSM data by AKUT, AFAD, a tent-city health team and the World Bank is documented on the same page. It is not tied to AI-derived data. HOT's activation and size-up pages, from the Internet Archive, contain no AI mention. No cited source documents Microsoft building footprints, fAIr or Meta maps in the 2023 Türkiye, 2022 Pakistan or 2019 Idai responses." }, "evidence": [ { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section 'Be wary of AI assisted mapping (RapiD)'. Community wiki page, last modified 5 June 2026.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki)", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "a significant drop in productivity in terms of the speed of tasks mapped for contributors using the RapiD editor — up to 12.4% slower" }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, validator feedback and disabling of RapiD.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), RapiD disabled", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "This validator feedback eventually resulted in the RapiD editor being disabled as an option to contribute to all projects in the activation." }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section on data use.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), data use by responders", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "OSM data used to support rescue coordination in Turkey by AKUT Search and Rescue Association and AFAD" }, { "kind": "press release", "citation": "Humanitarian OpenStreetMap Team (2023). Türkiye Earthquakes, February 2023 Activation. hotosm.org disaster services page, Internet Archive capture of 7 February 2023.", "title": "Türkiye Earthquakes, February 2023 Activation", "url": "https://web.archive.org/web/20230207114951/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-activation/", "date": "2023-02-07", "written_by": "deployer", "quote": "This is in activation led by Yer Çizenler for the earthquake in Central Türkiye and northern Syria." }, { "kind": "report", "citation": "Humanitarian OpenStreetMap Team (2023). Turkey and Syria Earthquake Response February 2023 Size-up. hotosm.org, Internet Archive capture of 29 May 2023.", "title": "Turkey and Syria Earthquake Response February 2023 Size-up", "url": "https://web.archive.org/web/20230529125025/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-size-up/", "date": "2023-05-29", "written_by": "deployer", "quote": "There are no requests from partners currently" } ], "replication": { "produced_by": [ "A HOT activation with large Tasking Manager project areas and Maxar imagery", "RapiD AI-assisted editing offered to volunteer contributors", "Validators reviewing contributions and feeding back on quality", "Independent researchers comparing 1,650 contributors before and during the response" ], "must_hold": [ "Volunteer contributors of mixed experience using AI suggestions without extra validation", "AI-suggested features (for example roads defaulting to “residential”) not corrected before upload", "Validator capacity to detect and report quality problems" ], "echoes": [ { "date": "2022-08-30", "setting": "HOT Pakistan floods monsoon 2022 activation (Asia Pacific Open Mapping Hub): activation page read from the Internet Archive records no AI tool and no outcome", "model_version": null, "outcome": "unknown", "source": "https://web.archive.org/web/20221126224438/https://www.hotosm.org/disaster-services/pakistan-floods-monsoon-season-2022-activation/" } ] }, "paired_incident": null, "headline": "RapiD AI-assisted mapping up to 12.4% slower, then disabled", "metric": "contributors using RapiD mapped tasks up to 12.4% slower", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later operational use or outcome is established.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hotosm.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report, the deployer's press release and the deployer's other. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0353", "catalog_version": "1.0.0", "source_fingerprint": "f70f534fb14bc31b8dcbef858340b77ff2bf40faa397b7bba30c33bf0c7043da", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0353-source-0001", "AIBD-0353-source-0002", "AIBD-0353-source-0003", "AIBD-0353-source-0004", "AIBD-0353-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Humanitarian OpenStreetMap Team with Yer Çizenler (activation lead)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI component (RapiD AI-assisted mapping) is documented by the community-authored OSM wiki as counter-productive. It was up to 12.4% slower at task mapping, with validator-reported quality problems, and was then disabled on all activation projects. Use of OSM data by AKUT, AFAD, a tent-city health team and the World Bank is documented on the same page. It is not tied to AI-derived data. HOT's activation and size-up pages, from the Internet Archive, contain no AI mention. No cited source documents Microsoft building footprints, fAIr or Meta maps in the 2023 Türkiye, 2022 Pakistan or 2019 Idai responses." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The AI component (RapiD AI-assisted mapping) is documented by the community-authored OSM wiki as counter-productive. It was up to 12.4% slower at task mapping, with validator-reported quality problems, and was then disabled on all activation projects. Use of OSM data by AKUT, AFAD, a tent-city health team and the World Bank is documented on the same page. It is not tied to AI-derived data. HOT's activation and size-up pages, from the Internet Archive, contain no AI mention. No cited source documents Microsoft building footprints, fAIr or Meta maps in the 2023 Türkiye, 2022 Pakistan or 2019 Idai responses." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report, the deployer's press release and the deployer's other. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No AI-attributable outcome: the AI-assisted editor was found slower and was disabled." }, { "group": "organizational", "reason": "No AI-attributable outcome: responders' use of OSM data is documented, but not tied to AI-derived features. The AI tool reduced mapping speed." }, { "group": "societal", "reason": "No AI-attributable outcome documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No AI-attributable outcome: the AI-assisted editor was found slower and was disabled." }, { "group": "organizational", "reason": "No AI-attributable outcome: responders' use of OSM data is documented, but not tied to AI-derived features. The AI tool reduced mapping speed." }, { "group": "societal", "reason": "No AI-attributable outcome documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "contributors using RapiD mapped tasks up to 12.4% slower", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later operational use or outcome is established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0353" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Task Time", "taxonomy_note": "The claimed good was faster mapping per contributor; the only independent study found contributors up to 12.4% slower and the tool was disabled." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "After the M7.8 earthquake in Türkiye on 6 February 2023, the Humanitarian OpenStreetMap Team (HOT) activated, led by the Turkish community Yer Çizenler. It ran Tasking Manager projects for roads and buildings in Türkiye and Syria. The OpenStreetMap (OSM) wiki page for the response is community-authored and was last modified 5 June 2026. It states that, because of the large project areas, AI-assisted mapping with the RapiD editor was originally encouraged. It proved counter-productive and was then disabled. Research from the University of Colorado Boulder and Indiana University, shared with HOT in August 2023, compared 1,650 Tasking Manager contributors before and during it. Contributors using RapiD mapped tasks up to 12.4% slower than those not using AI-assisted mapping. Validators reported many data-quality issues from RapiD contributors, which led to RapiD being disabled on all activation projects. The same page records that OSM data supported rescue coordination by the AKUT Search and Rescue Association and AFAD. It also supported public-health programming in the Kahramanmaraş tent city and the World Bank's GRADE damage report. HOT's own activation and size-up pages (Internet Archive captures of 7 February and 29 May 2023) mention no AI tool and list no partner requests. No cited source documents Microsoft building footprints, HOT's fAIr or Meta maps here, nor any AI role in HOT's 2022 Pakistan floods activation. Cyclone Idai material was not found.", "benefit_type": "Reduced Task Time" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No AI-attributable outcome: the AI-assisted editor was found slower and was disabled." }, { "group": "organizational", "reason": "No AI-attributable outcome: responders' use of OSM data is documented, but not tied to AI-derived features. The AI tool reduced mapping speed." }, { "group": "societal", "reason": "No AI-attributable outcome documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "AI-assisted mapping was encouraged to speed building and road mapping over large areas for responders. The evidence shows it slowed mapping and lowered quality in this activation. The claimed benefit was not delivered." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Türkiye (Kahramanmaraş earthquakes) and northern Syria", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "AI-assisted mapping was encouraged to speed building and road mapping over large areas for responders. The evidence shows it slowed mapping and lowered quality in this activation. The claimed benefit was not delivered." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-02-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hotosm.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A HOT activation with large Tasking Manager project areas and Maxar imagery", "RapiD AI-assisted editing offered to volunteer contributors", "Validators reviewing contributions and feeding back on quality", "Independent researchers comparing 1,650 contributors before and during the response" ], "must_hold": [ "Volunteer contributors of mixed experience using AI suggestions without extra validation", "AI-suggested features (for example roads defaulting to “residential”) not corrected before upload", "Validator capacity to detect and report quality problems" ], "echoes": [ { "date": "2022-08-30", "setting": "HOT Pakistan floods monsoon 2022 activation (Asia Pacific Open Mapping Hub): activation page read from the Internet Archive records no AI tool and no outcome", "outcome": "unknown", "source": "https://web.archive.org/web/20221126224438/https://www.hotosm.org/disaster-services/pakistan-floods-monsoon-season-2022-activation/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A HOT activation with large Tasking Manager project areas and Maxar imagery", "RapiD AI-assisted editing offered to volunteer contributors", "Validators reviewing contributions and feeding back on quality", "Independent researchers comparing 1,650 contributors before and during the response" ], "must_hold": [ "Volunteer contributors of mixed experience using AI suggestions without extra validation", "AI-suggested features (for example roads defaulting to “residential”) not corrected before upload", "Validator capacity to detect and report quality problems" ], "echoes": [ { "date": "2022-08-30", "setting": "HOT Pakistan floods monsoon 2022 activation (Asia Pacific Open Mapping Hub): activation page read from the Internet Archive records no AI tool and no outcome", "outcome": "unknown", "source": "https://web.archive.org/web/20221126224438/https://www.hotosm.org/disaster-services/pakistan-floods-monsoon-season-2022-activation/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hotosm.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Humanitarian mapping / disaster response", "segment": "Volunteer humanitarian mapping" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section 'Be wary of AI assisted mapping (RapiD)'. Community wiki page, last modified 5 June 2026.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki)", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "a significant drop in productivity in terms of the speed of tasks mapped for contributors using the RapiD editor — up to 12.4% slower" }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, validator feedback and disabling of RapiD.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), RapiD disabled", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "This validator feedback eventually resulted in the RapiD editor being disabled as an option to contribute to all projects in the activation." }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section on data use.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), data use by responders", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "OSM data used to support rescue coordination in Turkey by AKUT Search and Rescue Association and AFAD" }, { "kind": "press release", "citation": "Humanitarian OpenStreetMap Team (2023). Türkiye Earthquakes, February 2023 Activation. hotosm.org disaster services page, Internet Archive capture of 7 February 2023.", "title": "Türkiye Earthquakes, February 2023 Activation", "url": "https://web.archive.org/web/20230207114951/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-activation/", "date": "2023-02-07", "written_by": "deployer", "quote": "This is in activation led by Yer Çizenler for the earthquake in Central Türkiye and northern Syria." }, { "kind": "report", "citation": "Humanitarian OpenStreetMap Team (2023). Turkey and Syria Earthquake Response February 2023 Size-up. hotosm.org, Internet Archive capture of 29 May 2023.", "title": "Turkey and Syria Earthquake Response February 2023 Size-up", "url": "https://web.archive.org/web/20230529125025/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-size-up/", "date": "2023-05-29", "written_by": "deployer", "quote": "There are no requests from partners currently" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0353-source-0001", "AIBD-0353-source-0002", "AIBD-0353-source-0003", "AIBD-0353-source-0004", "AIBD-0353-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section 'Be wary of AI assisted mapping (RapiD)'. Community wiki page, last modified 5 June 2026.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki)", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "a significant drop in productivity in terms of the speed of tasks mapped for contributors using the RapiD editor — up to 12.4% slower" }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, validator feedback and disabling of RapiD.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), RapiD disabled", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "This validator feedback eventually resulted in the RapiD editor being disabled as an option to contribute to all projects in the activation." }, { "kind": "other", "citation": "OpenStreetMap wiki (2023-2026). 2023 Turkey Earthquakes, section on data use.", "title": "2023 Turkey Earthquakes (OpenStreetMap wiki), data use by responders", "url": "https://wiki.openstreetmap.org/wiki/2023_Turkey_Earthquakes", "date": "2026-06-05", "written_by": "deployer", "quote": "OSM data used to support rescue coordination in Turkey by AKUT Search and Rescue Association and AFAD" }, { "kind": "press release", "citation": "Humanitarian OpenStreetMap Team (2023). Türkiye Earthquakes, February 2023 Activation. hotosm.org disaster services page, Internet Archive capture of 7 February 2023.", "title": "Türkiye Earthquakes, February 2023 Activation", "url": "https://web.archive.org/web/20230207114951/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-activation/", "date": "2023-02-07", "written_by": "deployer", "quote": "This is in activation led by Yer Çizenler for the earthquake in Central Türkiye and northern Syria." }, { "kind": "report", "citation": "Humanitarian OpenStreetMap Team (2023). Turkey and Syria Earthquake Response February 2023 Size-up. hotosm.org, Internet Archive capture of 29 May 2023.", "title": "Turkey and Syria Earthquake Response February 2023 Size-up", "url": "https://web.archive.org/web/20230529125025/https://www.hotosm.org/disaster-services/turkiye-earthquakes-february-2023-size-up/", "date": "2023-05-29", "written_by": "deployer", "quote": "There are no requests from partners currently" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "OSM wiki: University of Colorado Boulder/Indiana University research found RapiD AI-assisted contributors up to 12.4% slower; RapiD disabled; OSM data used by AKUT and AFAD. No AI benefit documented.", "account": "After the M7.8 earthquake in Türkiye on 6 February 2023, the Humanitarian OpenStreetMap Team (HOT) activated, led by the Turkish community Yer Çizenler. It ran Tasking Manager projects for roads and buildings in Türkiye and Syria. The OpenStreetMap (OSM) wiki page for the response is community-authored and was last modified 5 June 2026. It states that, because of the large project areas, AI-assisted mapping with the RapiD editor was originally encouraged. It proved counter-productive and was then disabled. Research from the University of Colorado Boulder and Indiana University, shared with HOT in August 2023, compared 1,650 Tasking Manager contributors before and during it. Contributors using RapiD mapped tasks up to 12.4% slower than those not using AI-assisted mapping. Validators reported many data-quality issues from RapiD contributors, which led to RapiD being disabled on all activation projects. The same page records that OSM data supported rescue coordination by the AKUT Search and Rescue Association and AFAD. It also supported public-health programming in the Kahramanmaraş tent city and the World Bank's GRADE damage report. HOT's own activation and size-up pages (Internet Archive captures of 7 February and 29 May 2023) mention no AI tool and list no partner requests. No cited source documents Microsoft building footprints, HOT's fAIr or Meta maps here, nor any AI role in HOT's 2022 Pakistan floods activation. Cyclone Idai material was not found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "RapiD editor (AI-assisted mapping) used on HOT Tasking Manager projects; the sources do not name its developer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-assisted RapiD mapping in HOT's February 2023 Türkiye earthquake activation was up to 12.4% slower and was disabled; OSM data still reached AKUT and AFAD", "headline": "RapiD AI-assisted mapping up to 12.4% slower, then disabled" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f70f534fb14bc31b8dcbef858340b77ff2bf40faa397b7bba30c33bf0c7043da" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "After the M7.8 earthquake in Türkiye on 6 February 2023, the Humanitarian OpenStreetMap Team (HOT) activated, led by the Turkish community Yer Çizenler. It ran Tasking Manager projects for roads and buildings in Türkiye and Syria. The OpenStreetMap (OSM) wiki page for the response is community-authored and was last modified 5 June 2026. It states that, because of the large project areas, AI-assisted mapping with the RapiD editor was originally encouraged. It proved counter-productive and was then disabled. Research from the University of Colorado Boulder and Indiana University, shared with HOT in August 2023, compared 1,650 Tasking Manager contributors before and during it. Contributors using RapiD mapped tasks up to 12.4% slower than those not using AI-assisted mapping. Validators reported many data-quality issues from RapiD contributors, which led to RapiD being disabled on all activation projects. The same page records that OSM data supported rescue coordination by the AKUT Search and Rescue Association and AFAD. It also supported public-health programming in the Kahramanmaraş tent city and the World Bank's GRADE damage report. HOT's own activation and size-up pages (Internet Archive captures of 7 February and 29 May 2023) mention no AI tool and list no partner requests. No cited source documents Microsoft building footprints, HOT's fAIr or Meta maps here, nor any AI role in HOT's 2022 Pakistan floods activation. Cyclone Idai material was not found.", "replication": { "produced_by": [ "A HOT activation with large Tasking Manager project areas and Maxar imagery", "RapiD AI-assisted editing offered to volunteer contributors", "Validators reviewing contributions and feeding back on quality", "Independent researchers comparing 1,650 contributors before and during the response" ], "must_hold": [ "Volunteer contributors of mixed experience using AI suggestions without extra validation", "AI-suggested features (for example roads defaulting to “residential”) not corrected before upload", "Validator capacity to detect and report quality problems" ], "echoes": [ { "date": "2022-08-30", "setting": "HOT Pakistan floods monsoon 2022 activation (Asia Pacific Open Mapping Hub): activation page read from the Internet Archive records no AI tool and no outcome", "outcome": "unknown", "source": "https://web.archive.org/web/20221126224438/https://www.hotosm.org/disaster-services/pakistan-floods-monsoon-season-2022-activation/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0243", "title": "Camera-based AI feedback on 100 Spin e-scooters in Santa Monica cuts time ridden on sidewalks by 22% in a randomized field test", "summary": "University of Washington study in Findings (20 Nov 2024): feedback disabled at random on 50 of 100 camera-equipped Spin scooters from 23 Nov 2022 to 14 Feb 2023; feedback-equipped scooters spent 22...", "date_observed": "2023-02-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mohammad Mehdi Oshanreh, Daniel Malarkey and Don MacKenzie partnered with the operator Spin. They fitted 100 shared e-scooters in Santa Monica, California with a camera-based computer-vision system. It classifies the riding surface (sidewalk, roadway or bike lane) without the Global Positioning System (GPS). On detecting sidewalk riding, it issues in-app notifications, audible beeps and a speed reduction. From 23 Nov 2022, 50 of the 100 scooters were randomly selected to have the feedback disabled, with riders unaware of assignment. Data were collected until 14 Feb 2023. The paper's abstract cites 488 trips and its methods section 456 trips for analysis (289 with feedback, 167 without). The feedback group spent 22% less time and 20% less distance on sidewalks and 5% more time on streets. Kolmogorov-Smirnov tests and a logistic regression found feedback reduced street-to-sidewalk transitions but not bike-lane-to-sidewalk transitions. About 10% of trips in both groups spent over 60% of their time on sidewalks. Targeted theft of camera-equipped scooters led Spin to withdraw them, limiting the sample. The paper does not name the camera system's maker. Funding came from the U.S. Department of Transportation via the C2SMART Center.", "category": "general benefit", "unexpected": false, "purpose": "The camera system was built to detect sidewalk riding in real time and discourage it through alerts and speed limits.", "system": "Camera-based computer-vision riding-surface detection with in-app notifications, audible beeps and speed reduction on Spin shared e-scooters (maker not named in the paper)", "model_version": null, "developer": "Not named in the paper", "deployer": "Spin (shared e-scooter operator), with University of Washington researchers", "location": "Santa Monica, United States", "domain": "Micromobility safety", "segment": "Shared e-scooters / pedestrian conflict", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Behavioral proxy (sidewalk time) measured across a cohort. No crash or injury outcome." }, { "group": "organizational", "depth": null, "reason": "No outcome for Spin or the city is documented beyond compliance behavior." }, { "group": "personal", "depth": null, "reason": "No identifiable individual outcome." } ], "ai_role": { "status": "assessed", "statement": "The computer-vision classifier produced the surface detections that triggered feedback. The randomized disabling of feedback isolates the feedback effect but not detection accuracy, which the paper does not report. Independent university authors with operator cooperation. The vendor is unnamed." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Oshanreh MM, Malarkey D, MacKenzie D (2024). AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters. Findings (Transport Findings), 20 Nov 2024. doi:10.32866/001c.125892.", "title": "AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters", "url": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "date": "2024-11-20", "written_by": "deployer", "quote": "Data from 488 trips revealed that feedback-equipped scooters spent 22% less time and 20% less distance on sidewalks." } ], "replication": { "produced_by": [ "Camera-based surface classification that does not depend on GPS", "Randomized disabling of feedback on half the equipped fleet with riders unaware of assignment", "A dense urban grid with sidewalks, streets and bike lanes where sidewalk riding is unlawful" ], "must_hold": [ "Equipped scooters remain in service (theft removed them here)", "Riders cannot tell which scooters give feedback", "Enough trips per arm for distributional tests" ], "echoes": [ { "date": "2026-03-20", "setting": "Lime's in-house “Lime Vision” camera AI with audible sidewalk alerts rolling out to 3,500 Seattle scooters by 1 June 2026; no outcome data reported", "model_version": null, "outcome": "unknown", "source": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/" } ] }, "paired_incident": null, "headline": "Camera AI on Spin e-scooters cuts time ridden on sidewalks 22%", "metric": "The feedback group spent 22% less time and 20% less distance on sidewalks", "comparator": { "against": "the no-feedback group (50 scooters with feedback mechanisms disabled at random)", "before": "0.22 (mean fraction of trip time on sidewalks, no-feedback group, Table 1)", "after": "0.17 (mean fraction of trip time on sidewalks, feedback group, Table 1)", "basis": "measured", "quote": "Data from 488 trips revealed that feedback-equipped scooters spent 22% less time and 20% less distance on sidewalks.", "url": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters" }, "later": { "status": "unknown", "date": null, "note": "The paper reports that targeted theft of camera-equipped scooters led Spin to withdraw all of them from operation, but it does not date the withdrawal, so it cannot be placed after the end of data collection.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Spin_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0243", "catalog_version": "1.0.0", "source_fingerprint": "3bf48e9de290f327daf40df81d6b733dc2f6824f917a2a5c3f15a678185635b7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0243-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not named in the paper", "deployer": "Spin (shared e-scooter operator), with University of Washington researchers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The computer-vision classifier produced the surface detections that triggered feedback. The randomized disabling of feedback isolates the feedback effect but not detection accuracy, which the paper does not report. Independent university authors with operator cooperation. The vendor is unnamed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The computer-vision classifier produced the surface detections that triggered feedback. The randomized disabling of feedback isolates the feedback effect but not detection accuracy, which the paper does not report. Independent university authors with operator cooperation. The vendor is unnamed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Behavioral proxy (sidewalk time) measured across a cohort. No crash or injury outcome." }, { "group": "organizational", "reason": "No outcome for Spin or the city is documented beyond compliance behavior." }, { "group": "personal", "reason": "No identifiable individual outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Behavioral proxy (sidewalk time) measured across a cohort. No crash or injury outcome." }, { "group": "organizational", "reason": "No outcome for Spin or the city is documented beyond compliance behavior." }, { "group": "personal", "reason": "No identifiable individual outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The feedback group spent 22% less time and 20% less distance on sidewalks", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The paper reports that targeted theft of camera-equipped scooters led Spin to withdraw all of them from operation, but it does not date the withdrawal, so it cannot be placed after the end of data collection." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0243" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mohammad Mehdi Oshanreh, Daniel Malarkey and Don MacKenzie partnered with the operator Spin. They fitted 100 shared e-scooters in Santa Monica, California with a camera-based computer-vision system. It classifies the riding surface (sidewalk, roadway or bike lane) without the Global Positioning System (GPS). On detecting sidewalk riding, it issues in-app notifications, audible beeps and a speed reduction. From 23 Nov 2022, 50 of the 100 scooters were randomly selected to have the feedback disabled, with riders unaware of assignment. Data were collected until 14 Feb 2023. The paper's abstract cites 488 trips and its methods section 456 trips for analysis (289 with feedback, 167 without). The feedback group spent 22% less time and 20% less distance on sidewalks and 5% more time on streets. Kolmogorov-Smirnov tests and a logistic regression found feedback reduced street-to-sidewalk transitions but not bike-lane-to-sidewalk transitions. About 10% of trips in both groups spent over 60% of their time on sidewalks. Targeted theft of camera-equipped scooters led Spin to withdraw them, limiting the sample. The paper does not name the camera system's maker. Funding came from the U.S. Department of Transportation via the C2SMART Center.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Behavioral proxy (sidewalk time) measured across a cohort. No crash or injury outcome." }, { "group": "organizational", "reason": "No outcome for Spin or the city is documented beyond compliance behavior." }, { "group": "personal", "reason": "No identifiable individual outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The camera system was built to detect sidewalk riding in real time and discourage it through alerts and speed limits." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Santa Monica, United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The camera system was built to detect sidewalk riding in real time and discourage it through alerts and speed limits." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-02-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Spin_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-based surface classification that does not depend on GPS", "Randomized disabling of feedback on half the equipped fleet with riders unaware of assignment", "A dense urban grid with sidewalks, streets and bike lanes where sidewalk riding is unlawful" ], "must_hold": [ "Equipped scooters remain in service (theft removed them here)", "Riders cannot tell which scooters give feedback", "Enough trips per arm for distributional tests" ], "echoes": [ { "date": "2026-03-20", "setting": "Lime's in-house “Lime Vision” camera AI with audible sidewalk alerts rolling out to 3,500 Seattle scooters by 1 June 2026; no outcome data reported", "outcome": "unknown", "source": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-based surface classification that does not depend on GPS", "Randomized disabling of feedback on half the equipped fleet with riders unaware of assignment", "A dense urban grid with sidewalks, streets and bike lanes where sidewalk riding is unlawful" ], "must_hold": [ "Equipped scooters remain in service (theft removed them here)", "Riders cannot tell which scooters give feedback", "Enough trips per arm for distributional tests" ], "echoes": [ { "date": "2026-03-20", "setting": "Lime's in-house “Lime Vision” camera AI with audible sidewalk alerts rolling out to 3,500 Seattle scooters by 1 June 2026; no outcome data reported", "outcome": "unknown", "source": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Spin_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Micromobility safety", "segment": "Shared e-scooters / pedestrian conflict" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Oshanreh MM, Malarkey D, MacKenzie D (2024). AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters. Findings (Transport Findings), 20 Nov 2024. doi:10.32866/001c.125892.", "title": "AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters", "url": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "date": "2024-11-20", "written_by": "deployer", "quote": "Data from 488 trips revealed that feedback-equipped scooters spent 22% less time and 20% less distance on sidewalks." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0243-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Oshanreh MM, Malarkey D, MacKenzie D (2024). AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters. Findings (Transport Findings), 20 Nov 2024. doi:10.32866/001c.125892.", "title": "AI-Driven Feedback Systems Reduce Sidewalk Riding on Shared E-Scooters", "url": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters", "date": "2024-11-20", "written_by": "deployer", "quote": "Data from 488 trips revealed that feedback-equipped scooters spent 22% less time and 20% less distance on sidewalks." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "University of Washington study in Findings (20 Nov 2024): feedback disabled at random on 50 of 100 camera-equipped Spin scooters from 23 Nov 2022 to 14 Feb 2023; feedback-equipped scooters spent 22...", "account": "Mohammad Mehdi Oshanreh, Daniel Malarkey and Don MacKenzie partnered with the operator Spin. They fitted 100 shared e-scooters in Santa Monica, California with a camera-based computer-vision system. It classifies the riding surface (sidewalk, roadway or bike lane) without the Global Positioning System (GPS). On detecting sidewalk riding, it issues in-app notifications, audible beeps and a speed reduction. From 23 Nov 2022, 50 of the 100 scooters were randomly selected to have the feedback disabled, with riders unaware of assignment. Data were collected until 14 Feb 2023. The paper's abstract cites 488 trips and its methods section 456 trips for analysis (289 with feedback, 167 without). The feedback group spent 22% less time and 20% less distance on sidewalks and 5% more time on streets. Kolmogorov-Smirnov tests and a logistic regression found feedback reduced street-to-sidewalk transitions but not bike-lane-to-sidewalk transitions. About 10% of trips in both groups spent over 60% of their time on sidewalks. Targeted theft of camera-equipped scooters led Spin to withdraw them, limiting the sample. The paper does not name the camera system's maker. Funding came from the U.S. Department of Transportation via the C2SMART Center." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Camera-based computer-vision riding-surface detection with in-app notifications, audible beeps and speed reduction on Spin shared e-scooters (maker not named in the paper)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the paper" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Camera-based AI feedback on 100 Spin e-scooters in Santa Monica cuts time ridden on sidewalks by 22% in a randomized field test", "headline": "Camera AI on Spin e-scooters cuts time ridden on sidewalks 22%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3bf48e9de290f327daf40df81d6b733dc2f6824f917a2a5c3f15a678185635b7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mohammad Mehdi Oshanreh, Daniel Malarkey and Don MacKenzie partnered with the operator Spin. They fitted 100 shared e-scooters in Santa Monica, California with a camera-based computer-vision system. It classifies the riding surface (sidewalk, roadway or bike lane) without the Global Positioning System (GPS). On detecting sidewalk riding, it issues in-app notifications, audible beeps and a speed reduction. From 23 Nov 2022, 50 of the 100 scooters were randomly selected to have the feedback disabled, with riders unaware of assignment. Data were collected until 14 Feb 2023. The paper's abstract cites 488 trips and its methods section 456 trips for analysis (289 with feedback, 167 without). The feedback group spent 22% less time and 20% less distance on sidewalks and 5% more time on streets. Kolmogorov-Smirnov tests and a logistic regression found feedback reduced street-to-sidewalk transitions but not bike-lane-to-sidewalk transitions. About 10% of trips in both groups spent over 60% of their time on sidewalks. Targeted theft of camera-equipped scooters led Spin to withdraw them, limiting the sample. The paper does not name the camera system's maker. Funding came from the U.S. Department of Transportation via the C2SMART Center.", "replication": { "produced_by": [ "Camera-based surface classification that does not depend on GPS", "Randomized disabling of feedback on half the equipped fleet with riders unaware of assignment", "A dense urban grid with sidewalks, streets and bike lanes where sidewalk riding is unlawful" ], "must_hold": [ "Equipped scooters remain in service (theft removed them here)", "Riders cannot tell which scooters give feedback", "Enough trips per arm for distributional tests" ], "echoes": [ { "date": "2026-03-20", "setting": "Lime's in-house “Lime Vision” camera AI with audible sidewalk alerts rolling out to 3,500 Seattle scooters by 1 June 2026; no outcome data reported", "outcome": "unknown", "source": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0346", "title": "xView2 machine-learning damage maps may have been used by UN INSARAG teams in Adıyaman and by AFAD, the World Bank, IFRC and WFP after the 6 February 2023 Türkiye earthquakes", "summary": "MIT Technology Review (20 February 2023), quoting DIU: xView2 used by two UN INSARAG teams in Adıyaman and by AFAD, World Bank, IFRC and WFP; Microsoft reports 3,849 damaged buildings mapped for AFAD.", "date_observed": "2023-02-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "MIT Technology Review reported on 20 February 2023 on xView2, an open-source building-damage assessment project. It was sponsored and developed in 2019 by the Pentagon's Defense Innovation Unit (DIU) and Carnegie Mellon University's Software Engineering Institute. Partners included Microsoft and UC Berkeley. It uses machine-learning (semantic segmentation) on satellite imagery to identify and grade building damage. Ritwik Gupta, DIU's principal AI scientist, told the magazine about use in Türkiye. At least two ground teams of search and rescue personnel from the UN's International Search and Rescue Advisory Group (INSARAG) had used xView2 in Adıyaman. He said it helped workers find damaged areas they were unaware of. He said AFAD, the World Bank, the IFRC and WFP had all used the platform. Atishay Abbhi, a World Bank disaster risk management specialist, said the same degree of assessment would typically take weeks and now takes hours or minutes. The article notes that the first usable satellite images came on 9 February 2023, three days after the first quake. It says the model is up to 85 or 90% accurate. Microsoft's February 2023 “Turkey Earthquake Report” has authors including Gupta and Microsoft AI for Good staff. It states that the team partnered with AFAD to deliver building-level damage estimates over four cities in southeast Türkiye. The imagery was from the first three days. It estimated 3,849 buildings damaged or destroyed, with Marash the most affected at 7.44% of buildings. The World Bank GRADE report does not mention xView2, AI or Microsoft. DLR's peer-reviewed account states its own AI damage products were not part of the viewer delivered to responders. Direct Relief's December 2025 article describes a research study on Microsoft and Google models rather than a response decision. No responder statement describing a decision taken on xView2 output is among the sources.", "category": "protective response", "unexpected": false, "purpose": "Rapid building-damage assessment from pre- and post-event satellite imagery for humanitarian assistance and disaster response. This use was that purpose.", "system": "xView2 building damage assessment models (semantic segmentation on satellite imagery, trained on the xBD dataset)", "model_version": null, "developer": "US Defense Innovation Unit (DIU) with Carnegie Mellon University Software Engineering Institute; research partners Microsoft AI for Good and UC Berkeley", "deployer": "UN INSARAG (search and rescue ground teams in Adıyaman); AFAD, World Bank, IFRC and WFP (per the developer's account); Microsoft AI for Good delivered estimates to AFAD (per Microsoft)", "location": "Adıyaman and four cities in southeast Türkiye including Kahramanmaraş (Marash)", "domain": "Disaster response / post-earthquake damage assessment", "segment": "Humanitarian and civil-protection organizations", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The responder-use claim rests on the developer's account relayed by one news item and Microsoft's own report.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual rescue or beneficiary is attributed to the maps in any cited source." }, { "group": "organizational", "depth": 2, "reason": "Responders are reported to have received building-level damage maps in hours instead of weeks and to have found damaged areas they were unaware of. The reports come from the developer and a World Bank specialist, not the responding agencies." }, { "group": "societal", "depth": 1, "reason": "No downstream effect on rescues, shelter siting or reconstruction is documented. The maps covered part of the affected zone after imagery became usable on 9 February." } ], "ai_role": { "status": "assessed", "statement": "The AI produced the damage classifications that responders are said to have used. Which decisions changed is not documented. Sources: the developer (DIU's Gupta) and the World Bank specialist, quoted in one news report, and Microsoft's own report of delivering estimates to AFAD. World Bank's GRADE report and DLR's account do not corroborate operational use of AI products." }, "evidence": [ { "kind": "news report", "citation": "Ryan-Mosley, T. (2023). How AI can actually be helpful in disaster response. MIT Technology Review, 20 Feb 2023.", "title": "How AI can actually be helpful in disaster response", "url": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/", "date": "2023-02-20", "written_by": "independent", "quote": "xView2 has been used by at least two different ground teams of search and rescue personnel from the UN’s International Search and Rescue Advisory Group in Adiyaman" }, { "kind": "news report", "citation": "Ryan-Mosley, T. (2023). Same article, organisations named by DIU's Ritwik Gupta.", "title": "How AI can actually be helpful in disaster response (organisations)", "url": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/", "date": "2023-02-20", "written_by": "independent", "quote": "noting Turkey’s Disaster and Emergency Management Presidency, the World Bank, the International Federation of the Red Cross, and the United Nations World Food Programme have all used the platform" }, { "kind": "news report", "citation": "Ryan-Mosley, T. (2023). Same article, World Bank specialist on assessment speed.", "title": "How AI can actually be helpful in disaster response (World Bank)", "url": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/", "date": "2023-02-20", "written_by": "independent", "quote": "Atishay Abbhi, a disaster risk management specialist at the World Bank, tells me that this same degree of assessment would typically take weeks and now takes hours or minutes." }, { "kind": "news report", "citation": "Ryan-Mosley, T. (2023). Same article, method description.", "title": "How AI can actually be helpful in disaster response (method)", "url": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/", "date": "2023-02-20", "written_by": "independent", "quote": "It uses machine-learning algorithms in conjunction with satellite imagery from other providers to identify building and infrastructure damage in the disaster area and categorize its severity" }, { "kind": "report", "citation": "Robinson, C., Gupta, R., Fobi Nsutezo, S., Pound, E., Ortiz, A., Rosa, M., White, K., Dodhia, R., Zolli, A., Birge, C., Lavista Ferres, J. M. (2023). Turkey Earthquake Report. Microsoft AI for Good Research Lab, February 2023.", "title": "Turkey Earthquake Report", "url": "https://www.microsoft.com/en-us/research/publication/turkey-earthquake-report/", "date": null, "written_by": "makers", "quote": "partnered with Turkey's Ministry of Interior Disaster and Emergency Management Presidency (AFAD) to deliver building level damage estimates over four cities in southeast Turkey" }, { "kind": "report", "citation": "Robinson, C. et al. (2023). Same report, results.", "title": "Turkey Earthquake Report (results)", "url": "https://www.microsoft.com/en-us/research/publication/turkey-earthquake-report/", "date": null, "written_by": "makers", "quote": "3,849 buildings were damaged/destroyed across the four cities" }, { "kind": "preprint", "citation": "Gupta, R., Hosfelt, R., Sajeev, S., Patel, N., Goodman, B., Doshi, J., Heim, E., Choset, H., Gaston, M. (2019). xBD: A Dataset for Assessing Building Damage from Satellite Imagery. arXiv:1911.09296.", "title": "xBD: A Dataset for Assessing Building Damage from Satellite Imagery", "url": "https://arxiv.org/abs/1911.09296", "date": "2019-11-21", "written_by": "makers", "quote": "Massive potential exists for using aerial imagery combined with computer vision algorithms to assess damage and reduce the potential danger to human life." }, { "kind": "news report", "citation": "Direct Relief (2025). After Disaster, AI Models Support Rapid Understanding of Health Facility Damage. 10 Dec 2025 (describes a Direct Relief/Stanford research study in PLOS Digital Health; does not mention xView2).", "title": "After Disaster, AI Models Support Rapid Understanding of Health Facility Damage", "url": "https://www.directrelief.org/2025/12/after-disaster-ai-models-support-rapid-understanding-of-health-facility-damage/", "date": "2025-12-10", "written_by": "independent", "quote": "Two of the most prominent models in use during the 2023 earthquake response came from Microsoft AI for Good and from Google." } ], "replication": { "produced_by": [ "Usable high-resolution post-event satellite imagery (first available 9 February 2023, three days after the quake)", "A pre-trained open-source damage model (xBD/xView2) run by the developers on request of responding organizations", "Direct contact between DIU/Microsoft researchers and responders (UN INSARAG teams, AFAD)" ], "must_hold": [ "Cloud-free daytime imagery with a satellite overhead. The article notes far fewer images in remote or less developed areas such as Syria", "Responder trust in an off-site AI product, which the developer describes as hard to obtain", "Documentation by the responding agency of what the maps changed, which no cited source provides" ], "echoes": [ { "date": null, "setting": "Earlier deployments by the California National Guard and the Australian Geospatial-Intelligence Organization for wildfires and after flooding in Nepal, per the same MIT Technology Review article; no outcomes documented", "model_version": null, "outcome": "unknown", "source": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/" }, { "date": "2025-12-10", "setting": "Research study by Direct Relief and Stanford assessing health-facility damage with Microsoft AI for Good and Google models for the 2023 earthquakes (not an operational use)", "model_version": null, "outcome": "unknown", "source": "https://www.directrelief.org/2025/12/after-disaster-ai-models-support-rapid-understanding-of-health-facility-damage/" } ] }, "paired_incident": null, "headline": "UN INSARAG teams in Adıyaman may have used xView2 damage maps", "metric": "estimating 3,849 buildings damaged or destroyed", "comparator": { "against": "conventional damage assessment", "before": "weeks", "after": "hours or minutes", "basis": "assumed", "quote": "this same degree of assessment would typically take weeks and now takes hours or minutes", "url": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/" }, "later": { "status": "unknown", "date": null, "note": "Direct Relief's 10 December 2025 article describes a retrospective research study of the Microsoft and Google 2023 models that found they disagreed in significant ways; no later operational use of xView2 was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Switzerland", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Defense_Innovation_Unit; https://en.wikipedia.org/wiki/International_Search_and_Rescue_Advisory_Group", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UN INSARAG.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' report and the makers' preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0346", "catalog_version": "1.0.0", "source_fingerprint": "0552f28b520cecd7eb1ac0a7189af9fb84ad3f2ef360d27b88bb995479c5f0d7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0346-source-0001", "AIBD-0346-source-0002", "AIBD-0346-source-0003", "AIBD-0346-source-0004", "AIBD-0346-source-0005", "AIBD-0346-source-0006", "AIBD-0346-source-0007", "AIBD-0346-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "US Defense Innovation Unit (DIU) with Carnegie Mellon University Software Engineering Institute; research partners Microsoft AI for Good and UC Berkeley", "deployer": "UN INSARAG (search and rescue ground teams in Adıyaman); AFAD, World Bank, IFRC and WFP (per the developer's account); Microsoft AI for Good delivered estimates to AFAD (per Microsoft)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI produced the damage classifications that responders are said to have used. 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It was sponsored and developed in 2019 by the Pentagon's Defense Innovation Unit (DIU) and Carnegie Mellon University's Software Engineering Institute. Partners included Microsoft and UC Berkeley. It uses machine-learning (semantic segmentation) on satellite imagery to identify and grade building damage. Ritwik Gupta, DIU's principal AI scientist, told the magazine about use in Türkiye. At least two ground teams of search and rescue personnel from the UN's International Search and Rescue Advisory Group (INSARAG) had used xView2 in Adıyaman. He said it helped workers find damaged areas they were unaware of. He said AFAD, the World Bank, the IFRC and WFP had all used the platform. Atishay Abbhi, a World Bank disaster risk management specialist, said the same degree of assessment would typically take weeks and now takes hours or minutes. The article notes that the first usable satellite images came on 9 February 2023, three days after the first quake. It says the model is up to 85 or 90% accurate. Microsoft's February 2023 “Turkey Earthquake Report” has authors including Gupta and Microsoft AI for Good staff. It states that the team partnered with AFAD to deliver building-level damage estimates over four cities in southeast Türkiye. The imagery was from the first three days. It estimated 3,849 buildings damaged or destroyed, with Marash the most affected at 7.44% of buildings. The World Bank GRADE report does not mention xView2, AI or Microsoft. DLR's peer-reviewed account states its own AI damage products were not part of the viewer delivered to responders. Direct Relief's December 2025 article describes a research study on Microsoft and Google models rather than a response decision. No responder statement describing a decision taken on xView2 output is among the sources.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual rescue or beneficiary is attributed to the maps in any cited source." }, { "group": "organizational", "depth": 2, "reason": "Responders are reported to have received building-level damage maps in hours instead of weeks and to have found damaged areas they were unaware of. The reports come from the developer and a World Bank specialist, not the responding agencies." }, { "group": "societal", "depth": 1, "reason": "No downstream effect on rescues, shelter siting or reconstruction is documented. 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It says the model is up to 85 or 90% accurate. Microsoft's February 2023 “Turkey Earthquake Report” has authors including Gupta and Microsoft AI for Good staff. It states that the team partnered with AFAD to deliver building-level damage estimates over four cities in southeast Türkiye. The imagery was from the first three days. It estimated 3,849 buildings damaged or destroyed, with Marash the most affected at 7.44% of buildings. The World Bank GRADE report does not mention xView2, AI or Microsoft. DLR's peer-reviewed account states its own AI damage products were not part of the viewer delivered to responders. Direct Relief's December 2025 article describes a research study on Microsoft and Google models rather than a response decision. 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It was sponsored and developed in 2019 by the Pentagon's Defense Innovation Unit (DIU) and Carnegie Mellon University's Software Engineering Institute. Partners included Microsoft and UC Berkeley. It uses machine-learning (semantic segmentation) on satellite imagery to identify and grade building damage. Ritwik Gupta, DIU's principal AI scientist, told the magazine about use in Türkiye. At least two ground teams of search and rescue personnel from the UN's International Search and Rescue Advisory Group (INSARAG) had used xView2 in Adıyaman. He said it helped workers find damaged areas they were unaware of. He said AFAD, the World Bank, the IFRC and WFP had all used the platform. Atishay Abbhi, a World Bank disaster risk management specialist, said the same degree of assessment would typically take weeks and now takes hours or minutes. The article notes that the first usable satellite images came on 9 February 2023, three days after the first quake. It says the model is up to 85 or 90% accurate. Microsoft's February 2023 “Turkey Earthquake Report” has authors including Gupta and Microsoft AI for Good staff. It states that the team partnered with AFAD to deliver building-level damage estimates over four cities in southeast Türkiye. The imagery was from the first three days. It estimated 3,849 buildings damaged or destroyed, with Marash the most affected at 7.44% of buildings. The World Bank GRADE report does not mention xView2, AI or Microsoft. DLR's peer-reviewed account states its own AI damage products were not part of the viewer delivered to responders. Direct Relief's December 2025 article describes a research study on Microsoft and Google models rather than a response decision. No responder statement describing a decision taken on xView2 output is among the sources.", "replication": { "produced_by": [ "Usable high-resolution post-event satellite imagery (first available 9 February 2023, three days after the quake)", "A pre-trained open-source damage model (xBD/xView2) run by the developers on request of responding organizations", "Direct contact between DIU/Microsoft researchers and responders (UN INSARAG teams, AFAD)" ], "must_hold": [ "Cloud-free daytime imagery with a satellite overhead. The article notes far fewer images in remote or less developed areas such as Syria", "Responder trust in an off-site AI product, which the developer describes as hard to obtain", "Documentation by the responding agency of what the maps changed, which no cited source provides" ], "echoes": [ { "setting": "Earlier deployments by the California National Guard and the Australian Geospatial-Intelligence Organization for wildfires and after flooding in Nepal, per the same MIT Technology Review article; no outcomes documented", "outcome": "unknown", "source": "https://www.technologyreview.com/2023/02/20/1068824/ai-actually-helpful-disaster-response-turkey-syria-earthquake/" }, { "date": "2025-12-10", "setting": "Research study by Direct Relief and Stanford assessing health-facility damage with Microsoft AI for Good and Google models for the 2023 earthquakes (not an operational use)", "outcome": "unknown", "source": "https://www.directrelief.org/2025/12/after-disaster-ai-models-support-rapid-understanding-of-health-facility-damage/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0218", "title": "Supreme Court of India starts AI live transcription of Constitution Bench hearings with TERES; lawyer-verified transcripts published on the court's website", "summary": "From 21 Feb 2023 the Supreme Court of India transcribed Constitution Bench hearings live with an AI service from TERES; 9 of 25 hearings had published transcripts by May 2023, and almost 10 matters...", "date_observed": "2023-02-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 21 February 2023 Chief Justice D.Y. Chandrachud's Constitution Bench heard the Maharashtra political crisis matter in Court Room 1. It used AI live transcription supplied by TERES, with screens facing the lawyers showing the text. The Chief Justice called it an experiment. He said transcripts would go to lawyers for verification and then onto the Supreme Court website (LiveLaw, 21 February 2023). The Supreme Court Observer reported on 18 May 2023 that 25 Constitution Bench hearings had been held across four cases. Only nine transcripts had been published: six for the marriage-equality case, three for the Maharashtra case, none for the other two. None was published in March 2023. NDTV reported on 8 December 2023 a written reply in the Lok Sabha by Law Minister Arjun Ram Meghwal. He said AI transcription had been deployed for Constitution Bench matters since February. Transcripts in almost ten main matters had been generated and published on the court's website. The use was on a trial basis. A Press Information Bureau feature of 11 February 2026 states that the system is being extended to regular hearing days. That follows successful use in Constitution Bench proceedings.", "category": "benefit created", "unexpected": false, "purpose": "The transcription was introduced to give judges, lawyers and law colleges a record of arguments and to make the court a court of record. Published transcripts are that purpose.", "system": "TERES AI live transcription (speech-to-text) of Constitution Bench hearings", "model_version": null, "developer": "TERES (named by LiveLaw as the company supplying the transcription service)", "deployer": "Supreme Court of India", "location": null, "domain": "Courts / language technology", "segment": "Court transcription", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The transcripts are a new record of hearings for lawyers and the public, published only partially.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The court gained lawyer-verified transcripts for some Constitution Bench hearings on a trial basis. That was 9 of 25 by May 2023, almost ten matters by December 2023." }, { "group": "societal", "depth": 1, "reason": "Transcripts were published on the court's website for public and academic use, but only for a minority of hearings in the first months." } ], "ai_role": { "status": "assessed", "statement": "The AI produced the live draft. Lawyers proofread before publication and, per the Chief Justice, people oversee overlapping speech. The published-transcript rate (36% of hearings by May 2023) shows the benefit depended as much on human vetting as on the recognizer." }, "evidence": [ { "kind": "news report", "citation": "Sharma P (21 Feb 2023). Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings. LiveLaw (quotes CJI DY Chandrachud; names TERES).", "title": "Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings", "url": "https://www.livelaw.in/top-stories/supreme-court-ai-live-transcriptions-of-its-hearings-222108", "date": "2023-02-21", "written_by": "independent", "quote": "We're just trying to explore the possibilities of live transcript. It is an experiment." }, { "kind": "news report", "citation": "Spandana RS (18 May 2023). SC's Live Transcription Project: A Failed Experiment? Supreme Court Observer.", "title": "SC's Live Transcription Project: A Failed Experiment?", "url": "https://www.scobserver.in/journal/scs-live-transcription-project-a-failed-experiment/", "date": "2023-05-18", "written_by": "independent", "quote": "25 Constitution Bench hearings have been conducted across 4 cases. However, only 9 transcripts have been published so far." }, { "kind": "news report", "citation": "NDTV (8 Dec 2023). Supreme Court Using AI To Transcribe Arguments By Constitution Benches (Law Minister Arjun Ram Meghwal's written reply in the Lok Sabha).", "title": "Supreme Court Using AI To Transcribe Arguments By Constitution Benches", "url": "https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186", "date": "2023-12-08", "written_by": "independent", "quote": "In almost 10 (main) constitution bench matters, transcripts of arguments by use of artificial intelligence have been generated and these are published through the official website of the Supreme Court." }, { "kind": "press release", "citation": "Press Information Bureau, Government of India (11 Feb 2026). From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India.", "title": "From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283%C2%AE=48&lang=2", "date": "2026-02-11", "written_by": "deployer", "quote": "The system is being gradually extended to regular hearing days after successful use in Constitution Bench proceedings." } ], "replication": { "produced_by": [ "A speech-to-text service installed in one courtroom with screens for counsel", "A verification step in which lawyers proofread transcripts before publication", "Court leadership willing to run it as an experiment on Constitution Bench matters" ], "must_hold": [ "Human vetting capacity, since unpublished transcripts accumulated in March 2023", "Handling of overlapping speech in the courtroom", "Continued institutional backing (the Law Ministry described it as trial use)" ], "echoes": [ { "date": "2023-12-08", "setting": "Lok Sabha written reply: AI transcripts generated in almost ten main Constitution Bench matters and published on the Supreme Court website", "model_version": null, "outcome": "recurred", "source": "NDTV, 8 Dec 2023, https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186" }, { "date": "2026-02-11", "setting": "Government feature states the transcription system is being extended to regular hearing days", "model_version": null, "outcome": "recurred", "source": "PIB, 11 Feb 2026, https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283®=48&lang=2" } ] }, "paired_incident": null, "headline": "Supreme Court of India publishes TERES AI hearing transcripts", "metric": "9 of 25 hearings had published transcripts by May 2023", "comparator": null, "later": null, "value": null, "developer_country": "Singapore", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://teres.ai/; https://en.wikipedia.org/wiki/Supreme_Court_of_India", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0218", "catalog_version": "1.0.0", "source_fingerprint": "c8b86bc4e518883437e91593485e92770ec074d62a17279dc847ae5161b72b49", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0218-source-0001", "AIBD-0218-source-0002", "AIBD-0218-source-0003", "AIBD-0218-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "TERES (named by LiveLaw as the company supplying the transcription service)", "deployer": "Supreme Court of India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI produced the live draft. 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Chandrachud's Constitution Bench heard the Maharashtra political crisis matter in Court Room 1. It used AI live transcription supplied by TERES, with screens facing the lawyers showing the text. The Chief Justice called it an experiment. He said transcripts would go to lawyers for verification and then onto the Supreme Court website (LiveLaw, 21 February 2023). The Supreme Court Observer reported on 18 May 2023 that 25 Constitution Bench hearings had been held across four cases. Only nine transcripts had been published: six for the marriage-equality case, three for the Maharashtra case, none for the other two. None was published in March 2023. NDTV reported on 8 December 2023 a written reply in the Lok Sabha by Law Minister Arjun Ram Meghwal. He said AI transcription had been deployed for Constitution Bench matters since February. Transcripts in almost ten main matters had been generated and published on the court's website. The use was on a trial basis. 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That was 9 of 25 by May 2023, almost ten matters by December 2023." }, { "group": "societal", "depth": 1, "reason": "Transcripts were published on the court's website for public and academic use, but only for a minority of hearings in the first months." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The transcription was introduced to give judges, lawyers and law colleges a record of arguments and to make the court a court of record. Published transcripts are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Singapore", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The transcription was introduced to give judges, lawyers and law colleges a record of arguments and to make the court a court of record. Published transcripts are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-02-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://teres.ai/; https://en.wikipedia.org/wiki/Supreme_Court_of_India", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A speech-to-text service installed in one courtroom with screens for counsel", "A verification step in which lawyers proofread transcripts before publication", "Court leadership willing to run it as an experiment on Constitution Bench matters" ], "must_hold": [ "Human vetting capacity, since unpublished transcripts accumulated in March 2023", "Handling of overlapping speech in the courtroom", "Continued institutional backing (the Law Ministry described it as trial use)" ], "echoes": [ { "date": "2023-12-08", "setting": "Lok Sabha written reply: AI transcripts generated in almost ten main Constitution Bench matters and published on the Supreme Court website", "outcome": "recurred", "source": "NDTV, 8 Dec 2023, https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186" }, { "date": "2026-02-11", "setting": "Government feature states the transcription system is being extended to regular hearing days", "outcome": "recurred", "source": "PIB, 11 Feb 2026, https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283®=48&lang=2" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A speech-to-text service installed in one courtroom with screens for counsel", "A verification step in which lawyers proofread transcripts before publication", "Court leadership willing to run it as an experiment on Constitution Bench matters" ], "must_hold": [ "Human vetting capacity, since unpublished transcripts accumulated in March 2023", "Handling of overlapping speech in the courtroom", "Continued institutional backing (the Law Ministry described it as trial use)" ], "echoes": [ { "date": "2023-12-08", "setting": "Lok Sabha written reply: AI transcripts generated in almost ten main Constitution Bench matters and published on the Supreme Court website", "outcome": "recurred", "source": "NDTV, 8 Dec 2023, https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186" }, { "date": "2026-02-11", "setting": "Government feature states the transcription system is being extended to regular hearing days", "outcome": "recurred", "source": "PIB, 11 Feb 2026, https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283®=48&lang=2" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://teres.ai/; https://en.wikipedia.org/wiki/Supreme_Court_of_India", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Courts / language technology", "segment": "Court transcription" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Sharma P (21 Feb 2023). Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings. LiveLaw (quotes CJI DY Chandrachud; names TERES).", "title": "Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings", "url": "https://www.livelaw.in/top-stories/supreme-court-ai-live-transcriptions-of-its-hearings-222108", "date": "2023-02-21", "written_by": "independent", "quote": "We're just trying to explore the possibilities of live transcript. It is an experiment." }, { "kind": "news report", "citation": "Spandana RS (18 May 2023). SC's Live Transcription Project: A Failed Experiment? Supreme Court Observer.", "title": "SC's Live Transcription Project: A Failed Experiment?", "url": "https://www.scobserver.in/journal/scs-live-transcription-project-a-failed-experiment/", "date": "2023-05-18", "written_by": "independent", "quote": "25 Constitution Bench hearings have been conducted across 4 cases. However, only 9 transcripts have been published so far." }, { "kind": "news report", "citation": "NDTV (8 Dec 2023). Supreme Court Using AI To Transcribe Arguments By Constitution Benches (Law Minister Arjun Ram Meghwal's written reply in the Lok Sabha).", "title": "Supreme Court Using AI To Transcribe Arguments By Constitution Benches", "url": "https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186", "date": "2023-12-08", "written_by": "independent", "quote": "In almost 10 (main) constitution bench matters, transcripts of arguments by use of artificial intelligence have been generated and these are published through the official website of the Supreme Court." }, { "kind": "press release", "citation": "Press Information Bureau, Government of India (11 Feb 2026). From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India.", "title": "From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283%C2%AE=48&lang=2", "date": "2026-02-11", "written_by": "deployer", "quote": "The system is being gradually extended to regular hearing days after successful use in Constitution Bench proceedings." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0218-source-0001", "AIBD-0218-source-0002", "AIBD-0218-source-0003", "AIBD-0218-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Sharma P (21 Feb 2023). Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings. LiveLaw (quotes CJI DY Chandrachud; names TERES).", "title": "Breaking: Supreme Court Utilises AI To Make Live Transcriptions Of Its Hearings", "url": "https://www.livelaw.in/top-stories/supreme-court-ai-live-transcriptions-of-its-hearings-222108", "date": "2023-02-21", "written_by": "independent", "quote": "We're just trying to explore the possibilities of live transcript. It is an experiment." }, { "kind": "news report", "citation": "Spandana RS (18 May 2023). SC's Live Transcription Project: A Failed Experiment? Supreme Court Observer.", "title": "SC's Live Transcription Project: A Failed Experiment?", "url": "https://www.scobserver.in/journal/scs-live-transcription-project-a-failed-experiment/", "date": "2023-05-18", "written_by": "independent", "quote": "25 Constitution Bench hearings have been conducted across 4 cases. However, only 9 transcripts have been published so far." }, { "kind": "news report", "citation": "NDTV (8 Dec 2023). Supreme Court Using AI To Transcribe Arguments By Constitution Benches (Law Minister Arjun Ram Meghwal's written reply in the Lok Sabha).", "title": "Supreme Court Using AI To Transcribe Arguments By Constitution Benches", "url": "https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186", "date": "2023-12-08", "written_by": "independent", "quote": "In almost 10 (main) constitution bench matters, transcripts of arguments by use of artificial intelligence have been generated and these are published through the official website of the Supreme Court." }, { "kind": "press release", "citation": "Press Information Bureau, Government of India (11 Feb 2026). From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India.", "title": "From Digitisation to Intelligence: How AI is Enhancing Access to Justice in India", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283%C2%AE=48&lang=2", "date": "2026-02-11", "written_by": "deployer", "quote": "The system is being gradually extended to regular hearing days after successful use in Constitution Bench proceedings." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "From 21 Feb 2023 the Supreme Court of India transcribed Constitution Bench hearings live with an AI service from TERES; 9 of 25 hearings had published transcripts by May 2023, and almost 10 matters...", "account": "On 21 February 2023 Chief Justice D.Y. Chandrachud's Constitution Bench heard the Maharashtra political crisis matter in Court Room 1. It used AI live transcription supplied by TERES, with screens facing the lawyers showing the text. The Chief Justice called it an experiment. He said transcripts would go to lawyers for verification and then onto the Supreme Court website (LiveLaw, 21 February 2023). The Supreme Court Observer reported on 18 May 2023 that 25 Constitution Bench hearings had been held across four cases. Only nine transcripts had been published: six for the marriage-equality case, three for the Maharashtra case, none for the other two. None was published in March 2023. NDTV reported on 8 December 2023 a written reply in the Lok Sabha by Law Minister Arjun Ram Meghwal. He said AI transcription had been deployed for Constitution Bench matters since February. Transcripts in almost ten main matters had been generated and published on the court's website. The use was on a trial basis. A Press Information Bureau feature of 11 February 2026 states that the system is being extended to regular hearing days. That follows successful use in Constitution Bench proceedings." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "TERES AI live transcription (speech-to-text) of Constitution Bench hearings" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "TERES (named by LiveLaw as the company supplying the transcription service)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Supreme Court of India starts AI live transcription of Constitution Bench hearings with TERES; lawyer-verified transcripts published on the court's website", "headline": "Supreme Court of India publishes TERES AI hearing transcripts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c8b86bc4e518883437e91593485e92770ec074d62a17279dc847ae5161b72b49" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 21 February 2023 Chief Justice D.Y. Chandrachud's Constitution Bench heard the Maharashtra political crisis matter in Court Room 1. It used AI live transcription supplied by TERES, with screens facing the lawyers showing the text. The Chief Justice called it an experiment. He said transcripts would go to lawyers for verification and then onto the Supreme Court website (LiveLaw, 21 February 2023). The Supreme Court Observer reported on 18 May 2023 that 25 Constitution Bench hearings had been held across four cases. Only nine transcripts had been published: six for the marriage-equality case, three for the Maharashtra case, none for the other two. None was published in March 2023. NDTV reported on 8 December 2023 a written reply in the Lok Sabha by Law Minister Arjun Ram Meghwal. He said AI transcription had been deployed for Constitution Bench matters since February. Transcripts in almost ten main matters had been generated and published on the court's website. The use was on a trial basis. A Press Information Bureau feature of 11 February 2026 states that the system is being extended to regular hearing days. That follows successful use in Constitution Bench proceedings.", "replication": { "produced_by": [ "A speech-to-text service installed in one courtroom with screens for counsel", "A verification step in which lawyers proofread transcripts before publication", "Court leadership willing to run it as an experiment on Constitution Bench matters" ], "must_hold": [ "Human vetting capacity, since unpublished transcripts accumulated in March 2023", "Handling of overlapping speech in the courtroom", "Continued institutional backing (the Law Ministry described it as trial use)" ], "echoes": [ { "date": "2023-12-08", "setting": "Lok Sabha written reply: AI transcripts generated in almost ten main Constitution Bench matters and published on the Supreme Court website", "outcome": "recurred", "source": "NDTV, 8 Dec 2023, https://www.ndtv.com/india-news/supreme-court-using-ai-to-transcribe-arguments-by-constitution-benches-4647186" }, { "date": "2026-02-11", "setting": "Government feature states the transcription system is being extended to regular hearing days", "outcome": "recurred", "source": "PIB, 11 Feb 2026, https://www.pib.gov.in/PressReleasePage.aspx?PRID=2226283®=48&lang=2" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0285", "title": "Smartwatch irregular-rhythm notifications send a 25-year-old man to the emergency department, where atrial fibrillation is confirmed and cardioverted", "summary": "A 25-year-old's smartwatch notified him several times of an irregular rhythm consistent with AF; ECG showed AF with rapid ventricular response, treated by TEE-guided cardioversion (Cureus, 2023).", "date_observed": "2023-03-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Bedi, Al Masri, Al Hennawi, Qadir and Ottman are internal medicine physicians at Abington Jefferson Hospital, Abington, USA, with a co-author at Alfaisal University, Riyadh. They reported in Cureus on 9 March 2023 a 25-year-old man with anxiety and depression. The event is undated. He came to an emergency department with 24 hours of chest pressure and palpitations. His smartwatch had notified him several times of an irregular rhythm consistent with atrial fibrillation (AF). The authors link this to weekend binge drinking. He was tachycardic above 120 bpm. The electrocardiogram (ECG) showed AF with rapid ventricular response at 123 bpm. Intravenous diltiazem and oral metoprolol did not restore rhythm. Enoxaparin was started. BNP was 796 with a clear chest X-ray. He was admitted and, on the cardiologist's recommendation, underwent transesophageal-echo-guided electrical cardioversion the next day, restoring sinus rhythm. Despite a CHA2DS2-VASc score of 0 he was given apixaban for four weeks. He was advised on alcohol cessation and gradual return to exercise and scheduled for monthly cardiology follow-up. The report names neither the watch's brand nor model. It describes smartwatches generically as using photoplethysmography with deep neural network algorithms.", "category": "benefit created", "unexpected": false, "purpose": "Smartwatch irregular-rhythm notifications are built to prompt the wearer to seek medical review. This benefit was that purpose.", "system": "Smartwatch irregular-rhythm notification (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "Abington, United States (authors' hospital; the report does not name the emergency department)", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "A 25-year-old received an ECG-confirmed AF diagnosis, cardioversion to sinus rhythm and four weeks of anticoagulation. A material benefit to one person, not described as life-saving." } ], "ai_role": { "status": "assessed", "statement": "The watch's own notification, repeated several times, is what the report says prompted the visit. Clinicians confirmed AF on a 12-lead ECG and chose cardioversion. The brand is unknown, so the algorithm behind the notification cannot be identified. The authors describe smartwatch rhythm detection generically as deep-neural-network analysis of pulse waves." }, "evidence": [ { "kind": "case report", "citation": "Bedi A, Al Masri MK, Al Hennawi H, Qadir S, Ottman P (2023). The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch. Cureus 15(3):e35941. doi:10.7759/cureus.35941 (PMC10082624).", "title": "The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10082624/", "date": "2023-03-09", "written_by": "independent", "quote": "The patient sought medical attention after his smartwatch notified him several times of an irregular heart rhythm consistent with atrial fibrillation (AF)" }, { "kind": "case report", "citation": "Bedi A et al. (2023), Cureus 15(3):e35941, treatment and outcome.", "title": "The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10082624/", "date": "2023-03-09", "written_by": "independent", "quote": "Upon the cardiologist's recommendation, the patient underwent transesophageal echocardiography (TEE)-guided electrical cardioversion the next day, and normal sinus rhythm was successfully restored." } ], "replication": { "produced_by": [ "A wearer with symptomatic AF whose smartwatch issued repeated irregular-rhythm notifications", "The wearer acting on the notifications by attending an emergency department", "Clinicians confirming the rhythm on a 12-lead ECG and treating it" ], "must_hold": [ "The watch's notification corresponds to a true arrhythmia (the authors cite a positive predictive value of 84% for irregular-pulse notifications in the Apple Heart Study)", "The wearer treats the notification as a reason to seek care" ], "echoes": [ { "date": null, "setting": "Apple Heart Study, cited in the report's discussion: 34% of participants alerted to an irregular rhythm were later diagnosed with AF, positive predictive value 84%", "model_version": null, "outcome": "recurred", "source": "Bedi A et al. (2023), Cureus 15(3):e35941, discussion, citing Perez et al. 2019" } ] }, "paired_incident": null, "headline": "Smartwatch AF alerts in a 25-year-old lead to cardioversion", "metric": "atrial fibrillation with rapid ventricular response at 123 bpm", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The report ends with monthly cardiology follow-up recommended; nothing later was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. 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(2023), Cureus 15(3):e35941, treatment and outcome.", "title": "The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10082624/", "date": "2023-03-09", "written_by": "independent", "quote": "Upon the cardiologist's recommendation, the patient underwent transesophageal echocardiography (TEE)-guided electrical cardioversion the next day, and normal sinus rhythm was successfully restored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0285-source-0001", "AIBD-0285-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Bedi A, Al Masri MK, Al Hennawi H, Qadir S, Ottman P (2023). The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch. Cureus 15(3):e35941. doi:10.7759/cureus.35941 (PMC10082624).", "title": "The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10082624/", "date": "2023-03-09", "written_by": "independent", "quote": "The patient sought medical attention after his smartwatch notified him several times of an irregular heart rhythm consistent with atrial fibrillation (AF)" }, { "kind": "case report", "citation": "Bedi A et al. (2023), Cureus 15(3):e35941, treatment and outcome.", "title": "The Integration of Artificial Intelligence Into Patient Care: A Case of Atrial Fibrillation Caught by a Smartwatch", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10082624/", "date": "2023-03-09", "written_by": "independent", "quote": "Upon the cardiologist's recommendation, the patient underwent transesophageal echocardiography (TEE)-guided electrical cardioversion the next day, and normal sinus rhythm was successfully restored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 25-year-old's smartwatch notified him several times of an irregular rhythm consistent with AF; ECG showed AF with rapid ventricular response, treated by TEE-guided cardioversion (Cureus, 2023).", "account": "Bedi, Al Masri, Al Hennawi, Qadir and Ottman are internal medicine physicians at Abington Jefferson Hospital, Abington, USA, with a co-author at Alfaisal University, Riyadh. They reported in Cureus on 9 March 2023 a 25-year-old man with anxiety and depression. The event is undated. He came to an emergency department with 24 hours of chest pressure and palpitations. His smartwatch had notified him several times of an irregular rhythm consistent with atrial fibrillation (AF). The authors link this to weekend binge drinking. He was tachycardic above 120 bpm. The electrocardiogram (ECG) showed AF with rapid ventricular response at 123 bpm. Intravenous diltiazem and oral metoprolol did not restore rhythm. Enoxaparin was started. BNP was 796 with a clear chest X-ray. He was admitted and, on the cardiologist's recommendation, underwent transesophageal-echo-guided electrical cardioversion the next day, restoring sinus rhythm. Despite a CHA2DS2-VASc score of 0 he was given apixaban for four weeks. He was advised on alcohol cessation and gradual return to exercise and scheduled for monthly cardiology follow-up. The report names neither the watch's brand nor model. It describes smartwatches generically as using photoplethysmography with deep neural network algorithms." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartwatch irregular-rhythm notification (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Smartwatch irregular-rhythm notifications send a 25-year-old man to the emergency department, where atrial fibrillation is confirmed and cardioverted", "headline": "Smartwatch AF alerts in a 25-year-old lead to cardioversion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2c98991014f1892d81ae3e4824ac9758a80cc67b0705038ed44aa222fef608fa" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Bedi, Al Masri, Al Hennawi, Qadir and Ottman are internal medicine physicians at Abington Jefferson Hospital, Abington, USA, with a co-author at Alfaisal University, Riyadh. They reported in Cureus on 9 March 2023 a 25-year-old man with anxiety and depression. The event is undated. He came to an emergency department with 24 hours of chest pressure and palpitations. His smartwatch had notified him several times of an irregular rhythm consistent with atrial fibrillation (AF). The authors link this to weekend binge drinking. He was tachycardic above 120 bpm. The electrocardiogram (ECG) showed AF with rapid ventricular response at 123 bpm. Intravenous diltiazem and oral metoprolol did not restore rhythm. Enoxaparin was started. BNP was 796 with a clear chest X-ray. He was admitted and, on the cardiologist's recommendation, underwent transesophageal-echo-guided electrical cardioversion the next day, restoring sinus rhythm. Despite a CHA2DS2-VASc score of 0 he was given apixaban for four weeks. He was advised on alcohol cessation and gradual return to exercise and scheduled for monthly cardiology follow-up. The report names neither the watch's brand nor model. It describes smartwatches generically as using photoplethysmography with deep neural network algorithms.", "replication": { "produced_by": [ "A wearer with symptomatic AF whose smartwatch issued repeated irregular-rhythm notifications", "The wearer acting on the notifications by attending an emergency department", "Clinicians confirming the rhythm on a 12-lead ECG and treating it" ], "must_hold": [ "The watch's notification corresponds to a true arrhythmia (the authors cite a positive predictive value of 84% for irregular-pulse notifications in the Apple Heart Study)", "The wearer treats the notification as a reason to seek care" ], "echoes": [ { "setting": "Apple Heart Study, cited in the report's discussion: 34% of participants alerted to an irregular rhythm were later diagnosed with AF, positive predictive value 84%", "outcome": "recurred", "source": "Bedi A et al. (2023), Cureus 15(3):e35941, discussion, citing Perez et al. 2019" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0138", "title": "GPT-4 lists immune-mediated hemolytic anemia among causes of a Border Collie's worsening anemia; a second vet confirms and treats", "summary": "GPT-4 listed IMHA among causes of a dog's worsening anemia; a second vet confirmed and treated; the dog recovered, per the owner's thread.", "date_observed": "2023-03-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A Twitter user, Cooper (@peakcooper), wrote on 25 March 2023 that his Border Collie, Sassy, had been treated for babesiosis but worsened. She had pale gums and more severe anemia. The first vet found no cause and advised waiting. He entered two sets of bloodwork into ChatGPT Plus running GPT-4. It said it was not a veterinarian, then listed possible underlying causes including immune-mediated hemolytic anemia (IMHA). At a second clinic he asked about IMHA. The vet agreed after further tests, treatment began, and Cooper reported an almost full recovery. The New York Post, India Today and Business Insider reported the thread (27 to 30 March). Cooper did not respond to Insider, and no veterinarian has spoken publicly.", "category": "protective response", "unexpected": false, "purpose": "GPT-4, served through ChatGPT, is a general-purpose conversational model built to answer questions and follow instructions. Answering a diagnostic question about a dog's bloodwork is an instance of that general use, not a designed veterinary function. The model itself prefaced its answer by saying it is not a veterinarian.", "system": "ChatGPT Plus (GPT-4)", "model_version": "GPT-4", "developer": "OpenAI", "deployer": "OpenAI", "location": null, "domain": "Veterinary medicine (consumer use)", "segment": "Consumer", "benefit_type": "Improved Physical Health", "taxonomy_note": "The patient is a dog, and the owner's gain is its recovery after a candidate diagnosis the model surfaced.", "registry_ids": { "oecd_aim": "2023-03-27-6c5c" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "By the owner's own account the diagnosis led to treatment and his dog's near-full recovery. The account is self-reported and unverified by any clinician. The beneficiary is one owner and one animal." } ], "ai_role": { "status": "assessed", "statement": "From the owner's typed description and two sets of blood results, GPT-4 explained the trend in the bloodwork. When asked what else could underlie the anemia, it listed candidate causes including IMHA. The owner chose IMHA to put to a second veterinarian, who confirmed it after further tests and treated the dog. Whether that vet would have reached IMHA unprompted is unknown. The owner himself notes IMHA is a common complication of babesiosis, so the counterfactual is unproven. The owner reported that GPT-3.5 did not reach the diagnosis. He said the tool “should be a tool to be used by professionals”." }, "evidence": [ { "kind": "news report", "citation": "Steinberg, B. / New York Post (2023). ChatGPT saved my dog's life after vets couldn't figure out diagnosis. New York Post, 27 March 2023.", "title": "ChatGPT saved my dog's life after vets couldn't figure out diagnosis", "url": "https://nypost.com/2023/03/27/chatgpt-saved-my-dogs-life-after-vet-couldnt-diagnosis-it/", "date": "2023-03-27", "written_by": "independent", "quote": "Once at the second vet, Cooper asked if it could be IMHA, and after many tests, the doctor confirmed that ChatGPT4 was correct." }, { "kind": "news report", "citation": "Nguyen, B. / Business Insider (2023). Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics. Business Insider, 30 March 2023.", "title": "Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics", "url": "https://www.businessinsider.com/twitter-user-claims-gpt4-saved-dogs-life-vet-couldnt-diagnose-2023-3", "date": "2023-03-30", "written_by": "independent", "quote": "Cooper asked the AI what other underlying issues could possibly be, and it gave him a list, including IMHA, or immune-mediated hemolytic anemia." }, { "kind": "news report", "citation": "Chakravarti, A. / India Today (2023). ChatGPT saves life of dog, diagnoses problem that even vet could not identify. India Today, 28 March 2023.", "title": "ChatGPT saves life of dog, diagnoses problem that even vet could not identify", "url": "https://www.indiatoday.in/technology/news/story/chatgpt-saves-life-of-dog-diagnoses-problem-that-even-vet-could-not-identify-2352306-2023-03-28", "date": "2023-03-28", "written_by": "independent", "quote": "it suggested that Sassy's bloodwork and symptoms could indicate immune-mediated hemolytic anaemia (IMHA)." }, { "kind": "other", "citation": "Cooper (@peakcooper) (2023). #GPT4 saved my dog's life. Twitter thread, 25 March 2023.", "title": "#GPT4 saved my dog's life (Twitter thread, first post)", "url": "https://twitter.com/peakcooper/status/1639716822680236032", "date": "2023-03-25", "written_by": "beneficiary", "quote": "#GPT4 saved my dog's life. After my dog got diagnosed with a tick-borne disease, the vet started her on the proper treatment" } ], "replication": { "produced_by": [ "The owner had two sets of actual blood results plus the babesiosis diagnosis and treatment history. He entered them, with which tests had been run, into GPT-4 via ChatGPT Plus rather than GPT-3.5.", "The first vet had no working diagnosis and advised waiting, which left the owner looking for a second opinion.", "A second veterinarian was willing to test for the owner-raised hypothesis and confirmed it before treating." ], "must_hold": [ "A licensed clinician confirms the model's suggestion with tests before any treatment is started.", "The model's output is treated as a hypothesis to raise with a clinician, not as a diagnosis, consistent with its own disclaimer.", "The underlying data entered are real laboratory results, not a lay description of symptoms alone." ], "echoes": [] }, "paired_incident": null, "headline": "GPT-4 lists IMHA among causes of a dog's anemia; vet confirms", "metric": null, "comparator": { "against": "the first veterinarian, who found no cause after further tests and advised waiting", "before": "the vet had no clue what it could be", "after": "After more blood tests, \"the diagnosis was confirmed. GPT4 was right.\"", "basis": "assumed", "quote": "After running more tests to find co-infections related to tick-borne diseases, Cooper said the tests were negative and that \"the vet had no clue what it could be.\" The vet suggested waiting to see what happened, but Cooper said that \"wasn't an acceptable answer,\" and sought a second opinion from another clinic.", "url": "https://www.businessinsider.com/twitter-user-claims-gpt4-saved-dogs-life-vet-couldnt-diagnose-2023-3" }, "later": { "status": "unknown", "date": null, "note": "Nothing after the March 2023 coverage was found; the thread itself already reported that Sassy had made almost a full recovery.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: every published account traces to the owner's own thread, no vet statement or record has surfaced, Business Insider got no reply from the owner, and the counterfactual is unproven. GPT-4 produced a list of candidate causes that included IMHA, not a single diagnosis. The event is dated to the thread (25 March 2023); the Monitor's ID date (27 March) is the New York Post report.", "source": "https://oecd.ai/en/incidents/2023-03-27-6c5c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.businessinsider.com/twitter-user-claims-gpt4-saved-dogs-life-vet-couldnt-diagnose-2023-3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0138", "catalog_version": "1.0.0", "source_fingerprint": "9752a9cc019ef4baa1ceef1adda01678b7a31e52cc30030e0291373c54164957", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0138-source-0001", "AIBD-0138-source-0002", "AIBD-0138-source-0003", "AIBD-0138-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "From the owner's typed description and two sets of blood results, GPT-4 explained the trend in the bloodwork. When asked what else could underlie the anemia, it listed candidate causes including IMHA. The owner chose IMHA to put to a second veterinarian, who confirmed it after further tests and treated the dog. Whether that vet would have reached IMHA unprompted is unknown. The owner himself notes IMHA is a common complication of babesiosis, so the counterfactual is unproven. The owner reported that GPT-3.5 did not reach the diagnosis. He said the tool “should be a tool to be used by professionals”." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "From the owner's typed description and two sets of blood results, GPT-4 explained the trend in the bloodwork. When asked what else could underlie the anemia, it listed candidate causes including IMHA. The owner chose IMHA to put to a second veterinarian, who confirmed it after further tests and treated the dog. Whether that vet would have reached IMHA unprompted is unknown. The owner himself notes IMHA is a common complication of babesiosis, so the counterfactual is unproven. The owner reported that GPT-3.5 did not reach the diagnosis. He said the tool “should be a tool to be used by professionals”." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the owner's own account the diagnosis led to treatment and his dog's near-full recovery. The account is self-reported and unverified by any clinician. The beneficiary is one owner and one animal." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the owner's own account the diagnosis led to treatment and his dog's near-full recovery. The account is self-reported and unverified by any clinician. The beneficiary is one owner and one animal." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the owner's own account the diagnosis led to treatment and his dog's near-full recovery. The account is self-reported and unverified by any clinician. 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ChatGPT saved my dog's life after vets couldn't figure out diagnosis. New York Post, 27 March 2023.", "title": "ChatGPT saved my dog's life after vets couldn't figure out diagnosis", "url": "https://nypost.com/2023/03/27/chatgpt-saved-my-dogs-life-after-vet-couldnt-diagnosis-it/", "date": "2023-03-27", "written_by": "independent", "quote": "Once at the second vet, Cooper asked if it could be IMHA, and after many tests, the doctor confirmed that ChatGPT4 was correct." }, { "kind": "news report", "citation": "Nguyen, B. / Business Insider (2023). Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics. Business Insider, 30 March 2023.", "title": "Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics", "url": "https://www.businessinsider.com/twitter-user-claims-gpt4-saved-dogs-life-vet-couldnt-diagnose-2023-3", "date": "2023-03-30", "written_by": "independent", "quote": "Cooper asked the AI what other underlying issues could possibly be, and it gave him a list, including IMHA, or immune-mediated hemolytic anemia." }, { "kind": "news report", "citation": "Chakravarti, A. / India Today (2023). ChatGPT saves life of dog, diagnoses problem that even vet could not identify. India Today, 28 March 2023.", "title": "ChatGPT saves life of dog, diagnoses problem that even vet could not identify", "url": "https://www.indiatoday.in/technology/news/story/chatgpt-saves-life-of-dog-diagnoses-problem-that-even-vet-could-not-identify-2352306-2023-03-28", "date": "2023-03-28", "written_by": "independent", "quote": "it suggested that Sassy's bloodwork and symptoms could indicate immune-mediated hemolytic anaemia (IMHA)." }, { "kind": "other", "citation": "Cooper (@peakcooper) (2023). #GPT4 saved my dog's life. Twitter thread, 25 March 2023.", "title": "#GPT4 saved my dog's life (Twitter thread, first post)", "url": "https://twitter.com/peakcooper/status/1639716822680236032", "date": "2023-03-25", "written_by": "beneficiary", "quote": "#GPT4 saved my dog's life. After my dog got diagnosed with a tick-borne disease, the vet started her on the proper treatment" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0138-source-0001", "AIBD-0138-source-0002", "AIBD-0138-source-0003", "AIBD-0138-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Steinberg, B. / New York Post (2023). ChatGPT saved my dog's life after vets couldn't figure out diagnosis. New York Post, 27 March 2023.", "title": "ChatGPT saved my dog's life after vets couldn't figure out diagnosis", "url": "https://nypost.com/2023/03/27/chatgpt-saved-my-dogs-life-after-vet-couldnt-diagnosis-it/", "date": "2023-03-27", "written_by": "independent", "quote": "Once at the second vet, Cooper asked if it could be IMHA, and after many tests, the doctor confirmed that ChatGPT4 was correct." }, { "kind": "news report", "citation": "Nguyen, B. / Business Insider (2023). Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics. Business Insider, 30 March 2023.", "title": "Twitter User Claims GPT-4 Saved Dog's Life Through Diagnostics", "url": "https://www.businessinsider.com/twitter-user-claims-gpt4-saved-dogs-life-vet-couldnt-diagnose-2023-3", "date": "2023-03-30", "written_by": "independent", "quote": "Cooper asked the AI what other underlying issues could possibly be, and it gave him a list, including IMHA, or immune-mediated hemolytic anemia." }, { "kind": "news report", "citation": "Chakravarti, A. / India Today (2023). ChatGPT saves life of dog, diagnoses problem that even vet could not identify. India Today, 28 March 2023.", "title": "ChatGPT saves life of dog, diagnoses problem that even vet could not identify", "url": "https://www.indiatoday.in/technology/news/story/chatgpt-saves-life-of-dog-diagnoses-problem-that-even-vet-could-not-identify-2352306-2023-03-28", "date": "2023-03-28", "written_by": "independent", "quote": "it suggested that Sassy's bloodwork and symptoms could indicate immune-mediated hemolytic anaemia (IMHA)." }, { "kind": "other", "citation": "Cooper (@peakcooper) (2023). #GPT4 saved my dog's life. Twitter thread, 25 March 2023.", "title": "#GPT4 saved my dog's life (Twitter thread, first post)", "url": "https://twitter.com/peakcooper/status/1639716822680236032", "date": "2023-03-25", "written_by": "beneficiary", "quote": "#GPT4 saved my dog's life. After my dog got diagnosed with a tick-borne disease, the vet started her on the proper treatment" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "GPT-4 listed IMHA among causes of a dog's worsening anemia; a second vet confirmed and treated; the dog recovered, per the owner's thread.", "account": "A Twitter user, Cooper (@peakcooper), wrote on 25 March 2023 that his Border Collie, Sassy, had been treated for babesiosis but worsened. She had pale gums and more severe anemia. The first vet found no cause and advised waiting. He entered two sets of bloodwork into ChatGPT Plus running GPT-4. It said it was not a veterinarian, then listed possible underlying causes including immune-mediated hemolytic anemia (IMHA). At a second clinic he asked about IMHA. The vet agreed after further tests, treatment began, and Cooper reported an almost full recovery. The New York Post, India Today and Business Insider reported the thread (27 to 30 March). Cooper did not respond to Insider, and no veterinarian has spoken publicly." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "GPT-4 interpreted blood-test results and suggested possible causes of the dog’s anemia." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GPT-4." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-4" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT Plus (GPT-4)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GPT-4 lists immune-mediated hemolytic anemia among causes of a Border Collie's worsening anemia; a second vet confirms and treats", "headline": "GPT-4 lists IMHA among causes of a dog's anemia; vet confirms" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9752a9cc019ef4baa1ceef1adda01678b7a31e52cc30030e0291373c54164957" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A Twitter user, Cooper (@peakcooper), wrote on 25 March 2023 that his Border Collie, Sassy, had been treated for babesiosis but worsened. She had pale gums and more severe anemia. The first vet found no cause and advised waiting. He entered two sets of bloodwork into ChatGPT Plus running GPT-4. It said it was not a veterinarian, then listed possible underlying causes including immune-mediated hemolytic anemia (IMHA). At a second clinic he asked about IMHA. The vet agreed after further tests, treatment began, and Cooper reported an almost full recovery. The New York Post, India Today and Business Insider reported the thread (27 to 30 March). Cooper did not respond to Insider, and no veterinarian has spoken publicly.", "replication": { "produced_by": [ "The owner had two sets of actual blood results plus the babesiosis diagnosis and treatment history. He entered them, with which tests had been run, into GPT-4 via ChatGPT Plus rather than GPT-3.5.", "The first vet had no working diagnosis and advised waiting, which left the owner looking for a second opinion.", "A second veterinarian was willing to test for the owner-raised hypothesis and confirmed it before treating." ], "must_hold": [ "A licensed clinician confirms the model's suggestion with tests before any treatment is started.", "The model's output is treated as a hypothesis to raise with a clinician, not as a diagnosis, consistent with its own disclaimer.", "The underlying data entered are real laboratory results, not a lay description of symptoms alone." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0116", "title": "York student has a £60 parking fine withdrawn after sending an appeal letter drafted by ChatGPT", "summary": "Millie Houlton, 22, asked ChatGPT to draft an appeal against a wrongly issued £60 parking fine; York City Council withdrew it.", "date_observed": "2023-03-31", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Millie Houlton, a 22-year-old final-year events and business management student at York St John University, received a £60 parking notice from York City Council. It was for parking on her own street, where she holds a permit. Busy with coursework, she was tempted to pay. Instead she typed into ChatGPT “please help me write a letter to the council, they gave me a parking ticket”. She gave the location, reference number and circumstances. The letter came back in minutes. Within days the council told her the appeal was accepted and the fine withdrawn. The BBC and ITV News reported the case on 30 and 31 March 2023, and she shared it on TikTok.", "category": "benefit created", "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant built to answer questions and draft text on request. Writing a formal appeal letter from the user's facts is squarely within that purpose.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": "OpenAI", "location": "York, United Kingdom", "domain": "Public administration (parking enforcement appeals)", "segment": "Consumer", "benefit_type": "Reduced Task Time", "taxonomy_note": "The good is a wrongly issued 60-pound fine withdrawn, and the type names the minutes-long drafting of the appeal that produced it.", "registry_ids": { "oecd_aim": "2023-03-31-6b48" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "One identifiable person avoided a £60 fine she considered wrongly issued and the time of drafting an appeal she said she found hard to articulate." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT drafted the appeal from the facts the student entered. The ground for withdrawal was her valid permit, which a human-written appeal could also have stated. The system's contribution was overcoming the effort barrier. She said she would otherwise have paid rather than spend time on a response. The council's reasoning has not been published, so the letter's causal weight is inferred, not documented." }, "evidence": [ { "kind": "news report", "citation": "BBC News (2023). York student uses AI chatbot to get parking fine revoked. BBC News, York & North Yorkshire, 31 March 2023.", "title": "York student uses AI chatbot to get parking fine revoked", "url": "https://www.bbc.co.uk/news/uk-england-york-north-yorkshire-65126772", "date": "2023-03-31", "written_by": "independent", "quote": "A student has successfully appealed against a £60 parking fine by using a letter written by an artificial intelligence chatbot." }, { "kind": "news report", "citation": "ITV News Calendar (2023). York student uses AI 'chatbot' to get £60 parking fine overturned. ITV News, 31 March 2023.", "title": "York student uses AI 'chatbot' to get £60 parking fine overturned", "url": "https://www.itv.com/news/calendar/2023-03-31/appeal-written-by-ai-chatbot-helps-student-overturn-parking-fine", "date": "2023-03-31", "written_by": "independent", "quote": "Within days she was notified that the appeal had been accepted." }, { "kind": "news report", "citation": "Ali, A. / Yorkshire Post (2023). Student overturns £60 parking ticket using ChatGPT. Yorkshire Post, 31 March 2023.", "title": "Student overturns £60 parking ticket using ChatGPT", "url": "https://www.yorkshirepost.co.uk/read-this/student-overturns-ps60-parking-ticket-using-chatgpt-4088236", "date": "2023-03-31", "written_by": "independent", "quote": "Millie Houlton, a 22-year-old from York, used the language tool to write a formal appeal to York City Council." }, { "kind": "news report", "citation": "Colton, E. / Fox News (2023). How an AI chatbot allegedly helped student terminate parking fine: 'Very relieved'. Fox News, 2 April 2023.", "title": "How an AI chatbot allegedly helped student terminate parking fine: 'Very relieved'", "url": "https://www.foxnews.com/world/how-ai-chatbot-allegedly-helped-student-terminate-parking-fine-very-relieved", "date": "2023-04-02", "written_by": "independent", "quote": "Houlton said she was \"very relieved\" when the local authority revoked the fine." } ], "replication": { "produced_by": [ "The appellant had a genuine ground (a valid residents' permit) and the specific facts to hand: location, date, reference number and circumstances.", "The appeal channel accepted a written letter, so a well-formed draft was the whole task.", "The user already used ChatGPT for work emails and so trusted it enough to try it rather than pay." ], "must_hold": [ "The facts entered are true and the appellant checks the draft before sending. The model can produce plausible but incorrect text, as the BBC noted OpenAI admits.", "The authority judges the appeal on its merits, so the outcome rests on the permit, not on prose quality." ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT appeal letter gets a York student's £60 fine withdrawn", "metric": "£60 parking fine; York City Council withdrew it", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later development was found beyond the 2 April 2023 Fox News retelling of the BBC report.", "quote": null, "url": null }, "value": { "amount": "£60", "what": "parking fine withdrawn by York City Council after the ChatGPT-drafted appeal", "who": "Millie Houlton", "estimate": false, "quote": "A student has successfully appealed against a £60 parking fine by using a letter written by an artificial intelligence chatbot.", "url": "https://www.bbc.co.uk/news/uk-england-york-north-yorkshire-65126772" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. The Monitor's listed sources are Macedonian-language reposts; the record is built on the BBC, ITV News, Yorkshire Post and Fox News originals. The BBC page displays 31 March 2023 while its metadata timestamp is 2023–03–30T16:21Z; the dates of the ticket and of the withdrawal letter are not reported, so the date observed is the reporting date. The Monitor's “hazard” label is dropped: the attached rationale concerns a different story (expert warnings about AI).", "source": "https://oecd.ai/en/incidents/2023-03-31-6b48", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://www.bbc.co.uk/news/uk-england-york-north-yorkshire-65126772", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0116", "catalog_version": "1.0.0", "source_fingerprint": "a8fb11627b1e865bc3cad7ab5718ad45bb284af62153e90166cfc52ca1c35af1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0116-source-0001", "AIBD-0116-source-0002", "AIBD-0116-source-0003", "AIBD-0116-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0116-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ChatGPT drafted the appeal from the facts the student entered. The ground for withdrawal was her valid permit, which a human-written appeal could also have stated. The system's contribution was overcoming the effort barrier. She said she would otherwise have paid rather than spend time on a response. The council's reasoning has not been published, so the letter's causal weight is inferred, not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "ChatGPT drafted the appeal from the facts the student entered. The ground for withdrawal was her valid permit, which a human-written appeal could also have stated. The system's contribution was overcoming the effort barrier. She said she would otherwise have paid rather than spend time on a response. The council's reasoning has not been published, so the letter's causal weight is inferred, not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One identifiable person avoided a £60 fine she considered wrongly issued and the time of drafting an appeal she said she found hard to articulate." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports. 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It was for parking on her own street, where she holds a permit. Busy with coursework, she was tempted to pay. Instead she typed into ChatGPT “please help me write a letter to the council, they gave me a parking ticket”. She gave the location, reference number and circumstances. The letter came back in minutes. Within days the council told her the appeal was accepted and the fine withdrawn. 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It was for parking on her own street, where she holds a permit. Busy with coursework, she was tempted to pay. Instead she typed into ChatGPT “please help me write a letter to the council, they gave me a parking ticket”. She gave the location, reference number and circumstances. The letter came back in minutes. Within days the council told her the appeal was accepted and the fine withdrawn. The BBC and ITV News reported the case on 30 and 31 March 2023, and she shared it on TikTok.", "replication": { "produced_by": [ "The appellant had a genuine ground (a valid residents' permit) and the specific facts to hand: location, date, reference number and circumstances.", "The appeal channel accepted a written letter, so a well-formed draft was the whole task.", "The user already used ChatGPT for work emails and so trusted it enough to try it rather than pay." ], "must_hold": [ "The facts entered are true and the appellant checks the draft before sending. The model can produce plausible but incorrect text, as the BBC noted OpenAI admits.", "The authority judges the appeal on its merits, so the outcome rests on the permit, not on prose quality." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0080", "title": "qXR flags suspicious nodules on chest X-rays taken for non-respiratory reasons; five adults without respiratory symptoms diagnosed with early-stage lung cancer", "summary": "qXR flagged nodules on X-rays done for other reasons; CT/biopsy confirmed early-stage lung cancer in five adults; four had surgery.", "date_observed": "2023-04-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "CREATE (NCT05817110) was a prospective multicenter study. The deep-learning software qXR (Qure.ai) was adopted for routine use on all chest X-rays across participating centers from April 2023 to December 2024. Five cases were found through the AI pathway. The paper names neither the centers nor their cities. Its clinical authors are at Hacettepe University (Ankara, Turkey) and with Aarthi Scans and Sri Ramachandra Medical College and Hospital (Chennai, India). The March 2026 Cureus report describes five individuals, none with respiratory symptoms. In each, qXR flagged suspicious pulmonary nodules on X-rays taken for non-respiratory reasons. They were a 57-year-old man screened before anti-TNF therapy for ulcerative colitis and a 64-year-old man with fever. Also a 65-year-old woman at a smoking-cessation consultation and two men aged 35 and 75 at annual health checks. Computed tomography (CT) and biopsy confirmed early-stage lung cancer in all five. Four underwent curative surgery, two with adjuvant chemotherapy, and one chose chemotherapy alone. Whether the original X-ray reports noted the nodules is not stated.", "category": "benefit created", "unexpected": false, "purpose": "qXR is built to detect abnormalities including pulmonary nodules on chest X-rays. 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Cureus 18(3):e104881 (second quotation).", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "Computed tomography imaging and biopsy confirmed early-stage lung cancer in all five cases." }, { "kind": "case report", "citation": "Koksal D et al. (2026). 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external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Koksal D, Govindarajan A, Baykan A, Durhan G, Sarinc S, Akpinar MG, Demirkazik F, Mathivanan KM, Vignesh P, Shivabasappa S (2026). A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers? Cureus 18(3):e104881.", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "We present a case series of five individuals in whom AI-enabled chest X-ray (qXR, Qure.ai, Mumbai, India) flagged suspicious pulmonary nodules on X-rays obtained for non-respiratory conditions." }, { "kind": "case report", "citation": "Koksal D et al. (2026). Cureus 18(3):e104881 (second quotation).", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "Computed tomography imaging and biopsy confirmed early-stage lung cancer in all five cases." }, { "kind": "case report", "citation": "Koksal D et al. (2026). Cureus 18(3):e104881 (third quotation, Discussion).", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "Without the assistance of AI, these cases would likely have been missed or delayed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0080-source-0001", "AIBD-0080-source-0002", "AIBD-0080-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Koksal D, Govindarajan A, Baykan A, Durhan G, Sarinc S, Akpinar MG, Demirkazik F, Mathivanan KM, Vignesh P, Shivabasappa S (2026). A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers? Cureus 18(3):e104881.", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "We present a case series of five individuals in whom AI-enabled chest X-ray (qXR, Qure.ai, Mumbai, India) flagged suspicious pulmonary nodules on X-rays obtained for non-respiratory conditions." }, { "kind": "case report", "citation": "Koksal D et al. (2026). Cureus 18(3):e104881 (second quotation).", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "Computed tomography imaging and biopsy confirmed early-stage lung cancer in all five cases." }, { "kind": "case report", "citation": "Koksal D et al. (2026). Cureus 18(3):e104881 (third quotation, Discussion).", "title": "A Case Series From a Multicentric Study: Can Artificial Intelligence (AI)-Enabled Chest X-Ray Assist in the Incidental Detection of Early-Stage Lung Cancers?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13058629/", "date": "2026-03-09", "written_by": "deployer", "quote": "Without the assistance of AI, these cases would likely have been missed or delayed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "qXR flagged nodules on X-rays done for other reasons; CT/biopsy confirmed early-stage lung cancer in five adults; four had surgery.", "account": "CREATE (NCT05817110) was a prospective multicenter study. The deep-learning software qXR (Qure.ai) was adopted for routine use on all chest X-rays across participating centers from April 2023 to December 2024. Five cases were found through the AI pathway. The paper names neither the centers nor their cities. Its clinical authors are at Hacettepe University (Ankara, Turkey) and with Aarthi Scans and Sri Ramachandra Medical College and Hospital (Chennai, India). The March 2026 Cureus report describes five individuals, none with respiratory symptoms. In each, qXR flagged suspicious pulmonary nodules on X-rays taken for non-respiratory reasons. They were a 57-year-old man screened before anti-TNF therapy for ulcerative colitis and a 64-year-old man with fever. Also a 65-year-old woman at a smoking-cessation consultation and two men aged 35 and 75 at annual health checks. Computed tomography (CT) and biopsy confirmed early-stage lung cancer in all five. Four underwent curative surgery, two with adjuvant chemotherapy, and one chose chemotherapy alone. Whether the original X-ray reports noted the nodules is not stated." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "qXR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Qure.ai" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "qXR flags suspicious nodules on chest X-rays taken for non-respiratory reasons; five adults without respiratory symptoms diagnosed with early-stage lung cancer", "headline": "qXR nodule flags lead to five early-stage lung cancer diagnoses" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b5fdd5f9bc5403c96cfb196d005f0c7d3bd14ee77d1fa5a4c61a4c4666a8a279" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "CREATE (NCT05817110) was a prospective multicenter study. The deep-learning software qXR (Qure.ai) was adopted for routine use on all chest X-rays across participating centers from April 2023 to December 2024. Five cases were found through the AI pathway. The paper names neither the centers nor their cities. Its clinical authors are at Hacettepe University (Ankara, Turkey) and with Aarthi Scans and Sri Ramachandra Medical College and Hospital (Chennai, India). The March 2026 Cureus report describes five individuals, none with respiratory symptoms. In each, qXR flagged suspicious pulmonary nodules on X-rays taken for non-respiratory reasons. They were a 57-year-old man screened before anti-TNF therapy for ulcerative colitis and a 64-year-old man with fever. Also a 65-year-old woman at a smoking-cessation consultation and two men aged 35 and 75 at annual health checks. Computed tomography (CT) and biopsy confirmed early-stage lung cancer in all five. Four underwent curative surgery, two with adjuvant chemotherapy, and one chose chemotherapy alone. Whether the original X-ray reports noted the nodules is not stated.", "replication": { "produced_by": [ "qXR running on routine chest X-rays ordered for non-respiratory indications", "A pathway from AI flag to CT or PET-CT and biopsy" ], "must_hold": [ "Clinicians act on AI flags on films ordered for unrelated reasons", "Tissue confirmation before treatment" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0297", "title": "Nelli audio-video AI seizure monitor records 247 nocturnal events missed by carers among 15 people with intellectual disability in Cornwall; Danish validation detected all 11 tonic-clonic seizures", "summary": "Cornwall NHS evaluation (15 people who could not tolerate EEG): Nelli flagged 707 possible seizure events, 247 unheard or unrecognised by carers; Danish phase-3 validation sensitivity 93.7%.", "date_observed": "2023-04-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Nelli, made by Neuro Event Labs of Tampere, Finland, is a camera-and-microphone unit. Computer vision and what its validators call an artificial-intelligence-based algorithm flag nocturnal motor seizures from its signals. A phase-3 validation at the Danish Epilepsy Center and Aarhus University Hospital had 191 participants, recruited 14 October 2019 to 18 June 2021. It had 4,183 night-time hours, analyzed in real time against video electroencephalography (EEG). Armand Larsen, Beniczky and colleagues, with two Neuro Event Labs co-authors, reported 93.7% sensitivity for major motor seizures (Brain and Behavior, 8 August 2022). All 11 tonic-clonic and four of five hypermotor seizures were detected. False detections were 0.16 per hour, device deficiency 10.5% of the time, and sensitivity for minor motor seizures only 8.3%. Lennard, Shankar and colleagues of the National Health Service (NHS) trust Cornwall Partnership NHS Foundation Trust then evaluated Nelli in the community. The 15 participants had intellectual disability and drug-resistant epilepsy and could not tolerate routine or ambulatory EEG. The report appeared in Epilepsy & Behavior Reports on 23 April 2023. The source gives no study dates. Nelli recorded 707 possible seizure events in 14 people, 247 of them unheard or unrecognized by carers. One person had half of possible events missed by night staff. Carers logged 165 “restless” or “seizure behavior” episodes that Nelli did not deem seizures. Acceptability was 93%. The authors conclude Nelli “allowed for improved communication and care planning”. A single-center feasibility study in Dravet and Lennox-Gastaut syndromes (Wilms et al., Epilepsia, online 9 October 2025; abstract read) ran four weeks of home monitoring. It detected 368 seizures with 97.8% accuracy, while only 26.1% were logged in diaries. No individual's changed outcome is documented in any cited source.", "category": "general benefit", "unexpected": false, "purpose": "Built to detect nocturnal major motor seizures from audio-video so that staff can intervene and clinicians can see events patients cannot report. The unrecognized events it surfaced are that purpose.", "system": "Nelli audio-video seizure monitoring system (computer vision and AI-based event detection)", "model_version": null, "developer": "Neuro Event Labs, Tampere, Finland", "deployer": "Cornwall Partnership NHS Foundation Trust (community evaluation); Danish Epilepsy Center, Dianalund, and Aarhus University Hospital (validation)", "location": "Cornwall, United Kingdom; Dianalund and Aarhus, Denmark", "domain": "Healthcare (epilepsy; nocturnal seizure monitoring)", "segment": "Residential and institutional seizure monitoring for people with intellectual disability", "benefit_type": "Improved Physical Health", "taxonomy_note": "The gain is seizure information for people with intellectual disability who could not tolerate EEG, which also reads as accessibility.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Carers reported peace of mind (13 of 14). Clinicians gained event counts for people who cannot report seizures. No cited source documents a treatment change or injury avoided for a named individual." }, { "group": "organizational", "depth": null, "reason": "The Cornwall authors describe improved care planning and carer training. No measured change in staffing, response times or incidents is reported." } ], "ai_role": { "status": "assessed", "statement": "The system flagged motor events that night staff and carers had not noticed (247 of 707 in Cornwall). In the Danish validation it detected every tonic-clonic seizure in real time. Clinicians still reviewed sampled clips to confirm events. Sensitivity for minor motor seizures was 8.3%. One Cornwall participant's unit was removed to prevent injury and equipment damage. The validation paper is co-authored by two vendor employees. The Cornwall evaluation is independent of the maker." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Lennard S, Newman R, McLean B, Jory C, Cox D, Young C, Corson E, Shankar R (2023). Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera. Epilepsy & Behavior Reports 22:100603 (PMC10160340).", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli recorded 707 possible seizure events across the 14 PwID of which 247 were either not heard or not recognised by carers." }, { "kind": "peer-reviewed study", "citation": "Lennard et al. (2023), Epilepsy Behav Rep 22:100603, abstract.", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli allowed for improved communication and care planning in a hitherto difficult to investigate population." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen S, Terney D, Østerkjerhuus T, Vinding Merinder T, Annala K, Knight A, Beniczky S (2022). Automated detection of nocturnal motor seizures using an audio-video system. Brain and Behavior 12(9):e2737 (PMC9480955). Annala and Knight are Neuro Event Labs employees and shareholders.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "The system detected all 11 TCS and four out of five (80%) hypermotor seizures." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen et al. (2022), Brain Behav 12(9):e2737, methods.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "we assessed the performance of automated detection of nocturnal motor seizures using audio‐video streaming, computer vision and an artificial intelligence‐based algorithm (Nelli)" }, { "kind": "peer-reviewed study", "citation": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2025). Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study. Epilepsia, online 9 October 2025; doi:10.1111/epi.18640 (PMID 41066202; PMC12893256). Neuro Event Labs co-authors.", "title": "Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study", "url": "https://europepmc.org/article/MED/41066202", "date": "2025-10-09", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A camera and microphone unit streaming to a server where computer-vision and AI algorithms flag motor events", "Night-time use for people with suspected nocturnal seizures who could not tolerate EEG, with family or carer consent", "Clinician review of flagged clips (the Cornwall paper says 8–9% of the recording is sampled by an epilepsy expert)" ], "must_hold": [ "Device deficiency kept low (10.5% of monitored time in the Danish validation)", "Staff available at night to act on alarms, the setting the validators say the system is suited to", "The target is major motor seizures; minor motor seizures were detected at 8.3% sensitivity" ], "echoes": [ { "date": "2025-10-09", "setting": "Single-center feasibility study, 20 patients with Dravet or Lennox-Gastaut syndrome, four weeks of home monitoring in bed, August 2023 to March 2024", "model_version": null, "outcome": "recurred", "source": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2026) Epilepsia 67(1):164-174, doi:10.1111/epi.18640 (abstract: 368 seizures detected with 97.8% accuracy; 'only 26.1% of the seizures were documented' in diaries; vendor co-authors)" } ] }, "paired_incident": null, "headline": "Nelli flags 247 nocturnal seizure events missed by carers", "metric": "Nelli flagged 707 possible seizure events, 247 unheard or unrecognised by carers", "comparator": { "against": "carers' hearing or recognition of night-time events in the same people", "before": "247 were not heard or recognised by carers", "after": "Nelli recorded 707 possible seizure events across the study cohort", "basis": "measured", "quote": "Nelli recorded 707 possible seizure events across the study cohort of which 247 were not heard or recognised by carers. Carers recorded 165 episodes of ‘restless’ or “seizure behaviour” which the Nelli did not deem to be seizures.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/" }, "later": { "status": "persisted", "date": "2025-10-09", "note": "A later single-center feasibility study in Dravet and Lennox-Gastaut syndromes, with vendor co-authors, reported that Nelli detected 368 seizures at 97.8% accuracy over four weeks of home monitoring while diaries documented only 26.1% of seizures.", "quote": "Nelli demonstrated high sensitivity and classification accuracy for detecting and categorizing seizures in bed in patients with DS and LGS, outperforming seizure diaries and providing a reliable tool for seizure monitoring in home settings.", "url": "https://europepmc.org/article/MED/41066202" }, "value": null, "developer_country": "Finland", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/; https://europepmc.org/article/MED/41066202", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://neuroeventlabs.com/contact/; https://directory.spineservices.nhs.uk/ORD/2-0-0/organisations/RJ8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: two peer-reviewed studies from the makers and the deployer's peer-reviewed study. 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In the Danish validation it detected every tonic-clonic seizure in real time. Clinicians still reviewed sampled clips to confirm events. Sensitivity for minor motor seizures was 8.3%. One Cornwall participant's unit was removed to prevent injury and equipment damage. The validation paper is co-authored by two vendor employees. The Cornwall evaluation is independent of the maker." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The system flagged motor events that night staff and carers had not noticed (247 of 707 in Cornwall). In the Danish validation it detected every tonic-clonic seizure in real time. Clinicians still reviewed sampled clips to confirm events. Sensitivity for minor motor seizures was 8.3%. One Cornwall participant's unit was removed to prevent injury and equipment damage. The validation paper is co-authored by two vendor employees. 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sensitivity and classification accuracy for detecting and categorizing seizures in bed in patients with DS and LGS, outperforming seizure diaries and providing a reliable tool for seizure monitoring in home settings.", "url": "https://europepmc.org/article/MED/41066202" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0297" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The gain is seizure information for people with intellectual disability who could not tolerate EEG, which also reads as accessibility." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nelli, made by Neuro Event Labs of Tampere, Finland, is a camera-and-microphone unit. Computer vision and what its validators call an artificial-intelligence-based algorithm flag nocturnal motor seizures from its signals. A phase-3 validation at the Danish Epilepsy Center and Aarhus University Hospital had 191 participants, recruited 14 October 2019 to 18 June 2021. It had 4,183 night-time hours, analyzed in real time against video electroencephalography (EEG). Armand Larsen, Beniczky and colleagues, with two Neuro Event Labs co-authors, reported 93.7% sensitivity for major motor seizures (Brain and Behavior, 8 August 2022). All 11 tonic-clonic and four of five hypermotor seizures were detected. False detections were 0.16 per hour, device deficiency 10.5% of the time, and sensitivity for minor motor seizures only 8.3%. Lennard, Shankar and colleagues of the National Health Service (NHS) trust Cornwall Partnership NHS Foundation Trust then evaluated Nelli in the community. The 15 participants had intellectual disability and drug-resistant epilepsy and could not tolerate routine or ambulatory EEG. The report appeared in Epilepsy & Behavior Reports on 23 April 2023. The source gives no study dates. Nelli recorded 707 possible seizure events in 14 people, 247 of them unheard or unrecognized by carers. One person had half of possible events missed by night staff. Carers logged 165 “restless” or “seizure behavior” episodes that Nelli did not deem seizures. Acceptability was 93%. The authors conclude Nelli “allowed for improved communication and care planning”. A single-center feasibility study in Dravet and Lennox-Gastaut syndromes (Wilms et al., Epilepsia, online 9 October 2025; abstract read) ran four weeks of home monitoring. It detected 368 seizures with 97.8% accuracy, while only 26.1% were logged in diaries. No individual's changed outcome is documented in any cited source.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Carers reported peace of mind (13 of 14). Clinicians gained event counts for people who cannot report seizures. No cited source documents a treatment change or injury avoided for a named individual." }, { "group": "organizational", "reason": "The Cornwall authors describe improved care planning and carer training. No measured change in staffing, response times or incidents is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect nocturnal major motor seizures from audio-video so that staff can intervene and clinicians can see events patients cannot report. The unrecognized events it surfaced are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cornwall, United Kingdom; Dianalund and Aarhus, Denmark", "developer_country": "Finland", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect nocturnal major motor seizures from audio-video so that staff can intervene and clinicians can see events patients cannot report. The unrecognized events it surfaced are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-04-23", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/; https://europepmc.org/article/MED/41066202", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://neuroeventlabs.com/contact/; https://directory.spineservices.nhs.uk/ORD/2-0-0/organisations/RJ8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A camera and microphone unit streaming to a server where computer-vision and AI algorithms flag motor events", "Night-time use for people with suspected nocturnal seizures who could not tolerate EEG, with family or carer consent", "Clinician review of flagged clips (the Cornwall paper says 8–9% of the recording is sampled by an epilepsy expert)" ], "must_hold": [ "Device deficiency kept low (10.5% of monitored time in the Danish validation)", "Staff available at night to act on alarms, the setting the validators say the system is suited to", "The target is major motor seizures; minor motor seizures were detected at 8.3% sensitivity" ], "echoes": [ { "date": "2025-10-09", "setting": "Single-center feasibility study, 20 patients with Dravet or Lennox-Gastaut syndrome, four weeks of home monitoring in bed, August 2023 to March 2024", "outcome": "recurred", "source": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2026) Epilepsia 67(1):164-174, doi:10.1111/epi.18640 (abstract: 368 seizures detected with 97.8% accuracy; 'only 26.1% of the seizures were documented' in diaries; vendor co-authors)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A camera and microphone unit streaming to a server where computer-vision and AI algorithms flag motor events", "Night-time use for people with suspected nocturnal seizures who could not tolerate EEG, with family or carer consent", "Clinician review of flagged clips (the Cornwall paper says 8–9% of the recording is sampled by an epilepsy expert)" ], "must_hold": [ "Device deficiency kept low (10.5% of monitored time in the Danish validation)", "Staff available at night to act on alarms, the setting the validators say the system is suited to", "The target is major motor seizures; 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it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/; https://europepmc.org/article/MED/41066202", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://neuroeventlabs.com/contact/; https://directory.spineservices.nhs.uk/ORD/2-0-0/organisations/RJ8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (epilepsy; nocturnal seizure monitoring)", "segment": "Residential and institutional seizure monitoring for people with intellectual disability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Lennard S, Newman R, McLean B, Jory C, Cox D, Young C, Corson E, Shankar R (2023). Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera. Epilepsy & Behavior Reports 22:100603 (PMC10160340).", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli recorded 707 possible seizure events across the 14 PwID of which 247 were either not heard or not recognised by carers." }, { "kind": "peer-reviewed study", "citation": "Lennard et al. (2023), Epilepsy Behav Rep 22:100603, abstract.", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli allowed for improved communication and care planning in a hitherto difficult to investigate population." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen S, Terney D, Østerkjerhuus T, Vinding Merinder T, Annala K, Knight A, Beniczky S (2022). Automated detection of nocturnal motor seizures using an audio-video system. Brain and Behavior 12(9):e2737 (PMC9480955). Annala and Knight are Neuro Event Labs employees and shareholders.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "The system detected all 11 TCS and four out of five (80%) hypermotor seizures." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen et al. (2022), Brain Behav 12(9):e2737, methods.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "we assessed the performance of automated detection of nocturnal motor seizures using audio‐video streaming, computer vision and an artificial intelligence‐based algorithm (Nelli)" }, { "kind": "peer-reviewed study", "citation": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2025). Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study. Epilepsia, online 9 October 2025; doi:10.1111/epi.18640 (PMID 41066202; PMC12893256). Neuro Event Labs co-authors.", "title": "Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study", "url": "https://europepmc.org/article/MED/41066202", "date": "2025-10-09", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0297-source-0001", "AIBD-0297-source-0002", "AIBD-0297-source-0003", "AIBD-0297-source-0004", "AIBD-0297-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Lennard S, Newman R, McLean B, Jory C, Cox D, Young C, Corson E, Shankar R (2023). Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera. Epilepsy & Behavior Reports 22:100603 (PMC10160340).", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli recorded 707 possible seizure events across the 14 PwID of which 247 were either not heard or not recognised by carers." }, { "kind": "peer-reviewed study", "citation": "Lennard et al. (2023), Epilepsy Behav Rep 22:100603, abstract.", "title": "Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10160340/", "date": "2023-04-23", "written_by": "deployer", "quote": "Nelli allowed for improved communication and care planning in a hitherto difficult to investigate population." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen S, Terney D, Østerkjerhuus T, Vinding Merinder T, Annala K, Knight A, Beniczky S (2022). Automated detection of nocturnal motor seizures using an audio-video system. Brain and Behavior 12(9):e2737 (PMC9480955). Annala and Knight are Neuro Event Labs employees and shareholders.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "The system detected all 11 TCS and four out of five (80%) hypermotor seizures." }, { "kind": "peer-reviewed study", "citation": "Armand Larsen et al. (2022), Brain Behav 12(9):e2737, methods.", "title": "Automated detection of nocturnal motor seizures using an audio-video system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9480955/", "date": "2022-08-08", "written_by": "makers", "quote": "we assessed the performance of automated detection of nocturnal motor seizures using audio‐video streaming, computer vision and an artificial intelligence‐based algorithm (Nelli)" }, { "kind": "peer-reviewed study", "citation": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2025). Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study. Epilepsia, online 9 October 2025; doi:10.1111/epi.18640 (PMID 41066202; PMC12893256). Neuro Event Labs co-authors.", "title": "Seizure classification using a multimodal seizure monitoring system (Nelli) in Dravet and Lennox-Gastaut syndromes: A non-randomized, single-center feasibility study", "url": "https://europepmc.org/article/MED/41066202", "date": "2025-10-09", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Cornwall NHS evaluation (15 people who could not tolerate EEG): Nelli flagged 707 possible seizure events, 247 unheard or unrecognised by carers; Danish phase-3 validation sensitivity 93.7%.", "account": "Nelli, made by Neuro Event Labs of Tampere, Finland, is a camera-and-microphone unit. Computer vision and what its validators call an artificial-intelligence-based algorithm flag nocturnal motor seizures from its signals. A phase-3 validation at the Danish Epilepsy Center and Aarhus University Hospital had 191 participants, recruited 14 October 2019 to 18 June 2021. It had 4,183 night-time hours, analyzed in real time against video electroencephalography (EEG). Armand Larsen, Beniczky and colleagues, with two Neuro Event Labs co-authors, reported 93.7% sensitivity for major motor seizures (Brain and Behavior, 8 August 2022). All 11 tonic-clonic and four of five hypermotor seizures were detected. False detections were 0.16 per hour, device deficiency 10.5% of the time, and sensitivity for minor motor seizures only 8.3%. Lennard, Shankar and colleagues of the National Health Service (NHS) trust Cornwall Partnership NHS Foundation Trust then evaluated Nelli in the community. The 15 participants had intellectual disability and drug-resistant epilepsy and could not tolerate routine or ambulatory EEG. The report appeared in Epilepsy & Behavior Reports on 23 April 2023. The source gives no study dates. Nelli recorded 707 possible seizure events in 14 people, 247 of them unheard or unrecognized by carers. One person had half of possible events missed by night staff. Carers logged 165 “restless” or “seizure behavior” episodes that Nelli did not deem seizures. Acceptability was 93%. The authors conclude Nelli “allowed for improved communication and care planning”. A single-center feasibility study in Dravet and Lennox-Gastaut syndromes (Wilms et al., Epilepsia, online 9 October 2025; abstract read) ran four weeks of home monitoring. It detected 368 seizures with 97.8% accuracy, while only 26.1% were logged in diaries. No individual's changed outcome is documented in any cited source." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Nelli audio-video seizure monitoring system (computer vision and AI-based event detection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Neuro Event Labs, Tampere, Finland" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Nelli audio-video AI seizure monitor records 247 nocturnal events missed by carers among 15 people with intellectual disability in Cornwall; Danish validation detected all 11 tonic-clonic seizures", "headline": "Nelli flags 247 nocturnal seizure events missed by carers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "916bef6a0a2af27bda417c248c50a5f12f401749fda46099943762426b41a002" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nelli, made by Neuro Event Labs of Tampere, Finland, is a camera-and-microphone unit. Computer vision and what its validators call an artificial-intelligence-based algorithm flag nocturnal motor seizures from its signals. A phase-3 validation at the Danish Epilepsy Center and Aarhus University Hospital had 191 participants, recruited 14 October 2019 to 18 June 2021. It had 4,183 night-time hours, analyzed in real time against video electroencephalography (EEG). Armand Larsen, Beniczky and colleagues, with two Neuro Event Labs co-authors, reported 93.7% sensitivity for major motor seizures (Brain and Behavior, 8 August 2022). All 11 tonic-clonic and four of five hypermotor seizures were detected. False detections were 0.16 per hour, device deficiency 10.5% of the time, and sensitivity for minor motor seizures only 8.3%. Lennard, Shankar and colleagues of the National Health Service (NHS) trust Cornwall Partnership NHS Foundation Trust then evaluated Nelli in the community. The 15 participants had intellectual disability and drug-resistant epilepsy and could not tolerate routine or ambulatory EEG. The report appeared in Epilepsy & Behavior Reports on 23 April 2023. The source gives no study dates. Nelli recorded 707 possible seizure events in 14 people, 247 of them unheard or unrecognized by carers. One person had half of possible events missed by night staff. Carers logged 165 “restless” or “seizure behavior” episodes that Nelli did not deem seizures. Acceptability was 93%. The authors conclude Nelli “allowed for improved communication and care planning”. A single-center feasibility study in Dravet and Lennox-Gastaut syndromes (Wilms et al., Epilepsia, online 9 October 2025; abstract read) ran four weeks of home monitoring. It detected 368 seizures with 97.8% accuracy, while only 26.1% were logged in diaries. No individual's changed outcome is documented in any cited source.", "replication": { "produced_by": [ "A camera and microphone unit streaming to a server where computer-vision and AI algorithms flag motor events", "Night-time use for people with suspected nocturnal seizures who could not tolerate EEG, with family or carer consent", "Clinician review of flagged clips (the Cornwall paper says 8–9% of the recording is sampled by an epilepsy expert)" ], "must_hold": [ "Device deficiency kept low (10.5% of monitored time in the Danish validation)", "Staff available at night to act on alarms, the setting the validators say the system is suited to", "The target is major motor seizures; minor motor seizures were detected at 8.3% sensitivity" ], "echoes": [ { "date": "2025-10-09", "setting": "Single-center feasibility study, 20 patients with Dravet or Lennox-Gastaut syndrome, four weeks of home monitoring in bed, August 2023 to March 2024", "outcome": "recurred", "source": "Wilms LK, Lossius MI, Annala K, Abdel-Khalik J, Fanter L, Elomaa K, Peltola J (2026) Epilepsia 67(1):164-174, doi:10.1111/epi.18640 (abstract: 368 seizures detected with 97.8% accuracy; 'only 26.1% of the seizures were documented' in diaries; vendor co-authors)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0277", "title": "Neural machine translation renders Akkadian cuneiform into English at BLEU4 36.5–37.5", "summary": "Tel Aviv and Ariel University researchers trained CNN-based models translating Akkadian from cuneiform glyphs or transliteration to English, best on short sentences; a capability demonstration only.", "date_observed": "2023-05-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Gutherz, Gordin, Saenz, Levy and Berant (PNAS Nexus, 2 May 2023) trained neural machine translation models to render Akkadian into English. One works directly from cuneiform Unicode glyphs (C2E), one from transliteration (T2E). They report BLEU4 scores of 36.52 and 37.47, improvements of 9.43 and 13.96 over a translation-memory baseline. Results were best on sentences of about 118 characters or fewer. They propose a human-in-the-loop system in which scholars correct outputs. No passage read and accepted by scholars is named. The authors report hallucinations in longer or fragmented texts. The work stands as a capability demonstration. The group's 2020 PLoS ONE paper (Akkademia) reported up to 97% accuracy for automatic transliteration and segmentation.", "category": "general benefit", "unexpected": false, "purpose": "Automatically translate Akkadian cuneiform texts into English to assist scholars", "system": "Akkadian-to-English neural machine translation (C2E and T2E models)", "model_version": "Fairseq convolutional model", "developer": "Tel Aviv University (Gutherz, Levy, Berant) and Ariel University (Gordin)", "deployer": "None (research demonstration)", "location": "Israel", "domain": "Digital humanities; Assyriology", "segment": "Assyriologists and interested lay readers", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary." }, { "group": "organizational", "depth": null, "reason": "No deployment reported." }, { "group": "societal", "depth": null, "reason": "No attributable event." } ], "ai_role": { "status": "assessed", "statement": "The models' translation quality is reported by their developers in a peer-reviewed paper. No scholar-accepted translation of a specific text is attributed to them. The authors note limits on longer and fragmented texts." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Gutherz G, Gordin S, Saenz L, Levy O, Berant J. PNAS Nexus 2(5):pgad096 (2023)", "title": "Translating Akkadian to English with neural machine translation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10153418/", "date": "2023-05-02", "written_by": "makers", "quote": "we get 36.52 and 37.47 Best Bilingual Evaluation Understudy 4 (BLEU4) scores for C2E and T2E, respectively" }, { "kind": "peer-reviewed study", "citation": "Gordin S, Gutherz G, Elazary A, et al. PLoS ONE 15(10):e0240511 (2020)", "title": "Reading Akkadian cuneiform using natural language processing", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7592802/", "date": "2020-10-28", "written_by": "makers", "quote": "with an accuracy reaching up to 97% for automatically transliterating and segmenting standard Unicode cuneiform glyphs into words." }, { "kind": "preprint", "citation": "Wang Z (14 May 2026). TabletCraft: Bridging a 4,000-Year Cultural Gap with Bidirectional Akkadian NMT and Cuneiform Rendering. arXiv:2608.02609.", "title": "TabletCraft: Bridging a 4,000-Year Cultural Gap with Bidirectional Akkadian NMT and Cuneiform Rendering", "url": "https://arxiv.org/abs/2608.02609", "date": "2026-05-14", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Convolutional neural network translation models trained on digitized Akkadian-English pairs" ], "must_hold": [ "Human scholars correct outputs, especially for long or fragmentary texts" ], "echoes": [ { "date": "2020-10-28", "setting": "Earlier Akkademia transliteration and segmentation models by the same group", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC7592802/" } ] }, "paired_incident": null, "headline": "Tel Aviv and Ariel models translate Akkadian at BLEU4 36.5–37.5", "metric": "BLEU4 scores of 36.52 and 37.47", "comparator": { "against": "a translation memory baseline on the same test data", "before": "the translation memory baseline achieved a BLEU4 score of 23.51", "after": "36.52 and 37.47 Best Bilingual Evaluation Understudy 4 (BLEU4) scores for C2E and T2E, respectively", "basis": "measured", "quote": "we get 36.52 and 37.47 Best Bilingual Evaluation Understudy 4 (BLEU4) scores for C2E and T2E, respectively. 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In the early hours of Thursday 11 May 2023 it led to 30 search warrants across Maipú, Pudahuel, Cerro Navia and other comunas. There were 17 detentions, ten linked to “encerronas” (robbery with intimidation or violence) whose perpetrators posted their robberies on TikTok. The release says they were identified through the software Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial). It is an AI model developed by several universities and incorporated into the Ministerio Público in March 2023. It proposes probable participants from prosecution and police records for prosecutors and police to work up. The Noveno Juzgado de Garantía accredited the eight robberies. Four adults went to preventive detention and four adolescents remained in provisional internment. T13 quotes Fiscal Nacional Ángel Valencia saying the algorithm accelerates criminal analysis. It reports that after three members were arrested the AI searched their links to raise persons of interest later identified by victims. The OECD AI Incidents Monitor records the case.", "category": "benefit created", "unexpected": false, "purpose": "Build networks of links among people with criminal records to propose probable members of a group tied to a specific crime. This reduces the case files prosecutors must review.", "system": "Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial)", "model_version": null, "developer": "Several universities (not named in the sources)", "deployer": "Ministerio Público de Chile (Fiscalía Regional Occidente, SACFI) with the Policía de Investigaciones", "location": null, "domain": "Criminal investigation / organized robbery", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 3, "reason": "A gang responsible for at least eight accredited violent robberies was detained and formalized, with four adults in preventive detention, per the prosecutor's office." }, { "group": "organizational", "depth": 2, "reason": "Prosecutors state the tool replaces review of hundreds of case files with a short list of proposed links." } ], "ai_role": { "status": "assessed", "statement": "The deploying public body credits the AI with the identification of probable participants, complemented by prosecutors' and police work and victim identification. T13 adds the mechanism (link search from three arrested members). No court document or independent evaluation of the model's accuracy is among the sources. The Fiscalía is both the source and the beneficiary." }, "evidence": [ { "kind": "press release", "citation": "Fiscalía de Chile, noticias regionales, 17 May 2023", "title": "“Operación Influencer”: Uso de IA permitió desarticular a banda de adolescentes que efectuó al menos 8 “encerronas” en Zona Occidente", "url": "https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "date": "2023-05-17", "written_by": "deployer", "quote": "Su identificación fue realizada gracias al uso del software denominado Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial), que es un modelo de IA" }, { "kind": "news report", "citation": "T13 (Teletrece), 12 May 2023", "title": "\"Operación Influencer\": Cómo la Inteligencia Artificial fue clave en la detención de banda dedicada a las encerronas", "url": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023", "date": "2023-05-12", "written_by": "independent", "quote": "El algoritmo acelera el análisis criminal." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2023-05-12-99fe", "title": "AI System Enables Major Criminal Gang Bust in Chile's 'Operación Influencer'", "url": "https://oecd.ai/en/incidents/2023-05-12-99fe", "date": "2023-05-12", "written_by": "independent", "quote": "Chilean authorities used an AI system to analyze criminal data and detect networks, leading to the arrest of 10 individuals involved in violent carjackings and related crimes." } ], "replication": { "produced_by": [ "Linked prosecution, prison and police records (SAF, Gendarmería, Carabineros)", "A few confirmed arrests seeding a link search", "Victim identification to confirm proposed persons of interest" ], "must_hold": [ "Suspects must already appear in the records the model draws on", "Human verification before charging", "Legal basis for cross-agency data linkage" ], "echoes": [] }, "paired_incident": null, "headline": "Fiscal Heredia may have identified a 10-member robbery gang", "metric": "detained a gang of 10 aged 15–22 behind eight accredited violent robberies", "comparator": { "against": "prosecutors manually analyzing hundreds of case folders to find links", "before": "analizar cientos de carpetas para dar con potenciales vínculos", "after": "el sistema realiza un filtro y propone un número acotado de ellos", "basis": "assumed", "quote": "El algoritmo acelera el análisis criminal. Con él, las y los fiscales ya no tendrán que analizar cientos de carpetas para dar con potenciales vínculos, ya que el sistema realiza un filtro y propone un número acotado de ellos, reduciendo el volumen y la complejidad de la búsqueda", "url": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023" }, "later": { "status": "litigated", "date": "2023-05-17", "note": "The Fiscalía's release of 17 May 2023 reports that the court accredited the eight robberies, placed four adults in preventive detention and kept four adolescents in provisional internment.", "quote": "El Tribunal dio por acreditado los 8 robos con modalidad encerronas.", "url": "https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de" }, "value": null, "developer_country": null, "deployer_country": "Chile", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023; https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.fiscaliadechile.cl/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the deployer's press release. 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"family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "litigated", "date": "2023-05-17", "note": "The Fiscalía's release of 17 May 2023 reports that the court accredited the eight robberies, placed four adults in preventive detention and kept four adolescents in provisional internment.", "quote": "El Tribunal dio por acreditado los 8 robos con modalidad encerronas.", "url": "https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0233" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Fiscalía de Chile's regional news release describes a joint investigation by Focos Occidente and the PDI's Brigada de Investigación Criminal. In the early hours of Thursday 11 May 2023 it led to 30 search warrants across Maipú, Pudahuel, Cerro Navia and other comunas. There were 17 detentions, ten linked to “encerronas” (robbery with intimidation or violence) whose perpetrators posted their robberies on TikTok. The release says they were identified through the software Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial). It is an AI model developed by several universities and incorporated into the Ministerio Público in March 2023. It proposes probable participants from prosecution and police records for prosecutors and police to work up. The Noveno Juzgado de Garantía accredited the eight robberies. Four adults went to preventive detention and four adolescents remained in provisional internment. T13 quotes Fiscal Nacional Ángel Valencia saying the algorithm accelerates criminal analysis. It reports that after three members were arrested the AI searched their links to raise persons of interest later identified by victims. The OECD AI Incidents Monitor records the case.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "A gang responsible for at least eight accredited violent robberies was detained and formalized, with four adults in preventive detention, per the prosecutor's office." }, { "group": "organizational", "depth": 2, "reason": "Prosecutors state the tool replaces review of hundreds of case files with a short list of proposed links." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Build networks of links among people with criminal records to propose probable members of a group tied to a specific crime. This reduces the case files prosecutors must review." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer_country": "Chile" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Build networks of links among people with criminal records to propose probable members of a group tied to a specific crime. This reduces the case files prosecutors must review." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-05-11", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023; https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.fiscaliadechile.cl/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Linked prosecution, prison and police records (SAF, Gendarmería, Carabineros)", "A few confirmed arrests seeding a link search", "Victim identification to confirm proposed persons of interest" ], "must_hold": [ "Suspects must already appear in the records the model draws on", "Human verification before charging", "Legal basis for cross-agency data linkage" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023; https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.fiscaliadechile.cl/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Criminal investigation / organized robbery", "segment": "Government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Fiscalía de Chile, noticias regionales, 17 May 2023", "title": "“Operación Influencer”: Uso de IA permitió desarticular a banda de adolescentes que efectuó al menos 8 “encerronas” en Zona Occidente", "url": "https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "date": "2023-05-17", "written_by": "deployer", "quote": "Su identificación fue realizada gracias al uso del software denominado Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial), que es un modelo de IA" }, { "kind": "news report", "citation": "T13 (Teletrece), 12 May 2023", "title": "\"Operación Influencer\": Cómo la Inteligencia Artificial fue clave en la detención de banda dedicada a las encerronas", "url": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023", "date": "2023-05-12", "written_by": "independent", "quote": "El algoritmo acelera el análisis criminal." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2023-05-12-99fe", "title": "AI System Enables Major Criminal Gang Bust in Chile's 'Operación Influencer'", "url": "https://oecd.ai/en/incidents/2023-05-12-99fe", "date": "2023-05-12", "written_by": "independent", "quote": "Chilean authorities used an AI system to analyze criminal data and detect networks, leading to the arrest of 10 individuals involved in violent carjackings and related crimes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0233-source-0001", "AIBD-0233-source-0002", "AIBD-0233-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Fiscalía de Chile, noticias regionales, 17 May 2023", "title": "“Operación Influencer”: Uso de IA permitió desarticular a banda de adolescentes que efectuó al menos 8 “encerronas” en Zona Occidente", "url": "https://www.fiscaliadechile.cl/actualidad/noticias/regionales/operacion-influencer-uso-de-ia-permitio-desarticular-banda-de", "date": "2023-05-17", "written_by": "deployer", "quote": "Su identificación fue realizada gracias al uso del software denominado Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial), que es un modelo de IA" }, { "kind": "news report", "citation": "T13 (Teletrece), 12 May 2023", "title": "\"Operación Influencer\": Cómo la Inteligencia Artificial fue clave en la detención de banda dedicada a las encerronas", "url": "https://www.t13.cl/noticia/nacional/operacion-influencer-inteligencia-artificial-clave-detencion-banda-encerronas-12-5-2023", "date": "2023-05-12", "written_by": "independent", "quote": "El algoritmo acelera el análisis criminal." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2023-05-12-99fe", "title": "AI System Enables Major Criminal Gang Bust in Chile's 'Operación Influencer'", "url": "https://oecd.ai/en/incidents/2023-05-12-99fe", "date": "2023-05-12", "written_by": "independent", "quote": "Chilean authorities used an AI system to analyze criminal data and detect networks, leading to the arrest of 10 individuals involved in violent carjackings and related crimes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "In Operación Influencer (11 May 2023) prosecutors and PDI detained a gang of 10 aged 15–22 behind eight accredited violent robberies; the Fiscalía credits the university-built AI model Fiscal Heredia.", "account": "The Fiscalía de Chile's regional news release describes a joint investigation by Focos Occidente and the PDI's Brigada de Investigación Criminal. In the early hours of Thursday 11 May 2023 it led to 30 search warrants across Maipú, Pudahuel, Cerro Navia and other comunas. There were 17 detentions, ten linked to “encerronas” (robbery with intimidation or violence) whose perpetrators posted their robberies on TikTok. The release says they were identified through the software Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial). It is an AI model developed by several universities and incorporated into the Ministerio Público in March 2023. It proposes probable participants from prosecution and police records for prosecutors and police to work up. The Noveno Juzgado de Garantía accredited the eight robberies. Four adults went to preventive detention and four adolescents remained in provisional internment. T13 quotes Fiscal Nacional Ángel Valencia saying the algorithm accelerates criminal analysis. It reports that after three members were arrested the AI searched their links to raise persons of interest later identified by victims. The OECD AI Incidents Monitor records the case." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Several universities (not named in the sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Chile's “Fiscal Heredia” AI model may have identified a 10-member “encerrona” robbery gang; a court accredits 8 robberies", "headline": "Fiscal Heredia may have identified a 10-member robbery gang" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ddb3d7fc67e58a23fa2552f7c68b582100dae25b98ad2f8a88a827164b6d5242" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Fiscalía de Chile's regional news release describes a joint investigation by Focos Occidente and the PDI's Brigada de Investigación Criminal. In the early hours of Thursday 11 May 2023 it led to 30 search warrants across Maipú, Pudahuel, Cerro Navia and other comunas. There were 17 detentions, ten linked to “encerronas” (robbery with intimidation or violence) whose perpetrators posted their robberies on TikTok. The release says they were identified through the software Fiscal Heredia (Herramienta para el Estudio del Delito Usando Inteligencia Artificial). It is an AI model developed by several universities and incorporated into the Ministerio Público in March 2023. It proposes probable participants from prosecution and police records for prosecutors and police to work up. The Noveno Juzgado de Garantía accredited the eight robberies. Four adults went to preventive detention and four adolescents remained in provisional internment. T13 quotes Fiscal Nacional Ángel Valencia saying the algorithm accelerates criminal analysis. It reports that after three members were arrested the AI searched their links to raise persons of interest later identified by victims. The OECD AI Incidents Monitor records the case.", "replication": { "produced_by": [ "Linked prosecution, prison and police records (SAF, Gendarmería, Carabineros)", "A few confirmed arrests seeding a link search", "Victim identification to confirm proposed persons of interest" ], "must_hold": [ "Suspects must already appear in the records the model draws on", "Human verification before charging", "Legal basis for cross-agency data linkage" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0171", "title": "ENEA and partners test a machine-learning system to forecast heatwave-driven grid failures in Italy", "summary": "The OECD AI Incidents Monitor records that ENEA, Politecnico di Bari and Università Roma Tre developed and tested an ML system to predict heatwave-induced grid failures (May 2023); no outcome given.", "date_observed": "2023-05-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry summarizes Italian press items of 24 to 26 May 2023 (Askanews, Teknoring, Ingenio and others, not among the sources). It says researchers from ENEA, Politecnico di Bari and Università Roma Tre developed and tested an AI-based system. It uses machine learning to predict and prevent electrical grid failures caused by heatwaves. It targets urban areas affected by climate change. The monitor labels it an AI hazard rather than an incident because the system is designed to prevent harm and no realized event is reported. The registry page is the only source on record. No deployment, grid operator or avoided outage is documented.", "category": "general benefit", "unexpected": false, "purpose": "The system was built to forecast heatwave-related failures on electricity networks so operators can act in advance. The record documents development and testing only.", "system": "ENEA machine-learning heatwave grid-failure forecasting model", "model_version": null, "developer": "ENEA with Politecnico di Bari and Università Roma Tre", "deployer": null, "location": "Italy", "domain": "Energy", "segment": "Electricity distribution resilience", "benefit_type": "Reduced Risk", "taxonomy_note": "The research announcement describes preventing heatwave-induced grid failures, with no deployment or avoided outage documented.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No avoided blackout or deployment is documented." }, { "group": "organizational", "depth": null, "reason": "No grid operator use is documented." } ], "ai_role": { "status": "unassessed", "statement": "The system's existence and purpose come from a registry summary of press reports. No evaluation, deployment or outcome was found, so no AI contribution to any event can be assessed." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2023-05-24-c85b, 'AI System Developed to Prevent Heatwave-Induced Blackouts in Italy'", "title": "AI System Developed to Prevent Heatwave-Induced Blackouts in Italy", "url": "https://oecd.ai/en/incidents/2023-05-24-c85b", "date": "2023-05-24", "written_by": "independent", "quote": "Researchers from ENEA, Politecnico di Bari, and Università Roma Tre developed and tested an AI-based system using machine learning to predict and prevent electrical grid failures caused by heatwaves." } ], "replication": { "produced_by": [ "Historical grid-failure and temperature data for Italian urban networks", "A research consortium of a public agency and two universities" ], "must_hold": [ "Operational deployment by a distribution operator", "Reporting of forecasts against realized failures" ], "echoes": [] }, "paired_incident": null, "headline": "ENEA tests ML heatwave grid-failure forecasts; no outcome given", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No development after the May 2023 announcement was found; the ENEA release as mirrored names only the RAFAEL project and an IEEE Transactions paper, with no figures.", "quote": null, "url": null }, "value": null, "developer_country": "Italy", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/ENEA_(Italy)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "Listed, not verified", "claim_basis": "Sources: a registry entry. 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The record documents development and testing only." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Italy", "developer_country": "Italy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The system was built to forecast heatwave-related failures on electricity networks so operators can act in advance. The record documents development and testing only." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-05-24", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/ENEA_(Italy)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Historical grid-failure and temperature data for Italian urban networks", "A research consortium of a public agency and two universities" ], "must_hold": [ "Operational deployment by a distribution operator", "Reporting of forecasts against realized failures" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0171-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2023-05-24-c85b, 'AI System Developed to Prevent Heatwave-Induced Blackouts in Italy'", "title": "AI System Developed to Prevent Heatwave-Induced Blackouts in Italy", "url": "https://oecd.ai/en/incidents/2023-05-24-c85b", "date": "2023-05-24", "written_by": "independent", "quote": "Researchers from ENEA, Politecnico di Bari, and Università Roma Tre developed and tested an AI-based system using machine learning to predict and prevent electrical grid failures caused by heatwaves." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The OECD AI Incidents Monitor records that ENEA, Politecnico di Bari and Università Roma Tre developed and tested an ML system to predict heatwave-induced grid failures (May 2023); no outcome given.", "account": "The OECD AI Incidents entry summarizes Italian press items of 24 to 26 May 2023 (Askanews, Teknoring, Ingenio and others, not among the sources). It says researchers from ENEA, Politecnico di Bari and Università Roma Tre developed and tested an AI-based system. It uses machine learning to predict and prevent electrical grid failures caused by heatwaves. It targets urban areas affected by climate change. The monitor labels it an AI hazard rather than an incident because the system is designed to prevent harm and no realized event is reported. The registry page is the only source on record. No deployment, grid operator or avoided outage is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ENEA machine-learning heatwave grid-failure forecasting model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ENEA with Politecnico di Bari and Università Roma Tre" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ENEA and partners test a machine-learning system to forecast heatwave-driven grid failures in Italy", "headline": "ENEA tests ML heatwave grid-failure forecasts; no outcome given" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d2e6e36c5834b75c3bf8855af1d5b8774bb65e73c428dab23353d9c8a3bd97b1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry summarizes Italian press items of 24 to 26 May 2023 (Askanews, Teknoring, Ingenio and others, not among the sources). It says researchers from ENEA, Politecnico di Bari and Università Roma Tre developed and tested an AI-based system. It uses machine learning to predict and prevent electrical grid failures caused by heatwaves. It targets urban areas affected by climate change. The monitor labels it an AI hazard rather than an incident because the system is designed to prevent harm and no realized event is reported. The registry page is the only source on record. No deployment, grid operator or avoided outage is documented.", "replication": { "produced_by": [ "Historical grid-failure and temperature data for Italian urban networks", "A research consortium of a public agency and two universities" ], "must_hold": [ "Operational deployment by a distribution operator", "Reporting of forecasts against realized failures" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0084", "title": "DGFiP's “Foncier innovant” deep-learning detection of undeclared swimming pools: 20,000+ pools taxed for 2022, about €10 million for communes", "summary": "DGFiP deep-learning pool detection: 20,000+ pools taxed for 2022 (~€10m for communes); 150,000 taxable pools found across metropolitan France excluding Paris and overseas departments", "date_observed": "2023-06-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "France's Direction générale des Finances publiques (DGFiP) runs “Foncier innovant”. A deep-learning algorithm finds building and pool outlines in public IGN aerial images. An automated check compares them to land-tax files. A tax agent verifies every anomaly before the owner is contacted. DGFiP's October 2021 note says Capgemini provided project-management and build assistance and Google the cloud infrastructure and services for developing the AI models. The 2022 experiment in nine departments led to more than 20,000 pools being taxed for 2022. That was close to €10 million of extra revenue for the communes concerned (DGFiP, 2 June 2023). The sources do not date the result separately from the announcement. The Sénat's April 2024 report puts the cost at €24 million. After generalization in 2023, the first pass covered metropolitan France, excluding Paris and the overseas departments (DROM). It detected 150,000 untaxed taxable pools, which the Sénat report calls “potentiellement taxables”. Industrialization began in June 2024.", "category": "general benefit", "unexpected": false, "purpose": "Detect undeclared pools and buildings from aerial imagery to bring them into the local property-tax base", "system": "Foncier innovant (DGFiP): open-source deep-learning segmentation of IGN orthophotos cross-checked with cadastral and tax files", "model_version": null, "developer": "DGFiP (Délégation à la transformation numérique) with Capgemini (assistance à maîtrise d'ouvrage et maîtrise d'œuvre) and Google (cloud infrastructure and AI-model development services)", "deployer": "Direction générale des Finances publiques (DGFiP)", "location": null, "domain": "Tax administration: local property tax base", "segment": "Cadastre and land-tax services", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The realized good is about 10 million euros in extra tax revenue for communes, which no type names, and the type names the detection of undeclared pools from aerial images.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate program results; no discrete attributable event." }, { "group": "organizational", "depth": null, "reason": "Revenue totals for communes (about €10 million for 2022) are program aggregates." }, { "group": "societal", "depth": null, "reason": "National program figures (150,000 pools detected) without a discrete event." } ], "ai_role": { "status": "unassessed", "statement": "Official sources describe the chain (AI detection, automated file check, human verification, owner contact) and attribute the taxed pools to it. No evaluation isolates the algorithm's contribution from the human verification and declaration campaign. The Assemblée nationale written answer of 14 December 2021 confirms DGFiP's use of AI on IGN imagery and that contractors do not access tax data." }, "evidence": [ { "kind": "press release", "citation": "Direction générale des Finances publiques (2023). Généralisation du « Foncier innovant ». impots.gouv.fr, 2 Jun 2023.", "title": "Généralisation du « Foncier innovant »", "url": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant", "date": "2023-06-02", "written_by": "makers", "quote": "plus de 20 000 piscines ont été taxées au titre de la taxe foncière (TF) pour l'année 2022, ce qui représente près de 10 M€ de recettes supplémentaires" }, { "kind": "press release", "citation": "Direction générale des collectivités locales (n.d.). Le Foncier innovant. collectivites-locales.gouv.fr (page describing the June 2024 industrialisation phase).", "title": "Le Foncier innovant", "url": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant", "date": null, "written_by": "makers", "quote": "Le premier passage des travaux de détection de piscines sur l'ensemble du territoire, hors Paris et DROM, a conduit à détecter 150 000 piscines imposables qui n'étaient pas imposées." }, { "kind": "press release", "citation": "Direction générale des Finances publiques (2021). Expérimentation du Foncier innovant (section 1, 'Les grandes lignes du projet du Foncier innovant'). impots.gouv.fr, 20 Oct 2021 (modified 29 Aug 2022).", "title": "Expérimentation du Foncier innovant", "url": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "date": "2021-10-20", "written_by": "makers", "quote": "la société Capgemini assure notamment les rôles d'assistance à maîtrise d'ouvrage et maîtrise d'œuvre" }, { "kind": "other", "citation": "Assemblée nationale (2021). Question écrite n° 41677 de M. Jean-Jacques Gaultier, réponse du ministère des Comptes publics publiée au JO le 14 décembre 2021.", "title": "Projet « Foncier innovant » – Question écrite n° 41677", "url": "https://www.assemblee-nationale.fr/dyn/15/questions/QANR5L15QE41677.pdf", "date": "2021-12-14", "written_by": "makers", "quote": "la DGFiP recourt, dans le cadre du projet « Foncier innovant », aux technologies innovantes d'intelligence artificielle et de valorisation des données à partir des prises de vue aériennes" }, { "kind": "report", "citation": "Rambaud, D. & Vermeillet, S. (2024). IA, impôts, prestations sociales et lutte contre la fraude. Rapport d'information n° 491, Sénat, délégation à la prospective, 2 Apr 2024, p. 50.", "title": "Rapport d'information n° 491 (2023-2024): IA, impôts, prestations sociales et lutte contre la fraude", "url": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "date": "2024-04-02", "written_by": "independent", "quote": "menée sur 9 départements pilotes en 2022 a permis de confirmer le caractère taxable de plus de 20 000 nouvelles piscines, représentant près de 10 millions d'euros" } ], "replication": { "produced_by": [ "Deep-learning segmentation of IGN orthophotos producing pool and building outlines", "Automated cross-check against cadastral and land-tax files", "Systematic verification by a tax agent and a declaration campaign to owners" ], "must_hold": [ "Regular high-resolution public aerial imagery (IGN triennial orthophotos)", "Reliable cadastral records to compare against", "Legal basis to tax detected constructions and agent capacity for verification" ], "echoes": [ { "date": "2023-05-01", "setting": "Nationwide generalization: e-mails (or letters for non-internet users) to more than 120,000 pool owners from the end of May 2023 (DGFiP, 2 June 2023; month only; end of May)", "model_version": null, "outcome": "recurred", "source": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant" }, { "date": "2024-06-01", "setting": "Industrialisation phase on IGN triennial orthophotos from June 2024 (DGCL page; month only)", "model_version": null, "outcome": "unknown", "source": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1082", "title": "California Homeowner Reportedly Loses Insurance After Purported Aerial Imagery-Based Roof Assessment", "url": "https://incidentdatabase.ai/cite/1082", "severity": null, "group": "personal", "basis": "AI analysis of aerial imagery of private property, as in DGFiP's pool detection, wrongly assessed a homeowner's roof and cost her insurance coverage." }, "headline": "DGFiP's Foncier innovant leads to 20,000+ pools taxed for 2022", "metric": "more than 20,000 pools being taxed for 2022, close to €10 million of extra revenue", "comparator": null, "later": { "status": "scaled", "date": "2024-04-02", "note": "The Sénat's April 2024 report records the generalization to all of metropolitan France in 2023, for about 150,000 potentially taxable pools, and the DGCL page dates an industrialization phase from June 2024.", "quote": "Le dispositif a donc été généralisé en 2023 à l’ensemble de la métropole (la Corse et l’Outre-mer devraient suivre), pour environ 150 000 piscines potentiellement taxables au total, soit une part non négligeable (5 %) des 3 millions de piscines enterrées que compte la France.", "url": "https://www.senat.fr/rap/r23-491/r23-4911.pdf" }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1082 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1082", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Limited the 150,000-pool figure to metropolitan France excluding Paris and the overseas departments as the DGCL page does and added the Sénat's “potentiellement taxables” wording; stated that the date observed is the publication date of the DGFiP announcement; credited Google with AI-model development services as well as cloud infrastructure per the DGFiP note; restored the page title “Expérimentation du Foncier innovant” on the 2021 evidence item; and re-dated the generalization echo to May 2023 (month only) with e-mails rather than letters as the DGFiP describes.", "source": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fr.wikipedia.org/wiki/Direction_g%C3%A9n%C3%A9rale_des_Finances_publiques; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, three press releases from the makers and the makers' other. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0084", "catalog_version": "1.0.0", "source_fingerprint": "31ca7f3f03307b92af0ce848385439e99481791c917ab842132c448ea2d0ff04", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0084-source-0001", "AIBD-0084-source-0002", "AIBD-0084-source-0003", "AIBD-0084-source-0004", "AIBD-0084-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DGFiP (Délégation à la transformation numérique) with Capgemini (assistance à maîtrise d'ouvrage et maîtrise d'œuvre) and Google (cloud infrastructure and AI-model development services)", "deployer": "Direction générale des Finances publiques (DGFiP)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Official sources describe the chain (AI detection, automated file check, human verification, owner contact) and attribute the taxed pools to it. No evaluation isolates the algorithm's contribution from the human verification and declaration campaign. 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stated that the date observed is the publication date of the DGFiP announcement; credited Google with AI-model development services as well as cloud infrastructure per the DGFiP note; restored the page title “Expérimentation du Foncier innovant” on the 2021 evidence item; and re-dated the generalization echo to May 2023 (month only) with e-mails rather than letters as the DGFiP describes.", "source": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fr.wikipedia.org/wiki/Direction_g%C3%A9n%C3%A9rale_des_Finances_publiques; 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month only; end of May)", "outcome": "recurred", "source": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant" }, { "date": "2024-06-01", "setting": "Industrialisation phase on IGN triennial orthophotos from June 2024 (DGCL page; month only)", "outcome": "unknown", "source": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1082 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1082", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Limited the 150,000-pool figure to metropolitan France excluding Paris and the overseas departments as the DGCL page does and added the Sénat's “potentiellement taxables” wording; stated that the date observed is the publication date of the DGFiP announcement; credited Google with AI-model development services as well as cloud infrastructure per the DGFiP note; restored the page title “Expérimentation du Foncier innovant” on the 2021 evidence item; and re-dated the generalization echo to May 2023 (month only) with e-mails rather than letters as the DGFiP describes.", "source": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://fr.wikipedia.org/wiki/Direction_g%C3%A9n%C3%A9rale_des_Finances_publiques; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Tax administration: local property tax base", "segment": "Cadastre and land-tax services" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Direction générale des Finances publiques (2023). Généralisation du « Foncier innovant ». impots.gouv.fr, 2 Jun 2023.", "title": "Généralisation du « Foncier innovant »", "url": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant", "date": "2023-06-02", "written_by": "makers", "quote": "plus de 20 000 piscines ont été taxées au titre de la taxe foncière (TF) pour l'année 2022, ce qui représente près de 10 M€ de recettes supplémentaires" }, { "kind": "press release", "citation": "Direction générale des collectivités locales (n.d.). Le Foncier innovant. collectivites-locales.gouv.fr (page describing the June 2024 industrialisation phase).", "title": "Le Foncier innovant", "url": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant", "written_by": "makers", "quote": "Le premier passage des travaux de détection de piscines sur l'ensemble du territoire, hors Paris et DROM, a conduit à détecter 150 000 piscines imposables qui n'étaient pas imposées." }, { "kind": "press release", "citation": "Direction générale des Finances publiques (2021). Expérimentation du Foncier innovant (section 1, 'Les grandes lignes du projet du Foncier innovant'). impots.gouv.fr, 20 Oct 2021 (modified 29 Aug 2022).", "title": "Expérimentation du Foncier innovant", "url": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "date": "2021-10-20", "written_by": "makers", "quote": "la société Capgemini assure notamment les rôles d'assistance à maîtrise d'ouvrage et maîtrise d'œuvre" }, { "kind": "other", "citation": "Assemblée nationale (2021). Question écrite n° 41677 de M. Jean-Jacques Gaultier, réponse du ministère des Comptes publics publiée au JO le 14 décembre 2021.", "title": "Projet « Foncier innovant » – Question écrite n° 41677", "url": "https://www.assemblee-nationale.fr/dyn/15/questions/QANR5L15QE41677.pdf", "date": "2021-12-14", "written_by": "makers", "quote": "la DGFiP recourt, dans le cadre du projet « Foncier innovant », aux technologies innovantes d'intelligence artificielle et de valorisation des données à partir des prises de vue aériennes" }, { "kind": "report", "citation": "Rambaud, D. & Vermeillet, S. (2024). IA, impôts, prestations sociales et lutte contre la fraude. Rapport d'information n° 491, Sénat, délégation à la prospective, 2 Apr 2024, p. 50.", "title": "Rapport d'information n° 491 (2023-2024): IA, impôts, prestations sociales et lutte contre la fraude", "url": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "date": "2024-04-02", "written_by": "independent", "quote": "menée sur 9 départements pilotes en 2022 a permis de confirmer le caractère taxable de plus de 20 000 nouvelles piscines, représentant près de 10 millions d'euros" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0084-source-0001", "AIBD-0084-source-0002", "AIBD-0084-source-0003", "AIBD-0084-source-0004", "AIBD-0084-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Direction générale des Finances publiques (2023). Généralisation du « Foncier innovant ». impots.gouv.fr, 2 Jun 2023.", "title": "Généralisation du « Foncier innovant »", "url": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant", "date": "2023-06-02", "written_by": "makers", "quote": "plus de 20 000 piscines ont été taxées au titre de la taxe foncière (TF) pour l'année 2022, ce qui représente près de 10 M€ de recettes supplémentaires" }, { "kind": "press release", "citation": "Direction générale des collectivités locales (n.d.). Le Foncier innovant. collectivites-locales.gouv.fr (page describing the June 2024 industrialisation phase).", "title": "Le Foncier innovant", "url": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant", "written_by": "makers", "quote": "Le premier passage des travaux de détection de piscines sur l'ensemble du territoire, hors Paris et DROM, a conduit à détecter 150 000 piscines imposables qui n'étaient pas imposées." }, { "kind": "press release", "citation": "Direction générale des Finances publiques (2021). Expérimentation du Foncier innovant (section 1, 'Les grandes lignes du projet du Foncier innovant'). impots.gouv.fr, 20 Oct 2021 (modified 29 Aug 2022).", "title": "Expérimentation du Foncier innovant", "url": "https://www.impots.gouv.fr/actualite/1-les-grandes-lignes-du-projet-du-foncier-innovant-afin-de-garantir-une-meilleure", "date": "2021-10-20", "written_by": "makers", "quote": "la société Capgemini assure notamment les rôles d'assistance à maîtrise d'ouvrage et maîtrise d'œuvre" }, { "kind": "other", "citation": "Assemblée nationale (2021). Question écrite n° 41677 de M. Jean-Jacques Gaultier, réponse du ministère des Comptes publics publiée au JO le 14 décembre 2021.", "title": "Projet « Foncier innovant » – Question écrite n° 41677", "url": "https://www.assemblee-nationale.fr/dyn/15/questions/QANR5L15QE41677.pdf", "date": "2021-12-14", "written_by": "makers", "quote": "la DGFiP recourt, dans le cadre du projet « Foncier innovant », aux technologies innovantes d'intelligence artificielle et de valorisation des données à partir des prises de vue aériennes" }, { "kind": "report", "citation": "Rambaud, D. & Vermeillet, S. (2024). IA, impôts, prestations sociales et lutte contre la fraude. Rapport d'information n° 491, Sénat, délégation à la prospective, 2 Apr 2024, p. 50.", "title": "Rapport d'information n° 491 (2023-2024): IA, impôts, prestations sociales et lutte contre la fraude", "url": "https://www.senat.fr/rap/r23-491/r23-4911.pdf", "date": "2024-04-02", "written_by": "independent", "quote": "menée sur 9 départements pilotes en 2022 a permis de confirmer le caractère taxable de plus de 20 000 nouvelles piscines, représentant près de 10 millions d'euros" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "DGFiP deep-learning pool detection: 20,000+ pools taxed for 2022 (~€10m for communes); 150,000 taxable pools found across metropolitan France excluding Paris and overseas departments", "account": "France's Direction générale des Finances publiques (DGFiP) runs “Foncier innovant”. A deep-learning algorithm finds building and pool outlines in public IGN aerial images. An automated check compares them to land-tax files. A tax agent verifies every anomaly before the owner is contacted. DGFiP's October 2021 note says Capgemini provided project-management and build assistance and Google the cloud infrastructure and services for developing the AI models. The 2022 experiment in nine departments led to more than 20,000 pools being taxed for 2022. That was close to €10 million of extra revenue for the communes concerned (DGFiP, 2 June 2023). The sources do not date the result separately from the announcement. The Sénat's April 2024 report puts the cost at €24 million. After generalization in 2023, the first pass covered metropolitan France, excluding Paris and the overseas departments (DROM). It detected 150,000 untaxed taxable pools, which the Sénat report calls “potentiellement taxables”. Industrialization began in June 2024." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Foncier innovant (DGFiP): open-source deep-learning segmentation of IGN orthophotos cross-checked with cadastral and tax files" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DGFiP (Délégation à la transformation numérique) with Capgemini (assistance à maîtrise d'ouvrage et maîtrise d'œuvre) and Google (cloud infrastructure and AI-model development services)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "DGFiP's “Foncier innovant” deep-learning detection of undeclared swimming pools: 20,000+ pools taxed for 2022, about €10 million for communes", "headline": "DGFiP's Foncier innovant leads to 20,000+ pools taxed for 2022" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "31ca7f3f03307b92af0ce848385439e99481791c917ab842132c448ea2d0ff04" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "France's Direction générale des Finances publiques (DGFiP) runs “Foncier innovant”. A deep-learning algorithm finds building and pool outlines in public IGN aerial images. An automated check compares them to land-tax files. A tax agent verifies every anomaly before the owner is contacted. DGFiP's October 2021 note says Capgemini provided project-management and build assistance and Google the cloud infrastructure and services for developing the AI models. The 2022 experiment in nine departments led to more than 20,000 pools being taxed for 2022. That was close to €10 million of extra revenue for the communes concerned (DGFiP, 2 June 2023). The sources do not date the result separately from the announcement. The Sénat's April 2024 report puts the cost at €24 million. After generalization in 2023, the first pass covered metropolitan France, excluding Paris and the overseas departments (DROM). It detected 150,000 untaxed taxable pools, which the Sénat report calls “potentiellement taxables”. Industrialization began in June 2024.", "replication": { "produced_by": [ "Deep-learning segmentation of IGN orthophotos producing pool and building outlines", "Automated cross-check against cadastral and land-tax files", "Systematic verification by a tax agent and a declaration campaign to owners" ], "must_hold": [ "Regular high-resolution public aerial imagery (IGN triennial orthophotos)", "Reliable cadastral records to compare against", "Legal basis to tax detected constructions and agent capacity for verification" ], "echoes": [ { "date": "2023-05-01", "setting": "Nationwide generalization: e-mails (or letters for non-internet users) to more than 120,000 pool owners from the end of May 2023 (DGFiP, 2 June 2023; month only; end of May)", "outcome": "recurred", "source": "https://www.impots.gouv.fr/actualite/generalisation-du-foncier-innovant" }, { "date": "2024-06-01", "setting": "Industrialisation phase on IGN triennial orthophotos from June 2024 (DGCL page; month only)", "outcome": "unknown", "source": "https://www.collectivites-locales.gouv.fr/animer-les-territoires/environnement-et-urbanisme/le-cadastre/le-foncier-innovant" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0026", "title": "Fitbit Sense ECG detection leading to diagnosis and treatment of ventricular tachycardia", "summary": "Fitbit Sense flagged an irregular 164 bpm rhythm; fascicular VT was diagnosed and controlled with verapamil (India, 2023).", "date_observed": "2023-07-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case report was published in Cureus on 18 July 2023 (event date not reported). A 55-year-old man in Jamshedpur, India, had symptoms at work. His Fitbit Sense watch detected an irregular heart rate of 164 beats per minute with irregular rhythm and bizarre QRS morphology. He sought care at Tata Main Hospital. A 12-lead electrocardiogram (ECG) showed tachycardia at 166 beats per minute with bizarre QRS complexes under 130 ms and right axis deviation. Idiopathic fascicular ventricular tachycardia (VT) was diagnosed. Holter monitoring, echocardiography and coronary angiography excluded structural heart disease. He got oral verapamil and telmisartan. After four cardiology visits he was reported to be doing well with no further complaints.", "category": "benefit created", "unexpected": false, "purpose": "The Fitbit Sense ECG app records a single-lead ECG to assess heart rhythm (its clearance is for atrial fibrillation). Capturing an abnormal rhythm for medical review was its purpose, although VT is outside its validated classification.", "system": "Fitbit Sense ECG app and heart-rate monitoring", "model_version": "Fitbit Sense", "developer": "Fitbit (Google)", "deployer": null, "location": "Jamshedpur, India", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "One man received a confirmed diagnosis of fascicular ventricular tachycardia and effective medical control. A material benefit to one person." } ], "ai_role": { "status": "assessed", "statement": "The watch's rhythm analysis flagged an irregular 164 bpm rhythm with abnormal QRS morphology, which sent the patient to hospital. The diagnosis and treatment were made by cardiologists from a 12-lead ECG and further tests." }, "evidence": [ { "kind": "case report", "citation": "Kumar S, Banerjee A (2023). Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia: A Case Report. Cureus 15:e42054.", "title": "Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia", "url": "https://europepmc.org/article/PMC/PMC10432923", "date": "2023-07-18", "written_by": "independent", "quote": "detected an irregular heart rate of 164 beats per minute along with irregular rhythm and bizarre QRS wave morphology" } ], "replication": { "produced_by": [ "The wearer has a Fitbit with the ECG app or heart-rate alerts", "A symptomatic tachyarrhythmia occurs while the device is worn and the result prompts care-seeking", "Clinicians confirm the rhythm and start treatment" ], "must_hold": [ "The device result is taken to a clinician promptly", "Confirmatory ECG and structural work-up are available", "Appropriate therapy is accessible" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "severity": null, "group": "personal", "basis": "No Fitbit incident exists; the nearest wearable false alarm is Apple Watch Crash Detection misclassifying skiing and dialing 911, harming watch users and dispatchers, the inverse of Fitbit Sense correctly flagging 164 bpm ventricular tachycardia." }, "headline": "Fitbit Sense flags a 164 bpm rhythm, leading to a VT diagnosis", "metric": "detected an irregular heart rate of 164 beats per minute with irregular rhythm", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The only cited source is the case report itself; no later development was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://support.google.com/product-documentation/answer/14816019", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0026", "catalog_version": "1.0.0", "source_fingerprint": "6f5c6804b6d93c5a7e22fac42f65e47f0b37d78df9dd171f32df21f8d5d21c65", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0026-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fitbit (Google)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's rhythm analysis flagged an irregular 164 bpm rhythm with abnormal QRS morphology, which sent the patient to hospital. The diagnosis and treatment were made by cardiologists from a 12-lead ECG and further tests." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's rhythm analysis flagged an irregular 164 bpm rhythm with abnormal QRS morphology, which sent the patient to hospital. 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Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia: A Case Report. Cureus 15:e42054.", "title": "Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia", "url": "https://europepmc.org/article/PMC/PMC10432923", "date": "2023-07-18", "written_by": "independent", "quote": "detected an irregular heart rate of 164 beats per minute along with irregular rhythm and bizarre QRS wave morphology" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0026-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Kumar S, Banerjee A (2023). Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia: A Case Report. Cureus 15:e42054.", "title": "Artificial Intelligence-Enabled Smartwatch Used for the Detection of Idiopathic Ventricular Tachycardia", "url": "https://europepmc.org/article/PMC/PMC10432923", "date": "2023-07-18", "written_by": "independent", "quote": "detected an irregular heart rate of 164 beats per minute along with irregular rhythm and bizarre QRS wave morphology" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Fitbit Sense flagged an irregular 164 bpm rhythm; fascicular VT was diagnosed and controlled with verapamil (India, 2023).", "account": "A case report was published in Cureus on 18 July 2023 (event date not reported). A 55-year-old man in Jamshedpur, India, had symptoms at work. His Fitbit Sense watch detected an irregular heart rate of 164 beats per minute with irregular rhythm and bizarre QRS morphology. He sought care at Tata Main Hospital. A 12-lead electrocardiogram (ECG) showed tachycardia at 166 beats per minute with bizarre QRS complexes under 130 ms and right axis deviation. Idiopathic fascicular ventricular tachycardia (VT) was diagnosed. Holter monitoring, echocardiography and coronary angiography excluded structural heart disease. He got oral verapamil and telmisartan. After four cardiology visits he was reported to be doing well with no further complaints." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The watch analyzed cardiac rhythm and flagged an irregular reading." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used a Fitbit Sense." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Fitbit Sense" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fitbit Sense ECG app and heart-rate monitoring" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Fitbit (Google)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fitbit Sense ECG detection leading to diagnosis and treatment of ventricular tachycardia", "headline": "Fitbit Sense flags a 164 bpm rhythm, leading to a VT diagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6f5c6804b6d93c5a7e22fac42f65e47f0b37d78df9dd171f32df21f8d5d21c65" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report was published in Cureus on 18 July 2023 (event date not reported). A 55-year-old man in Jamshedpur, India, had symptoms at work. His Fitbit Sense watch detected an irregular heart rate of 164 beats per minute with irregular rhythm and bizarre QRS morphology. He sought care at Tata Main Hospital. A 12-lead electrocardiogram (ECG) showed tachycardia at 166 beats per minute with bizarre QRS complexes under 130 ms and right axis deviation. Idiopathic fascicular ventricular tachycardia (VT) was diagnosed. Holter monitoring, echocardiography and coronary angiography excluded structural heart disease. He got oral verapamil and telmisartan. After four cardiology visits he was reported to be doing well with no further complaints.", "replication": { "produced_by": [ "The wearer has a Fitbit with the ECG app or heart-rate alerts", "A symptomatic tachyarrhythmia occurs while the device is worn and the result prompts care-seeking", "Clinicians confirm the rhythm and start treatment" ], "must_hold": [ "The device result is taken to a clinician promptly", "Confirmatory ECG and structural work-up are available", "Appropriate therapy is accessible" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0146", "title": "HelioLinc3D identifies potentially hazardous asteroid 2022 SF289 from sparse ATLAS detections", "summary": "HelioLinc3D linked sparse ATLAS detections into PHA 2022 SF289, published by the Minor Planet Center in MPEC 2023-O26 (Jul 2023).", "date_observed": "2023-07-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 18 July 2023 the HelioLinc3D linking algorithm identified an unrecognized near-Earth asteroid, 2022 SF289. It was a test on archival data from the NASA-funded ATLAS survey operated by the University of Hawaii (UH). HelioLinc3D was developed by Ari Heinze and colleagues at the University of Washington's (UW) DiRAC Institute for the Vera C. Rubin Observatory. ATLAS had first imaged the object on 19 September 2022 and observed it three times across four nights. Conventional discovery requires more same-night detections. The Minor Planet Center (MPC) published the object in MPEC 2023-O26, issued 18 July 2023. It is an Apollo-type potentially hazardous asteroid about 600 feet across with an Earth MOID of 0.0015 AU and no foreseeable risk to Earth. The sources call HelioLinc3D an algorithm, not a learned model.", "category": "benefit created", "unexpected": false, "purpose": "Built as Rubin Observatory's linking algorithm to discover moving objects, including near-Earth asteroids, from sparse multi-night detections. This benefit was that purpose.", "system": "HelioLinc3D (heliocentric linking algorithm for Rubin Observatory solar-system processing)", "model_version": null, "developer": "University of Washington DiRAC Institute / Rubin Observatory (Ari Heinze, Siegfried Eggl, Mario Juric)", "deployer": "University of Washington DiRAC Institute, test run on ATLAS survey data", "location": null, "domain": "Astronomy / planetary defense", "segment": "Academic research / observatory operations", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Rubin Observatory and UW DiRAC team obtained a real-data validation of the linking software before the ten-year survey began." }, { "group": "societal", "depth": 2, "reason": "One roughly 600-foot potentially hazardous asteroid was added to the catalog. The sources state that it poses no foreseeable risk, so the benefit is knowledge, not averted harm." } ], "ai_role": { "status": "assessed", "statement": "HelioLinc3D linked detections from separate nights that conventional pipelines could not combine, producing the orbit that the MPC published. Caveat: UW, UH, Rubin and MPC sources call it a “next-generation algorithm”. No cited source describes it as machine learning or AI." }, "evidence": [ { "kind": "dataset", "citation": "Minor Planet Center (2023). MPEC 2023-O26: 2022 SF289. IAU Minor Planet Electronic Circular.", "title": "MPEC 2023-O26 : 2022 SF289", "url": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "date": "2023-07-18", "written_by": "independent", "quote": "Earth MOID = 0.0015 AU" }, { "kind": "dataset", "citation": "Minor Planet Center (2023). MPC Database entry for 2022 SF289.", "title": "2022 SF289 - MPC database", "url": "https://minorplanetcenter.net/db_search/show_object?object_id=2022+SF289", "date": null, "written_by": "independent", "quote": "Initial reported observation by ATLAS-HKO, Haleakala on 2022-09-19." }, { "kind": "press release", "citation": "University of Hawaii (2023). 'Potentially hazardous' asteroid identified through new algorithm. UH News.", "title": "'Potentially hazardous' asteroid identified through new algorithm", "url": "https://www.hawaii.edu/news/2023/07/31/identify-potentially-hazardous-asteroid/", "date": "2023-07-31", "written_by": "deployer", "quote": "By demonstrating the real-world effectiveness of the software that Rubin will use to look for thousands of yet-unknown potentially hazardous asteroids" }, { "kind": "press release", "citation": "University of Washington (2023). New algorithm ensnares its first 'potentially hazardous' asteroid. UW News.", "title": "New algorithm ensnares its first 'potentially hazardous' asteroid", "url": "https://www.washington.edu/news/2023/07/31/heliolinc3d/", "date": "2023-07-31", "written_by": "makers", "quote": "By demonstrating the real-world effectiveness of the software that Rubin will use to look for thousands of yet-unknown potentially hazardous asteroids, the discovery of 2022 SF289 makes us all safer." }, { "kind": "press release", "citation": "Rubin Observatory (2023). New Algorithm Developed for Rubin Ensnares its First Asteroid.", "title": "New Algorithm Developed for Rubin Ensnares its First Asteroid", "url": "https://rubinobservatory.org/news/new-algorithm-asteroid", "date": "2023-07-31", "written_by": "makers", "quote": "boosts scientists' ability to identify new near-Earth asteroids using Rubin data" }, { "kind": "press release", "citation": "University of Washington (2026). Early data from Rubin Observatory reveals over 11,000 new asteroids. UW News, 2 April 2026.", "title": "Early data from Rubin Observatory reveals over 11,000 new asteroids", "url": "https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/", "date": "2026-04-02", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Survey detections too sparse per night for conventional linking", "Heliocentric linking across multiple nights", "Submission to and designation by the Minor Planet Center" ], "must_hold": [ "Astrometry from several nights must be precise enough to constrain a heliocentric orbit", "The Minor Planet Center must confirm the linkage as a new object" ], "echoes": [] }, "paired_incident": null, "headline": "HelioLinc3D finds asteroid 2022 SF289 in sparse ATLAS detections", "metric": "about 600 feet across with an Earth MOID of 0.0015 AU", "comparator": { "against": "conventional near-Earth-object discovery, which needs four observations of an object on one night", "before": "ATLAS had observed 2022 SF289 three times on four separate nights, but never the requisite four times on one night to be identified as a new NEO", "after": "It successfully combined fragments of data from all four nights and made the discovery.", "basis": "measured", "quote": "In retrospect, ATLAS had observed 2022 SF289 three times on four separate nights, but never the requisite four times on one night to be identified as a new NEO. But these are just the occasions where HelioLinc3D excels: It successfully combined fragments of data from all four nights and made the discovery.", "url": "https://www.washington.edu/news/2023/07/31/heliolinc3d/" }, "later": { "status": "scaled", "date": "2026-04-02", "note": "On 2 April 2026 UW and Rubin announced over 11,000 new asteroids, including 33 near-Earth objects, confirmed by the Minor Planet Center and found with DiRAC-developed discovery software built by Ari Heinze and Jacob Kurlander; the release does not use the name HelioLinc3D.", "quote": "The findings were confirmed by the International Astronomical Union's Minor Planet Center (MPC), and include hundreds of distant worlds beyond Neptune as well as 33 previously unknown near-Earth objects.", "url": "https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.washington.edu/news/2023/07/31/heliolinc3d/; https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Washington; https://en.wikipedia.org/wiki/University_of_Washington", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent datasets, three press releases from the makers and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0146", "catalog_version": "1.0.0", "source_fingerprint": "e5c3b3a731212ce81da6de652bc2850343bf892504226b1fa540bdeeddeb41f6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0146-source-0001", "AIBD-0146-source-0002", "AIBD-0146-source-0003", "AIBD-0146-source-0004", "AIBD-0146-source-0005", "AIBD-0146-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Washington DiRAC Institute / Rubin Observatory (Ari Heinze, Siegfried Eggl, Mario Juric)", "deployer": "University of Washington DiRAC Institute, test run on ATLAS survey data" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "HelioLinc3D linked detections from separate nights that conventional pipelines could not combine, producing the orbit that the MPC published. Caveat: UW, UH, Rubin and MPC sources call it a “next-generation algorithm”. No cited source describes it as machine learning or AI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "HelioLinc3D linked detections from separate nights that conventional pipelines could not combine, producing the orbit that the MPC published. Caveat: UW, UH, Rubin and MPC sources call it a “next-generation algorithm”. No cited source describes it as machine learning or AI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Rubin Observatory and UW DiRAC team obtained a real-data validation of the linking software before the ten-year survey began." }, { "group": "societal", "depth": 2, "reason": "One roughly 600-foot potentially hazardous asteroid was added to the catalog. The sources state that it poses no foreseeable risk, so the benefit is knowledge, not averted harm." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent datasets, three press releases from the makers and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Rubin Observatory and UW DiRAC team obtained a real-data validation of the linking software before the ten-year survey began." }, { "group": "societal", "depth": 2, "reason": "One roughly 600-foot potentially hazardous asteroid was added to the catalog. The sources state that it poses no foreseeable risk, so the benefit is knowledge, not averted harm." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Rubin Observatory and UW DiRAC team obtained a real-data validation of the linking software before the ten-year survey began." }, { "group": "societal", "depth": 2, "reason": "One roughly 600-foot potentially hazardous asteroid was added to the catalog. The sources state that it poses no foreseeable risk, so the benefit is knowledge, not averted harm." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "about 600 feet across with an Earth MOID of 0.0015 AU", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-04-02", "note": "On 2 April 2026 UW and Rubin announced over 11,000 new asteroids, including 33 near-Earth objects, confirmed by the Minor Planet Center and found with DiRAC-developed discovery software built by Ari Heinze and Jacob Kurlander; the release does not use the name HelioLinc3D.", "quote": "The findings were confirmed by the International Astronomical Union's Minor Planet Center (MPC), and include hundreds of distant worlds beyond Neptune as well as 33 previously unknown near-Earth objects.", "url": "https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0146" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 18 July 2023 the HelioLinc3D linking algorithm identified an unrecognized near-Earth asteroid, 2022 SF289. It was a test on archival data from the NASA-funded ATLAS survey operated by the University of Hawaii (UH). HelioLinc3D was developed by Ari Heinze and colleagues at the University of Washington's (UW) DiRAC Institute for the Vera C. Rubin Observatory. ATLAS had first imaged the object on 19 September 2022 and observed it three times across four nights. Conventional discovery requires more same-night detections. The Minor Planet Center (MPC) published the object in MPEC 2023-O26, issued 18 July 2023. It is an Apollo-type potentially hazardous asteroid about 600 feet across with an Earth MOID of 0.0015 AU and no foreseeable risk to Earth. The sources call HelioLinc3D an algorithm, not a learned model.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Rubin Observatory and UW DiRAC team obtained a real-data validation of the linking software before the ten-year survey began." }, { "group": "societal", "depth": 2, "reason": "One roughly 600-foot potentially hazardous asteroid was added to the catalog. The sources state that it poses no foreseeable risk, so the benefit is knowledge, not averted harm." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built as Rubin Observatory's linking algorithm to discover moving objects, including near-Earth asteroids, from sparse multi-night detections. This benefit was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built as Rubin Observatory's linking algorithm to discover moving objects, including near-Earth asteroids, from sparse multi-night detections. This benefit was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-07-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.washington.edu/news/2023/07/31/heliolinc3d/; https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Washington; https://en.wikipedia.org/wiki/University_of_Washington", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Survey detections too sparse per night for conventional linking", "Heliocentric linking across multiple nights", "Submission to and designation by the Minor Planet Center" ], "must_hold": [ "Astrometry from several nights must be precise enough to constrain a heliocentric orbit", "The Minor Planet Center must confirm the linkage as a new object" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.washington.edu/news/2023/07/31/heliolinc3d/; https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Washington; https://en.wikipedia.org/wiki/University_of_Washington", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Astronomy / planetary defense", "segment": "Academic research / observatory operations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "dataset", "citation": "Minor Planet Center (2023). MPEC 2023-O26: 2022 SF289. IAU Minor Planet Electronic Circular.", "title": "MPEC 2023-O26 : 2022 SF289", "url": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "date": "2023-07-18", "written_by": "independent", "quote": "Earth MOID = 0.0015 AU" }, { "kind": "dataset", "citation": "Minor Planet Center (2023). MPC Database entry for 2022 SF289.", "title": "2022 SF289 - MPC database", "url": "https://minorplanetcenter.net/db_search/show_object?object_id=2022+SF289", "written_by": "independent", "quote": "Initial reported observation by ATLAS-HKO, Haleakala on 2022-09-19." }, { "kind": "press release", "citation": "University of Hawaii (2023). 'Potentially hazardous' asteroid identified through new algorithm. UH News.", "title": "'Potentially hazardous' asteroid identified through new algorithm", "url": "https://www.hawaii.edu/news/2023/07/31/identify-potentially-hazardous-asteroid/", "date": "2023-07-31", "written_by": "deployer", "quote": "By demonstrating the real-world effectiveness of the software that Rubin will use to look for thousands of yet-unknown potentially hazardous asteroids" }, { "kind": "press release", "citation": "University of Washington (2023). New algorithm ensnares its first 'potentially hazardous' asteroid. UW News.", "title": "New algorithm ensnares its first 'potentially hazardous' asteroid", "url": "https://www.washington.edu/news/2023/07/31/heliolinc3d/", "date": "2023-07-31", "written_by": "makers", "quote": "By demonstrating the real-world effectiveness of the software that Rubin will use to look for thousands of yet-unknown potentially hazardous asteroids, the discovery of 2022 SF289 makes us all safer." }, { "kind": "press release", "citation": "Rubin Observatory (2023). New Algorithm Developed for Rubin Ensnares its First Asteroid.", "title": "New Algorithm Developed for Rubin Ensnares its First Asteroid", "url": "https://rubinobservatory.org/news/new-algorithm-asteroid", "date": "2023-07-31", "written_by": "makers", "quote": "boosts scientists' ability to identify new near-Earth asteroids using Rubin data" }, { "kind": "press release", "citation": "University of Washington (2026). Early data from Rubin Observatory reveals over 11,000 new asteroids. UW News, 2 April 2026.", "title": "Early data from Rubin Observatory reveals over 11,000 new asteroids", "url": "https://www.washington.edu/news/2026/04/02/rubin-observatory-11000-new-asteroids/", "date": "2026-04-02", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0146-source-0001", "AIBD-0146-source-0002", "AIBD-0146-source-0003", "AIBD-0146-source-0004", "AIBD-0146-source-0005", "AIBD-0146-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The Minor Planet Center publishes the observations and orbit. The University of Washington identifies HelioLinc3D as the discovery software. The circular is an astronomical record." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0146-source-0001", "AIBD-0146-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The Minor Planet Center publishes the observations and orbit. The University of Washington identifies HelioLinc3D as the discovery software. The circular is an astronomical record." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0146-source-0001", "retained_source_order": [ "AIBD-0146-source-0001", "AIBD-0146-source-0002", "AIBD-0146-source-0003", "AIBD-0146-source-0004", "AIBD-0146-source-0005", "AIBD-0146-source-0006" ], "origins": [ { "url": "https://minorplanetcenter.net/mpec/K23/K23O26.html", "locator": "MPEC 2023-O26, observations, observer details, orbital elements, and ephemeris.", "contribution": "Independent confirmation of the asteroid’s observations and orbit.", "relationship": "Minor Planet Center astronomical circular.", "source_refs": [ "AIBD-0146-source-0001" ] }, { "url": "https://www.washington.edu/news/2023/07/31/heliolinc3d/", "locator": "Discovery account and link to MPEC 2023-O26.", "contribution": "Attributes the sparse-observation discovery to HelioLinc3D.", "relationship": "The developer’s original announcement; distinct from the MPC orbit record.", "source_refs": [ "AIBD-0146-source-0004" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0146-source-0001", "AIBD-0146-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The Minor Planet Center publishes the observations and orbit. The University of Washington identifies HelioLinc3D as the discovery software. The circular is an astronomical record." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "HelioLinc3D linked sparse ATLAS detections into PHA 2022 SF289, published by the Minor Planet Center in MPEC 2023-O26 (Jul 2023).", "account": "On 18 July 2023 the HelioLinc3D linking algorithm identified an unrecognized near-Earth asteroid, 2022 SF289. It was a test on archival data from the NASA-funded ATLAS survey operated by the University of Hawaii (UH). HelioLinc3D was developed by Ari Heinze and colleagues at the University of Washington's (UW) DiRAC Institute for the Vera C. Rubin Observatory. ATLAS had first imaged the object on 19 September 2022 and observed it three times across four nights. Conventional discovery requires more same-night detections. The Minor Planet Center (MPC) published the object in MPEC 2023-O26, issued 18 July 2023. It is an Apollo-type potentially hazardous asteroid about 600 feet across with an Earth MOID of 0.0015 AU and no foreseeable risk to Earth. The sources call HelioLinc3D an algorithm, not a learned model." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "HelioLinc3D (heliocentric linking algorithm for Rubin Observatory solar-system processing)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Washington DiRAC Institute / Rubin Observatory (Ari Heinze, Siegfried Eggl, Mario Juric)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "HelioLinc3D identifies potentially hazardous asteroid 2022 SF289 from sparse ATLAS detections", "headline": "HelioLinc3D finds asteroid 2022 SF289 in sparse ATLAS detections" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e5c3b3a731212ce81da6de652bc2850343bf892504226b1fa540bdeeddeb41f6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 18 July 2023 the HelioLinc3D linking algorithm identified an unrecognized near-Earth asteroid, 2022 SF289. It was a test on archival data from the NASA-funded ATLAS survey operated by the University of Hawaii (UH). HelioLinc3D was developed by Ari Heinze and colleagues at the University of Washington's (UW) DiRAC Institute for the Vera C. Rubin Observatory. ATLAS had first imaged the object on 19 September 2022 and observed it three times across four nights. Conventional discovery requires more same-night detections. The Minor Planet Center (MPC) published the object in MPEC 2023-O26, issued 18 July 2023. It is an Apollo-type potentially hazardous asteroid about 600 feet across with an Earth MOID of 0.0015 AU and no foreseeable risk to Earth. The sources call HelioLinc3D an algorithm, not a learned model.", "replication": { "produced_by": [ "Survey detections too sparse per night for conventional linking", "Heliocentric linking across multiple nights", "Submission to and designation by the Minor Planet Center" ], "must_hold": [ "Astrometry from several nights must be precise enough to constrain a heliocentric orbit", "The Minor Planet Center must confirm the linkage as a new object" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 2, "record_mapped": 27, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0355", "title": "India's YES-TECH AI/ML yield estimates settle PMFBY crop-insurance claims, perhaps faster; Madhya Pradesh gives them 100% weight", "summary": "Launched 21 July 2023; nine states by Jan 2025; Madhya Pradesh 100% weightage from kharif 2023. PIB claims faster claims; CSE and DTE report lower payouts and rollback calls in three districts.", "date_observed": "2023-07-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested.", "system": "YES-TECH (Yield Estimation System based on Technology): satellite remote sensing, weather data and analytical models, including an 'AI/ML model' for kharif crops and a 'semi-physical model' for rabi crops in Madhya Pradesh", "model_version": null, "developer": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)", "deployer": "Government of Madhya Pradesh under PMFBY with insurers (AIC, SBI General Insurance, HDFC Ergo); nine states in all as of January 2025", "location": "Madhya Pradesh, India (CSE field assessment in Sehore, Vidisha and Bhopal districts)", "domain": "Agricultural crop insurance / yield estimation", "segment": "Government crop-insurance scheme (PMFBY)", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "Officials claim faster claim settlement without figures, while independent sources report lower payouts and rollback demands in three districts.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No verified individual outcome. CSE reports some farmers valuing faster disbursement and others reporting lower claims than losses." }, { "group": "organizational", "depth": null, "reason": "PIB claims faster settlement without figures. CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "depth": null, "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ], "ai_role": { "status": "assessed", "statement": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. No independent quantified beneficial outcome was found." }, "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ], "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "date": null, "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "model_version": null, "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] }, "paired_incident": null, "headline": "YES-TECH may speed PMFBY crop-insurance claims", "metric": "kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore", "comparator": { "against": "claims paid under manual crop-cutting experiments (2018)", "before": "R217.91 crore", "after": "R55.2 crore", "basis": "measured", "quote": "For instance, between 2018 and 2024, claim amounts disbursed in Bhopal, Sehore and Vidisha districts dropped from a total of R217.91 crore to R55.2 crore in the kharif season; and from R110.5 crore to just R9.28 crore in the rabi season.", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens" }, "later": { "status": "scaled", "date": "2025-01-01", "note": "By January 2025 nine states had adopted YES-TECH with Madhya Pradesh fully transitioned, per the PIB backgrounder of 14 February 2026; Down To Earth reports that Madhya Pradesh farmers and unions protested low payouts in 2024-25.", "quote": "As of January 2025, it has been adopted by nine states, with Madhya Pradesh fully transitioning to technology-based yield estimation, thereby enabling timely loss assessment and faster claim settlement.", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, two independent news reports and three press releases from the makers. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0355", "catalog_version": "1.0.0", "source_fingerprint": "8ab6dfa1e286704fc3aa3f673427f6be6cc4553446cd4c78058ac6bca2ace34b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0355-source-0001", "AIBD-0355-source-0002", "AIBD-0355-source-0003", "AIBD-0355-source-0004", "AIBD-0355-source-0005", "AIBD-0355-source-0006", "AIBD-0355-source-0007", "AIBD-0355-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)", "deployer": "Government of Madhya Pradesh under PMFBY with insurers (AIC, SBI General Insurance, HDFC Ergo); nine states in all as of January 2025" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. No independent quantified beneficial outcome was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "YES-TECH produced estimates of crop yields that Madhya Pradesh used to calculate insurance payments. The cited CSE presentation describes an AI or machine-learning model for kharif crops.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Official PIB documents (deployer, not the model's maker) state YES-TECH employs AI-driven analytics and that Madhya Pradesh relies fully on technology-based yield estimates. CSE's presentation says kharif yields come from an “AI/ML model” whose results are used to disburse claims. The model output thus directly determines payouts. Whether this produced a benefit is contested. PIB asserts faster, more transparent settlement without data. CSE and Down To Earth document reduced claims, protests and rollback calls among large soybean farmers in Sehore, Vidisha and Bhopal. They also record some farmers' appreciation of timeliness and insurers' claim that manual yields were under-reported. 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CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No verified individual outcome. 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Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Official accounts assert faster settlement without quantified supporting results. CSE and Down To Earth report both appreciation of prompt payments and complaints that the estimates reduced payouts. The sources do not establish an independently measured net benefit.", "editor_note": "" } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2025-01-01", "note": "By January 2025 nine states had adopted YES-TECH with Madhya Pradesh fully transitioned, per the PIB backgrounder of 14 February 2026; Down To Earth reports that Madhya Pradesh farmers and unions protested low payouts in 2024-25.", "quote": "As of January 2025, it has been adopted by nine states, with Madhya Pradesh fully transitioning to technology-based yield estimation, thereby enabling timely loss assessment and faster claim settlement.", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0355" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "Officials claim faster claim settlement without figures, while independent sources report lower payouts and rollback demands in three districts." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No verified individual outcome. CSE reports some farmers valuing faster disbursement and others reporting lower claims than losses." }, { "group": "organizational", "reason": "PIB claims faster settlement without figures. CSE records insurers' view that manual CCEs were manipulated and that YES-TECH removed that interface." }, { "group": "societal", "reason": "Adoption by nine states is stated, but no outcome at scale is documented. Down To Earth reports payouts in three districts fell sharply between 2018 and 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Madhya Pradesh, India (CSE field assessment in Sehore, Vidisha and Bhopal districts)", "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Estimate crop yields from satellite, weather and model data to replace or supplement manual crop-cutting experiments. The aim: insurance losses assessed accurately and claims paid on time. The claimed benefit (faster, more transparent settlement) is that purpose and is contested." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-07-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.downtoearth.org.in/agriculture/beyond-the-lens; https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ministry_of_Agriculture_%26_Farmers%27_Welfare; https://en.wikipedia.org/wiki/Government_of_Madhya_Pradesh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Agricultural crop insurance / yield estimation", "segment": "Government crop-insurance scheme (PMFBY)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0355-source-0001", "AIBD-0355-source-0002", "AIBD-0355-source-0003", "AIBD-0355-source-0004", "AIBD-0355-source-0005", "AIBD-0355-source-0006", "AIBD-0355-source-0007", "AIBD-0355-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau (2023). Centre launches Technological Advancements in Crop Insurance to Empowering Farmers and Streamlining Operations in PMFBY. Ministry of Agriculture and Farmers Welfare, 21 July 2023 (PRID 1941597).", "title": "Centre launches Technological Advancements in Crop Insurance (YES-Tech manual, WINDS portal, AIDE app)", "url": "https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=1941597", "date": "2023-07-21", "written_by": "makers", "quote": "YES-TECH Manual is a comprehensive guide developed after extensive testing and piloting in 100 districts of India." }, { "kind": "press release", "citation": "Press Information Bureau (2025). Pradhan Mantri Fasal Bima Yojana turns Nine. 17 February 2025 (PRID 2104175).", "title": "Pradhan Mantri Fasal Bima Yojana turns Nine", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2104175", "date": "2025-02-17", "written_by": "makers", "quote": "YES-TECH enables large scale adoption of technology-based yield estimates for yield loss and insurance claim assessments under PMFBY." }, { "kind": "press release", "citation": "Press Information Bureau (2026). Artificial Intelligence (AI) Transforming Indian Agriculture. PIB Backgrounder, 14 February 2026 (PressNoteDetails id 157351).", "title": "Artificial Intelligence (AI) Transforming Indian Agriculture (PIB Backgrounder)", "url": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3", "date": "2026-02-14", "written_by": "makers", "quote": "YES-TECH, CROPIC, and the PMFBY WhatsApp Chatbot are leveraging AI-enabled tools to make crop insurance under PMFBY more innovative, faster, and more transparent for farmers." }, { "kind": "report", "citation": "Mahaur, C. (2026). Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh. Centre for Science and Environment presentation (PDF), CSE webinar of 18 May 2026.", "title": "Implementation of Yield Estimation System Based on Technology (YES-TECH) in Madhya Pradesh", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Data is run into the 'AI/ML model' (kharif) and 'semi-physical model' (rabi) to estimate the yield or into a set of their merged parameters, if needed" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective slides.", "title": "Implementation of YES-TECH in Madhya Pradesh (farmers' perspective)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Large soybean farmers expressed dissatisfaction with shift to YES-TECH, reporting decline in claims received compared to manual CCEs" }, { "kind": "report", "citation": "Mahaur, C. (2026). Same CSE presentation, farmers' perspective (2/2).", "title": "Implementation of YES-TECH in Madhya Pradesh (timeliness)", "url": "https://cdn.cseindia.org/attachments/0.70726700_1779095588_yestech.pdf", "date": "2026-05-18", "written_by": "independent", "quote": "Some farmers expressed satisfaction - they appreciated the timeliness of claim disbursement compared earlier settlement time" }, { "kind": "news report", "citation": "Mahaur, C. (2026). Can technology make India's crop insurance payouts more accurate? Down To Earth, 27 May 2026.", "title": "Can technology make India's crop insurance payouts more accurate?", "url": "https://www.downtoearth.org.in/agriculture/can-technology-make-indias-crop-insurance-payouts-more-accurate", "date": "2026-05-27", "written_by": "independent", "quote": "Starting kharif 2023, Madhya Pradesh took the lead by adopting YES-TECH for select crops such as soybean, wheat and paddy" }, { "kind": "news report", "citation": "Mahaur, C. & Khurana, A. (2026). Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY. Down To Earth, 20 August 2026.", "title": "Beyond the Lens: Madhya Pradesh Farmers Struggle With Satellite-Based Crop Insurance Under PMFBY", "url": "https://www.downtoearth.org.in/agriculture/beyond-the-lens", "date": "2026-08-20", "written_by": "independent", "quote": "In 2024-25, farmers and unions in multiple districts of Madhya Pradesh mounted protests, claiming that insurance payouts were too low to cover their losses despite high premiums being paid." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Launched 21 July 2023; nine states by Jan 2025; Madhya Pradesh 100% weightage from kharif 2023. PIB claims faster claims; CSE and DTE report lower payouts and rollback calls in three districts.", "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "YES-TECH (Yield Estimation System based on Technology): satellite remote sensing, weather data and analytical models, including an 'AI/ML model' for kharif crops and a 'semi-physical model' for rabi crops in Madhya Pradesh" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Ministry of Agriculture and Farmers Welfare (YES-TECH manual); Madhya Pradesh implementation by the Madhya Pradesh Council of Science and Technology as Technology Implementation Partner, mentored by NRSC Hyderabad (per CSE)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "India's YES-TECH AI/ML yield estimates settle PMFBY crop-insurance claims, perhaps faster; Madhya Pradesh gives them 100% weight", "headline": "YES-TECH may speed PMFBY crop-insurance claims" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8ab6dfa1e286704fc3aa3f673427f6be6cc4553446cd4c78058ac6bca2ace34b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 21 July 2023 India's Ministry of Agriculture and Farmers Welfare launched the YES-TECH manual. It covers a technology-driven yield estimation system under the Pradhan Mantri Fasal Bima Yojana (PMFBY), piloted in 100 districts. It estimates yields at gram panchayat level for claim assessment. A Press Information Bureau (PIB) release of 17 February 2025 says YES-TECH was introduced from kharif 2023. It blends technology-based yield estimates with manual crop-cutting experiments (CCEs). A PIB backgrounder of 14 February 2026 says it uses remote sensing and AI-driven analytics. It was introduced for paddy and wheat in kharif 2023 and extended to soybean in kharif 2024 with a minimum 30 percent weightage. As of January 2025 nine states had adopted it, with Madhya Pradesh fully transitioning. The backgrounder says this enables timely loss assessment and faster claim settlement, without figures. A Centre for Science and Environment (CSE) presentation by Chhavi Mahaur (webinar of 18 May 2026) describes the Madhya Pradesh implementation. The Madhya Pradesh Council of Science and Technology (MPCST) runs it with NRSC Hyderabad. Satellite and weather data are run into a machine learning (ML) model (the “AI/ML model”) for kharif and a “semi-physical model” for rabi. Insurers use the results to disburse PMFBY claims. Madhya Pradesh is the only major state giving YES-TECH 100 percent weightage. CSE's field assessment covered some 50 farmers in Sehore, Vidisha and Bhopal. Large soybean farmers reported lower claims than under manual CCEs and some urged a rollback, while some appreciated faster disbursement. Insurers and officials blamed lower claims on historically under-reported manual yields. Down To Earth (20 August 2026) reports kharif payouts in the three districts fell from Rs 217.91 crore to Rs 55.2 crore over 2018–2024. Farmers and unions protested in 2024–25. No official document with a quantified beneficial outcome is among the sources.", "replication": { "produced_by": [ "A national YES-TECH manual and guidelines mandating technology-based yield estimates with at least 30 percent weightage", "A state Technology Implementation Partner (MPCST) running satellite, weather and ground-truth data through AI/ML and semi-physical models", "Ground-truthing points (130,989 in Madhya Pradesh as of August 2025, per CSE) and a YES-TECH committee reviewing periodic reports", "Insurers computing claims from estimated actual yield against threshold yield" ], "must_hold": [ "Accurate historical yield data, since threshold yields and model training depend on past CCE records (CSE)", "Open satellite data (Sentinel-1) and weather-station data availability", "Farmer trust and transparency about input data validation, which CSE found lacking in three districts", "State decision on weightage (100 percent in Madhya Pradesh, 30–50 percent elsewhere)" ], "echoes": [ { "setting": "Nine states adopting YES-TECH with minimum 30 percent weightage as of January 2025, per the PIB backgrounder; no outcomes reported", "outcome": "unknown", "source": "https://www.pib.gov.in/PressNoteDetails.aspx?id=157351&NoteId=157351&ModuleId=3" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0276", "title": "Bradford facial-recognition AI may have identified the de Brecy Tondo as a Raphael; the painting goes on show", "summary": "Ugail's deep-learning comparison found 97% facial similarity with the Sistine Madonna; Cartwright Hall showed the Tondo July 2023-Jan 2024; Raphael scholars call it a copy; Art Recognition says not.", "date_observed": "2023-07-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Hassan Ugail (University of Bradford) led a facial-recognition deep-learning comparison with University of Nottingham colleagues. It was reported on 26 January 2023 (Artforum). It found 97% similarity between the Madonna of the de Brecy Tondo and Raphael's Sistine Madonna, and 86% for the child. Ugail said the two “are undoubtedly by the same artist” (BBC, 25 July 2023). The painting, owned by the de Brecy Trust, went on public display at Cartwright Hall Art Gallery, Bradford, from July 2023. The display was extended “due to popular demand” to 3 January 2024, per Bradford Museums' own page. That page calls it “a mystery painting found to be undoubtedly by Raphael”. The Art Newspaper (26 July 2023) quoted Raphael scholars rejecting the attribution. An anonymous specialist said “The picture is clearly a copy from the 19th century”. Angelamaria Aceto (Ashmolean) would not support an AI-based assessment. Artnet (18 September 2023) reported that Art Recognition's model found with 85% probability that the Tondo was not painted by Raphael. The same company had earlier asserted with 92% certainty that the National Gallery's Samson and Delilah might not be by Rubens. No source on record shows a museum or auction house accepting an AI attribution. The AI finding was reported on 26 January 2023.", "category": "benefit created", "unexpected": false, "purpose": "Test whether facial features in a disputed painting match those in an authenticated Raphael", "system": "University of Bradford facial-recognition deep-learning comparison (Hassan Ugail); contrasted with Art Recognition's authentication model", "model_version": null, "developer": "University of Bradford and University of Nottingham team (Ugail); Art Recognition AG (Carina Popovici)", "deployer": "de Brecy Trust; Bradford Museums & Galleries (Cartwright Hall Art Gallery)", "location": "Bradford, England, UK", "domain": "Cultural heritage; art attribution", "segment": "Museum visitors and the painting's owners", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The Raphael attribution is rejected by named scholars and a second AI system, so the only realized outcome is a public exhibition.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary." }, { "group": "organizational", "depth": 1, "reason": "Bradford Museums exhibited the painting as a possible Raphael and extended the display “due to popular demand”." }, { "group": "societal", "depth": null, "reason": "The attribution is not accepted by scholars or institutions." } ], "ai_role": { "status": "unassessed", "statement": "Bradford's model produced the similarity figures that underpinned the “undoubtedly Raphael” claim and the exhibition. Raphael scholars reject the attribution. Art Recognition's model gives 85% probability against Raphael. The evidence is press reporting and the deployer's own page. No peer-reviewed report of the Tondo analysis and no institutional acceptance was found." }, "evidence": [ { "kind": "news report", "citation": "BBC News, 25 Jul 2023", "title": "Lost Raphael masterpiece goes on show in Bradford in UK first", "url": "https://www.bbc.co.uk/news/uk-england-leeds-66291225", "date": "2023-07-25", "written_by": "independent", "quote": "the Tondo and the Sistine Madonna are undoubtedly by the same artist" }, { "kind": "news report", "citation": "The Art Newspaper, 26 Jul 2023", "title": "'Clearly a copy from the 19th century'-Old Masters scholars reject AI-attributed Raphael", "url": "https://www.theartnewspaper.com/2023/07/26/clearly-a-copy-from-the-19th-centuryold-masters-scholars-reject-ai-attributed-raphael", "date": "2023-07-26", "written_by": "independent", "quote": "The picture is clearly a copy from the 19th century." }, { "kind": "news report", "citation": "Artnet News, 18 Sep 2023", "title": "Two A.I. Models Set Out to Authenticate a Raphael Painting and Got Different Results, Casting Doubt on the Technology's Future", "url": "https://news.artnet.com/art-world/ai-art-authentication-will-not-replace-humans-2340290", "date": "2023-09-18", "written_by": "independent", "quote": "found with 85 percent probability that the de Brecy Tondo was not painted by Raphael." }, { "kind": "press release", "citation": "Bradford Museums & Galleries event page", "title": "The de Brecy Tondo", "url": "https://www.bradfordmuseums.org/whats-on/the-de-brecy-tondo", "date": null, "written_by": "deployer", "quote": "a mystery painting found to be 'undoubtedly' by Raphael." }, { "kind": "other", "citation": "Art Recognition AG (n.d.). Raphael and the de Brécy Tondo Madonna: When One AI Gets Ahead of the Evidence. Case study.", "title": "Raphael and the de Brécy Tondo Madonna: When One AI Gets Ahead of the Evidence", "url": "https://art-recognition.com/case-studies/raphael-the-brecy-tondo/", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Deep-learning facial-feature comparison between the Tondo and the Sistine Madonna", "Public exhibition by a municipal gallery" ], "must_hold": [ "Scholarly acceptance of AI attribution (absent)", "Agreement between independent AI authentication models (absent)" ], "echoes": [ { "date": "2023-09-18", "setting": "Art Recognition model applied to the same painting", "model_version": null, "outcome": "did not recur", "source": "https://news.artnet.com/art-world/ai-art-authentication-will-not-replace-humans-2340290" }, { "date": null, "setting": "Art Recognition claim that the National Gallery's Samson and Delilah might not be by Rubens; no institutional acceptance located", "model_version": null, "outcome": "did not recur", "source": "https://news.artnet.com/art-world/ai-art-authentication-will-not-replace-humans-2340290" } ] }, "paired_incident": null, "headline": "Bradford AI may have identified the de Brecy Tondo as a Raphael", "metric": "97% facial similarity with the Sistine Madonna", "comparator": null, "later": { "status": "reversed", "date": "2023-09-18", "note": "Raphael scholars quoted by The Art Newspaper the day after the display opened called the painting a 19th-century copy, and in September 2023 (reported by Artnet on 18 September) the rival authentication firm Art Recognition said its model classified the Tondo as not by Raphael with 85 percent probability; no museum or auction house accepted the attribution.", "quote": "Our model classified the painting as not autograph by Raphael, with an 85 percent probability.", "url": "https://art-recognition.com/case-studies/raphael-the-brecy-tondo/" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://art-recognition.com/case-studies/raphael-the-brecy-tondo/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Bradford; https://www.debrecy.org.uk/community/press_photo_download", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' other and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0276", "catalog_version": "1.0.0", "source_fingerprint": "1fd297a79151c946bf8dcc227acc54176b4aed494ecd8eb5d22804920cc3ae53", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0276-source-0001", "AIBD-0276-source-0002", "AIBD-0276-source-0003", "AIBD-0276-source-0004", "AIBD-0276-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Bradford and University of Nottingham team (Ugail); Art Recognition AG (Carina Popovici)", "deployer": "de Brecy Trust; Bradford Museums & Galleries (Cartwright Hall Art Gallery)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "Bradford's model produced the similarity figures that underpinned the “undoubtedly Raphael” claim and the exhibition. Raphael scholars reject the attribution. Art Recognition's model gives 85% probability against Raphael. The evidence is press reporting and the deployer's own page. No peer-reviewed report of the Tondo analysis and no institutional acceptance was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary." }, { "group": "organizational", "depth": 1, "reason": "Bradford Museums exhibited the painting as a possible Raphael and extended the display “due to popular demand”." }, { "group": "societal", "reason": "The attribution is not accepted by scholars or institutions." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports, the makers' other and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary." }, { "group": "organizational", "depth": 1, "reason": "Bradford Museums exhibited the painting as a possible Raphael and extended the display “due to popular demand”." }, { "group": "societal", "reason": "The attribution is not accepted by scholars or institutions." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD 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It was reported on 26 January 2023 (Artforum). It found 97% similarity between the Madonna of the de Brecy Tondo and Raphael's Sistine Madonna, and 86% for the child. Ugail said the two “are undoubtedly by the same artist” (BBC, 25 July 2023). The painting, owned by the de Brecy Trust, went on public display at Cartwright Hall Art Gallery, Bradford, from July 2023. The display was extended “due to popular demand” to 3 January 2024, per Bradford Museums' own page. That page calls it “a mystery painting found to be undoubtedly by Raphael”. The Art Newspaper (26 July 2023) quoted Raphael scholars rejecting the attribution. An anonymous specialist said “The picture is clearly a copy from the 19th century”. Angelamaria Aceto (Ashmolean) would not support an AI-based assessment. Artnet (18 September 2023) reported that Art Recognition's model found with 85% probability that the Tondo was not painted by Raphael. The same company had earlier asserted with 92% certainty that the National Gallery's Samson and Delilah might not be by Rubens. No source on record shows a museum or auction house accepting an AI attribution. The AI finding was reported on 26 January 2023." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "University of Bradford facial-recognition deep-learning comparison (Hassan Ugail); contrasted with Art Recognition's authentication model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Bradford and University of Nottingham team (Ugail); Art Recognition AG (Carina Popovici)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Bradford facial-recognition AI may have identified the de Brecy Tondo as a Raphael; the painting goes on show", "headline": "Bradford AI may have identified the de Brecy Tondo as a Raphael" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1fd297a79151c946bf8dcc227acc54176b4aed494ecd8eb5d22804920cc3ae53" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Hassan Ugail (University of Bradford) led a facial-recognition deep-learning comparison with University of Nottingham colleagues. It was reported on 26 January 2023 (Artforum). It found 97% similarity between the Madonna of the de Brecy Tondo and Raphael's Sistine Madonna, and 86% for the child. Ugail said the two “are undoubtedly by the same artist” (BBC, 25 July 2023). The painting, owned by the de Brecy Trust, went on public display at Cartwright Hall Art Gallery, Bradford, from July 2023. The display was extended “due to popular demand” to 3 January 2024, per Bradford Museums' own page. That page calls it “a mystery painting found to be undoubtedly by Raphael”. The Art Newspaper (26 July 2023) quoted Raphael scholars rejecting the attribution. An anonymous specialist said “The picture is clearly a copy from the 19th century”. Angelamaria Aceto (Ashmolean) would not support an AI-based assessment. Artnet (18 September 2023) reported that Art Recognition's model found with 85% probability that the Tondo was not painted by Raphael. The same company had earlier asserted with 92% certainty that the National Gallery's Samson and Delilah might not be by Rubens. No source on record shows a museum or auction house accepting an AI attribution. The AI finding was reported on 26 January 2023.", "replication": { "produced_by": [ "Deep-learning facial-feature comparison between the Tondo and the Sistine Madonna", "Public exhibition by a municipal gallery" ], "must_hold": [ "Scholarly acceptance of AI attribution (absent)", "Agreement between independent AI authentication models (absent)" ], "echoes": [ { "date": "2023-09-18", "setting": "Art Recognition model applied to the same painting", "outcome": "did not recur", "source": "https://news.artnet.com/art-world/ai-art-authentication-will-not-replace-humans-2340290" }, { "setting": "Art Recognition claim that the National Gallery's Samson and Delilah might not be by Rubens; no institutional acceptance located", "outcome": "did not recur", "source": "https://news.artnet.com/art-world/ai-art-authentication-will-not-replace-humans-2340290" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0118", "title": "Double neural bypass restores arm movement and touch for Keith Thomas, paralyzed since a 2020 diving accident", "summary": "Keith Thomas, paralyzed since 2020, regained arm movement and touch after a 15-hour brain-implant operation in Manhasset, New York.", "date_observed": "2023-07-28", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 9 March 2023, surgeons led by Ashesh Mehta and Netanel Ben-Shalom implanted five microelectrode arrays in the brain of Keith Thomas, 45. The 15-hour operation was at North Shore University Hospital. A diving accident on 18 July 2020 had paralyzed him from the chest down. The Feinstein Institutes' double neural bypass decodes his movement intentions with recurrent neural networks and reinforcement learning. It pairs them with patterned spinal cord stimulation and restores touch by cortical microstimulation. By 28 July 2023 he could move his arms at will and feel his sister's hand. The Feinstein release of 16 July 2026 on the Nature Medicine paper reports 86% and 62% arm-strength gains, self-feeding and gains persisting beyond two years. The original paper distinguishes the earlier arm-strength gains from the AI-controlled hand tasks. Its grasp-force comparison reports 87% success with reinforcement learning and 27% without it.", "category": "benefit created", "unexpected": false, "purpose": "ClinicalTrials.gov NCT03680872 describes an early feasibility trial of the Bidirectional Neural Bypass System. It is meant to restore movement and sensation in the hand and wrist of up to seven people with tetraplegia. This benefit is that purpose.", "system": "Double neural bypass (Bidirectional Neural Bypass System): intracortical brain-computer interface with an LSTM decoder and deep reinforcement-learning agent, patterned spinal cord stimulation and intracortical microstimulation", "model_version": null, "developer": "Feinstein Institutes for Medical Research, Northwell Health (Institute of Bioelectronic Medicine, Chad Bouton)", "deployer": "Northwell Health, North Shore University Hospital", "location": "Manhasset, United States", "domain": "Healthcare (neuroprosthetics and spinal cord injury)", "segment": "Complete cervical spinal cord injury (C4 sensory/C5 motor tetraplegia)", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-07-28-1c4b" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "In the laboratory, Thomas used AI-decoded intent to control grasping, including self-feeding, alongside spinal stimulation and sensory feedback. This restored meaningful abilities in one person. The study does not isolate every component’s contribution." } ], "ai_role": { "status": "assessed", "statement": "The decoder turns motor-cortex activity into intended hand movements. A reinforcement-learning agent regulates grasp force: figure 4c of the original paper reports 87% task success with the agent and 27% without it. The separate 86% and 62% arm-strength gains occurred during spinal stimulation and activity-based training before the hand neuroprosthesis. The full system combines AI with surgery, stimulation, an orthosis, and rehabilitation. The paper anonymizes its participant; Northwell identifies him as Keith Thomas." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Chandrasekaran S, Wandelt SK, Jangam A, et al. (2026). A neuroprosthesis for restoring hand movement and sensation in a person with complete tetraplegia. Nature Medicine 32(7):2591–2601. Figure 4c reports the comparison with and without reinforcement learning; figure 2 concerns earlier spinal stimulation and training.", "title": "A neuroprosthesis for restoring hand movement and sensation in a person with complete tetraplegia", "url": "https://doi.org/10.1038/s41591-026-04498-0", "date": "2026-07-16", "written_by": "makers", "quote": "87% success with RL and 27% success without RL" }, { "kind": "news report", "citation": "Barmash J. / Patch Massapequa (2023). Inspirational Quadraplegic Massapequa Man In 'Amazing' Clinical Trial. Patch.", "title": "Inspirational Quadraplegic Massapequa Man In 'Amazing' Clinical Trial", "url": "https://patch.com/new-york/massapequa/inspirational-quadraplegic-massapequa-man-amazing-clinical-trial", "date": "2023-08-09", "written_by": "independent", "quote": "Mobility in my right arm has increased by 110% compared to my baseline that I started with" }, { "kind": "press release", "citation": "Feinstein Institutes for Medical Research / Northwell Health (August 2024). Double Neural Bypass Update: Bites Transcript. Institutional interview transcript, pp. 1–2.", "title": "Double Neural Bypass Update: Bites Transcript", "url": "https://msnewsroommedia.s3.amazonaws.com/mcp/northwell/neuralbypass/03-2024/3-Soundbites_Script%20%28New_Aug._2024%29/Double%20Neural%20Bypass%20Update%20-%20Bites%20Transcript.pdf", "date": null, "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "Libassi M. / Feinstein Institutes for Medical Research (2023). Feinstein Institutes researchers first to use double neural bypass to restore feeling, movement in man living with quadriplegia. Northwell Health news release.", "title": "Feinstein Institutes researchers first to use double neural bypass to restore feeling, movement in man living with quadriplegia", "url": "https://msnewsroommedia.s3.amazonaws.com/mcp/northwell/neuralbypass/02-2023/2023_Press_Release/DoubleNeuralBypass_Release.pdf", "date": "2023-07-28", "written_by": "makers", "quote": "Paralyzed from the chest down, Keith Thomas, 45, of Massapequa, NY, is the first human to use the technology." }, { "kind": "press release", "citation": "Libassi M. / Feinstein Institutes for Medical Research (2026). Feinstein Institutes technology that restores movement and sensation after paralysis featured in Nature Medicine. Northwell Health news release.", "title": "Feinstein Institutes technology that restores movement and sensation after paralysis featured in Nature Medicine", "url": "https://northwell.multimedia-newsroom.com/index.php/2026/07/16/paralyzed-man-has-feeling-lasting-movement-restored-in-hand/", "date": "2026-07-16", "written_by": "makers", "quote": "Over 35 weeks of this intervention, Mr. Thomas achieved statistically significant increases of 86% in right arm strength and 62% in left arm strength." }, { "kind": "dataset", "citation": "Bouton C / Northwell Health. Restoring Motor and Sensory Hand Function in Tetraplegia Using a Neural Bypass System. ClinicalTrials.gov NCT03680872, first posted September 21, 2018, updated March 11, 2026. Sponsor-submitted registration; not a regulatory finding of benefit.", "title": "Restoring Motor and Sensory Hand Function in Tetraplegia Using a Neural Bypass System", "url": "https://clinicaltrials.gov/study/NCT03680872", "date": "2018-09-21", "written_by": "makers", "quote": "an investigational device called the Bidirectional Neural Bypass System can lead to the restoration of movement and sensation in the hand and wrist of up to seven individuals with tetraplegia" } ], "replication": { "produced_by": [ "Chronic complete cervical spinal cord injury (C4 sensory/C5 motor) with movement intentions still readable from motor cortex", "Five microelectrode arrays placed in motor and somatosensory cortex during a 15-hour mapped operation with the participant partly awake", "An LSTM plus deep reinforcement-learning decoder paired with patterned spinal cord stimulation and intracortical microstimulation", "Thirty-five weeks of supervised laboratory sessions inside an approved early-feasibility trial (NCT03680872)" ], "must_hold": [ "Decoder accuracy sustained over months (84.6% over five months) so intended movements reliably trigger stimulation", "Neurosurgical, engineering and rehabilitation teams present throughout. The gains were measured in the laboratory", "Follow-up with the system switched off to confirm that strength and sensation gains persist" ], "echoes": [] }, "paired_incident": null, "headline": "Double neural bypass restores Keith Thomas's movement and touch", "metric": "87% vs 27% successful grasp-force control with and without reinforcement learning", "comparator": { "against": "Grasp-force control with the reinforcement-learning agent switched off, in the same participant", "before": "27% successful force control without the reinforcement-learning agent", "after": "87% successful force control with the reinforcement-learning agent", "basis": "measured", "quote": "87% success with RL and 27% success without RL", "url": "https://doi.org/10.1038/s41591-026-04498-0" }, "later": { "status": "persisted", "date": "2026-07-16", "note": "The Feinstein Institutes' July 2026 release on the Nature Medicine paper reports that the strength and sensation gains were still present at a follow-up more than two years later.", "quote": "“Remarkably, in a recent follow up, it was found these gains were still present after more than two years. This is incredibly encouraging,” said Dr. Bouton.", "url": "https://northwell.multimedia-newsroom.com/index.php/2026/07/16/paralyzed-man-has-feeling-lasting-movement-restored-in-hand/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-07-28-1c4b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://doi.org/10.1038/s41591-026-04498-0; https://feinstein.northwell.edu/news/the-latest/double-neural-bypass-technology-featured-on-cover-of-nature-medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Feinstein_Institutes_for_Medical_Research; https://en.wikipedia.org/wiki/Northwell_Health", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original paper, extended data, supplementary information, reporting summary, sponsor registration, original releases and firsthand interviews. Separated spinal-stimulation strength gains from the direct AI grasp-control comparison. Corrected the sponsor-submitted registry from independent regulatory evidence to a maker-authored dataset. Replaced the derivative one-year news account with the original institutional interview transcript. Retained Patch’s separate patient/researcher interviews. The original 2023 publication date remains unchanged.", "source": "https://doi.org/10.1038/s41591-026-04498-0", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study, the makers' dataset and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0118", "catalog_version": "1.0.0", "source_fingerprint": "0e65c8e90f1a2cb021bc98811b6fa50aaa89cf4801bb2c5f5676c66e38ecc9e8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0118-source-0001", "AIBD-0118-source-0002", "AIBD-0118-source-0003", "AIBD-0118-source-0004", "AIBD-0118-source-0005", "AIBD-0118-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Feinstein Institutes for Medical Research, Northwell Health (Institute of Bioelectronic Medicine, Chad Bouton)", "deployer": "Northwell Health, North Shore University Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The decoder turns motor-cortex activity into intended hand movements. 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Feinstein Institutes researchers first to use double neural bypass to restore feeling, movement in man living with quadriplegia. Northwell Health news release.", "title": "Feinstein Institutes researchers first to use double neural bypass to restore feeling, movement in man living with quadriplegia", "url": "https://msnewsroommedia.s3.amazonaws.com/mcp/northwell/neuralbypass/02-2023/2023_Press_Release/DoubleNeuralBypass_Release.pdf", "date": "2023-07-28", "written_by": "makers", "quote": "Paralyzed from the chest down, Keith Thomas, 45, of Massapequa, NY, is the first human to use the technology." }, { "kind": "press release", "citation": "Libassi M. / Feinstein Institutes for Medical Research (2026). Feinstein Institutes technology that restores movement and sensation after paralysis featured in Nature Medicine. 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Sponsor-submitted registration; not a regulatory finding of benefit.", "title": "Restoring Motor and Sensory Hand Function in Tetraplegia Using a Neural Bypass System", "url": "https://clinicaltrials.gov/study/NCT03680872", "date": "2018-09-21", "written_by": "makers", "quote": "an investigational device called the Bidirectional Neural Bypass System can lead to the restoration of movement and sensation in the hand and wrist of up to seven individuals with tetraplegia" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. 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Peer review is not an independent replication." }, { "source_refs": [ "AIBD-0118-source-0002" ], "url": "https://patch.com/new-york/massapequa/inspirational-quadraplegic-massapequa-man-amazing-clinical-trial", "relationship": "Original 2023 interviews with Thomas and investigator Chandrasekaran add firsthand experience. The patient’s 110% statement is not the paper’s later clinical metric." }, { "source_refs": [ "AIBD-0118-source-0003" ], "url": "https://msnewsroommedia.s3.amazonaws.com/mcp/northwell/neuralbypass/03-2024/3-Soundbites_Script%20%28New_Aug._2024%29/Double%20Neural%20Bypass%20Update%20-%20Bites%20Transcript.pdf", "relationship": "Original institutional interview transcript for the 2024 follow-up. Read from the media kit linked by Northwell’s 2026 page." }, { "source_refs": [ "AIBD-0118-source-0004" ], "url": "https://msnewsroommedia.s3.amazonaws.com/mcp/northwell/neuralbypass/02-2023/2023_Press_Release/DoubleNeuralBypass_Release.pdf", "relationship": "Original July 28, 2023 release PDF, recovered from the institutional media kit. Establishes the named participant, accident and surgery dates, and original announcement." }, { "source_refs": [ "AIBD-0118-source-0005" ], "url": "https://northwell.multimedia-newsroom.com/index.php/2026/07/16/paralyzed-man-has-feeling-lasting-movement-restored-in-hand/", "relationship": "Original institutional 2026 report identifies the anonymized paper participant and adds the investigator’s report of persistence beyond two years." }, { "source_refs": [ "AIBD-0118-source-0006" ], "url": "https://clinicaltrials.gov/study/NCT03680872", "relationship": "Sponsor-investigator registration accessed through the ClinicalTrials.gov API. Establishes protocol and planned enrollment, not regulatory confirmation or independent benefit evidence." } ], "excluded_republications": [ { "url": "https://www.foxnews.com/health/man-paralyzed-diving-mishap-medical-miracle-year-after-ai-powered-brain-implant", "relationship": "The material one-year follow-up claims are available in the original Northwell interview transcript. This report does not independently test the clinical result." } ], "embedded_material_reviewed": [ { "url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41591-026-04498-0/MediaObjects/41591_2026_4498_MOESM1_ESM.pdf", "extent": "Supplementary table 1 and video descriptions read; the videos themselves were not reviewed." }, { "url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41591-026-04498-0/MediaObjects/41591_2026_4498_MOESM2_ESM.pdf", "extent": "Reporting summary pp. 2–3 visually reviewed: one participant, no randomization, no investigator blinding, data collection 2021–2025." }, { "url": "https://clinicaltrials.gov/api/v2/studies/NCT03680872", "extent": "Protocol and sponsor identity read." }, { "url": "https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1210328/full", "extent": "Reference 16 checked: earlier spinal-stimulation method study with two different participants, not independent corroboration of Thomas’s AI-assisted tasks." } ], "limitations": [ "One participant, with repeated sessions rather than independent replication.", "Data and code require author access; this review does not independently reproduce the analysis.", "The paper’s text and figure 4c caption differ on whether the reported t-test was paired. 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Data and code require author access. The text and figure 4c caption disagree on whether the t-test was paired, and the investigators’ report of two-year persistence has no independent evaluation.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Keith Thomas, paralyzed since 2020, regained arm movement and touch after a 15-hour brain-implant operation in Manhasset, New York.", "account": "On 9 March 2023, surgeons led by Ashesh Mehta and Netanel Ben-Shalom implanted five microelectrode arrays in the brain of Keith Thomas, 45. The 15-hour operation was at North Shore University Hospital. A diving accident on 18 July 2020 had paralyzed him from the chest down. The Feinstein Institutes' double neural bypass decodes his movement intentions with recurrent neural networks and reinforcement learning. It pairs them with patterned spinal cord stimulation and restores touch by cortical microstimulation. By 28 July 2023 he could move his arms at will and feel his sister's hand. The Feinstein release of 16 July 2026 on the Nature Medicine paper reports 86% and 62% arm-strength gains, self-feeding and gains persisting beyond two years. The original paper distinguishes the earlier arm-strength gains from the AI-controlled hand tasks. Its grasp-force comparison reports 87% success with reinforcement learning and 27% without it." } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. 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The 15-hour operation was at North Shore University Hospital. A diving accident on 18 July 2020 had paralyzed him from the chest down. The Feinstein Institutes' double neural bypass decodes his movement intentions with recurrent neural networks and reinforcement learning. It pairs them with patterned spinal cord stimulation and restores touch by cortical microstimulation. By 28 July 2023 he could move his arms at will and feel his sister's hand. The Feinstein release of 16 July 2026 on the Nature Medicine paper reports 86% and 62% arm-strength gains, self-feeding and gains persisting beyond two years. The original paper distinguishes the earlier arm-strength gains from the AI-controlled hand tasks. Its grasp-force comparison reports 87% success with reinforcement learning and 27% without it.", "replication": { "produced_by": [ "Chronic complete cervical spinal cord injury (C4 sensory/C5 motor) with movement intentions still readable from motor cortex", "Five microelectrode arrays placed in motor and somatosensory cortex during a 15-hour mapped operation with the participant partly awake", "An LSTM plus deep reinforcement-learning decoder paired with patterned spinal cord stimulation and intracortical microstimulation", "Thirty-five weeks of supervised laboratory sessions inside an approved early-feasibility trial (NCT03680872)" ], "must_hold": [ "Decoder accuracy sustained over months (84.6% over five months) so intended movements reliably trigger stimulation", "Neurosurgical, engineering and rehabilitation teams present throughout. The gains were measured in the laboratory", "Follow-up with the system switched off to confirm that strength and sensation gains persist" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected fields after reading the original evidence and its source lineage. Other field assessments are preserved.", "record_fields": [ "account" ], "source_refs": [ "AIBD-0118-source-0001", "AIBD-0118-source-0002", "AIBD-0118-source-0003", "AIBD-0118-source-0004", "AIBD-0118-source-0005", "AIBD-0118-source-0006" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 2, "record_mapped": 28, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0002", "title": "Intracortical speech neuroprosthesis restores conversation for a man with ALS (UC Davis, BrainGate2)", "summary": "Four 64-electrode arrays plus RNN decoder let Casey Harrell (ALS) converse at 97.5% accuracy; later 1.96 million words at home", "date_observed": "2023-08-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At the University of California Davis, a 45-year-old man with amyotrophic lateral sclerosis and severe dysarthria took part in the BrainGate2 trial (NCT00912041). Press identify him as Casey Harrell. Four 64-electrode arrays were implanted in his left precentral gyrus in July 2023. From August 2023, a decoder predicting phonemes every 80 ms, with language models over a 125,000-word vocabulary, converted his attempted speech to text. Accuracy was 99.6% with a 50-word vocabulary on day one and 90.2% with the full vocabulary on day two. It was 97.5% sustained over 248 hours of self-paced conversation with family, friends and colleagues (Card et al., NEJM, August 2024). The paper gives only the month for the first session, so 1 August 2023 is used.", "category": "benefit created", "unexpected": false, "purpose": "Built to restore communication by decoding attempted speech from intracortical activity into text. Conversational communication was the intended benefit and is what occurred.", "system": "UC Davis intracortical speech neuroprosthesis (BrainGate2 trial)", "model_version": "Four 64-electrode microelectrode arrays (256 electrodes) in the left precentral gyrus; phoneme decoder with an openly available language model assembling phonemes into words and two further open-source language models producing the sentence, over a 125,000-word vocabulary", "developer": "UC Davis Neuroprosthetics Lab (Brandman, Stavisky) with the BrainGate consortium", "deployer": "UC Davis Health", "location": "Davis, United States", "domain": "Healthcare / assistive communication", "segment": "ALS with severe dysarthria", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-06-15-4dfc" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "Life-changing benefit to one identifiable person: conversational communication with family and colleagues was restored. The 2026 follow-up documents over 3,800 hours of unsupervised home use, nearly two million words and continued full-time employment." } ], "ai_role": { "status": "assessed", "statement": "A neural-network decoder (phoneme prediction every 80 ms) combined with language models is the mechanism converting attempted speech into text. The benefit is attributable to the decoding system, with surgery and arrays as enabling hardware." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Card NS, Wairagkar M, Iacobacci C, et al. (2024). An Accurate and Rapidly Calibrating Speech Neuroprosthesis. N Engl J Med 391(7):609-618 (issue of 15 August 2024).", "title": "An Accurate and Rapidly Calibrating Speech Neuroprosthesis", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/", "date": "2024-08-15", "written_by": "makers", "quote": "With further training data, the neuroprosthesis sustained 97.5% accuracy for self-paced conversations for over 248 cumulative hours over 8.4 months after surgical implantation." }, { "kind": "peer-reviewed study", "citation": "Card NS, Singer-Clark T, Peracha H, et al. (2026). Long-term independent use of an intracortical brain-computer interface for speech and cursor control. Nature Medicine.", "title": "Long-term independent use of an intracortical brain-computer interface for speech and cursor control", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/", "date": "2026-06-15", "written_by": "makers", "quote": "Over nearly 2 years, the participant used the BCI for more than 3,800 h at home with no researchers present." }, { "kind": "news report", "citation": "Sanders L (2026). Brain implants are helping people who've lost their voice. Science News.", "title": "Brain implants are helping people who've lost their voice", "url": "https://www.sciencenews.org/article/brain-implants-restore-voices-injuries", "date": "2026-10-15", "written_by": "independent", "quote": "In 2023, Harrell had four small devices implanted on the left side of his brain." }, { "kind": "press release", "citation": "UC Davis Health (2024). New brain-computer interface allows man with ALS to 'speak' again. Institutional release republished by ScienceDaily.", "title": "New brain-computer interface allows man with ALS to 'speak' again", "url": "https://www.sciencedaily.com/releases/2024/08/240814170129.htm", "date": "2024-08-14", "written_by": "makers", "quote": "To develop the system, the team enrolled Casey Harrell, a 45-year-old man with ALS, in the BrainGate clinical trial." } ], "replication": { "produced_by": [ "Preserved speech-motor cortical activity during attempted speech despite severe dysarthria", "256-electrode intracortical recording in the ventral precentral gyrus", "Phoneme decoder plus large-vocabulary language models calibrated on the participant's own data within minutes", "Regulated trial setting (BrainGate2, NCT00912041) with ongoing research support" ], "must_hold": [ "Array signal quality remains stable over months to years", "Participant retains the ability to attempt speech and the cognition to operate the system", "Decoder recalibration available as neural signals drift" ], "echoes": [ { "date": "2025-06-12", "setting": "Same participant (T15), UC Davis: instantaneous voice synthesis from the same four 64-electrode arrays (256 electrodes), with neural processing from signal acquisition to speech synthesis within 10 ms, including intonation control and singing short melodies", "model_version": "Four 64-electrode arrays (256 electrodes); brain-to-voice model adapted from the Transformer architecture", "outcome": "recurred", "source": "Wairagkar M, Card NS, et al. (2025). An instantaneous voice-synthesis neuroprosthesis. Nature. https://pmc.ncbi.nlm.nih.gov/articles/PMC12369848/" }, { "date": "2026-06-15", "setting": "Same participant, at-home independent use over nearly two years: 183,060 sentences, 1,960,163 words, 56 words per minute, full-time employment maintained", "model_version": null, "outcome": "recurred", "source": "Card NS, et al. (2026). Long-term independent use of an intracortical brain-computer interface for speech and cursor control. Nature Medicine. https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "732", "title": "Whisper Speech-to-Text AI Reportedly Found to Create Violent Hallucinations", "url": "https://incidentdatabase.ai/cite/732", "severity": null, "group": "personal", "basis": "Both decode speech for people with impaired speech; Whisper fabricated words and violent phrases when transcribing impaired speech." }, "headline": "UC Davis neuroprosthesis restores conversation for Casey Harrell", "metric": "97.5% sustained accuracy over 248 hours of self-paced conversation", "comparator": null, "later": { "status": "persisted", "date": "2026-06-15", "note": "A Nature Medicine report covering nearly two years of unsupervised home use found the same participant communicated 1,960,163 words at 56 words per minute and kept full-time employment.", "quote": "Over nearly 2 years, the participant used the BCI for more than 3,800 h at home with no researchers present to maintain rich interpersonal communication with his family and friends, independently control his personal computer and sustain full-time employment—despite being paralyzed.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 732 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/732", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced the placeholder NEJM date with the 15 August 2024 issue date, restored the full 97.5% sentence, recounted the language models as one word-assembling model plus two further sentence-level models as the paper describes, and verified the 10 ms, Transformer and same-participant (T15) details of the 2025 voice-synthesis echo against the full text at PMC and the cited 2026 Nature Medicine paper, which says T15's clinical status was previously reported in the NEJM paper.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11328962/; https://pmc.ncbi.nlm.nih.gov/articles/PMC12369848/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Davis; https://health.ucdavis.edu/about/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, two peer-reviewed studies from the makers and the makers' press release. 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Institutional release republished by ScienceDaily.", "title": "New brain-computer interface allows man with ALS to 'speak' again", "url": "https://www.sciencedaily.com/releases/2024/08/240814170129.htm", "date": "2024-08-14", "written_by": "makers", "quote": "To develop the system, the team enrolled Casey Harrell, a 45-year-old man with ALS, in the BrainGate clinical trial." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0002-source-0001", "AIBD-0002-source-0002", "AIBD-0002-source-0003", "AIBD-0002-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Card NS, Wairagkar M, Iacobacci C, et al. 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Institutional release republished by ScienceDaily.", "title": "New brain-computer interface allows man with ALS to 'speak' again", "url": "https://www.sciencedaily.com/releases/2024/08/240814170129.htm", "date": "2024-08-14", "written_by": "makers", "quote": "To develop the system, the team enrolled Casey Harrell, a 45-year-old man with ALS, in the BrainGate clinical trial." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Four 64-electrode arrays plus RNN decoder let Casey Harrell (ALS) converse at 97.5% accuracy; later 1.96 million words at home", "account": "At the University of California Davis, a 45-year-old man with amyotrophic lateral sclerosis and severe dysarthria took part in the BrainGate2 trial (NCT00912041). Press identify him as Casey Harrell. Four 64-electrode arrays were implanted in his left precentral gyrus in July 2023. From August 2023, a decoder predicting phonemes every 80 ms, with language models over a 125,000-word vocabulary, converted his attempted speech to text. Accuracy was 99.6% with a 50-word vocabulary on day one and 90.2% with the full vocabulary on day two. It was 97.5% sustained over 248 hours of self-paced conversation with family, friends and colleagues (Card et al., NEJM, August 2024). The paper gives only the month for the first session, so 1 August 2023 is used." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The models translated attempted speech into text from cortical recordings." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Four arrays recorded signals from 256 electrodes in the left precentral gyrus. The language models used a vocabulary of 125,000 words." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The system converted cortical activity into phonemes, then words and sentences." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A decoder identifies phonemes. Three language models convert them into words and sentences." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Four 64-electrode microelectrode arrays (256 electrodes) in the left precentral gyrus; phoneme decoder with an openly available language model assembling phonemes into words and two further open-source language models producing the sentence, over a 125,000-word vocabulary" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UC Davis intracortical speech neuroprosthesis (BrainGate2 trial)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UC Davis Neuroprosthetics Lab (Brandman, Stavisky) with the BrainGate consortium" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Intracortical speech neuroprosthesis restores conversation for a man with ALS (UC Davis, BrainGate2)", "headline": "UC Davis neuroprosthesis restores conversation for Casey Harrell" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6a9f2d960f0e13b349fc546eda3f4f78295d1879369345d1a57c563f7d7bfbac" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At the University of California Davis, a 45-year-old man with amyotrophic lateral sclerosis and severe dysarthria took part in the BrainGate2 trial (NCT00912041). Press identify him as Casey Harrell. Four 64-electrode arrays were implanted in his left precentral gyrus in July 2023. From August 2023, a decoder predicting phonemes every 80 ms, with language models over a 125,000-word vocabulary, converted his attempted speech to text. Accuracy was 99.6% with a 50-word vocabulary on day one and 90.2% with the full vocabulary on day two. It was 97.5% sustained over 248 hours of self-paced conversation with family, friends and colleagues (Card et al., NEJM, August 2024). The paper gives only the month for the first session, so 1 August 2023 is used.", "replication": { "produced_by": [ "Preserved speech-motor cortical activity during attempted speech despite severe dysarthria", "256-electrode intracortical recording in the ventral precentral gyrus", "Phoneme decoder plus large-vocabulary language models calibrated on the participant's own data within minutes", "Regulated trial setting (BrainGate2, NCT00912041) with ongoing research support" ], "must_hold": [ "Array signal quality remains stable over months to years", "Participant retains the ability to attempt speech and the cognition to operate the system", "Decoder recalibration available as neural signals drift" ], "echoes": [ { "date": "2025-06-12", "setting": "Same participant (T15), UC Davis: instantaneous voice synthesis from the same four 64-electrode arrays (256 electrodes), with neural processing from signal acquisition to speech synthesis within 10 ms, including intonation control and singing short melodies", "model_version": "Four 64-electrode arrays (256 electrodes); brain-to-voice model adapted from the Transformer architecture", "outcome": "recurred", "source": "Wairagkar M, Card NS, et al. (2025). An instantaneous voice-synthesis neuroprosthesis. Nature. https://pmc.ncbi.nlm.nih.gov/articles/PMC12369848/" }, { "date": "2026-06-15", "setting": "Same participant, at-home independent use over nearly two years: 183,060 sentences, 1,960,163 words, 56 words per minute, full-time employment maintained", "outcome": "recurred", "source": "Card NS, et al. (2026). Long-term independent use of an intracortical brain-computer interface for speech and cursor control. Nature Medicine. https://pmc.ncbi.nlm.nih.gov/articles/PMC13375540/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0120", "title": "ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna; human operators verify it and Cal Fire holds the fire to under a quarter acre", "summary": "AI on Cleveland National Forest cameras flagged smoke at about 3 am on 5 August 2023; Cal Fire held the verified fire under a quarter acre.", "date_observed": "2023-08-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At about 3 am on 5 August 2023, the ALERTCalifornia AI flagged a column of smoke in the Cleveland National Forest near Mount Laguna. That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers.", "category": "protective response", "unexpected": false, "purpose": "The tool was built to spot smoke in ALERTCalifornia camera feeds and notify Cal Fire emergency command centers. Crews can then reach a fire in its incipient phase. This detection was that purpose.", "system": "ALERTCalifornia AI wildfire detection (machine-learned smoke and anomaly detection on the ALERTCalifornia pan-tilt-zoom camera network)", "model_version": null, "developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path", "deployer": "California Department of Forestry and Fire Protection (CAL FIRE)", "location": "Mount Laguna, California, United States", "domain": "Emergency services (wildfire detection and response)", "segment": "State fire agency using a university camera network", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-09-12-f6ac" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Cal Fire's Mount Laguna station received a verified alert at about 3 am. Its crews extinguished the fire at under a quarter acre. Cal Fire intelligence specialist Suzann Leininger says the system “is getting us time to react in a faster manner”." }, { "group": "societal", "depth": 2, "reason": "Residents, property and forest around Mount Laguna were spared a larger fire. Captain Yeary's statement that it “could have been a devastating fire” is a judgment, not a proven counterfactual." } ], "ai_role": { "status": "assessed", "statement": "The model's contribution was the detection. Its algorithm flagged a smoke column in a Cleveland National Forest camera feed at about 3 am. Human operators verified it before Cal Fire was alerted. The containment was done by Captain Yeary's crews. No source records whether a 911 call would have come later. The time gained is documented only for the program as a whole. TIME reports 77 fires identified before any 911 call in the first two months. UC San Diego's Neal Driscoll says the alerts beat 911 calls about 40 percent of the time. AFP also notes the system sometimes misreads dust, insects or weather as smoke. That is why the human verification step sits between the model and the dispatch." }, "evidence": [ { "kind": "news report", "citation": "Fonsegrives R. / AFP via Phys.org (2023). California firefighters use AI to battle wildfires. AFP wire report.", "title": "California firefighters use AI to battle wildfires", "url": "https://phys.org/news/2023-09-california-firefighters-ai-wildfires.html", "date": "2023-09-12", "written_by": "independent", "quote": "Had the AI not alerted us to it, it could have gotten much bigger" }, { "kind": "news report", "citation": "AFP via Asharq Al-Awsat English (2023). California Firefighters Use AI to Battle Wildfires. Same AFP wire text (not independent of the Phys.org copy).", "title": "California Firefighters Use AI to Battle Wildfires", "url": "https://english.aawsat.com/node/4540976", "date": "2023-09-12", "written_by": "independent", "quote": "Human operators were able to verify the machines were correct and alerted Yeary" }, { "kind": "news report", "citation": "AFP via France 24 (2023). California firefighters use AI to battle wildfires. Same AFP wire text (not independent).", "title": "California firefighters use AI to battle wildfires", "url": "https://www.france24.com/en/live-news/20230912-california-firefighters-use-ai-to-battle-wildfires", "date": "2023-09-12", "written_by": "independent", "quote": "We beat 911 calls about 40 percent of the time. And it's going to get better." }, { "kind": "news report", "citation": "Fonsegrives R. / AFP via Oman Observer (2023). Firefighters use AI to battle wildfires. Same AFP wire text (not independent).", "title": "Firefighters use AI to battle wildfires", "url": "https://www.omanobserver.om/article/1142729/opinion/firefighters-use-ai-to-battle-wildfires", "date": "2023-09-12", "written_by": "independent", "quote": "It's getting us time to react in a faster manner." }, { "kind": "press release", "citation": "CAL FIRE and ALERTCalifornia (2023). CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial. Agency press release, Sacramento.", "title": "CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial", "url": "https://alertcalifornia.org/cal-fire-and-university-of-california-san-diegos-alertcalifornia-program-join-forces-to-enhance-wildfire-response-with-artificial-intelligence-implementation-trial/", "date": "2023-07-10", "written_by": "makers", "quote": "a machine-learned model has been created to accurately differentiate between smoke and other particles in the air" }, { "kind": "news report", "citation": "Dixit P. / TIME (2023). AlertCalifornia and Cal Fire AI Wildfire Detector. The Best Inventions of 2023.", "title": "AlertCalifornia and Cal Fire AI Wildfire Detector", "url": "https://time.com/collection/best-inventions-2023/6327137/alertcalifornia-ai-wildfire-detector/", "date": "2023-10-24", "written_by": "independent", "quote": "In the first two months, the system had correctly identified 77 fires before any 911 calls came in." }, { "kind": "press release", "citation": "Scully C. / UC San Diego Today (2023). ALERTCalifornia and CAL FIRE's Fire Detection AI Program Named One of TIME's Best Inventions of 2023. University news release.", "title": "ALERTCalifornia and CAL FIRE's Fire Detection AI Program Named One of TIME's Best Inventions of 2023", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "date": "2023-10-24", "written_by": "makers", "quote": "The AI tool became available to all 21 CAL FIRE 911 Dispatch Centers in September 2023." }, { "kind": "news report", "citation": "Jennewein C. / Times of San Diego (2023). Time Magazine: California's AI Wildfire Detection System a Top Invention of 2023. Describes a second AI-first detection near Grass Valley on 11 September 2023.", "title": "Time Magazine: California's AI Wildfire Detection System a Top Invention of 2023", "url": "https://timesofsandiego.com/tech/2023/10/24/time-magazine-californias-ai-wildfire-detection-system-a-top-invention-of-2023/", "date": "2023-10-24", "written_by": "independent", "quote": "the first 911 call was not made until 6:01 a.m., and firefighters were already at the scene" }, { "kind": "press release", "citation": "ALERTCalifornia / UC San Diego (n.d.). Technology. Programme web page describing the AI detection workflow and watchstander vetting.", "title": "ALERTCalifornia: Technology", "url": "https://alertcalifornia.org/technology/", "date": null, "written_by": "makers", "quote": "If the incident is vetted and confirmed by trained watchstanders, firefighters respond quickly to extinguish the fire at the incipient phase." } ], "replication": { "produced_by": [ "A camera network with machine-learned smoke detection watching remote forest at night, when human spotting is weakest", "A verification step by trained operators that turns a model flag into a confirmed alert to the local Cal Fire station", "A fire still small at detection, with a crew close enough to reach it before it grows" ], "must_hold": [ "The detection must precede any human report for the time gained to be attributable to the model. For this fire no source documents the absence of a 911 call", "Human verification must be fast enough that the alert still arrives in the incipient phase", "False positives from dust, insects or weather must be screened out so that crews keep trusting the alerts" ], "echoes": [] }, "paired_incident": null, "headline": "ALERTCalifornia AI flags smoke; fire held under a quarter acre", "metric": "Cal Fire held the verified fire under a quarter acre", "comparator": { "against": "911 calls from the public as the first notice of a fire", "before": "not stated", "after": "the AI beats 911 calls about 40 percent of the time", "basis": "measured", "quote": "\"We beat 911 calls about 40 percent of the time. And it's going to get better.\"", "url": "https://english.aawsat.com/node/4540976" }, "later": { "status": "scaled", "date": "2023-09-01", "note": "After the summer trial the AI tool was rolled out to all 21 Cal Fire dispatch centers in September 2023 (day not given; first day of month used), and TIME named it one of the best inventions of 2023 on 24 October 2023.", "quote": "The AI tool became available to all 21 Cal Fire dispatch centers in September. The new tool is especially effective in spotting anomalies in remote locations and has proven effective at night, even alerting firefighters before 911 calls.", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-09-12-f6ac", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://english.aawsat.com/node/4540976; https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://alertcalifornia.org/about/; https://en.wikipedia.org/wiki/California_Department_of_Forestry_and_Fire_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports and three press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0120", "catalog_version": "1.0.0", "source_fingerprint": "6a95bb51aedb168ccf10e609ab16860e9bcb15daf5287425833fc7fb98bb145b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0120-source-0001", "AIBD-0120-source-0002", "AIBD-0120-source-0003", "AIBD-0120-source-0004", "AIBD-0120-source-0005", "AIBD-0120-source-0006", "AIBD-0120-source-0007", "AIBD-0120-source-0008", "AIBD-0120-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path", "deployer": "California Department of Forestry and Fire Protection (CAL FIRE)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model's contribution was the detection. 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For this fire no source documents the absence of a 911 call", "Human verification must be fast enough that the alert still arrives in the incipient phase", "False positives from dust, insects or weather must be screened out so that crews keep trusting the alerts" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-09-12-f6ac", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://english.aawsat.com/node/4540976; https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://alertcalifornia.org/about/; https://en.wikipedia.org/wiki/California_Department_of_Forestry_and_Fire_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Emergency services (wildfire detection and response)", "segment": "State fire agency using a university camera network" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Fonsegrives R. / AFP via Phys.org (2023). 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CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial. Agency press release, Sacramento.", "title": "CAL FIRE and University of California San Diego's ALERTCalifornia Program Join Forces to Enhance Wildfire Response with Artificial Intelligence Implementation Trial", "url": "https://alertcalifornia.org/cal-fire-and-university-of-california-san-diegos-alertcalifornia-program-join-forces-to-enhance-wildfire-response-with-artificial-intelligence-implementation-trial/", "date": "2023-07-10", "written_by": "makers", "quote": "a machine-learned model has been created to accurately differentiate between smoke and other particles in the air" }, { "kind": "news report", "citation": "Dixit P. / TIME (2023). AlertCalifornia and Cal Fire AI Wildfire Detector. 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University news release.", "title": "ALERTCalifornia and CAL FIRE's Fire Detection AI Program Named One of TIME's Best Inventions of 2023", "url": "https://today.ucsd.edu/story/alertcalifornia-and-cal-fires-fire-detection-ai-program-named-one-of-times-best-inventions-of-2023", "date": "2023-10-24", "written_by": "makers", "quote": "The AI tool became available to all 21 CAL FIRE 911 Dispatch Centers in September 2023." }, { "kind": "news report", "citation": "Jennewein C. / Times of San Diego (2023). Time Magazine: California's AI Wildfire Detection System a Top Invention of 2023. 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That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALERTCalifornia AI wildfire detection (machine-learned smoke and anomaly detection on the ALERTCalifornia pan-tilt-zoom camera network)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ALERTCalifornia, University of California San Diego, with industry partner Digital Path" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna; human operators verify it and Cal Fire holds the fire to under a quarter acre", "headline": "ALERTCalifornia AI flags smoke; fire held under a quarter acre" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6a95bb51aedb168ccf10e609ab16860e9bcb15daf5287425833fc7fb98bb145b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 3 am on 5 August 2023, the ALERTCalifornia AI flagged a column of smoke in the Cleveland National Forest near Mount Laguna. That is about 40 miles east of San Diego. The AI, a machine-learned model run by UC San Diego, watches live feeds from more than 1,000 cameras. Human operators verified the detection and alerted Cal Fire Captain Kris Yeary. His crews put it out at less than a quarter acre. Yeary told AFP that it could have become a devastating fire had the AI not alerted them. The AI watch over the feeds began at the end of June 2023 under a Cal Fire trial. By September 2023 the tool reached all 21 Cal Fire dispatch centers.", "replication": { "produced_by": [ "A camera network with machine-learned smoke detection watching remote forest at night, when human spotting is weakest", "A verification step by trained operators that turns a model flag into a confirmed alert to the local Cal Fire station", "A fire still small at detection, with a crew close enough to reach it before it grows" ], "must_hold": [ "The detection must precede any human report for the time gained to be attributable to the model. For this fire no source documents the absence of a 911 call", "Human verification must be fast enough that the alert still arrives in the incipient phase", "False positives from dust, insects or weather must be screened out so that crews keep trusting the alerts" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0224", "title": "HSI's Operation Renewed Hope uses facial recognition and AI image enhancement to identify 311 probable child victims in cold cases", "summary": "A three-week HSI-led surge from 17 Jul 2023 produced 311 probable identifications of unknown child victims, 14 positive contacts and several rescues; officials credit facial recognition and AI images.", "date_observed": "2023-08-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The operation began on 17 July 2023 and ended in early August. HSI's Cyber Crimes Center hosted investigators from the FBI, U.S. Marshals, Interpol, Europol and 13 foreign agencies to review unidentified child sexual abuse material series. ICE reports 311 probable identifications of previously unknown victims, 14 positive contacts and several confirmed rescues from active abuse. Over 100 leads went to field offices and 25 countries, with arrests already made in the United States and Canada. NBC News reports that HSI officials credited new facial recognition and artificial intelligence technology for fresh leads. Mike Prado of HSI described AI- or machine-learning-enhanced images as a starting point for investigation. ABC (Australia) reports that the operation used Clearview AI's facial recognition alongside other techniques, citing Queensland Police analyst Scott Anderson. Forbes reports that officials did not confirm Clearview or any specific program. The ICE release itself does not mention AI.", "category": "benefit created", "unexpected": false, "purpose": "Identify previously unknown victims and offenders in seized child sexual abuse material so that children can be located and rescued.", "system": "Facial recognition (reported as Clearview AI) and AI/machine-learning image enhancement used in victim identification", "model_version": null, "developer": "Clearview AI (reported by ABC and Forbes; not confirmed by HSI) and unnamed image-enhancement tools", "deployer": "Homeland Security Investigations (U.S. Immigration and Customs Enforcement), Cyber Crimes Center", "location": "Washington, United States", "domain": "Child protection / online child sexual exploitation", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "ICE reports several confirmed rescues of children from active abuse and 14 positive contacts. The number of rescues is unstated." }, { "group": "societal", "depth": 3, "reason": "More than 100 leads disseminated and arrests of active abusers in the United States and Canada, per ICE and NBC." } ], "ai_role": { "status": "assessed", "statement": "Official and independent sources agree the surge produced the identifications. The AI's share is described only qualitatively. NBC quotes an HSI official on AI-enhanced images giving investigators a starting point or tentative identification. ABC names Clearview AI's facial recognition as one tool. HSI did not confirm any product, and much of the work was manual contextual analysis (flora, fauna, geolocation). 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external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Washington, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify previously unknown victims and offenders in seized child sexual abuse material so that children can be located and rescued." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-08-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nbcnews.com/news/investigations/homeland-security-identifies-311-child-victims-sexual-exploitation-rcna97357; https://www.abc.net.au/news/2023-08-24/qld-facial-recognition-child-abuse-artificial-intelligence/102761618", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Clearview_AI; https://en.wikipedia.org/wiki/Homeland_Security_Investigations", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Large holdings of unidentified abuse-material series concentrated for a time-boxed multi-agency review", "Facial recognition against web-scraped reference images plus AI image enhancement feeding human investigators", "Lead dissemination through Interpol's ICSE database and partner agencies" ], "must_hold": [ "Legal authority to use web-scraped facial recognition (banned for this use in Australia, per ABC)", "Human investigators to verify tentative identifications before action", "Partner agencies able to act on leads" ], "echoes": [ { "date": "2024-03-14", "setting": "Second US-based international victim identification surge reported by HSToday (headline only)", "outcome": "unknown", "source": "https://www.hstoday.us/subject-matter-areas/customs-immigration/hsi-partners-conduct-us-based-international-victim-identification-surge/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Large holdings of unidentified abuse-material series concentrated for a time-boxed multi-agency review", "Facial recognition against web-scraped reference images plus AI image enhancement feeding human investigators", "Lead dissemination through Interpol's ICSE database and partner agencies" ], "must_hold": [ "Legal authority to use web-scraped facial recognition (banned for this use in Australia, per ABC)", "Human investigators to verify tentative identifications before action", "Partner agencies able to act on leads" ], "echoes": [ { "date": "2024-03-14", "setting": "Second US-based international victim identification surge reported by HSToday (headline only)", "outcome": "unknown", "source": "https://www.hstoday.us/subject-matter-areas/customs-immigration/hsi-partners-conduct-us-based-international-victim-identification-surge/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.nbcnews.com/news/investigations/homeland-security-identifies-311-child-victims-sexual-exploitation-rcna97357; https://www.abc.net.au/news/2023-08-24/qld-facial-recognition-child-abuse-artificial-intelligence/102761618", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Clearview_AI; https://en.wikipedia.org/wiki/Homeland_Security_Investigations", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Child protection / online child sexual exploitation", "segment": "Government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Immigration and Customs Enforcement, news release, 9 Aug 2023", "title": "HSI, partners launch first US-based international victim identification surge", "url": "https://www.ice.gov/news/releases/hsi-partners-launch-first-us-based-international-victim-identification-surge", "date": "2023-08-09", "written_by": "deployer", "quote": "resulting in the generation of 311 probable identifications of previously unknown victims, including 14 positive contacts and several confirmed victim rescues from active abuse." }, { "kind": "news report", "citation": "Julia Ainsley, NBC News, 9 Aug 2023", "title": "Homeland Security identifies 311 child victims of sexual exploitation in 'cold cases'", "url": "https://www.nbcnews.com/news/investigations/homeland-security-identifies-311-child-victims-sexual-exploitation-rcna97357", "date": "2023-08-09", "written_by": "independent", "quote": "Thanks to new facial recognition and artificial intelligence technology, there are now fresh leads in these formerly cold cases." }, { "kind": "news report", "citation": "Antonia O'Flaherty, ABC News (Australia), 24 Aug 2023", "title": "Operation Renewed Hope identifies more than 300 probable victims of child sexual abuse using controversial AI", "url": "https://www.abc.net.au/news/2023-08-24/qld-facial-recognition-child-abuse-artificial-intelligence/102761618", "date": "2023-08-24", "written_by": "independent", "quote": "The operation used the US-based company Clearview AI's facial recognition technology as well as other victim identification techniques." }, { "kind": "news report", "citation": "Mary Whitfill Roeloffs, Forbes, 9 Aug 2023", "title": "DHS Says It Identified 311 New Child Sexual Exploitation Victims—After Forbes Reports AI Facial Recognition Push", "url": "https://www.forbes.com/sites/maryroeloffs/2023/08/09/dhs-says-it-identified-311-new-child-sexual-exploitation-victims-after-forbes-reports-ai-facial-recognition-push/", "date": "2023-08-09", "written_by": "independent", "quote": "scanning more than 4.3 million images and videos to pick up on previously overlooked clues or identifying materials." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0224-source-0001", "AIBD-0224-source-0002", "AIBD-0224-source-0003", "AIBD-0224-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Immigration and Customs Enforcement, news release, 9 Aug 2023", "title": "HSI, partners launch first US-based international victim identification surge", "url": "https://www.ice.gov/news/releases/hsi-partners-launch-first-us-based-international-victim-identification-surge", "date": "2023-08-09", "written_by": "deployer", "quote": "resulting in the generation of 311 probable identifications of previously unknown victims, including 14 positive contacts and several confirmed victim rescues from active abuse." }, { "kind": "news report", "citation": "Julia Ainsley, NBC News, 9 Aug 2023", "title": "Homeland Security identifies 311 child victims of sexual exploitation in 'cold cases'", "url": "https://www.nbcnews.com/news/investigations/homeland-security-identifies-311-child-victims-sexual-exploitation-rcna97357", "date": "2023-08-09", "written_by": "independent", "quote": "Thanks to new facial recognition and artificial intelligence technology, there are now fresh leads in these formerly cold cases." }, { "kind": "news report", "citation": "Antonia O'Flaherty, ABC News (Australia), 24 Aug 2023", "title": "Operation Renewed Hope identifies more than 300 probable victims of child sexual abuse using controversial AI", "url": "https://www.abc.net.au/news/2023-08-24/qld-facial-recognition-child-abuse-artificial-intelligence/102761618", "date": "2023-08-24", "written_by": "independent", "quote": "The operation used the US-based company Clearview AI's facial recognition technology as well as other victim identification techniques." }, { "kind": "news report", "citation": "Mary Whitfill Roeloffs, Forbes, 9 Aug 2023", "title": "DHS Says It Identified 311 New Child Sexual Exploitation Victims—After Forbes Reports AI Facial Recognition Push", "url": "https://www.forbes.com/sites/maryroeloffs/2023/08/09/dhs-says-it-identified-311-new-child-sexual-exploitation-victims-after-forbes-reports-ai-facial-recognition-push/", "date": "2023-08-09", "written_by": "independent", "quote": "scanning more than 4.3 million images and videos to pick up on previously overlooked clues or identifying materials." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A three-week HSI-led surge from 17 Jul 2023 produced 311 probable identifications of unknown child victims, 14 positive contacts and several rescues; officials credit facial recognition and AI images.", "account": "The operation began on 17 July 2023 and ended in early August. HSI's Cyber Crimes Center hosted investigators from the FBI, U.S. Marshals, Interpol, Europol and 13 foreign agencies to review unidentified child sexual abuse material series. ICE reports 311 probable identifications of previously unknown victims, 14 positive contacts and several confirmed rescues from active abuse. Over 100 leads went to field offices and 25 countries, with arrests already made in the United States and Canada. NBC News reports that HSI officials credited new facial recognition and artificial intelligence technology for fresh leads. Mike Prado of HSI described AI- or machine-learning-enhanced images as a starting point for investigation. ABC (Australia) reports that the operation used Clearview AI's facial recognition alongside other techniques, citing Queensland Police analyst Scott Anderson. Forbes reports that officials did not confirm Clearview or any specific program. The ICE release itself does not mention AI." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Facial recognition (reported as Clearview AI) and AI/machine-learning image enhancement used in victim identification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Clearview AI (reported by ABC and Forbes; not confirmed by HSI) and unnamed image-enhancement tools" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "HSI's Operation Renewed Hope uses facial recognition and AI image enhancement to identify 311 probable child victims in cold cases", "headline": "Facial recognition helps HSI identify 311 probable child victims" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c810f6131be841afe2b59d0dda3bc5c8de217b37e35eb344472e8535098e3170" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The operation began on 17 July 2023 and ended in early August. HSI's Cyber Crimes Center hosted investigators from the FBI, U.S. Marshals, Interpol, Europol and 13 foreign agencies to review unidentified child sexual abuse material series. ICE reports 311 probable identifications of previously unknown victims, 14 positive contacts and several confirmed rescues from active abuse. Over 100 leads went to field offices and 25 countries, with arrests already made in the United States and Canada. NBC News reports that HSI officials credited new facial recognition and artificial intelligence technology for fresh leads. Mike Prado of HSI described AI- or machine-learning-enhanced images as a starting point for investigation. ABC (Australia) reports that the operation used Clearview AI's facial recognition alongside other techniques, citing Queensland Police analyst Scott Anderson. Forbes reports that officials did not confirm Clearview or any specific program. The ICE release itself does not mention AI.", "replication": { "produced_by": [ "Large holdings of unidentified abuse-material series concentrated for a time-boxed multi-agency review", "Facial recognition against web-scraped reference images plus AI image enhancement feeding human investigators", "Lead dissemination through Interpol's ICSE database and partner agencies" ], "must_hold": [ "Legal authority to use web-scraped facial recognition (banned for this use in Australia, per ABC)", "Human investigators to verify tentative identifications before action", "Partner agencies able to act on leads" ], "echoes": [ { "date": "2024-03-14", "setting": "Second US-based international victim identification surge reported by HSToday (headline only)", "outcome": "unknown", "source": "https://www.hstoday.us/subject-matter-areas/customs-immigration/hsi-partners-conduct-us-based-international-victim-identification-surge/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0119", "title": "Awake robot-guided surgery removes a 4 cm brain hemorrhage from a 58-year-old man at Tam Anh General Hospital, Ho Chi Minh City", "summary": "Awake surgery guided by the Modus V Synaptive robot removed a 58-year-old stroke patient's 4 cm clot at Tam Anh Hospital; full recovery.", "date_observed": "2023-08-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 10 August 2023 a 58-year-old man, Mr. Hải, reached Tam Anh General Hospital at 14:00. He was drowsy and weak over 24 hours after a hemorrhagic stroke. Magnetic resonance imaging (MRI) showed a clot up to 4 cm pressing on motor and language areas. Surgery began at 17:00 under local anesthesia. First the Modus V Synaptive robot's AI fused MRI, DTI, computed tomography (CT) and DSA scans into one 3D view of fiber tracts and clot. There neurosurgeon Chu Tấn Sĩ rehearsed the approach. In surgery its traffic-light warnings policed the path while the awake patient talked and moved on request. About 40 ml of clot came out in just over 30 minutes. CT later showed none left and he went home on day six.", "category": "protective response", "unexpected": false, "purpose": "Tam Anh launched the Modus V Synaptive robot in May 2023 for brain tumor, hemorrhagic stroke and other neurosurgery. It shows fiber tracts on fused images, allows 3D rehearsal and warns when the instrument leaves the planned path. This use was that purpose.", "system": "Modus V Synaptive robotic digital microscope with Neuro-Navigation AI (image fusion, fiber-tract display, surgical simulation, trajectory warnings)", "model_version": "Modus V™", "developer": "Synaptive Medical Inc. (Toronto)", "deployer": "Tam Anh General Hospital, Ho Chi Minh City", "location": "Ho Chi Minh City, Vietnam", "domain": "Healthcare (neurosurgery)", "segment": "Haemorrhagic stroke surgery", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-08-14-9862" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The surgeons said that without urgent surgery he faced hemiplegia, speech loss, blurred vision or death. After the guided awake operation CT showed no residual clot. His movement, vision and cognition were normal and he went home on day six. The life-saving element belongs to the operation as a whole. The robot's own contribution was preserving function." } ], "ai_role": { "status": "assessed", "statement": "The sources attribute three things to the robot's AI. It fused MRI, DTI, CT and DSA into one 3D image showing fiber tracts and clot. It allowed a rehearsal so the skull opening and path avoided the tracts. It gave green-amber-red warnings during surgery when the instrument strayed from the planned path. Clot removal, hemostasis and the awake function tests were done by the surgical and anesthesia teams. No source compares this with conventional surgery for this patient. None says what in the system is machine learning rather than image processing, so the counterfactual is unproven. One sentence in two reports calls the patient Mr. Vinh; all otherwise call him Mr. Hải." }, "evidence": [ { "kind": "news report", "citation": "VietNamNet (2023). Người bệnh hát trong lúc được robot AI mổ não. VietNamNet, Sức khỏe.", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://vietnamnet.vn/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-2177047.html", "date": "2023-08-14", "written_by": "independent", "quote": "Nếu không mổ khẩn cấp, người bệnh đối mặt liệt nửa người, nói khó, nhìn mờ, thậm chí tử vong." }, { "kind": "news report", "citation": "Ngân D. / Báo Đầu Tư (2023). Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não. Báo Đầu Tư.", "title": "Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não", "url": "https://baodautu.vn/tin-moi-ve-y-te-ngay-148-nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-d196299.html", "date": "2023-08-14", "written_by": "independent", "quote": "Ông Hải (58 tuổi) bị đột quỵ xuất huyết não đã hơn 24 giờ, được mổ lấy máu tụ tỉnh thức bằng robot AI" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Người bệnh hát trong lúc được robot AI mổ não. Hospital case news (deployer's account).", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/", "date": "2023-08-18", "written_by": "deployer", "quote": "kết quả chụp CT 768 lát cắt cho thấy không còn máu tụ trong não, vận động, thị giác và nhận thức của người bệnh hoàn toàn bình thường" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM. Hospital news (system launch).", "title": "Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM", "url": "https://tamanhhospital.vn/tin-tuc/ra-mat-robot-mo-nao-duy-nhat-viet-nam-tai-bvdk-tam-anh-tphcm/", "date": "2023-05-29", "written_by": "deployer", "quote": "Robot có thể giúp bác sĩ thấy rõ các bó sợi thần kinh, các mô não lành xung quanh khối u, vùng tổn thương não" }, { "kind": "press release", "citation": "Synaptive Medical (2020). Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V. Company press release, Toronto.", "title": "Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V", "url": "https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "date": "2020-01-15", "written_by": "makers", "quote": "a fully automated robotic digital microscope designed to assist surgeons in the operating room" } ], "replication": { "produced_by": [ "A large (4 cm) hemorrhagic-stroke clot compressing motor and language areas in a patient still able to cooperate with awake surgery", "A hospital that owns the Modus V Synaptive robot with navigation software and a team trained to run it", "Pre-operative fusion of MRI, DTI, CT and DSA and a simulated approach that avoids fiber tracts", "Local anesthesia and intensive-care anesthesiology able to keep the patient awake and stable for function testing" ], "must_hold": [ "Surgery within hours of arrival. The surgeon notes about two million brain cells are lost per minute after a stroke", "The surgeon follows the rehearsed trajectory and heeds the robot's warnings", "Awake testing during clot removal so any tract injury is noticed immediately" ], "echoes": [] }, "paired_incident": null, "headline": "Modus V Synaptive guides awake removal of a 4 cm brain clot", "metric": "About 40 ml of clot came out in just over 30 minutes", "comparator": { "against": "conventional (traditional) brain surgery under general anesthesia", "before": "nếu mổ theo phương pháp truyền thống, nguy cơ di chứng cao (high risk of sequelae with the traditional method)", "after": "khi được mổ lấy máu tụ tỉnh thức bằng robot AI, ông có thể song ca cùng bác sĩ ngay khi đang mổ (awake robot-assisted clot removal while talking and singing)", "basis": "assumed", "quote": "Ông Hải (58 tuổi) bị đột quỵ xuất huyết não đã hơn 24 giờ, dần lơ mơ yếu liệt, nếu mổ theo phương pháp truyền thống, nguy cơ di chứng cao nhưng khi được mổ lấy máu tụ tỉnh thức bằng robot AI, ông có thể song ca cùng bác sĩ ngay khi đang mổ.", "url": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/" }, "later": { "status": "unknown", "date": null, "note": "No report on the patient after discharge on day six was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "Canada", "deployer_country": "Vietnam", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-08-14-9862", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/; https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.synaptivemedical.com/contact-us/; https://tamanhhospital.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' press release and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0119", "catalog_version": "1.0.0", "source_fingerprint": "e603a114bf59fa1fabdce8892a052cad025e112d8e70282017cf0e55fdaae32f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0119-source-0001", "AIBD-0119-source-0002", "AIBD-0119-source-0003", "AIBD-0119-source-0004", "AIBD-0119-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Synaptive Medical Inc. (Toronto)", "deployer": "Tam Anh General Hospital, Ho Chi Minh City" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The sources attribute three things to the robot's AI. It fused MRI, DTI, CT and DSA into one 3D image showing fiber tracts and clot. It allowed a rehearsal so the skull opening and path avoided the tracts. It gave green-amber-red warnings during surgery when the instrument strayed from the planned path. Clot removal, hemostasis and the awake function tests were done by the surgical and anesthesia teams. No source compares this with conventional surgery for this patient. None says what in the system is machine learning rather than image processing, so the counterfactual is unproven. One sentence in two reports calls the patient Mr. Vinh; all otherwise call him Mr. Hải." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The sources attribute three things to the robot's AI. It fused MRI, DTI, CT and DSA into one 3D image showing fiber tracts and clot. It allowed a rehearsal so the skull opening and path avoided the tracts. It gave green-amber-red warnings during surgery when the instrument strayed from the planned path. Clot removal, hemostasis and the awake function tests were done by the surgical and anesthesia teams. No source compares this with conventional surgery for this patient. None says what in the system is machine learning rather than image processing, so the counterfactual is unproven. One sentence in two reports calls the patient Mr. Vinh; all otherwise call him Mr. Hải." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The surgeons said that without urgent surgery he faced hemiplegia, speech loss, blurred vision or death. After the guided awake operation CT showed no residual clot. His movement, vision and cognition were normal and he went home on day six. The life-saving element belongs to the operation as a whole. The robot's own contribution was preserving function." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, the makers' press release and two press releases from the deployer. 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after discharge on day six was found in the cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0119" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 10 August 2023 a 58-year-old man, Mr. Hải, reached Tam Anh General Hospital at 14:00. He was drowsy and weak over 24 hours after a hemorrhagic stroke. Magnetic resonance imaging (MRI) showed a clot up to 4 cm pressing on motor and language areas. Surgery began at 17:00 under local anesthesia. First the Modus V Synaptive robot's AI fused MRI, DTI, computed tomography (CT) and DSA scans into one 3D view of fiber tracts and clot. There neurosurgeon Chu Tấn Sĩ rehearsed the approach. In surgery its traffic-light warnings policed the path while the awake patient talked and moved on request. About 40 ml of clot came out in just over 30 minutes. CT later showed none left and he went home on day six.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The surgeons said that without urgent surgery he faced hemiplegia, speech loss, blurred vision or death. After the guided awake operation CT showed no residual clot. His movement, vision and cognition were normal and he went home on day six. The life-saving element belongs to the operation as a whole. The robot's own contribution was preserving function." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Tam Anh launched the Modus V Synaptive robot in May 2023 for brain tumor, hemorrhagic stroke and other neurosurgery. It shows fiber tracts on fused images, allows 3D rehearsal and warns when the instrument leaves the planned path. This use was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ho Chi Minh City, Vietnam", "developer_country": "Canada", "deployer_country": "Vietnam" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Tam Anh launched the Modus V Synaptive robot in May 2023 for brain tumor, hemorrhagic stroke and other neurosurgery. It shows fiber tracts on fused images, allows 3D rehearsal and warns when the instrument leaves the planned path. This use was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-08-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-08-14-9862", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/; https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.synaptivemedical.com/contact-us/; https://tamanhhospital.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A large (4 cm) hemorrhagic-stroke clot compressing motor and language areas in a patient still able to cooperate with awake surgery", "A hospital that owns the Modus V Synaptive robot with navigation software and a team trained to run it", "Pre-operative fusion of MRI, DTI, CT and DSA and a simulated approach that avoids fiber tracts", "Local anesthesia and intensive-care anesthesiology able to keep the patient awake and stable for function testing" ], "must_hold": [ "Surgery within hours of arrival. The surgeon notes about two million brain cells are lost per minute after a stroke", "The surgeon follows the rehearsed trajectory and heeds the robot's warnings", "Awake testing during clot removal so any tract injury is noticed immediately" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-08-14-9862", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/; https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.synaptivemedical.com/contact-us/; https://tamanhhospital.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (neurosurgery)", "segment": "Haemorrhagic stroke surgery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "VietNamNet (2023). Người bệnh hát trong lúc được robot AI mổ não. VietNamNet, Sức khỏe.", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://vietnamnet.vn/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-2177047.html", "date": "2023-08-14", "written_by": "independent", "quote": "Nếu không mổ khẩn cấp, người bệnh đối mặt liệt nửa người, nói khó, nhìn mờ, thậm chí tử vong." }, { "kind": "news report", "citation": "Ngân D. / Báo Đầu Tư (2023). Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não. Báo Đầu Tư.", "title": "Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não", "url": "https://baodautu.vn/tin-moi-ve-y-te-ngay-148-nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-d196299.html", "date": "2023-08-14", "written_by": "independent", "quote": "Ông Hải (58 tuổi) bị đột quỵ xuất huyết não đã hơn 24 giờ, được mổ lấy máu tụ tỉnh thức bằng robot AI" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Người bệnh hát trong lúc được robot AI mổ não. Hospital case news (deployer's account).", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/", "date": "2023-08-18", "written_by": "deployer", "quote": "kết quả chụp CT 768 lát cắt cho thấy không còn máu tụ trong não, vận động, thị giác và nhận thức của người bệnh hoàn toàn bình thường" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM. Hospital news (system launch).", "title": "Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM", "url": "https://tamanhhospital.vn/tin-tuc/ra-mat-robot-mo-nao-duy-nhat-viet-nam-tai-bvdk-tam-anh-tphcm/", "date": "2023-05-29", "written_by": "deployer", "quote": "Robot có thể giúp bác sĩ thấy rõ các bó sợi thần kinh, các mô não lành xung quanh khối u, vùng tổn thương não" }, { "kind": "press release", "citation": "Synaptive Medical (2020). Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V. Company press release, Toronto.", "title": "Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V", "url": "https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "date": "2020-01-15", "written_by": "makers", "quote": "a fully automated robotic digital microscope designed to assist surgeons in the operating room" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0119-source-0001", "AIBD-0119-source-0002", "AIBD-0119-source-0003", "AIBD-0119-source-0004", "AIBD-0119-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "VietNamNet (2023). Người bệnh hát trong lúc được robot AI mổ não. VietNamNet, Sức khỏe.", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://vietnamnet.vn/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-2177047.html", "date": "2023-08-14", "written_by": "independent", "quote": "Nếu không mổ khẩn cấp, người bệnh đối mặt liệt nửa người, nói khó, nhìn mờ, thậm chí tử vong." }, { "kind": "news report", "citation": "Ngân D. / Báo Đầu Tư (2023). Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não. Báo Đầu Tư.", "title": "Tin mới về y tế ngày 14/8: Người bệnh hát trong lúc được robot AI mổ não", "url": "https://baodautu.vn/tin-moi-ve-y-te-ngay-148-nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao-d196299.html", "date": "2023-08-14", "written_by": "independent", "quote": "Ông Hải (58 tuổi) bị đột quỵ xuất huyết não đã hơn 24 giờ, được mổ lấy máu tụ tỉnh thức bằng robot AI" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Người bệnh hát trong lúc được robot AI mổ não. Hospital case news (deployer's account).", "title": "Người bệnh hát trong lúc được robot AI mổ não", "url": "https://tamanhhospital.vn/tin-tuc/nguoi-benh-hat-trong-luc-duoc-robot-ai-mo-nao/", "date": "2023-08-18", "written_by": "deployer", "quote": "kết quả chụp CT 768 lát cắt cho thấy không còn máu tụ trong não, vận động, thị giác và nhận thức của người bệnh hoàn toàn bình thường" }, { "kind": "press release", "citation": "Tam Anh General Hospital (2023). Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM. Hospital news (system launch).", "title": "Ra mắt robot mổ não duy nhất Việt Nam tại BVĐK Tâm Anh TP.HCM", "url": "https://tamanhhospital.vn/tin-tuc/ra-mat-robot-mo-nao-duy-nhat-viet-nam-tai-bvdk-tam-anh-tphcm/", "date": "2023-05-29", "written_by": "deployer", "quote": "Robot có thể giúp bác sĩ thấy rõ các bó sợi thần kinh, các mô não lành xung quanh khối u, vùng tổn thương não" }, { "kind": "press release", "citation": "Synaptive Medical (2020). Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V. Company press release, Toronto.", "title": "Synaptive Medical Announces Product Update to Flagship Surgical Technology, Modus V", "url": "https://www.synaptivemedical.com/news/synaptive-medical-announces-product-update-to-flagship-surgical-technology-modus-v-tm-automated-robotic-microscope", "date": "2020-01-15", "written_by": "makers", "quote": "a fully automated robotic digital microscope designed to assist surgeons in the operating room" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Awake surgery guided by the Modus V Synaptive robot removed a 58-year-old stroke patient's 4 cm clot at Tam Anh Hospital; full recovery.", "account": "On 10 August 2023 a 58-year-old man, Mr. Hải, reached Tam Anh General Hospital at 14:00. He was drowsy and weak over 24 hours after a hemorrhagic stroke. Magnetic resonance imaging (MRI) showed a clot up to 4 cm pressing on motor and language areas. Surgery began at 17:00 under local anesthesia. First the Modus V Synaptive robot's AI fused MRI, DTI, computed tomography (CT) and DSA scans into one 3D view of fiber tracts and clot. There neurosurgeon Chu Tấn Sĩ rehearsed the approach. In surgery its traffic-light warnings policed the path while the awake patient talked and moved on request. About 40 ml of clot came out in just over 30 minutes. CT later showed none left and he went home on day six." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used the Modus V system." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Modus V™" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Modus V Synaptive robotic digital microscope with Neuro-Navigation AI (image fusion, fiber-tract display, surgical simulation, trajectory warnings)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Synaptive Medical Inc. (Toronto)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Awake robot-guided surgery removes a 4 cm brain hemorrhage from a 58-year-old man at Tam Anh General Hospital, Ho Chi Minh City", "headline": "Modus V Synaptive guides awake removal of a 4 cm brain clot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e603a114bf59fa1fabdce8892a052cad025e112d8e70282017cf0e55fdaae32f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 10 August 2023 a 58-year-old man, Mr. Hải, reached Tam Anh General Hospital at 14:00. He was drowsy and weak over 24 hours after a hemorrhagic stroke. Magnetic resonance imaging (MRI) showed a clot up to 4 cm pressing on motor and language areas. Surgery began at 17:00 under local anesthesia. First the Modus V Synaptive robot's AI fused MRI, DTI, computed tomography (CT) and DSA scans into one 3D view of fiber tracts and clot. There neurosurgeon Chu Tấn Sĩ rehearsed the approach. In surgery its traffic-light warnings policed the path while the awake patient talked and moved on request. About 40 ml of clot came out in just over 30 minutes. CT later showed none left and he went home on day six.", "replication": { "produced_by": [ "A large (4 cm) hemorrhagic-stroke clot compressing motor and language areas in a patient still able to cooperate with awake surgery", "A hospital that owns the Modus V Synaptive robot with navigation software and a team trained to run it", "Pre-operative fusion of MRI, DTI, CT and DSA and a simulated approach that avoids fiber tracts", "Local anesthesia and intensive-care anesthesiology able to keep the patient awake and stable for function testing" ], "must_hold": [ "Surgery within hours of arrival. The surgeon notes about two million brain cells are lost per minute after a stroke", "The surgeon follows the rehearsed trajectory and heeds the robot's warnings", "Awake testing during clot removal so any tract injury is noticed immediately" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0313", "title": "ALERTCalifornia cameras and AI may have helped crews rapidly detect and contain Kern County's 52-acre Trotter Fire (August 2023)", "summary": "Trotter Fire, Bear Valley Springs near Tehachapi, 14–17 August 2023, 52 acres; the AI-detection claim and “nearly 4,000 acres” counterfactual come only from ALERTCalifornia's founder via Microsoft.", "date_observed": "2023-08-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Cal Fire's incident record lists the Trotter fire at Trotter Dr and Skyline Drive, west of Tehachapi, Kern County. It started 14 August 2023 at 18:10 UTC under the Kern County Fire Department (not a Cal Fire incident). It burned 52 acres and was 100% contained and extinguished 17 August 2023. It says nothing about how the fire was detected or reported. KBAK (Bakersfield, 14 August 2023) reported a mandatory evacuation for Skyline Drive between Saddleback Drive and Cumberland Road in Bear Valley Springs. It gave an estimated 40 acres, forward progress stopped by 2:17 p.m. and the evacuation lifted by 3:12 p.m. The Kern County Fire Department said the fire “was started by an electrical strike”. A KGET headline the same day blamed lightning and said no homes were damaged. Microsoft's “Unlocked” feature “The first five minutes” (Bruna Mori, 27 August 2026) was published after Microsoft's $5 million contribution to ALERTCalifornia. It included a $3 million Azure grant (announced by ALERTCalifornia on 3 February 2026). The feature says in 2023 ALERTCalifornia's cameras and AI helped crews rapidly detect and contain the Trotter Fire at 52 acres. Without AI-powered imaging, ALERTCalifornia founder Neal Driscoll estimates it may have spread to nearly 4,000 acres. It quotes Zachary Wells, deputy chief of the Kern County Fire Department and deputy director of operations at ALERTCalifornia. The claim is found only in Microsoft and ALERTCalifornia material. No fire-agency, regulator or independent news account of the fire mentions AI detection. None says which agency received the alert or its timing relative to 911 calls.", "category": "protective response", "unexpected": false, "purpose": "Built to detect smoke in camera feeds and alert fire agencies. The claimed detection is that purpose.", "system": "ALERTCalifornia camera network with AI smoke detection (the Microsoft feature does not name the detection software; AIBD-0007 identifies DigitalPath)", "model_version": null, "developer": "ALERTCalifornia, University of California San Diego (camera network); AI detection software supplier not named in the sources", "deployer": "Kern County Fire Department (incident agency); which agency received the AI alert is not stated", "location": "Bear Valley Springs, west of Tehachapi, Kern County, California, United States", "domain": "Wildfire detection and response", "segment": "Public safety / fire services", "benefit_type": "Reduced Risk", "taxonomy_note": "The AI detection and the “nearly 4,000 acres” counterfactual come only from ALERTCalifornia's founder via Microsoft.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 3, "reason": "The fire was held to 52 acres and the evacuation lifted the same afternoon (Cal Fire record; KBAK), a risk removed for the neighborhood. The claim that the camera network detected it first comes only from ALERTCalifornia's founder via Microsoft." }, { "group": "organizational", "depth": 2, "reason": "An early alert to the Kern County Fire Department is described only in the vendor's account. The department's own account mentions no camera alert." } ], "ai_role": { "status": "unassessed", "statement": "The only statement that AI detection played a role is a Microsoft-published feature (Microsoft funds ALERTCalifornia) quoting its founder Neal Driscoll. His “nearly 4,000 acres” counterfactual is his estimate. The quoted deputy fire chief is also ALERTCalifornia's deputy director of operations. Cal Fire's incident record and KBAK's same-day report say nothing about how the fire was detected. KBAK attributes the start to an electrical strike." }, "evidence": [ { "kind": "report", "citation": "California Department of Forestry and Fire Protection (2023). Trotter fire, Kern County, incident record (started 14 August 2023; the incident page is the public view).", "title": "Trotter Fire", "url": "https://www.fire.ca.gov/incidents/2023/8/14/trotter/", "date": "2023-08-17", "written_by": "independent", "quote": "Trotter Dr and Skyline Drive, West of Tehachapi" }, { "kind": "news report", "citation": "KBAK / Bakersfield Now (2023). Evacuation order lifted in Bear Valley Springs following Trotter Fire. 14 August 2023.", "title": "Evacuation order lifted in Bear Valley Springs following Trotter Fire", "url": "https://bakersfieldnow.com/news/local/kern-county-fire-department-orders-evacuation-in-bear-valley-springs-due-to-vegetation-fires-kern-county", "date": "2023-08-14", "written_by": "independent", "quote": "The Kern County Fire Department said that the Trotter Fire was started by an electrical strike." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (Microsoft funds ALERTCalifornia; the source of the AI-detection claim).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "In 2023, ALERTCalifornia's cameras and AI helped crews rapidly detect and contain Kern County's Trotter Fire at 52 acres." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (the counterfactual estimate).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "Without AI-powered imaging, Driscoll estimates it may have spread to nearly 4,000 acres." }, { "kind": "press release", "citation": "ALERTCalifornia (2026). New collaboration expands capabilities and enhances natural disaster resilience. 3 February 2026 (the Microsoft funding announcement; the page does not mention the Trotter Fire).", "title": "New collaboration expands capabilities and enhances natural disaster resilience", "url": "https://alertcalifornia.org/new-collaboration-expands-capabilities-and-enhances-natural-disaster-resilience/", "date": "2026-02-03", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "ALERTCalifornia's camera network with AI smoke detection covering the Tehachapi area", "A fire agency able to act on an early detection. Which agency received this alert is not stated", "A lightning or electrical-strike ignition on 14 August 2023 that crews stopped at 52 acres" ], "must_hold": [ "An alert reaching dispatch before or alongside 911 calls, which no cited source documents for this fire", "A counterfactual spread that depends on fuels, wind and response time. 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"record_fields", "fields": { "account": "Cal Fire's incident record lists the Trotter fire at Trotter Dr and Skyline Drive, west of Tehachapi, Kern County. It started 14 August 2023 at 18:10 UTC under the Kern County Fire Department (not a Cal Fire incident). It burned 52 acres and was 100% contained and extinguished 17 August 2023. It says nothing about how the fire was detected or reported. KBAK (Bakersfield, 14 August 2023) reported a mandatory evacuation for Skyline Drive between Saddleback Drive and Cumberland Road in Bear Valley Springs. It gave an estimated 40 acres, forward progress stopped by 2:17 p.m. and the evacuation lifted by 3:12 p.m. The Kern County Fire Department said the fire “was started by an electrical strike”. A KGET headline the same day blamed lightning and said no homes were damaged. Microsoft's “Unlocked” feature “The first five minutes” (Bruna Mori, 27 August 2026) was published after Microsoft's $5 million contribution to ALERTCalifornia. It included a $3 million Azure grant (announced by ALERTCalifornia on 3 February 2026). The feature says in 2023 ALERTCalifornia's cameras and AI helped crews rapidly detect and contain the Trotter Fire at 52 acres. Without AI-powered imaging, ALERTCalifornia founder Neal Driscoll estimates it may have spread to nearly 4,000 acres. It quotes Zachary Wells, deputy chief of the Kern County Fire Department and deputy director of operations at ALERTCalifornia. The claim is found only in Microsoft and ALERTCalifornia material. No fire-agency, regulator or independent news account of the fire mentions AI detection. None says which agency received the alert or its timing relative to 911 calls.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "The fire was held to 52 acres and the evacuation lifted the same afternoon (Cal Fire record; KBAK), a risk removed for the neighborhood. The claim that the camera network detected it first comes only from ALERTCalifornia's founder via Microsoft." }, { "group": "organizational", "depth": 2, "reason": "An early alert to the Kern County Fire Department is described only in the vendor's account. The department's own account mentions no camera alert." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect smoke in camera feeds and alert fire agencies. 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The claimed detection is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-08-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 3 for societal and 2 for organizational on the documented outcome, with the reason stated on each rating.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://alertcalifornia.org/about/; https://www.kerncountyfire.org/about-us/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALERTCalifornia's camera network with AI smoke detection covering the Tehachapi area", "A fire agency able to act on an early detection. Which agency received this alert is not stated", "A lightning or electrical-strike ignition on 14 August 2023 that crews stopped at 52 acres" ], "must_hold": [ "An alert reaching dispatch before or alongside 911 calls, which no cited source documents for this fire", "A counterfactual spread that depends on fuels, wind and response time. The 4,000-acre figure is an estimate by the network's founder" ], "echoes": [ { "date": "2024-07-06", "setting": "ALERTCalifornia AI camera alert at 2:33 a.m. sends Cal Fire engines to a fire near Auburn before any 911 call; held to a 30 x 30 ft area (AIBD-0007)", "outcome": "recurred", "source": "AIBD-0007" }, { "date": "2026-05-04", "setting": "Cal Fire battalion chief Brent Pascua, quoted by AP, says responses have started before 911 was called and in a few cases fires were put out with no 911 call ever received (aggregate statement)", "outcome": "recurred", "source": "Associated Press, 4 May 2026, https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALERTCalifornia's camera network with AI smoke detection covering the Tehachapi area", "A fire agency able to act on an early detection. Which agency received this alert is not stated", "A lightning or electrical-strike ignition on 14 August 2023 that crews stopped at 52 acres" ], "must_hold": [ "An alert reaching dispatch before or alongside 911 calls, which no cited source documents for this fire", "A counterfactual spread that depends on fuels, wind and response time. The 4,000-acre figure is an estimate by the network's founder" ], "echoes": [ { "date": "2024-07-06", "setting": "ALERTCalifornia AI camera alert at 2:33 a.m. sends Cal Fire engines to a fire near Auburn before any 911 call; held to a 30 x 30 ft area (AIBD-0007)", "outcome": "recurred", "source": "AIBD-0007" }, { "date": "2026-05-04", "setting": "Cal Fire battalion chief Brent Pascua, quoted by AP, says responses have started before 911 was called and in a few cases fires were put out with no 911 call ever received (aggregate statement)", "outcome": "recurred", "source": "Associated Press, 4 May 2026, https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 3 for societal and 2 for organizational on the documented outcome, with the reason stated on each rating.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://alertcalifornia.org/about/; https://www.kerncountyfire.org/about-us/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Wildfire detection and response", "segment": "Public safety / fire services" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "California Department of Forestry and Fire Protection (2023). Trotter fire, Kern County, incident record (started 14 August 2023; the incident page is the public view).", "title": "Trotter Fire", "url": "https://www.fire.ca.gov/incidents/2023/8/14/trotter/", "date": "2023-08-17", "written_by": "independent", "quote": "Trotter Dr and Skyline Drive, West of Tehachapi" }, { "kind": "news report", "citation": "KBAK / Bakersfield Now (2023). Evacuation order lifted in Bear Valley Springs following Trotter Fire. 14 August 2023.", "title": "Evacuation order lifted in Bear Valley Springs following Trotter Fire", "url": "https://bakersfieldnow.com/news/local/kern-county-fire-department-orders-evacuation-in-bear-valley-springs-due-to-vegetation-fires-kern-county", "date": "2023-08-14", "written_by": "independent", "quote": "The Kern County Fire Department said that the Trotter Fire was started by an electrical strike." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (Microsoft funds ALERTCalifornia; the source of the AI-detection claim).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "In 2023, ALERTCalifornia's cameras and AI helped crews rapidly detect and contain Kern County's Trotter Fire at 52 acres." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (the counterfactual estimate).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "Without AI-powered imaging, Driscoll estimates it may have spread to nearly 4,000 acres." }, { "kind": "press release", "citation": "ALERTCalifornia (2026). New collaboration expands capabilities and enhances natural disaster resilience. 3 February 2026 (the Microsoft funding announcement; the page does not mention the Trotter Fire).", "title": "New collaboration expands capabilities and enhances natural disaster resilience", "url": "https://alertcalifornia.org/new-collaboration-expands-capabilities-and-enhances-natural-disaster-resilience/", "date": "2026-02-03", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0313-source-0001", "AIBD-0313-source-0002", "AIBD-0313-source-0003", "AIBD-0313-source-0004", "AIBD-0313-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "California Department of Forestry and Fire Protection (2023). Trotter fire, Kern County, incident record (started 14 August 2023; the incident page is the public view).", "title": "Trotter Fire", "url": "https://www.fire.ca.gov/incidents/2023/8/14/trotter/", "date": "2023-08-17", "written_by": "independent", "quote": "Trotter Dr and Skyline Drive, West of Tehachapi" }, { "kind": "news report", "citation": "KBAK / Bakersfield Now (2023). Evacuation order lifted in Bear Valley Springs following Trotter Fire. 14 August 2023.", "title": "Evacuation order lifted in Bear Valley Springs following Trotter Fire", "url": "https://bakersfieldnow.com/news/local/kern-county-fire-department-orders-evacuation-in-bear-valley-springs-due-to-vegetation-fires-kern-county", "date": "2023-08-14", "written_by": "independent", "quote": "The Kern County Fire Department said that the Trotter Fire was started by an electrical strike." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (Microsoft funds ALERTCalifornia; the source of the AI-detection claim).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "In 2023, ALERTCalifornia's cameras and AI helped crews rapidly detect and contain Kern County's Trotter Fire at 52 acres." }, { "kind": "press release", "citation": "Mori B (2026). The first five minutes. Microsoft Unlocked, 27 August 2026 (the counterfactual estimate).", "title": "The first five minutes", "url": "https://unlocked.microsoft.com/alertcalifornia-ai-wildfire-detection/", "date": "2026-08-27", "written_by": "independent", "quote": "Without AI-powered imaging, Driscoll estimates it may have spread to nearly 4,000 acres." }, { "kind": "press release", "citation": "ALERTCalifornia (2026). New collaboration expands capabilities and enhances natural disaster resilience. 3 February 2026 (the Microsoft funding announcement; the page does not mention the Trotter Fire).", "title": "New collaboration expands capabilities and enhances natural disaster resilience", "url": "https://alertcalifornia.org/new-collaboration-expands-capabilities-and-enhances-natural-disaster-resilience/", "date": "2026-02-03", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Trotter Fire, Bear Valley Springs near Tehachapi, 14–17 August 2023, 52 acres; the AI-detection claim and “nearly 4,000 acres” counterfactual come only from ALERTCalifornia's founder via Microsoft.", "account": "Cal Fire's incident record lists the Trotter fire at Trotter Dr and Skyline Drive, west of Tehachapi, Kern County. It started 14 August 2023 at 18:10 UTC under the Kern County Fire Department (not a Cal Fire incident). It burned 52 acres and was 100% contained and extinguished 17 August 2023. It says nothing about how the fire was detected or reported. KBAK (Bakersfield, 14 August 2023) reported a mandatory evacuation for Skyline Drive between Saddleback Drive and Cumberland Road in Bear Valley Springs. It gave an estimated 40 acres, forward progress stopped by 2:17 p.m. and the evacuation lifted by 3:12 p.m. The Kern County Fire Department said the fire “was started by an electrical strike”. A KGET headline the same day blamed lightning and said no homes were damaged. Microsoft's “Unlocked” feature “The first five minutes” (Bruna Mori, 27 August 2026) was published after Microsoft's $5 million contribution to ALERTCalifornia. It included a $3 million Azure grant (announced by ALERTCalifornia on 3 February 2026). The feature says in 2023 ALERTCalifornia's cameras and AI helped crews rapidly detect and contain the Trotter Fire at 52 acres. Without AI-powered imaging, ALERTCalifornia founder Neal Driscoll estimates it may have spread to nearly 4,000 acres. It quotes Zachary Wells, deputy chief of the Kern County Fire Department and deputy director of operations at ALERTCalifornia. The claim is found only in Microsoft and ALERTCalifornia material. No fire-agency, regulator or independent news account of the fire mentions AI detection. None says which agency received the alert or its timing relative to 911 calls." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALERTCalifornia camera network with AI smoke detection (the Microsoft feature does not name the detection software; AIBD-0007 identifies DigitalPath)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ALERTCalifornia, University of California San Diego (camera network); AI detection software supplier not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ALERTCalifornia cameras and AI may have helped crews rapidly detect and contain Kern County's 52-acre Trotter Fire (August 2023)", "headline": "ALERTCalifornia AI may have helped contain the Trotter Fire" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b83738a9b8addc0e441ba937a2c21d50301a9915bf167e11bd5207f50a469d3e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Cal Fire's incident record lists the Trotter fire at Trotter Dr and Skyline Drive, west of Tehachapi, Kern County. It started 14 August 2023 at 18:10 UTC under the Kern County Fire Department (not a Cal Fire incident). It burned 52 acres and was 100% contained and extinguished 17 August 2023. It says nothing about how the fire was detected or reported. KBAK (Bakersfield, 14 August 2023) reported a mandatory evacuation for Skyline Drive between Saddleback Drive and Cumberland Road in Bear Valley Springs. It gave an estimated 40 acres, forward progress stopped by 2:17 p.m. and the evacuation lifted by 3:12 p.m. The Kern County Fire Department said the fire “was started by an electrical strike”. A KGET headline the same day blamed lightning and said no homes were damaged. Microsoft's “Unlocked” feature “The first five minutes” (Bruna Mori, 27 August 2026) was published after Microsoft's $5 million contribution to ALERTCalifornia. It included a $3 million Azure grant (announced by ALERTCalifornia on 3 February 2026). The feature says in 2023 ALERTCalifornia's cameras and AI helped crews rapidly detect and contain the Trotter Fire at 52 acres. Without AI-powered imaging, ALERTCalifornia founder Neal Driscoll estimates it may have spread to nearly 4,000 acres. It quotes Zachary Wells, deputy chief of the Kern County Fire Department and deputy director of operations at ALERTCalifornia. The claim is found only in Microsoft and ALERTCalifornia material. No fire-agency, regulator or independent news account of the fire mentions AI detection. None says which agency received the alert or its timing relative to 911 calls.", "replication": { "produced_by": [ "ALERTCalifornia's camera network with AI smoke detection covering the Tehachapi area", "A fire agency able to act on an early detection. Which agency received this alert is not stated", "A lightning or electrical-strike ignition on 14 August 2023 that crews stopped at 52 acres" ], "must_hold": [ "An alert reaching dispatch before or alongside 911 calls, which no cited source documents for this fire", "A counterfactual spread that depends on fuels, wind and response time. The 4,000-acre figure is an estimate by the network's founder" ], "echoes": [ { "date": "2024-07-06", "setting": "ALERTCalifornia AI camera alert at 2:33 a.m. sends Cal Fire engines to a fire near Auburn before any 911 call; held to a 30 x 30 ft area (AIBD-0007)", "outcome": "recurred", "source": "AIBD-0007" }, { "date": "2026-05-04", "setting": "Cal Fire battalion chief Brent Pascua, quoted by AP, says responses have started before 911 was called and in a few cases fires were put out with no 911 call ever received (aggregate statement)", "outcome": "recurred", "source": "Associated Press, 4 May 2026, https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0085", "title": "STF's VitorIA identifies at least 247 similar appeals in the controversy behind Tema 1.261; Plenary finds no general repercussion on 22 August 2023", "summary": "VitorIA identified at least 247 similar appeals in the controversy behind Tema 1.261; STF Plenary found no general repercussion on 22 August 2023 (final 23 September 2023)", "date_observed": "2023-08-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Brazil's Supremo Tribunal Federal (STF) uses VitorIA, operational since 2023, to compare the texts of incoming appeals. It groups cases raising similar legal questions for the staff who screen candidates for repercussão geral themes. The court says the tool does not judge cases. On 28 September 2026 the STF described the controversy behind Tema 1.261 (leading case ARE 1441934, on municipal teachers' personal pay advantages). VitorIA identified at least 247 appeals with similar legal questions by grouping on content similarity. The STF added that finding so many similar cases did not determine the result. The theme record shows the Plenary decided unanimously on 22 August 2023 that there is no general repercussion because the question is infraconstitutional. It became final on 23 September 2023. No cited source says what then happened to the 247 appeals. The STF credits VitorIA with four themes in 2023, 19 in 2024 and 11 in 2025. It says these figures do not refer to decisions taken with AI help and do not allow calculating accuracy or time saved.", "category": "benefit created", "unexpected": false, "purpose": "Identify clusters of textually similar appeals so the court can treat them jointly or open new general-repercussion themes", "system": "VitorIA (STF), textual-similarity clustering tool that groups appeals raising similar legal questions; in development in 2022 and operational in 2023 per the STF", "model_version": null, "developer": "Supremo Tribunal Federal (STF); the STF's 28 Sep 2026 item names no external developer and does not link VitorIA to the court's earlier Victor project", "deployer": "Supremo Tribunal Federal (STF)", "location": "Brasília, Brazil", "domain": "Courts: appellate case management", "segment": "Supreme court general-repercussion screening", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary or per-party outcome is documented. The STF says its figures do not refer to decisions taken with AI help and do not allow calculating time saved." }, { "group": "organizational", "depth": 2, "reason": "Material to the court's screening work: in one controversy VitorIA identified at least 247 appeals with similar legal questions. The STF describes this as the technology taking part in organizing and identifying patterns in its case flow. The STF does not quantify time saved." }, { "group": "societal", "depth": 1, "reason": "Small at system scale. One theme among the 34 the STF credits to VitorIA for 2023–2025." } ], "ai_role": { "status": "assessed", "statement": "The STF says its function precedes judgment: “identificar grupos de casos parecidos, que depois passam pela análise das equipes responsáveis e, quando necessário, dos ministros.” The identification of at least 247 similar appeals is attributed to VitorIA by the court itself. The court adds that finding them “não determinou o resultado”. The theme decision was made by the Plenary. Developer and deployer are the same public body (STF). The STF news items are the court documenting its own tool. No cited source names an external developer or links VitorIA to the court's earlier Victor project (STF with UnB). The STF said in August 2021 that Victor's classifier was not yet in production." }, "evidence": [ { "kind": "press release", "citation": "Supremo Tribunal Federal (2026). Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes. STF news, 28 Sep 2026.", "title": "Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes", "url": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "date": "2026-09-28", "written_by": "makers", "quote": "a VitorIA identificou pelo menos 247 recursos com questões jurídicas semelhantes" }, { "kind": "court document", "citation": "Supremo Tribunal Federal (2023). Repercussão Geral, Tema 1261, leading case ARE 1441934 (Relator: Ministro Presidente); decision of 22 Aug 2023, trânsito em julgado 23 Sep 2023.", "title": "Tema 1261 – Revisão da base de cálculo das vantagens pessoais remuneratórias de servidor público de magistério municipal", "url": "https://portal.stf.jus.br/jurisprudenciaRepercussao/tema.asp?num=1261", "date": null, "written_by": "makers", "quote": "Não há repercussão geral (questão infraconstitucional)" }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2021). Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral. STF news, 19 Aug 2021. Background on the court's earlier Victor project (STF with Universidade de Brasília); the item does not mention VitorIA.", "title": "Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral", "url": "https://portal.stf.jus.br/noticias/verNoticiaDetalhe.asp?idConteudo=471331", "date": "2021-08-19", "written_by": "makers", "quote": "todos os recursos recebidos diariamente no STF em meio eletrônico têm suas peças devidamente ocerizadas no mesmo dia" } ], "replication": { "produced_by": [ "Electronic appeals in machine-readable text for VitorIA to compare. The STF's 2021 Victor item documents same-day OCR of all electronic appeals since December 2020. No cited source ties that layer to VitorIA, so the dependency is inferred", "Textual-similarity clustering by VitorIA proposing groups of similar appeals", "Human screening teams and ministers deciding whether to open a theme and how to rule" ], "must_hold": [ "Appeals filed electronically with machine-readable text", "A procedural device (repercussão geral themes) that lets one decision govern many appeals", "Staff capacity to review proposed clusters" ], "echoes": [ { "date": "2024-01-01", "setting": "19 general-repercussion themes created with support from VitorIA data in 2024 (STF, 28 September 2026; year only)", "model_version": null, "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" }, { "date": "2025-01-01", "setting": "11 themes created with VitorIA support in 2025 (STF, 28 September 2026; year only)", "model_version": null, "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1497", "title": "Hidden Prompt Injection in Brazilian Labor-Court Petition Reportedly Tried to Manipulate Galileu", "url": "https://incidentdatabase.ai/cite/1497", "severity": null, "group": "organizational", "basis": "Brazilian court AI that reads case petitions (Galileu), the same kind of tool as STF's VitorIA, was targeted by hidden prompt injection, harming judicial integrity and defendants." }, "headline": "STF's VitorIA finds at least 247 similar appeals for Tema 1.261", "metric": "identified at least 247 similar appeals in the controversy behind Tema 1.261", "comparator": null, "later": { "status": "persisted", "date": "2026-09-28", "note": "The STF's September 2026 statement reports the tool still in use after Tema 1.261, credited with 19 themes in 2024 and 11 in 2025 after four in 2023 (years only), while saying the figures do not allow computing accuracy or time saved.", "quote": "A VitorIA auxiliou na identificação de quatro temas em 2023; em 2024, 19 foram criados com apoio de dados extraídos da ferramenta; já em 2025, foram 11.", "url": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" }, "value": null, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1497 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1497", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsourced claims that the Tema 1.261 decision settled or disposed of the grouped appeals and that parties obtained a faster disposition (personal depth now null); wrote “at least 247” in title, headline and metric as the STF does; dropped the Victor lineage, UnB credit and OCR dependency because no cited source links VitorIA to the Victor project, re-describing the 2021 Victor item as background; added that developer and deployer are the same public body (STF); and set the benefit type to Trustible's “Improved Knowledge Discovery” with a note that the STF says its figures do not allow calculating time saved or accuracy.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Supreme_Federal_Court; https://en.wikipedia.org/wiki/Supreme_Federal_Court", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' court document and two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0085", "catalog_version": "1.0.0", "source_fingerprint": "d4e33ebdaef438cc3f33a49e57b063b80abeb14577d84b683384c5ae0cc6720e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0085-source-0001", "AIBD-0085-source-0002", "AIBD-0085-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Supremo Tribunal Federal (STF); the STF's 28 Sep 2026 item names no external developer and does not link VitorIA to the court's earlier Victor project", "deployer": "Supremo Tribunal Federal (STF)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The STF says its function precedes judgment: “identificar grupos de casos parecidos, que depois passam pela análise das equipes responsáveis e, quando necessário, dos ministros.” The identification of at least 247 similar appeals is attributed to VitorIA by the court itself. The court adds that finding them “não determinou o resultado”. The theme decision was made by the Plenary. Developer and deployer are the same public body (STF). The STF news items are the court documenting its own tool. No cited source names an external developer or links VitorIA to the court's earlier Victor project (STF with UnB). The STF said in August 2021 that Victor's classifier was not yet in production." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The STF says its function precedes judgment: “identificar grupos de casos parecidos, que depois passam pela análise das equipes responsáveis e, quando necessário, dos ministros.” The identification of at least 247 similar appeals is attributed to VitorIA by the court itself. The court adds that finding them “não determinou o resultado”. The theme decision was made by the Plenary. Developer and deployer are the same public body (STF). The STF news items are the court documenting its own tool. No cited source names an external developer or links VitorIA to the court's earlier Victor project (STF with UnB). The STF said in August 2021 that Victor's classifier was not yet in production." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or per-party outcome is documented. The STF says its figures do not refer to decisions taken with AI help and do not allow calculating time saved." }, { "group": "organizational", "depth": 2, "reason": "Material to the court's screening work: in one controversy VitorIA identified at least 247 appeals with similar legal questions. The STF describes this as the technology taking part in organizing and identifying patterns in its case flow. The STF does not quantify time saved." }, { "group": "societal", "depth": 1, "reason": "Small at system scale. One theme among the 34 the STF credits to VitorIA for 2023–2025." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' court document and two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or per-party outcome is documented. The STF says its figures do not refer to decisions taken with AI help and do not allow calculating time saved." }, { "group": "organizational", "depth": 2, "reason": "Material to the court's screening work: in one controversy VitorIA identified at least 247 appeals with similar legal questions. The STF describes this as the technology taking part in organizing and identifying patterns in its case flow. The STF does not quantify time saved." }, { "group": "societal", "depth": 1, "reason": "Small at system scale. One theme among the 34 the STF credits to VitorIA for 2023–2025." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or per-party outcome is documented. The STF says its figures do not refer to decisions taken with AI help and do not allow calculating time saved." }, { "group": "organizational", "depth": 2, "reason": "Material to the court's screening work: in one controversy VitorIA identified at least 247 appeals with similar legal questions. The STF describes this as the technology taking part in organizing and identifying patterns in its case flow. The STF does not quantify time saved." }, { "group": "societal", "depth": 1, "reason": "Small at system scale. One theme among the 34 the STF credits to VitorIA for 2023–2025." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Brazilian court AI that reads case petitions (Galileu), the same kind of tool as STF's VitorIA, was targeted by hidden prompt injection, harming judicial integrity and defendants.", "links": [ { "database": "AI Incident Database", "identifier": "1497", "title": "Hidden Prompt Injection in Brazilian Labor-Court Petition Reportedly Tried to Manipulate Galileu", "url": "https://incidentdatabase.ai/cite/1497", "group": "organizational", "basis": "Brazilian court AI that reads case petitions (Galileu), the same kind of tool as STF's VitorIA, was targeted by hidden prompt injection, harming judicial integrity and defendants.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "identified at least 247 similar appeals in the controversy behind Tema 1.261", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "1497", "title": "Hidden Prompt Injection in Brazilian Labor-Court Petition Reportedly Tried to Manipulate Galileu", "url": "https://incidentdatabase.ai/cite/1497", "group": "organizational", "basis": "Brazilian court AI that reads case petitions (Galileu), the same kind of tool as STF's VitorIA, was targeted by hidden prompt injection, harming judicial integrity and defendants." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-09-28", "note": "The STF's September 2026 statement reports the tool still in use after Tema 1.261, credited with 19 themes in 2024 and 11 in 2025 after four in 2023 (years only), while saying the figures do not allow computing accuracy or time saved.", "quote": "A VitorIA auxiliou na identificação de quatro temas em 2023; em 2024, 19 foram criados com apoio de dados extraídos da ferramenta; já em 2025, foram 11.", "url": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0085" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Brazil's Supremo Tribunal Federal (STF) uses VitorIA, operational since 2023, to compare the texts of incoming appeals. It groups cases raising similar legal questions for the staff who screen candidates for repercussão geral themes. The court says the tool does not judge cases. On 28 September 2026 the STF described the controversy behind Tema 1.261 (leading case ARE 1441934, on municipal teachers' personal pay advantages). VitorIA identified at least 247 appeals with similar legal questions by grouping on content similarity. The STF added that finding so many similar cases did not determine the result. The theme record shows the Plenary decided unanimously on 22 August 2023 that there is no general repercussion because the question is infraconstitutional. It became final on 23 September 2023. No cited source says what then happened to the 247 appeals. The STF credits VitorIA with four themes in 2023, 19 in 2024 and 11 in 2025. It says these figures do not refer to decisions taken with AI help and do not allow calculating accuracy or time saved.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or per-party outcome is documented. The STF says its figures do not refer to decisions taken with AI help and do not allow calculating time saved." }, { "group": "organizational", "depth": 2, "reason": "Material to the court's screening work: in one controversy VitorIA identified at least 247 appeals with similar legal questions. The STF describes this as the technology taking part in organizing and identifying patterns in its case flow. The STF does not quantify time saved." }, { "group": "societal", "depth": 1, "reason": "Small at system scale. One theme among the 34 the STF credits to VitorIA for 2023–2025." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify clusters of textually similar appeals so the court can treat them jointly or open new general-repercussion themes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Brasília, Brazil", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify clusters of textually similar appeals so the court can treat them jointly or open new general-repercussion themes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-08-22", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1497 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1497", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsourced claims that the Tema 1.261 decision settled or disposed of the grouped appeals and that parties obtained a faster disposition (personal depth now null); wrote “at least 247” in title, headline and metric as the STF does; dropped the Victor lineage, UnB credit and OCR dependency because no cited source links VitorIA to the Victor project, re-describing the 2021 Victor item as background; added that developer and deployer are the same public body (STF); and set the benefit type to Trustible's “Improved Knowledge Discovery” with a note that the STF says its figures do not allow calculating time saved or accuracy.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Supreme_Federal_Court; https://en.wikipedia.org/wiki/Supreme_Federal_Court", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Electronic appeals in machine-readable text for VitorIA to compare. The STF's 2021 Victor item documents same-day OCR of all electronic appeals since December 2020. No cited source ties that layer to VitorIA, so the dependency is inferred", "Textual-similarity clustering by VitorIA proposing groups of similar appeals", "Human screening teams and ministers deciding whether to open a theme and how to rule" ], "must_hold": [ "Appeals filed electronically with machine-readable text", "A procedural device (repercussão geral themes) that lets one decision govern many appeals", "Staff capacity to review proposed clusters" ], "echoes": [ { "date": "2024-01-01", "setting": "19 general-repercussion themes created with support from VitorIA data in 2024 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" }, { "date": "2025-01-01", "setting": "11 themes created with VitorIA support in 2025 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Electronic appeals in machine-readable text for VitorIA to compare. The STF's 2021 Victor item documents same-day OCR of all electronic appeals since December 2020. No cited source ties that layer to VitorIA, so the dependency is inferred", "Textual-similarity clustering by VitorIA proposing groups of similar appeals", "Human screening teams and ministers deciding whether to open a theme and how to rule" ], "must_hold": [ "Appeals filed electronically with machine-readable text", "A procedural device (repercussão geral themes) that lets one decision govern many appeals", "Staff capacity to review proposed clusters" ], "echoes": [ { "date": "2024-01-01", "setting": "19 general-repercussion themes created with support from VitorIA data in 2024 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" }, { "date": "2025-01-01", "setting": "11 themes created with VitorIA support in 2025 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1497 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1497", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsourced claims that the Tema 1.261 decision settled or disposed of the grouped appeals and that parties obtained a faster disposition (personal depth now null); wrote “at least 247” in title, headline and metric as the STF does; dropped the Victor lineage, UnB credit and OCR dependency because no cited source links VitorIA to the Victor project, re-describing the 2021 Victor item as background; added that developer and deployer are the same public body (STF); and set the benefit type to Trustible's “Improved Knowledge Discovery” with a note that the STF says its figures do not allow calculating time saved or accuracy.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Supreme_Federal_Court; https://en.wikipedia.org/wiki/Supreme_Federal_Court", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Courts: appellate case management", "segment": "Supreme court general-repercussion screening" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Supremo Tribunal Federal (2026). Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes. STF news, 28 Sep 2026.", "title": "Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes", "url": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "date": "2026-09-28", "written_by": "makers", "quote": "a VitorIA identificou pelo menos 247 recursos com questões jurídicas semelhantes" }, { "kind": "court document", "citation": "Supremo Tribunal Federal (2023). Repercussão Geral, Tema 1261, leading case ARE 1441934 (Relator: Ministro Presidente); decision of 22 Aug 2023, trânsito em julgado 23 Sep 2023.", "title": "Tema 1261 – Revisão da base de cálculo das vantagens pessoais remuneratórias de servidor público de magistério municipal", "url": "https://portal.stf.jus.br/jurisprudenciaRepercussao/tema.asp?num=1261", "written_by": "makers", "quote": "Não há repercussão geral (questão infraconstitucional)" }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2021). Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral. STF news, 19 Aug 2021. Background on the court's earlier Victor project (STF with Universidade de Brasília); the item does not mention VitorIA.", "title": "Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral", "url": "https://portal.stf.jus.br/noticias/verNoticiaDetalhe.asp?idConteudo=471331", "date": "2021-08-19", "written_by": "makers", "quote": "todos os recursos recebidos diariamente no STF em meio eletrônico têm suas peças devidamente ocerizadas no mesmo dia" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0085-source-0001", "AIBD-0085-source-0002", "AIBD-0085-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Supremo Tribunal Federal (2026). Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes. STF news, 28 Sep 2026.", "title": "Inteligência artificial ajuda STF a identificar processos que discutem questões semelhantes", "url": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/", "date": "2026-09-28", "written_by": "makers", "quote": "a VitorIA identificou pelo menos 247 recursos com questões jurídicas semelhantes" }, { "kind": "court document", "citation": "Supremo Tribunal Federal (2023). Repercussão Geral, Tema 1261, leading case ARE 1441934 (Relator: Ministro Presidente); decision of 22 Aug 2023, trânsito em julgado 23 Sep 2023.", "title": "Tema 1261 – Revisão da base de cálculo das vantagens pessoais remuneratórias de servidor público de magistério municipal", "url": "https://portal.stf.jus.br/jurisprudenciaRepercussao/tema.asp?num=1261", "written_by": "makers", "quote": "Não há repercussão geral (questão infraconstitucional)" }, { "kind": "press release", "citation": "Supremo Tribunal Federal (2021). Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral. STF news, 19 Aug 2021. Background on the court's earlier Victor project (STF with Universidade de Brasília); the item does not mention VitorIA.", "title": "Projeto Victor avança em pesquisa e desenvolvimento para identificação dos temas de repercussão geral", "url": "https://portal.stf.jus.br/noticias/verNoticiaDetalhe.asp?idConteudo=471331", "date": "2021-08-19", "written_by": "makers", "quote": "todos os recursos recebidos diariamente no STF em meio eletrônico têm suas peças devidamente ocerizadas no mesmo dia" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "VitorIA identified at least 247 similar appeals in the controversy behind Tema 1.261; STF Plenary found no general repercussion on 22 August 2023 (final 23 September 2023)", "account": "Brazil's Supremo Tribunal Federal (STF) uses VitorIA, operational since 2023, to compare the texts of incoming appeals. It groups cases raising similar legal questions for the staff who screen candidates for repercussão geral themes. The court says the tool does not judge cases. On 28 September 2026 the STF described the controversy behind Tema 1.261 (leading case ARE 1441934, on municipal teachers' personal pay advantages). VitorIA identified at least 247 appeals with similar legal questions by grouping on content similarity. The STF added that finding so many similar cases did not determine the result. The theme record shows the Plenary decided unanimously on 22 August 2023 that there is no general repercussion because the question is infraconstitutional. It became final on 23 September 2023. No cited source says what then happened to the 247 appeals. The STF credits VitorIA with four themes in 2023, 19 in 2024 and 11 in 2025. It says these figures do not refer to decisions taken with AI help and do not allow calculating accuracy or time saved." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "VitorIA (STF), textual-similarity clustering tool that groups appeals raising similar legal questions; in development in 2022 and operational in 2023 per the STF" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Supremo Tribunal Federal (STF); the STF's 28 Sep 2026 item names no external developer and does not link VitorIA to the court's earlier Victor project" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "STF's VitorIA identifies at least 247 similar appeals in the controversy behind Tema 1.261; Plenary finds no general repercussion on 22 August 2023", "headline": "STF's VitorIA finds at least 247 similar appeals for Tema 1.261" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d4e33ebdaef438cc3f33a49e57b063b80abeb14577d84b683384c5ae0cc6720e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Brazil's Supremo Tribunal Federal (STF) uses VitorIA, operational since 2023, to compare the texts of incoming appeals. It groups cases raising similar legal questions for the staff who screen candidates for repercussão geral themes. The court says the tool does not judge cases. On 28 September 2026 the STF described the controversy behind Tema 1.261 (leading case ARE 1441934, on municipal teachers' personal pay advantages). VitorIA identified at least 247 appeals with similar legal questions by grouping on content similarity. The STF added that finding so many similar cases did not determine the result. The theme record shows the Plenary decided unanimously on 22 August 2023 that there is no general repercussion because the question is infraconstitutional. It became final on 23 September 2023. No cited source says what then happened to the 247 appeals. The STF credits VitorIA with four themes in 2023, 19 in 2024 and 11 in 2025. It says these figures do not refer to decisions taken with AI help and do not allow calculating accuracy or time saved.", "replication": { "produced_by": [ "Electronic appeals in machine-readable text for VitorIA to compare. The STF's 2021 Victor item documents same-day OCR of all electronic appeals since December 2020. No cited source ties that layer to VitorIA, so the dependency is inferred", "Textual-similarity clustering by VitorIA proposing groups of similar appeals", "Human screening teams and ministers deciding whether to open a theme and how to rule" ], "must_hold": [ "Appeals filed electronically with machine-readable text", "A procedural device (repercussão geral themes) that lets one decision govern many appeals", "Staff capacity to review proposed clusters" ], "echoes": [ { "date": "2024-01-01", "setting": "19 general-repercussion themes created with support from VitorIA data in 2024 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" }, { "date": "2025-01-01", "setting": "11 themes created with VitorIA support in 2025 (STF, 28 September 2026; year only)", "outcome": "recurred", "source": "https://noticias.stf.jus.br/postsnoticias/inteligencia-artificial-ajuda-stf-a-identificar-processos-que-discutem-questoes-semelhantes/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0039", "title": "A physics tutor more than doubled students’ median learning gains", "summary": "Harvard students who used PS2 Pal, powered by GPT-4-0613, learned more in less time than students in an active-learning class.", "date_observed": "2023-09-01", "date_basis": "event", "date_precision": "year", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "In autumn 2023 the course team of Harvard University's Physical Sciences 2 ran a randomized controlled crossover experiment with 194 students. It covered two topics, surface tension and fluid flow. Each student learned one topic in an in-class active-learning session and the other at home with a purpose-built AI tutor. The supplement identifies the tutor as PS2 Pal, built in TeachGPT and powered by GPT-4-0613. Instructors supplied the solutions and teaching prompts. The paper was published in Scientific Reports on 3 June 2025. It reports that “students learn significantly more in less time when using the AI tutor”. Median learning gains were over double those of the class session, with a median of 49 minutes on task, and higher engagement and motivation. The paper places the study in “the Fall 2023 semester” and “the ninth and tenth weeks of the course” without a calendar date. The lessons themselves came later in the term.", "category": "general benefit", "unexpected": false, "purpose": "The tutor was built to teach these physics lessons with research-based pedagogy. The learning gain was that purpose.", "system": "PS2 Pal, Harvard’s physics tutor built in TeachGPT using GPT-4-0613", "model_version": "GPT-4-0613", "developer": "Harvard University (Kestin, Miller, Klales, Milbourne, Ponti)", "deployer": "Harvard University, Physical Sciences 2", "location": "Cambridge, United States", "domain": "Education", "segment": "Undergraduate physics", "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Students achieved a measurable improvement in immediate post-test scores. The trial did not establish a lasting change in their capabilities." }, { "group": "organizational", "depth": 2, "reason": "The course demonstrated a teaching format with better post-test results. This uses the same trial evidence as the student assessment, not a separate organizational study." } ], "ai_role": { "status": "assessed", "statement": "The language model delivered the instruction. The comparison was active learning taught in class. The authors credit the research-based design (prompts, scaffolding) beside the model." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Kestin G, Miller K, Klales A, Milbourne T, Ponti G (2025). AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting. 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Peer groups of two or three students were assigned together, then switched conditions the following week." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "structured", "data": { "median_post_test": { "AI": 4.5, "classroom": 3.5, "unit": "points" }, "learning_gain_definition": "Each condition’s median post-test score compared with the pooled pre-test median of 2.75.", "reported_gain_comparison": "More than double with AI.", "linear_regression_effect": { "standard_deviations": 0.63, "p_less_than": 1e-08 }, "rank_sum_test": { "z": -5.6, "p_less_than": 1e-08 }, "quantile_regression_effect_range": { "minimum": 0.73, "maximum": 1.3, "unit": "standard deviations", "interpretation": "Authors’ alternative estimates to address the ceiling effect; not a confidence interval." } } }, "provenance": { "kind": "source_review", "basis": "Results: Learning gains: post-test scores; Learning gains: linear regression model; Supplementary Table S1.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Median post-test scores were 4.5 with AI and 3.5 in class. The adjusted advantage was 0.63 standard deviations." } }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "Each participant was assigned one AI lesson and one classroom lesson in consecutive weeks. The AI lessons took a median of 49 minutes." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design; Results: Time on task; Supplementary Table S3.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Each participant was assigned one AI lesson and one classroom lesson in consecutive weeks. The AI lessons took a median of 49 minutes." } }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "Harvard PS2 tutoring study, protocol IRB23-0797." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design. This is the Harvard ethics protocol identifier, not a trial-registry identifier.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Harvard PS2 tutoring study, protocol IRB23-0797." } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used quizzes before and after each lesson, logged time with the tutor, and asked students about their experience on a five-point scale." }, "provenance": { "kind": "source_review", "basis": "Results: Learning gains: post-test scores; Time on task; AI tutor: students’ perceptions of learning; Supplementary Material 1: Perception of Learning Experience Questions.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Researchers used quizzes before and after each lesson, logged time with the tutor, and asked students about their experience on a five-point scale." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "structured", "data": { "learning": { "measure": "Post-test score compared with the pooled pre-test baseline", "unit": "points", "AI_post_test_median": 4.5, "classroom_post_test_median": 3.5, "pooled_pre_test_median": 2.75, "pooled_pre_test_observations": 316 }, "time": { "unit": "minutes", "AI_median": 49, "classroom_assumed_learning_time": 60, "AI_proportion_under_60_minutes": 0.7 }, "experience": { "scale": "Five-point agreement scale", "engagement_mean": { "AI": 4.1, "classroom": 3.6 }, "motivation_mean": { "AI": 3.4, "classroom": 3.1 }, "enjoyment_and_growth_mindset": "No statistically significant difference." } } }, "provenance": { "kind": "source_review", "basis": "Results: Learning gains: post-test scores; Time on task; AI tutor: students’ perceptions of learning; Supplementary Material 1: Perception of Learning Experience Questions.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Post-test scores, time spent learning, and students’ ratings of engagement, motivation, enjoyment, and growth mindset." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "structured", "data": { "supplement_url": "https://media.springernature.com/original/springer-static/esm/art%3A10.1038%2Fs41598-025-97652-6/MediaObjects/41598_2025_97652_MOESM1_ESM.docx", "materials": [ "Assignment persona", "An example question-specific prompt and worked solution", "Test-validation measures", "Study design", "Regression coefficients" ], "dataset_url": "https://github.com/HarvardAItutor/Study-Data-v4", "dataset_file": "Harvard_AI_Tutor_Study_Data.dta", "repository_commit": "c5bf864c5369fbedd61c248743a89da95dcaa114", "inventory_checked_on": "2026-10-25", "data_reanalyzed": false, "analysis_scripts_in_repository": false } }, "provenance": { "kind": "source_review", "basis": "Data availability; Supplementary Material 1; original repository file inventory, checked on 25 October 2026. No analysis scripts appeared in that inventory.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The supplement contains teaching prompts and methods. The authors also published a Stata data file on GitHub." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "structured", "data": { "institution": "Harvard University", "course": "Physical Sciences 2", "term": "fall 2023", "course_weeks": [ 9, 10 ], "enrolled": 233, "eligible": 194, "allocation_groups": [ 96, 98 ], "eligibility": [ "Consent", "Participation in both teaching formats", "Completion of pre-tests and post-tests" ], "post_test_observations": { "AI": 142, "classroom": 174 }, "topics": [ "Surface tension", "Fluid flow" ] } }, "provenance": { "kind": "source_review", "basis": "Methods: Study population; Results: Learning gains: post-test scores; Supplementary Table S2A.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Harvard’s introductory physics course for life-science students. The paper reports 194 eligible students and compares 142 AI post-tests with 174 classroom post-tests.", "editor_note": "Methods reports 194 eligible students. Results gives 142 AI post-tests and 174 classroom post-tests. Whether these counts describe the same analysis population is unclear." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The study covered two lessons at one university. High scores limited the test’s ability to distinguish further gains." }, "provenance": { "kind": "source_review", "basis": "Methods: Study population; Results: Learning gains: post-test scores and linear regression model; Discussion: Context, limitations, and future directions. 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Students then worked with the tutor on their own. A separate team member wrote the tests." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design; Additional controls; Supplementary Material 1: AI Tutor System and Implementation.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Instructors wrote the worked solutions and tested the prompts before use. Students then worked with the tutor on their own. 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Instructors supplied videos, questions, and worked solutions." }, "provenance": { "kind": "source_review", "basis": "Discussion: Context, limitations, and future directions; Supplementary Material 1: AI Tutor System and Implementation and Figure S1.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students needed internet access to use TeachGPT with GPT-4-0613. Instructors supplied videos, questions, and worked solutions." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Students in Harvard’s Physical Sciences 2 course, and the course that provided the lessons." }, "provenance": { "kind": "source_review", "basis": "Methods: Study population; Course setting; the organizational assessment concerns the same measured teaching result.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students in Harvard’s Physical Sciences 2 course, and the course that provided the lessons." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "structured", "data": { "course_enrollment": 233, "eligible_participants": 194, "post_test_observations": { "AI": 142, "classroom": 174 }, "counting_note": "The study reports group results, not the number of students who individually benefited." } }, "provenance": { "kind": "source_review", "basis": "Methods: Study population; Results: Learning gains: post-test scores.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The course enrolled 233 students, of whom 194 were eligible for the study. The paper does not count individual beneficiaries." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Learning" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "Students had higher post-test scores after the AI lesson and spent a median of 49 minutes on it." }, "provenance": { "kind": "source_review", "basis": "Results: Learning gains: post-test scores; Time on task.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students had higher post-test scores after the AI lesson and spent a median of 49 minutes on it." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Higher post-test scores occurred among students with lower and higher prior physics scores. The at-home lesson required internet access." }, "provenance": { "kind": "source_review", "basis": "Methods: Study population, subgroups below and above 40% on the Force Concept Inventory; Discussion: Context, limitations, and future directions.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Higher post-test scores occurred among students with lower and higher prior physics scores. The at-home lesson required internet access." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "Learning was tested immediately after each lesson. The study does not report later retention." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design; Discussion: Context, limitations, and future directions.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Learning was tested immediately after each lesson. 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Both depend on the same study.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two outcomes within one study: student learning and the course’s teaching capability." } }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Students achieved a measurable improvement in immediate post-test scores. The trial did not establish a lasting change in their capabilities." }, { "group": "organizational", "depth": 2, "reason": "The course demonstrated a teaching format with better post-test results. This uses the same trial evidence as the student assessment, not a separate organizational study." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Observed in the trial." }, "provenance": { "kind": "source_review", "basis": "Results: Learning gains: post-test scores; Time on task.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Observed in the trial." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Preparing each AI lesson took several days, after several months of platform development. Thirty percent of AI sessions exceeded the classroom’s assumed 60 minutes of learning." }, "provenance": { "kind": "source_review", "basis": "Methods: Additional controls; Results: Time on task; Supplementary Material 1: AI Tutor System and Implementation.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Preparing each AI lesson took several days, after several months of platform development. Thirty percent of AI sessions exceeded the classroom’s assumed 60 minutes of learning." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The tutor was built to teach these physics lessons with research-based pedagogy. The learning gain was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cambridge, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The tutor was built to teach these physics lessons with research-based pedagogy. The learning gain was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "occurrence": { "year": 2023, "season": "fall", "course_weeks": [ 9, 10 ], "precision": "year" }, "publication": { "date": "2025-06-03", "precision": "day" }, "reviewed_on": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Methods: Study population; Course setting; article publication metadata.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The lessons took place in weeks 9 and 10 of fall 2023. The paper was published on 3 June 2025." } }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Lesson content pre-structured by instructors into the tutor", "Prompts enforcing research-based pedagogy rather than answer-giving", "Students with access to the tutor at home and a pre/post test design" ], "must_hold": [ "The model follows complex pedagogical prompts", "Topics are self-contained and short (two lessons tested)" ], "echoes": [ { "date": "2024-06-01", "setting": "Edo State, Nigeria: six-week after-school program (June-July 2024; first day of month used) for first-year senior secondary students in Benin City using Microsoft Copilot (GPT-4); 0.31 SD overall, 0.23 SD in English; World Bank Policy Research Working Paper 11125 (May 2025)", "model_version": "GPT-4 via Microsoft Copilot", "outcome": "recurred", "source": "ERIC record ED676624 https://eric.ed.gov/?q=source:%22World+Bank%22&id=ED676624 (quote: 'a significant improvement of 0.31 standard deviation'); World Bank blog 9 Jan 2025 https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-Transforming-learning-in-Nigeria (quote: 'equivalent to nearly two years of typical learning in just six weeks')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The cited Nigerian program used Microsoft Copilot. It was a related study, not a replication of PS2 Pal." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "Instructors supplied carefully tested prompts, worked solutions, and videos. Students needed internet access and time to work at their own pace. The study covered two introductory topics." }, "provenance": { "kind": "source_review", "basis": "Discussion: Context, limitations, and future directions; Methods: Additional controls; Supplementary Material 1.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Instructors supplied carefully tested prompts, worked solutions, and videos. Students needed internet access and time to work at their own pace. The study covered two introductory topics." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 793 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/793", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Softened the title and summary from “GPT-4-based” to “LLM-based (GPT-4)” and quoted the Methods and Discussion sentences in the account as the paper's only basis for naming GPT-4, corrected the date disclosure to say that the paper places the lessons in the ninth and tenth weeks of the Fall 2023 semester with 1 September used as a placeholder, and dropped “public” from the Nigeria echo setting because neither cited source states it.", "source": "Kestin G et al. (2025) Scientific Reports, PMC12179260: https://pmc.ncbi.nlm.nih.gov/articles/PMC12179260/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12179260/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Harvard_University; https://en.wikipedia.org/wiki/Harvard_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified the AI model, software, configuration, and human controls from the original paper, supplement, or author documentation. Replaced the superseded account of the model’s identity with the supplement’s explicit identification. 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They switched formats for the second lesson." }, "provenance": { "kind": "source_review", "basis": "Methods: Study design; Supplementary Table S3.", "record_fields": [], "source_refs": [ "AIBD-0039-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Students completed a quiz, studied with PS2 Pal at home or attended an active-learning class, and took another quiz. They switched formats for the second lesson." } } }, "summary": { "total": 91, "addressed": 91, "known": 71, "reviewed": 60, "record_mapped": 22, "not_assessed": 9, "complete": false, "by_state": { "value_present": 71, "not_reported": 11, "unresolved": 0, "not_assessed": 9, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0338", "title": "IRS applies AI and machine learning to select large partnerships for examination (IR-2023–166, 8 September 2023); two AI models prioritize partnership audits", "summary": "IRS (8 September 2023): AI to help detect cheating and select cases; exams planned for 75 partnerships averaging over $10bn in assets. GAO (Jun 2024): two AI models prioritize partnership audits.", "date_observed": "2023-09-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 8 September 2023 the Internal Revenue Service (IRS) announced (IR-2023–166) a compliance effort funded by the Inflation Reduction Act. It would use improved technology and artificial intelligence to help compliance teams detect tax cheating, identify emerging compliance threats and improve case-selection tools. It described data scientists and tax-enforcement experts collaborating to apply machine learning to compliance risk in partnership, income and international tax. It planned to open examinations of 75 of the largest US partnerships, each averaging more than $10 billion in assets. These fall under the expanded Large Partnership Compliance program launched in 2021. A US Government Accountability Office (GAO) WatchBlog post of 6 June 2024 adds detail. The IRS already uses AI models to select a representative sample of returns for its annual audits. It uses two AI models to prioritize partnership returns for audit. It is piloting a new model for refundable-credit audits that IRS officials said finds risky taxpayers more effectively than the previous model. GAO recommended documenting the models and noted design weaknesses that may limit their ability to identify the highest-risk returns objectively. No cited source attributes a recovered amount to the AI selection.", "category": "general benefit", "unexpected": false, "purpose": "Built to select high-risk returns for examination and to detect compliance threats. The claimed benefit is that purpose, with no attributable outcome documented.", "system": "IRS AI and machine-learning case-selection models (two partnership prioritization models; a refundable-credit audit selection model in pilot; machine learning for partnership, income and international tax risk)", "model_version": "TY 2021 LPC model (Large Partnership Compliance return selection model)", "developer": "Internal Revenue Service (in-house data scientists with tax-enforcement experts)", "deployer": "Internal Revenue Service", "location": "United States (national)", "domain": "Public administration: tax enforcement", "segment": "National revenue agency", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The good is audit case selection for the agency, and no recovered amount is attributed to AI in the sources.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome is documented." }, { "group": "organizational", "depth": null, "reason": "The IRS gives no results from the AI-selected examinations and GAO reports only officials' pilot claims." }, { "group": "societal", "depth": null, "reason": "No revenue or fairness outcome is attributed to the models." } ], "ai_role": { "status": "assessed", "statement": "The models prioritize or select returns for human examiners. Examinations and any assessments are human decisions. The IRS release is the deployer's own account of a system it builds in-house. The GAO post is an independent government source that relays IRS officials' claims about the pilot model and adds caveats. Neither reports an outcome attributable to the AI." }, "evidence": [ { "kind": "press release", "citation": "Internal Revenue Service (2023). IRS announces sweeping effort to restore fairness to tax system with Inflation Reduction Act funding, new compliance efforts focused on increasing scrutiny on high-income, partnerships, corporations and promoters abusing tax rules. IR-2023-166, 8 Sep 2023.", "title": "IR-2023-166: IRS announces sweeping effort to restore fairness to tax system", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "Artificial Intelligence that will help IRS compliance teams better detect tax cheating, identify emerging compliance threats and improve case selection tools" }, { "kind": "press release", "citation": "Internal Revenue Service (2023). IR-2023-166, section on large partnerships and machine learning.", "title": "IR-2023-166 (machine learning for compliance risk)", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "cutting-edge machine learning technology to identify potential compliance risk in the areas of partnership tax, general income tax and accounting, and international tax" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap. GAO WatchBlog, 6 Jun 2024.", "title": "Artificial Intelligence May Help IRS Close the Tax Gap", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "IRS currently uses two AI models to help prioritize partnership returns for audit" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap, GAO WatchBlog, 6 Jun 2024 (refundable-credit pilot claim and caveat).", "title": "Artificial Intelligence May Help IRS Close the Tax Gap (pilot model and design weaknesses)", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "may limit these models' ability to objectively identify the most high-risk returns" }, { "kind": "report", "citation": "Treasury Inspector General for Tax Administration (2025). The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance. Report 2025-308-022, 19 May 2025.", "title": "The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf", "date": "2025-05-19", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Inflation Reduction Act funding for IRS compliance work", "Collaboration between IRS data scientists and tax-enforcement experts", "Partnership return data for the Large Partnership Compliance program launched in 2021" ], "must_hold": [ "Sustained funding and staffing for the examinations the models select", "Documentation of the models, which GAO found lacking in 2024", "Correction of the design weaknesses GAO said may limit objective identification of high-risk returns" ], "echoes": [] }, "paired_incident": null, "headline": "IRS applies AI to select large partnerships for examination", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2025-05-19", "note": "TIGTA's May 2025 audit found the Large Partnership Compliance model still in production, with the first 82 high-risk TY 2021 returns under examination, no closed examination results yet, and uncertainty over reduced staffing after the end of the contractor's work.", "quote": "According to LB&I Division management, the first 82 large partnership returns identified as high risk by the LPC model and currently under examination are TY 2021 returns. On average, these returns have more than $10 billion in assets.", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf" }, "value": { "amount": "approximately $26.1 million", "what": "additional tax assessments yearly that IRS management estimates from reassigning 14 classifiers to examinations after the Form 1040 return classification AI model automated classification (an SB/SE individual-return model, not the partnership models)", "who": "the Internal Revenue Service (U.S. Treasury)", "estimate": true, "quote": "According to IRS management, automating the classification function has allowed the IRS to reassign 14 classifiers to the examination function and they estimate the increased examinations could generate approximately $26.1 million in additional tax assessments yearly.", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version, the value as stated from the cited sources.", "source": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf; https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf; https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Internal_Revenue_Service; https://en.wikipedia.org/wiki/Internal_Revenue_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: two independent reports and the makers' press release. 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On average, these returns have more than $10 billion in assets.", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0338" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The good is audit case selection for the agency, and no recovered amount is attributed to AI in the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 8 September 2023 the Internal Revenue Service (IRS) announced (IR-2023–166) a compliance effort funded by the Inflation Reduction Act. It would use improved technology and artificial intelligence to help compliance teams detect tax cheating, identify emerging compliance threats and improve case-selection tools. It described data scientists and tax-enforcement experts collaborating to apply machine learning to compliance risk in partnership, income and international tax. It planned to open examinations of 75 of the largest US partnerships, each averaging more than $10 billion in assets. These fall under the expanded Large Partnership Compliance program launched in 2021. A US Government Accountability Office (GAO) WatchBlog post of 6 June 2024 adds detail. The IRS already uses AI models to select a representative sample of returns for its annual audits. It uses two AI models to prioritize partnership returns for audit. It is piloting a new model for refundable-credit audits that IRS officials said finds risky taxpayers more effectively than the previous model. GAO recommended documenting the models and noted design weaknesses that may limit their ability to identify the highest-risk returns objectively. No cited source attributes a recovered amount to the AI selection.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual outcome is documented." }, { "group": "organizational", "reason": "The IRS gives no results from the AI-selected examinations and GAO reports only officials' pilot claims." }, { "group": "societal", "reason": "No revenue or fairness outcome is attributed to the models." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to select high-risk returns for examination and to detect compliance threats. The claimed benefit is that purpose, with no attributable outcome documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United States (national)", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to select high-risk returns for examination and to detect compliance threats. The claimed benefit is that purpose, with no attributable outcome documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-09-08", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version, the value as stated from the cited sources.", "source": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf; https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf; https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Internal_Revenue_Service; https://en.wikipedia.org/wiki/Internal_Revenue_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Inflation Reduction Act funding for IRS compliance work", "Collaboration between IRS data scientists and tax-enforcement experts", "Partnership return data for the Large Partnership Compliance program launched in 2021" ], "must_hold": [ "Sustained funding and staffing for the examinations the models select", "Documentation of the models, which GAO found lacking in 2024", "Correction of the design weaknesses GAO said may limit objective identification of high-risk returns" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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https://en.wikipedia.org/wiki/Internal_Revenue_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: tax enforcement", "segment": "National revenue agency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Internal Revenue Service (2023). IRS announces sweeping effort to restore fairness to tax system with Inflation Reduction Act funding, new compliance efforts focused on increasing scrutiny on high-income, partnerships, corporations and promoters abusing tax rules. IR-2023-166, 8 Sep 2023.", "title": "IR-2023-166: IRS announces sweeping effort to restore fairness to tax system", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "Artificial Intelligence that will help IRS compliance teams better detect tax cheating, identify emerging compliance threats and improve case selection tools" }, { "kind": "press release", "citation": "Internal Revenue Service (2023). IR-2023-166, section on large partnerships and machine learning.", "title": "IR-2023-166 (machine learning for compliance risk)", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "cutting-edge machine learning technology to identify potential compliance risk in the areas of partnership tax, general income tax and accounting, and international tax" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap. GAO WatchBlog, 6 Jun 2024.", "title": "Artificial Intelligence May Help IRS Close the Tax Gap", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "IRS currently uses two AI models to help prioritize partnership returns for audit" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap, GAO WatchBlog, 6 Jun 2024 (refundable-credit pilot claim and caveat).", "title": "Artificial Intelligence May Help IRS Close the Tax Gap (pilot model and design weaknesses)", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "may limit these models' ability to objectively identify the most high-risk returns" }, { "kind": "report", "citation": "Treasury Inspector General for Tax Administration (2025). The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance. Report 2025-308-022, 19 May 2025.", "title": "The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf", "date": "2025-05-19", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0338-source-0001", "AIBD-0338-source-0002", "AIBD-0338-source-0003", "AIBD-0338-source-0004", "AIBD-0338-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Internal Revenue Service (2023). IRS announces sweeping effort to restore fairness to tax system with Inflation Reduction Act funding, new compliance efforts focused on increasing scrutiny on high-income, partnerships, corporations and promoters abusing tax rules. IR-2023-166, 8 Sep 2023.", "title": "IR-2023-166: IRS announces sweeping effort to restore fairness to tax system", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "Artificial Intelligence that will help IRS compliance teams better detect tax cheating, identify emerging compliance threats and improve case selection tools" }, { "kind": "press release", "citation": "Internal Revenue Service (2023). IR-2023-166, section on large partnerships and machine learning.", "title": "IR-2023-166 (machine learning for compliance risk)", "url": "https://www.irs.gov/newsroom/irs-announces-sweeping-effort-to-restore-fairness-to-tax-system-with-inflation-reduction-act-funding-new-compliance-efforts", "date": "2023-09-08", "written_by": "makers", "quote": "cutting-edge machine learning technology to identify potential compliance risk in the areas of partnership tax, general income tax and accounting, and international tax" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap. GAO WatchBlog, 6 Jun 2024.", "title": "Artificial Intelligence May Help IRS Close the Tax Gap", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "IRS currently uses two AI models to help prioritize partnership returns for audit" }, { "kind": "report", "citation": "U.S. Government Accountability Office (2024). Artificial Intelligence May Help IRS Close the Tax Gap, GAO WatchBlog, 6 Jun 2024 (refundable-credit pilot claim and caveat).", "title": "Artificial Intelligence May Help IRS Close the Tax Gap (pilot model and design weaknesses)", "url": "https://www.gao.gov/blog/artificial-intelligence-may-help-irs-close-tax-gap", "date": "2024-06-06", "written_by": "independent", "quote": "may limit these models' ability to objectively identify the most high-risk returns" }, { "kind": "report", "citation": "Treasury Inspector General for Tax Administration (2025). The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance. Report 2025-308-022, 19 May 2025.", "title": "The IRS Could Leverage Examination Results in Artificial Intelligence Examination Case Selection Models and Improve Processes to Evaluate Performance", "url": "https://www.oversight.gov/sites/default/files/documents/reports/2025-05/2025308022fr.pdf", "date": "2025-05-19", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "IRS (8 September 2023): AI to help detect cheating and select cases; exams planned for 75 partnerships averaging over $10bn in assets. 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It uses two AI models to prioritize partnership returns for audit. It is piloting a new model for refundable-credit audits that IRS officials said finds risky taxpayers more effectively than the previous model. GAO recommended documenting the models and noted design weaknesses that may limit their ability to identify the highest-risk returns objectively. No cited source attributes a recovered amount to the AI selection." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The models prioritized tax returns for human examiners." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The IRS used its Large Partnership Compliance model for tax year 2021." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The Large Partnership Compliance model for tax year 2021." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "TY 2021 LPC model (Large Partnership Compliance return selection model)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "IRS AI and machine-learning case-selection models (two partnership prioritization models; a refundable-credit audit selection model in pilot; machine learning for partnership, income and international tax risk)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Internal Revenue Service (in-house data scientists with tax-enforcement experts)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "IRS applies AI and machine learning to select large partnerships for examination (IR-2023–166, 8 September 2023); two AI models prioritize partnership audits", "headline": "IRS applies AI to select large partnerships for examination" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "60071e95f8b4a67a5862bac21ef2520dee82f77e4588dd9c0878d40d985e2b07" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 8 September 2023 the Internal Revenue Service (IRS) announced (IR-2023–166) a compliance effort funded by the Inflation Reduction Act. It would use improved technology and artificial intelligence to help compliance teams detect tax cheating, identify emerging compliance threats and improve case-selection tools. It described data scientists and tax-enforcement experts collaborating to apply machine learning to compliance risk in partnership, income and international tax. It planned to open examinations of 75 of the largest US partnerships, each averaging more than $10 billion in assets. These fall under the expanded Large Partnership Compliance program launched in 2021. A US Government Accountability Office (GAO) WatchBlog post of 6 June 2024 adds detail. The IRS already uses AI models to select a representative sample of returns for its annual audits. It uses two AI models to prioritize partnership returns for audit. It is piloting a new model for refundable-credit audits that IRS officials said finds risky taxpayers more effectively than the previous model. GAO recommended documenting the models and noted design weaknesses that may limit their ability to identify the highest-risk returns objectively. No cited source attributes a recovered amount to the AI selection.", "replication": { "produced_by": [ "Inflation Reduction Act funding for IRS compliance work", "Collaboration between IRS data scientists and tax-enforcement experts", "Partnership return data for the Large Partnership Compliance program launched in 2021" ], "must_hold": [ "Sustained funding and staffing for the examinations the models select", "Documentation of the models, which GAO found lacking in 2024", "Correction of the design weaknesses GAO said may limit objective identification of high-risk returns" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0060", "title": "ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors over three years; pediatric neurosurgeon confirms and operates", "summary": "Mother entered son's MRI notes and symptoms into ChatGPT; it suggested tethered cord syndrome, confirmed and operated on by a neurosurgeon.", "date_observed": "2023-09-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In 2023 Courtney, mother of Alex, entered his magnetic resonance imaging (MRI) notes and symptom observations line by line into ChatGPT. Alex's chronic pain began at age 4 during the COVID-19 lockdown. He went on to grind his teeth, stop growing taller and drag his left foot. 17 physicians over three years had found no diagnosis. ChatGPT suggested tethered cord syndrome. She booked a new neurosurgeon, Dr Holly Gilmer of the Michigan Head & Spine Institute. Gilmer reviewed the MRI, found spina bifida occulta with a tethered cord and operated to release it. That was a few weeks before the TODAY.com report (11 September 2023, updated 12 September 2023). Alex was still recovering. The month of the ChatGPT query and the surgery date are not given.", "category": "benefit created", "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant built to answer user prompts. Producing a diagnostic hypothesis from entered clinical notes is an instance of that general function, not a designed or validated medical capability.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": null, "location": null, "domain": "Healthcare - pediatric neurosurgery / rare diagnosis", "segment": "Caregiver-initiated use of a consumer LLM", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A child with three years of chronic pain, mobility problems and growth delay received a diagnosis and corrective spinal surgery. The report describes him as recovering, so the benefit is life-changing but not shown to be life-saving." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT produced the hypothesis (tethered cord syndrome) that the mother took to a new neurosurgeon. The diagnosis itself was made by the neurosurgeon from the existing MRI, and the treatment was surgical. ChatGPT's contribution was ending the diagnostic search. The source is a news report quoting the mother and treating neurosurgeon, not a peer-reviewed case report." }, "evidence": [ { "kind": "news report", "citation": "Holohan M (2023). TODAY.com (NBC News) report on a mother's use of ChatGPT to identify her son's tethered cord syndrome, updated 12 September 2023.", "title": "A boy saw 17 doctors over 3 years for chronic pain. ChatGPT found the diagnosis", "url": "https://www.today.com/health/mom-chatgpt-diagnosis-pain-rcna101843", "date": "2023-09-11", "written_by": "independent", "quote": "ChatGPT suggested a diagnosis of tethered cord syndrome, 'it made a lot of sense,' she recalls." }, { "kind": "news report", "citation": "Holohan M (2023). TODAY.com (NBC News), updated 12 September 2023; quotation from Dr Holly Gilmer, pediatric neurosurgeon, Michigan Head & Spine Institute, who treated Alex.", "title": "A boy saw 17 doctors over 3 years for chronic pain. ChatGPT found the diagnosis", "url": "https://www.today.com/health/mom-chatgpt-diagnosis-pain-rcna101843", "date": "2023-09-11", "written_by": "independent", "quote": "\"We detach the cord from where it is stuck at the bottom of the tailbone essentially,\" Gilmer says. \"That releases the tension.\"" } ], "replication": { "produced_by": [ "A caregiver entering detailed clinical records (MRI report text, symptom observations) in a general-purpose language model", "A clinician willing to re-review existing imaging against the proposed diagnosis" ], "must_hold": [ "The model's hypothesis is verified by a qualified clinician against imaging or testing before treatment", "The caregiver has access to the patient's own records to supply to the model" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1166", "title": "ChatGPT Reportedly Suggests Sodium Bromide as Chloride Substitute, Leading to Bromism and Hospitalization", "url": "https://incidentdatabase.ai/cite/1166", "severity": null, "group": "personal", "basis": "Same system and developer, both lay users acting on ChatGPT health guidance; the incident's 60-year-old man substituted sodium bromide for salt and was hospitalized three weeks with bromism and psychosis." }, "headline": "ChatGPT suggests tethered cord syndrome; neurosurgeon confirms", "metric": null, "comparator": { "against": "17 physicians consulted over three years", "before": "But Alex still had no diagnosis that explained all his symptoms.", "after": "when ChatGPT suggested a diagnosis of tethered cord syndrome, 'it made a lot of sense,'", "basis": "assumed", "quote": "In total, they visited 17 different doctors over three years. 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ChatGPT found the diagnosis", "url": "https://www.today.com/health/mom-chatgpt-diagnosis-pain-rcna101843", "date": "2023-09-11", "written_by": "independent", "quote": "\"We detach the cord from where it is stuck at the bottom of the tailbone essentially,\" Gilmer says. \"That releases the tension.\"" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0060-source-0001", "AIBD-0060-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Holohan M (2023). TODAY.com (NBC News) report on a mother's use of ChatGPT to identify her son's tethered cord syndrome, updated 12 September 2023.", "title": "A boy saw 17 doctors over 3 years for chronic pain. ChatGPT found the diagnosis", "url": "https://www.today.com/health/mom-chatgpt-diagnosis-pain-rcna101843", "date": "2023-09-11", "written_by": "independent", "quote": "ChatGPT suggested a diagnosis of tethered cord syndrome, 'it made a lot of sense,' she recalls." }, { "kind": "news report", "citation": "Holohan M (2023). TODAY.com (NBC News), updated 12 September 2023; quotation from Dr Holly Gilmer, pediatric neurosurgeon, Michigan Head & Spine Institute, who treated Alex.", "title": "A boy saw 17 doctors over 3 years for chronic pain. ChatGPT found the diagnosis", "url": "https://www.today.com/health/mom-chatgpt-diagnosis-pain-rcna101843", "date": "2023-09-11", "written_by": "independent", "quote": "\"We detach the cord from where it is stuck at the bottom of the tailbone essentially,\" Gilmer says. \"That releases the tension.\"" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Mother entered son's MRI notes and symptoms into ChatGPT; it suggested tethered cord syndrome, confirmed and operated on by a neurosurgeon.", "account": "In 2023 Courtney, mother of Alex, entered his magnetic resonance imaging (MRI) notes and symptom observations line by line into ChatGPT. Alex's chronic pain began at age 4 during the COVID-19 lockdown. He went on to grind his teeth, stop growing taller and drag his left foot. 17 physicians over three years had found no diagnosis. ChatGPT suggested tethered cord syndrome. She booked a new neurosurgeon, Dr Holly Gilmer of the Michigan Head & Spine Institute. Gilmer reviewed the MRI, found spina bifida occulta with a tethered cord and operated to release it. That was a few weeks before the TODAY.com report (11 September 2023, updated 12 September 2023). Alex was still recovering. The month of the ChatGPT query and the surgery date are not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors over three years; pediatric neurosurgeon confirms and operates", "headline": "ChatGPT suggests tethered cord syndrome; neurosurgeon confirms" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "138819f530d8b799e1a23a48da6885b4577868fac4a0c10813dba09825ec1d7a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In 2023 Courtney, mother of Alex, entered his magnetic resonance imaging (MRI) notes and symptom observations line by line into ChatGPT. Alex's chronic pain began at age 4 during the COVID-19 lockdown. He went on to grind his teeth, stop growing taller and drag his left foot. 17 physicians over three years had found no diagnosis. ChatGPT suggested tethered cord syndrome. She booked a new neurosurgeon, Dr Holly Gilmer of the Michigan Head & Spine Institute. Gilmer reviewed the MRI, found spina bifida occulta with a tethered cord and operated to release it. That was a few weeks before the TODAY.com report (11 September 2023, updated 12 September 2023). Alex was still recovering. The month of the ChatGPT query and the surgery date are not given.", "replication": { "produced_by": [ "A caregiver entering detailed clinical records (MRI report text, symptom observations) in a general-purpose language model", "A clinician willing to re-review existing imaging against the proposed diagnosis" ], "must_hold": [ "The model's hypothesis is verified by a qualified clinician against imaging or testing before treatment", "The caregiver has access to the patient's own records to supply to the model" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0318", "title": "TrailGuard AI camera in Kishanpur Wildlife Sanctuary transmits images of armed poachers on two nights; Dudhwa Tiger Reserve officials identify them and investigate", "summary": "Dertien et al. (BioScience 2023): one TrailGuard AI unit captured poachers “carrying a gun and knives” on two dates and a poached chital; officials identified them. Arrests claimed only in releases.", "date_observed": "2023-09-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Dertien, Negi, Dinerstein and colleagues (BioScience 73(10):748–757, published online 14 September 2023) report deploying the TrailGuard AI camera-alert system. The paper does not date the detections. The system “runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images”. It was deployed in the Kanha-Pench corridor and in Dudhwa Tiger Reserve, Uttar Pradesh. All seven Dudhwa units transmitted images; three transmitted objects of interest to forest department officials. “One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates, and a presumably poached chital (Axis axis) on the second detection”. “Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter”. Tigers were detected at the same spot three days before the second poacher detection. The authors include RESOLVE and CVEDIA staff (the system's developers) alongside Dudhwa Tiger Reserve, Wildlife Institute of India and Global Tiger Forum co-authors. AFP (Taipei Times, 6 October 2023) reported the study's claim of “identifying a team of poachers”. A Clemson University release of 15 September 2023 carries Nightjar/RESOLVE boilerplate. It states that the alerts “led the authorities to the arrest of these individuals for poaching a few weeks later”. It quotes Sanjay Kumar Pathak, former field director of Dudhwa, that the system “led to the detection and arrest of poachers in Dudhwa”. The Hindu (16 September 2023) cited a person involved in the experiment. Poachers caught on camera had a year later helped forest authorities secure a conviction. It quoted Piyush Yadav of Nightjar, the manufacturer, that “A year down, these poachers were arrested with images from TrailGuard playing a key role”. The article's lead puts the capture in Kanha-Pench and the Yadav quote in Dudhwa. No forest-department statement or court record of an arrest was found.", "category": "protective response", "unexpected": false, "purpose": "Built to detect tigers and people on trails with embedded AI and send real-time images to forest officials. Detecting and transmitting the poachers' images was that purpose.", "system": "TrailGuard AI camera-alert system (embedded AI on an Intel computer-vision chip; cellular transmission)", "model_version": null, "developer": "Nightjar / RESOLVE, Washington DC (inventor Steve Gulick), with CVEDIA Ltd", "deployer": "Dudhwa Tiger Reserve, Uttar Pradesh Forest Department, with the Global Tiger Forum, National Tiger Conservation Authority and Clemson University", "location": "Kishanpur Wildlife Sanctuary, Dudhwa Tiger Reserve, Uttar Pradesh, India", "domain": "Conservation / anti-poaching law enforcement", "segment": "Anti-poaching enforcement", "benefit_type": "Reduced Violence", "taxonomy_note": "The paper documents detection and identification of armed poachers for investigation, with arrests claimed only in releases, and the protected asset is wildlife.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Forest officials received the images in near real time and identified the individuals. The paper documents an investigation, not an arrest or prosecution, so the recorded gain is an investigative lead." }, { "group": "societal", "depth": null, "reason": "Protection of the reserve's wildlife from this gang is claimed through arrests only in the Clemson release, developer material and The Hindu's second-hand report. The paper notes a chital presumably poached before the second detection." } ], "ai_role": { "status": "assessed", "statement": "The camera's on-board classifier filtered motion triggers to people and tigers and transmitted the poachers' images to officials' phones within about a minute. Identification and investigation were done by officials. The peer-reviewed account is co-authored by the developers (RESOLVE, CVEDIA) with Dudhwa and Wildlife Institute of India staff and stops at “investigating”. The arrest claim rests on a Clemson release quoting the ex-field director, developer press releases and The Hindu quoting the manufacturer and an unnamed participant." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Dertien JS, Negi H, Dinerstein E, Krishnamurthy R, Negi HS, Gopal R, Gulick S, Pathak SK, Kapoor M, Yadav P, Benitez M, Ferreira M, Wijnveen AJ, Lee ATL, Wright B, Baldwin RF (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10):748-757, doi:10.1093/biosci/biad076 (PMC10580963; authors include RESOLVE and CVEDIA developer staff and Dudhwa Tiger Reserve staff).", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates" }, { "kind": "peer-reviewed study", "citation": "Dertien et al. (2023), same paper, results on the Dudhwa deployment.", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter" }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.", "title": "AI of the tiger: Tiny camera 'protects' predator - and people", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "date": "2023-10-06", "written_by": "independent", "quote": "The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers." }, { "kind": "press release", "citation": "Clemson News (2023). Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans. 15 September 2023 (university release of the lead author's institution; carries Nightjar/RESOLVE boilerplate; quotes former Dudhwa field director Sanjay Kumar Pathak).", "title": "Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans", "url": "https://news.clemson.edu/clemson-students-deployment-of-novel-camera-alert-system-trailguard-ai-featured-in-bioscience-promotes-coexistence-of-tigers-humans/", "date": "2023-09-15", "written_by": "deployer", "quote": "TrailGuard AI offers park protection that led to the detection and arrest of poachers in Dudhwa," }, { "kind": "news report", "citation": "The Hindu (2023). AI cameras to curb poaching in Madhya Pradesh. 16 Sep 2023.", "title": "AI cameras to curb poaching in Madhya Pradesh", "url": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "A year down, these poachers were arrested with images from TrailGuard playing a key role" }, { "kind": "news report", "citation": "The Hindu (2023). Same article, lead paragraph.", "title": "AI cameras to curb poaching in Madhya Pradesh (conviction claim)", "url": "https://web.archive.org/web/20240808102127/https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "caught poachers on camera that — a year down — helped forest authorities secure a conviction, according to a person involved in the experiment" } ], "replication": { "produced_by": [ "Camouflaged camera units on trails inside the reserve used by both tigers and poachers", "Cellular coverage allowing images to reach forest officials' phones in under a minute" ], "must_hold": [ "Officials act on the images while the poachers can still be found. The paper records identification and investigation only", "The embedded classifier suppresses non-target triggers so that officials keep trusting the alerts" ], "echoes": [ { "date": null, "setting": "Similipal Tiger Reserve, Odisha (recorded separately as AIBD-0102); The Better India (30 June 2025) reports “96 poacher arrests and 86 firearms seized within ten months” from TrailGuard AI deployments there", "model_version": null, "outcome": "recurred", "source": "https://thebetterindia.com/457142/ai-applications-that-tackle-poaching-india/" } ] }, "paired_incident": null, "headline": "TrailGuard AI transmits images of armed poachers in Kishanpur", "metric": null, "comparator": { "against": "camera traps without real-time notification", "before": "camera traps have lacked the real-time notification capabilities and practicality necessary for prevention of poaching", "after": "notifications of tiger presence via email or push notification between 30 and 42 seconds after detections", "basis": "assumed", "quote": "Until recently, camera traps have lacked the real-time notification capabilities and practicality necessary for prevention of poaching and human–wildlife conflict.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/" }, "later": { "status": "persisted", "date": "2023-09-16", "note": "Two days after the paper, The Hindu quoted Nightjar's Piyush Yadav that the Dudhwa poachers were arrested about a year after the images, with TrailGuard images playing a key role; Clemson's release of 15 September 2023 says the arrests came a few weeks later, and no forest department or court record was found.", "quote": "But in the Dudhwa [tiger reserve] we learnt that not only could we track [in this case] tigers approaching a village but we also caught a gang of poachers on camera who were walking with a hunted chital. A year down, these poachers were arrested with images from TrailGuard playing a key role,", "url": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece" }, "value": null, "developer_country": "United States", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged the Dudhwa poacher material from a second write-up: added The Hindu's report of the arrest and conviction claims; the BioScience paper is marked as written by the system's developers.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/; https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.3blmedia.com/news/trailguard-ai-named-times-list-best-inventions-2023; https://en.wikipedia.org/wiki/Dudhwa_Tiger_Reserve", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' peer-reviewed study and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0318", "catalog_version": "1.0.0", "source_fingerprint": "3da3ea7fd080d05b95a11dd87baa78b9d68631cb63ea47cec85c691e5b783a51", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0318-source-0001", "AIBD-0318-source-0002", "AIBD-0318-source-0003", "AIBD-0318-source-0004", "AIBD-0318-source-0005", "AIBD-0318-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Nightjar / RESOLVE, Washington DC (inventor Steve Gulick), with CVEDIA Ltd", "deployer": "Dudhwa Tiger Reserve, Uttar Pradesh Forest Department, with the Global Tiger Forum, National Tiger Conservation Authority and Clemson University" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The camera's on-board classifier filtered motion triggers to people and tigers and transmitted the poachers' images to officials' phones within about a minute. Identification and investigation were done by officials. The peer-reviewed account is co-authored by the developers (RESOLVE, CVEDIA) with Dudhwa and Wildlife Institute of India staff and stops at “investigating”. The arrest claim rests on a Clemson release quoting the ex-field director, developer press releases and The Hindu quoting the manufacturer and an unnamed participant." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The camera's on-board classifier filtered motion triggers to people and tigers and transmitted the poachers' images to officials' phones within about a minute. Identification and investigation were done by officials. The peer-reviewed account is co-authored by the developers (RESOLVE, CVEDIA) with Dudhwa and Wildlife Institute of India staff and stops at “investigating”. The arrest claim rests on a Clemson release quoting the ex-field director, developer press releases and The Hindu quoting the manufacturer and an unnamed participant." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Forest officials received the images in near real time and identified the individuals. The paper documents an investigation, not an arrest or prosecution, so the recorded gain is an investigative lead." }, { "group": "societal", "reason": "Protection of the reserve's wildlife from this gang is claimed through arrests only in the Clemson release, developer material and The Hindu's second-hand report. The paper notes a chital presumably poached before the second detection." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports, the makers' peer-reviewed study and the deployer's press release. 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Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10):748-757, doi:10.1093/biosci/biad076 (PMC10580963; authors include RESOLVE and CVEDIA developer staff and Dudhwa Tiger Reserve staff).", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates" }, { "kind": "peer-reviewed study", "citation": "Dertien et al. (2023), same paper, results on the Dudhwa deployment.", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter" }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. 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Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans. 15 September 2023 (university release of the lead author's institution; carries Nightjar/RESOLVE boilerplate; quotes former Dudhwa field director Sanjay Kumar Pathak).", "title": "Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans", "url": "https://news.clemson.edu/clemson-students-deployment-of-novel-camera-alert-system-trailguard-ai-featured-in-bioscience-promotes-coexistence-of-tigers-humans/", "date": "2023-09-15", "written_by": "deployer", "quote": "TrailGuard AI offers park protection that led to the detection and arrest of poachers in Dudhwa," }, { "kind": "news report", "citation": "The Hindu (2023). AI cameras to curb poaching in Madhya Pradesh. 16 Sep 2023.", "title": "AI cameras to curb poaching in Madhya Pradesh", "url": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "A year down, these poachers were arrested with images from TrailGuard playing a key role" }, { "kind": "news report", "citation": "The Hindu (2023). Same article, lead paragraph.", "title": "AI cameras to curb poaching in Madhya Pradesh (conviction claim)", "url": "https://web.archive.org/web/20240808102127/https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "caught poachers on camera that — a year down — helped forest authorities secure a conviction, according to a person involved in the experiment" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0318-source-0001", "AIBD-0318-source-0002", "AIBD-0318-source-0003", "AIBD-0318-source-0004", "AIBD-0318-source-0005", "AIBD-0318-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Dertien JS, Negi H, Dinerstein E, Krishnamurthy R, Negi HS, Gopal R, Gulick S, Pathak SK, Kapoor M, Yadav P, Benitez M, Ferreira M, Wijnveen AJ, Lee ATL, Wright B, Baldwin RF (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10):748-757, doi:10.1093/biosci/biad076 (PMC10580963; authors include RESOLVE and CVEDIA developer staff and Dudhwa Tiger Reserve staff).", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates" }, { "kind": "peer-reviewed study", "citation": "Dertien et al. (2023), same paper, results on the Dudhwa deployment.", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10580963/", "date": "2023-09-14", "written_by": "makers", "quote": "Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter" }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.", "title": "AI of the tiger: Tiny camera 'protects' predator - and people", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "date": "2023-10-06", "written_by": "independent", "quote": "The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers." }, { "kind": "press release", "citation": "Clemson News (2023). Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans. 15 September 2023 (university release of the lead author's institution; carries Nightjar/RESOLVE boilerplate; quotes former Dudhwa field director Sanjay Kumar Pathak).", "title": "Clemson students' deployment of novel camera alert system, TrailGuard AI, featured in BioScience, promotes coexistence of tigers, humans", "url": "https://news.clemson.edu/clemson-students-deployment-of-novel-camera-alert-system-trailguard-ai-featured-in-bioscience-promotes-coexistence-of-tigers-humans/", "date": "2023-09-15", "written_by": "deployer", "quote": "TrailGuard AI offers park protection that led to the detection and arrest of poachers in Dudhwa," }, { "kind": "news report", "citation": "The Hindu (2023). AI cameras to curb poaching in Madhya Pradesh. 16 Sep 2023.", "title": "AI cameras to curb poaching in Madhya Pradesh", "url": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "A year down, these poachers were arrested with images from TrailGuard playing a key role" }, { "kind": "news report", "citation": "The Hindu (2023). Same article, lead paragraph.", "title": "AI cameras to curb poaching in Madhya Pradesh (conviction claim)", "url": "https://web.archive.org/web/20240808102127/https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece", "date": "2023-09-16", "written_by": "independent", "quote": "caught poachers on camera that — a year down — helped forest authorities secure a conviction, according to a person involved in the experiment" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Dertien et al. (BioScience 2023): one TrailGuard AI unit captured poachers “carrying a gun and knives” on two dates and a poached chital; officials identified them. Arrests claimed only in releases.", "account": "Dertien, Negi, Dinerstein and colleagues (BioScience 73(10):748–757, published online 14 September 2023) report deploying the TrailGuard AI camera-alert system. The paper does not date the detections. The system “runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images”. It was deployed in the Kanha-Pench corridor and in Dudhwa Tiger Reserve, Uttar Pradesh. All seven Dudhwa units transmitted images; three transmitted objects of interest to forest department officials. “One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates, and a presumably poached chital (Axis axis) on the second detection”. “Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter”. Tigers were detected at the same spot three days before the second poacher detection. The authors include RESOLVE and CVEDIA staff (the system's developers) alongside Dudhwa Tiger Reserve, Wildlife Institute of India and Global Tiger Forum co-authors. AFP (Taipei Times, 6 October 2023) reported the study's claim of “identifying a team of poachers”. A Clemson University release of 15 September 2023 carries Nightjar/RESOLVE boilerplate. It states that the alerts “led the authorities to the arrest of these individuals for poaching a few weeks later”. It quotes Sanjay Kumar Pathak, former field director of Dudhwa, that the system “led to the detection and arrest of poachers in Dudhwa”. The Hindu (16 September 2023) cited a person involved in the experiment. Poachers caught on camera had a year later helped forest authorities secure a conviction. It quoted Piyush Yadav of Nightjar, the manufacturer, that “A year down, these poachers were arrested with images from TrailGuard playing a key role”. The article's lead puts the capture in Kanha-Pench and the Yadav quote in Dudhwa. No forest-department statement or court record of an arrest was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "TrailGuard AI camera-alert system (embedded AI on an Intel computer-vision chip; cellular transmission)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Nightjar / RESOLVE, Washington DC (inventor Steve Gulick), with CVEDIA Ltd" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TrailGuard AI camera in Kishanpur Wildlife Sanctuary transmits images of armed poachers on two nights; Dudhwa Tiger Reserve officials identify them and investigate", "headline": "TrailGuard AI transmits images of armed poachers in Kishanpur" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3da3ea7fd080d05b95a11dd87baa78b9d68631cb63ea47cec85c691e5b783a51" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Dertien, Negi, Dinerstein and colleagues (BioScience 73(10):748–757, published online 14 September 2023) report deploying the TrailGuard AI camera-alert system. The paper does not date the detections. The system “runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images”. It was deployed in the Kanha-Pench corridor and in Dudhwa Tiger Reserve, Uttar Pradesh. All seven Dudhwa units transmitted images; three transmitted objects of interest to forest department officials. “One unit within Kishanpur Wildlife Sanctuary captured a group of poachers carrying a gun and knives on two separate dates, and a presumably poached chital (Axis axis) on the second detection”. “Authorities were able to quickly identify the individuals via the transmitted images and were investigating the matter”. Tigers were detected at the same spot three days before the second poacher detection. The authors include RESOLVE and CVEDIA staff (the system's developers) alongside Dudhwa Tiger Reserve, Wildlife Institute of India and Global Tiger Forum co-authors. AFP (Taipei Times, 6 October 2023) reported the study's claim of “identifying a team of poachers”. A Clemson University release of 15 September 2023 carries Nightjar/RESOLVE boilerplate. It states that the alerts “led the authorities to the arrest of these individuals for poaching a few weeks later”. It quotes Sanjay Kumar Pathak, former field director of Dudhwa, that the system “led to the detection and arrest of poachers in Dudhwa”. The Hindu (16 September 2023) cited a person involved in the experiment. Poachers caught on camera had a year later helped forest authorities secure a conviction. It quoted Piyush Yadav of Nightjar, the manufacturer, that “A year down, these poachers were arrested with images from TrailGuard playing a key role”. The article's lead puts the capture in Kanha-Pench and the Yadav quote in Dudhwa. No forest-department statement or court record of an arrest was found.", "replication": { "produced_by": [ "Camouflaged camera units on trails inside the reserve used by both tigers and poachers", "Cellular coverage allowing images to reach forest officials' phones in under a minute" ], "must_hold": [ "Officials act on the images while the poachers can still be found. The paper records identification and investigation only", "The embedded classifier suppresses non-target triggers so that officials keep trusting the alerts" ], "echoes": [ { "setting": "Similipal Tiger Reserve, Odisha (recorded separately as AIBD-0102); The Better India (30 June 2025) reports “96 poacher arrests and 86 firearms seized within ten months” from TrailGuard AI deployments there", "outcome": "recurred", "source": "https://thebetterindia.com/457142/ai-applications-that-tackle-poaching-india/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0358", "title": "TrailGuard AI cameras in the Kanha-Pench corridor transmit tiger alerts to researchers and forest officials 30 to 42 seconds after detection in a 2022 pilot", "summary": "BioScience 2023: 12 TrailGuard AI cameras ran in the Kanha-Pench corridor, Madhya Pradesh, mid-May to mid-July 2022 (591 trap nights); tiger notifications arrived 30 to 42 seconds after detection.", "date_observed": "2023-09-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Dertien et al. reported in BioScience (published 14 September 2023) that 12 TrailGuard AI camera-alert systems ran in the Kanha-Pench corridor, Madhya Pradesh. They ran from mid-May to mid-July 2022 (591 trap nights). The cameras run embedded AI on an Intel Myriad chip to detect tigers and humans and transmit only images of interest. Researchers and forest department officials received tiger notifications 30 to 42 seconds after detection. AFP (Taipei Times, 6 October 2023) reported the study's claim. The cameras were “immediately effective, picking up a tiger just 300 meters from a village”. The Hindu (16 September 2023) reported the Madhya Pradesh deployment. It quoted H.S. Negi of the Global Tiger Forum on plans to incorporate the system in other tiger reserves. The paper's second site, Dudhwa Tiger Reserve in Uttar Pradesh, where a unit captured armed poachers, is recorded separately. No forest department document on the pilot is among the sources.", "category": "protective response", "unexpected": false, "purpose": "Real-time detection of tigers and humans for human-wildlife conflict early warning and anti-poaching. The reported detections and follow-up were the intended use.", "system": "TrailGuard AI camera-alert system with embedded AI (Intel Myriad processor; detectors trained with CVEDIA synthetic renderings)", "model_version": "2022 pilot units", "developer": "RESOLVE (design) with CVEDIA Ltd (AI training); units manufactured by Nightjar", "deployer": "Madhya Pradesh and Uttar Pradesh forest departments with Clemson University, Wildlife Institute of India and Global Tiger Forum", "location": "Kanha-Pench corridor, Madhya Pradesh, India", "domain": "Wildlife protection and human-wildlife conflict", "segment": "State forest departments and conservation research partners", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No identified individual beneficiary. Villagers near three units are mentioned only as sources of daily notifications." }, { "group": "organizational", "depth": 1, "reason": "Researchers and forest department officials received tiger alerts 30 to 42 seconds after detection during the two-month pilot. No action taken on an alert is documented." }, { "group": "societal", "depth": null, "reason": "No measured effect on human-wildlife conflict in the two-month pilot of 12 cameras." } ], "ai_role": { "status": "assessed", "statement": "Embedded AI on the camera selected and transmitted images of tigers and humans within 30 to 42 seconds. That is the mechanism in the developer-affiliated BioScience paper. Whether any alert changed what villagers or officials did is not documented." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Dertien, J. S., Negi, H., Dinerstein, E., Krishnamurthy, R., Negi, H. S., Gopal, R., Gulick, S., Pathak, S. K., Kapoor, M., Yadav, P., Benitez, M., Ferreira, M., Wijnveen, A. J., Lee, A. T. L., Wright, B., Baldwin, R. F. (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10), 748-756. doi:10.1093/biosci/biad076", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://doi.org/10.1093/biosci/biad076", "date": "2023-09-14", "written_by": "makers", "quote": "We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers." }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.", "title": "AI of the tiger: Tiny camera 'protects' predator - and people", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "date": "2023-10-06", "written_by": "independent", "quote": "The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers." } ], "replication": { "produced_by": [ "Camera units with on-device detectors for tigers and humans placed on trails", "Cellular or satellite transmission to officials' phones and email", "Forest department staff willing to act on transmitted images", "Research consortium funding (Tigers United, Clemson, Khosla grant)" ], "must_hold": [ "Transmission path within cell range or via the slower protocol", "Detector accuracy high enough to avoid alert fatigue", "Investigative follow-up by forest and police authorities", "Battery life and concealment of units" ], "echoes": [ { "date": "2025-02-17", "setting": "Similipal Tiger Reserve, Odisha: TrailGuard AI cameras linked to multiple poacher arrests (recorded separately as AIBD-0102)", "model_version": null, "outcome": "recurred", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-fit-cameras-in-similipal-tiger-reserve-send-poaching-plummeting/article69225924.ece" }, { "date": null, "setting": "Plans to incorporate the system in other tiger reserves, per H.S. Negi of the Global Tiger Forum in The Hindu", "model_version": null, "outcome": "unknown", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece" } ] }, "paired_incident": null, "headline": "TrailGuard AI sends tiger alerts within 30 to 42 seconds", "metric": "tiger notifications arrived 30 to 42 seconds after detection", "comparator": { "against": "conventional camera traps tripped by passing boars or falling leaves", "before": null, "after": "almost wiped out false alarms", "basis": "assumed", "quote": "They say their system was the first AI camera to identify and transmit a picture of a tiger, and it has almost wiped out false alarms — when traps are tripped by passing boars or falling leaves.", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276" }, "later": { "status": "scaled", "date": "2023-10-06", "note": "AFP reported that RESOLVE's Eric Dinerstein was widening the TrailGuard rollout to larger animals such as elephants; the BioScience article also notes continued transmission from Kanha-Pench and other reserves.", "quote": "Those uncertainties aside, Dinerstein is widening the rollout of TrailGuard — this time with even bigger animals in his sights.", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276" }, "value": null, "developer_country": "United States", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Narrowed to the Kanha-Pench pilot; the Dudhwa poacher detection from the same paper is recorded separately as AIBD-0318.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276; https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.3blmedia.com/news/trailguard-ai-named-times-list-best-inventions-2023; https://en.wikipedia.org/wiki/Madhya_Pradesh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' peer-reviewed study. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0358", "catalog_version": "1.0.0", "source_fingerprint": "b8c957579f35e7fc9fae4447086ddc6204eb2f610b0e4b44bc2b988b71a6e26c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0358-source-0001", "AIBD-0358-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "RESOLVE (design) with CVEDIA Ltd (AI training); units manufactured by Nightjar", "deployer": "Madhya Pradesh and Uttar Pradesh forest departments with Clemson University, Wildlife Institute of India and Global Tiger Forum" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Embedded AI on the camera selected and transmitted images of tigers and humans within 30 to 42 seconds. That is the mechanism in the developer-affiliated BioScience paper. Whether any alert changed what villagers or officials did is not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Embedded AI on the camera selected and transmitted images of tigers and humans within 30 to 42 seconds. That is the mechanism in the developer-affiliated BioScience paper. Whether any alert changed what villagers or officials did is not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identified individual beneficiary. Villagers near three units are mentioned only as sources of daily notifications." }, { "group": "organizational", "depth": 1, "reason": "Researchers and forest department officials received tiger alerts 30 to 42 seconds after detection during the two-month pilot. No action taken on an alert is documented." }, { "group": "societal", "reason": "No measured effect on human-wildlife conflict in the two-month pilot of 12 cameras." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' peer-reviewed study. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identified individual beneficiary. Villagers near three units are mentioned only as sources of daily notifications." }, { "group": "organizational", "depth": 1, "reason": "Researchers and forest department officials received tiger alerts 30 to 42 seconds after detection during the two-month pilot. 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"quote": "Those uncertainties aside, Dinerstein is widening the rollout of TrailGuard — this time with even bigger animals in his sights.", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0358" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Dertien et al. reported in BioScience (published 14 September 2023) that 12 TrailGuard AI camera-alert systems ran in the Kanha-Pench corridor, Madhya Pradesh. They ran from mid-May to mid-July 2022 (591 trap nights). The cameras run embedded AI on an Intel Myriad chip to detect tigers and humans and transmit only images of interest. Researchers and forest department officials received tiger notifications 30 to 42 seconds after detection. AFP (Taipei Times, 6 October 2023) reported the study's claim. The cameras were “immediately effective, picking up a tiger just 300 meters from a village”. The Hindu (16 September 2023) reported the Madhya Pradesh deployment. It quoted H.S. Negi of the Global Tiger Forum on plans to incorporate the system in other tiger reserves. The paper's second site, Dudhwa Tiger Reserve in Uttar Pradesh, where a unit captured armed poachers, is recorded separately. No forest department document on the pilot is among the sources.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identified individual beneficiary. Villagers near three units are mentioned only as sources of daily notifications." }, { "group": "organizational", "depth": 1, "reason": "Researchers and forest department officials received tiger alerts 30 to 42 seconds after detection during the two-month pilot. No action taken on an alert is documented." }, { "group": "societal", "reason": "No measured effect on human-wildlife conflict in the two-month pilot of 12 cameras." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Real-time detection of tigers and humans for human-wildlife conflict early warning and anti-poaching. The reported detections and follow-up were the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Kanha-Pench corridor, Madhya Pradesh, India", "developer_country": "United States", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Real-time detection of tigers and humans for human-wildlife conflict early warning and anti-poaching. 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Negi of the Global Tiger Forum in The Hindu", "outcome": "unknown", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera units with on-device detectors for tigers and humans placed on trails", "Cellular or satellite transmission to officials' phones and email", "Forest department staff willing to act on transmitted images", "Research consortium funding (Tigers United, Clemson, Khosla grant)" ], "must_hold": [ "Transmission path within cell range or via the slower protocol", "Detector accuracy high enough to avoid alert fatigue", "Investigative follow-up by forest and police authorities", "Battery life and concealment of units" ], "echoes": [ { "date": "2025-02-17", "setting": "Similipal Tiger Reserve, Odisha: TrailGuard AI cameras linked to multiple poacher arrests (recorded separately as AIBD-0102)", "outcome": "recurred", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-fit-cameras-in-similipal-tiger-reserve-send-poaching-plummeting/article69225924.ece" }, { "setting": "Plans to incorporate the system in other tiger reserves, per H.S. Negi of the Global Tiger Forum in The Hindu", "outcome": "unknown", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Narrowed to the Kanha-Pench pilot; the Dudhwa poacher detection from the same paper is recorded separately as AIBD-0318.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276; https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.3blmedia.com/news/trailguard-ai-named-times-list-best-inventions-2023; https://en.wikipedia.org/wiki/Madhya_Pradesh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Wildlife protection and human-wildlife conflict", "segment": "State forest departments and conservation research partners" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Dertien, J. S., Negi, H., Dinerstein, E., Krishnamurthy, R., Negi, H. S., Gopal, R., Gulick, S., Pathak, S. K., Kapoor, M., Yadav, P., Benitez, M., Ferreira, M., Wijnveen, A. J., Lee, A. T. L., Wright, B., Baldwin, R. F. (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10), 748-756. doi:10.1093/biosci/biad076", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://doi.org/10.1093/biosci/biad076", "date": "2023-09-14", "written_by": "makers", "quote": "We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers." }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.", "title": "AI of the tiger: Tiny camera 'protects' predator - and people", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "date": "2023-10-06", "written_by": "independent", "quote": "The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0358-source-0001", "AIBD-0358-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Dertien, J. S., Negi, H., Dinerstein, E., Krishnamurthy, R., Negi, H. S., Gopal, R., Gulick, S., Pathak, S. K., Kapoor, M., Yadav, P., Benitez, M., Ferreira, M., Wijnveen, A. J., Lee, A. T. L., Wright, B., Baldwin, R. F. (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10), 748-756. doi:10.1093/biosci/biad076", "title": "Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system", "url": "https://doi.org/10.1093/biosci/biad076", "date": "2023-09-14", "written_by": "makers", "quote": "We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers." }, { "kind": "news report", "citation": "AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.", "title": "AI of the tiger: Tiny camera 'protects' predator - and people", "url": "https://www.taipeitimes.com/News/feat/archives/2023/10/06/2003807276", "date": "2023-10-06", "written_by": "independent", "quote": "The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "BioScience 2023: 12 TrailGuard AI cameras ran in the Kanha-Pench corridor, Madhya Pradesh, mid-May to mid-July 2022 (591 trap nights); tiger notifications arrived 30 to 42 seconds after detection.", "account": "Dertien et al. reported in BioScience (published 14 September 2023) that 12 TrailGuard AI camera-alert systems ran in the Kanha-Pench corridor, Madhya Pradesh. They ran from mid-May to mid-July 2022 (591 trap nights). The cameras run embedded AI on an Intel Myriad chip to detect tigers and humans and transmit only images of interest. Researchers and forest department officials received tiger notifications 30 to 42 seconds after detection. AFP (Taipei Times, 6 October 2023) reported the study's claim. The cameras were “immediately effective, picking up a tiger just 300 meters from a village”. The Hindu (16 September 2023) reported the Madhya Pradesh deployment. It quoted H.S. Negi of the Global Tiger Forum on plans to incorporate the system in other tiger reserves. The paper's second site, Dudhwa Tiger Reserve in Uttar Pradesh, where a unit captured armed poachers, is recorded separately. No forest department document on the pilot is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The camera’s models detected tigers and people and transmitted selected images." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used the 2022 pilot units." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "2022 pilot units" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "TrailGuard AI camera-alert system with embedded AI (Intel Myriad processor; detectors trained with CVEDIA synthetic renderings)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "RESOLVE (design) with CVEDIA Ltd (AI training); units manufactured by Nightjar" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TrailGuard AI cameras in the Kanha-Pench corridor transmit tiger alerts to researchers and forest officials 30 to 42 seconds after detection in a 2022 pilot", "headline": "TrailGuard AI sends tiger alerts within 30 to 42 seconds" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b8c957579f35e7fc9fae4447086ddc6204eb2f610b0e4b44bc2b988b71a6e26c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Dertien et al. reported in BioScience (published 14 September 2023) that 12 TrailGuard AI camera-alert systems ran in the Kanha-Pench corridor, Madhya Pradesh. They ran from mid-May to mid-July 2022 (591 trap nights). The cameras run embedded AI on an Intel Myriad chip to detect tigers and humans and transmit only images of interest. Researchers and forest department officials received tiger notifications 30 to 42 seconds after detection. AFP (Taipei Times, 6 October 2023) reported the study's claim. The cameras were “immediately effective, picking up a tiger just 300 meters from a village”. The Hindu (16 September 2023) reported the Madhya Pradesh deployment. It quoted H.S. Negi of the Global Tiger Forum on plans to incorporate the system in other tiger reserves. The paper's second site, Dudhwa Tiger Reserve in Uttar Pradesh, where a unit captured armed poachers, is recorded separately. No forest department document on the pilot is among the sources.", "replication": { "produced_by": [ "Camera units with on-device detectors for tigers and humans placed on trails", "Cellular or satellite transmission to officials' phones and email", "Forest department staff willing to act on transmitted images", "Research consortium funding (Tigers United, Clemson, Khosla grant)" ], "must_hold": [ "Transmission path within cell range or via the slower protocol", "Detector accuracy high enough to avoid alert fatigue", "Investigative follow-up by forest and police authorities", "Battery life and concealment of units" ], "echoes": [ { "date": "2025-02-17", "setting": "Similipal Tiger Reserve, Odisha: TrailGuard AI cameras linked to multiple poacher arrests (recorded separately as AIBD-0102)", "outcome": "recurred", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-fit-cameras-in-similipal-tiger-reserve-send-poaching-plummeting/article69225924.ece" }, { "setting": "Plans to incorporate the system in other tiger reserves, per H.S. Negi of the Global Tiger Forum in The Hindu", "outcome": "unknown", "source": "https://www.thehindu.com/sci-tech/energy-and-environment/ai-cameras-to-curb-poaching/article67315766.ece" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0341", "title": "A GraphCast live run on ECMWF charts may have forecast Hurricane Lee's Nova Scotia landfall about nine days ahead", "summary": "DeepMind says a live GraphCast run on ECMWF's site forecast Lee's Nova Scotia landfall about nine days ahead; NHC records landfall 16 September 2023; no forecaster use of the run is documented.", "date_observed": "2023-09-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Google DeepMind's blog post of 14 November 2023 describes a live version of its publicly available GraphCast model, deployed on the ECMWF website. In September 2023 it predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia. MIT Technology Review (14 November 2023) relayed the claim from DeepMind staff research scientist Rémi Lam. It added that traditional forecasting models pinpointed Nova Scotia only six days in advance. The article quotes no ECMWF staff on Lee. ECMWF's Newsletter 177 editorial (Autumn 2023) confirms that GraphCast, Pangu-Weather and FourCastNet were made available on ECMWF's public charts pages from ECMWF's own initial conditions. The NHC tropical cyclone report on Lee (21 March 2024) records the landfall. Lee, by then post-tropical, made landfall on Long Island in southwestern Nova Scotia around 2000 UTC on 16 September 2023. Maximum sustained winds were about 55 kt. NHC official track errors were exceptionally low through 72 h and below five-year means through 120 h. The report mentions no AI model. No ECMWF document recording the Lee forecast is on record, and the NHC 2023 verification report contains no AI-model entry. It found only an intensity-structure mention of Lee in the independent CIRA preprint. The forecast itself is dated only as “September” by the vendor. No cited source documents a forecaster or authority acting on the GraphCast Lee run.", "category": "general benefit", "unexpected": false, "purpose": "Machine-learning global medium-range weather forecasting (10 days, 0.25 degree), including severe-event prediction such as tropical cyclone tracks. This forecast was that purpose.", "system": "GraphCast (Google DeepMind graph neural network weather model), experimental live run on ECMWF public charts", "model_version": "GraphCast (live version deployed on the ECMWF website)", "developer": "DeepMind", "deployer": "ECMWF (experimental data-driven forecasts on its public charts pages)", "location": "Long Island, southwestern Nova Scotia, Canada (landfall)", "domain": "Weather forecasting / tropical cyclones", "segment": "Public-sector meteorological service; AI research laboratory", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The nine-day claim is vendor-sourced and no forecaster use of the run is documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome is documented." }, { "group": "organizational", "depth": null, "reason": "General benefit. No cited source documents a forecast office using the GraphCast Lee run in its products." }, { "group": "societal", "depth": null, "reason": "General benefit. No public-safety decision is linked to the run in any cited source." } ], "ai_role": { "status": "assessed", "statement": "The only sources for the nine-day Lee forecast are the maker's own blog and a news report quoting the maker's scientist. ECMWF's editorial confirms only that GraphCast ran experimentally on its charts. NHC's Lee report records exceptionally low official track errors without mentioning AI guidance. The AI output is therefore documented as a forecast, not as an input to any decision." }, "evidence": [ { "kind": "press release", "citation": "Google DeepMind (2023). GraphCast: AI model for faster and more accurate global weather forecasting. DeepMind blog, 14 Nov 2023.", "title": "GraphCast: AI model for faster and more accurate global weather forecasting", "url": "https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "date": "2023-11-14", "written_by": "makers", "quote": "a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia" }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Google DeepMind's weather AI can forecast extreme weather faster and more accurately. MIT Technology Review, 14 Nov 2023.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "In September, GraphCast accurately predicted that Hurricane Lee would make landfall in Nova Scotia nine days in advance, says Rémi Lam, a staff research scientist at Google DeepMind." }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Same article, comparison with conventional models.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately (conventional-model comparison)", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "Traditional weather forecasting models pinpointed the hurricane to Nova Scotia only six days in advance." }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). National Hurricane Center Tropical Cyclone Report: Hurricane Lee (AL132023), 5-16 September 2023. NOAA/NWS, 21 Mar 2024.", "title": "Tropical Cyclone Report: Hurricane Lee (AL132023)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "making landfall on Long Island, in southwestern Nova Scotia, later that day around 2000 UTC with maximum sustained winds of about 55 kt well east of the center" }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). Same report, forecast verification section (no AI model is mentioned anywhere in the report).", "title": "Tropical Cyclone Report: Hurricane Lee (track verification)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "Official track forecast errors were exceptionally low through 72 h, and below the previous 5-year period means through 120 h." }, { "kind": "press release", "citation": "Rabier, F. (2023). The AIFS is launched (editorial). ECMWF Newsletter No. 177, Autumn 2023.", "title": "The AIFS is launched", "url": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched", "date": null, "written_by": "deployer", "quote": "We have made these systems available on ECMWF's public charts pages, based on our own initial conditions." }, { "kind": "preprint", "citation": "Lam, R., Sanchez-Gonzalez, A., Willson, M., et al. (2022/2023). GraphCast: Learning skillful medium-range global weather forecasting. arXiv:2212.12794 (published in Science, Nov 2023).", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "url": "https://arxiv.org/abs/2212.12794", "date": "2022-12-24", "written_by": "makers", "quote": "its forecasts support better severe event prediction, including tropical cyclones, atmospheric rivers, and extreme temperatures" }, { "kind": "peer-reviewed study", "citation": "Olivetti L, Messori G (2024). Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast. Geoscientific Model Development 17:7915-7962, doi:10.5194/gmd-17-7915-2024.", "title": "Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast", "url": "https://gmd.copernicus.org/articles/17/7915/2024/", "date": "2024-11-07", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "GraphCast trained on decades of ERA5 reanalysis and run live from ECMWF initial conditions on ECMWF's experimental charts", "A long-lived Cabo Verde hurricane whose track was, per NHC, easier than normal to forecast (low climatology-persistence errors)", "Vendor retrospective comparison of its own run against conventional models" ], "must_hold": [ "Independent verification of the specific nine-day run against the official track record (not found in any ECMWF or NHC document among the sources)", "Access to ECMWF initial conditions for the live run", "A forecaster or authority actually consulting the AI run for it to become an attributable benefit" ], "echoes": [ { "date": null, "setting": "2023 season verification by CIRA of GraphCast and peer AI models against operational cyclone track guidance (existing record AIBD-0090)", "model_version": null, "outcome": "recurred", "source": "AIBD-0090 (DeMaria et al. 2024 preprint cited there)" } ] }, "paired_incident": null, "headline": "GraphCast may have forecast Lee's landfall nine days ahead", "metric": "forecast Lee's Nova Scotia landfall about nine days ahead", "comparator": { "against": "traditional physics-based forecasts of Hurricane Lee's landfall (DeepMind's own account)", "before": "only locked in on Nova Scotia about six days in advance", "after": "about nine days in advance", "basis": "assumed", "quote": "In September, a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia. By contrast, traditional forecasts had greater variability in where and when landfall would occur, and only locked in on Nova Scotia about six days in advance.", "url": "https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/" }, "later": { "status": "persisted", "date": "2024-11-07", "note": "An independent Uppsala University evaluation published 7 November 2024 confirmed GraphCast's general advantage over ECMWF's IFS HRES, including on near-surface temperature and wind extremes; it does not examine the Hurricane Lee forecast, and the NHC's March 2024 report on Lee names no AI model.", "quote": "Both data-driven models perform significantly better than ECMWF's IFS HRES globally and in most regions. Most impressively, GraphCast significantly outperforms IFS HRES across all regions and lead times.", "url": "https://gmd.copernicus.org/articles/17/7915/2024/" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/; https://gmd.copernicus.org/articles/17/7915/2024/; https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://en.wikipedia.org/wiki/European_Centre_for_Medium-Range_Weather_Forecasts", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study, one independent report, one independent news report, the makers' preprint, the makers' press release and the deployer's press release. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0341", "catalog_version": "1.0.0", "source_fingerprint": "9911fcda891b59bf2c4d643ddd69e62d178eee161f30fd0f122f939e02fca957", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0341-source-0001", "AIBD-0341-source-0002", "AIBD-0341-source-0003", "AIBD-0341-source-0004", "AIBD-0341-source-0005", "AIBD-0341-source-0006", "AIBD-0341-source-0007", "AIBD-0341-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepMind", "deployer": "ECMWF (experimental data-driven forecasts on its public charts pages)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The only sources for the nine-day Lee forecast are the maker's own blog and a news report quoting the maker's scientist. ECMWF's editorial confirms only that GraphCast ran experimentally on its charts. NHC's Lee report records exceptionally low official track errors without mentioning AI guidance. The AI output is therefore documented as a forecast, not as an input to any decision." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The only sources for the nine-day Lee forecast are the maker's own blog and a news report quoting the maker's scientist. ECMWF's editorial confirms only that GraphCast ran experimentally on its charts. NHC's Lee report records exceptionally low official track errors without mentioning AI guidance. The AI output is therefore documented as a forecast, not as an input to any decision." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study, one independent report, one independent news report, the makers' preprint, the makers' press release and the deployer's press release. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual outcome is documented." }, { "group": "organizational", "reason": "General benefit. No cited source documents a forecast office using the GraphCast Lee run in its products." }, { "group": "societal", "reason": "General benefit. 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GraphCast: AI model for faster and more accurate global weather forecasting. DeepMind blog, 14 Nov 2023.", "title": "GraphCast: AI model for faster and more accurate global weather forecasting", "url": "https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "date": "2023-11-14", "written_by": "makers", "quote": "a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia" }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Google DeepMind's weather AI can forecast extreme weather faster and more accurately. MIT Technology Review, 14 Nov 2023.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "In September, GraphCast accurately predicted that Hurricane Lee would make landfall in Nova Scotia nine days in advance, says Rémi Lam, a staff research scientist at Google DeepMind." }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Same article, comparison with conventional models.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately (conventional-model comparison)", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "Traditional weather forecasting models pinpointed the hurricane to Nova Scotia only six days in advance." }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). National Hurricane Center Tropical Cyclone Report: Hurricane Lee (AL132023), 5-16 September 2023. NOAA/NWS, 21 Mar 2024.", "title": "Tropical Cyclone Report: Hurricane Lee (AL132023)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "making landfall on Long Island, in southwestern Nova Scotia, later that day around 2000 UTC with maximum sustained winds of about 55 kt well east of the center" }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). Same report, forecast verification section (no AI model is mentioned anywhere in the report).", "title": "Tropical Cyclone Report: Hurricane Lee (track verification)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "Official track forecast errors were exceptionally low through 72 h, and below the previous 5-year period means through 120 h." }, { "kind": "press release", "citation": "Rabier, F. (2023). The AIFS is launched (editorial). ECMWF Newsletter No. 177, Autumn 2023.", "title": "The AIFS is launched", "url": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched", "written_by": "deployer", "quote": "We have made these systems available on ECMWF's public charts pages, based on our own initial conditions." }, { "kind": "preprint", "citation": "Lam, R., Sanchez-Gonzalez, A., Willson, M., et al. (2022/2023). GraphCast: Learning skillful medium-range global weather forecasting. arXiv:2212.12794 (published in Science, Nov 2023).", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "url": "https://arxiv.org/abs/2212.12794", "date": "2022-12-24", "written_by": "makers", "quote": "its forecasts support better severe event prediction, including tropical cyclones, atmospheric rivers, and extreme temperatures" }, { "kind": "peer-reviewed study", "citation": "Olivetti L, Messori G (2024). Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast. Geoscientific Model Development 17:7915-7962, doi:10.5194/gmd-17-7915-2024.", "title": "Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast", "url": "https://gmd.copernicus.org/articles/17/7915/2024/", "date": "2024-11-07", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0341-source-0001", "AIBD-0341-source-0002", "AIBD-0341-source-0003", "AIBD-0341-source-0004", "AIBD-0341-source-0005", "AIBD-0341-source-0006", "AIBD-0341-source-0007", "AIBD-0341-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Google DeepMind (2023). GraphCast: AI model for faster and more accurate global weather forecasting. DeepMind blog, 14 Nov 2023.", "title": "GraphCast: AI model for faster and more accurate global weather forecasting", "url": "https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "date": "2023-11-14", "written_by": "makers", "quote": "a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia" }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Google DeepMind's weather AI can forecast extreme weather faster and more accurately. MIT Technology Review, 14 Nov 2023.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "In September, GraphCast accurately predicted that Hurricane Lee would make landfall in Nova Scotia nine days in advance, says Rémi Lam, a staff research scientist at Google DeepMind." }, { "kind": "news report", "citation": "Heikkilä, M. (2023). Same article, comparison with conventional models.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately (conventional-model comparison)", "url": "https://web.archive.org/web/20231114164801/https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "Traditional weather forecasting models pinpointed the hurricane to Nova Scotia only six days in advance." }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). National Hurricane Center Tropical Cyclone Report: Hurricane Lee (AL132023), 5-16 September 2023. NOAA/NWS, 21 Mar 2024.", "title": "Tropical Cyclone Report: Hurricane Lee (AL132023)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "making landfall on Long Island, in southwestern Nova Scotia, later that day around 2000 UTC with maximum sustained winds of about 55 kt well east of the center" }, { "kind": "report", "citation": "Blake, E. and Nepaul, H. (2024). Same report, forecast verification section (no AI model is mentioned anywhere in the report).", "title": "Tropical Cyclone Report: Hurricane Lee (track verification)", "url": "https://www.nhc.noaa.gov/data/tcr/AL132023_Lee.pdf", "date": "2024-03-21", "written_by": "independent", "quote": "Official track forecast errors were exceptionally low through 72 h, and below the previous 5-year period means through 120 h." }, { "kind": "press release", "citation": "Rabier, F. (2023). The AIFS is launched (editorial). ECMWF Newsletter No. 177, Autumn 2023.", "title": "The AIFS is launched", "url": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched", "written_by": "deployer", "quote": "We have made these systems available on ECMWF's public charts pages, based on our own initial conditions." }, { "kind": "preprint", "citation": "Lam, R., Sanchez-Gonzalez, A., Willson, M., et al. (2022/2023). GraphCast: Learning skillful medium-range global weather forecasting. arXiv:2212.12794 (published in Science, Nov 2023).", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "url": "https://arxiv.org/abs/2212.12794", "date": "2022-12-24", "written_by": "makers", "quote": "its forecasts support better severe event prediction, including tropical cyclones, atmospheric rivers, and extreme temperatures" }, { "kind": "peer-reviewed study", "citation": "Olivetti L, Messori G (2024). Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast. Geoscientific Model Development 17:7915-7962, doi:10.5194/gmd-17-7915-2024.", "title": "Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast", "url": "https://gmd.copernicus.org/articles/17/7915/2024/", "date": "2024-11-07", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "DeepMind says a live GraphCast run on ECMWF's site forecast Lee's Nova Scotia landfall about nine days ahead; NHC records landfall 16 September 2023; no forecaster use of the run is documented.", "account": "Google DeepMind's blog post of 14 November 2023 describes a live version of its publicly available GraphCast model, deployed on the ECMWF website. In September 2023 it predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia. MIT Technology Review (14 November 2023) relayed the claim from DeepMind staff research scientist Rémi Lam. It added that traditional forecasting models pinpointed Nova Scotia only six days in advance. The article quotes no ECMWF staff on Lee. ECMWF's Newsletter 177 editorial (Autumn 2023) confirms that GraphCast, Pangu-Weather and FourCastNet were made available on ECMWF's public charts pages from ECMWF's own initial conditions. The NHC tropical cyclone report on Lee (21 March 2024) records the landfall. Lee, by then post-tropical, made landfall on Long Island in southwestern Nova Scotia around 2000 UTC on 16 September 2023. Maximum sustained winds were about 55 kt. NHC official track errors were exceptionally low through 72 h and below five-year means through 120 h. The report mentions no AI model. No ECMWF document recording the Lee forecast is on record, and the NHC 2023 verification report contains no AI-model entry. It found only an intensity-structure mention of Lee in the independent CIRA preprint. The forecast itself is dated only as “September” by the vendor. No cited source documents a forecaster or authority acting on the GraphCast Lee run." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "GraphCast generated weather forecasts, including the projected path of Hurricane Lee." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used the live GraphCast forecasts available through ECMWF." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GraphCast." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GraphCast (live version deployed on the ECMWF website)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "GraphCast (Google DeepMind graph neural network weather model), experimental live run on ECMWF public charts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A GraphCast live run on ECMWF charts may have forecast Hurricane Lee's Nova Scotia landfall about nine days ahead", "headline": "GraphCast may have forecast Lee's landfall nine days ahead" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9911fcda891b59bf2c4d643ddd69e62d178eee161f30fd0f122f939e02fca957" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Google DeepMind's blog post of 14 November 2023 describes a live version of its publicly available GraphCast model, deployed on the ECMWF website. In September 2023 it predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia. MIT Technology Review (14 November 2023) relayed the claim from DeepMind staff research scientist Rémi Lam. It added that traditional forecasting models pinpointed Nova Scotia only six days in advance. The article quotes no ECMWF staff on Lee. ECMWF's Newsletter 177 editorial (Autumn 2023) confirms that GraphCast, Pangu-Weather and FourCastNet were made available on ECMWF's public charts pages from ECMWF's own initial conditions. The NHC tropical cyclone report on Lee (21 March 2024) records the landfall. Lee, by then post-tropical, made landfall on Long Island in southwestern Nova Scotia around 2000 UTC on 16 September 2023. Maximum sustained winds were about 55 kt. NHC official track errors were exceptionally low through 72 h and below five-year means through 120 h. The report mentions no AI model. No ECMWF document recording the Lee forecast is on record, and the NHC 2023 verification report contains no AI-model entry. It found only an intensity-structure mention of Lee in the independent CIRA preprint. The forecast itself is dated only as “September” by the vendor. No cited source documents a forecaster or authority acting on the GraphCast Lee run.", "replication": { "produced_by": [ "GraphCast trained on decades of ERA5 reanalysis and run live from ECMWF initial conditions on ECMWF's experimental charts", "A long-lived Cabo Verde hurricane whose track was, per NHC, easier than normal to forecast (low climatology-persistence errors)", "Vendor retrospective comparison of its own run against conventional models" ], "must_hold": [ "Independent verification of the specific nine-day run against the official track record (not found in any ECMWF or NHC document among the sources)", "Access to ECMWF initial conditions for the live run", "A forecaster or authority actually consulting the AI run for it to become an attributable benefit" ], "echoes": [ { "setting": "2023 season verification by CIRA of GraphCast and peer AI models against operational cyclone track guidance (existing record AIBD-0090)", "outcome": "recurred", "source": "AIBD-0090 (DeMaria et al. 2024 preprint cited there)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0034", "title": "Blind and low-vision participants complete everyday tasks with Be My AI in peer-reviewed interview studies", "summary": "Peer-reviewed interview studies record blind users completing everyday tasks with Be My AI, e.g., airport gate numbers, a handwritten check.", "date_observed": "2023-09-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Xie and colleagues at Pennsylvania State University interviewed 14 visually impaired users of Be My AI. That is the large-multimodal-model image-description feature of the Be My Eyes app. They analyzed image descriptions gathered from 25 September 2023 to 31 March 2024. The paper appeared at CHI 2025. Individual uses are recorded. “P2 utilized it to identify gate numbers at the airport”. “P10 used it to recognize her surroundings when disoriented in her neighborhood”. P13 received a description locating “a hair tie in the upper right hand corner” of a carpet. A separate ASSETS 2025 interview study of 21 participants (November 2024 to January 2025) records P9 using Be My AI to read a handwritten check. Be My AI was publicly released on 25 September 2023. That starts the first paper's social-media collection window. The interview participants' uses are undated and outcomes self-reported.", "category": "benefit created", "unexpected": false, "purpose": "Be My AI was built to describe photographed scenes and objects to blind and low-vision users. These task completions were that purpose. Xie et al. state that Be My AI is built on OpenAI's GPT-4 models.", "system": "Be My AI (large-multimodal-model image description in the Be My Eyes app)", "model_version": "GPT-4 (per Xie et al. 2025)", "developer": "Be My Eyes (feature built on OpenAI's GPT-4)", "deployer": "Be My Eyes (consumer app used by study participants)", "location": null, "domain": "Accessibility / visual assistance", "segment": "Blind and low-vision users", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "Everyday tasks (gate numbers, orientation, locating a dropped item, reading a check) completed independently by identifiable participants. Small, self-reported, and the same papers document frequent errors." } ], "ai_role": { "status": "assessed", "statement": "The multimodal model generated the descriptions participants acted on. No independent per-task accuracy check was made. Participants themselves reported risk (P9: “I knew there was a risk”)." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Xie J, Yu R, Zhang H, Billah SM, Lee S, Carroll JM (2025). Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models. Proc. CHI 2025 (PMC12338113).", "title": "Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12338113/", "date": "2025-04-25", "written_by": "independent", "quote": "P10 used it to recognize her surroundings when disoriented in her neighborhood" }, { "kind": "preprint", "citation": "Sharma T, Tseng Y-Y, Zhang L, Ide A, Mack KA, Findlater L, Gurari D, Wang Y (2025). 'Before, I Asked My Mom, Now I Ask ChatGPT': Visual Privacy Management with Generative AI for Blind and Low-Vision People. arXiv:2507.00286 (published ASSETS 2025).", "title": "Visual Privacy Management with Generative AI for Blind and Low Vision People", "url": "https://arxiv.org/html/2507.00286v1", "date": "2025-06-30", "written_by": "independent", "quote": "I have used Be My Eyes AI to read a handwritten check in a pinch, but I knew there was a risk." }, { "kind": "other", "citation": "Penn State Pure research record (2025). Publication venue entry for Sharma et al.", "title": "Penn State Pure: 'Before, I Asked My Mom, Now I Ask ChatGPT'", "url": "https://pure.psu.edu/en/publications/before-i-asked-my-mom-now-i-ask-chatgpt-visual-privacy-management/", "date": "2025-10-22", "written_by": "independent", "quote": "ASSETS 2025 - Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility" } ], "replication": { "produced_by": [ "Smartphone photograph submitted to Be My AI by a blind or low-vision user", "Task in a familiar or low-stakes setting", "User interprets a text description and acts on it" ], "must_hold": [ "The model does not hallucinate in the specific scene (both studies document hallucinations)", "User cross-checks high-stakes outputs such as medication or finances" ], "echoes": [ { "date": "2024-11-01", "setting": "ASSETS 2025 interview study, 21 US participants, interviews November 2024 to January 2025 (first day of month used); P9 read a handwritten check", "model_version": null, "outcome": "recurred", "source": "https://arxiv.org/html/2507.00286v1" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "830", "title": "Error-Prone AI Accessibility Tools Reportedly Lead to Navigation Issues for Blind Internet Users", "url": "https://incidentdatabase.ai/cite/830", "severity": null, "group": "personal", "basis": "Same stakeholders and task: AI describing visual content for blind users; Be My AI read gate numbers and a check, while AI accessibility overlays mislabelled web content, misleading blind and visually impaired people such as Jakob Rosin." }, "headline": "Be My AI reads airport gate numbers and a check for blind users", "metric": null, "comparator": { "against": "asking a sighted family member or friend to check a photo", "before": "Before GenAI, I would often send it to my mom or friend to check for me.", "after": "Now I Ask ChatGPT", "basis": "assumed", "quote": "I don't want to give a weird impression when posting my picture. Before GenAI, I would often send it to my mom or friend to check for me.", "url": "https://arxiv.org/html/2507.00286v1" }, "later": { "status": "persisted", "date": "2025-06-30", "note": "An independent interview study run from November 2024 to January 2025 recorded blind participants still using Be My AI for everyday reading tasks such as a handwritten check.", "quote": "I've used Be My Eyes AI to read a handwritten check in a pinch, but I knew there was a risk—it could've exposed bank info", "url": "https://arxiv.org/html/2507.00286v1" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added the GPT-4 basis that Xie et al. state (the record had said no source names the model vendor), removed P1's pregnancy-test reading from the echo because the source reports inconsistent results rather than a completed task, explained that the observation date is Be My AI's release date and that the interview uses are undated, and matched the arXiv v1 title's unhyphenated “Low Vision”.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12338113/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://arxiv.org/html/2507.00286v1; https://arxiv.org/html/2507.00286v1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.bemyeyes.com/terms; https://www.bemyeyes.com/terms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study, one independent preprint and one other independent source. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0034", "catalog_version": "1.0.0", "source_fingerprint": "6ddf264b722b43d9ee85c0372ded73b64a0a3670d062ea0f2fd3fdda94996f59", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0034-source-0001", "AIBD-0034-source-0002", "AIBD-0034-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Be My Eyes (feature built on OpenAI's GPT-4)", "deployer": "Be My Eyes (consumer app used by study participants)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The multimodal model generated the descriptions participants acted on. No independent per-task accuracy check was made. Participants themselves reported risk (P9: “I knew there was a risk”)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The multimodal model generated the descriptions participants acted on. No independent per-task accuracy check was made. 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Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models. Proc. CHI 2025 (PMC12338113).", "title": "Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12338113/", "date": "2025-04-25", "written_by": "independent", "quote": "P10 used it to recognize her surroundings when disoriented in her neighborhood" }, { "kind": "preprint", "citation": "Sharma T, Tseng Y-Y, Zhang L, Ide A, Mack KA, Findlater L, Gurari D, Wang Y (2025). 'Before, I Asked My Mom, Now I Ask ChatGPT': Visual Privacy Management with Generative AI for Blind and Low-Vision People. arXiv:2507.00286 (published ASSETS 2025).", "title": "Visual Privacy Management with Generative AI for Blind and Low Vision People", "url": "https://arxiv.org/html/2507.00286v1", "date": "2025-06-30", "written_by": "independent", "quote": "I have used Be My Eyes AI to read a handwritten check in a pinch, but I knew there was a risk." }, { "kind": "other", "citation": "Penn State Pure research record (2025). Publication venue entry for Sharma et al.", "title": "Penn State Pure: 'Before, I Asked My Mom, Now I Ask ChatGPT'", "url": "https://pure.psu.edu/en/publications/before-i-asked-my-mom-now-i-ask-chatgpt-visual-privacy-management/", "date": "2025-10-22", "written_by": "independent", "quote": "ASSETS 2025 - Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Peer-reviewed interview studies record blind users completing everyday tasks with Be My AI, e.g., airport gate numbers, a handwritten check.", "account": "Xie and colleagues at Pennsylvania State University interviewed 14 visually impaired users of Be My AI. That is the large-multimodal-model image-description feature of the Be My Eyes app. They analyzed image descriptions gathered from 25 September 2023 to 31 March 2024. The paper appeared at CHI 2025. Individual uses are recorded. “P2 utilized it to identify gate numbers at the airport”. “P10 used it to recognize her surroundings when disoriented in her neighborhood”. P13 received a description locating “a hair tie in the upper right hand corner” of a carpet. A separate ASSETS 2025 interview study of 21 participants (November 2024 to January 2025) records P9 using Be My AI to read a handwritten check. Be My AI was publicly released on 25 September 2023. That starts the first paper's social-media collection window. The interview participants' uses are undated and outcomes self-reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model described images for people with impaired vision." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GPT-4." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-4 (per Xie et al. 2025)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Be My AI (large-multimodal-model image description in the Be My Eyes app)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Be My Eyes (feature built on OpenAI's GPT-4)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Blind and low-vision participants complete everyday tasks with Be My AI in peer-reviewed interview studies", "headline": "Be My AI reads airport gate numbers and a check for blind users" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6ddf264b722b43d9ee85c0372ded73b64a0a3670d062ea0f2fd3fdda94996f59" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Xie and colleagues at Pennsylvania State University interviewed 14 visually impaired users of Be My AI. That is the large-multimodal-model image-description feature of the Be My Eyes app. They analyzed image descriptions gathered from 25 September 2023 to 31 March 2024. The paper appeared at CHI 2025. Individual uses are recorded. “P2 utilized it to identify gate numbers at the airport”. “P10 used it to recognize her surroundings when disoriented in her neighborhood”. P13 received a description locating “a hair tie in the upper right hand corner” of a carpet. A separate ASSETS 2025 interview study of 21 participants (November 2024 to January 2025) records P9 using Be My AI to read a handwritten check. Be My AI was publicly released on 25 September 2023. That starts the first paper's social-media collection window. The interview participants' uses are undated and outcomes self-reported.", "replication": { "produced_by": [ "Smartphone photograph submitted to Be My AI by a blind or low-vision user", "Task in a familiar or low-stakes setting", "User interprets a text description and acts on it" ], "must_hold": [ "The model does not hallucinate in the specific scene (both studies document hallucinations)", "User cross-checks high-stakes outputs such as medication or finances" ], "echoes": [ { "date": "2024-11-01", "setting": "ASSETS 2025 interview study, 21 US participants, interviews November 2024 to January 2025 (first day of month used); P9 read a handwritten check", "outcome": "recurred", "source": "https://arxiv.org/html/2507.00286v1" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0287", "title": "Smartwatch ECG app confirms atrial fibrillation in a 43-year-old chief officer mid-Indian Ocean; Italy's CIRM telemedicine doctor has the ship diverted to port", "summary": "On 29 Sep 2023 a merchant ship with no ECG used a smartwatch ECG app under CIRM guidance; it confirmed AF within seconds, the ship diverted, hospital ECG confirmed AF and the seafarer was repatriated.", "date_observed": "2023-09-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Ruocco, Amenta, Angeloni, Frisicale, Vaia and Sagaro reported a case in International Maritime Health (2025;76(2):93–96). The early publication date is 5 March 2025 as printed on the journal page. They are at the University of Camerino's Telemedicine and Telepharmacy Center, the Centro Internazionale Radio Medico (CIRM) research department and Italy's Ministry of Health. A 43-year-old chief officer from the United Kingdom fell ill on a merchant ship in the middle of the Indian Ocean. He had chest pain, malaise and palpitations. CIRM, the Italian Telemedical Maritime Assistance Service, received the request on 29 September 2023. Blood pressure was 115/80 then 110/70 mmHg with tachycardia and an irregular heartbeat. The ship had no electrocardiograph and was too far from land for prompt rescue. The captain and the CIRM duty doctor used a smartwatch's electrocardiogram (ECG) application. Within seconds it confirmed the diagnostic hypothesis of atrial fibrillation (AF). The doctor reviewed the recording and recommended diversion to the nearest port. Metoprolol 100 mg and aspirin 300 mg daily were given on board. The hospital later confirmed AF. The seafarer, with no prior history, was repatriated safely without complications and diagnosed with new-onset AF. The report does not name the watch's brand or whose watch it was.", "category": "benefit created", "unexpected": false, "purpose": "Smartwatch ECG apps are built to record a single-lead ECG and classify it for atrial fibrillation. This use, relayed to a telemedicine doctor, was that purpose in an unusual setting.", "system": "Smartwatch ECG application with atrial fibrillation classification (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": "Centro Internazionale Radio Medico (CIRM), the Italian Telemedical Maritime Assistance Service, with the ship's captain", "location": "Indian Ocean (merchant ship), with the CIRM center in Rome, Italy", "domain": "Healthcare (maritime telemedicine; cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The seafarer received a diagnosis, rate control and aspirin at sea, diversion to port and hospital confirmation. He was repatriated without complications. Material: the authors say the service “has the potential to save lives”, but no life-threatening complication is documented." }, { "group": "organizational", "depth": 1, "reason": "CIRM's duty doctor could make a rhythm diagnosis and a diversion decision on an ECG trace rather than on symptoms alone. The report gives no measure beyond the single decision." } ], "ai_role": { "status": "assessed", "statement": "The ECG app's automatic reading confirmed the suspected AF “within seconds”. The CIRM doctor then reviewed the trace himself and identified irregularities consistent with AF. So the classification and the human reading agreed. The diversion, drugs and hospital confirmation were human decisions. The brand is unknown, so the algorithm cannot be identified." }, "evidence": [ { "kind": "case report", "citation": "Ruocco C, Amenta F, Angeloni U, Frisicale EM, Vaia F, Sagaro GG (2025). A smartwatch electrocardiogram for atrial fibrillation detection: a case report. International Maritime Health 76(2):93-96. doi:10.5603/imh.99319 (open access, CC BY-NC-ND).", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "Within seconds, the application confirmed the diagnostic hypothesis, allowing the doctor on duty to identify the specific issue affecting the crew member’s heart" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, diversion.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/download/99319/83501", "date": "2025-03-05", "written_by": "deployer", "quote": "Upon the doctor’s recommendation, the captain diverted the ship to the nearest port where the crew member could receive medical treatment" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, date of the request.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "CIRM received a request for medical assistance on September 29th, 2023, on World Heart Day." } ], "replication": { "produced_by": [ "A ship without an electrocardiograph but with a smartwatch carrying an ECG app on board", "A telemedical maritime assistance service (CIRM) reachable from the ship and willing to act on a smartwatch trace", "A captain able to run the app on the patient and to divert the vessel" ], "must_hold": [ "The app's AF classification and the remote doctor's reading of the trace agree, as they did here and as the hospital ECG later confirmed", "A port is within reach for diversion and the patient remains stable on the drugs available on board" ], "echoes": [] }, "paired_incident": null, "headline": "Smartwatch ECG app confirms AF at sea; CIRM diverts the ship", "metric": null, "comparator": { "against": "no electrocardiograph on board the ship", "before": null, "after": "Within seconds, the application confirmed the diagnostic hypothesis", "basis": "assumed", "quote": "Unfortunately, the ship did not have an electrocardiograph, which would have been instrumental in confirming the diagnosis and guiding the appropriate treatment.", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319" }, "later": null, "value": null, "developer_country": null, "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://it.wikipedia.org/wiki/Centro_Internazionale_Radio_Medico", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: two case reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0287", "catalog_version": "1.0.0", "source_fingerprint": "900ddc2cd62a200c9778a96eca323e5717fe3a31bbd175bcf0734ec3386bcfca", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0287-source-0001", "AIBD-0287-source-0002", "AIBD-0287-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)", "deployer": "Centro Internazionale Radio Medico (CIRM), the Italian Telemedical Maritime Assistance Service, with the ship's captain" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ECG app's automatic reading confirmed the suspected AF “within seconds”. The CIRM doctor then reviewed the trace himself and identified irregularities consistent with AF. So the classification and the human reading agreed. The diversion, drugs and hospital confirmation were human decisions. The brand is unknown, so the algorithm cannot be identified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The ECG app's automatic reading confirmed the suspected AF “within seconds”. The CIRM doctor then reviewed the trace himself and identified irregularities consistent with AF. So the classification and the human reading agreed. The diversion, drugs and hospital confirmation were human decisions. The brand is unknown, so the algorithm cannot be identified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The seafarer received a diagnosis, rate control and aspirin at sea, diversion to port and hospital confirmation. He was repatriated without complications. Material: the authors say the service “has the potential to save lives”, but no life-threatening complication is documented." }, { "group": "organizational", "depth": 1, "reason": "CIRM's duty doctor could make a rhythm diagnosis and a diversion decision on an ECG trace rather than on symptoms alone. The report gives no measure beyond the single decision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: two case reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The seafarer received a diagnosis, rate control and aspirin at sea, diversion to port and hospital confirmation. He was repatriated without complications. Material: the authors say the service “has the potential to save lives”, but no life-threatening complication is documented." }, { "group": "organizational", "depth": 1, "reason": "CIRM's duty doctor could make a rhythm diagnosis and a diversion decision on an ECG trace rather than on symptoms alone. The report gives no measure beyond the single decision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The seafarer received a diagnosis, rate control and aspirin at sea, diversion to port and hospital confirmation. He was repatriated without complications. Material: the authors say the service “has the potential to save lives”, but no life-threatening complication is documented." }, { "group": "organizational", "depth": 1, "reason": "CIRM's duty doctor could make a rhythm diagnosis and a diversion decision on an ECG trace rather than on symptoms alone. The report gives no measure beyond the single decision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": 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The early publication date is 5 March 2025 as printed on the journal page. They are at the University of Camerino's Telemedicine and Telepharmacy Center, the Centro Internazionale Radio Medico (CIRM) research department and Italy's Ministry of Health. A 43-year-old chief officer from the United Kingdom fell ill on a merchant ship in the middle of the Indian Ocean. He had chest pain, malaise and palpitations. CIRM, the Italian Telemedical Maritime Assistance Service, received the request on 29 September 2023. Blood pressure was 115/80 then 110/70 mmHg with tachycardia and an irregular heartbeat. The ship had no electrocardiograph and was too far from land for prompt rescue. The captain and the CIRM duty doctor used a smartwatch's electrocardiogram (ECG) application. Within seconds it confirmed the diagnostic hypothesis of atrial fibrillation (AF). The doctor reviewed the recording and recommended diversion to the nearest port. Metoprolol 100 mg and aspirin 300 mg daily were given on board. The hospital later confirmed AF. The seafarer, with no prior history, was repatriated safely without complications and diagnosed with new-onset AF. The report does not name the watch's brand or whose watch it was.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The seafarer received a diagnosis, rate control and aspirin at sea, diversion to port and hospital confirmation. He was repatriated without complications. Material: the authors say the service “has the potential to save lives”, but no life-threatening complication is documented." }, { "group": "organizational", "depth": 1, "reason": "CIRM's duty doctor could make a rhythm diagnosis and a diversion decision on an ECG trace rather than on symptoms alone. The report gives no measure beyond the single decision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Smartwatch ECG apps are built to record a single-lead ECG and classify it for atrial fibrillation. This use, relayed to a telemedicine doctor, was that purpose in an unusual setting." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Indian Ocean (merchant ship), with the CIRM center in Rome, Italy", "deployer_country": "Italy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Smartwatch ECG apps are built to record a single-lead ECG and classify it for atrial fibrillation. This use, relayed to a telemedicine doctor, was that purpose in an unusual setting." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-09-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://it.wikipedia.org/wiki/Centro_Internazionale_Radio_Medico", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A ship without an electrocardiograph but with a smartwatch carrying an ECG app on board", "A telemedical maritime assistance service (CIRM) reachable from the ship and willing to act on a smartwatch trace", "A captain able to run the app on the patient and to divert the vessel" ], "must_hold": [ "The app's AF classification and the remote doctor's reading of the trace agree, as they did here and as the hospital ECG later confirmed", "A port is within reach for diversion and the patient remains stable on the drugs available on board" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (maritime telemedicine; cardiology)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Ruocco C, Amenta F, Angeloni U, Frisicale EM, Vaia F, Sagaro GG (2025). A smartwatch electrocardiogram for atrial fibrillation detection: a case report. International Maritime Health 76(2):93-96. doi:10.5603/imh.99319 (open access, CC BY-NC-ND).", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "Within seconds, the application confirmed the diagnostic hypothesis, allowing the doctor on duty to identify the specific issue affecting the crew member’s heart" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, diversion.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/download/99319/83501", "date": "2025-03-05", "written_by": "deployer", "quote": "Upon the doctor’s recommendation, the captain diverted the ship to the nearest port where the crew member could receive medical treatment" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, date of the request.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "CIRM received a request for medical assistance on September 29th, 2023, on World Heart Day." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0287-source-0001", "AIBD-0287-source-0002", "AIBD-0287-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Ruocco C, Amenta F, Angeloni U, Frisicale EM, Vaia F, Sagaro GG (2025). A smartwatch electrocardiogram for atrial fibrillation detection: a case report. International Maritime Health 76(2):93-96. doi:10.5603/imh.99319 (open access, CC BY-NC-ND).", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "Within seconds, the application confirmed the diagnostic hypothesis, allowing the doctor on duty to identify the specific issue affecting the crew member’s heart" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, diversion.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/download/99319/83501", "date": "2025-03-05", "written_by": "deployer", "quote": "Upon the doctor’s recommendation, the captain diverted the ship to the nearest port where the crew member could receive medical treatment" }, { "kind": "case report", "citation": "Ruocco C et al. (2025), Int Marit Health 76(2):93-96, date of the request.", "title": "A smartwatch electrocardiogram for atrial fibrillation detection: a case report", "url": "https://journals.viamedica.pl/international_maritime_health/article/view/99319", "date": "2025-03-05", "written_by": "deployer", "quote": "CIRM received a request for medical assistance on September 29th, 2023, on World Heart Day." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "On 29 Sep 2023 a merchant ship with no ECG used a smartwatch ECG app under CIRM guidance; it confirmed AF within seconds, the ship diverted, hospital ECG confirmed AF and the seafarer was repatriated.", "account": "Ruocco, Amenta, Angeloni, Frisicale, Vaia and Sagaro reported a case in International Maritime Health (2025;76(2):93–96). The early publication date is 5 March 2025 as printed on the journal page. They are at the University of Camerino's Telemedicine and Telepharmacy Center, the Centro Internazionale Radio Medico (CIRM) research department and Italy's Ministry of Health. A 43-year-old chief officer from the United Kingdom fell ill on a merchant ship in the middle of the Indian Ocean. He had chest pain, malaise and palpitations. CIRM, the Italian Telemedical Maritime Assistance Service, received the request on 29 September 2023. Blood pressure was 115/80 then 110/70 mmHg with tachycardia and an irregular heartbeat. The ship had no electrocardiograph and was too far from land for prompt rescue. The captain and the CIRM duty doctor used a smartwatch's electrocardiogram (ECG) application. Within seconds it confirmed the diagnostic hypothesis of atrial fibrillation (AF). The doctor reviewed the recording and recommended diversion to the nearest port. Metoprolol 100 mg and aspirin 300 mg daily were given on board. The hospital later confirmed AF. The seafarer, with no prior history, was repatriated safely without complications and diagnosed with new-onset AF. The report does not name the watch's brand or whose watch it was." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartwatch ECG application with atrial fibrillation classification (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Smartwatch ECG app confirms atrial fibrillation in a 43-year-old chief officer mid-Indian Ocean; Italy's CIRM telemedicine doctor has the ship diverted to port", "headline": "Smartwatch ECG app confirms AF at sea; CIRM diverts the ship" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "900ddc2cd62a200c9778a96eca323e5717fe3a31bbd175bcf0734ec3386bcfca" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Ruocco, Amenta, Angeloni, Frisicale, Vaia and Sagaro reported a case in International Maritime Health (2025;76(2):93–96). The early publication date is 5 March 2025 as printed on the journal page. They are at the University of Camerino's Telemedicine and Telepharmacy Center, the Centro Internazionale Radio Medico (CIRM) research department and Italy's Ministry of Health. A 43-year-old chief officer from the United Kingdom fell ill on a merchant ship in the middle of the Indian Ocean. He had chest pain, malaise and palpitations. CIRM, the Italian Telemedical Maritime Assistance Service, received the request on 29 September 2023. Blood pressure was 115/80 then 110/70 mmHg with tachycardia and an irregular heartbeat. The ship had no electrocardiograph and was too far from land for prompt rescue. The captain and the CIRM duty doctor used a smartwatch's electrocardiogram (ECG) application. Within seconds it confirmed the diagnostic hypothesis of atrial fibrillation (AF). The doctor reviewed the recording and recommended diversion to the nearest port. Metoprolol 100 mg and aspirin 300 mg daily were given on board. The hospital later confirmed AF. The seafarer, with no prior history, was repatriated safely without complications and diagnosed with new-onset AF. The report does not name the watch's brand or whose watch it was.", "replication": { "produced_by": [ "A ship without an electrocardiograph but with a smartwatch carrying an ECG app on board", "A telemedical maritime assistance service (CIRM) reachable from the ship and willing to act on a smartwatch trace", "A captain able to run the app on the patient and to divert the vessel" ], "must_hold": [ "The app's AF classification and the remote doctor's reading of the trace agree, as they did here and as the hospital ECG later confirmed", "A port is within reach for diversion and the patient remains stable on the drugs available on board" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0121", "title": "Karin's bone-anchored, nerve-connected Mia Hand: after more than three years of daily use her phantom pain fell from 5 to 3 and her stump pain vanished (Science Robotics case report)", "summary": "Swedish amputee Karin uses a bone-anchored, nerve-linked Mia Hand daily; phantom pain fell 5 to 3, stump pain gone (Sci. Robotics 2023).", "date_observed": "2023-10-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Karin, a Swedish woman born in 1973, lost her right hand below the elbow in a farming accident. She received a neuromusculoskeletal prosthesis at Sahlgrenska University Hospital. It comprises titanium implants in the radius and ulna and severed nerves transferred to muscle grafts. Implanted electrodes feed an embedded controller and a Prensilia Mia Hand. The study ran from September 2018 to April 2021, and the EU DeTOP consortium announced the implantation on 5 February 2019. The case report (Science Robotics, 11 October 2023) states her phantom limb pain fell from 5 to 3 and stump pain vanished. Quality of life rose, and she had used the hand in daily life for more than three years and continues to.", "category": "benefit created", "unexpected": false, "purpose": "The prosthesis was built to give reliable control, feedback and attachment after amputation, with surgical reconstruction to add myoelectric sites and treat neuropathic pain. The reported function and pain outcomes were that purpose.", "system": "Transradial neuromusculoskeletal prosthesis: osseointegrated titanium implants with implanted muscle and nerve electrodes, an embedded controller, and the Prensilia Mia Hand", "model_version": "Mia Hand", "developer": "Center for Bionics and Pain Research (Chalmers University of Technology and Sahlgrenska University Hospital, Mölndal) with Integrum AB; hand by Scuola Superiore Sant'Anna and Prensilia SRL, under the EU DeTOP project", "deployer": "Sahlgrenska University Hospital, Sweden (surgery led by Rickard Brånemark and Paolo Sassu)", "location": "Mölndal, Sweden", "domain": "Healthcare (upper-limb prosthetics and phantom limb pain)", "segment": "Academic clinical research, single-patient implementation", "benefit_type": "Improved Physical Health", "taxonomy_note": "The daily use of the nerve-linked hand for over three years is also an accessibility gain.", "registry_ids": { "oecd_aim": "2023-10-09-84b0" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The paper reports phantom limb pain down from 5 to 3, stump pain from 6 to 0 and sleep interference gone. EQ-5D-5L is up from 0.23 to 0.63 and daily use tops three years. Karin says the research “has given me a better life” and that she needs much less medication. Life-changing for one identifiable person, from a single-patient study without a control group." } ], "ai_role": { "status": "assessed", "statement": "The benefit comes from the whole neuromusculoskeletal interface, not from a learned model alone. The paper reports that in daily life the hand ran on direct control. Signals from two implanted electrodes mapped to open and close, and a sustained open signal switched grasps. Decoding of six movements (100 percent completion) and of five individual fingers (up to 95 percent) was shown in laboratory Motion Tests. The paper never uses the words AI or machine learning. The AI framing comes from the institutions' release (Brånemark: osseointegration, reconstructive surgery, implanted electrodes “and AI”). It also comes from CNN (“AI algorithms inside the prosthesis interpret the signal”). Keep the record only if that framing is acceptable as the AI claim." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Ortiz-Catalan M., Zbinden J., Millenaar J., et al. (2023). A highly integrated bionic hand with neural control and feedback for use in daily life. Science Robotics 8(83): eadf7360. PMID 37820004. Co-authors include Integrum AB and Prensilia SRL staff; open-access manuscript at research.chalmers.se/publication/537965.", "title": "A highly integrated bionic hand with neural control and feedback for use in daily life", "url": "https://doi.org/10.1126/scirobotics.adf7360", "date": "2023-10-11", "written_by": "makers", "quote": "Phantom limb pain intensity decreased from 5 to 3, and stump pain vanished entirely compared with 6 of 10 before the intervention." }, { "kind": "news report", "citation": "Christensen J. / CNN via KEYT (2023). It's not Star Wars-level tech yet, but doctors get a step closer to a bionic hand with special surgery and AI. CNN Health; quotes an independent neurosurgeon, Jorge Gonzalez-Martinez of the University of Pittsburgh.", "title": "It's not Star Wars-level tech yet, but doctors get a step closer to a bionic hand with special surgery and AI", "url": "https://keyt.com/health/cnn-health/2023/10/11/its-not-star-wars-level-tech-yet-but-doctors-get-a-step-closer-to-a-bionic-hand-with-special-surgery-and-ai", "date": "2023-10-11", "written_by": "independent", "quote": "AI algorithms inside the prosthesis interpret the signal and allow her to move the bionic hand." }, { "kind": "press release", "citation": "Sant'Anna School of Advanced Studies via Medical Xpress (2023). Bionic hand merges with user's nervous and skeletal systems. Institutional release reprinted by Medical Xpress.", "title": "Bionic hand merges with user's nervous and skeletal systems", "url": "https://medicalxpress.com/news/2023-10-bionic-merges-user-nervous-skeletal.html", "date": "2023-10-11", "written_by": "makers", "quote": "The robotic hand developed by Prensilia, namely Mia Hand, featured unique motor and sensory components that allowed the user to carry out 80% of the activities of daily living." }, { "kind": "news report", "citation": "Paul A. / Popular Science (2023). Titanium-fused bone tissue connects this bionic hand directly to a patient's nerves. Popular Science.", "title": "Titanium-fused bone tissue connects this bionic hand directly to a patient's nerves", "url": "https://www.popsci.com/technology/bionic-hand-phantom-pain", "date": "2023-10-12", "written_by": "independent", "quote": "By combining osseointegration with reconstructive surgery, implanted electrodes, and AI, we can restore human function in an unprecedented way" }, { "kind": "news report", "citation": "Cara E. / Gizmodo (2023). Woman's Experimental Bionic Hand Passes Major Test With Flying Colors. Gizmodo.", "title": "Woman's Experimental Bionic Hand Passes Major Test With Flying Colors", "url": "https://gizmodo.com/bionic-mia-hand-prosthetic-amputee-phantom-pain-1850919751", "date": "2023-10-12", "written_by": "independent", "quote": "Karin was the first person with below-elbow amputation who received this new concept of a highly integrated bionic hand that can be used independently and reliably in daily life." }, { "kind": "news report", "citation": "Thompson B. / New Atlas (2023). Groundbreaking bionic hand restores quality of life to amputee. New Atlas.", "title": "Groundbreaking bionic hand restores quality of life to amputee", "url": "https://newatlas.com/medical/bionic-hand-restores-life-amputees", "date": "2023-10-11", "written_by": "independent", "quote": "Karin is now using somewhat the same neural resources to control the prosthesis as she did for her missing biological hand." }, { "kind": "news report", "citation": "ScienceAlert (2023). Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves. ScienceAlert.", "title": "Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves", "url": "https://www.sciencealert.com/revolutionary-bionic-hand-fuses-with-womans-bones-muscles-and-nerves", "date": "2023-10-17", "written_by": "independent", "quote": "I have better control over my prosthesis, but above all, my pain has decreased. Today, I need much less medication." }, { "kind": "press release", "citation": "DeTOP project (2019). The first dexterous and sentient hand prosthesis has been successfully implanted. News item on the EU Horizon 2020 consortium site (coordinator Scuola Superiore Sant'Anna; partners include Integrum AB and Prensilia).", "title": "The first dexterous and sentient hand prosthesis has been successfully implanted", "url": "https://www.detop-project.eu/2019/02/05/the-first-dexterous-and-sentient-hand-prosthesis-has-been-successfully-implanted/", "date": "2019-02-05", "written_by": "makers", "quote": "A female Swedish patient with hand amputation has become the first recipient of an osseo-neuromuscular implant to control a dexterous hand prosthesis." } ], "replication": { "produced_by": [ "Osseointegrated titanium implants giving skeletal attachment and a wired path from implanted electrodes to the hand", "Surgical reconstruction that transfers severed nerves to free muscle grafts, adding myoelectric sites and treating neuropathic pain", "A self-contained prosthesis with an embedded controller and battery that needs no external equipment, so it can be worn all day" ], "must_hold": [ "The fixtures must osseointegrate. Here the radial fixture failed, was removed after 5 months and reimplanted with a larger diameter", "Implanted electrodes must stay within working range for years. One e-abutment screw broke after 3.5 years and was replaced", "Outcomes are from one patient with no control group, so the effect size is not established beyond this case" ], "echoes": [] }, "paired_incident": null, "headline": "Bone-anchored Mia Hand cuts Karin's phantom pain from 5 to 3", "metric": "her phantom limb pain fell from 5 to 3, stump pain vanished", "comparator": { "against": "her own phantom limb pain and stump pain before the neuromusculoskeletal prosthesis (also a conventional prosthesis for grip precision)", "before": "phantom pain level 5", "after": "phantom pain level 3; stump pain vanished entirely", "basis": "measured", "quote": "Her phantom pain level dropped from a 5 to a 3, the study said, and her stump pain vanished entirely. She said she’s also been able to sleep better.", "url": "https://keyt.com/health/cnn-health/2023/10/11/its-not-star-wars-level-tech-yet-but-doctors-get-a-step-closer-to-a-bionic-hand-with-special-surgery-and-ai" }, "later": { "status": "unknown", "date": null, "note": "The October 2023 coverage reports more than three years of daily use up to publication; nothing dated after the paper was found.", "quote": null, "url": null }, "value": null, "developer_country": "Sweden", "deployer_country": "Sweden", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-10-09-84b0", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://keyt.com/health/cnn-health/2023/10/11/its-not-star-wars-level-tech-yet-but-doctors-get-a-step-closer-to-a-bionic-hand-with-special-surgery-and-ai; https://medicalxpress.com/news/2023-10-bionic-merges-user-nervous-skeletal.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=AFF:%22Center%20for%20Bionics%20and%20Pain%20Research%22&resultType=core&format=json&pageSize=5; https://en.wikipedia.org/wiki/Sahlgrenska_University_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports, the makers' peer-reviewed study and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0121", "catalog_version": "1.0.0", "source_fingerprint": "fd19527eb4eddf2f9fda28092351bc634dbfca0de59759b028f74b4c07b0463f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0121-source-0001", "AIBD-0121-source-0002", "AIBD-0121-source-0003", "AIBD-0121-source-0004", "AIBD-0121-source-0005", "AIBD-0121-source-0006", "AIBD-0121-source-0007", "AIBD-0121-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Center for Bionics and Pain Research (Chalmers University of Technology and Sahlgrenska University Hospital, Mölndal) with Integrum AB; hand by Scuola Superiore Sant'Anna and Prensilia SRL, under the EU DeTOP project", "deployer": "Sahlgrenska University Hospital, Sweden (surgery led by Rickard Brånemark and Paolo Sassu)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The benefit comes from the whole neuromusculoskeletal interface, not from a learned model alone. The paper reports that in daily life the hand ran on direct control. Signals from two implanted electrodes mapped to open and close, and a sustained open signal switched grasps. Decoding of six movements (100 percent completion) and of five individual fingers (up to 95 percent) was shown in laboratory Motion Tests. The paper never uses the words AI or machine learning. The AI framing comes from the institutions' release (Brånemark: osseointegration, reconstructive surgery, implanted electrodes “and AI”). It also comes from CNN (“AI algorithms inside the prosthesis interpret the signal”). Keep the record only if that framing is acceptable as the AI claim." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Implanted electrodes let the patient control the prosthetic hand. Daily use relied on direct signals for opening, closing, and changing the grasp; more complex decoding was demonstrated in laboratory tests.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The benefit comes from the whole neuromusculoskeletal interface, not from a learned model alone. The paper reports that in daily life the hand ran on direct control. Signals from two implanted electrodes mapped to open and close, and a sustained open signal switched grasps. Decoding of six movements (100 percent completion) and of five individual fingers (up to 95 percent) was shown in laboratory Motion Tests. The paper never uses the words AI or machine learning. The AI framing comes from the institutions' release (Brånemark: osseointegration, reconstructive surgery, implanted electrodes “and AI”). It also comes from CNN (“AI algorithms inside the prosthesis interpret the signal”). Keep the record only if that framing is acceptable as the AI claim." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The paper reports phantom limb pain down from 5 to 3, stump pain from 6 to 0 and sleep interference gone. EQ-5D-5L is up from 0.23 to 0.63 and daily use tops three years. Karin says the research “has given me a better life” and that she needs much less medication. Life-changing for one identifiable person, from a single-patient study without a control group." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports, the makers' peer-reviewed study and two press releases from the makers. 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Life-changing for one identifiable person, from a single-patient study without a control group." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The paper reports phantom limb pain down from 5 to 3, stump pain from 6 to 0 and sleep interference gone. EQ-5D-5L is up from 0.23 to 0.63 and daily use tops three years. Karin says the research “has given me a better life” and that she needs much less medication. Life-changing for one identifiable person, from a single-patient study without a control group." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "her phantom limb pain fell from 5 to 3, stump pain vanished", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The paper does not identify a learned model or describe the method as AI. The institutions’ announcement and CNN supply that description. The reported benefit cannot be attributed to a learned decoder alone.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2023-10-09-84b0" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The October 2023 coverage reports more than three years of daily use up to publication; nothing dated after the paper was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "The patient controlled the hand through signals from her implanted electrodes." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0121" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The daily use of the nerve-linked hand for over three years is also an accessibility gain." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Karin, a Swedish woman born in 1973, lost her right hand below the elbow in a farming accident. She received a neuromusculoskeletal prosthesis at Sahlgrenska University Hospital. It comprises titanium implants in the radius and ulna and severed nerves transferred to muscle grafts. Implanted electrodes feed an embedded controller and a Prensilia Mia Hand. The study ran from September 2018 to April 2021, and the EU DeTOP consortium announced the implantation on 5 February 2019. The case report (Science Robotics, 11 October 2023) states her phantom limb pain fell from 5 to 3 and stump pain vanished. 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Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves. ScienceAlert.", "title": "Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves", "url": "https://www.sciencealert.com/revolutionary-bionic-hand-fuses-with-womans-bones-muscles-and-nerves", "date": "2023-10-17", "written_by": "independent", "quote": "I have better control over my prosthesis, but above all, my pain has decreased. Today, I need much less medication." }, { "kind": "press release", "citation": "DeTOP project (2019). The first dexterous and sentient hand prosthesis has been successfully implanted. 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Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves. ScienceAlert.", "title": "Revolutionary Bionic Hand Fuses With Woman's Bones, Muscles, And Nerves", "url": "https://www.sciencealert.com/revolutionary-bionic-hand-fuses-with-womans-bones-muscles-and-nerves", "date": "2023-10-17", "written_by": "independent", "quote": "I have better control over my prosthesis, but above all, my pain has decreased. Today, I need much less medication." }, { "kind": "press release", "citation": "DeTOP project (2019). The first dexterous and sentient hand prosthesis has been successfully implanted. 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Robotics 2023).", "account": "Karin, a Swedish woman born in 1973, lost her right hand below the elbow in a farming accident. She received a neuromusculoskeletal prosthesis at Sahlgrenska University Hospital. It comprises titanium implants in the radius and ulna and severed nerves transferred to muscle grafts. Implanted electrodes feed an embedded controller and a Prensilia Mia Hand. The study ran from September 2018 to April 2021, and the EU DeTOP consortium announced the implantation on 5 February 2019. The case report (Science Robotics, 11 October 2023) states her phantom limb pain fell from 5 to 3 and stump pain vanished. Quality of life rose, and she had used the hand in daily life for more than three years and continues to." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used a Mia Hand." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Mia Hand" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Transradial neuromusculoskeletal prosthesis: osseointegrated titanium implants with implanted muscle and nerve electrodes, an embedded controller, and the Prensilia Mia Hand" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Center for Bionics and Pain Research (Chalmers University of Technology and Sahlgrenska University Hospital, Mölndal) with Integrum AB; hand by Scuola Superiore Sant'Anna and Prensilia SRL, under the EU DeTOP project" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Karin's bone-anchored, nerve-connected Mia Hand: after more than three years of daily use her phantom pain fell from 5 to 3 and her stump pain vanished (Science Robotics case report)", "headline": "Bone-anchored Mia Hand cuts Karin's phantom pain from 5 to 3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fd19527eb4eddf2f9fda28092351bc634dbfca0de59759b028f74b4c07b0463f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Karin, a Swedish woman born in 1973, lost her right hand below the elbow in a farming accident. She received a neuromusculoskeletal prosthesis at Sahlgrenska University Hospital. It comprises titanium implants in the radius and ulna and severed nerves transferred to muscle grafts. Implanted electrodes feed an embedded controller and a Prensilia Mia Hand. The study ran from September 2018 to April 2021, and the EU DeTOP consortium announced the implantation on 5 February 2019. The case report (Science Robotics, 11 October 2023) states her phantom limb pain fell from 5 to 3 and stump pain vanished. Quality of life rose, and she had used the hand in daily life for more than three years and continues to.", "replication": { "produced_by": [ "Osseointegrated titanium implants giving skeletal attachment and a wired path from implanted electrodes to the hand", "Surgical reconstruction that transfers severed nerves to free muscle grafts, adding myoelectric sites and treating neuropathic pain", "A self-contained prosthesis with an embedded controller and battery that needs no external equipment, so it can be worn all day" ], "must_hold": [ "The fixtures must osseointegrate. Here the radial fixture failed, was removed after 5 months and reimplanted with a larger diameter", "Implanted electrodes must stay within working range for years. One e-abutment screw broke after 3.5 years and was replaced", "Outcomes are from one patient with no control group, so the effect size is not established beyond this case" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0198", "title": "Observe Technologies' camera AI registers behavioral change when gill disease hits two Scottish salmon farms", "summary": "University of Stirling study, 2023 season: fish activity rose from 25.6% to 43.6% (Farm A) and 24.9% to 32.6% (Farm B) after gill health deteriorated; proliferative gill disease drove it.", "date_observed": "2023-10-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Researchers at the University of Stirling's Institute of Aquaculture applied Observe's algorithm to feed-camera video at two commercial Atlantic salmon marine farms in Scotland. Co-authors were from Observe Technologies (Richmond, UK), with Innovate UK funding in partnership with Observe and AKVA Group. The algorithm, a patented convolutional neural network (EP3644717), ran on video in every cage, with 5 and 4 extra cameras in one cage per farm. It outputs “activity” (%), combining fish abundance, speed and shoal cohesion. Gill health, operational welfare indicators, mortality and specific feeding rate were scored weekly. Data were collected from 10 May to 10 September 2023 at Farm A and 22 June to 13 October 2023 at Farm B. Gill health issues arose at both farms in summer 2023. Mean activity in the two months before was 25.6 ± 10.5% (A) and 24.9 ± 7.0% (B). It rose for two months after to 43.6 ± 15.1% and 32.6 ± 9.6%, with fish moving to the cage center. A mixed model found proliferative gill disease the main driver. The paper proposes behavior as a non-invasive welfare indicator but reports no alert preceding diagnosis or changed treatment.", "category": "general benefit", "unexpected": false, "purpose": "Extract group behavior (abundance, speed, shoal cohesion) from feed-camera video as a non-invasive indicator of fish health and welfare.", "system": "Observe Technologies behavioral monitoring algorithm (patented convolutional neural network, EP3644717)", "model_version": null, "developer": "Observe Technologies, Richmond, UK", "deployer": "Two commercial Atlantic salmon marine farms in Scotland, studied by the University of Stirling", "location": null, "domain": "Aquaculture / fish welfare", "segment": "Atlantic salmon sea cages", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Gill disease was scored weekly by conventional means. The paper does not report any farm decision changed by the activity signal." }, { "group": "personal", "depth": null, "reason": "No outcome for farm staff or fish welfare beyond the behavioral correlation is documented." } ], "ai_role": { "status": "assessed", "statement": "The vendor's neural network quantified a behavioral response that coincided with gill disease already identified by weekly scoring. The study shows correlation, not an alert that changed what happened. Vendor staff co-authored the peer-reviewed paper." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Burke M, Nikolic D, Fabry P, Rishi H, Telfer T, Rey Planellas S. Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms. Aquaculture Science and Management 2:15 (2025). doi:10.1186/s44365-025-00020-8", "title": "Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms", "url": "https://doi.org/10.1186/s44365-025-00020-8", "date": "2025-08-15", "written_by": "independent", "quote": "After gill health was compromised, the activity rose significantly for two months in all cages with a mean of 43.6 ± 15.1% and 32.6 ± 9.6%, respectively." } ], "replication": { "produced_by": [ "Feed cameras in all cages plus 4–5 extra cameras in one cage per farm", "Weekly gill scoring, welfare indicators, mortality and feeding-rate records", "A summer 2023 gill-health episode at both farms" ], "must_hold": [ "Gill disease severe enough to alter shoaling and distribution", "Camera coverage of the cage volume" ], "echoes": [] }, "paired_incident": null, "headline": "Observe's AI registers salmon activity rising with gill disease", "metric": "fish activity rose from 25.6% to 43.6% (Farm A) and 24.9% to 32.6% (Farm B)", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later report on the Observe algorithm's use on these or other farms after the 2023 season was found.", "quote": null, "url": null }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/10500815; https://pmc.ncbi.nlm.nih.gov/articles/PMC12369403/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0198", "catalog_version": "1.0.0", "source_fingerprint": "f28425452cbe878906069d1526a8220f9946ddf3b8972ab4a20c7357ae4eeff5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0198-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Observe Technologies, Richmond, UK", "deployer": "Two commercial Atlantic salmon marine farms in Scotland, studied by the University of Stirling" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The vendor's neural network quantified a behavioral response that coincided with gill disease already identified by weekly scoring. The study shows correlation, not an alert that changed what happened. Vendor staff co-authored the peer-reviewed paper." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The vendor's neural network quantified a behavioral response that coincided with gill disease already identified by weekly scoring. The study shows correlation, not an alert that changed what happened. Vendor staff co-authored the peer-reviewed paper." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Gill disease was scored weekly by conventional means. The paper does not report any farm decision changed by the activity signal." }, { "group": "personal", "reason": "No outcome for farm staff or fish welfare beyond the behavioral correlation is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Gill disease was scored weekly by conventional means. The paper does not report any farm decision changed by the activity signal." }, { "group": "personal", "reason": "No outcome for farm staff or fish welfare beyond the behavioral correlation is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "fish activity rose from 25.6% to 43.6% (Farm A) and 24.9% to 32.6% (Farm B)", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later report on the Observe algorithm's use on these or other farms after the 2023 season was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0198" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Researchers at the University of Stirling's Institute of Aquaculture applied Observe's algorithm to feed-camera video at two commercial Atlantic salmon marine farms in Scotland. Co-authors were from Observe Technologies (Richmond, UK), with Innovate UK funding in partnership with Observe and AKVA Group. The algorithm, a patented convolutional neural network (EP3644717), ran on video in every cage, with 5 and 4 extra cameras in one cage per farm. It outputs “activity” (%), combining fish abundance, speed and shoal cohesion. Gill health, operational welfare indicators, mortality and specific feeding rate were scored weekly. Data were collected from 10 May to 10 September 2023 at Farm A and 22 June to 13 October 2023 at Farm B. Gill health issues arose at both farms in summer 2023. Mean activity in the two months before was 25.6 ± 10.5% (A) and 24.9 ± 7.0% (B). It rose for two months after to 43.6 ± 15.1% and 32.6 ± 9.6%, with fish moving to the cage center. A mixed model found proliferative gill disease the main driver. The paper proposes behavior as a non-invasive welfare indicator but reports no alert preceding diagnosis or changed treatment.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Gill disease was scored weekly by conventional means. The paper does not report any farm decision changed by the activity signal." }, { "group": "personal", "reason": "No outcome for farm staff or fish welfare beyond the behavioral correlation is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Extract group behavior (abundance, speed, shoal cohesion) from feed-camera video as a non-invasive indicator of fish health and welfare." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Extract group behavior (abundance, speed, shoal cohesion) from feed-camera video as a non-invasive indicator of fish health and welfare." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-10-13", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/10500815; https://pmc.ncbi.nlm.nih.gov/articles/PMC12369403/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Feed cameras in all cages plus 4–5 extra cameras in one cage per farm", "Weekly gill scoring, welfare indicators, mortality and feeding-rate records", "A summer 2023 gill-health episode at both farms" ], "must_hold": [ "Gill disease severe enough to alter shoaling and distribution", "Camera coverage of the cage volume" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/10500815; https://pmc.ncbi.nlm.nih.gov/articles/PMC12369403/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Aquaculture / fish welfare", "segment": "Atlantic salmon sea cages" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Burke M, Nikolic D, Fabry P, Rishi H, Telfer T, Rey Planellas S. Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms. Aquaculture Science and Management 2:15 (2025). doi:10.1186/s44365-025-00020-8", "title": "Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms", "url": "https://doi.org/10.1186/s44365-025-00020-8", "date": "2025-08-15", "written_by": "independent", "quote": "After gill health was compromised, the activity rose significantly for two months in all cages with a mean of 43.6 ± 15.1% and 32.6 ± 9.6%, respectively." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0198-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Burke M, Nikolic D, Fabry P, Rishi H, Telfer T, Rey Planellas S. Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms. Aquaculture Science and Management 2:15 (2025). doi:10.1186/s44365-025-00020-8", "title": "Precision farming in aquaculture: assessing gill health in Atlantic salmon (Salmo salar) using a non-invasive, AI-driven behavioural monitoring approach in commercial farms", "url": "https://doi.org/10.1186/s44365-025-00020-8", "date": "2025-08-15", "written_by": "independent", "quote": "After gill health was compromised, the activity rose significantly for two months in all cages with a mean of 43.6 ± 15.1% and 32.6 ± 9.6%, respectively." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "University of Stirling study, 2023 season: fish activity rose from 25.6% to 43.6% (Farm A) and 24.9% to 32.6% (Farm B) after gill health deteriorated; proliferative gill disease drove it.", "account": "Researchers at the University of Stirling's Institute of Aquaculture applied Observe's algorithm to feed-camera video at two commercial Atlantic salmon marine farms in Scotland. Co-authors were from Observe Technologies (Richmond, UK), with Innovate UK funding in partnership with Observe and AKVA Group. The algorithm, a patented convolutional neural network (EP3644717), ran on video in every cage, with 5 and 4 extra cameras in one cage per farm. It outputs “activity” (%), combining fish abundance, speed and shoal cohesion. Gill health, operational welfare indicators, mortality and specific feeding rate were scored weekly. Data were collected from 10 May to 10 September 2023 at Farm A and 22 June to 13 October 2023 at Farm B. Gill health issues arose at both farms in summer 2023. Mean activity in the two months before was 25.6 ± 10.5% (A) and 24.9 ± 7.0% (B). It rose for two months after to 43.6 ± 15.1% and 32.6 ± 9.6%, with fish moving to the cage center. A mixed model found proliferative gill disease the main driver. The paper proposes behavior as a non-invasive welfare indicator but reports no alert preceding diagnosis or changed treatment." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Observe Technologies behavioral monitoring algorithm (patented convolutional neural network, EP3644717)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Observe Technologies, Richmond, UK" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Observe Technologies' camera AI registers behavioral change when gill disease hits two Scottish salmon farms", "headline": "Observe's AI registers salmon activity rising with gill disease" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f28425452cbe878906069d1526a8220f9946ddf3b8972ab4a20c7357ae4eeff5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Researchers at the University of Stirling's Institute of Aquaculture applied Observe's algorithm to feed-camera video at two commercial Atlantic salmon marine farms in Scotland. Co-authors were from Observe Technologies (Richmond, UK), with Innovate UK funding in partnership with Observe and AKVA Group. The algorithm, a patented convolutional neural network (EP3644717), ran on video in every cage, with 5 and 4 extra cameras in one cage per farm. It outputs “activity” (%), combining fish abundance, speed and shoal cohesion. Gill health, operational welfare indicators, mortality and specific feeding rate were scored weekly. Data were collected from 10 May to 10 September 2023 at Farm A and 22 June to 13 October 2023 at Farm B. Gill health issues arose at both farms in summer 2023. Mean activity in the two months before was 25.6 ± 10.5% (A) and 24.9 ± 7.0% (B). It rose for two months after to 43.6 ± 15.1% and 32.6 ± 9.6%, with fish moving to the cage center. A mixed model found proliferative gill disease the main driver. The paper proposes behavior as a non-invasive welfare indicator but reports no alert preceding diagnosis or changed treatment.", "replication": { "produced_by": [ "Feed cameras in all cages plus 4–5 extra cameras in one cage per farm", "Weekly gill scoring, welfare indicators, mortality and feeding-rate records", "A summer 2023 gill-health episode at both farms" ], "must_hold": [ "Gill disease severe enough to alter shoaling and distribution", "Camera coverage of the cage volume" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0201", "title": "Student-built AI flags listless and feverish lion-head geese; survival at a Shantou cooperative may have risen 30%", "summary": "Sixteen Shenzhen University students with Tencent engineers built a camera system from 6,000 labeled images; Xinhua (13 Oct 2023) reports real-time alerts and 30% higher survival at the cooperative.", "date_observed": "2023-10-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Xinhua reported on 13 October 2023 (syndicated by CGTN the next day) on 16 students from the Shenzhen University-Tencent Cloud AI BEng program. Goose farmer Jin Shutao had invited them in 2022 to his lion-head goose cooperative in Houxi Village, Chenghai District, Shantou. They built an AI program that identifies sick geese by measuring how long each bird stays still, supplemented by detecting feverish goslings. They worked in a 500 m² space holding over 4,000 geese. They used existing farm cameras and manually labeled 6,000 images of 300,000 geese. With Tencent engineers they improved recognition in crowded scenes and tracking of each goose's stillness. The program now gives real-time alerts for “listless geese” and “feverish geese” and displays temperature, humidity and PM2.5 trends. Xinhua states this has helped the farm increase survival of lion-head geese by 30 percent. It quotes student Wang Yifeng and Shen Linlin of Shenzhen University's visual research institute. The article recalls a 2018 avian influenza outbreak that left five of thousands of geese in the village alive. The OECD AI Incidents Monitor lists the event. The 30% figure is undated and has no supporting method.", "category": "benefit created", "unexpected": false, "purpose": "Identify sick geese from camera footage by how long they stay still (and fever in goslings) and alert breeders in real time.", "system": "AI goose-breeding program (recognition and tracking algorithms on farm cameras)", "model_version": null, "developer": "Sixteen students of the Shenzhen University-Tencent Cloud AI BEng program, guided by university teachers and Tencent engineers", "deployer": "Jin Shutao's lion-head goose farming cooperative, Houxi Village, Chenghai District, Shantou", "location": "Shantou, China", "domain": "Livestock health", "segment": "Goose farming", "benefit_type": "Reduced Risk", "taxonomy_note": "The good is fewer goose deaths at the cooperative, a livestock loss reduced, and the 30% figure rests on state media with no baseline.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Xinhua states the program “has helped the farm increase the survival rate of lion-head geese by 30 percent”. No baseline, period or verification is given." }, { "group": "personal", "depth": null, "reason": "Farmer Jin Shutao is named but no personal outcome beyond the farm figure is reported." } ], "ai_role": { "status": "assessed", "statement": "The system's real-time alerts are the only mechanism described for the survival gain. The reports do not separate the AI's effect from other changes on the farm. Sources are independent news reports (Xinhua, CGTN) with named sources. No veterinary or peer-reviewed confirmation was found." }, "evidence": [ { "kind": "news report", "citation": "Xinhua. Across China: AI program developed by students benefits goose farm. Xinhua, Shenzhen, 13 October 2023.", "title": "Across China: AI program developed by students benefits goose farm", "url": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html", "date": "2023-10-13", "written_by": "independent", "quote": "This has helped the farm increase the survival rate of lion-head geese by 30 percent." }, { "kind": "news report", "citation": "CGTN. AI program developed by Chinese college students benefits goose farm. CGTN, 14 October 2023.", "title": "AI program developed by Chinese college students benefits goose farm", "url": "https://news.cgtn.com/news/2023-10-14/AI-program-developed-by-Chinese-college-students-benefits-goose-farm-1nTtBT0TBlK/index.html", "date": "2023-10-14", "written_by": "independent", "quote": "an artificial intelligence (AI) program that helps identify sick lion-head geese for breeders, increasing the survival rate of the gaggle by 30 percent." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI System Developed by Students Boosts Goose Survival Rates in China. Record 2023-10-13-d63c.", "title": "AI System Developed by Students Boosts Goose Survival Rates in China", "url": "https://oecd.ai/en/incidents/2023-10-13-d63c", "date": "2023-10-13", "written_by": "independent", "quote": "The system increased the geese's survival rate by 30%, demonstrating AI's positive impact on animal health and agricultural productivity." } ], "replication": { "produced_by": [ "Existing farm cameras and 6,000 manually labeled images of 300,000 geese", "Stillness duration as the sickness proxy, with fever detection in goslings", "Over 4,000 geese in a 500 m² space" ], "must_hold": [ "Camera coverage in dense flocks", "Continued tuning of the algorithm to the specific farm (the students found no one-size-fits-all algorithm)" ], "echoes": [] }, "paired_incident": null, "headline": "Shenzhen students' goose AI may have lifted survival 30%", "metric": "helped the farm increase survival of lion-head geese by 30 percent", "comparator": { "against": "the farm's survival rate before the AI program (no baseline figure is given)", "before": null, "after": "survival rate of lion-head geese increased by 30 percent", "basis": "assumed", "quote": "This has helped the farm increase the survival rate of lion-head geese by 30 percent.", "url": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html" }, "later": { "status": "unknown", "date": null, "note": "No later report on the cooperative or the program after October 2023 was found.", "quote": null, "url": null }, "value": null, "developer_country": "China", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Shenzhen_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0201", "catalog_version": "1.0.0", "source_fingerprint": "d6635139496c236f8df3b26dc3192b18983db0ce410110d52327c24bc3af4108", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0201-source-0001", "AIBD-0201-source-0002", "AIBD-0201-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Sixteen students of the Shenzhen University-Tencent Cloud AI BEng program, guided by university teachers and Tencent engineers", "deployer": "Jin Shutao's lion-head goose farming cooperative, Houxi Village, Chenghai District, Shantou" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's real-time alerts are the only mechanism described for the survival gain. The reports do not separate the AI's effect from other changes on the farm. Sources are independent news reports (Xinhua, CGTN) with named sources. No veterinary or peer-reviewed confirmation was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The system's real-time alerts are the only mechanism described for the survival gain. The reports do not separate the AI's effect from other changes on the farm. Sources are independent news reports (Xinhua, CGTN) with named sources. No veterinary or peer-reviewed confirmation was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Xinhua states the program “has helped the farm increase the survival rate of lion-head geese by 30 percent”. No baseline, period or verification is given." }, { "group": "personal", "reason": "Farmer Jin Shutao is named but no personal outcome beyond the farm figure is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and a registry entry. 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the farm increase survival of lion-head geese by 30 percent", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later report on the cooperative or the program after October 2023 was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0201" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "The good is fewer goose deaths at the cooperative, a livestock loss reduced, and the 30% figure rests on state media with no baseline." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Xinhua reported on 13 October 2023 (syndicated by CGTN the next day) on 16 students from the Shenzhen University-Tencent Cloud AI BEng program. Goose farmer Jin Shutao had invited them in 2022 to his lion-head goose cooperative in Houxi Village, Chenghai District, Shantou. They built an AI program that identifies sick geese by measuring how long each bird stays still, supplemented by detecting feverish goslings. They worked in a 500 m² space holding over 4,000 geese. They used existing farm cameras and manually labeled 6,000 images of 300,000 geese. With Tencent engineers they improved recognition in crowded scenes and tracking of each goose's stillness. The program now gives real-time alerts for “listless geese” and “feverish geese” and displays temperature, humidity and PM2.5 trends. Xinhua states this has helped the farm increase survival of lion-head geese by 30 percent. It quotes student Wang Yifeng and Shen Linlin of Shenzhen University's visual research institute. The article recalls a 2018 avian influenza outbreak that left five of thousands of geese in the village alive. The OECD AI Incidents Monitor lists the event. 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No baseline, period or verification is given." }, { "group": "personal", "reason": "Farmer Jin Shutao is named but no personal outcome beyond the farm figure is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify sick geese from camera footage by how long they stay still (and fever in goslings) and alert breeders in real time." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Shantou, China", "developer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Shenzhen_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Livestock health", "segment": "Goose farming" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Xinhua. Across China: AI program developed by students benefits goose farm. Xinhua, Shenzhen, 13 October 2023.", "title": "Across China: AI program developed by students benefits goose farm", "url": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html", "date": "2023-10-13", "written_by": "independent", "quote": "This has helped the farm increase the survival rate of lion-head geese by 30 percent." }, { "kind": "news report", "citation": "CGTN. AI program developed by Chinese college students benefits goose farm. CGTN, 14 October 2023.", "title": "AI program developed by Chinese college students benefits goose farm", "url": "https://news.cgtn.com/news/2023-10-14/AI-program-developed-by-Chinese-college-students-benefits-goose-farm-1nTtBT0TBlK/index.html", "date": "2023-10-14", "written_by": "independent", "quote": "an artificial intelligence (AI) program that helps identify sick lion-head geese for breeders, increasing the survival rate of the gaggle by 30 percent." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI System Developed by Students Boosts Goose Survival Rates in China. Record 2023-10-13-d63c.", "title": "AI System Developed by Students Boosts Goose Survival Rates in China", "url": "https://oecd.ai/en/incidents/2023-10-13-d63c", "date": "2023-10-13", "written_by": "independent", "quote": "The system increased the geese's survival rate by 30%, demonstrating AI's positive impact on animal health and agricultural productivity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0201-source-0001", "AIBD-0201-source-0002", "AIBD-0201-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Xinhua. Across China: AI program developed by students benefits goose farm. Xinhua, Shenzhen, 13 October 2023.", "title": "Across China: AI program developed by students benefits goose farm", "url": "https://english.news.cn/20231013/3c56fe0ec8b74246a934ca2ad09ac3ea/c.html", "date": "2023-10-13", "written_by": "independent", "quote": "This has helped the farm increase the survival rate of lion-head geese by 30 percent." }, { "kind": "news report", "citation": "CGTN. AI program developed by Chinese college students benefits goose farm. CGTN, 14 October 2023.", "title": "AI program developed by Chinese college students benefits goose farm", "url": "https://news.cgtn.com/news/2023-10-14/AI-program-developed-by-Chinese-college-students-benefits-goose-farm-1nTtBT0TBlK/index.html", "date": "2023-10-14", "written_by": "independent", "quote": "an artificial intelligence (AI) program that helps identify sick lion-head geese for breeders, increasing the survival rate of the gaggle by 30 percent." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI System Developed by Students Boosts Goose Survival Rates in China. Record 2023-10-13-d63c.", "title": "AI System Developed by Students Boosts Goose Survival Rates in China", "url": "https://oecd.ai/en/incidents/2023-10-13-d63c", "date": "2023-10-13", "written_by": "independent", "quote": "The system increased the geese's survival rate by 30%, demonstrating AI's positive impact on animal health and agricultural productivity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Sixteen Shenzhen University students with Tencent engineers built a camera system from 6,000 labeled images; Xinhua (13 Oct 2023) reports real-time alerts and 30% higher survival at the cooperative.", "account": "Xinhua reported on 13 October 2023 (syndicated by CGTN the next day) on 16 students from the Shenzhen University-Tencent Cloud AI BEng program. Goose farmer Jin Shutao had invited them in 2022 to his lion-head goose cooperative in Houxi Village, Chenghai District, Shantou. They built an AI program that identifies sick geese by measuring how long each bird stays still, supplemented by detecting feverish goslings. They worked in a 500 m² space holding over 4,000 geese. They used existing farm cameras and manually labeled 6,000 images of 300,000 geese. With Tencent engineers they improved recognition in crowded scenes and tracking of each goose's stillness. The program now gives real-time alerts for “listless geese” and “feverish geese” and displays temperature, humidity and PM2.5 trends. Xinhua states this has helped the farm increase survival of lion-head geese by 30 percent. It quotes student Wang Yifeng and Shen Linlin of Shenzhen University's visual research institute. The article recalls a 2018 avian influenza outbreak that left five of thousands of geese in the village alive. The OECD AI Incidents Monitor lists the event. The 30% figure is undated and has no supporting method." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI goose-breeding program (recognition and tracking algorithms on farm cameras)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Sixteen students of the Shenzhen University-Tencent Cloud AI BEng program, guided by university teachers and Tencent engineers" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Student-built AI flags listless and feverish lion-head geese; survival at a Shantou cooperative may have risen 30%", "headline": "Shenzhen students' goose AI may have lifted survival 30%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d6635139496c236f8df3b26dc3192b18983db0ce410110d52327c24bc3af4108" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Xinhua reported on 13 October 2023 (syndicated by CGTN the next day) on 16 students from the Shenzhen University-Tencent Cloud AI BEng program. Goose farmer Jin Shutao had invited them in 2022 to his lion-head goose cooperative in Houxi Village, Chenghai District, Shantou. They built an AI program that identifies sick geese by measuring how long each bird stays still, supplemented by detecting feverish goslings. They worked in a 500 m² space holding over 4,000 geese. They used existing farm cameras and manually labeled 6,000 images of 300,000 geese. With Tencent engineers they improved recognition in crowded scenes and tracking of each goose's stillness. The program now gives real-time alerts for “listless geese” and “feverish geese” and displays temperature, humidity and PM2.5 trends. Xinhua states this has helped the farm increase survival of lion-head geese by 30 percent. It quotes student Wang Yifeng and Shen Linlin of Shenzhen University's visual research institute. The article recalls a 2018 avian influenza outbreak that left five of thousands of geese in the village alive. The OECD AI Incidents Monitor lists the event. The 30% figure is undated and has no supporting method.", "replication": { "produced_by": [ "Existing farm cameras and 6,000 manually labeled images of 300,000 geese", "Stillness duration as the sickness proxy, with fever detection in goslings", "Over 4,000 geese in a 500 m² space" ], "must_hold": [ "Camera coverage in dense flocks", "Continued tuning of the algorithm to the specific farm (the students found no one-size-fits-all algorithm)" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0379", "title": "LAPD's Boston Dynamics Spot quadruped is sent onto a Hollywood Metro bus during a two-hour standoff with an armed man found asleep; he wakes, surrenders and is arrested, and the gun proves to be a BB gun", "summary": "LAPD deployed its Boston Dynamics Spot quadruped during a 8 November 2023 standoff with an armed man asleep on a Hollywood Metro bus; he woke, surrendered and was arrested; the gun was a BB gun.", "date_observed": "2023-11-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Just before 4 a.m. on 8 November 2023, a passenger on a Metro bus in Hollywood reported an armed man aboard. The bus was at Melrose and Western avenues. The driver pulled over and evacuated the other passengers. Officers got no response from the man, and a two-hour standoff followed (Los Angeles Times via Police1, 9 November 2023). The LAPD sent in its Boston Dynamics Spot quadruped. Its camera confirmed the man was asleep with a gun (Police1). The LAPD's quarterly report to the Police Commission says the robot was a barrier between suspect and firearm (NBC Los Angeles, 8 March 2024). The man woke, left the bus and was taken into custody about 6:40 a.m. The weapon was a BB gun (Police1). Deputy Chief David Kowalski approves each use. The robot cost nearly $300,000 (NBC). International Business Times' October 2024 account says the robot removed the gun.", "category": "protective response", "unexpected": false, "purpose": "Acquired, in Deputy Chief Kowalski's words, “to save lives” by putting a camera and an articulating arm into dangerous scenes ahead of officers. This standoff was that use.", "system": "Boston Dynamics Spot quadruped robot (LAPD 'Quadruped Unmanned Ground Vehicle') with camera and articulating arm", "model_version": null, "developer": "Boston Dynamics", "deployer": "Los Angeles Police Department", "location": "Los Angeles, United States", "domain": "Law enforcement / tactical operations", "segment": "Armed standoffs and barricaded suspects", "benefit_type": "Reduced Risk", "taxonomy_note": "Trustible's Reduced Violence covers a weapon found, but what the sources establish is that officers kept their distance while a camera confirmed a sleeping, apparently armed man and the gun proved to be a BB gun; the good is the lowered risk to officers and the public while the standoff ran.", "registry_ids": { "oecd_aim": "2024-10-02-1544" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The LAPD could confirm from the robot's camera that the man was asleep. By its own report, it kept the robot between him and the gun. The two-hour standoff ended in an arrest with no injury reported. A measurable result for the unit, with no counterfactual that officers would otherwise have been hurt." }, { "group": "personal", "depth": null, "reason": "The passengers had been evacuated before the robot was used, and the suspect was taken into custody unharmed. None of the reports ties either outcome to the robot rather than to the man waking and leaving the bus." } ], "ai_role": { "status": "assessed", "statement": "The accounts describe a remotely deployed quadruped with a camera and an articulating arm. None says that any autonomous function made a decision in this incident. The robot contributed a camera view confirming the man was asleep and, per the LAPD's report, a physical barrier between him and the gun. The Monitor's “AI-powered” label rests on the Boston Dynamics platform, not on anything the system is reported to have decided." }, "evidence": [ { "kind": "news report", "citation": "Goldberg, N., Los Angeles Times via Police1 (2023). LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus. Police1, November 9, 2023.", "title": "LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus", "url": "https://www.police1.com/police-robots/lapd-robot-dog-brings-peaceful-end-to-standoff-after-sniffing-out-armed-man-on-bus", "date": "2023-11-09", "written_by": "independent", "quote": "The guy eventually woke up, got off the bus and officers were able to talk to him and take him into custody for further questioning." }, { "kind": "news report", "citation": "NBC Los Angeles (2024). LAPD reports 2 more uses of its robotic dog. NBC Los Angeles, March 8, 2024.", "title": "LAPD reports 2 more uses of its robotic dog", "url": "https://www.nbclosangeles.com/investigations/lapd-reports-2-more-uses-of-its-robotic-dog/3359391/", "date": "2024-03-08", "written_by": "independent", "quote": "create a barrier between the suspect and the firearm" }, { "kind": "news report", "citation": "Urban, E. (2024). LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized. International Business Times, October 3, 2024.", "title": "LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized", "url": "https://www.ibtimes.com/lapd-robot-dog-spot-3745457", "date": "2024-10-03", "written_by": "independent", "quote": "The main reason that we acquired Spot is to save lives." }, { "kind": "other", "citation": "Los Angeles City Clerk (2023). Council File 22-1438, Quadruped Unmanned Ground Vehicle donation to the LAPD. Los Angeles City Clerk Connect, May 23, 2023.", "title": "Council File 22-1438", "url": "https://cityclerk.lacity.org/lacityclerkconnect/index.cfm?fa=ccfi.viewrecord&cfnumber=22-1438", "date": "2023-05-23", "written_by": "deployer", "quote": "Report from Board of Police Commissioners" }, { "kind": "registry label", "citation": "OECD.AI (2024). LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns. OECD AI Incidents and Hazards Monitor, 2024-10-02.", "title": "LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns", "url": "https://oecd.ai/en/incidents/2024-10-02-1544", "date": "2024-10-02", "written_by": "independent", "quote": "to safely disarm an armed suspect on a Metro bus, preventing injury" } ], "replication": { "produced_by": [ "An armed or apparently armed person unresponsive in a confined space that officers cannot safely approach", "A tactical unit with a camera-and-arm ground robot on call and a deputy chief's approval for each use" ], "must_hold": [ "Officers position the robot and watch its camera before any approach rather than acting on its own motion", "Each deployment is approved in advance and reported to the Police Commission and City Council" ], "echoes": [] }, "paired_incident": null, "headline": "Robot dog checks armed man on Hollywood bus; standoff ends in arrest", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-10-02-1544", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Boston_Dynamics; https://en.wikipedia.org/wiki/Los_Angeles_Police_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, a registry entry and the deployer's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0379", "catalog_version": "1.0.0", "source_fingerprint": "60b68178677d3993985f56f004eb346c79bb0003c8a8d5bd6b296ca89336d3d1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0379-source-0001", "AIBD-0379-source-0002", "AIBD-0379-source-0003", "AIBD-0379-source-0004", "AIBD-0379-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Boston Dynamics", "deployer": "Los Angeles Police Department" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The accounts describe a remotely deployed quadruped with a camera and an articulating arm. None says that any autonomous function made a decision in this incident. The robot contributed a camera view confirming the man was asleep and, per the LAPD's report, a physical barrier between him and the gun. The Monitor's “AI-powered” label rests on the Boston Dynamics platform, not on anything the system is reported to have decided." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The accounts describe a remotely deployed quadruped with a camera and an articulating arm. None says that any autonomous function made a decision in this incident. The robot contributed a camera view confirming the man was asleep and, per the LAPD's report, a physical barrier between him and the gun. The Monitor's “AI-powered” label rests on the Boston Dynamics platform, not on anything the system is reported to have decided." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The LAPD could confirm from the robot's camera that the man was asleep. 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None of the reports ties either outcome to the robot rather than to the man waking and leaving the bus." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports, a registry entry and the deployer's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The LAPD could confirm from the robot's camera that the man was asleep. By its own report, it kept the robot between him and the gun. The two-hour standoff ended in an arrest with no injury reported. A measurable result for the unit, with no counterfactual that officers would otherwise have been hurt." }, { "group": "personal", "reason": "The passengers had been evacuated before the robot was used, and the suspect was taken into custody unharmed. None of the reports ties either outcome to the robot rather than to the man waking and leaving the bus." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The LAPD could confirm from the robot's camera that the man was asleep. By its own report, it kept the robot between him and the gun. The two-hour standoff ended in an arrest with no injury reported. A measurable result for the unit, with no counterfactual that officers would otherwise have been hurt." }, { "group": "personal", "reason": "The passengers had been evacuated before the robot was used, and the suspect was taken into custody unharmed. None of the reports ties either outcome to the robot rather than to the man waking and leaving the bus." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { 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}, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2024-10-02-1544" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0379" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "Trustible's Reduced Violence covers a weapon found, but what the sources establish is that officers kept their distance while a camera confirmed a sleeping, apparently armed man and the gun proved to be a BB gun; the good is the lowered risk to officers and the public while the standoff ran." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Just before 4 a.m. on 8 November 2023, a passenger on a Metro bus in Hollywood reported an armed man aboard. The bus was at Melrose and Western avenues. The driver pulled over and evacuated the other passengers. Officers got no response from the man, and a two-hour standoff followed (Los Angeles Times via Police1, 9 November 2023). The LAPD sent in its Boston Dynamics Spot quadruped. Its camera confirmed the man was asleep with a gun (Police1). The LAPD's quarterly report to the Police Commission says the robot was a barrier between suspect and firearm (NBC Los Angeles, 8 March 2024). The man woke, left the bus and was taken into custody about 6:40 a.m. The weapon was a BB gun (Police1). Deputy Chief David Kowalski approves each use. The robot cost nearly $300,000 (NBC). International Business Times' October 2024 account says the robot removed the gun.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The LAPD could confirm from the robot's camera that the man was asleep. By its own report, it kept the robot between him and the gun. The two-hour standoff ended in an arrest with no injury reported. A measurable result for the unit, with no counterfactual that officers would otherwise have been hurt." }, { "group": "personal", "reason": "The passengers had been evacuated before the robot was used, and the suspect was taken into custody unharmed. None of the reports ties either outcome to the robot rather than to the man waking and leaving the bus." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Acquired, in Deputy Chief Kowalski's words, “to save lives” by putting a camera and an articulating arm into dangerous scenes ahead of officers. This standoff was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Los Angeles, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Acquired, in Deputy Chief Kowalski's words, “to save lives” by putting a camera and an articulating arm into dangerous scenes ahead of officers. This standoff was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-11-08", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-10-02-1544", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Boston_Dynamics; https://en.wikipedia.org/wiki/Los_Angeles_Police_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An armed or apparently armed person unresponsive in a confined space that officers cannot safely approach", "A tactical unit with a camera-and-arm ground robot on call and a deputy chief's approval for each use" ], "must_hold": [ "Officers position the robot and watch its camera before any approach rather than acting on its own motion", "Each deployment is approved in advance and reported to the Police Commission and City Council" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-10-02-1544", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Boston_Dynamics; https://en.wikipedia.org/wiki/Los_Angeles_Police_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Law enforcement / tactical operations", "segment": "Armed standoffs and barricaded suspects" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Goldberg, N., Los Angeles Times via Police1 (2023). LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus. Police1, November 9, 2023.", "title": "LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus", "url": "https://www.police1.com/police-robots/lapd-robot-dog-brings-peaceful-end-to-standoff-after-sniffing-out-armed-man-on-bus", "date": "2023-11-09", "written_by": "independent", "quote": "The guy eventually woke up, got off the bus and officers were able to talk to him and take him into custody for further questioning." }, { "kind": "news report", "citation": "NBC Los Angeles (2024). LAPD reports 2 more uses of its robotic dog. NBC Los Angeles, March 8, 2024.", "title": "LAPD reports 2 more uses of its robotic dog", "url": "https://www.nbclosangeles.com/investigations/lapd-reports-2-more-uses-of-its-robotic-dog/3359391/", "date": "2024-03-08", "written_by": "independent", "quote": "create a barrier between the suspect and the firearm" }, { "kind": "news report", "citation": "Urban, E. (2024). LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized. International Business Times, October 3, 2024.", "title": "LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized", "url": "https://www.ibtimes.com/lapd-robot-dog-spot-3745457", "date": "2024-10-03", "written_by": "independent", "quote": "The main reason that we acquired Spot is to save lives." }, { "kind": "other", "citation": "Los Angeles City Clerk (2023). Council File 22-1438, Quadruped Unmanned Ground Vehicle donation to the LAPD. Los Angeles City Clerk Connect, May 23, 2023.", "title": "Council File 22-1438", "url": "https://cityclerk.lacity.org/lacityclerkconnect/index.cfm?fa=ccfi.viewrecord&cfnumber=22-1438", "date": "2023-05-23", "written_by": "deployer", "quote": "Report from Board of Police Commissioners" }, { "kind": "registry label", "citation": "OECD.AI (2024). LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns. OECD AI Incidents and Hazards Monitor, 2024-10-02.", "title": "LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns", "url": "https://oecd.ai/en/incidents/2024-10-02-1544", "date": "2024-10-02", "written_by": "independent", "quote": "to safely disarm an armed suspect on a Metro bus, preventing injury" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0379-source-0001", "AIBD-0379-source-0002", "AIBD-0379-source-0003", "AIBD-0379-source-0004", "AIBD-0379-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Goldberg, N., Los Angeles Times via Police1 (2023). LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus. Police1, November 9, 2023.", "title": "LAPD robot dog brings peaceful end to standoff after 'sniffing out' armed man on bus", "url": "https://www.police1.com/police-robots/lapd-robot-dog-brings-peaceful-end-to-standoff-after-sniffing-out-armed-man-on-bus", "date": "2023-11-09", "written_by": "independent", "quote": "The guy eventually woke up, got off the bus and officers were able to talk to him and take him into custody for further questioning." }, { "kind": "news report", "citation": "NBC Los Angeles (2024). LAPD reports 2 more uses of its robotic dog. NBC Los Angeles, March 8, 2024.", "title": "LAPD reports 2 more uses of its robotic dog", "url": "https://www.nbclosangeles.com/investigations/lapd-reports-2-more-uses-of-its-robotic-dog/3359391/", "date": "2024-03-08", "written_by": "independent", "quote": "create a barrier between the suspect and the firearm" }, { "kind": "news report", "citation": "Urban, E. (2024). LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized. International Business Times, October 3, 2024.", "title": "LAPD Defends Unleashing Robot Dog on City, Promises 'Spot' Will Never Be Weaponized", "url": "https://www.ibtimes.com/lapd-robot-dog-spot-3745457", "date": "2024-10-03", "written_by": "independent", "quote": "The main reason that we acquired Spot is to save lives." }, { "kind": "other", "citation": "Los Angeles City Clerk (2023). Council File 22-1438, Quadruped Unmanned Ground Vehicle donation to the LAPD. Los Angeles City Clerk Connect, May 23, 2023.", "title": "Council File 22-1438", "url": "https://cityclerk.lacity.org/lacityclerkconnect/index.cfm?fa=ccfi.viewrecord&cfnumber=22-1438", "date": "2023-05-23", "written_by": "deployer", "quote": "Report from Board of Police Commissioners" }, { "kind": "registry label", "citation": "OECD.AI (2024). LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns. OECD AI Incidents and Hazards Monitor, 2024-10-02.", "title": "LAPD Deploys AI Robot Dog 'Spot' to Disarm Armed Suspect, Raising Community Concerns", "url": "https://oecd.ai/en/incidents/2024-10-02-1544", "date": "2024-10-02", "written_by": "independent", "quote": "to safely disarm an armed suspect on a Metro bus, preventing injury" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "LAPD deployed its Boston Dynamics Spot quadruped during a 8 November 2023 standoff with an armed man asleep on a Hollywood Metro bus; he woke, surrendered and was arrested; the gun was a BB gun.", "account": "Just before 4 a.m. on 8 November 2023, a passenger on a Metro bus in Hollywood reported an armed man aboard. The bus was at Melrose and Western avenues. The driver pulled over and evacuated the other passengers. Officers got no response from the man, and a two-hour standoff followed (Los Angeles Times via Police1, 9 November 2023). The LAPD sent in its Boston Dynamics Spot quadruped. Its camera confirmed the man was asleep with a gun (Police1). The LAPD's quarterly report to the Police Commission says the robot was a barrier between suspect and firearm (NBC Los Angeles, 8 March 2024). The man woke, left the bus and was taken into custody about 6:40 a.m. The weapon was a BB gun (Police1). Deputy Chief David Kowalski approves each use. The robot cost nearly $300,000 (NBC). International Business Times' October 2024 account says the robot removed the gun." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Boston Dynamics Spot quadruped robot (LAPD 'Quadruped Unmanned Ground Vehicle') with camera and articulating arm" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Boston Dynamics" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "LAPD's Boston Dynamics Spot quadruped is sent onto a Hollywood Metro bus during a two-hour standoff with an armed man found asleep; he wakes, surrenders and is arrested, and the gun proves to be a BB gun", "headline": "Robot dog checks armed man on Hollywood bus; standoff ends in arrest" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "60b68178677d3993985f56f004eb346c79bb0003c8a8d5bd6b296ca89336d3d1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Just before 4 a.m. on 8 November 2023, a passenger on a Metro bus in Hollywood reported an armed man aboard. The bus was at Melrose and Western avenues. The driver pulled over and evacuated the other passengers. Officers got no response from the man, and a two-hour standoff followed (Los Angeles Times via Police1, 9 November 2023). The LAPD sent in its Boston Dynamics Spot quadruped. Its camera confirmed the man was asleep with a gun (Police1). The LAPD's quarterly report to the Police Commission says the robot was a barrier between suspect and firearm (NBC Los Angeles, 8 March 2024). The man woke, left the bus and was taken into custody about 6:40 a.m. The weapon was a BB gun (Police1). Deputy Chief David Kowalski approves each use. The robot cost nearly $300,000 (NBC). International Business Times' October 2024 account says the robot removed the gun.", "replication": { "produced_by": [ "An armed or apparently armed person unresponsive in a confined space that officers cannot safely approach", "A tactical unit with a camera-and-arm ground robot on call and a deputy chief's approval for each use" ], "must_hold": [ "Officers position the robot and watch its camera before any approach rather than acting on its own motion", "Each deployment is approved in advance and reported to the Police Commission and City Council" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0183", "title": "Nearly a third of French tax controls now come from mass-data risk analysis, with efficacy hard to measure", "summary": "The Cour des comptes (November 2023) found that nearly a third of DGFiP tax controls rest on mass-data risk analyzes (target 50% by 2027); a July 2026 parliamentary exchange put data mining at 44% ...", "date_observed": "2023-11-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Cour des comptes published its report “La détection de la fraude fiscale des particuliers” on 15 November 2023. It says nearly a third of tax controls now rest on risk analyses fed by mass data processing. The administration aims at 50% by 2027. Their efficacy remains difficult to measure. Mass data cross-matching may assist controls but can never automatically characterize fraud. The “foncier innovant” scheme illustrates the growing use of artificial intelligence. It gives 14.6 billion euro of droits et pénalités from controls in 2022, slightly more than a third on individuals. It attributes no share to data mining. It gives a 55% recovery rate that has barely improved since 2018. La Revue du Digital (22 July 2026) reported a divergence at the parliamentary finance commission on 21 July. LFI rapporteur Mathilde Feld said that data-mining controls were 44% of Direction générale des Finances publiques (DGFiP) controls in 2023. She said they produced less than 14% of droits et pénalités, less than a seventh of the total. DGFiP Director General Amélie Verdier defended data mining as an efficient and far less staff-intensive way to detect declarative inconsistencies.", "category": "general benefit", "unexpected": false, "purpose": "Target tax audits by cross-matching mass data to detect declarative inconsistencies.", "system": "DGFiP data-mining targeting of tax controls (program name not given in the sources)", "model_version": null, "developer": "Direction générale des Finances publiques (DGFiP)", "deployer": "Direction générale des Finances publiques (DGFiP)", "location": null, "domain": "Tax compliance", "segment": "Audit targeting and fraud detection", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The benefit is a share of control programming, and the Cour judged efficacy hard to measure.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Sources give the share of controls programmed by data mining and a contested yield share, not an outcome attributable to the system." }, { "group": "societal", "depth": null, "reason": "No recovered amount is attributed to data mining by the Cour. 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It says nearly a third of tax controls now rest on risk analyses fed by mass data processing. The administration aims at 50% by 2027. Their efficacy remains difficult to measure. Mass data cross-matching may assist controls but can never automatically characterize fraud. The “foncier innovant” scheme illustrates the growing use of artificial intelligence. It gives 14.6 billion euro of droits et pénalités from controls in 2022, slightly more than a third on individuals. It attributes no share to data mining. It gives a 55% recovery rate that has barely improved since 2018. La Revue du Digital (22 July 2026) reported a divergence at the parliamentary finance commission on 21 July. LFI rapporteur Mathilde Feld said that data-mining controls were 44% of Direction générale des Finances publiques (DGFiP) controls in 2023. She said they produced less than 14% of droits et pénalités, less than a seventh of the total. DGFiP Director General Amélie Verdier defended data mining as an efficient and far less staff-intensive way to detect declarative inconsistencies." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DGFiP data-mining targeting of tax controls (program name not given in the sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Direction générale des Finances publiques (DGFiP)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Nearly a third of French tax controls now come from mass-data risk analysis, with efficacy hard to measure", "headline": "Nearly a third of DGFiP tax controls rest on mass-data analysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b75dc7ffc8ceee7143961fa75eace84bb40c179da09028d5272b98015ccd8f75" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Cour des comptes published its report “La détection de la fraude fiscale des particuliers” on 15 November 2023. It says nearly a third of tax controls now rest on risk analyses fed by mass data processing. The administration aims at 50% by 2027. Their efficacy remains difficult to measure. Mass data cross-matching may assist controls but can never automatically characterize fraud. The “foncier innovant” scheme illustrates the growing use of artificial intelligence. It gives 14.6 billion euro of droits et pénalités from controls in 2022, slightly more than a third on individuals. It attributes no share to data mining. It gives a 55% recovery rate that has barely improved since 2018. La Revue du Digital (22 July 2026) reported a divergence at the parliamentary finance commission on 21 July. LFI rapporteur Mathilde Feld said that data-mining controls were 44% of Direction générale des Finances publiques (DGFiP) controls in 2023. She said they produced less than 14% of droits et pénalités, less than a seventh of the total. DGFiP Director General Amélie Verdier defended data mining as an efficient and far less staff-intensive way to detect declarative inconsistencies.", "replication": { "produced_by": [ "Mass cross-matching of declarative and third-party data to program a growing share of controls" ], "must_hold": [ "The legal limit that cross-matching assists but never automatically characterizes fraud", "Audit staff capacity to convert targeting into droits et pénalités, which the 2026 debate questioned" ], "echoes": [ { "setting": "DGFiP activity for 2023 as cited at the finance commission (2023)", "outcome": "recurred", "source": "La Revue du Digital: 44% of controls from data mining, under 14% of droits et pénalités" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0179", "title": "Singapore's ScamShield flags about 5 million SMSes and blocks about 80,000 scam numbers by October 2023", "summary": "MHA told Parliament in November 2023 that ScamShield, built by Open Government Products with the NCPC and the Police, had about 750,000 downloads, about 80,000 numbers blacklisted and about 5 milli...", "date_observed": "2023-11-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "ScamShield is a Singapore government app by Open Government Products, a unit of GovTech. It was developed with the National Crime Prevention Council (NCPC) and the Singapore Police Force. GovInsider (June 2021) described an on-device machine-learning model that files suspected scam SMS into a junk folder. It also blocks calls from numbers on a police blocklist. It reported 722,865 SMS reported and 5,537 numbers blocked since launch, with a 95% detection accuracy claim. It quoted product manager Lennard Lim on the model's need to adapt as scammers change their attacks. Minister of State Sun Xueling gave an oral reply to parliamentary questions on 22 November 2023. She said ScamShield had about 750,000 downloads as of October 2023. About 80,000 unique scam-tainted phone numbers had been blacklisted and blocked. About 5 million SMSes had been flagged to users as potential scams. She said it has effectively protected users. She also cited about 180 million suspected scam calls blocked at network level in the first half of 2023. That is a telco measure separate from the app. No victim-level evaluation appears in the sources.", "category": "general benefit", "unexpected": false, "purpose": "Filter scam SMS on-device and block calls from police-blacklisted numbers to protect users from scams.", "system": "ScamShield app", "model_version": null, "developer": "Open Government Products (GovTech) with the National Crime Prevention Council and the Singapore Police Force", "deployer": "Singapore Police Force and National Crime Prevention Council", "location": "Singapore, Singapore", "domain": "Scam prevention", "segment": "Consumer scam calls and SMS", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Flagged-SMS and blocked-number counts are aggregates. No loss avoided by an identifiable user is documented." }, { "group": "societal", "depth": null, "reason": "No measured change in scam losses is attributed to the app in the sources." } ], "ai_role": { "status": "assessed", "statement": "GovInsider attributes SMS filtering to an on-device machine-learning model and call blocking to a police-maintained blocklist. So only the SMS figures involve the model. The parliamentary reply gives counts without attributing them to AI. Developer (Open Government Products, a public body) and deployer (the Police and NCPC) are both government bodies. The reply was given by their ministry." }, "evidence": [ { "kind": "report", "citation": "Ministry of Home Affairs, Singapore, oral reply by Ms Sun Xueling, Minister of State, to parliamentary questions, 22 November 2023", "title": "Oral Reply to Parliamentary Questions on Effectiveness of ScamShield in Preventing Scams", "url": "https://www.mha.gov.sg/media-room/newsroom/oral-reply-to-pq-on-effectiveness-of-scamshield-in-preventing-scams/", "date": "2023-11-22", "written_by": "deployer", "quote": "ScamShield has been effective in protecting users from scam calls and SMSes" }, { "kind": "news report", "citation": "Shirley Tay, GovInsider, June 2021 (date from Google News RSS)", "title": "Meet Singapore's latest weapon against scams", "url": "https://govinsider.asia/intl-en/article/meet-singapores-latest-weapon-against-scams-open-government-products-scamshield", "date": "2021-06-06", "written_by": "independent", "quote": "Meet Singapore's latest weapon against scams" }, { "kind": "other", "citation": "Ministry of Digital Development and Information (2026). Anti-scam efforts by MDDI. MDDI web page, last updated 18 August 2026.", "title": "Anti-scam efforts by MDDI", "url": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/", "date": "2026-08-18", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "On-device SMS classification combined with a police-maintained blocklist of scam numbers", "User reports feeding the blocklist (722,865 SMS reported by mid-2021)" ], "must_hold": [ "Adoption at scale (about 750,000 downloads by October 2023)", "Police intelligence to keep the blocklist current", "Model updates as scam wording changes" ], "echoes": [ { "date": "2021-06-06", "setting": "Singapore, first months after launch", "model_version": null, "outcome": "recurred", "source": "GovInsider: 5,537 numbers blocked, 722,865 SMS reported" }, { "date": "2026-02-02", "setting": "Straits Times forum letter on ScamShield's multi-layered approach", "model_version": null, "outcome": "unknown", "source": "Google News RSS headline only" } ] }, "paired_incident": null, "headline": "ScamShield flags about 5 million SMSes by October 2023", "metric": "about 5 million SMSes had been flagged to users as potential scams", "comparator": null, "later": { "status": "scaled", "date": "2026-08-18", "note": "MDDI's anti-scam page, updated 18 August 2026, says the enhanced ScamShield app launched in August 2024 grew its user base from 944,000 to 1.53 million.", "quote": "Since the launch of the enhanced ScamShield app in August 2024, the app’s user base has grown by 61.8%, from 944,000 to 1.53 million users.", "url": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/" }, "value": null, "developer_country": "Singapore", "deployer_country": "Singapore", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Open_Government_Products; https://en.wikipedia.org/wiki/Singapore_Police_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the deployer's report and the deployer's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0179", "catalog_version": "1.0.0", "source_fingerprint": "e18a9e6a97e4e84c7230cc2cedcf3c3d96e6cedbadbeead0db7ce282981d4728", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0179-source-0001", "AIBD-0179-source-0002", "AIBD-0179-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Open Government Products (GovTech) with the National Crime Prevention Council and the Singapore Police Force", "deployer": "Singapore Police Force and National Crime Prevention Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "GovInsider attributes SMS filtering to an on-device machine-learning model and call blocking to a police-maintained blocklist. So only the SMS figures involve the model. The parliamentary reply gives counts without attributing them to AI. Developer (Open Government Products, a public body) and deployer (the Police and NCPC) are both government bodies. The reply was given by their ministry." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "GovInsider attributes SMS filtering to an on-device machine-learning model and call blocking to a police-maintained blocklist. So only the SMS figures involve the model. The parliamentary reply gives counts without attributing them to AI. Developer (Open Government Products, a public body) and deployer (the Police and NCPC) are both government bodies. The reply was given by their ministry." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the deployer's report and the deployer's other. 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{ "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "about 5 million SMSes had been flagged to users as potential scams", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-08-18", "note": "MDDI's anti-scam page, updated 18 August 2026, says the enhanced ScamShield app launched in August 2024 grew its user base from 944,000 to 1.53 million.", "quote": "Since the launch of the enhanced ScamShield app in August 2024, the app’s user base has grown by 61.8%, from 944,000 to 1.53 million users.", "url": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0179" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ScamShield is a Singapore government app by Open Government Products, a unit of GovTech. It was developed with the National Crime Prevention Council (NCPC) and the Singapore Police Force. GovInsider (June 2021) described an on-device machine-learning model that files suspected scam SMS into a junk folder. It also blocks calls from numbers on a police blocklist. It reported 722,865 SMS reported and 5,537 numbers blocked since launch, with a 95% detection accuracy claim. It quoted product manager Lennard Lim on the model's need to adapt as scammers change their attacks. Minister of State Sun Xueling gave an oral reply to parliamentary questions on 22 November 2023. She said ScamShield had about 750,000 downloads as of October 2023. About 80,000 unique scam-tainted phone numbers had been blacklisted and blocked. About 5 million SMSes had been flagged to users as potential scams. She said it has effectively protected users. She also cited about 180 million suspected scam calls blocked at network level in the first half of 2023. That is a telco measure separate from the app. No victim-level evaluation appears in the sources.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Flagged-SMS and blocked-number counts are aggregates. No loss avoided by an identifiable user is documented." }, { "group": "societal", "reason": "No measured change in scam losses is attributed to the app in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Filter scam SMS on-device and block calls from police-blacklisted numbers to protect users from scams." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Singapore, Singapore", "developer_country": "Singapore", "deployer_country": "Singapore" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Filter scam SMS on-device and block calls from police-blacklisted numbers to protect users from scams." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2023-11-22", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Open_Government_Products; https://en.wikipedia.org/wiki/Singapore_Police_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "On-device SMS classification combined with a police-maintained blocklist of scam numbers", "User reports feeding the blocklist (722,865 SMS reported by mid-2021)" ], "must_hold": [ "Adoption at scale (about 750,000 downloads by October 2023)", "Police intelligence to keep the blocklist current", "Model updates as scam wording changes" ], "echoes": [ { "date": "2021-06-06", "setting": "Singapore, first months after launch", "outcome": "recurred", "source": "GovInsider: 5,537 numbers blocked, 722,865 SMS reported" }, { "date": "2026-02-02", "setting": "Straits Times forum letter on ScamShield's multi-layered approach", "outcome": "unknown", "source": "Google News RSS headline only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "On-device SMS classification combined with a police-maintained blocklist of scam numbers", "User reports feeding the blocklist (722,865 SMS reported by mid-2021)" ], "must_hold": [ "Adoption at scale (about 750,000 downloads by October 2023)", "Police intelligence to keep the blocklist current", "Model updates as scam wording changes" ], "echoes": [ { "date": "2021-06-06", "setting": "Singapore, first months after launch", "outcome": "recurred", "source": "GovInsider: 5,537 numbers blocked, 722,865 SMS reported" }, { "date": "2026-02-02", "setting": "Straits Times forum letter on ScamShield's multi-layered approach", "outcome": "unknown", "source": "Google News RSS headline only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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https://en.wikipedia.org/wiki/Singapore_Police_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Scam prevention", "segment": "Consumer scam calls and SMS" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Ministry of Home Affairs, Singapore, oral reply by Ms Sun Xueling, Minister of State, to parliamentary questions, 22 November 2023", "title": "Oral Reply to Parliamentary Questions on Effectiveness of ScamShield in Preventing Scams", "url": "https://www.mha.gov.sg/media-room/newsroom/oral-reply-to-pq-on-effectiveness-of-scamshield-in-preventing-scams/", "date": "2023-11-22", "written_by": "deployer", "quote": "ScamShield has been effective in protecting users from scam calls and SMSes" }, { "kind": "news report", "citation": "Shirley Tay, GovInsider, June 2021 (date from Google News RSS)", "title": "Meet Singapore's latest weapon against scams", "url": "https://govinsider.asia/intl-en/article/meet-singapores-latest-weapon-against-scams-open-government-products-scamshield", "date": "2021-06-06", "written_by": "independent", "quote": "Meet Singapore's latest weapon against scams" }, { "kind": "other", "citation": "Ministry of Digital Development and Information (2026). Anti-scam efforts by MDDI. MDDI web page, last updated 18 August 2026.", "title": "Anti-scam efforts by MDDI", "url": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/", "date": "2026-08-18", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0179-source-0001", "AIBD-0179-source-0002", "AIBD-0179-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Ministry of Home Affairs, Singapore, oral reply by Ms Sun Xueling, Minister of State, to parliamentary questions, 22 November 2023", "title": "Oral Reply to Parliamentary Questions on Effectiveness of ScamShield in Preventing Scams", "url": "https://www.mha.gov.sg/media-room/newsroom/oral-reply-to-pq-on-effectiveness-of-scamshield-in-preventing-scams/", "date": "2023-11-22", "written_by": "deployer", "quote": "ScamShield has been effective in protecting users from scam calls and SMSes" }, { "kind": "news report", "citation": "Shirley Tay, GovInsider, June 2021 (date from Google News RSS)", "title": "Meet Singapore's latest weapon against scams", "url": "https://govinsider.asia/intl-en/article/meet-singapores-latest-weapon-against-scams-open-government-products-scamshield", "date": "2021-06-06", "written_by": "independent", "quote": "Meet Singapore's latest weapon against scams" }, { "kind": "other", "citation": "Ministry of Digital Development and Information (2026). Anti-scam efforts by MDDI. MDDI web page, last updated 18 August 2026.", "title": "Anti-scam efforts by MDDI", "url": "https://www.mddi.gov.sg/other-pages/anti-scam-efforts/", "date": "2026-08-18", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "MHA told Parliament in November 2023 that ScamShield, built by Open Government Products with the NCPC and the Police, had about 750,000 downloads, about 80,000 numbers blacklisted and about 5 milli...", "account": "ScamShield is a Singapore government app by Open Government Products, a unit of GovTech. It was developed with the National Crime Prevention Council (NCPC) and the Singapore Police Force. GovInsider (June 2021) described an on-device machine-learning model that files suspected scam SMS into a junk folder. It also blocks calls from numbers on a police blocklist. It reported 722,865 SMS reported and 5,537 numbers blocked since launch, with a 95% detection accuracy claim. It quoted product manager Lennard Lim on the model's need to adapt as scammers change their attacks. Minister of State Sun Xueling gave an oral reply to parliamentary questions on 22 November 2023. She said ScamShield had about 750,000 downloads as of October 2023. About 80,000 unique scam-tainted phone numbers had been blacklisted and blocked. About 5 million SMSes had been flagged to users as potential scams. She said it has effectively protected users. She also cited about 180 million suspected scam calls blocked at network level in the first half of 2023. That is a telco measure separate from the app. No victim-level evaluation appears in the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ScamShield app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Open Government Products (GovTech) with the National Crime Prevention Council and the Singapore Police Force" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Singapore's ScamShield flags about 5 million SMSes and blocks about 80,000 scam numbers by October 2023", "headline": "ScamShield flags about 5 million SMSes by October 2023" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e18a9e6a97e4e84c7230cc2cedcf3c3d96e6cedbadbeead0db7ce282981d4728" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ScamShield is a Singapore government app by Open Government Products, a unit of GovTech. It was developed with the National Crime Prevention Council (NCPC) and the Singapore Police Force. GovInsider (June 2021) described an on-device machine-learning model that files suspected scam SMS into a junk folder. It also blocks calls from numbers on a police blocklist. It reported 722,865 SMS reported and 5,537 numbers blocked since launch, with a 95% detection accuracy claim. It quoted product manager Lennard Lim on the model's need to adapt as scammers change their attacks. Minister of State Sun Xueling gave an oral reply to parliamentary questions on 22 November 2023. She said ScamShield had about 750,000 downloads as of October 2023. About 80,000 unique scam-tainted phone numbers had been blacklisted and blocked. About 5 million SMSes had been flagged to users as potential scams. She said it has effectively protected users. She also cited about 180 million suspected scam calls blocked at network level in the first half of 2023. That is a telco measure separate from the app. No victim-level evaluation appears in the sources.", "replication": { "produced_by": [ "On-device SMS classification combined with a police-maintained blocklist of scam numbers", "User reports feeding the blocklist (722,865 SMS reported by mid-2021)" ], "must_hold": [ "Adoption at scale (about 750,000 downloads by October 2023)", "Police intelligence to keep the blocklist current", "Model updates as scam wording changes" ], "echoes": [ { "date": "2021-06-06", "setting": "Singapore, first months after launch", "outcome": "recurred", "source": "GovInsider: 5,537 numbers blocked, 722,865 SMS reported" }, { "date": "2026-02-02", "setting": "Straits Times forum letter on ScamShield's multi-layered approach", "outcome": "unknown", "source": "Google News RSS headline only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0122", "title": "CBP machine-learning flag at San Ysidro leads to 75 kg narcotics seizure and arrest (2023)", "summary": "CBP ML model flagged a car's crossing history at San Ysidro in 2023; review found 75 kg of narcotics and the driver was arrested.", "date_observed": "2023-11-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In 2023 a car driving north from Mexico approached the Point of Entry at San Ysidro. A U.S. Customs and Border Protection (CBP) machine-learning model identified a suspicious pattern in its border-crossing history and flagged it for review. The review found 75 kilograms of narcotics hidden in the vehicle and led to the driver's arrest (DHS AI page, 27 November 2023). At the Axios AI+ Summit on 28 November 2023 Secretary Alejandro Mayorkas described a matching case. The Office of Field Operations model flagged a “truck” in 1.4 seconds that held about 75 kilograms of narcotics. DHS's 2024 AI Roadmap repeats it: a secondary-review flag yielding over 75 kg of drugs. No source names the drug or the seizure date.", "category": "harm prevented", "unexpected": false, "purpose": "CBP's model was built to identify potentially suspicious patterns in vehicle border-crossing histories (DHS AI Roadmap 2024). It flags vehicles for secondary review at ports of entry. The San Ysidro seizure was that use, not a side effect.", "system": "U.S. Customs and Border Protection (Office of Field Operations) machine-learning model that scores vehicle border-crossing histories for suspicious patterns; not named in any source", "model_version": null, "developer": null, "deployer": "U.S. Customs and Border Protection, Office of Field Operations (U.S. Department of Homeland Security)", "location": "San Ysidro, United States", "domain": "Border security and law enforcement", "segment": "Narcotics interdiction at a land port of entry", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2023-11-28-9430" }, "ratings": [ { "group": "societal", "depth": 3, "reason": "DHS states that 75 kilograms of narcotics hidden in the car were found and the driver arrested. That load did not reach U.S. streets. The drug is not named in any source, so a life-saving claim is not supported." }, { "group": "organizational", "depth": 2, "reason": "CBP's Office of Field Operations obtained a seizure and an arrest from a flag that Mayorkas said took 1.4 seconds. DHS leads both its AI page and its 2024 AI Roadmap with the case as its example of AI in use." } ], "ai_role": { "status": "assessed", "statement": "The model's contribution was the referral. DHS says it identified a suspicious pattern in the car's border-crossing history and flagged it for review. Mayorkas said the anomaly was identified in 1.4 seconds. The discovery of the narcotics and the arrest were done by officers in secondary review. No source states whether the car would have been referred without the flag. The model's counterfactual contribution is thus asserted by DHS, not demonstrated. The Monitor entry also bundles Mayorkas's claim that AI age-progression imagery has recovered abducted children. That claim names no case, date, or child." }, "evidence": [ { "kind": "press release", "citation": "U.S. Department of Homeland Security (2023). Artificial Intelligence at DHS. dhs.gov (page last updated 27 November 2023; archived 1 December 2023 at web.archive.org/web/20231201224758/https://www.dhs.gov/ai).", "title": "Artificial Intelligence at DHS", "url": "https://www.dhs.gov/ai", "date": "2023-11-27", "written_by": "deployer", "quote": "flagged it for further review, which revealed 75 kilograms of narcotics hidden in the vehicle and led to the arrest of the driver" }, { "kind": "news report", "citation": "Giaritelli, A. (2023). Mayorkas: DHS using AI to catch fentanyl at border, track down kidnapped children. Washington Examiner.", "title": "Mayorkas: DHS using AI to catch fentanyl at border, track down kidnapped children", "url": "https://www.washingtonexaminer.com/policy/technology/mayorkas-dhs-ai-fentanyl-border-kidnapped-children", "date": "2023-11-28", "written_by": "independent", "quote": "in 1.4 seconds, we identified an anomaly of a particular truck that ended up having about 75 kilograms of narcotics in it" }, { "kind": "news report", "citation": "Kelley, A. (2023). DHS aims to lead in defense against 'adversarial' AI. Nextgov/FCW.", "title": "DHS aims to lead in defense against 'adversarial' AI", "url": "https://www.nextgov.com/artificial-intelligence/2023/11/dhs-aims-lead-defense-against-adversarial-ai/392321/", "date": "2023-11-28", "written_by": "independent", "quote": "AI systems are currently aiding DHS operations in border patrol efforts and combating drug trafficking and creating age progression estimations of missing children" }, { "kind": "report", "citation": "U.S. Department of Homeland Security (2024). Artificial Intelligence Roadmap 2024. dhs.gov (PDF).", "title": "Department of Homeland Security Artificial Intelligence Roadmap 2024", "url": "https://www.dhs.gov/sites/default/files/2024-03/24_0315_ocio_roadmap_artificialintelligence-ciov3-signed-508.pdf", "date": null, "written_by": "deployer", "quote": "CBP recently used the model to flag a car for secondary review, which yielded the discovery of over 75 kgs of drugs hidden in the automobile" } ], "replication": { "produced_by": [ "A CBP machine-learning model scoring vehicle border-crossing histories was running on traffic at the San Ysidro Point of Entry", "The model's flag reached officers in time to send the car to further (secondary) review before it left the port", "Officers physically searched the car, found the 75 kilograms of narcotics and arrested the driver" ], "must_hold": [ "The crossing-history pattern the model keys on must actually distinguish smuggling loads. No source gives hit rates or false-positive rates", "Officers must have the discretion and capacity to act on a flag within normal crossing processing", "The seizure is documented only by DHS and the Secretary. An independent CBP release or court filing giving the date, drug and quantity has not been found" ], "echoes": [] }, "paired_incident": null, "headline": "CBP machine-learning flag at San Ysidro finds 75 kg of narcotics", "metric": "review found 75 kg of narcotics and the driver was arrested", "comparator": null, "later": { "status": "unknown", "date": null, "note": "DHS's March 2024 AI Roadmap restates the same seizure as an example; no later development, seizure date or drug type was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-11-28-9430", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/U.S._Customs_and_Border_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the deployer's report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0122", "catalog_version": "1.0.0", "source_fingerprint": "b3d5594ab9851e2a212fa5733953fb908641fb42e802ba3b5b44a1e8bb9fce8f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0122-source-0001", "AIBD-0122-source-0002", "AIBD-0122-source-0003", "AIBD-0122-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "U.S. Customs and Border Protection, Office of Field Operations (U.S. Department of Homeland Security)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model's contribution was the referral. DHS says it identified a suspicious pattern in the car's border-crossing history and flagged it for review. Mayorkas said the anomaly was identified in 1.4 seconds. The discovery of the narcotics and the arrest were done by officers in secondary review. No source states whether the car would have been referred without the flag. The model's counterfactual contribution is thus asserted by DHS, not demonstrated. The Monitor entry also bundles Mayorkas's claim that AI age-progression imagery has recovered abducted children. That claim names no case, date, or child." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The model's contribution was the referral. DHS says it identified a suspicious pattern in the car's border-crossing history and flagged it for review. Mayorkas said the anomaly was identified in 1.4 seconds. The discovery of the narcotics and the arrest were done by officers in secondary review. No source states whether the car would have been referred without the flag. The model's counterfactual contribution is thus asserted by DHS, not demonstrated. The Monitor entry also bundles Mayorkas's claim that AI age-progression imagery has recovered abducted children. That claim names no case, date, or child." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "DHS states that 75 kilograms of narcotics hidden in the car were found and the driver arrested. That load did not reach U.S. streets. The drug is not named in any source, so a life-saving claim is not supported." }, { "group": "organizational", "depth": 2, "reason": "CBP's Office of Field Operations obtained a seizure and an arrest from a flag that Mayorkas said took 1.4 seconds. DHS leads both its AI page and its 2024 AI Roadmap with the case as its example of AI in use." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, the deployer's report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "DHS states that 75 kilograms of narcotics hidden in the car were found and the driver arrested. That load did not reach U.S. streets. The drug is not named in any source, so a life-saving claim is not supported." }, { "group": "organizational", "depth": 2, "reason": "CBP's Office of Field Operations obtained a seizure and an arrest from a flag that Mayorkas said took 1.4 seconds. DHS leads both its AI page and its 2024 AI Roadmap with the case as its example of AI in use." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 3, "reason": "DHS states that 75 kilograms of narcotics hidden in the car were found and the driver arrested. That load did not reach U.S. streets. The drug is not named in any source, so a life-saving claim is not supported." }, { "group": "organizational", "depth": 2, "reason": "CBP's Office of Field Operations obtained a seizure and an arrest from a flag that Mayorkas said took 1.4 seconds. DHS leads both its AI page and its 2024 AI Roadmap with the case as its example of AI in use." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "review found 75 kg of narcotics and the driver was arrested", "editor_note": "" 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DHS leads both its AI page and its 2024 AI Roadmap with the case as its example of AI in use." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "CBP's model was built to identify potentially suspicious patterns in vehicle border-crossing histories (DHS AI Roadmap 2024). It flags vehicles for secondary review at ports of entry. 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No source gives hit rates or false-positive rates", "Officers must have the discretion and capacity to act on a flag within normal crossing processing", "The seizure is documented only by DHS and the Secretary. An independent CBP release or court filing giving the date, drug and quantity has not been found" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2023-11-28-9430", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/U.S._Customs_and_Border_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Border security and law enforcement", "segment": "Narcotics interdiction at a land port of entry" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Department of Homeland Security (2023). Artificial Intelligence at DHS. dhs.gov (page last updated 27 November 2023; archived 1 December 2023 at web.archive.org/web/20231201224758/https://www.dhs.gov/ai).", "title": "Artificial Intelligence at DHS", "url": "https://www.dhs.gov/ai", "date": "2023-11-27", "written_by": "deployer", "quote": "flagged it for further review, which revealed 75 kilograms of narcotics hidden in the vehicle and led to the arrest of the driver" }, { "kind": "news report", "citation": "Giaritelli, A. (2023). Mayorkas: DHS using AI to catch fentanyl at border, track down kidnapped children. Washington Examiner.", "title": "Mayorkas: DHS using AI to catch fentanyl at border, track down kidnapped children", "url": "https://www.washingtonexaminer.com/policy/technology/mayorkas-dhs-ai-fentanyl-border-kidnapped-children", "date": "2023-11-28", "written_by": "independent", "quote": "in 1.4 seconds, we identified an anomaly of a particular truck that ended up having about 75 kilograms of narcotics in it" }, { "kind": "news report", "citation": "Kelley, A. (2023). DHS aims to lead in defense against 'adversarial' AI. Nextgov/FCW.", "title": "DHS aims to lead in defense against 'adversarial' AI", "url": "https://www.nextgov.com/artificial-intelligence/2023/11/dhs-aims-lead-defense-against-adversarial-ai/392321/", "date": "2023-11-28", "written_by": "independent", "quote": "AI systems are currently aiding DHS operations in border patrol efforts and combating drug trafficking and creating age progression estimations of missing children" }, { "kind": "report", "citation": "U.S. Department of Homeland Security (2024). Artificial Intelligence Roadmap 2024. dhs.gov (PDF).", "title": "Department of Homeland Security Artificial Intelligence Roadmap 2024", "url": "https://www.dhs.gov/sites/default/files/2024-03/24_0315_ocio_roadmap_artificialintelligence-ciov3-signed-508.pdf", "written_by": "deployer", "quote": "CBP recently used the model to flag a car for secondary review, which yielded the discovery of over 75 kgs of drugs hidden in the automobile" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0122-source-0001", "AIBD-0122-source-0002", "AIBD-0122-source-0003", "AIBD-0122-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Department of Homeland Security (2023). 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Washington Examiner.", "title": "Mayorkas: DHS using AI to catch fentanyl at border, track down kidnapped children", "url": "https://www.washingtonexaminer.com/policy/technology/mayorkas-dhs-ai-fentanyl-border-kidnapped-children", "date": "2023-11-28", "written_by": "independent", "quote": "in 1.4 seconds, we identified an anomaly of a particular truck that ended up having about 75 kilograms of narcotics in it" }, { "kind": "news report", "citation": "Kelley, A. (2023). DHS aims to lead in defense against 'adversarial' AI. Nextgov/FCW.", "title": "DHS aims to lead in defense against 'adversarial' AI", "url": "https://www.nextgov.com/artificial-intelligence/2023/11/dhs-aims-lead-defense-against-adversarial-ai/392321/", "date": "2023-11-28", "written_by": "independent", "quote": "AI systems are currently aiding DHS operations in border patrol efforts and combating drug trafficking and creating age progression estimations of missing children" }, { "kind": "report", "citation": "U.S. Department of Homeland Security (2024). Artificial Intelligence Roadmap 2024. dhs.gov (PDF).", "title": "Department of Homeland Security Artificial Intelligence Roadmap 2024", "url": "https://www.dhs.gov/sites/default/files/2024-03/24_0315_ocio_roadmap_artificialintelligence-ciov3-signed-508.pdf", "written_by": "deployer", "quote": "CBP recently used the model to flag a car for secondary review, which yielded the discovery of over 75 kgs of drugs hidden in the automobile" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CBP ML model flagged a car's crossing history at San Ysidro in 2023; review found 75 kg of narcotics and the driver was arrested.", "account": "In 2023 a car driving north from Mexico approached the Point of Entry at San Ysidro. A U.S. Customs and Border Protection (CBP) machine-learning model identified a suspicious pattern in its border-crossing history and flagged it for review. The review found 75 kilograms of narcotics hidden in the vehicle and led to the driver's arrest (DHS AI page, 27 November 2023). At the Axios AI+ Summit on 28 November 2023 Secretary Alejandro Mayorkas described a matching case. The Office of Field Operations model flagged a “truck” in 1.4 seconds that held about 75 kilograms of narcotics. DHS's 2024 AI Roadmap repeats it: a secondary-review flag yielding over 75 kg of drugs. No source names the drug or the seizure date." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "U.S. Customs and Border Protection (Office of Field Operations) machine-learning model that scores vehicle border-crossing histories for suspicious patterns; not named in any source" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CBP machine-learning flag at San Ysidro leads to 75 kg narcotics seizure and arrest (2023)", "headline": "CBP machine-learning flag at San Ysidro finds 75 kg of narcotics" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b3d5594ab9851e2a212fa5733953fb908641fb42e802ba3b5b44a1e8bb9fce8f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In 2023 a car driving north from Mexico approached the Point of Entry at San Ysidro. A U.S. Customs and Border Protection (CBP) machine-learning model identified a suspicious pattern in its border-crossing history and flagged it for review. The review found 75 kilograms of narcotics hidden in the vehicle and led to the driver's arrest (DHS AI page, 27 November 2023). At the Axios AI+ Summit on 28 November 2023 Secretary Alejandro Mayorkas described a matching case. The Office of Field Operations model flagged a “truck” in 1.4 seconds that held about 75 kilograms of narcotics. DHS's 2024 AI Roadmap repeats it: a secondary-review flag yielding over 75 kg of drugs. No source names the drug or the seizure date.", "replication": { "produced_by": [ "A CBP machine-learning model scoring vehicle border-crossing histories was running on traffic at the San Ysidro Point of Entry", "The model's flag reached officers in time to send the car to further (secondary) review before it left the port", "Officers physically searched the car, found the 75 kilograms of narcotics and arrested the driver" ], "must_hold": [ "The crossing-history pattern the model keys on must actually distinguish smuggling loads. No source gives hit rates or false-positive rates", "Officers must have the discretion and capacity to act on a flag within normal crossing processing", "The seizure is documented only by DHS and the Secretary. An independent CBP release or court filing giving the date, drug and quantity has not been found" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0261", "title": "GNoME predicts 2.2 million crystal structures, of which few may be useful new compounds", "summary": "Google DeepMind's GNoME proposed 2.2 million crystal structures (380,000 stable); independent reviews (Cheetham & Seshadri 2024, Kurlin 2026) find duplicates and scant evidence of useful compounds.", "date_observed": "2023-11-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 29 November 2023 Google DeepMind published GNoME in Nature. It reported 2.2 million structures below the convex hull, calling it “an order-of-magnitude expansion in stable materials known to humanity”. It stated that 736 of the stable structures had already been independently realized. The company blog adds that the Berkeley Lab A-Lab synthesized more than 41 materials from the predictions. Cheetham and Seshadri (UC Santa Barbara, Chem. Mater., 8 April 2024) examined the listings. They reported “scant evidence for compounds that fulfill the trifecta of novelty, credibility, and utility”. 404 Media (11 April 2024) quoted Cheetham that the paper “falls way short” as a practical contribution and DeepMind that it stands by all claims. C&EN (15 October 2026) reported an arXiv analysis by Vitaliy Kurlin (Liverpool). It found more than 15% near-duplicates within GNoME, about 24% duplicating Materials Project entries and about 17% close to ICSD entries. Leslie Schoop (Princeton) called some entries “completely unrealistic”. The Chem. Mater. critique itself was not available. Its abstract on Europe PMC (PMC11044265) is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Predict stable inorganic crystal structures at scale to accelerate materials discovery", "system": "GNoME (Graph Networks for Materials Exploration)", "model_version": null, "developer": "DeepMind", "deployer": "DeepMind (dataset released openly; stable structures contributed to the Materials Project)", "location": "Mountain View, California, USA", "domain": "Materials science", "segment": "Materials researchers", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "Independent reviewers dispute the novelty and utility of the predicted structures.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary. A dataset release." }, { "group": "organizational", "depth": null, "reason": "Use by the Materials Project and A-Lab is reported only by the vendor. 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Human Researchers Say...", "url": "https://www.404media.co/google-says-it-discovered-millions-of-new-materials-with-ai-human-researchers/", "date": "2024-04-11", "written_by": "independent", "quote": "the Google paper falls way short in terms of it being a useful, practical contribution to the experimental materials scientists." }, { "kind": "news report", "citation": "Chemical & Engineering News, 15 Oct 2026", "title": "Google DeepMind AI crystallography database includes near duplicate structures and unrealistic compounds", "url": "https://cen.acs.org/research-integrity/Google-DeepMind-structures-near-duplicates-questionable/104/web/2026/10", "date": "2026-10-15", "written_by": "independent", "quote": "My biggest problem with GNoME is that there are materials in there that are completely unrealistic." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0261-source-0001", "AIBD-0261-source-0002", "AIBD-0261-source-0003", "AIBD-0261-source-0004", "AIBD-0261-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Merchant A, Batzner S, Schoenholz SS, Aykol M, Cheon G, Cubuk ED. 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It reported 2.2 million structures below the convex hull, calling it “an order-of-magnitude expansion in stable materials known to humanity”. It stated that 736 of the stable structures had already been independently realized. The company blog adds that the Berkeley Lab A-Lab synthesized more than 41 materials from the predictions. Cheetham and Seshadri (UC Santa Barbara, Chem. Mater., 8 April 2024) examined the listings. They reported “scant evidence for compounds that fulfill the trifecta of novelty, credibility, and utility”. 404 Media (11 April 2024) quoted Cheetham that the paper “falls way short” as a practical contribution and DeepMind that it stands by all claims. C&EN (15 October 2026) reported an arXiv analysis by Vitaliy Kurlin (Liverpool). It found more than 15% near-duplicates within GNoME, about 24% duplicating Materials Project entries and about 17% close to ICSD entries. Leslie Schoop (Princeton) called some entries “completely unrealistic”. The Chem. 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Its abstract on Europe PMC (PMC11044265) is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "GNoME (Graph Networks for Materials Exploration)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GNoME predicts 2.2 million crystal structures, of which few may be useful new compounds", "headline": "GNoME's 2.2 million predicted crystals may include useful compounds" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4b33996fd343295677781a9abca4c40244fce51cc5014c72c542405c1573fc90" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 29 November 2023 Google DeepMind published GNoME in Nature. It reported 2.2 million structures below the convex hull, calling it “an order-of-magnitude expansion in stable materials known to humanity”. It stated that 736 of the stable structures had already been independently realized. The company blog adds that the Berkeley Lab A-Lab synthesized more than 41 materials from the predictions. Cheetham and Seshadri (UC Santa Barbara, Chem. Mater., 8 April 2024) examined the listings. They reported “scant evidence for compounds that fulfill the trifecta of novelty, credibility, and utility”. 404 Media (11 April 2024) quoted Cheetham that the paper “falls way short” as a practical contribution and DeepMind that it stands by all claims. C&EN (15 October 2026) reported an arXiv analysis by Vitaliy Kurlin (Liverpool). It found more than 15% near-duplicates within GNoME, about 24% duplicating Materials Project entries and about 17% close to ICSD entries. Leslie Schoop (Princeton) called some entries “completely unrealistic”. The Chem. 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Its abstract on Europe PMC (PMC11044265) is among the sources.", "replication": { "produced_by": [ "Graph neural network trained on existing crystal databases with iterative active learning", "High-throughput DFT stability checks of candidates", "Open release of the predicted structures" ], "must_hold": [ "Predicted structures are genuinely novel rather than near-duplicates of known entries", "Predicted compounds are synthesizable and have useful properties", "Independent experimental confirmation of utility" ], "echoes": [ { "date": "2024-04-08", "setting": "Independent review of GNoME listings by Cheetham and Seshadri (UC Santa Barbara)", "outcome": "did not recur", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11044265/" }, { "date": "2026-10-09", "setting": "Kurlin et al. arXiv analysis of the November 2024 GNoME update, reported by C&EN", "model_version": "GNoME dataset update, Nov 2024", "outcome": "did not recur", "source": "https://cen.acs.org/research-integrity/Google-DeepMind-structures-near-duplicates-questionable/104/web/2026/10" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0227", "title": "ZeroEyes detection at Hobbs' Del Norte Pool lot leads police to people firing at clays near a street; one charged", "summary": "On 30 November 2023 ZeroEyes alerted Hobbs police to a gun on a camera at Del Norte Pool's lot; officers detained people shooting clays near a street and charged one, per the police chief.", "date_observed": "2023-11-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Odessa American (reproduced by GovTech) reports, from a ZeroEyes news release, on an alert at 6:35 p.m. MDT on 30 November 2023. ZeroEyes alerted the Hobbs Police Department and the Eagle I.C. dispatch center. A gun had been detected on a security camera in Del Norte Pool's parking lot. Those involved were shooting sporting clays close to North Grimes Street. Responding officers detained them and charges were filed against one. Hobbs Police Chief August Fons is quoted saying detection and rapid human verification helped stop the activity before anyone was hurt. Lubbock Lights later reported ZeroEyes co-founder Sam Alaimo showing images from the incident. He said it resulted in an arrest with no one hurt and listed the City of Hobbs and its school system among local clients. No court record is among the sources.", "category": "protective response", "unexpected": false, "purpose": "Detect visible firearms in existing security-camera feeds, verify with human analysts and alert police within seconds to reduce response times to potential shootings.", "system": "ZeroEyes AI gun detection", "model_version": null, "developer": "ZeroEyes", "deployer": "City of Hobbs / Hobbs Police Department", "location": "Hobbs, United States", "domain": "Public safety / weapons detection", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "Unlawful shooting near a public street was interrupted and a charge filed, per the police chief as quoted in the vendor release." }, { "group": "personal", "depth": null, "reason": "No individual beneficiary or averted injury is documented." } ], "ai_role": { "status": "assessed", "statement": "The chain (AI detection, human verification, dispatch) is described only in ZeroEyes' release and the vendor's later interview. 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He “presented to our nephrological institution with a complex medical history”. It included “progressive hearing loss and amaurosis since shortly after birth”, dilated cardiomyopathy, chronic kidney disease and cirrhosis. The physicians “used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)”. A geneticist “within just two business days confirmed that the patient actually possesses two distinct mutations in ALMS1”. Further tests then characterized hypogonadism and metabolic findings consistent with the syndrome. The consultation date is not stated.", "category": "benefit created", "unexpected": true, "purpose": "ChatGPT is a general-purpose conversational assistant. Generating candidate genes for a rare multisystem disease is not a function it was built for. This benefit was not its designed purpose.", "system": "ChatGPT", "model_version": "ChatGPT (Sep 14 version), as cited by the authors", "developer": "OpenAI", "deployer": "Medical University of Vienna, Division of Nephrology and Dialysis", "location": "Vienna, Austria", "domain": "Healthcare / nephrology and clinical genetics", "segment": "Rare disease diagnosis", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "A unifying genetic diagnosis at 44 for symptoms present since infancy, enabling targeted follow-up. No curative treatment is reported, so material rather than life-saving." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT proposed ALMS1 among candidate genes from a physician-written history. The clinicians framed the query and ordered targeted genetic testing, which made the diagnosis." }, "evidence": [ { "kind": "case report", "citation": "Haller F, Autherith M, Lehner R, Schmidt A, Sunder-Plassmann G (2023). Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases. Clinical Kidney Journal (letter; PMC10783252).", "title": "Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/", "date": "2023-12-08", "written_by": "deployer", "quote": "we used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)" } ], "replication": { "produced_by": [ "A structured multisystem history entered by physicians", "Rapid access to targeted genetic testing", "Clinicians willing to test an AI-generated hypothesis" ], "must_hold": [ "The AI's candidate list includes the true gene", "Confirmatory sequencing is available" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1281", "title": "Alleged Harmful Health Outcomes Following Reported Use of Purported ChatGPT-Generated Medical Advice in Hyderabad", "url": "https://incidentdatabase.ai/cite/1281", "severity": null, "group": "personal", "basis": "Same system and specialty: ChatGPT in nephrology; it proposed ALMS1 for a Vienna kidney patient, while in Hyderabad its advice led a kidney-transplant recipient to stop medication and suffer graft failure." }, "headline": "ChatGPT proposes ALMS1; Alström confirmed in two business days", "metric": "Alström syndrome confirmed in two days", "comparator": { "against": "untargeted analysis of the sequenced exome", "before": "the genetic analysis of the sequenced exome can take up to months", "after": "the suspected diagnosis of AS was confirmed within just two business days", "basis": "assumed", "quote": "After providing the geneticist with the information generated from ChatGPT, the suspected diagnosis of AS was confirmed within just two business days.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Austria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1281 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1281", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Medical_University_of_Vienna", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. 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facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Accessibility / visual assistance", "segment": "Blind and low-vision users (wearable reading assistant)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Castaldo J (26 Dec 2023, updated 27 Dec 2023). For some blind and low-vision people, AI glasses unlock a new independence. The Globe and Mail (named users Wes Ramage, Calgary; Nayla Farah, Toronto).", "title": "For some blind and low-vision people, AI glasses unlock a new independence", "url": "https://www.theglobeandmail.com/business/article-ai-smart-glasses-apps-vision/", "date": "2023-12-26", "written_by": "independent", "quote": "That brings a level of comfort I have not had in so many years." }, { "kind": "press release", "citation": "Envision. Envision Glasses product page (maker's page).", "title": "Envision Glasses", "url": "https://www.letsenvision.com/glasses", "written_by": "makers", "quote": "Lightweight glasses with a camera and direct speaker, Envision Glasses speak out text and environmental information." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0220-source-0001", "AIBD-0220-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Castaldo J (26 Dec 2023, updated 27 Dec 2023). For some blind and low-vision people, AI glasses unlock a new independence. The Globe and Mail (named users Wes Ramage, Calgary; Nayla Farah, Toronto).", "title": "For some blind and low-vision people, AI glasses unlock a new independence", "url": "https://www.theglobeandmail.com/business/article-ai-smart-glasses-apps-vision/", "date": "2023-12-26", "written_by": "independent", "quote": "That brings a level of comfort I have not had in so many years." }, { "kind": "press release", "citation": "Envision. Envision Glasses product page (maker's page).", "title": "Envision Glasses", "url": "https://www.letsenvision.com/glasses", "written_by": "makers", "quote": "Lightweight glasses with a camera and direct speaker, Envision Glasses speak out text and environmental information." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Globe and Mail, 26 December 2023: Wes Ramage of Calgary uses Envision Glasses (Google Glass plus Envision's AI) to read signs for transit, read menus, find chairs and objects and describe scenes.", "account": "In a Globe and Mail report of 26 December 2023, Joe Castaldo described how Wes Ramage of Calgary, who is blind, uses Envision Glasses. They are a Google Glass headset with Envision's AI software. He uses them to describe scenes, identify clothing colors, find empty chairs and misplaced objects, read street signs when navigating transit and read menus. Ramage said the glasses bring a level of comfort he had not had in many years. He described heading out each morning with his glasses, keys and wallet. The article gives a price of US$1,899 to US$3,499, accessed in his case through a provincial assistance program. It also profiles Nayla Farah of Toronto using the Be My AI app, covered by an existing record. Envision's product page says the glasses are built on Google Glass Enterprise Edition 2. They offer Instant Text, Scan Text, Describe Scene and an Ask Envision feature on an OpenAI model. It does not date the individual uses." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The glasses recognized text and described scenes aloud." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GPT-4 for the Ask Envision feature." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-4" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Envision Glasses: Google Glass Enterprise Edition 2 running Envision's text recognition, scene description and Ask Envision features" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Envision" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Envision Glasses read street signs, menus and scenes for Wes Ramage in Calgary, bringing comfort he had not had in years", "headline": "Envision Glasses read street signs and menus for Wes Ramage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0c21b15adc893137d2d87a7739594b7188ee7bc82ce998ecb5aa9655a04d5adf" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In a Globe and Mail report of 26 December 2023, Joe Castaldo described how Wes Ramage of Calgary, who is blind, uses Envision Glasses. They are a Google Glass headset with Envision's AI software. He uses them to describe scenes, identify clothing colors, find empty chairs and misplaced objects, read street signs when navigating transit and read menus. Ramage said the glasses bring a level of comfort he had not had in many years. He described heading out each morning with his glasses, keys and wallet. The article gives a price of US$1,899 to US$3,499, accessed in his case through a provincial assistance program. It also profiles Nayla Farah of Toronto using the Be My AI app, covered by an existing record. Envision's product page says the glasses are built on Google Glass Enterprise Edition 2. They offer Instant Text, Scan Text, Describe Scene and an Ask Envision feature on an OpenAI model. It does not date the individual uses.", "replication": { "produced_by": [ "A head-worn camera with on-device OCR and cloud scene description", "Funding through a provincial assistance program for a device priced at US$1,899 to US$3,499", "A user who learned the environment and routines with the device" ], "must_hold": [ "Affordability or subsidy for the hardware", "Legible text and adequate lighting for OCR", "Continued software support (the maker sells annual feature updates)" ], "echoes": [ { "date": "2023-12-26", "setting": "Toronto: Nayla Farah using the Be My AI smartphone app for photo and scene descriptions (same article)", "model_version": "GPT-4 (Be My AI, per the article's references to ChatGPT and GPT-4)", "outcome": "recurred", "source": "The Globe and Mail, 26 Dec 2023, https://www.theglobeandmail.com/business/article-ai-smart-glasses-apps-vision/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0036", "title": "Glider-borne automated whale-call classifier triggers a NOAA Right Whale Slow Zone east of Portland, Maine", "summary": "WHOI/NOAA glider's automated call classifier detected right whales on 27 December 2023; NOAA declared a Slow Zone east of Portland, ME.", "date_observed": "2023-12-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 27 December 2023 the Gulf of Maine Winter Slocum glider acoustically detected North Atlantic right whales east of Portland, Maine. Woods Hole Oceanographic Institution and NOAA's Northeast Fisheries Science Center operate it. Such gliders carry a DMON instrument running the Low-Frequency Detection and Classification System (LFDCS). It matches pitch-tracked calls against a call library using quadratic discriminant function analysis. Shore-based analysts validate detections. On 29 December 2023 NOAA Fisheries announced a voluntary Right Whale Slow Zone bounded by 43°49'N, 43°09'N, 67°02'W and 68°57'W. It ran 27 December 2023 through 11 January 2024. NOAA asked mariners to route around the area or transit at 10 knots or less.", "category": "protective response", "unexpected": false, "purpose": "LFDCS was built to detect and classify baleen whale calls in near real time for management use. The Slow Zone trigger was that purpose.", "system": "DMON instrument running the Low-Frequency Detection and Classification System (LFDCS) on a Slocum glider", "model_version": null, "developer": "Woods Hole Oceanographic Institution (Mark Baumgartner)", "deployer": "Woods Hole Oceanographic Institution and NOAA Northeast Fisheries Science Center; NOAA Fisheries issues Slow Zones", "location": "Gulf of Maine east of Portland, United States", "domain": "Marine conservation / shipping", "segment": "Endangered-species vessel-strike mitigation", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "A protective speed-reduction request for an endangered species over a defined area for about 15 days. No evidence that a strike was averted or that specific vessels complied." } ], "ai_role": { "status": "assessed", "statement": "Automated classification produced the candidate detections. Analysts validated them on shore before NOAA acted. The resulting Slow Zone is voluntary." }, "evidence": [ { "kind": "regulatory document", "citation": "NOAA Fisheries (29 Dec 2023). New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11. GovDelivery bulletin.", "title": "New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11", "url": "https://content.govdelivery.com/accounts/USNOAAFISHERIES/bulletins/3824b02", "date": "2023-12-29", "written_by": "deployer", "quote": "detected the presence of right whales east of Portland, ME" }, { "kind": "peer-reviewed study", "citation": "Indeck KL, Baumgartner MF, Lecavalier L, et al. (2025). Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales. Oceanography 38(Suppl. 1):13-21.", "title": "Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales", "url": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales", "date": null, "written_by": "makers", "quote": "154 Slow Zones have been triggered or extended by acoustic detections of NARWs, and 51 (33%) of those Slow Zones were triggered or extended by gliders" }, { "kind": "other", "citation": "Baumgartner M (WHOI). Low-Frequency Detection and Classification System (LFDCS) user manual (developer documentation).", "title": "Low-Frequency Detection and Classification System (LFDCS)", "url": "https://dcs.whoi.edu/lfdcs_manual/lfdcs_manual.html", "date": null, "written_by": "makers", "quote": "The call library can contain hundreds of these known call types, allowing the LFDCS to efficiently detect and classify many different calls produced by numerous species." }, { "kind": "report", "citation": "Wilder J, Davis G, DeAngelis A, Van Parijs S, Baumgartner M (2023). Low-Frequency Detection and Classification System (LFDCS) Reference Guide. NOAA Institutional Repository.", "title": "Low-Frequency Detection and Classification System (LFDCS) Reference Guide", "url": "https://repository.library.noaa.gov/view/noaa/48671", "date": null, "written_by": "makers", "quote": "a software system created for automated detection and classification of low-frequency baleen whale vocalizations in archival and real-time acoustic data" }, { "kind": "regulatory document", "citation": "NOAA Fisheries. Reducing Vessel Strikes to North Atlantic Right Whales (Slow Zones policy page).", "title": "Reducing Vessel Strikes to North Atlantic Right Whales", "url": "https://www.fisheries.noaa.gov/national/endangered-species-conservation/reducing-vessel-strikes-north-atlantic-right-whales", "date": null, "written_by": "deployer", "quote": "For a period of 15 days after a whale is detected, mariners are encouraged to avoid these areas" } ], "replication": { "produced_by": [ "Glider or buoy carrying DMON/LFDCS in right whale habitat", "Shore-based analyst validation protocol", "NOAA Slow Zone program (established late 2020) accepting acoustic triggers" ], "must_hold": [ "Whales vocalize within detection range", "Mariners comply voluntarily for any protective effect to materialize" ], "echoes": [ { "date": "2024-01-20", "setting": "Southeast US waters; first definite glider-based acoustic detection there, which triggered a Southeast Early Warning System alert for vessel strike mitigation", "model_version": null, "outcome": "recurred", "source": "Indeck et al. (2025) Oceanography, https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales" }, { "date": null, "setting": "US East Coast, four years of the Slow Zone program: 154 Slow Zones triggered or extended by acoustic detections, 51 by gliders", "model_version": null, "outcome": "recurred", "source": "Indeck et al. (2025) Oceanography" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "severity": null, "group": "societal", "basis": "Automated detection to protect an endangered species: the glider's whale-call classifier triggered a ship Slow Zone, while Ezemvelo KZN Wildlife's AI cameras failed to detect poachers and four rhinos were killed." }, "headline": "LFDCS glider detections trigger a NOAA Right Whale Slow Zone", "metric": "mariners route around the area or transit at 10 knots or less", "comparator": { "against": "aerial surveillance", "before": null, "after": "more slowdowns than aerial surveillance by a factor of two to five during fall and summer", "basis": "measured", "quote": "Gliders triggered more slowdowns than aerial surveillance by a factor of two to five during fall and summer but were less effective during spring, as whales migrating into the GoSL tend to call at lower rates and occur at lower densities than during other behavioral states (Parks et al., 2011; Matthews and Parks, 2021).", "url": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales" }, "later": { "status": "scaled", "date": "2025-01-21", "note": "By early 2025 gliders had triggered or extended 51 of the 154 acoustically triggered Slow Zones, and on 20 January 2024 a glider made the first definite glider-based acoustic detection in southeast US waters.", "quote": "In the four years since its inception, 154 Slow Zones have been triggered or extended by acoustic detections of NARWs, and 51 (33%) of those Slow Zones were triggered or extended by gliders operated by the Woods Hole Oceanographic Institution, Rutgers University, Stony Brook University, and The University of Maine during 57 separate glider missions.", "url": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales; https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Woods_Hole_Oceanographic_Institution; https://en.wikipedia.org/wiki/Woods_Hole_Oceanographic_Institution", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' report, the makers' other and two regulatory documents from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0036", "catalog_version": "1.0.0", "source_fingerprint": "181041b30300fced8151c056ec9a4d5c663517c4a7701680671af7c2eeb1c947", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0036-source-0001", "AIBD-0036-source-0002", "AIBD-0036-source-0003", "AIBD-0036-source-0004", "AIBD-0036-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Woods Hole Oceanographic Institution (Mark Baumgartner)", "deployer": "Woods Hole Oceanographic Institution and NOAA Northeast Fisheries Science Center; NOAA Fisheries issues Slow Zones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Automated classification produced the candidate detections. Analysts validated them on shore before NOAA acted. The resulting Slow Zone is voluntary." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Automated classification produced the candidate detections. Analysts validated them on shore before NOAA acted. The resulting Slow Zone is voluntary." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A protective speed-reduction request for an endangered species over a defined area for about 15 days. No evidence that a strike was averted or that specific vessels complied." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' peer-reviewed study, the makers' report, the makers' other and two regulatory documents from the deployer. 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Woods Hole Oceanographic Institution and NOAA's Northeast Fisheries Science Center operate it. Such gliders carry a DMON instrument running the Low-Frequency Detection and Classification System (LFDCS). It matches pitch-tracked calls against a call library using quadratic discriminant function analysis. Shore-based analysts validate detections. On 29 December 2023 NOAA Fisheries announced a voluntary Right Whale Slow Zone bounded by 43°49'N, 43°09'N, 67°02'W and 68°57'W. It ran 27 December 2023 through 11 January 2024. 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(2025) Oceanography, https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales" }, { "setting": "US East Coast, four years of the Slow Zone program: 154 Slow Zones triggered or extended by acoustic detections, 51 by gliders", "outcome": "recurred", "source": "Indeck et al. 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New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11. GovDelivery bulletin.", "title": "New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11", "url": "https://content.govdelivery.com/accounts/USNOAAFISHERIES/bulletins/3824b02", "date": "2023-12-29", "written_by": "deployer", "quote": "detected the presence of right whales east of Portland, ME" }, { "kind": "peer-reviewed study", "citation": "Indeck KL, Baumgartner MF, Lecavalier L, et al. (2025). Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales. Oceanography 38(Suppl. 1):13-21.", "title": "Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales", "url": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales", "written_by": "makers", "quote": "154 Slow Zones have been triggered or extended by acoustic detections of NARWs, and 51 (33%) of those Slow Zones were triggered or extended by gliders" }, { "kind": "other", "citation": "Baumgartner M (WHOI). Low-Frequency Detection and Classification System (LFDCS) user manual (developer documentation).", "title": "Low-Frequency Detection and Classification System (LFDCS)", "url": "https://dcs.whoi.edu/lfdcs_manual/lfdcs_manual.html", "written_by": "makers", "quote": "The call library can contain hundreds of these known call types, allowing the LFDCS to efficiently detect and classify many different calls produced by numerous species." }, { "kind": "report", "citation": "Wilder J, Davis G, DeAngelis A, Van Parijs S, Baumgartner M (2023). Low-Frequency Detection and Classification System (LFDCS) Reference Guide. NOAA Institutional Repository.", "title": "Low-Frequency Detection and Classification System (LFDCS) Reference Guide", "url": "https://repository.library.noaa.gov/view/noaa/48671", "written_by": "makers", "quote": "a software system created for automated detection and classification of low-frequency baleen whale vocalizations in archival and real-time acoustic data" }, { "kind": "regulatory document", "citation": "NOAA Fisheries. Reducing Vessel Strikes to North Atlantic Right Whales (Slow Zones policy page).", "title": "Reducing Vessel Strikes to North Atlantic Right Whales", "url": "https://www.fisheries.noaa.gov/national/endangered-species-conservation/reducing-vessel-strikes-north-atlantic-right-whales", "written_by": "deployer", "quote": "For a period of 15 days after a whale is detected, mariners are encouraged to avoid these areas" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0036-source-0001", "AIBD-0036-source-0002", "AIBD-0036-source-0003", "AIBD-0036-source-0004", "AIBD-0036-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "regulatory document", "citation": "NOAA Fisheries (29 Dec 2023). New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11. GovDelivery bulletin.", "title": "New Right Whale Slow Zone: East of Portland, ME - Effective Through 1/11", "url": "https://content.govdelivery.com/accounts/USNOAAFISHERIES/bulletins/3824b02", "date": "2023-12-29", "written_by": "deployer", "quote": "detected the presence of right whales east of Portland, ME" }, { "kind": "peer-reviewed study", "citation": "Indeck KL, Baumgartner MF, Lecavalier L, et al. (2025). Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales. Oceanography 38(Suppl. 1):13-21.", "title": "Glider Surveillance for Near-Real-Time Detection and Spatial Management of North Atlantic Right Whales", "url": "https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales", "written_by": "makers", "quote": "154 Slow Zones have been triggered or extended by acoustic detections of NARWs, and 51 (33%) of those Slow Zones were triggered or extended by gliders" }, { "kind": "other", "citation": "Baumgartner M (WHOI). Low-Frequency Detection and Classification System (LFDCS) user manual (developer documentation).", "title": "Low-Frequency Detection and Classification System (LFDCS)", "url": "https://dcs.whoi.edu/lfdcs_manual/lfdcs_manual.html", "written_by": "makers", "quote": "The call library can contain hundreds of these known call types, allowing the LFDCS to efficiently detect and classify many different calls produced by numerous species." }, { "kind": "report", "citation": "Wilder J, Davis G, DeAngelis A, Van Parijs S, Baumgartner M (2023). Low-Frequency Detection and Classification System (LFDCS) Reference Guide. NOAA Institutional Repository.", "title": "Low-Frequency Detection and Classification System (LFDCS) Reference Guide", "url": "https://repository.library.noaa.gov/view/noaa/48671", "written_by": "makers", "quote": "a software system created for automated detection and classification of low-frequency baleen whale vocalizations in archival and real-time acoustic data" }, { "kind": "regulatory document", "citation": "NOAA Fisheries. Reducing Vessel Strikes to North Atlantic Right Whales (Slow Zones policy page).", "title": "Reducing Vessel Strikes to North Atlantic Right Whales", "url": "https://www.fisheries.noaa.gov/national/endangered-species-conservation/reducing-vessel-strikes-north-atlantic-right-whales", "written_by": "deployer", "quote": "For a period of 15 days after a whale is detected, mariners are encouraged to avoid these areas" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "WHOI/NOAA glider's automated call classifier detected right whales on 27 December 2023; NOAA declared a Slow Zone east of Portland, ME.", "account": "On 27 December 2023 the Gulf of Maine Winter Slocum glider acoustically detected North Atlantic right whales east of Portland, Maine. Woods Hole Oceanographic Institution and NOAA's Northeast Fisheries Science Center operate it. Such gliders carry a DMON instrument running the Low-Frequency Detection and Classification System (LFDCS). It matches pitch-tracked calls against a call library using quadratic discriminant function analysis. Shore-based analysts validate detections. On 29 December 2023 NOAA Fisheries announced a voluntary Right Whale Slow Zone bounded by 43°49'N, 43°09'N, 67°02'W and 68°57'W. It ran 27 December 2023 through 11 January 2024. NOAA asked mariners to route around the area or transit at 10 knots or less." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DMON instrument running the Low-Frequency Detection and Classification System (LFDCS) on a Slocum glider" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Woods Hole Oceanographic Institution (Mark Baumgartner)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Glider-borne automated whale-call classifier triggers a NOAA Right Whale Slow Zone east of Portland, Maine", "headline": "LFDCS glider detections trigger a NOAA Right Whale Slow Zone" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "181041b30300fced8151c056ec9a4d5c663517c4a7701680671af7c2eeb1c947" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 27 December 2023 the Gulf of Maine Winter Slocum glider acoustically detected North Atlantic right whales east of Portland, Maine. Woods Hole Oceanographic Institution and NOAA's Northeast Fisheries Science Center operate it. Such gliders carry a DMON instrument running the Low-Frequency Detection and Classification System (LFDCS). It matches pitch-tracked calls against a call library using quadratic discriminant function analysis. Shore-based analysts validate detections. On 29 December 2023 NOAA Fisheries announced a voluntary Right Whale Slow Zone bounded by 43°49'N, 43°09'N, 67°02'W and 68°57'W. It ran 27 December 2023 through 11 January 2024. NOAA asked mariners to route around the area or transit at 10 knots or less.", "replication": { "produced_by": [ "Glider or buoy carrying DMON/LFDCS in right whale habitat", "Shore-based analyst validation protocol", "NOAA Slow Zone program (established late 2020) accepting acoustic triggers" ], "must_hold": [ "Whales vocalize within detection range", "Mariners comply voluntarily for any protective effect to materialize" ], "echoes": [ { "date": "2024-01-20", "setting": "Southeast US waters; first definite glider-based acoustic detection there, which triggered a Southeast Early Warning System alert for vessel strike mitigation", "outcome": "recurred", "source": "Indeck et al. (2025) Oceanography, https://tos.org/oceanography/article/glider-surveillance-for-near-real-time-detection-and-spatial-management-of-north-atlantic-right-whales" }, { "setting": "US East Coast, four years of the Slow Zone program: 154 Slow Zones triggered or extended by acoustic detections, 51 by gliders", "outcome": "recurred", "source": "Indeck et al. (2025) Oceanography" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0077", "title": "SpliceAI nominates a deep intronic PKHD1 variant in a neonate who died of ARPKD; RNA validation confirms it and the parents proceed to IVF with PGT-M", "summary": "SpliceAI scored a deep intronic PKHD1 variant 0.98; RNA studies confirmed aberrant splicing; parents used the diagnosis for IVF with PGT-M.", "date_observed": "2024-01-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A male infant was delivered at an outside hospital at 34+2 weeks and had bilateral kidney enlargement with innumerable tiny cysts consistent with autosomal recessive polycystic kidney disease; he was cared for in the Mount Sinai neonatal intensive care unit, New York, and died at two days of life. Whole-genome sequencing found a known paternal pathogenic missense variant, and SpliceAI scores in the NICUnet Rareservoir identified a maternally inherited deep intronic PKHD1 variant scoring 0.98, which RNA studies on maternal urine-derived renal epithelial cells confirmed creates a novel exon with a premature stop codon; GeneDx classified it likely pathogenic. After genetic counseling the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders within one year of the death.", "category": "benefit created", "unexpected": false, "purpose": "SpliceAI is a deep-learning model built to predict the effect of DNA variants on RNA splicing. Nominating a splice-altering deep intronic variant is exactly its intended use.", "system": "SpliceAI", "model_version": null, "developer": "SpliceAI authors (Jaganathan et al., Cell 2019), as cited in the case report; the developing organization is not named in the source text", "deployer": "NICUnet consortium / Icahn School of Medicine at Mount Sinai (Rareservoir variant database)", "location": "New York, United States", "domain": "Healthcare - neonatology / clinical genomics", "segment": "Genome reanalysis in a neonatal research network", "benefit_type": "Improved Physical Health", "taxonomy_note": "The patient had died, so the diagnosis changed the bereaved parents' reproductive planning rather than the infant's outcome.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "An identifiable family received a definitive molecular cause of their son's death. They used it for IVF with preimplantation genetic testing to avoid a lethal disease recurring. Life-changing for the family, not life-saving for the patient." } ], "ai_role": { "status": "assessed", "statement": "SpliceAI's score of 0.98 nominated the maternally inherited deep intronic variant as the second allele. Among 78,575 rare intronic PKHD1 variants in gnomAD only one scored higher. Pathogenicity was then established by RT-PCR and Sanger sequencing of maternal urine-derived cells and GeneDx's likely-pathogenic classification. The AI's contribution was candidate selection. Without it the second allele would have remained unexplained. Authors declare no relevant financial interests." }, "evidence": [ { "kind": "case report", "citation": "Richter F, Rutherford KD, Cooke AJ, Meshkati M, Eddy-Abrams V, Greene D, Kosowsky J, Park Y, Aggarwal S, Burke RJ, Chang W, Connors J, Giannone PJ, Hays T, Khattar D, Polak M, Senaldi L, Smith-Raska M, Sridhar S, Steiner L, Swanson JR, Tauber KA, Barbosa M, Guttmann KF, Turro E (2024). A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease. American Journal of Kidney Diseases 83(6):829-833 (online 10 January 2024).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "Using SpliceAI scores in the NICUnet Rareservoir, we identified a maternally inherited intronic variant with a score of 0.98 (chr6:52030169 T>C, Figure 1D)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (second quotation).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "After genetic counseling, the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders (PGT-M)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (third quotation, GeneDx classification).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "produced a diagnostic molecular report listing the missense pathogenic variant and classifying the intronic variant as likely pathogenic" } ], "replication": { "produced_by": [ "Whole-genome sequencing with SpliceAI scoring of rare intronic variants in a disease gene already implicated by one pathogenic allele", "Access to parental samples for RNA-level validation" ], "must_hold": [ "Functional or RNA confirmation before clinical use of the variant", "Genetic counseling and access to IVF with PGT-M" ], "echoes": [] }, "paired_incident": null, "headline": "SpliceAI nominates a deep intronic PKHD1 variant in fatal ARPKD", "metric": "a maternally inherited deep intronic PKHD1 variant scoring 0.98", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The parents' IVF with PGT-M within a year of the death is reported in the case report itself; nothing dated after publication was found,.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&id=30661751&retmode=xml; https://en.wikipedia.org/wiki/Icahn_School_of_Medicine_at_Mount_Sinai", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0077", "catalog_version": "1.0.0", "source_fingerprint": "8e4e4c47ca8d99fd3ca480fd7c3fd2b3508a61307d91eb3d5e0f4dc45104f741", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0077-source-0001", "AIBD-0077-source-0002", "AIBD-0077-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "SpliceAI authors (Jaganathan et al., Cell 2019), as cited in the case report; the developing organization is not named in the source text", "deployer": "NICUnet consortium / Icahn School of Medicine at Mount Sinai (Rareservoir variant database)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "SpliceAI's score of 0.98 nominated the maternally inherited deep intronic variant as the second allele. Among 78,575 rare intronic PKHD1 variants in gnomAD only one scored higher. Pathogenicity was then established by RT-PCR and Sanger sequencing of maternal urine-derived cells and GeneDx's likely-pathogenic classification. The AI's contribution was candidate selection. Without it the second allele would have remained unexplained. Authors declare no relevant financial interests." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "SpliceAI's score of 0.98 nominated the maternally inherited deep intronic variant as the second allele. Among 78,575 rare intronic PKHD1 variants in gnomAD only one scored higher. Pathogenicity was then established by RT-PCR and Sanger sequencing of maternal urine-derived cells and GeneDx's likely-pathogenic classification. The AI's contribution was candidate selection. Without it the second allele would have remained unexplained. Authors declare no relevant financial interests." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An identifiable family received a definitive molecular cause of their son's death. They used it for IVF with preimplantation genetic testing to avoid a lethal disease recurring. Life-changing for the family, not life-saving for the patient." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An identifiable family received a definitive molecular cause of their son's death. They used it for IVF with preimplantation genetic testing to avoid a lethal disease recurring. Life-changing for the family, not life-saving for the patient." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An identifiable family received a definitive molecular cause of their son's death. They used it for IVF with preimplantation genetic testing to avoid a lethal disease recurring. 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Whole-genome sequencing found a known paternal pathogenic missense variant, and SpliceAI scores in the NICUnet Rareservoir identified a maternally inherited deep intronic PKHD1 variant scoring 0.98, which RNA studies on maternal urine-derived renal epithelial cells confirmed creates a novel exon with a premature stop codon; GeneDx classified it likely pathogenic. 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A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease. American Journal of Kidney Diseases 83(6):829-833 (online 10 January 2024).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "Using SpliceAI scores in the NICUnet Rareservoir, we identified a maternally inherited intronic variant with a score of 0.98 (chr6:52030169 T>C, Figure 1D)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (second quotation).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "After genetic counseling, the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders (PGT-M)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (third quotation, GeneDx classification).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "produced a diagnostic molecular report listing the missense pathogenic variant and classifying the intronic variant as likely pathogenic" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0077-source-0001", "AIBD-0077-source-0002", "AIBD-0077-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Richter F, Rutherford KD, Cooke AJ, Meshkati M, Eddy-Abrams V, Greene D, Kosowsky J, Park Y, Aggarwal S, Burke RJ, Chang W, Connors J, Giannone PJ, Hays T, Khattar D, Polak M, Senaldi L, Smith-Raska M, Sridhar S, Steiner L, Swanson JR, Tauber KA, Barbosa M, Guttmann KF, Turro E (2024). A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease. American Journal of Kidney Diseases 83(6):829-833 (online 10 January 2024).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "Using SpliceAI scores in the NICUnet Rareservoir, we identified a maternally inherited intronic variant with a score of 0.98 (chr6:52030169 T>C, Figure 1D)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (second quotation).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "After genetic counseling, the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders (PGT-M)." }, { "kind": "case report", "citation": "Richter F et al. (2024). Am J Kidney Dis 83(6):829-833 (third quotation, GeneDx classification).", "title": "A Deep Intronic PKHD1 Variant Identified by SpliceAI in a Deceased Neonate With Autosomal Recessive Polycystic Kidney Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11116050/", "date": "2024-01-10", "written_by": "deployer", "quote": "produced a diagnostic molecular report listing the missense pathogenic variant and classifying the intronic variant as likely pathogenic" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SpliceAI scored a deep intronic PKHD1 variant 0.98; RNA studies confirmed aberrant splicing; parents used the diagnosis for IVF with PGT-M.", "account": "A male infant was delivered at an outside hospital at 34+2 weeks and had bilateral kidney enlargement with innumerable tiny cysts consistent with autosomal recessive polycystic kidney disease; he was cared for in the Mount Sinai neonatal intensive care unit, New York, and died at two days of life. 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After genetic counseling the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders within one year of the death." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SpliceAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "SpliceAI authors (Jaganathan et al., Cell 2019), as cited in the case report; the developing organization is not named in the source text" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "SpliceAI nominates a deep intronic PKHD1 variant in a neonate who died of ARPKD; RNA validation confirms it and the parents proceed to IVF with PGT-M", "headline": "SpliceAI nominates a deep intronic PKHD1 variant in fatal ARPKD" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8e4e4c47ca8d99fd3ca480fd7c3fd2b3508a61307d91eb3d5e0f4dc45104f741" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A male infant was delivered at an outside hospital at 34+2 weeks and had bilateral kidney enlargement with innumerable tiny cysts consistent with autosomal recessive polycystic kidney disease; he was cared for in the Mount Sinai neonatal intensive care unit, New York, and died at two days of life. Whole-genome sequencing found a known paternal pathogenic missense variant, and SpliceAI scores in the NICUnet Rareservoir identified a maternally inherited deep intronic PKHD1 variant scoring 0.98, which RNA studies on maternal urine-derived renal epithelial cells confirmed creates a novel exon with a premature stop codon; GeneDx classified it likely pathogenic. After genetic counseling the parents proceeded with IVF and preimplantation genetic testing for monogenic disorders within one year of the death.", "replication": { "produced_by": [ "Whole-genome sequencing with SpliceAI scoring of rare intronic variants in a disease gene already implicated by one pathogenic allele", "Access to parental samples for RNA-level validation" ], "must_hold": [ "Functional or RNA confirmation before clinical use of the variant", "Genetic counseling and access to IVF with PGT-M" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0579", "title": "COMPOSER sepsis alerts are associated with lower mortality at UC San Diego Health", "summary": "At UC San Diego, mortality after COMPOSER deployment was 9.49%, versus a modeled 11.39% without it.", "date_observed": "2024-01-23", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "UC San Diego Health evaluated COMPOSER in two emergency departments among 6,217 adults with sepsis. The model went live on December 7, 2022, with follow-up through April 30, 2023. Post-deployment mortality was 9.49%, compared with a modeled counterfactual of 11.39%: an adjusted reduction of 1.9 percentage points (95% confidence interval 0.3–3.5). Raw pre-deployment mortality was 10.3%. The estimated benefit was statistically significant at one hospital and not the other. The study used historical controls, without randomization or a concurrent untreated group.", "category": "general benefit", "unexpected": false, "purpose": "Identify emerging sepsis so that clinical teams can assess and treat patients sooner.", "system": "COMPOSER deep-learning sepsis prediction and nurse alert system", "model_version": null, "developer": "University of California San Diego research team", "deployer": "UC San Diego Health", "location": "San Diego, California, United States", "domain": "Healthcare - sepsis", "segment": "Electronic-health-record early warning system", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "The reported benefit is lower mortality. Its magnitude is estimated against a historical model rather than a randomized control." } ], "ai_role": { "status": "assessed", "statement": "COMPOSER analyzed patient data and alerted nurses to possible sepsis. Nurses reviewed patients with physicians, who selected treatment. The outcome concerns AI-assisted clinical care." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Boussina A, Shashikumar SP, Malhotra A, et al. (2024). npj Digital Medicine 7:14. doi:10.1038/s41746-023-00986-6. Evaluation by COMPOSER's developers and deploying health system. Results; corrected Table 3; Supplementary Notes 2–8 and hospital-specific analyses.", "title": "Impact of a deep learning sepsis prediction model on quality of care and survival", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10805720/", "date": "2024-01-23", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Boussina A, Shashikumar SP, Malhotra A, et al. (2024). Author Correction: Impact of a deep learning sepsis prediction model on quality of care and survival. npj Digital Medicine 7:153. doi:10.1038/s41746-024-01149-x.", "title": "Author Correction: Impact of a deep learning sepsis prediction model on quality of care and survival", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11169238/", "date": "2024-06-12", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Supreeth P. 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The model went live on December 7, 2022, with follow-up through April 30, 2023. Post-deployment mortality was 9.49%, compared with a modeled counterfactual of 11.39%: an adjusted reduction of 1.9 percentage points (95% confidence interval 0.3–3.5). Raw pre-deployment mortality was 10.3%. The estimated benefit was statistically significant at one hospital and not the other. The study used historical controls, without randomization or a concurrent untreated group.", "replication": { "produced_by": [ "Continuous analysis of electronic patient data and alerts delivered to nursing staff.", "Nurse review, physician assessment, and treatment at UC San Diego Medical Center and Jacobs Medical Center." ], "must_hold": [ "Reliable data and prompt clinical assessment are likely requirements. Local evaluation is needed to establish whether the benefit recurs." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 72, "reviewed": 77, "record_mapped": 10, "not_assessed": 4, "complete": false, "by_state": { "value_present": 72, "not_reported": 15, "unresolved": 0, "not_assessed": 4, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0229", "title": "Pindrop's deepfake detector attributes the Biden New Hampshire robocall to ElevenLabs technology, corroborated by UC Berkeley", "summary": "After a deepfake Biden robocall targeted New Hampshire's Jan 2024 primary, Pindrop's analysis against 120+ voice engines pointed to ElevenLabs; Hany Farid's Berkeley team reached the same conclusion.", "date_observed": "2024-01-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Pindrop's blog post appeared the day before. Voters in New Hampshire received an AI-generated robocall impersonating President Biden before the 23 January 2024 primary. Pindrop, a company that builds synthetic-audio detection tools, analyzed a 39-second clip, checking its patterns against more than 120 voice synthesis engines. Its CEO Vijay Balasubramaniyan told WIRED the result came back well north of 99 percent for ElevenLabs. Hany Farid's UC Berkeley team, initially skeptical, ran its own model on the same sample. It concluded with high confidence that it was AI-generated and likely ElevenLabs. ElevenLabs' own detector returned 84 percent, a result WIRED reproduced. In May 2024 the New Hampshire Attorney General announced 26 charges against Steven Kramer and the FCC proposed a $6 million fine (NHPR). The sources do not connect those actions to Pindrop's analysis.", "category": "benefit created", "unexpected": false, "purpose": "Identify synthetic (deepfake) audio and attribute it to the generating system.", "system": "Pindrop deepfake audio analysis (voice-engine attribution)", "model_version": null, "developer": "Pindrop", "deployer": "Pindrop (developer and deployer are the same company); independent corroboration by Hany Farid's UC Berkeley model", "location": null, "domain": "Election integrity / deepfake detection", "segment": "Technology", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The system attributed a harm after the fact rather than preventing it.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 1, "reason": "Public attribution of the robocall's toolchain, corroborated by an academic team. No enforcement outcome in the sources is traced to the analysis." } ], "ai_role": { "status": "assessed", "statement": "The attribution is the vendor's own analysis, reported by WIRED with named sources and independently replicated by Farid's team. ElevenLabs did not comment on the incident. 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0229-source-0001", "AIBD-0229-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kate Knibbs, WIRED, 26 Jan 2024", "title": "Researchers Say the Deepfake Biden Robocall Was Likely Made With Tools From AI Startup ElevenLabs", "url": "https://www.wired.com/story/biden-robocall-deepfake-elevenlabs/", "date": "2024-01-26", "written_by": "independent", "quote": "Our model says with high confidence that it is AI-generated and likely to be ElevenLabs," }, { "kind": "news report", "citation": "Todd Bookman, New Hampshire Public Radio, 23 May 2024", "title": "Political operative linked to AI Biden robocalls facing charges in NH, FCC fines", "url": "https://www.nhpr.org/politics/2024-05-23/political-operative-linked-to-ai-biden-robocalls-facing-charges-in-nh-fcc-fines", "date": "2024-05-23", "written_by": "independent", "quote": "In total, he’s facing 26 charges, including 13 felonies." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "After a deepfake Biden robocall targeted New Hampshire's Jan 2024 primary, Pindrop's analysis against 120+ voice engines pointed to ElevenLabs; Hany Farid's Berkeley team reached the same conclusion.", "account": "Pindrop's blog post appeared the day before. Voters in New Hampshire received an AI-generated robocall impersonating President Biden before the 23 January 2024 primary. Pindrop, a company that builds synthetic-audio detection tools, analyzed a 39-second clip, checking its patterns against more than 120 voice synthesis engines. Its CEO Vijay Balasubramaniyan told WIRED the result came back well north of 99 percent for ElevenLabs. Hany Farid's UC Berkeley team, initially skeptical, ran its own model on the same sample. It concluded with high confidence that it was AI-generated and likely ElevenLabs. ElevenLabs' own detector returned 84 percent, a result WIRED reproduced. In May 2024 the New Hampshire Attorney General announced 26 charges against Steven Kramer and the FCC proposed a $6 million fine (NHPR). The sources do not connect those actions to Pindrop's analysis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Pindrop deepfake audio analysis (voice-engine attribution)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Pindrop" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Pindrop's deepfake detector attributes the Biden New Hampshire robocall to ElevenLabs technology, corroborated by UC Berkeley", "headline": "Pindrop traces the Biden New Hampshire robocall to ElevenLabs" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8214b8556babe9cf20a70009bb6e001f80fe1f3ec1f88e30c4c95f12a2d2f31e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Pindrop's blog post appeared the day before. Voters in New Hampshire received an AI-generated robocall impersonating President Biden before the 23 January 2024 primary. Pindrop, a company that builds synthetic-audio detection tools, analyzed a 39-second clip, checking its patterns against more than 120 voice synthesis engines. Its CEO Vijay Balasubramaniyan told WIRED the result came back well north of 99 percent for ElevenLabs. Hany Farid's UC Berkeley team, initially skeptical, ran its own model on the same sample. It concluded with high confidence that it was AI-generated and likely ElevenLabs. ElevenLabs' own detector returned 84 percent, a result WIRED reproduced. In May 2024 the New Hampshire Attorney General announced 26 charges against Steven Kramer and the FCC proposed a $6 million fine (NHPR). The sources do not connect those actions to Pindrop's analysis.", "replication": { "produced_by": [ "A clean audio sample of the deepfake", "A library of fingerprints for many commercial voice-synthesis engines", "A second, independent model run on the same sample" ], "must_hold": [ "The generating engine must be among those fingerprinted", "Sample length and quality sufficient for attribution" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0123", "title": "Wireless epidural BCI lets a man quadriplegic for 14 years drink unaided (NEO, Xuanwu Hospital and Tsinghua)", "summary": "54-year-old man, quadriplegic for 14 years, drank unaided by driving a pneumatic glove through the NEO epidural BCI; announced 29 January 2024.", "date_observed": "2024-01-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 24 October 2023, teams led by Zhao Guoguang (Xuanwu Hospital) and Hong Bo (Tsinghua University) implanted the NEO wireless epidural brain-computer interface (BCI). The patient was a 54-year-old man with complete C4 spinal cord injury (ASIA A) from a car accident, quadriplegic for 14 years. Discharged ten days later, he trained three months at home. At a 29 January 2024 trial-phase summary meeting the team reported he could drive a pneumatic glove with his brain activity to drink water unaided. Grasp-decoding accuracy was above 90%, with improved ASIA scores and somatosensory evoked potentials. A September 2024 preprint reported nine months of home use: a 0.91 grasp-detection F1-score, eating and drinking, and a 27-point ARAT gain.", "category": "benefit created", "unexpected": false, "purpose": "NEO was built to let people with tetraplegia control external equipment, including a pneumatic exoskeleton glove, from epidural brain signals. The aim is assistance and hand-function rehabilitation at home. Restoring this patient's grasp so that he could drink was that purpose.", "system": "NEO (Neural Electronic Opportunity) wireless minimally invasive epidural brain-computer interface: eight epidural electrodes over the sensorimotor cortex, a battery-free coin-sized skull implant powered and read through the scalp, and a Riemannian-geometry grasp-intention decoder driving a pneumatic exoskeleton glove", "model_version": "NEO（Neural Electronic Opportunity）", "developer": "Tsinghua University School of Medicine, Prof. Hong Bo's team, with Neuracle Medical Technology (Shanghai) Co., Ltd. (博睿康科技), the trial sponsor", "deployer": "Xuanwu Hospital, Capital Medical University, Beijing (teams of Zhao Guoguang and Shan Yongzhi)", "location": "Beijing, China", "domain": "Healthcare", "segment": "Neurotechnology and spinal cord injury rehabilitation", "benefit_type": "Improved Physical Health", "taxonomy_note": "Drinking unaided through the pneumatic glove is also an accessibility gain.", "registry_ids": { "oecd_aim": "2024-01-27-c761" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "After 14 years of complete quadriplegia the patient regained the ability to drink and eat by himself through the BCI-driven glove. The preprint reports neurological recovery: upper-limb motor score +5, ARAT +27, and the ability to hold objects without the BCI." } ], "ai_role": { "status": "assessed", "statement": "The AI contribution is the decoder, a Riemannian-geometry classifier with a hidden Markov model for temporal smoothing. Calibrated in about ten minutes on beta, low-gamma and high-gamma features of eight-channel epidural ECoG, it detects grasp intention and triggers the pneumatic glove. The preprint reports 94% calibration accuracy and a grasp-detection F1-score rising above 0.9 after three months (average 0.91 over nine months). It gives 100% object-transfer success with the BCI against 35% without. The electrodes, implant, surgery and glove are not AI. The authors attribute the later neurological recovery to repeated BCI training, not the decoder alone." }, "evidence": [ { "kind": "preprint", "citation": "Liu D, Shan Y, Wei P, Li W, Xu H, Liang F, Liu T, Zhao G, Hong B (2024). Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface. medRxiv 2024.09.05.24313041 (v1 6 Sep 2024; v7 15 Jul 2025).", "title": "Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface", "url": "https://doi.org/10.1101/2024.09.05.24313041", "date": "2024-09-06", "written_by": "makers", "quote": "Over a 9-month period of home use, the patient achieved an average grasping detection F1-score of 0.91, and a 100% success rate in object transfer tests" }, { "kind": "news report", "citation": "Chen Bin, China Science Daily / ScienceNet (2024). 首例患者脑机接口康复取得突破性进展 [First patient's brain-computer interface rehabilitation makes breakthrough progress]. news.sciencenet.cn, 31 January 2024.", "title": "首例患者脑机接口康复取得突破性进展", "url": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "date": "2024-01-31", "written_by": "independent", "quote": "患者可以通过脑电活动驱动气动手套，实现自主喝水等脑控功能，抓握解码准确率超过90%" }, { "kind": "news report", "citation": "Interface News (界面新闻), republished by CCTV News (2024). 我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水 [China's BCI achieves technical breakthrough; quadriplegic patient drinks by brain control]. news.cctv.com, 31 January 2024.", "title": "我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水", "url": "https://news.cctv.com/2024/01/31/ARTIAm1lfoEPddPWL8sZzJPd240131.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "54岁，男性，此前长期处于四肢瘫痪状态" }, { "kind": "news report", "citation": "Sun Leqi, Beijing Daily client (2024). 脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水 [Major BCI breakthrough lets quadriplegic patient drink by brain control]. news.bjd.com.cn, 31 January 2024.", "title": "脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水", "url": "https://news.bjd.com.cn/2024/01/31/10691652.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "去年10月24日，宣武医院院长赵国光团队和清华大学教授洪波团队共同完成了无线微创脑机接口NEO临床植入试验" }, { "kind": "regulatory document", "citation": "Neuracle Medical Technology (Shanghai) Co., Ltd. (2023, updated 2024). A Prospective Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability. ClinicalTrials.gov NCT05920174.", "title": "Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability", "url": "https://clinicaltrials.gov/study/NCT05920174", "date": "2023-06-27", "written_by": "makers", "quote": "patients can control the external equipment（wheelchairs, robotic arms, the WeChat app and other physical aids）with brain signals to improve the patients quality of life" }, { "kind": "news report", "citation": "People's Daily client, republished on Tsinghua University's 'Media Tsinghua' page (2024). 中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\" [New progress in China's BCI technology: paraplegic patient achieves 'brain-controlled drinking']. tsinghua.edu.cn, page dated 6 February 2024.", "title": "中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\"", "url": "https://www.tsinghua.edu.cn/info/1182/109663.htm", "date": "2024-02-06", "written_by": "independent", "quote": "在1月29日召开的临床试验阶段总结会上，联合团队宣布首例患者脑机接口康复取得突破性进展" } ], "replication": { "produced_by": [ "Eight chronic epidural electrodes over the sensorimotor cortex of a patient whose cortex still generated grasp-related signals after 14 years of complete C4 injury", "A grasp-intention decoder calibrated in about ten minutes and robust to the signal drift and chewing artifacts of home use", "A battery-free implant powered and read through the scalp, so the patient could train at home daily after discharge ten days post-surgery", "A wearable pneumatic glove able to execute the decoded grasp on the patient's right hand, which retained limited forearm movement" ], "must_hold": [ "The patient's motor cortex must still produce decodable grasp intention despite years of paralysis", "The decoder must stay accurate without frequent recalibration across months of home use", "The patient or a caregiver must be able to attach the external coil and the glove for daily sessions", "Neurological recovery beyond assisted grasping is a single-patient finding and must be reproduced in further patients" ], "echoes": [] }, "paired_incident": null, "headline": "NEO BCI lets a man quadriplegic for 14 years drink unaided", "metric": "drink water unaided, with grasp-decoding accuracy above 90%", "comparator": { "against": "his own state before implantation, quadriplegic for 14 years after complete cervical spinal cord injury (ASIA A)", "before": "处于四肢瘫痪状态已经14年 (no hand function for 14 years)", "after": "实现自主喝水等脑控功能，抓握解码准确率超过90% (brain-controlled drinking, grasp decoding accuracy above 90%)", "basis": "measured", "quote": "经过三个月的居家脑机接口康复训练，患者可以通过脑电活动驱动气动手套，实现自主喝水等脑控功能，抓握解码准确率超过90%；患者脊髓损伤的ASIA临床评分和感觉诱发电位响应均有显著改善。", "url": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm" }, "later": { "status": "unknown", "date": null, "note": "Later work includes a September 2024 medRxiv preprint on nine months of home use and a Tsinghua Medicine page on a 2025 multicenter trial. Their findings remain unverified.", "quote": null, "url": null }, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-01-27-c761", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm; https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tsinghua_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports, the makers' regulatory document and the makers' preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0123", "catalog_version": "1.0.0", "source_fingerprint": "fbb504178db47e2724955bf5311c462d14b4b2b6a308f9541240335cdb8e4d4b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0123-source-0001", "AIBD-0123-source-0002", "AIBD-0123-source-0003", "AIBD-0123-source-0004", "AIBD-0123-source-0005", "AIBD-0123-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tsinghua University School of Medicine, Prof. Hong Bo's team, with Neuracle Medical Technology (Shanghai) Co., Ltd. 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The preprint reports 94% calibration accuracy and a grasp-detection F1-score rising above 0.9 after three months (average 0.91 over nine months). It gives 100% object-transfer success with the BCI against 35% without. The electrodes, implant, surgery and glove are not AI. The authors attribute the later neurological recovery to repeated BCI training, not the decoder alone." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI contribution is the decoder, a Riemannian-geometry classifier with a hidden Markov model for temporal smoothing. Calibrated in about ten minutes on beta, low-gamma and high-gamma features of eight-channel epidural ECoG, it detects grasp intention and triggers the pneumatic glove. The preprint reports 94% calibration accuracy and a grasp-detection F1-score rising above 0.9 after three months (average 0.91 over nine months). It gives 100% object-transfer success with the BCI against 35% without. The electrodes, implant, surgery and glove are not AI. The authors attribute the later neurological recovery to repeated BCI training, not the decoder alone." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After 14 years of complete quadriplegia the patient regained the ability to drink and eat by himself through the BCI-driven glove. 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "drink water unaided, with grasp-decoding accuracy above 90%", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2024-01-27-c761" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Later work includes a September 2024 medRxiv preprint on nine months of home use and a Tsinghua Medicine page on a 2025 multicenter trial. Their findings remain unverified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0123" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "Drinking unaided through the pneumatic glove is also an accessibility gain." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 24 October 2023, teams led by Zhao Guoguang (Xuanwu Hospital) and Hong Bo (Tsinghua University) implanted the NEO wireless epidural brain-computer interface (BCI). The patient was a 54-year-old man with complete C4 spinal cord injury (ASIA A) from a car accident, quadriplegic for 14 years. Discharged ten days later, he trained three months at home. At a 29 January 2024 trial-phase summary meeting the team reported he could drive a pneumatic glove with his brain activity to drink water unaided. Grasp-decoding accuracy was above 90%, with improved ASIA scores and somatosensory evoked potentials. A September 2024 preprint reported nine months of home use: a 0.91 grasp-detection F1-score, eating and drinking, and a 27-point ARAT gain.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After 14 years of complete quadriplegia the patient regained the ability to drink and eat by himself through the BCI-driven glove. The preprint reports neurological recovery: upper-limb motor score +5, ARAT +27, and the ability to hold objects without the BCI." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "NEO was built to let people with tetraplegia control external equipment, including a pneumatic exoskeleton glove, from epidural brain signals. The aim is assistance and hand-function rehabilitation at home. Restoring this patient's grasp so that he could drink was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Beijing, China", "developer_country": "China", "deployer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "NEO was built to let people with tetraplegia control external equipment, including a pneumatic exoskeleton glove, from epidural brain signals. The aim is assistance and hand-function rehabilitation at home. Restoring this patient's grasp so that he could drink was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-01-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-01-27-c761", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm; https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tsinghua_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Eight chronic epidural electrodes over the sensorimotor cortex of a patient whose cortex still generated grasp-related signals after 14 years of complete C4 injury", "A grasp-intention decoder calibrated in about ten minutes and robust to the signal drift and chewing artifacts of home use", "A battery-free implant powered and read through the scalp, so the patient could train at home daily after discharge ten days post-surgery", "A wearable pneumatic glove able to execute the decoded grasp on the patient's right hand, which retained limited forearm movement" ], "must_hold": [ "The patient's motor cortex must still produce decodable grasp intention despite years of paralysis", "The decoder must stay accurate without frequent recalibration across months of home use", "The patient or a caregiver must be able to attach the external coil and the glove for daily sessions", "Neurological recovery beyond assisted grasping is a single-patient finding and must be reproduced in further patients" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-01-27-c761", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm; https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tsinghua_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xuanwu_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare", "segment": "Neurotechnology and spinal cord injury rehabilitation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Liu D, Shan Y, Wei P, Li W, Xu H, Liang F, Liu T, Zhao G, Hong B (2024). Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface. medRxiv 2024.09.05.24313041 (v1 6 Sep 2024; v7 15 Jul 2025).", "title": "Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface", "url": "https://doi.org/10.1101/2024.09.05.24313041", "date": "2024-09-06", "written_by": "makers", "quote": "Over a 9-month period of home use, the patient achieved an average grasping detection F1-score of 0.91, and a 100% success rate in object transfer tests" }, { "kind": "news report", "citation": "Chen Bin, China Science Daily / ScienceNet (2024). 首例患者脑机接口康复取得突破性进展 [First patient's brain-computer interface rehabilitation makes breakthrough progress]. news.sciencenet.cn, 31 January 2024.", "title": "首例患者脑机接口康复取得突破性进展", "url": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "date": "2024-01-31", "written_by": "independent", "quote": "患者可以通过脑电活动驱动气动手套，实现自主喝水等脑控功能，抓握解码准确率超过90%" }, { "kind": "news report", "citation": "Interface News (界面新闻), republished by CCTV News (2024). 我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水 [China's BCI achieves technical breakthrough; quadriplegic patient drinks by brain control]. news.cctv.com, 31 January 2024.", "title": "我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水", "url": "https://news.cctv.com/2024/01/31/ARTIAm1lfoEPddPWL8sZzJPd240131.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "54岁，男性，此前长期处于四肢瘫痪状态" }, { "kind": "news report", "citation": "Sun Leqi, Beijing Daily client (2024). 脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水 [Major BCI breakthrough lets quadriplegic patient drink by brain control]. news.bjd.com.cn, 31 January 2024.", "title": "脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水", "url": "https://news.bjd.com.cn/2024/01/31/10691652.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "去年10月24日，宣武医院院长赵国光团队和清华大学教授洪波团队共同完成了无线微创脑机接口NEO临床植入试验" }, { "kind": "regulatory document", "citation": "Neuracle Medical Technology (Shanghai) Co., Ltd. (2023, updated 2024). A Prospective Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability. ClinicalTrials.gov NCT05920174.", "title": "Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability", "url": "https://clinicaltrials.gov/study/NCT05920174", "date": "2023-06-27", "written_by": "makers", "quote": "patients can control the external equipment（wheelchairs, robotic arms, the WeChat app and other physical aids）with brain signals to improve the patients quality of life" }, { "kind": "news report", "citation": "People's Daily client, republished on Tsinghua University's 'Media Tsinghua' page (2024). 中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\" [New progress in China's BCI technology: paraplegic patient achieves 'brain-controlled drinking']. tsinghua.edu.cn, page dated 6 February 2024.", "title": "中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\"", "url": "https://www.tsinghua.edu.cn/info/1182/109663.htm", "date": "2024-02-06", "written_by": "independent", "quote": "在1月29日召开的临床试验阶段总结会上，联合团队宣布首例患者脑机接口康复取得突破性进展" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0123-source-0001", "AIBD-0123-source-0002", "AIBD-0123-source-0003", "AIBD-0123-source-0004", "AIBD-0123-source-0005", "AIBD-0123-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "Liu D, Shan Y, Wei P, Li W, Xu H, Liang F, Liu T, Zhao G, Hong B (2024). Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface. medRxiv 2024.09.05.24313041 (v1 6 Sep 2024; v7 15 Jul 2025).", "title": "Reclaiming Hand Functions after Complete Spinal Cord Injury with Epidural Brain-Computer Interface", "url": "https://doi.org/10.1101/2024.09.05.24313041", "date": "2024-09-06", "written_by": "makers", "quote": "Over a 9-month period of home use, the patient achieved an average grasping detection F1-score of 0.91, and a 100% success rate in object transfer tests" }, { "kind": "news report", "citation": "Chen Bin, China Science Daily / ScienceNet (2024). 首例患者脑机接口康复取得突破性进展 [First patient's brain-computer interface rehabilitation makes breakthrough progress]. news.sciencenet.cn, 31 January 2024.", "title": "首例患者脑机接口康复取得突破性进展", "url": "https://news.sciencenet.cn/htmlnews/2024/1/516951.shtm", "date": "2024-01-31", "written_by": "independent", "quote": "患者可以通过脑电活动驱动气动手套，实现自主喝水等脑控功能，抓握解码准确率超过90%" }, { "kind": "news report", "citation": "Interface News (界面新闻), republished by CCTV News (2024). 我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水 [China's BCI achieves technical breakthrough; quadriplegic patient drinks by brain control]. news.cctv.com, 31 January 2024.", "title": "我国脑机接口实现技术突破，四肢截瘫患者实现脑控喝水", "url": "https://news.cctv.com/2024/01/31/ARTIAm1lfoEPddPWL8sZzJPd240131.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "54岁，男性，此前长期处于四肢瘫痪状态" }, { "kind": "news report", "citation": "Sun Leqi, Beijing Daily client (2024). 脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水 [Major BCI breakthrough lets quadriplegic patient drink by brain control]. news.bjd.com.cn, 31 January 2024.", "title": "脑机接口技术重大突破，让四肢截瘫患者实现自主脑控喝水", "url": "https://news.bjd.com.cn/2024/01/31/10691652.shtml", "date": "2024-01-31", "written_by": "independent", "quote": "去年10月24日，宣武医院院长赵国光团队和清华大学教授洪波团队共同完成了无线微创脑机接口NEO临床植入试验" }, { "kind": "regulatory document", "citation": "Neuracle Medical Technology (Shanghai) Co., Ltd. (2023, updated 2024). A Prospective Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability. ClinicalTrials.gov NCT05920174.", "title": "Clinical Trial to Evaluate the Safety and Efficacy of an Implantable Neural Acquisitor & Stimulator System in Patients With Motor Disability", "url": "https://clinicaltrials.gov/study/NCT05920174", "date": "2023-06-27", "written_by": "makers", "quote": "patients can control the external equipment（wheelchairs, robotic arms, the WeChat app and other physical aids）with brain signals to improve the patients quality of life" }, { "kind": "news report", "citation": "People's Daily client, republished on Tsinghua University's 'Media Tsinghua' page (2024). 中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\" [New progress in China's BCI technology: paraplegic patient achieves 'brain-controlled drinking']. tsinghua.edu.cn, page dated 6 February 2024.", "title": "中国脑机接口技术新进展！截瘫患者实现\"脑控喝水\"", "url": "https://www.tsinghua.edu.cn/info/1182/109663.htm", "date": "2024-02-06", "written_by": "independent", "quote": "在1月29日召开的临床试验阶段总结会上，联合团队宣布首例患者脑机接口康复取得突破性进展" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "54-year-old man, quadriplegic for 14 years, drank unaided by driving a pneumatic glove through the NEO epidural BCI; announced 29 January 2024.", "account": "On 24 October 2023, teams led by Zhao Guoguang (Xuanwu Hospital) and Hong Bo (Tsinghua University) implanted the NEO wireless epidural brain-computer interface (BCI). The patient was a 54-year-old man with complete C4 spinal cord injury (ASIA A) from a car accident, quadriplegic for 14 years. Discharged ten days later, he trained three months at home. At a 29 January 2024 trial-phase summary meeting the team reported he could drive a pneumatic glove with his brain activity to drink water unaided. Grasp-decoding accuracy was above 90%, with improved ASIA scores and somatosensory evoked potentials. A September 2024 preprint reported nine months of home use: a 0.91 grasp-detection F1-score, eating and drinking, and a 27-point ARAT gain." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The decoder detected intended grasping movements and triggered the pneumatic glove." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used the NEO brain-computer interface." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A classifier based on Riemannian geometry, with a hidden Markov model for temporal smoothing." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "NEO（Neural Electronic Opportunity）" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "NEO (Neural Electronic Opportunity) wireless minimally invasive epidural brain-computer interface: eight epidural electrodes over the sensorimotor cortex, a battery-free coin-sized skull implant powered and read through the scalp, and a Riemannian-geometry grasp-intention decoder driving a pneumatic exoskeleton glove" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tsinghua University School of Medicine, Prof. Hong Bo's team, with Neuracle Medical Technology (Shanghai) Co., Ltd. (博睿康科技), the trial sponsor" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Wireless epidural BCI lets a man quadriplegic for 14 years drink unaided (NEO, Xuanwu Hospital and Tsinghua)", "headline": "NEO BCI lets a man quadriplegic for 14 years drink unaided" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fbb504178db47e2724955bf5311c462d14b4b2b6a308f9541240335cdb8e4d4b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 24 October 2023, teams led by Zhao Guoguang (Xuanwu Hospital) and Hong Bo (Tsinghua University) implanted the NEO wireless epidural brain-computer interface (BCI). The patient was a 54-year-old man with complete C4 spinal cord injury (ASIA A) from a car accident, quadriplegic for 14 years. Discharged ten days later, he trained three months at home. At a 29 January 2024 trial-phase summary meeting the team reported he could drive a pneumatic glove with his brain activity to drink water unaided. Grasp-decoding accuracy was above 90%, with improved ASIA scores and somatosensory evoked potentials. A September 2024 preprint reported nine months of home use: a 0.91 grasp-detection F1-score, eating and drinking, and a 27-point ARAT gain.", "replication": { "produced_by": [ "Eight chronic epidural electrodes over the sensorimotor cortex of a patient whose cortex still generated grasp-related signals after 14 years of complete C4 injury", "A grasp-intention decoder calibrated in about ten minutes and robust to the signal drift and chewing artifacts of home use", "A battery-free implant powered and read through the scalp, so the patient could train at home daily after discharge ten days post-surgery", "A wearable pneumatic glove able to execute the decoded grasp on the patient's right hand, which retained limited forearm movement" ], "must_hold": [ "The patient's motor cortex must still produce decodable grasp intention despite years of paralysis", "The decoder must stay accurate without frequent recalibration across months of home use", "The patient or a caregiver must be able to attach the external coil and the glove for daily sessions", "Neurological recovery beyond assisted grasping is a single-patient finding and must be reproduced in further patients" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0301", "title": "A 76-year-old reads a transient negative T-wave on his own Apple Watch ECG after gym exercise; work-up finds silent three-vessel disease and he has quadruple bypass surgery (Amsterdam UMC)", "summary": "Koster et al. (EHJ Case Reports, 30 Jan 2024): a patient-initiated lead-I watch ECG showed a negative T-wave normalizing after 22 min; exercise test, CT and angiography found 3-vessel disease; CABG.", "date_observed": "2024-01-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Koster, de Winter, Verberne, Spijkerboer and Chamuleau of Amsterdam UMC reported a case in European Heart Journal Case Reports on 30 January 2024. The manuscript was received 26 June 2023 and the event is undated. The patient was a 76-year-old asymptomatic man with a strong family history of coronary disease. He had 30 years of treated hypercholesterolemia and four years of type 2 diabetes. He exercised weekly on a cross trainer. Very infrequently and “solely out of interest”, he recorded a lead-I electrocardiogram (ECG) with his Apple Watch right afterwards. On the last recording he noticed a negative T-wave that deepened over about seven minutes and normalized after 22 minutes. He had no chest pain, breathlessness, dizziness or palpitations. He consulted a cardiologist, whose resting ECG and examination were normal. A bicycle exercise test two days later reproduced the lead-I T-wave change with ST depression up to 4 mm in V5. Cardiac computed tomography (CT) showed stenoses in all coronary arteries (CAD-RADS 4). Invasive angiography showed three-vessel disease and a perfusion scan reversible ischemia in 16% of the myocardium. The heart team chose surgery and he received four bypass grafts. Recovery was uneventful and a repeat exercise ECG at 11 weeks was normal. The authors note Apple does not recommend the watch for detecting infarction or ischemia. They note lead I is not ideal for ischemia and the finding requires systematic study before clinical use. The paper reports no output from the ECG app's rhythm classifier. The wearer saw the abnormality on the trace and clinicians confirmed it.", "category": "benefit created", "unexpected": true, "purpose": "The ECG app is built to record a single-lead ECG and classify atrial fibrillation. Using the trace to spot exercise-induced ischemia is, as the authors say, not endorsed by Apple.", "system": "Apple Watch ECG app (single lead-I recording; its rhythm classifier is not mentioned in the report)", "model_version": null, "developer": "Apple", "deployer": null, "location": "Amsterdam, the Netherlands", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Silent, extensive, reversible ischemia from three-vessel disease was found and treated with quadruple bypass in an asymptomatic man. The authors' learning point is that such ischemia can end in exercise-induced sudden death. The counterfactual is not established." } ], "ai_role": { "status": "assessed", "statement": "The watch recorded a 30-second lead-I trace at the wearer's initiative. The report gives no classification result from the app. The negative T-wave was noticed by the patient and interpreted by cardiologists, who ordered the exercise test, imaging and surgery. No machine-learning output contributed to the finding as described. The single source is an independent peer-reviewed case report. No maker material was used." }, "evidence": [ { "kind": "case report", "citation": "Koster RW, de Winter RJ, Verberne HJ, Spijkerboer AM, Chamuleau SA (2024). Severe silent ischaemia detected with an Apple Watch in the home setting: a case report. European Heart Journal - Case Reports 8(2):ytae043 (PMC10872691).", "title": "Severe silent ischaemia detected with an Apple Watch in the home setting: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/", "date": "2024-01-30", "written_by": "independent", "quote": "The use for detecting myocardial ischaemia is not endorsed by Apple but is documented in this case." }, { "kind": "case report", "citation": "Koster et al. (2024), Eur Heart J Case Rep 8(2):ytae043, case presentation.", "title": "Severe silent ischaemia detected with an Apple Watch in the home setting: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/", "date": "2024-01-30", "written_by": "independent", "quote": "he noticed immediately after exercise, a negative T-wave that became more prominent in ∼7 min, then slowly returned back to a normal positive T-wave after 22 min" }, { "kind": "case report", "citation": "Koster et al. (2024), Eur Heart J Case Rep 8(2):ytae043, treatment.", "title": "Severe silent ischaemia detected with an Apple Watch in the home setting: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/", "date": "2024-01-30", "written_by": "independent", "quote": "Coronary bypass surgery was performed with four bypasses on all coronary arteries involved" }, { "kind": "case report", "citation": "Koster et al. (2024), Eur Heart J Case Rep 8(2):ytae043, learning points.", "title": "Severe silent ischaemia detected with an Apple Watch in the home setting: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/", "date": "2024-01-30", "written_by": "independent", "quote": "Extensive exercise-induced reversible myocardial ischaemia may remain asymptomatic and can result in exercise-induced sudden death." } ], "replication": { "produced_by": [ "A wearer who records a watch ECG right after exercise and looks at the waveform, not only the rhythm label", "A cardiologist willing to investigate a watch trace in an asymptomatic patient", "Exercise testing, CT, angiography and perfusion imaging to confirm and grade the disease" ], "must_hold": [ "The lead-I trace reproduces T-wave changes faithfully, which the authors say appeared accurate though frequency characteristics are undocumented", "Ischemia that shows in lead I, which the authors call not ideal for the purpose", "Tolerance of false positives and investigation cascades, which the authors flag as unstudied" ], "echoes": [] }, "paired_incident": null, "headline": "Apple Watch ECG T-wave leads a 76-year-old to quadruple bypass", "metric": "he received four bypass grafts; recovery was uneventful", "comparator": { "against": "the cardiologist's resting 12-lead ECG and physical examination", "before": "A standard ECG was completely normal, as was physical examination.", "after": "he noticed immediately after exercise, a negative T-wave that became more prominent in ∼7 min, then slowly returned back to a normal positive T-wave after 22 min", "basis": "measured", "quote": "He consulted a cardiologist and there was agreement that this Apple Watch observation warranted further investigation. A standard ECG was completely normal, as was physical examination.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/" }, "later": { "status": "unknown", "date": null, "note": "The paper's own 11-week postoperative exercise ECG (normal) is part of the first report; nothing published later about the patient was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10872691/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0301", "catalog_version": "1.0.0", "source_fingerprint": "7f02698d60bc4f405f2972c173105df69d640a735070abf328fc8c24784f1e95", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0301-source-0001", "AIBD-0301-source-0002", "AIBD-0301-source-0003", "AIBD-0301-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch recorded a 30-second lead-I trace at the wearer's initiative. The report gives no classification result from the app. The negative T-wave was noticed by the patient and interpreted by cardiologists, who ordered the exercise test, imaging and surgery. No machine-learning output contributed to the finding as described. The single source is an independent peer-reviewed case report. No maker material was used." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch recorded a 30-second lead-I trace at the wearer's initiative. The report gives no classification result from the app. The negative T-wave was noticed by the patient and interpreted by cardiologists, who ordered the exercise test, imaging and surgery. No machine-learning output contributed to the finding as described. The single source is an independent peer-reviewed case report. No maker material was used." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Silent, extensive, reversible ischemia from three-vessel disease was found and treated with quadruple bypass in an asymptomatic man. The authors' learning point is that such ischemia can end in exercise-induced sudden death. 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(EHJ Case Reports, 30 Jan 2024): a patient-initiated lead-I watch ECG showed a negative T-wave normalizing after 22 min; exercise test, CT and angiography found 3-vessel disease; CABG.", "account": "Koster, de Winter, Verberne, Spijkerboer and Chamuleau of Amsterdam UMC reported a case in European Heart Journal Case Reports on 30 January 2024. The manuscript was received 26 June 2023 and the event is undated. The patient was a 76-year-old asymptomatic man with a strong family history of coronary disease. He had 30 years of treated hypercholesterolemia and four years of type 2 diabetes. He exercised weekly on a cross trainer. Very infrequently and “solely out of interest”, he recorded a lead-I electrocardiogram (ECG) with his Apple Watch right afterwards. On the last recording he noticed a negative T-wave that deepened over about seven minutes and normalized after 22 minutes. He had no chest pain, breathlessness, dizziness or palpitations. He consulted a cardiologist, whose resting ECG and examination were normal. A bicycle exercise test two days later reproduced the lead-I T-wave change with ST depression up to 4 mm in V5. Cardiac computed tomography (CT) showed stenoses in all coronary arteries (CAD-RADS 4). Invasive angiography showed three-vessel disease and a perfusion scan reversible ischemia in 16% of the myocardium. The heart team chose surgery and he received four bypass grafts. Recovery was uneventful and a repeat exercise ECG at 11 weeks was normal. The authors note Apple does not recommend the watch for detecting infarction or ischemia. They note lead I is not ideal for ischemia and the finding requires systematic study before clinical use. The paper reports no output from the ECG app's rhythm classifier. The wearer saw the abnormality on the trace and clinicians confirmed it." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch ECG app (single lead-I recording; its rhythm classifier is not mentioned in the report)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A 76-year-old reads a transient negative T-wave on his own Apple Watch ECG after gym exercise; work-up finds silent three-vessel disease and he has quadruple bypass surgery (Amsterdam UMC)", "headline": "Apple Watch ECG T-wave leads a 76-year-old to quadruple bypass" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7f02698d60bc4f405f2972c173105df69d640a735070abf328fc8c24784f1e95" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Koster, de Winter, Verberne, Spijkerboer and Chamuleau of Amsterdam UMC reported a case in European Heart Journal Case Reports on 30 January 2024. The manuscript was received 26 June 2023 and the event is undated. The patient was a 76-year-old asymptomatic man with a strong family history of coronary disease. He had 30 years of treated hypercholesterolemia and four years of type 2 diabetes. He exercised weekly on a cross trainer. Very infrequently and “solely out of interest”, he recorded a lead-I electrocardiogram (ECG) with his Apple Watch right afterwards. On the last recording he noticed a negative T-wave that deepened over about seven minutes and normalized after 22 minutes. He had no chest pain, breathlessness, dizziness or palpitations. He consulted a cardiologist, whose resting ECG and examination were normal. A bicycle exercise test two days later reproduced the lead-I T-wave change with ST depression up to 4 mm in V5. Cardiac computed tomography (CT) showed stenoses in all coronary arteries (CAD-RADS 4). Invasive angiography showed three-vessel disease and a perfusion scan reversible ischemia in 16% of the myocardium. The heart team chose surgery and he received four bypass grafts. Recovery was uneventful and a repeat exercise ECG at 11 weeks was normal. The authors note Apple does not recommend the watch for detecting infarction or ischemia. They note lead I is not ideal for ischemia and the finding requires systematic study before clinical use. The paper reports no output from the ECG app's rhythm classifier. The wearer saw the abnormality on the trace and clinicians confirmed it.", "replication": { "produced_by": [ "A wearer who records a watch ECG right after exercise and looks at the waveform, not only the rhythm label", "A cardiologist willing to investigate a watch trace in an asymptomatic patient", "Exercise testing, CT, angiography and perfusion imaging to confirm and grade the disease" ], "must_hold": [ "The lead-I trace reproduces T-wave changes faithfully, which the authors say appeared accurate though frequency characteristics are undocumented", "Ischemia that shows in lead I, which the authors call not ideal for the purpose", "Tolerance of false positives and investigation cascades, which the authors flag as unstudied" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0582", "title": "AI flags Julie Knichel's brain hemorrhage before aneurysm treatment and her return to nursing", "summary": "Julie Knichel’s doctors received an alert after software, apparently Viz.ai, detected her brain bleed.", "date_observed": "2024-02-02", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Julie Knichel, a 57-year-old nurse, suffered a ruptured brain aneurysm. At Baptist Health's Marcus Neuroscience Institute, AI reviewed her scan and alerted clinicians to the bleeding. They sealed the aneurysm with coils delivered through a catheter. After about three weeks in hospital, she recovered and returned to full-time nursing. Her symptoms began on 2 February 2024. Baptist Health gives the day and month, and Jan Engoren’s subsequent interviews with Knichel and Snelling establish the year. The surgeon names Viz.ai in a later interview and describes an unnamed ICU nurse whose circumstances match Knichel’s. The product attribution is therefore inferred. Neither account identifies the module or release.", "category": "harm prevented", "unexpected": false, "purpose": "Detect brain hemorrhage and alert clinicians.", "system": "Viz.ai stroke detection and care coordination (attribution inferred)", "model_version": null, "developer": "Viz.ai (inferred)", "deployer": "Baptist Health, Marcus Neuroscience Institute", "location": "Boca Raton, Florida, United States", "domain": "Stroke care", "segment": "Emergency patients with brain hemorrhage", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "Knichel survived a life-threatening hemorrhage and resumed her work and activities." } ], "ai_role": { "status": "assessed", "statement": "AI flagged the bleeding and notified the stroke team, according to her treating surgeon. Clinicians treated the aneurysm. Viz.ai is an inferred identification from his separate interview. The sources do not isolate the software’s effect on survival." }, "evidence": [ { "kind": "report", "citation": "Adrienne Sylver, Baptist Health, November 25, 2024.", "title": "Stroke Nurse Shares Her Experience After Brain Aneurysm", "url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "date": "2024-11-25", "written_by": "deployer", "quote": "Ms. Knichel is happy to have returned to work full time and to her previous activities" }, { "kind": "news report", "citation": "Brian Snelling and Felipe De Los Rios. “Incorporating AI Into Stroke Triage,” NeurologyLive, October 22, 2025. Original video, 2:29–2:36 and 5:03–5:36; edited transcript, Snelling’s responses.", "title": "Incorporating AI Into Stroke Triage", "url": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "date": "2025-10-22", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Jan Engoren. “Health & Harmony: Fast action, expert surgeon empower nurse’s recovery from stroke,” The Coastal Star, April 29, 2025. Paragraphs describing February 2024 treatment, subarachnoid hemorrhage, and recovery.", "title": "Health & Harmony: Fast action, expert surgeon empower nurse’s recovery from stroke", "url": "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover", "date": "2025-04-29", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Kara Duffy. “From caregiver to cared for: How an ICU nurse’s training saved her own life.” CBS12/WPEC, October 29, 2024.", "title": "From caregiver to cared for: How an ICU nurse’s training saved her own life", "url": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "date": "2024-10-29", "written_by": "independent", "quote": null }, { "kind": "report", "citation": "Viz.ai. “Viz.ai Trust Center Privacy Notice.” Section 14, “Viz.ai Head Office.” Undated.", "title": "Viz.ai Trust Center Privacy Notice", "url": "https://www.viz.ai/trust-center-privacy-notice", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "AI-assisted imaging and specialist treatment." ], "must_hold": [ "Prompt clinical review and access to aneurysm treatment." ], "echoes": [] }, "paired_incident": null, "headline": "Doctors found a nurse’s brain bleed with help from AI", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Baptist Health's original patient and clinician account, including the surrounding video reference and stroke background. Kept one institutional source and preserved the absence of a named system, measured time saving or patient-specific comparison.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Marked Viz.ai as inferred in the system and developer fields and qualified the AI-role statement. Added earlier original CBS12 interviews, preserved the clinical testimony, and recorded the absence of a confirmed module or release.", "source": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the editorial parenthetical and unconfirmed product name from the subtitle. Preserved the inferred Viz.ai identification and its supporting evidence in the case account, system assessment, and source notes.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Restored Viz.ai in the subtitle with an explicit qualification and numbered the two reported clauses. Preserved the inferred system identification and the existing source assessments.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the subtitle to the alert and detection sequence while retaining the qualified Viz.ai identification.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added the United States as the jurisdiction of the inferred developer, Viz.ai, using its own headquarters statement. Preserved the inferred product attribution and existing clinical chronology, account, and ratings. The corporate notice is not evidence that Viz.ai was used for this patient.", "source": "https://www.viz.ai/trust-center-privacy-notice", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' report, the deployer's report and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0582", "catalog_version": "1.0.0", "source_fingerprint": "2e3e3df9046689dd81d56e536fd692f7e4e834745f330a46e124736af5bf6e5f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004", "AIBD-0582-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Viz.ai (inferred)", "deployer": "Baptist Health, Marcus Neuroscience Institute" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "deployer", "developer" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Baptist Health’s Marcus Neuroscience Institute treated Knichel. Viz.ai probably supplied the detection software.", "editor_note": "" } }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AI flagged the bleeding and notified the stroke team, according to her treating surgeon. Clinicians treated the aneurysm. Viz.ai is an inferred identification from his separate interview. The sources do not isolate the software’s effect on survival." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The surgeon reported that software detected the bleeding and alerted the stroke team. Clinicians treated the aneurysm. The sources do not separately measure the software’s effect on survival.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "AI flagged the bleeding and notified the stroke team, according to her treating surgeon. Clinicians treated the aneurysm. Viz.ai is an inferred identification from his separate interview. The sources do not isolate the software’s effect on survival." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Knichel survived a life-threatening hemorrhage and resumed her work and activities." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Baptist Health, CBS12/WPEC, The Coastal Star, and NeurologyLive provide patient or treating-clinician accounts. No independent study measures the AI contribution, and no finding by a regulator or court is cited.", "interpretation": "Independent interviews corroborate the patient outcome and event year. The product attribution follows the treating clinician’s account and is not independently verified.", "system_identity_review": "Additional sources clarify technical identity or chronology. They do not establish the AI contribution independently of the original investigators or witnesses." } }, "provenance": { "kind": "source_review", "basis": "Recomputed the existing display rule after adding the reviewed sources. Source independence remains claim-specific.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Knichel survived a life-threatening hemorrhage and resumed her work and activities." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported 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"review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0582" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Julie Knichel, a 57-year-old nurse, suffered a ruptured brain aneurysm. At Baptist Health's Marcus Neuroscience Institute, AI reviewed her scan and alerted clinicians to the bleeding. They sealed the aneurysm with coils delivered through a catheter. After about three weeks in hospital, she recovered and returned to full-time nursing. Her symptoms began on 2 February 2024. Baptist Health gives the day and month, and Jan Engoren’s subsequent interviews with Knichel and Snelling establish the year. The surgeon names Viz.ai in a later interview and describes an unnamed ICU nurse whose circumstances match Knichel’s. The product attribution is therefore inferred. Neither account identifies the module or release.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Knichel survived a life-threatening hemorrhage and resumed her work and activities." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect brain hemorrhage and alert clinicians." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "location": "Boca Raton, Florida, United States", "developer_country": "United States", "deployer_country": "United States", "developer_jurisdictions": [ "United States" ], "case_jurisdictions": [ "United States" ], "developer_jurisdiction_inferred": true, "developer_note": "Viz.ai is the inferred developer. Its U.S. headquarters is documented, but its involvement in this patient’s care remains inferred." } }, "provenance": { "kind": "source_review", "basis": "Section 14 of Viz.ai’s own Trust Center Privacy Notice explicitly identifies U.S. headquarters and a San Francisco address. The system and developer attribution to Knichel remain inferred, so the developer jurisdiction is conditional on that attribution. The notice supplies no patient-specific evidence and has no stated publication date. The existing U.S. hospital and benefit location are preserved from the reviewed hospital account.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Knichel received care in Boca Raton, Florida, United States. Both Baptist Health and the inferred provider, Viz.ai, are based in the United States.", "editor_note": "" } }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect brain hemorrhage and alert clinicians." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-02-02", "date_basis": "event", "date_precision": "day", "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Baptist Health's original patient and clinician account, including the surrounding video reference and stroke background. Kept one institutional source and preserved the absence of a named system, measured time saving or patient-specific comparison.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Marked Viz.ai as inferred in the system and developer fields and qualified the AI-role statement. Added earlier original CBS12 interviews, preserved the clinical testimony, and recorded the absence of a confirmed module or release.", "source": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the editorial parenthetical and unconfirmed product name from the subtitle. Preserved the inferred Viz.ai identification and its supporting evidence in the case account, system assessment, and source notes.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Restored Viz.ai in the subtitle with an explicit qualification and numbered the two reported clauses. Preserved the inferred system identification and the existing source assessments.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the subtitle to the alert and detection sequence while retaining the qualified Viz.ai identification.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added the United States as the jurisdiction of the inferred developer, Viz.ai, using its own headquarters statement. Preserved the inferred product attribution and existing clinical chronology, account, and ratings. The corporate notice is not evidence that Viz.ai was used for this patient.", "source": "https://www.viz.ai/trust-center-privacy-notice", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Added the geography review to the revision history and preserved the previously assessed event chronology and its evidence.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "AI-assisted imaging and specialist treatment." ], "must_hold": [ "Prompt clinical review and access to aneurysm treatment." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read Baptist Health's original patient and clinician account, including the surrounding video reference and stroke background. Kept one institutional source and preserved the absence of a named system, measured time saving or patient-specific comparison.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Marked Viz.ai as inferred in the system and developer fields and qualified the AI-role statement. Added earlier original CBS12 interviews, preserved the clinical testimony, and recorded the absence of a confirmed module or release.", "source": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the editorial parenthetical and unconfirmed product name from the subtitle. Preserved the inferred Viz.ai identification and its supporting evidence in the case account, system assessment, and source notes.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Restored Viz.ai in the subtitle with an explicit qualification and numbered the two reported clauses. Preserved the inferred system identification and the existing source assessments.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the subtitle to the alert and detection sequence while retaining the qualified Viz.ai identification.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added the United States as the jurisdiction of the inferred developer, Viz.ai, using its own headquarters statement. Preserved the inferred product attribution and existing clinical chronology, account, and ratings. The corporate notice is not evidence that Viz.ai was used for this patient.", "source": "https://www.viz.ai/trust-center-privacy-notice", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Added the geography review to the revision history and preserved the previously assessed event chronology and its evidence.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Stroke care", "segment": "Emergency patients with brain hemorrhage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "versions_and_access": [ { "source_url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "published_on": "2024-11-25", "status": "Complete article and outgoing links inspected." }, { "source_url": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "status": "Original source inspected.", "locator": "Original video 2:29–2:36, 5:03–5:36. The edited transcript omits the pointer to the earlier press release.", "reviewed_on": "2026-10-24" }, { "source_url": "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover", "status": "Original source inspected.", "locator": "Paragraph beginning “Knichel came under Snelling’s care in February 2024”; treatment and recovery paragraphs.", "reviewed_on": "2026-10-24" }, { "source_url": "https://players.brightcove.net/10203567001/wf0hzDVjW_default/index.html?videoId=6383528276112", "source_ref": "AIBD-0582-source-0002", "status": "Original interview captions inspected; same work as the edited transcript.", "locator": "2:29–2:36 and 5:03–5:36." }, { "source_url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "source_ref": "AIBD-0582-source-0001", "status": "Embedded hospital-video transcript and frames inspected. No product brand appears in the AI passage.", "locator": "1:42–2:19." }, { "source_url": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "source_ref": "AIBD-0582-source-0004", "publication_date": "2024-10-29", "accessed_on": "2026-10-24", "status": "Original publisher text inspected.", "locator": "Opening patient account, Snelling’s first response, and the video caption." }, { "source_ref": "AIBD-0582-source-0001", "source_url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "access_url": "https://physicianresources.baptisthealth.net/videos/ai-saves-the-day", "captions_url": "https://s7d9.scene7.com/is/content/bhsf/Transcript-English-AI%20Saves%20the%20Day", "accessed_on": "2026-10-24", "locator": "1:42–2:19", "status": "Original hospital video and publisher-supplied captions inspected. Snelling describes the AI alert in Julie’s case without naming the product. This is the same video as the embedded hospital article, not another source." }, { "source_url": "https://www.viz.ai/trust-center-privacy-notice", "source_ref": "AIBD-0582-source-0005", "accessed_on": "2026-10-25", "language": "English", "status": "Original developer webpage inspected for corporate geography.", "locator": "Section 14, “Viz.ai Head Office”: U.S. headquarters and San Francisco address." } ], "limitations": [ "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred.", "No reviewed source identifies the exact Viz.ai module or model version, or supplies a patient-specific measured comparison of AI against manual review." ] } }, "provenance": { "kind": "source_review", "basis": "Inspected the additional corporate-geography source and retained prior access and identity limitations.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital’s patient story and the surgeon’s interviews describe detection and treatment. They provide no scan-specific processing record or comparison of the software with manual review.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Adrienne Sylver, Baptist Health, November 25, 2024.", "title": "Stroke Nurse Shares Her Experience After Brain Aneurysm", "url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "date": "2024-11-25", "written_by": "deployer", "quote": "Ms. Knichel is happy to have returned to work full time and to her previous activities" }, { "kind": "news report", "citation": "Brian Snelling and Felipe De Los Rios. “Incorporating AI Into Stroke Triage,” NeurologyLive, October 22, 2025. Original video, 2:29–2:36 and 5:03–5:36; edited transcript, Snelling’s responses.", "title": "Incorporating AI Into Stroke Triage", "url": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "date": "2025-10-22", "written_by": "deployer" }, { "kind": "news report", "citation": "Jan Engoren. “Health & Harmony: Fast action, expert surgeon empower nurse’s recovery from stroke,” The Coastal Star, April 29, 2025. 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Paragraphs describing February 2024 treatment, subarachnoid hemorrhage, and recovery.", "title": "Health & Harmony: Fast action, expert surgeon empower nurse’s recovery from stroke", "url": "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover", "date": "2025-04-29", "written_by": "independent" }, { "kind": "news report", "citation": "Kara Duffy. “From caregiver to cared for: How an ICU nurse’s training saved her own life.” CBS12/WPEC, October 29, 2024.", "title": "From caregiver to cared for: How an ICU nurse’s training saved her own life", "url": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "date": "2024-10-29", "written_by": "independent" }, { "kind": "report", "citation": "Viz.ai. “Viz.ai Trust Center Privacy Notice.” Section 14, “Viz.ai Head Office.” Undated.", "title": "Viz.ai Trust Center Privacy Notice", "url": "https://www.viz.ai/trust-center-privacy-notice", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Appended an original corporate-geography source while preserving the existing evidence, ordering, and clinical or system-identity qualifications.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0582-source-0001", "retained_source_order": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004", "AIBD-0582-source-0005" ], "origins": [ { "url": "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "contribution": "Original patient and treating-team interviews describe the brain bleed, scan review, coiling, three-week admission and return to work.", "locator": "Unique stroke services; Colleagues who care.", "relationship": "Treating institution's account. The accompanying video is part of the same publication, not corroboration.", "source_refs": [ "AIBD-0582-source-0001" ], "display_name": "Baptist Health" }, { "url": "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "contribution": "Snelling names Viz.ai as a hospital system and later recounts an unnamed nurse’s case that matches Knichel’s circumstances.", "locator": "Original video 2:29–2:36, 5:03–5:36. The edited transcript omits the pointer to the earlier press release.", "relationship": "Original clinician testimony. The product attribution and matching of the unnamed patient remain inferences; the video is less explicit than the edited transcript.", "source_refs": [ "AIBD-0582-source-0002" ], "display_name": "NeurologyLive", "access_url": "https://players.brightcove.net/10203567001/wf0hzDVjW_default/index.html?videoId=6383528276112" }, { "url": "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover", "contribution": "Patient and clinician interviews establish February 2024, subarachnoid hemorrhage, treatment, and return to work.", "locator": "Paragraph beginning “Knichel came under Snelling’s care in February 2024”; treatment and recovery paragraphs.", "relationship": "Original reporting corroborates the patient outcome and chronology, not the AI product or its separate effect.", "source_refs": [ "AIBD-0582-source-0003" ], "display_name": "The Coastal Star" }, { "url": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "source_refs": [ "AIBD-0582-source-0004" ], "locator": "Opening patient account, Snelling’s first response, and the video caption.", "display_name": "CBS12/WPEC", "contribution": "Earlier original interviews name Knichel, date the episode to February 2024, and quote Snelling’s account of AI detecting the bleed before clinicians.", "relationship": "Separate reporting from the same patient and treating surgeon. It establishes an earlier public account but supplies no brand identification, clinical record, or independent measurement of the AI contribution." }, { "url": "https://www.viz.ai/trust-center-privacy-notice", "contribution": "Establishes Viz.ai’s U.S. headquarters. The attribution of Viz.ai to Knichel remains inferred.", "locator": "Section 14, “Viz.ai Head Office”: U.S. headquarters and San Francisco address.", "relationship": "Original developer statement about corporate geography. It does not identify the software used for this patient or independently corroborate her clinical outcome.", "source_refs": [ "AIBD-0582-source-0005" ], "display_name": "Viz.ai" } ], "claim_chains": [ { "claim": "AI-assisted care and recovery", "path": [ "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life" ], "finding": "The hospital account and an earlier CBS12 interview directly report AI assistance through the treating surgeon. Neither supplies a scan record, model evaluation, or software brand." }, { "claim": "System identity", "path": [ "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover" ], "finding": "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred." }, { "claim": "System attribution", "path": [ "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "https://www.neurologylive.com/view/incorporating-ai-into-stroke-triage", "https://players.brightcove.net/10203567001/wf0hzDVjW_default/index.html?videoId=6383528276112" ], "finding": "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred." }, { "claim": "Event chronology", "path": [ "https://baptisthealth.net/baptist-health-news/stroke-nurse-shares-her-experience-after-brain-aneurysm", "https://thecoastalstar.com/profiles/blogs/fast-action-expert-surgeon-empowers-nurse-to-recover" ], "finding": "The hospital gives February 2. The subsequent patient and clinician interviews establish February 2024, supporting 2 February 2024." }, { "claim": "Developer jurisdiction and geographic scope", "path": [ "https://www.viz.ai/trust-center-privacy-notice" ], "finding": "Section 14 of Viz.ai’s own Trust Center Privacy Notice explicitly identifies U.S. headquarters and a San Francisco address. The system and developer attribution to Knichel remain inferred, so the developer jurisdiction is conditional on that attribution. The notice supplies no patient-specific evidence and has no stated publication date. The existing U.S. hospital and benefit location are preserved from the reviewed hospital account." } ], "limitations": [ "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred.", "No reviewed source identifies the exact Viz.ai module or model version, or supplies a patient-specific measured comparison of AI against manual review." ], "excluded_or_consolidated_sources": [], "review_scope": "Reviewed the earlier CBS12 report, original hospital video and captions, NeurologyLive video, and additional patient interviews. AI involvement is directly reported by the treating surgeon; the product, module, and release remain unconfirmed for this patient. Additional review on October 25, 2026, establishes developer jurisdiction and clarifies geographic scope; prior clinical and attribution limitations remain unchanged.", "homepage_source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002" ], "earlier_reporting": [ { "url": "https://cbs12.com/news/local/from-caregiver-to-cared-for-how-an-icu-nurses-training-saved-her-own-life", "publication_date": "2024-10-29", "finding": "Original named-patient and surgeon interviews precede the retained hospital article." } ], "additional_interviews_checked": [ { "url": "https://www.theeducatedpatient.com/view/hear-my-journey-from-neuro-icu-nurse-to-brain-aneurysm-survivor", "title": "Hear My Journey: From Neuro ICU Nurse to Brain Aneurysm Survivor", "author": "Lana Pine", "publication_date": "2025-08-06", "format_inspected": "Complete original interview audio, approximately 9 minutes, reviewed through a local automated transcription; the webpage is an edited account.", "finding": "The interview describes the hemorrhage, treatment, hospitalization, and return to work but does not discuss AI. It does not resolve the system identity.", "relationship": "Additional testimony from the same patient and clinician; retained as a checked source note, not a separate confirmation." }, { "url": "https://www.wpbf.com/article/on-the-record-knowing-the-signs-of-a-stroke/71263276", "title": "On the Record: Knowing the signs of a stroke", "author": "Malcolm Shields", "publication_date": "2026-05-10", "format_inspected": "Complete original interview audio, approximately 20 minutes, reviewed through a local automated transcription. No publisher transcript was available.", "locators": [ "1:04–1:10: Knichel dates the episode to February 2, 2024", "5:15–6:02: Snelling describes the AI alert", "8:33–8:59: return to work" ], "finding": "The patient and treating surgeon confirm the reported course and AI alert. No product, module, or release is named.", "relationship": "Follow-up testimony from the same witnesses; retained as a checked source note, not an independent evaluation." } ] } }, "provenance": { "kind": "source_review", "basis": "Added corporate geography and its original source without repeating or replacing the prior clinical and system-identity assessments.", "record_fields": [ "evidence", "developer_country", "location" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004", "AIBD-0582-source-0005" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Baptist Health, CBS12, and The Coastal Star interview Knichel and her surgeon. NeurologyLive separately interviews the surgeon about Viz.ai. These accounts support the treatment history but do not independently measure the software’s contribution.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Julie Knichel’s doctors received an alert after software, apparently Viz.ai, detected her brain bleed.", "account": "Julie Knichel, a 57-year-old nurse, suffered a ruptured brain aneurysm. At Baptist Health's Marcus Neuroscience Institute, AI reviewed her scan and alerted clinicians to the bleeding. They sealed the aneurysm with coils delivered through a catheter. After about three weeks in hospital, she recovered and returned to full-time nursing. Her symptoms began on 2 February 2024. Baptist Health gives the day and month, and Jan Engoren’s subsequent interviews with Knichel and Snelling establish the year. The surgeon names Viz.ai in a later interview and describes an unnamed ICU nurse whose circumstances match Knichel’s. The product attribution is therefore inferred. Neither account identifies the module or release." } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "clinical_setting": "Marcus Neuroscience Institute, Baptist Health, Boca Raton.", "reported_workflow": "AI reviewed brain imaging and alerted clinicians before their own review, according to the treating surgeon.", "unreported_details": [ "Confirmed product and module for this patient", "Model and software release", "Scan-specific processing record" ] } }, "provenance": { "kind": "source_review", "basis": "Patient and treating-clinician accounts establish the clinical workflow but not the exact technical configuration.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Software analyzed brain images and alerted the treating team before its review, according to the surgeon.", "editor_note": "" } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The named-patient accounts do not identify the software brand, module, underlying model, or release. The Viz.ai attribution relies on a separate interview and remains inferred.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "reason": "The named-patient accounts do not identify the software brand, module, underlying model, or release. The Viz.ai attribution relies on a separate interview and remains inferred.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The detector for brain bleeding is not separately named.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The named-patient accounts do not identify the software brand, module, underlying model, or release. The Viz.ai attribution relies on a separate interview and remains inferred.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "reason": "The named-patient accounts do not identify the software brand, module, underlying model, or release. The Viz.ai attribution relies on a separate interview and remains inferred.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The sources do not identify the installed release.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Viz.ai stroke detection and care coordination (attribution inferred)" } }, "provenance": { "kind": "derivation", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Apparently Viz.ai.", "editor_note": "In a separate interview, the surgeon names Viz.ai and describes an unnamed ICU nurse whose circumstances match Knichel’s hospital story. He does not explicitly connect her name to the product (references 1–3)." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "provider": "Viz.ai", "attribution": "inferred", "basis": "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred." } }, "provenance": { "kind": "derivation", "basis": "Snelling names Viz.ai as software used by the hospital, then discusses workflows and an unnamed ICU nurse whose circumstances match Knichel’s. The original video does not explicitly connect her name to the product. The attribution remains inferred.", "record_fields": [ "developer", "system" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Viz.ai, inferred from the surgeon’s separate interview.", "editor_note": "" } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI flags Julie Knichel's brain hemorrhage before aneurysm treatment and her return to nursing", "headline": "Doctors found a nurse’s brain bleed with help from AI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2e3e3df9046689dd81d56e536fd692f7e4e834745f330a46e124736af5bf6e5f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after the homepage copy revision.", "record_fields": [ "summary", "revisions" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Julie Knichel, a 57-year-old nurse, suffered a ruptured brain aneurysm. At Baptist Health's Marcus Neuroscience Institute, AI reviewed her scan and alerted clinicians to the bleeding. They sealed the aneurysm with coils delivered through a catheter. After about three weeks in hospital, she recovered and returned to full-time nursing. Her symptoms began on 2 February 2024. Baptist Health gives the day and month, and Jan Engoren’s subsequent interviews with Knichel and Snelling establish the year. The surgeon names Viz.ai in a later interview and describes an unnamed ICU nurse whose circumstances match Knichel’s. The product attribution is therefore inferred. Neither account identifies the module or release.", "replication": { "produced_by": [ "AI-assisted imaging and specialist treatment." ], "must_hold": [ "Prompt clinical review and access to aneurysm treatment." ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0582-source-0001", "AIBD-0582-source-0002", "AIBD-0582-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Software detected bleeding in brain images and alerted clinicians. The treating team investigated and treated the aneurysm.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 20, "record_mapped": 14, "not_assessed": 57, "complete": false, "by_state": { "value_present": 32, "not_reported": 2, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0013", "title": "Vesuvius Challenge 2023: machine-learning ink detection reads over 2,000 characters from unopened Herculaneum scroll PHerc.Paris.4", "summary": "ML ink detection let contestants read 2,000+ characters of a sealed Herculaneum scroll; papyrologists confirmed the text (Feb 2024).", "date_observed": "2024-02-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 12 October 2023 the Vesuvius Challenge announced that contestant Luke Farritor, a 21-year-old student, had read ΠΟΡΦΥΡΑϹ (“purple”) inside the unopened Herculaneum scroll PHerc.Paris.4. He used a machine-learning model trained on the “crackle” pattern of ink visible in X-ray computed tomography (CT) scans. On 5 February 2024 the organizers gave the $700,000 grand prize to Youssef Nader, Luke Farritor and Julian Schilliger. Their TimeSformer-based ink-detection models recovered 15 columns and more than 2,000 characters of Greek text. Papyrologists Federica Nicolardi, Richard Janko and Robert Fowler reviewed the passages, which discuss pleasure, food and music and are probably by Philodemus. The University of Kentucky, whose virtual-unwrapping software underlies the contest, called the result a new, readable Herculaneum text.", "category": "benefit created", "unexpected": false, "purpose": "Built to detect ink in X-ray CT scans of carbonized Herculaneum papyri so that the text can be read. This benefit was that purpose.", "system": "Vesuvius Challenge grand-prize ink-detection models (TimeSformer-based ensemble) applied to virtually unwrapped CT segments", "model_version": "2023 grand-prize submission (TimeSformer-based architecture combined with multiple model architectures)", "developer": "Youssef Nader, Luke Farritor and Julian Schilliger (contestants)", "deployer": "Vesuvius Challenge (co-founded by Brent Seales, University of Kentucky)", "location": null, "domain": "Humanities / papyrology", "segment": "Open competition / academic research", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Nader, Farritor and Schilliger shared a $700,000 prize announced by the organizers on 5 February 2024. Farritor had earlier won the First Letters prize for the first word." }, { "group": "organizational", "depth": 2, "reason": "The University of Kentucky program behind the virtual unwrapping, described by Seales as a 20-year dream, was validated with a readable text." }, { "group": "societal", "depth": 3, "reason": "A previously unknown Greek philosophical text became readable. Nature reports that the method paves the way to deciphering the rest of the scrolls." } ], "ai_role": { "status": "assessed", "statement": "The contestants' ink-detection models produced the ink images from which papyrologists read the text. The ink is not visible in the raw CT data. Virtual unwrapping (non-AI) was a necessary precondition. The readings were validated by an independent papyrological review organized by the contest." }, "evidence": [ { "kind": "press release", "citation": "Vesuvius Challenge (2024). 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UKNow.", "title": "'Grand Prize' discovery made from 2,000-year-old Herculaneum scrolls", "url": "https://uknow.uky.edu/research/grand-prize-discovery-made-2000-year-old-herculaneum-scrolls", "date": "2024-02-05", "written_by": "deployer", "quote": "The grand prize contestants have clearly demonstrated what our systematic experimental framework envisioned: that virtual unwrapping and AI techniques together can deliver substantial texts" }, { "kind": "news report", "citation": "Marchant, J. (2024). First passages of rolled-up Herculaneum scroll revealed. Nature news.", "title": "First passages of rolled-up Herculaneum scroll revealed", "url": "https://www.nature.com/articles/d41586-024-00346-8", "date": "2024-02-05", "written_by": "independent", "quote": "trained their machine-learning algorithms on scans of the rolled-up papyrus" }, { "kind": "press release", "citation": "Bodleian Libraries. Inside of Herculaneum scroll seen for the first time in almost 2,000 years. 5 February 2025.", "title": "Inside of Herculaneum scroll seen for the first time in almost 2,000 years", "url": "https://www.bodleian.ox.ac.uk/about/media/feb25/herculaneum-scroll", "date": "2025-02-05", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ML ink detection let contestants read 2,000+ characters of a sealed Herculaneum scroll; papyrologists confirmed the text (Feb 2024).", "account": "On 12 October 2023 the Vesuvius Challenge announced that contestant Luke Farritor, a 21-year-old student, had read ΠΟΡΦΥΡΑϹ (“purple”) inside the unopened Herculaneum scroll PHerc.Paris.4. He used a machine-learning model trained on the “crackle” pattern of ink visible in X-ray computed tomography (CT) scans. On 5 February 2024 the organizers gave the $700,000 grand prize to Youssef Nader, Luke Farritor and Julian Schilliger. Their TimeSformer-based ink-detection models recovered 15 columns and more than 2,000 characters of Greek text. Papyrologists Federica Nicolardi, Richard Janko and Robert Fowler reviewed the passages, which discuss pleasure, food and music and are probably by Philodemus. The University of Kentucky, whose virtual-unwrapping software underlies the contest, called the result a new, readable Herculaneum text." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The models detected traces of ink in CT images of the scrolls." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The model was part of the 2023 grand-prize submission to the Vesuvius Challenge." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The submission combined a TimeSformer-based model with other architectures." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "2023 grand-prize submission (TimeSformer-based architecture combined with multiple model architectures)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Vesuvius Challenge grand-prize ink-detection models (TimeSformer-based ensemble) applied to virtually unwrapped CT segments" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Youssef Nader, Luke Farritor and Julian Schilliger (contestants)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Vesuvius Challenge 2023: machine-learning ink detection reads over 2,000 characters from unopened Herculaneum scroll PHerc.Paris.4", "headline": "ML ink detection reads 2,000+ characters of a Herculaneum scroll" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "69be89d05e9a4d4a1d283e09bee7b34a3d166f1e192bab160292b6e0df88ba2a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 12 October 2023 the Vesuvius Challenge announced that contestant Luke Farritor, a 21-year-old student, had read ΠΟΡΦΥΡΑϹ (“purple”) inside the unopened Herculaneum scroll PHerc.Paris.4. He used a machine-learning model trained on the “crackle” pattern of ink visible in X-ray computed tomography (CT) scans. On 5 February 2024 the organizers gave the $700,000 grand prize to Youssef Nader, Luke Farritor and Julian Schilliger. Their TimeSformer-based ink-detection models recovered 15 columns and more than 2,000 characters of Greek text. Papyrologists Federica Nicolardi, Richard Janko and Robert Fowler reviewed the passages, which discuss pleasure, food and music and are probably by Philodemus. The University of Kentucky, whose virtual-unwrapping software underlies the contest, called the result a new, readable Herculaneum text.", "replication": { "produced_by": [ "High-resolution synchrotron CT scan of a carbonized scroll", "Virtual unwrapping into flattened segments", "Ink-detection model trained on labeled crackle/ink texture", "Independent papyrological review of the output" ], "must_hold": [ "Ink must produce a detectable texture or density signal in the CT data", "Segmentation must be accurate enough to preserve letter order", "Readings must be confirmed by papyrologists, not only by model output" ], "echoes": [ { "date": "2025-02-05", "setting": "PHerc. 172 (Bodleian Libraries, Oxford), scanned at Diamond Light Source in July 2024; machine-learning ink detection revealed columns of text including the word διατροπή", "outcome": "recurred", "source": "https://www.bodleian.ox.ac.uk/about/media/feb25/herculaneum-scroll" }, { "date": "2025-05-05", "setting": "First Title Prize: Marcel Roth and Micha Nowak read the end-title of PHerc. 172; a papyrological team led by Federica Nicolardi unanimously read the author as Philodemus and the title as On Vices; the book number is probably 1", "outcome": "recurred", "source": "https://scrollprize.substack.com/p/60000-first-title-prize-awarded ; https://www.herculaneum.ox.ac.uk/index.php/2025/05/06/60000-first-title-prize-awarded/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 41, "reviewed": 0, "record_mapped": 41, "not_assessed": 50, "complete": false, "by_state": { "value_present": 41, "not_reported": 0, "unresolved": 0, "not_assessed": 50, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0101", "title": "AI thermal-camera early warning stops trains for elephants at Madukkarai, Tamil Nadu", "summary": "TN Forest Dept AI cameras on a 7.05 km rail stretch: 7,116+ alerts, thousands of train stops, zero elephant deaths since Feb 2024.", "date_observed": "2024-02-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Tamil Nadu Forest Department installed 24 hybrid thermal cameras with AI detection on 12 towers. They cover 7.05 km of the Ettimadai–Walayar railway section in Madukkarai forest range, Coimbatore district. They have operated since 9 February 2024. A trial run already generated alerts by 7 January 2024. Alerts go to a control room at Puthupathi. Its staff warn station masters and loco pilots and drive elephants away from the tracks. By 7 July 2026 the department's Additional Chief Secretary reported over 7,116 alerts and 3,281 train slow-downs or stops (DT Next reports 3,821). It also gave about 9,481 safe elephant crossings and no elephant deaths on the stretch. Eleven elephants were killed there between 2008 and 2022.", "category": "protective response", "unexpected": false, "purpose": "Detect elephants near railway tracks with thermal cameras and AI, alert forest staff and railway crews, and prevent train-elephant collisions.", "system": "AI-based elephant early warning system (24 hybrid thermal cameras on 12 towers, Elephant Control and Command Center, Puthupathi)", "model_version": null, "developer": null, "deployer": "Tamil Nadu Forest Department (Department of Environment, Climate Change and Forests), with railway station masters at Walayar and Ettimadai and loco pilots", "location": "Madukkarai, Coimbatore district, India", "domain": "Conservation and biodiversity", "segment": "Wildlife protection / railway operations", "benefit_type": "Increased Product Safety", "taxonomy_note": "The collisions avoided are between trains and elephants, so the gain is shared with conservation.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The reports count train stops and crossings, not injuries avoided by crews or passengers." }, { "group": "organizational", "depth": 2, "reason": "The Forest Department reports zero elephant deaths on a stretch that recorded eleven deaths from 2008 to 2022, including three in November 2021." }, { "group": "societal", "depth": 3, "reason": "Reported 9,481 safe crossings and no track deaths for wild elephants on a stretch that recorded eleven deaths from 2008 to 2022. The number of deaths that would otherwise have occurred remains unknown." } ], "ai_role": { "status": "assessed", "statement": "AI classification of thermal-camera feeds generated the alerts that triggered staff intervention and train slow-downs. The figures (alerts, stops, crossings, zero deaths) are the department's own statements as reproduced verbatim in news reports. No official document is among the sources. No per-event counterfactual is established." }, "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range.", "title": "AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range", "url": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "date": "2026-07-08", "written_by": "independent", "quote": "has generated more than 7,116 real-time alerts regarding animal movement, leading to 3,281 instances of loco pilots stopping or slowing down trains" }, { "kind": "news report", "citation": "The New Indian Express (2025). No elephant deaths on railway tracks in Madukkarai stretch in 22 months.", "title": "No elephant deaths on railway tracks in Madukkarai stretch in 22 months", "url": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "date": "2025-12-21", "written_by": "independent", "quote": "Two dozen 360-degree-wide hybrid thermal cameras have been functioning since February 9, 2024 for a 7.05-kilometre distance" }, { "kind": "news report", "citation": "India Today (2025). Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants.", "title": "Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants", "url": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12", "date": "2025-08-12", "written_by": "independent", "quote": "In Madukkarai, the AI-powered early warning system has ensured zero elephant deaths on rail tracks since Nov 2023." }, { "kind": "news report", "citation": "DT Next (2026). AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths.", "title": "AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths", "url": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths", "date": "2026-07-07", "written_by": "independent", "quote": "resulting in 3,821 instances where trains were slowed down or halted to allow elephants to cross tracks safely" }, { "kind": "news report", "citation": "The Hindu (2024). Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants.", "title": "Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants", "url": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece", "date": "2024-01-07", "written_by": "independent", "quote": "Their intervention based on the early warning has already prevented several elephants from walking along the tracks or crossing them before train movement." } ], "replication": { "produced_by": [ "Thermal cameras covering a known elephant crossing corridor", "24-hour staffed control room that relays alerts to station masters and loco pilots", "Field staff able to move elephants away from the track", "Railway agreement to slow or stop trains on alert" ], "must_hold": [ "Camera coverage of the full vulnerable section", "Low false-alert rate so crews keep responding", "Communication chain (intercom, walkie-talkie, WhatsApp) functioning at night", "Elephant movement continuing to cross at monitored points" ], "echoes": [ { "date": "2024-01-07", "setting": "Trial run, same stretch, alerts to Forest Department only", "model_version": null, "outcome": "recurred", "source": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece" }, { "date": "2025-08-12", "setting": "Department statement: 6,592 safe crossings, zero deaths since Nov 2023", "model_version": null, "outcome": "recurred", "source": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12" }, { "date": "2026-07-07", "setting": "Department statement at 2.5 years: 9,481 crossings, zero deaths", "model_version": null, "outcome": "recurred", "source": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "severity": null, "group": "societal", "basis": "AI wildlife-reserve cameras failed to detect intruders and four rhinos were killed; Madukkarai's thermal cameras are the same detection-to-alert design protecting elephants." }, "headline": "AI thermal cameras stop trains for elephants at Madukkarai", "metric": "about 9,481 safe elephant crossings and no elephant deaths on the stretch", "comparator": { "against": "the same 7.05 km Madukkarai railway stretch before the cameras (2008 to 2022)", "before": "Eleven wild elephants were killed on railway tracks in Madukkarai stretch from 2008 to 2022", "after": "no elephant deaths on the railway tracks in the last 22 months (as of 21 December 2025)", "basis": "measured", "quote": "Eleven wild elephants were killed on railway tracks in Madukkarai stretch from 2008 to 2022 with the last being reported in November 2021 when three elephants died.", "url": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months" }, "later": { "status": "persisted", "date": "2026-07-08", "note": "At two and a half years the department reported about 9,481 safe crossings and still no elephant deaths on the stretch, and had added AI-powered drones to extend surveillance beyond the fixed cameras.", "quote": "\"These are the unsung heroes whose constant vigilance, dedication, and hard work have facilitated around 9,481 safe elephant crossings, ensuring zero elephant deaths on railway tracks and demonstrating how technology, human vigilance, and teamwork can come together to protect wildlife,\" said Supriya Sahu.", "url": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range" }, "value": null, "developer_country": null, "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “Southern Railway” in deployer with the sources' station masters at Walayar and Ettimadai and loco pilots, restated the trial as already generating alerts by 7 January 2024 rather than beginning then, attributed the zero-deaths figure to the Forest Department alone and dropped “endangered” from the societal reason, because no cited source names Southern Railway, dates the trial's start, quotes the railway on deaths or calls the elephants endangered.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range; https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece; https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months; https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tamil_Nadu_Forest_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0101", "catalog_version": "1.0.0", "source_fingerprint": "457b98c55b5eb77a2c5d54faa3fb9712f6689ce678abccfa92e2bfaa11b4378e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0101-source-0001", "AIBD-0101-source-0002", "AIBD-0101-source-0003", "AIBD-0101-source-0004", "AIBD-0101-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Tamil Nadu Forest Department (Department of Environment, Climate Change and Forests), with railway station masters at Walayar and Ettimadai and loco pilots" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AI classification of thermal-camera feeds generated the alerts that triggered staff intervention and train slow-downs. The figures (alerts, stops, crossings, zero deaths) are the department's own statements as reproduced verbatim in news reports. No official document is among the sources. No per-event counterfactual is established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "AI classification of thermal-camera feeds generated the alerts that triggered staff intervention and train slow-downs. The figures (alerts, stops, crossings, zero deaths) are the department's own statements as reproduced verbatim in news reports. No official document is among the sources. No per-event counterfactual is established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports count train stops and crossings, not injuries avoided by crews or passengers." }, { "group": "organizational", "depth": 2, "reason": "The Forest Department reports zero elephant deaths on a stretch that recorded eleven deaths from 2008 to 2022, including three in November 2021." }, { "group": "societal", "depth": 3, "reason": "Reported 9,481 safe crossings and no track deaths for wild elephants on a stretch that recorded eleven deaths from 2008 to 2022. The number of deaths that would otherwise have occurred remains unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports count train stops and crossings, not injuries avoided by crews or passengers." }, { "group": "organizational", "depth": 2, "reason": "The Forest Department reports zero elephant deaths on a stretch that recorded eleven deaths from 2008 to 2022, including three in November 2021." }, { "group": "societal", "depth": 3, "reason": "Reported 9,481 safe crossings and no track deaths for wild elephants on a stretch that recorded eleven deaths from 2008 to 2022. The number of deaths that would otherwise have occurred remains unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports count train stops and crossings, not injuries avoided by crews or passengers." }, { "group": "organizational", "depth": 2, "reason": "The Forest Department reports zero elephant deaths on a stretch that recorded eleven deaths from 2008 to 2022, including three in November 2021." }, { "group": "societal", "depth": 3, "reason": "Reported 9,481 safe crossings and no track deaths for wild elephants on a stretch that recorded eleven deaths from 2008 to 2022. The number of deaths that would otherwise have occurred remains unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "AI wildlife-reserve cameras failed to detect intruders and four rhinos were killed; Madukkarai's thermal cameras are the same detection-to-alert design protecting elephants.", "links": [ { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "group": "societal", "basis": "AI wildlife-reserve cameras failed to detect intruders and four rhinos were killed; Madukkarai's thermal cameras are the same detection-to-alert design protecting elephants.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "about 9,481 safe elephant crossings and no elephant deaths on the stretch", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "group": "societal", "basis": "AI wildlife-reserve cameras failed to detect intruders and four rhinos were killed; Madukkarai's thermal cameras are the same detection-to-alert design protecting elephants." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-07-08", "note": "At two and a half years the department reported about 9,481 safe crossings and still no elephant deaths on the stretch, and had added AI-powered drones to extend surveillance beyond the fixed cameras.", "quote": "\"These are the unsung heroes whose constant vigilance, dedication, and hard work have facilitated around 9,481 safe elephant crossings, ensuring zero elephant deaths on railway tracks and demonstrating how technology, human vigilance, and teamwork can come together to protect wildlife,\" said Supriya Sahu.", "url": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0101" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "The collisions avoided are between trains and elephants, so the gain is shared with conservation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tamil Nadu Forest Department installed 24 hybrid thermal cameras with AI detection on 12 towers. They cover 7.05 km of the Ettimadai–Walayar railway section in Madukkarai forest range, Coimbatore district. They have operated since 9 February 2024. A trial run already generated alerts by 7 January 2024. Alerts go to a control room at Puthupathi. Its staff warn station masters and loco pilots and drive elephants away from the tracks. By 7 July 2026 the department's Additional Chief Secretary reported over 7,116 alerts and 3,281 train slow-downs or stops (DT Next reports 3,821). It also gave about 9,481 safe elephant crossings and no elephant deaths on the stretch. Eleven elephants were killed there between 2008 and 2022.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The reports count train stops and crossings, not injuries avoided by crews or passengers." }, { "group": "organizational", "depth": 2, "reason": "The Forest Department reports zero elephant deaths on a stretch that recorded eleven deaths from 2008 to 2022, including three in November 2021." }, { "group": "societal", "depth": 3, "reason": "Reported 9,481 safe crossings and no track deaths for wild elephants on a stretch that recorded eleven deaths from 2008 to 2022. The number of deaths that would otherwise have occurred remains unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect elephants near railway tracks with thermal cameras and AI, alert forest staff and railway crews, and prevent train-elephant collisions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Madukkarai, Coimbatore district, India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect elephants near railway tracks with thermal cameras and AI, alert forest staff and railway crews, and prevent train-elephant collisions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-02-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “Southern Railway” in deployer with the sources' station masters at Walayar and Ettimadai and loco pilots, restated the trial as already generating alerts by 7 January 2024 rather than beginning then, attributed the zero-deaths figure to the Forest Department alone and dropped “endangered” from the societal reason, because no cited source names Southern Railway, dates the trial's start, quotes the railway on deaths or calls the elephants endangered.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range; https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece; https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months; https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tamil_Nadu_Forest_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Thermal cameras covering a known elephant crossing corridor", "24-hour staffed control room that relays alerts to station masters and loco pilots", "Field staff able to move elephants away from the track", "Railway agreement to slow or stop trains on alert" ], "must_hold": [ "Camera coverage of the full vulnerable section", "Low false-alert rate so crews keep responding", "Communication chain (intercom, walkie-talkie, WhatsApp) functioning at night", "Elephant movement continuing to cross at monitored points" ], "echoes": [ { "date": "2024-01-07", "setting": "Trial run, same stretch, alerts to Forest Department only", "outcome": "recurred", "source": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece" }, { "date": "2025-08-12", "setting": "Department statement: 6,592 safe crossings, zero deaths since Nov 2023", "outcome": "recurred", "source": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12" }, { "date": "2026-07-07", "setting": "Department statement at 2.5 years: 9,481 crossings, zero deaths", "outcome": "recurred", "source": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Thermal cameras covering a known elephant crossing corridor", "24-hour staffed control room that relays alerts to station masters and loco pilots", "Field staff able to move elephants away from the track", "Railway agreement to slow or stop trains on alert" ], "must_hold": [ "Camera coverage of the full vulnerable section", "Low false-alert rate so crews keep responding", "Communication chain (intercom, walkie-talkie, WhatsApp) functioning at night", "Elephant movement continuing to cross at monitored points" ], "echoes": [ { "date": "2024-01-07", "setting": "Trial run, same stretch, alerts to Forest Department only", "outcome": "recurred", "source": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece" }, { "date": "2025-08-12", "setting": "Department statement: 6,592 safe crossings, zero deaths since Nov 2023", "outcome": "recurred", "source": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12" }, { "date": "2026-07-07", "setting": "Department statement at 2.5 years: 9,481 crossings, zero deaths", "outcome": "recurred", "source": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced “Southern Railway” in deployer with the sources' station masters at Walayar and Ettimadai and loco pilots, restated the trial as already generating alerts by 7 January 2024 rather than beginning then, attributed the zero-deaths figure to the Forest Department alone and dropped “endangered” from the societal reason, because no cited source names Southern Railway, dates the trial's start, quotes the railway on deaths or calls the elephants endangered.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range; https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece; https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months; https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tamil_Nadu_Forest_Department", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Conservation and biodiversity", "segment": "Wildlife protection / railway operations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range.", "title": "AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range", "url": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "date": "2026-07-08", "written_by": "independent", "quote": "has generated more than 7,116 real-time alerts regarding animal movement, leading to 3,281 instances of loco pilots stopping or slowing down trains" }, { "kind": "news report", "citation": "The New Indian Express (2025). No elephant deaths on railway tracks in Madukkarai stretch in 22 months.", "title": "No elephant deaths on railway tracks in Madukkarai stretch in 22 months", "url": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "date": "2025-12-21", "written_by": "independent", "quote": "Two dozen 360-degree-wide hybrid thermal cameras have been functioning since February 9, 2024 for a 7.05-kilometre distance" }, { "kind": "news report", "citation": "India Today (2025). Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants.", "title": "Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants", "url": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12", "date": "2025-08-12", "written_by": "independent", "quote": "In Madukkarai, the AI-powered early warning system has ensured zero elephant deaths on rail tracks since Nov 2023." }, { "kind": "news report", "citation": "DT Next (2026). AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths.", "title": "AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths", "url": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths", "date": "2026-07-07", "written_by": "independent", "quote": "resulting in 3,821 instances where trains were slowed down or halted to allow elephants to cross tracks safely" }, { "kind": "news report", "citation": "The Hindu (2024). Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants.", "title": "Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants", "url": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece", "date": "2024-01-07", "written_by": "independent", "quote": "Their intervention based on the early warning has already prevented several elephants from walking along the tracks or crossing them before train movement." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0101-source-0001", "AIBD-0101-source-0002", "AIBD-0101-source-0003", "AIBD-0101-source-0004", "AIBD-0101-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range.", "title": "AI camera system along railway tracks ends jumbo deaths in Madukkarai forest range", "url": "https://www.newindianexpress.com/states/tamil-nadu/2026/Jul/08/ai-camera-system-along-railway-tracks-ends-jumbo-deaths-in-madukkarai-forest-range", "date": "2026-07-08", "written_by": "independent", "quote": "has generated more than 7,116 real-time alerts regarding animal movement, leading to 3,281 instances of loco pilots stopping or slowing down trains" }, { "kind": "news report", "citation": "The New Indian Express (2025). No elephant deaths on railway tracks in Madukkarai stretch in 22 months.", "title": "No elephant deaths on railway tracks in Madukkarai stretch in 22 months", "url": "https://www.newindianexpress.com/states/tamil-nadu/2025/Dec/21/no-elephant-deaths-on-railway-tracks-in-madukkarai-stretch-in-22-months", "date": "2025-12-21", "written_by": "independent", "quote": "Two dozen 360-degree-wide hybrid thermal cameras have been functioning since February 9, 2024 for a 7.05-kilometre distance" }, { "kind": "news report", "citation": "India Today (2025). Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants.", "title": "Tamil Nadu Forest Department shares video showing how AI ensures safety of elephants", "url": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12", "date": "2025-08-12", "written_by": "independent", "quote": "In Madukkarai, the AI-powered early warning system has ensured zero elephant deaths on rail tracks since Nov 2023." }, { "kind": "news report", "citation": "DT Next (2026). AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths.", "title": "AI powered elephant alert system enables 9,481 safe crossings, records zero train track deaths", "url": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths", "date": "2026-07-07", "written_by": "independent", "quote": "resulting in 3,821 instances where trains were slowed down or halted to allow elephants to cross tracks safely" }, { "kind": "news report", "citation": "The Hindu (2024). Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants.", "title": "Trial run of AI-based early warning system near Coimbatore proves promising as field staff save elephants", "url": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece", "date": "2024-01-07", "written_by": "independent", "quote": "Their intervention based on the early warning has already prevented several elephants from walking along the tracks or crossing them before train movement." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "TN Forest Dept AI cameras on a 7.05 km rail stretch: 7,116+ alerts, thousands of train stops, zero elephant deaths since Feb 2024.", "account": "The Tamil Nadu Forest Department installed 24 hybrid thermal cameras with AI detection on 12 towers. They cover 7.05 km of the Ettimadai–Walayar railway section in Madukkarai forest range, Coimbatore district. They have operated since 9 February 2024. A trial run already generated alerts by 7 January 2024. Alerts go to a control room at Puthupathi. Its staff warn station masters and loco pilots and drive elephants away from the tracks. By 7 July 2026 the department's Additional Chief Secretary reported over 7,116 alerts and 3,281 train slow-downs or stops (DT Next reports 3,821). It also gave about 9,481 safe elephant crossings and no elephant deaths on the stretch. Eleven elephants were killed there between 2008 and 2022." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI-based elephant early warning system (24 hybrid thermal cameras on 12 towers, Elephant Control and Command Center, Puthupathi)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI thermal-camera early warning stops trains for elephants at Madukkarai, Tamil Nadu", "headline": "AI thermal cameras stop trains for elephants at Madukkarai" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "457b98c55b5eb77a2c5d54faa3fb9712f6689ce678abccfa92e2bfaa11b4378e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Tamil Nadu Forest Department installed 24 hybrid thermal cameras with AI detection on 12 towers. They cover 7.05 km of the Ettimadai–Walayar railway section in Madukkarai forest range, Coimbatore district. They have operated since 9 February 2024. A trial run already generated alerts by 7 January 2024. Alerts go to a control room at Puthupathi. Its staff warn station masters and loco pilots and drive elephants away from the tracks. By 7 July 2026 the department's Additional Chief Secretary reported over 7,116 alerts and 3,281 train slow-downs or stops (DT Next reports 3,821). It also gave about 9,481 safe elephant crossings and no elephant deaths on the stretch. Eleven elephants were killed there between 2008 and 2022.", "replication": { "produced_by": [ "Thermal cameras covering a known elephant crossing corridor", "24-hour staffed control room that relays alerts to station masters and loco pilots", "Field staff able to move elephants away from the track", "Railway agreement to slow or stop trains on alert" ], "must_hold": [ "Camera coverage of the full vulnerable section", "Low false-alert rate so crews keep responding", "Communication chain (intercom, walkie-talkie, WhatsApp) functioning at night", "Elephant movement continuing to cross at monitored points" ], "echoes": [ { "date": "2024-01-07", "setting": "Trial run, same stretch, alerts to Forest Department only", "outcome": "recurred", "source": "https://www.thehindu.com/news/cities/Coimbatore/trial-run-of-ai-based-early-warning-system-near-coimbatore-proves-promising-as-field-staff-save-elephants/article67716099.ece" }, { "date": "2025-08-12", "setting": "Department statement: 6,592 safe crossings, zero deaths since Nov 2023", "outcome": "recurred", "source": "https://www.indiatoday.in/trending-news/story/tamil-nadu-forest-department-shares-video-showing-how-ai-ensures-safety-of-elephants-2770278-2025-08-12" }, { "date": "2026-07-07", "setting": "Department statement at 2.5 years: 9,481 crossings, zero deaths", "outcome": "recurred", "source": "https://www.dtnext.in/news/tamilnadu/ai-powered-elephant-alert-system-enables-9481-safe-crossings-records-zero-train-track-deaths" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0165", "title": "Princeton deep RL controller steers DIII-D plasmas clear of tearing instability; only two of the controlled shots disrupt", "summary": "An RL controller trained on a tearing-likelihood model kept DIII-D plasmas below the instability threshold; before RL control all but one shot disrupted, after it only two did (Nature, 21 Feb 2024).", "date_observed": "2024-02-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Seo et al. (Nature, published 21 February 2024), from Princeton University, the Princeton Plasma Physics Laboratory and partners, trained a reinforcement-learning (RL) controller. Its training environment was built from a multimodal dynamic model that estimates the likelihood of future tearing instability, the leading cause of disruptions. It was deployed on DIII-D, the largest magnetic fusion facility in the United States, at General Atomics in San Diego. It adjusted total beam power and plasma triangularity to keep the estimated tearability under a threshold while maintaining H-mode performance. It did so even at low safety factor and low torque. In the experimental session, discharges up to 193276 either had no RL control or tore before control started. Of the controlled discharges from 193277, only two (193277 and 193282) were disrupted. Before RL control all shots except one were disrupted. Average time-integrated normalized beta rose. Princeton Engineering's release (21 February 2024) says the model could forecast tearing mode instabilities up to 300 milliseconds in advance. The OECD AI Incidents Monitor logged the result as a positive outcome. The experiment dates are not given.", "category": "benefit created", "unexpected": false, "purpose": "The controller was built to avoid tearing instability while maintaining high-pressure plasma in DIII-D. The avoided disruptions were its intended use.", "system": "Deep reinforcement learning tearing-avoidance controller with a DNN tearability predictor (Keras model converted to real-time C)", "model_version": null, "developer": "Princeton University / Princeton Plasma Physics Laboratory (Kolemen group), with Chung-Ang University", "deployer": "DIII-D National Fusion Facility, General Atomics", "location": "San Diego, United States", "domain": "Energy research (magnetic confinement fusion)", "segment": "Tokamak plasma control", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The gain is control performance in a fusion experiment rather than accuracy of a human task.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The DIII-D session obtained plasmas tracking a stable path with fewer disruptions and higher time-integrated beta. The paper calls it a path toward ITER-relevant scenarios." }, { "group": "societal", "depth": null, "reason": "No outcome beyond fusion research is documented." } ], "ai_role": { "status": "assessed", "statement": "The RL controller set the high-level actuator commands that the plasma control system executed. The disruption outcomes in the controlled shots are therefore attributable to it. The comparison is within one session, and the paper is authored by the system's developers. Independent evaluation is the journal's peer review and the OECD AIM registry entry." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Seo, J., Kim, S., Jalalvand, A. et al., 'Avoiding fusion plasma tearing instability with deep reinforcement learning', Nature (2024), doi:10.1038/s41586-024-07024-9", "title": "Avoiding fusion plasma tearing instability with deep reinforcement learning", "url": "https://www.nature.com/articles/s41586-024-07024-9", "date": "2024-02-21", "written_by": "makers", "quote": "We demonstrate artificial intelligence control to lower the possibility of disruptive tearing instabilities in DIII-D, the largest magnetic fusion facility in the United States." }, { "kind": "peer-reviewed study", "citation": "Seo et al., Nature 2024, results on controlled discharges", "title": "Avoiding fusion plasma tearing instability with deep reinforcement learning", "url": "https://www.nature.com/articles/s41586-024-07024-9", "date": "2024-02-21", "written_by": "makers", "quote": "after RL control was applied, only two (193277 and 193282) were disrupted" }, { "kind": "press release", "citation": "Princeton Engineering news, 'Engineers use AI to wrangle fusion power for the grid', 21 February 2024", "title": "Engineers use AI to wrangle fusion power for the grid", "url": "https://engineering.princeton.edu/news/2024/02/21/engineers-use-ai-wrangle-fusion-power-grid", "date": "2024-02-21", "written_by": "makers", "quote": "could forecast potential plasma instabilities known as tearing mode instabilities up to 300 milliseconds in advance" }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2024-02-24-7d77", "title": "AI Breakthrough Enables Real-Time Prediction and Prevention of Plasma Instabilities in Nuclear Fusion Reactors", "url": "https://oecd.ai/en/incidents/2024-02-24-7d77", "date": "2024-02-24", "written_by": "independent", "quote": "This is a clear example of AI use leading to a positive outcome by preventing harm" } ], "replication": { "produced_by": [ "A database of past DIII-D discharges to train the tearability predictor", "Real-time profile reconstruction and equilibrium fitting feeding the DNN", "A plasma control system that accepts high-level beam-power and shape commands" ], "must_hold": [ "A tearability model valid for the operating regime", "Actuators (beam power, triangularity) able to move the plasma along the stable path", "Session-level comparison shots to judge disruption rates" ], "echoes": [ { "date": "2022-02-16", "setting": "TCV, Lausanne; DeepMind deep RL magnetic controller (different objective)", "model_version": null, "outcome": "recurred", "source": "https://www.nature.com/articles/s41586-021-04301-9" } ] }, "paired_incident": null, "headline": "Princeton RL controller cuts DIII-D disruptions to two shots", "metric": "before RL control all but one shot disrupted, after it only two did", "comparator": { "against": "DIII-D discharges in the same experiment session without RL control", "before": "all shots except one (193266: low-βN reference shown in Fig. 3b) were disrupted", "after": "only two (193277 and 193282) were disrupted", "basis": "measured", "quote": "Before RL control, all shots except one (193266: low-βN reference shown in Fig. 3b) were disrupted, but after RL control was applied, only two (193277 and 193282) were disrupted, which were discussed earlier.", "url": "https://www.nature.com/articles/s41586-024-07024-9" }, "later": { "status": "unknown", "date": null, "note": "Later DIII-D papers from the same group describe successor tearing-mode controllers but no further result for this RL controller was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; 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They tested it with FEV Tutor, a virtual tutoring provider, and a large southern U.S. school district serving over 30,000 students. Nine schools took part. The district identified 1,787 students in grades 3–8, 80% Hispanic, who had performed below grade level. The preprint (arXiv, 3 October 2024) says that the study started at the end of March 2024 and lasted two months. The 900 tutors were evenly split between treatment and control. Students of treated tutors were 4 percentage points more likely to master topics. Students of lower-rated tutors gained 9 points, at about $20 per tutor per year. Education Week (31 October 2024), quoting co-author Susanna Loeb, reported that tutors using the tool were more likely to prompt students to explain. They were less likely to give away solutions. The 74 (7 October 2024) and MIT Technology Review (28 October 2024) reported that the system runs on OpenAI's GPT-4. 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The measured change runs through tutor behavior (more prompting for explanations, fewer given-away solutions). Outside researchers quoted by MIT Technology Review note that the mathematics was relatively basic." }, "evidence": [ { "kind": "preprint", "citation": "Wang RE et al. Tutor CoPilot, arXiv:2410.03017v2 (study start and partner details).", "title": "Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise (v2 PDF)", "url": "https://arxiv.org/pdf/2410.03017v2", "date": "2025-01-26", "written_by": "makers", "quote": "We partnered with FEV Tutor (a virtual tutoring provider) and a large southern U.S. school district." }, { "kind": "other", "citation": "Rose E. Wang, Tutor_CoPilot_Demo.ipynb, commit 25c6eab7e416614f2033358bceddd30a4d5ca616, October 28, 2024.", "title": "Tutor CoPilot demonstration notebook", "url": "https://github.com/rosewang2008/tutor-copilot/blob/25c6eab7e416614f2033358bceddd30a4d5ca616/Tutor_CoPilot_Demo.ipynb", "date": "2024-10-28", "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Langreo L (31 Oct 2024). What Happens When an AI Assistant Helps the Tutor, Instead of the Student. Education Week (quotes Susanna Loeb, Stanford).", "title": "What Happens When an AI Assistant Helps the Tutor, Instead of the Student", "url": "https://www.edweek.org/technology/what-happens-when-an-ai-assistant-helps-the-tutor-instead-of-the-student/2024/10", "date": "2024-10-31", "written_by": "independent", "quote": "The tutors using Tutor CoPilot were more likely to prompt students to explain and ask guiding questions, and significantly less likely to give away solutions." }, { "kind": "news report", "citation": "Toppo G (7 Oct 2024). Study: AI-Assisted Tutoring Boosts Students' Math Skills. The 74 (quotes Rose E. Wang, Susanna Loeb, Amanda Bickerstaff, Benjamin Riley, Dan Meyer).", "title": "Study: AI-Assisted Tutoring Boosts Students' Math Skills", "url": "https://www.the74million.org/article/study-ai-assisted-tutoring-boosts-students-math-skills/", "date": "2024-10-07", "written_by": "independent", "quote": "The big dream is to be able to enhance humans." }, { "kind": "news report", "citation": "Williams R (28 Oct 2024). This AI system makes human tutors better at teaching children math. MIT Technology Review (quotes Rose Wang, Simon Frieder of Oxford, Mina Lee of Chicago).", "title": "This AI system makes human tutors better at teaching children math", "url": "https://www.technologyreview.com/2024/10/28/1106251/this-ai-system-makes-human-tutors-better-at-teaching-children-math/", "date": "2024-10-28", "written_by": "independent", "quote": "The tool isn't designed to actually teach the students math." } ], "replication": { "produced_by": [ "A language model prompted with a taxonomy of expert tutoring moves rather than answers", "Integration into a live virtual-tutoring platform where tutors can request suggestions mid-session", "Tutor-level randomization (900 tutors) with preregistered analysis" ], "must_hold": [ "Human tutors willing to use suggestions in real time", "Basic-level mathematics content (outside researchers' caveat)", "Students below grade level in under-served schools, the population studied" ], "echoes": [] }, "paired_incident": null, "headline": "Stanford's Tutor CoPilot lifts math mastery 4 percentage points", "metric": "students of treated tutors were 4 percentage points more likely to master topics", "comparator": { "against": "students of control-group tutors on the same platform who did not have access to Tutor CoPilot", "before": "62% student passing rate on exit tickets (control tutors)", "after": "66% passing rate (tutors with Tutor CoPilot), 4 percentage points higher", "basis": "measured", "quote": "Students working with treatment tutors were 4 percentage points (p.p.) more likely to pass their exit tickets (p< 0.01, 62% → 66% student passing rate from control to treatment).", "url": "https://arxiv.org/pdf/2410.03017v2" }, "later": { "status": "unknown", "date": null, "note": "The preprint was revised again on 10 October 2026, but no later deployment, replication or publication of the trial was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/pdf/2410.03017v2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.stanford.edu/about/; https://builtin.com/company/fev-tutor", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Stanford University.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified the AI model, software, configuration, and human controls from the original paper, supplement, or author documentation. 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It supplies 160 million liters a day to 300,000 homes and businesses in parts of Surrey, Kent and South London. It was among the first UK companies using AI across its whole network to reduce leaks. 1,000 underground sensors monitor flow and pressure. The technology predicts what levels should be. When a leak happens an alarm is raised within minutes and engineers deployed. Innovation manager Jeremy Heath said pipes are often repaired before customers notice a drop in pressure. Head of asset strategy Liam Ahearne said the smart network had reduced leakage run rate times by up to 40%. The BBC noted Ofwat's figure that about a fifth of water put into the network in England and Wales is lost to leakage. It gave SES Water's 2022/23 loss of 76 liters per property per day. It cited the Angling Trust's criticism that the company's targets were not good enough. The vendor and method are not named. No regulator report of a specific repaired burst was found.", "category": "general benefit", "unexpected": false, "purpose": "The smart network was built to detect leaks early from sensor data against predicted levels and dispatch repairs. The reduced run times are its intended use.", "system": "SES Water smart network: 1,000 flow and pressure sensors with AI-based predicted-level leak alarms (vendor not named)", "model_version": "Aquasuite Burst", "developer": null, "deployer": "Sutton and East Surrey (SES) Water", "location": "Surrey, United Kingdom", "domain": "Water infrastructure", "segment": "Water distribution leakage management", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": "The measured quantity is leak run time; the water saved is inferred, and Trustible's description names water consumption.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The up-to-40% reduction in leakage run rate times is the utility's own claim without an independent figure." }, { "group": "societal", "depth": null, "reason": "Leakage reduction targets (15% over five years) are stated as plans; no measured outcome is attributed to the AI." } ], "ai_role": { "status": "unassessed", "statement": "The BBC report, an independent source with named utility staff, describes the AI only in general terms (prediction of expected levels, alarms within minutes). 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The 40% figure is the deployer's claim, so the AI's share of any leakage reduction is unverified." }, "evidence": [ { "kind": "news report", "citation": "Yvette Austin, 'SES Water: Artificial intelligence helps reduce water leaks', BBC News, 11 March 2024", "title": "Artificial intelligence helps reduce water leaks", "url": "https://www.bbc.co.uk/news/articles/c4n5pwny536o", "date": "2024-03-11", "written_by": "independent", "quote": "Sutton and East Surrey (SES) Water has installed 1000 sensors underground that monitor flow and pressure, then send data back to base." }, { "kind": "news report", "citation": "BBC News, 11 March 2024 (Liam Ahearne, SES Water)", "title": "Artificial intelligence helps reduce water leaks", "url": "https://www.bbc.co.uk/news/articles/c4n5pwny536o", "date": "2024-03-11", "written_by": "independent", "quote": "Our smart network has enabled us to reduce our leakage run rate times by up to 40%." }, { "kind": "case report", "citation": "Royal HaskoningDHV (undated). SES Water achieves a 40% reduction in leak run time with Aquasuite. Haskoning project page.", "title": "SES Water achieves a 40% reduction in leak run time with Aquasuite", "url": "https://www.haskoning.com/en/projects/ses-water-achieves-a-reduction-in-leak-run-time", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Dense sensor coverage (1,000 flow and pressure sensors) across a compact supply area", "Predicted-versus-actual comparison raising alarms within minutes", "Repair crews dispatched on alarms rather than customer reports" ], "must_hold": [ "Sensor density and telemetry sufficient to localize anomalies", "Crew capacity to act on alarms quickly", "Independent reporting of leakage volumes to confirm the claimed effect" ], "echoes": [] }, "paired_incident": null, "headline": "SES Water's AI leak alarms may cut leakage run times by up to 40%", "metric": "reduced leakage run rate times by up to 40%", "comparator": { "against": "leak run times before the sensor network", "before": "previous leakage run rate times (not quantified)", "after": "reduce our leakage run rate times by up to 40%", "basis": "measured", "quote": "Our smart network has enabled us to reduce our leakage run rate times by up to 40%.", "url": "https://www.bbc.co.uk/news/articles/c4n5pwny536o" }, "later": { "status": "unknown", "date": null, "note": "No dated development after March 2024 was found; the vendor's undated case study repeats the 40% figure.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.bbc.co.uk/news/articles/c4n5pwny536o; https://www.haskoning.com/en/projects/ses-water-achieves-a-reduction-in-leak-run-time", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.seswater.co.uk/about-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' case report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0169", "catalog_version": "1.0.0", "source_fingerprint": "dbaab786bf860854009ad610e7138b10284f0fa325e2828b8d190cd27df6093f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0169-source-0001", "AIBD-0169-source-0002", "AIBD-0169-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Sutton and East Surrey (SES) Water" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The BBC report, an independent source with named utility staff, describes the AI only in general terms (prediction of expected levels, alarms within minutes). 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It supplies 160 million liters a day to 300,000 homes and businesses in parts of Surrey, Kent and South London. It was among the first UK companies using AI across its whole network to reduce leaks. 1,000 underground sensors monitor flow and pressure. The technology predicts what levels should be. When a leak happens an alarm is raised within minutes and engineers deployed. Innovation manager Jeremy Heath said pipes are often repaired before customers notice a drop in pressure. Head of asset strategy Liam Ahearne said the smart network had reduced leakage run rate times by up to 40%. The BBC noted Ofwat's figure that about a fifth of water put into the network in England and Wales is lost to leakage. It gave SES Water's 2022/23 loss of 76 liters per property per day. It cited the Angling Trust's criticism that the company's targets were not good enough. The vendor and method are not named. No regulator report of a specific repaired burst was found.", "replication": { "produced_by": [ "Dense sensor coverage (1,000 flow and pressure sensors) across a compact supply area", "Predicted-versus-actual comparison raising alarms within minutes", "Repair crews dispatched on alarms rather than customer reports" ], "must_hold": [ "Sensor density and telemetry sufficient to localize anomalies", "Crew capacity to act on alarms quickly", "Independent reporting of leakage volumes to confirm the claimed effect" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0319", "title": "Te Hiku Media's te reo Māori speech recognition may be 92% accurate; archive transcription tests with the University of Auckland, RNZ and Ngā Taonga are under way", "summary": "Iwi broadcaster's ASR, trained on 310 hours of community recordings (86% accuracy, 2022), reported at 92% in 2024; archive tests announced in 2024 with results to come; no speaker outcome documented.", "date_observed": "2024-03-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Te Hiku Media, a charitable iwi media and technology organization in Kaitaia, New Zealand, built its own te reo Māori automatic speech recognition. MIT Technology Review (22 April 2022) described a ten-day community competition in 2018. It collected “310 hours of speech-text pairs from some 200,000 recordings made by roughly 2,500 people”. From that, bootstrapping an open-source Mozilla model, “Te Hiku created its very first te reo speech recognition model with 86% accuracy”. The tools are offered through the Papa Reo platform. NVIDIA's blog (16 January 2024) says the model “transcribes te reo Māori with 92% accuracy” using the NeMo toolkit. An RNZ release of 11 September 2024 quotes Te Hiku chief executive Peter-Lucas Jones in te reo giving the same 92% figure. The University of Auckland announced on 18 March 2024 that its Archive of Māori and Pacific Sound is working with Te Hiku Media. They are testing it on archival recordings with different dialects, recording qualities and sung forms. Automatic output is compared “against human-generated ones”, with results to be shared with the galleries, libraries, archives and museums sector. It says the tool “is performing very well for their purposes” in Te Hiku's broadcasting arm. RNZ and Ngā Taonga Sound & Vision agreed in September 2024 to supply previously broadcast te reo recordings to train and review the tools. No cited source reports a measured outcome for a speaker, learner or archive user. The accuracy figures originate with Te Hiku Media and NVIDIA.", "category": "general benefit", "unexpected": false, "purpose": "Built to transcribe te reo Māori recordings so that archives and broadcasts become searchable and readable by learners, under Māori data-sovereignty rules. The transcription tests are that intended use.", "system": "Te Hiku Media te reo Māori automatic speech recognition and transcription tool (Papa Reo platform; trained with Mozilla DeepSpeech-era open-source tooling, later NVIDIA NeMo)", "model_version": null, "developer": "Te Hiku Media (Kaitaia, New Zealand)", "deployer": "Te Hiku Media; test partners Archive of Māori and Pacific Sound (University of Auckland), RNZ and Ngā Taonga Sound & Vision", "location": "Kaitaia and Auckland, New Zealand", "domain": "Language technology / Indigenous language revitalisation", "segment": "Iwi media and audiovisual archives", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The documented good is recognition accuracy; serving te reo Maori speakers would be inclusion, but no speaker outcome is reported.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Te Hiku Media and its archive partners report the tool performs well for broadcasting and are testing it on archival material. No measured time saving or completed archive transcription is documented." }, { "group": "societal", "depth": null, "reason": "Benefits to te reo speakers and learners are the stated aim; no cited source measures them." } ], "ai_role": { "status": "assessed", "statement": "The accuracy figures come from Te Hiku Media. MIT Technology Review reported 86% in 2022. NVIDIA, a tooling vendor, and Te Hiku's chief executive through RNZ stated 92% in 2024. The University of Auckland's independent test compares outputs against human transcripts, with results to follow. No cited source reports an outcome for any speaker, learner or archive beyond the developer's own broadcasting use." }, "evidence": [ { "kind": "press release", "citation": "University of Auckland (2024). Putting te reo artificial intelligence to the test. News, 18 March 2024.", "title": "Putting te reo artificial intelligence to the test", "url": "https://www.auckland.ac.nz/en/news/2024/03/18/te-reo-artificial-intelligence.html", "date": "2024-03-18", "written_by": "deployer", "quote": "This ever-evolving tool is performing very well for their purposes, providing their audience with an alternative way of exploring their output." }, { "kind": "press release", "citation": "University of Auckland (2024), same article, on the test design.", "title": "Putting te reo artificial intelligence to the test", "url": "https://www.auckland.ac.nz/en/news/2024/03/18/te-reo-artificial-intelligence.html", "date": "2024-03-18", "written_by": "deployer", "quote": "This project will see a sampling of recordings put through the automatic transcription process, then the output compared against human-generated ones" }, { "kind": "news report", "citation": "Hao K (2022). A new vision of artificial intelligence for the people. MIT Technology Review, 22 April 2022.", "title": "A new vision of artificial intelligence for the people", "url": "https://www.technologyreview.com/2022/04/22/1050394/artificial-intelligence-for-the-people/", "date": "2022-04-22", "written_by": "independent", "quote": "Te Hiku created its very first te reo speech recognition model with 86% accuracy." }, { "kind": "press release", "citation": "Lee A (2024). Māori Speech AI Model Helps Preserve and Promote New Zealand Indigenous Language. NVIDIA Blog, 16 January 2024 (NVIDIA supplies the NeMo toolkit and hardware).", "title": "Māori Speech AI Model Helps Preserve and Promote New Zealand Indigenous Language", "url": "https://blogs.nvidia.com/blog/te-hiku-media-maori-speech-ai/", "date": "2024-01-16", "written_by": "makers", "quote": "Te Hiku Media's automatic speech recognition model transcribes te reo Māori with 92% accuracy using trustworthy AI and the NVIDIA NeMo toolkit." }, { "kind": "press release", "citation": "RNZ (2024). Media collaboration to develop Māori language tools. RNZ media release, 11 September 2024 (RNZ is a data partner of Te Hiku Media in this agreement).", "title": "Media collaboration to develop Māori language tools", "url": "https://www.rnz.co.nz/media/226", "date": "2024-09-11", "written_by": "deployer", "quote": "a review of the tools to check for improved handling of dialect nuances and the accuracy of transcription, in particular for names no longer in use." } ], "replication": { "produced_by": [ "A community-contributed read-speech corpus (310 hours in ten days) held under Te Hiku Media's data-sovereignty rules", "Bootstrapping from open-source speech models and, later, NVIDIA's NeMo toolkit" ], "must_hold": [ "Recordings resemble the training data. The 2024 tests deliberately probe regional dialects, recording quality and sung forms such as mōteatea and waiata", "Archive holders license recordings on the partners' conditions (no pecuniary gain, previously broadcast material only)" ], "echoes": [ { "date": "2024-09-11", "setting": "RNZ and Ngā Taonga archive-access agreement to train and review the tools on historical te reo broadcasts", "model_version": null, "outcome": "unknown", "source": "https://www.rnz.co.nz/media/226" } ] }, "paired_incident": null, "headline": "Te Hiku Media's te reo Māori recognition may be 92% accurate", "metric": "transcribes te reo Māori with 92% accuracy", "comparator": { "against": "te reo Māori speech recognition attempts by major tech companies", "before": null, "after": "an accuracy of 92%", "basis": "assumed", "quote": "Our tools already outperform attempts by major tech companies at te reo Māori ASR, with an accuracy of 92%.", "url": "https://www.rnz.co.nz/media/226" }, "later": { "status": "scaled", "date": "2024-09-11", "note": "RNZ announced on 11 September 2024 that it is integrating Te Hiku's Papa Reo API into its workflows for search and captions, with RNZ and Ngā Taonga supplying archival te reo broadcasts to train and review the tools.", "quote": "RNZ is in the process of integrating the Papa Reo API into its workflows, initially adding transcribed audio to the search capability and then allowing it to add captions to its player in the near future.", "url": "https://www.rnz.co.nz/media/226" }, "value": null, "developer_country": "New Zealand", "deployer_country": "New Zealand", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.rnz.co.nz/media/226; https://www.rnz.co.nz/media/226", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://tehiku.nz/; https://tehiku.nz/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Te Hiku Media.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' press release and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0319", "catalog_version": "1.0.0", "source_fingerprint": "bf2371c20b4c7276d2ddb9a009ac394e61d6aca8bfb9cddac61b871ff041efff", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0319-source-0001", "AIBD-0319-source-0002", "AIBD-0319-source-0003", "AIBD-0319-source-0004", "AIBD-0319-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Te Hiku Media (Kaitaia, New Zealand)", "deployer": "Te Hiku Media; test partners Archive of Māori and Pacific Sound (University of Auckland), RNZ and Ngā Taonga Sound & Vision" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The accuracy figures come from Te Hiku Media. MIT Technology Review reported 86% in 2022. NVIDIA, a tooling vendor, and Te Hiku's chief executive through RNZ stated 92% in 2024. The University of Auckland's independent test compares outputs against human transcripts, with results to follow. No cited source reports an outcome for any speaker, learner or archive beyond the developer's own broadcasting use." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The accuracy figures come from Te Hiku Media. MIT Technology Review reported 86% in 2022. NVIDIA, a tooling vendor, and Te Hiku's chief executive through RNZ stated 92% in 2024. The University of Auckland's independent test compares outputs against human transcripts, with results to follow. No cited source reports an outcome for any speaker, learner or archive beyond the developer's own broadcasting use." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the makers' press release and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Te Hiku Media and its archive partners report the tool performs well for broadcasting and are testing it on archival material. No measured time saving or completed archive transcription is documented." }, { "group": "societal", "reason": "Benefits to te reo speakers and learners are the stated aim; no cited source measures them." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Te Hiku Media and its archive partners report the tool performs well for broadcasting and are testing it on archival material. 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"evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": 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train and review the tools.", "quote": "RNZ is in the process of integrating the Papa Reo API into its workflows, initially adding transcribed audio to the search capability and then allowing it to add captions to its player in the near future.", "url": "https://www.rnz.co.nz/media/226" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0319" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, 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"fields": { "account": "Te Hiku Media, a charitable iwi media and technology organization in Kaitaia, New Zealand, built its own te reo Māori automatic speech recognition. 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Automatic output is compared “against human-generated ones”, with results to be shared with the galleries, libraries, archives and museums sector. It says the tool “is performing very well for their purposes” in Te Hiku's broadcasting arm. RNZ and Ngā Taonga Sound & Vision agreed in September 2024 to supply previously broadcast te reo recordings to train and review the tools. No cited source reports a measured outcome for a speaker, learner or archive user. 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No measured time saving or completed archive transcription is documented." }, { "group": "societal", "reason": "Benefits to te reo speakers and learners are the stated aim; no cited source measures them." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to transcribe te reo Māori recordings so that archives and broadcasts become searchable and readable by learners, under Māori data-sovereignty rules. 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The 2024 tests deliberately probe regional dialects, recording quality and sung forms such as mōteatea and waiata", "Archive holders license recordings on the partners' conditions (no pecuniary gain, previously broadcast material only)" ], "echoes": [ { "date": "2024-09-11", "setting": "RNZ and Ngā Taonga archive-access agreement to train and review the tools on historical te reo broadcasts", "outcome": "unknown", "source": "https://www.rnz.co.nz/media/226" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A community-contributed read-speech corpus (310 hours in ten days) held under Te Hiku Media's data-sovereignty rules", "Bootstrapping from open-source speech models and, later, NVIDIA's NeMo toolkit" ], "must_hold": [ "Recordings resemble the training data. 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A new vision of artificial intelligence for the people. MIT Technology Review, 22 April 2022.", "title": "A new vision of artificial intelligence for the people", "url": "https://www.technologyreview.com/2022/04/22/1050394/artificial-intelligence-for-the-people/", "date": "2022-04-22", "written_by": "independent", "quote": "Te Hiku created its very first te reo speech recognition model with 86% accuracy." }, { "kind": "press release", "citation": "Lee A (2024). Māori Speech AI Model Helps Preserve and Promote New Zealand Indigenous Language. NVIDIA Blog, 16 January 2024 (NVIDIA supplies the NeMo toolkit and hardware).", "title": "Māori Speech AI Model Helps Preserve and Promote New Zealand Indigenous Language", "url": "https://blogs.nvidia.com/blog/te-hiku-media-maori-speech-ai/", "date": "2024-01-16", "written_by": "makers", "quote": "Te Hiku Media's automatic speech recognition model transcribes te reo Māori with 92% accuracy using trustworthy AI and the NVIDIA NeMo toolkit." }, { "kind": "press release", "citation": "RNZ (2024). Media collaboration to develop Māori language tools. RNZ media release, 11 September 2024 (RNZ is a data partner of Te Hiku Media in this agreement).", "title": "Media collaboration to develop Māori language tools", "url": "https://www.rnz.co.nz/media/226", "date": "2024-09-11", "written_by": "deployer", "quote": "a review of the tools to check for improved handling of dialect nuances and the accuracy of transcription, in particular for names no longer in use." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0319-source-0001", "AIBD-0319-source-0002", "AIBD-0319-source-0003", "AIBD-0319-source-0004", "AIBD-0319-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "University of Auckland (2024). 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Automatic output is compared “against human-generated ones”, with results to be shared with the galleries, libraries, archives and museums sector. It says the tool “is performing very well for their purposes” in Te Hiku's broadcasting arm. RNZ and Ngā Taonga Sound & Vision agreed in September 2024 to supply previously broadcast te reo recordings to train and review the tools. No cited source reports a measured outcome for a speaker, learner or archive user. 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MIT Technology Review (22 April 2022) described a ten-day community competition in 2018. It collected “310 hours of speech-text pairs from some 200,000 recordings made by roughly 2,500 people”. From that, bootstrapping an open-source Mozilla model, “Te Hiku created its very first te reo speech recognition model with 86% accuracy”. The tools are offered through the Papa Reo platform. NVIDIA's blog (16 January 2024) says the model “transcribes te reo Māori with 92% accuracy” using the NeMo toolkit. An RNZ release of 11 September 2024 quotes Te Hiku chief executive Peter-Lucas Jones in te reo giving the same 92% figure. The University of Auckland announced on 18 March 2024 that its Archive of Māori and Pacific Sound is working with Te Hiku Media. They are testing it on archival recordings with different dialects, recording qualities and sung forms. Automatic output is compared “against human-generated ones”, with results to be shared with the galleries, libraries, archives and museums sector. It says the tool “is performing very well for their purposes” in Te Hiku's broadcasting arm. RNZ and Ngā Taonga Sound & Vision agreed in September 2024 to supply previously broadcast te reo recordings to train and review the tools. No cited source reports a measured outcome for a speaker, learner or archive user. The accuracy figures originate with Te Hiku Media and NVIDIA.", "replication": { "produced_by": [ "A community-contributed read-speech corpus (310 hours in ten days) held under Te Hiku Media's data-sovereignty rules", "Bootstrapping from open-source speech models and, later, NVIDIA's NeMo toolkit" ], "must_hold": [ "Recordings resemble the training data. The 2024 tests deliberately probe regional dialects, recording quality and sung forms such as mōteatea and waiata", "Archive holders license recordings on the partners' conditions (no pecuniary gain, previously broadcast material only)" ], "echoes": [ { "date": "2024-09-11", "setting": "RNZ and Ngā Taonga archive-access agreement to train and review the tools on historical te reo broadcasts", "outcome": "unknown", "source": "https://www.rnz.co.nz/media/226" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0335", "title": "France's Foncier innovant aerial-image AI detects 140,000 undeclared pools and about €40 million in extra property tax by 20 March 2024; Dordogne alone 1,500 in 2023", "summary": "Minister Cazenave (20 March 2024): DGFiP's AI tool detected 140,000 undeclared pools, c. €40m extra property tax for local authorities; Dordogne found 1,500 in 2023. No commune-level figure found.", "date_observed": "2024-03-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 20 March 2024 Thomas Cazenave, minister for public accounts, presented the first bilan of the government's anti-fraud plan at Bercy. He said the DGFiP's algorithmic tool, Foncier innovant, introduced in October 2021, had detected 140,000 undeclared swimming pools. The tool detects pools and buildings on IGN aerial photographs and compares them with declarations. An agent then checks each detection. That would let local authorities collect about €40 million in property tax. Owners received DGFiP letters asking them to regularize (RMC, Ouest-France, L'Indépendant, 21 March 2024). CNews (11 June 2024) cites the DGFiP annual activity report as reported by Ouest-France. It gives 140,000 pools identified in 2023 and €40 million that should have been paid in 2023. That compares with 20,000 pools in the 2022 experiment in nine départements (20 Minutes). L'Indépendant instead states 120,000 for 2022, so the press accounts of the yearly split disagree. At département level, ici (France Bleu) reported on 24 March 2024 on the Dordogne public-finance office. It had found about 1,500 undeclared pools in 2023 among some 30,000 in the département. It would send property-tax catch-up notices by the end of March. No official DGFiP or ministry document is among the sources, as the ministry's website was not available. No commune-level result was found.", "category": "benefit created", "unexpected": false, "purpose": "Detect undeclared pools and buildings from aerial imagery so that they are added to the cadastral base and taxed. This was the tool's intended purpose.", "system": "Foncier innovant (DGFiP deep-learning detection of pools and buildings on IGN aerial photographs, built with Capgemini and Google)", "model_version": null, "developer": "Direction générale des Finances publiques (DGFiP) with Capgemini and Google", "deployer": "Direction générale des Finances publiques (DGFiP), ministère de l'Économie et des Finances", "location": "France (national; Dordogne example)", "domain": "Public finance: property-tax base and anti-fraud", "segment": "Tax administration", "benefit_type": "Increased Product Revenue", "taxonomy_note": "Tax yield is read as the authority's revenue; Trustible's description is written for product sales.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Owners of detected pools bear a cost; no individual beneficiary is documented." }, { "group": "organizational", "depth": 2, "reason": "Material to the DGFiP and to local authorities. The minister attributed about €40 million of additional property tax to the tool. Dordogne alone is recovering tax on about 1,500 pools." }, { "group": "societal", "depth": 1, "reason": "About €40 million nationally is small against total property-tax receipts. The press accounts disagree on the yearly split." } ], "ai_role": { "status": "assessed", "statement": "The AI detects pool outlines on aerial photographs and compares them with declarations. An agent verifies each detection before the construction is added to the cadastral value (Ouest-France). The 140,000 pools and €40 million are the minister's own attribution to the tool, relayed by several news outlets. CNews cites the DGFiP annual report via Ouest-France. No official document is among the sources. A CGT Finances publiques official told Ouest-France that field colleagues put the algorithm's error threshold at 55–60%. So the detections required substantial human checking. No commune-level outcome is on record. The Dordogne figure is the most local one read." }, "evidence": [ { "kind": "news report", "citation": "Dussourt, G. (2024). Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros. RMC, 21 Mar 2024 (quoting minister Thomas Cazenave).", "title": "Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "date": "2024-03-21", "written_by": "independent", "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière" }, { "kind": "news report", "citation": "Ouest-France (2024). Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés. 21 Mar 2024.", "title": "Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "l’outil algorithmique introduit par la DGFiP en octobre 2021 avait permis la détection de 140 000 piscines, pour 40 millions d’euros de recettes supplémentaires" }, { "kind": "news report", "citation": "Ouest-France (2024). Same article, statements on verification and on error rates (Olivier Vilois, CGT Finances publiques).", "title": "Garages, vérandas, piscines… (verification and error rate)", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "D’après mes collègues sur le terrain, le seuil d’erreurs des algorithmes atteint 55 à 60% en ce moment" }, { "kind": "news report", "citation": "CNews (2024). Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA. 11 Jun 2024 (citing the DGFiP annual activity report via Ouest-France).", "title": "Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA", "url": "https://www.cnews.fr/france/2024-06-11/piscines-non-declarees-le-fisc-repere-140000-fraudeurs-grace-lia-1511264", "date": "2024-06-11", "written_by": "independent", "quote": "En 2023, cette technique a permis à la Direction générale des finances publiques d'identifier 140.000 piscines non déclarées, selon son rapport annuel d'activité publié par Ouest France." }, { "kind": "news report", "citation": "Bertrand, M. (2024). Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle. ici (France Bleu Périgord), 24 Mar 2024.", "title": "Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle", "url": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279", "date": "2024-03-24", "written_by": "independent", "quote": "Les finances publiques de Dordogne ont repéré quelque 1.500 piscines non déclarées au fisc en Dordogne, au cours de l'année 2023, sur les quelque 30.000 piscines du département." }, { "kind": "news report", "citation": "20 Minutes (2024). Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023. 12 Jun 2024.", "title": "Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023", "url": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023", "date": "2024-06-12", "written_by": "independent", "quote": "En 2022, 20.000 piscines non déclarées avaient ainsi été repérées pour un redressement estimé à 10 millions d’euros." } ], "replication": { "produced_by": [ "IGN aerial photographs covering the whole territory", "A detection model built with Capgemini and Google, generalized nationally after the 2022 nine-département experiment", "Comparison of detected outlines with cadastral declarations", "Agent verification of each detection and letters inviting owners to regularize" ], "must_hold": [ "Recent, high-resolution aerial coverage", "A false-detection rate low enough for agents to verify (a union official cites 55–60% errors)", "Legal basis to add undeclared constructions to the cadastral value", "Local offices with capacity to send and handle catch-up notices" ], "echoes": [ { "date": "2022-12-31", "setting": "2022 experiment in nine départements: about 20,000 undeclared pools, about €10 million", "model_version": null, "outcome": "recurred", "source": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" }, { "date": "2024-03-24", "setting": "Dordogne département, 2023 campaign: about 1,500 undeclared pools, catch-up notices sent by end of March 2024", "model_version": null, "outcome": "recurred", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279" }, { "date": "2024-03-20", "setting": "Announced extension of the same tool from pools to undeclared buildings (garages, verandas); no outcome yet", "model_version": null, "outcome": "unknown", "source": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727" } ] }, "paired_incident": null, "headline": "Foncier innovant finds 140,000 undeclared pools", "metric": "detected 140,000 undeclared pools, c. €40m extra property tax", "comparator": { "against": "a surveyor noticing a new pool in a neighborhood by eye and checking the cadastre", "before": "le géomètre qui remarquait une nouvelle piscine dans un quartier et devait vérifier dans le cadastre si elle était déclarée ou pas", "after": "Dans toute la France, 140.000 piscines clandestines ont été repérées, ce qui va rapporter 40 millions d'euros.", "basis": "assumed", "quote": "Fini, le géomètre qui remarquait une nouvelle piscine dans un quartier et devait vérifier dans le cadastre si elle était déclarée ou pas. Désormais, les impôts utilisent des photos prises par avion et analysées par l'intelligence artificielle qui repère automatiquement les carrés bleus des piscines et les compare aux fichiers existants.", "url": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279" }, "later": { "status": "persisted", "date": "2024-06-12", "note": "In June 2024 the DGFiP's 2023 activity report, as relayed by 20 Minutes and CNews, restated the 140,000 pools and the 40 million euros of property tax, against 20,000 pools in 2022, and the plan to extend detection to undeclared buildings.", "quote": "140.000 piscines non déclarées ont été épinglées par le fisc en 2023, a dévoilé la Direction générale des finances publiques ce mardi dans son rapport d’activité 2023 relayé par Ouest-France.", "url": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" }, "value": { "amount": "40 millions d’euros", "what": "additional property tax (taxe foncière) to be collected on the 140,000 detected pools", "who": "local authorities (collectivités), which receive the taxe foncière", "estimate": true, "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html" }, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279; https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023; https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0335", "catalog_version": "1.0.0", "source_fingerprint": "87e51983bab417c733b46e4cfa086ffdca9be62d3de6113d831a444fa7d06335", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0335-source-0001", "AIBD-0335-source-0002", "AIBD-0335-source-0003", "AIBD-0335-source-0004", "AIBD-0335-source-0005", "AIBD-0335-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0335-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Direction générale des Finances publiques (DGFiP) with Capgemini and Google", "deployer": "Direction générale des Finances publiques (DGFiP), ministère de l'Économie et des Finances" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI detects pool outlines on aerial photographs and compares them with declarations. An agent verifies each detection before the construction is added to the cadastral value (Ouest-France). The 140,000 pools and €40 million are the minister's own attribution to the tool, relayed by several news outlets. CNews cites the DGFiP annual report via Ouest-France. No official document is among the sources. A CGT Finances publiques official told Ouest-France that field colleagues put the algorithm's error threshold at 55–60%. So the detections required substantial human checking. No commune-level outcome is on record. The Dordogne figure is the most local one read." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI detects pool outlines on aerial photographs and compares them with declarations. An agent verifies each detection before the construction is added to the cadastral value (Ouest-France). The 140,000 pools and €40 million are the minister's own attribution to the tool, relayed by several news outlets. CNews cites the DGFiP annual report via Ouest-France. No official document is among the sources. A CGT Finances publiques official told Ouest-France that field colleagues put the algorithm's error threshold at 55–60%. So the detections required substantial human checking. No commune-level outcome is on record. The Dordogne figure is the most local one read." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Owners of detected pools bear a cost; no individual beneficiary is documented." }, { "group": "organizational", "depth": 2, "reason": "Material to the DGFiP and to local authorities. The minister attributed about €40 million of additional property tax to the tool. Dordogne alone is recovering tax on about 1,500 pools." }, { "group": "societal", "depth": 1, "reason": "About €40 million nationally is small against total property-tax receipts. The press accounts disagree on the yearly split." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Owners of detected pools bear a cost; no individual beneficiary is documented." }, { "group": "organizational", "depth": 2, "reason": "Material to the DGFiP and to local authorities. The minister attributed about €40 million of additional property tax to the tool. Dordogne alone is recovering tax on about 1,500 pools." }, { "group": "societal", "depth": 1, "reason": "About €40 million nationally is small against total property-tax receipts. The press accounts disagree on the yearly split." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Owners of detected pools bear a cost; no individual beneficiary is documented." }, { "group": "organizational", "depth": 2, "reason": "Material to the DGFiP and to local authorities. The minister attributed about €40 million of additional property tax to the tool. Dordogne alone is recovering tax on about 1,500 pools." }, { "group": "societal", "depth": 1, "reason": "About €40 million nationally is small against total property-tax receipts. The press accounts disagree on the yearly split." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "40 millions d’euros", "what": "additional property tax (taxe foncière) to be collected on the 140,000 detected pools", "who": "local authorities (collectivités), which receive the taxe foncière", "estimate": true, "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "40 millions d’euros", "what": "additional property tax (taxe foncière) to be collected on the 140,000 detected pools", "who": "local authorities (collectivités), which receive the taxe foncière", "estimate": true, "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "40 millions d’euros", "what": "additional property tax (taxe foncière) to be collected on the 140,000 detected pools", "who": "local authorities (collectivités), which receive the taxe foncière", "estimate": true, "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "detected 140,000 undeclared pools, c. €40m extra property tax", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2024-06-12", "note": "In June 2024 the DGFiP's 2023 activity report, as relayed by 20 Minutes and CNews, restated the 140,000 pools and the 40 million euros of property tax, against 20,000 pools in 2022, and the plan to extend detection to undeclared buildings.", "quote": "140.000 piscines non déclarées ont été épinglées par le fisc en 2023, a dévoilé la Direction générale des finances publiques ce mardi dans son rapport d’activité 2023 relayé par Ouest-France.", "url": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0335" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Revenue", "taxonomy_note": "Tax yield is read as the authority's revenue; Trustible's description is written for product sales." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 20 March 2024 Thomas Cazenave, minister for public accounts, presented the first bilan of the government's anti-fraud plan at Bercy. He said the DGFiP's algorithmic tool, Foncier innovant, introduced in October 2021, had detected 140,000 undeclared swimming pools. The tool detects pools and buildings on IGN aerial photographs and compares them with declarations. An agent then checks each detection. That would let local authorities collect about €40 million in property tax. Owners received DGFiP letters asking them to regularize (RMC, Ouest-France, L'Indépendant, 21 March 2024). CNews (11 June 2024) cites the DGFiP annual activity report as reported by Ouest-France. It gives 140,000 pools identified in 2023 and €40 million that should have been paid in 2023. That compares with 20,000 pools in the 2022 experiment in nine départements (20 Minutes). L'Indépendant instead states 120,000 for 2022, so the press accounts of the yearly split disagree. At département level, ici (France Bleu) reported on 24 March 2024 on the Dordogne public-finance office. It had found about 1,500 undeclared pools in 2023 among some 30,000 in the département. It would send property-tax catch-up notices by the end of March. No official DGFiP or ministry document is among the sources, as the ministry's website was not available. No commune-level result was found.", "benefit_type": "Increased Product Revenue" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Owners of detected pools bear a cost; no individual beneficiary is documented." }, { "group": "organizational", "depth": 2, "reason": "Material to the DGFiP and to local authorities. The minister attributed about €40 million of additional property tax to the tool. Dordogne alone is recovering tax on about 1,500 pools." }, { "group": "societal", "depth": 1, "reason": "About €40 million nationally is small against total property-tax receipts. The press accounts disagree on the yearly split." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect undeclared pools and buildings from aerial imagery so that they are added to the cadastral base and taxed. This was the tool's intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "France (national; Dordogne example)", "developer_country": "France", "deployer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect undeclared pools and buildings from aerial imagery so that they are added to the cadastral base and taxed. This was the tool's intended purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-03-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279; https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023; https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "IGN aerial photographs covering the whole territory", "A detection model built with Capgemini and Google, generalized nationally after the 2022 nine-département experiment", "Comparison of detected outlines with cadastral declarations", "Agent verification of each detection and letters inviting owners to regularize" ], "must_hold": [ "Recent, high-resolution aerial coverage", "A false-detection rate low enough for agents to verify (a union official cites 55–60% errors)", "Legal basis to add undeclared constructions to the cadastral value", "Local offices with capacity to send and handle catch-up notices" ], "echoes": [ { "date": "2022-12-31", "setting": "2022 experiment in nine départements: about 20,000 undeclared pools, about €10 million", "outcome": "recurred", "source": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" }, { "date": "2024-03-24", "setting": "Dordogne département, 2023 campaign: about 1,500 undeclared pools, catch-up notices sent by end of March 2024", "outcome": "recurred", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279" }, { "date": "2024-03-20", "setting": "Announced extension of the same tool from pools to undeclared buildings (garages, verandas); no outcome yet", "outcome": "unknown", "source": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "IGN aerial photographs covering the whole territory", "A detection model built with Capgemini and Google, generalized nationally after the 2022 nine-département experiment", "Comparison of detected outlines with cadastral declarations", "Agent verification of each detection and letters inviting owners to regularize" ], "must_hold": [ "Recent, high-resolution aerial coverage", "A false-detection rate low enough for agents to verify (a union official cites 55–60% errors)", "Legal basis to add undeclared constructions to the cadastral value", "Local offices with capacity to send and handle catch-up notices" ], "echoes": [ { "date": "2022-12-31", "setting": "2022 experiment in nine départements: about 20,000 undeclared pools, about €10 million", "outcome": "recurred", "source": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" }, { "date": "2024-03-24", "setting": "Dordogne département, 2023 campaign: about 1,500 undeclared pools, catch-up notices sent by end of March 2024", "outcome": "recurred", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279" }, { "date": "2024-03-20", "setting": "Announced extension of the same tool from pools to undeclared buildings (garages, verandas); no outcome yet", "outcome": "unknown", "source": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279; https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023; https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public finance: property-tax base and anti-fraud", "segment": "Tax administration" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dussourt, G. (2024). Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros. RMC, 21 Mar 2024 (quoting minister Thomas Cazenave).", "title": "Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "date": "2024-03-21", "written_by": "independent", "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière" }, { "kind": "news report", "citation": "Ouest-France (2024). Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés. 21 Mar 2024.", "title": "Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "l’outil algorithmique introduit par la DGFiP en octobre 2021 avait permis la détection de 140 000 piscines, pour 40 millions d’euros de recettes supplémentaires" }, { "kind": "news report", "citation": "Ouest-France (2024). Same article, statements on verification and on error rates (Olivier Vilois, CGT Finances publiques).", "title": "Garages, vérandas, piscines… (verification and error rate)", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "D’après mes collègues sur le terrain, le seuil d’erreurs des algorithmes atteint 55 à 60% en ce moment" }, { "kind": "news report", "citation": "CNews (2024). Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA. 11 Jun 2024 (citing the DGFiP annual activity report via Ouest-France).", "title": "Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA", "url": "https://www.cnews.fr/france/2024-06-11/piscines-non-declarees-le-fisc-repere-140000-fraudeurs-grace-lia-1511264", "date": "2024-06-11", "written_by": "independent", "quote": "En 2023, cette technique a permis à la Direction générale des finances publiques d'identifier 140.000 piscines non déclarées, selon son rapport annuel d'activité publié par Ouest France." }, { "kind": "news report", "citation": "Bertrand, M. (2024). Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle. ici (France Bleu Périgord), 24 Mar 2024.", "title": "Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle", "url": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279", "date": "2024-03-24", "written_by": "independent", "quote": "Les finances publiques de Dordogne ont repéré quelque 1.500 piscines non déclarées au fisc en Dordogne, au cours de l'année 2023, sur les quelque 30.000 piscines du département." }, { "kind": "news report", "citation": "20 Minutes (2024). Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023. 12 Jun 2024.", "title": "Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023", "url": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023", "date": "2024-06-12", "written_by": "independent", "quote": "En 2022, 20.000 piscines non déclarées avaient ainsi été repérées pour un redressement estimé à 10 millions d’euros." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0335-source-0001", "AIBD-0335-source-0002", "AIBD-0335-source-0003", "AIBD-0335-source-0004", "AIBD-0335-source-0005", "AIBD-0335-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dussourt, G. (2024). Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros. RMC, 21 Mar 2024 (quoting minister Thomas Cazenave).", "title": "Grâce à l'IA, l'Etat découvre 140.000 piscines non déclarées et récupère 40 millions d'euros", "url": "https://rmc.bfmtv.com/actualites/economie/grace-a-l-ia-l-etat-decouvre-140-000-piscines-non-declarees-et-recupere-40-millions-d-euros_AV-202403210525.html", "date": "2024-03-21", "written_by": "independent", "quote": "ce sont 140.000 piscines qui ont été détectées et qui permettront à nos collectivités de récolter 40 millions d’euros au titre de la taxe foncière" }, { "kind": "news report", "citation": "Ouest-France (2024). Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés. 21 Mar 2024.", "title": "Garages, vérandas, piscines… Comment le fisc repère les bâtiments non déclarés", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "l’outil algorithmique introduit par la DGFiP en octobre 2021 avait permis la détection de 140 000 piscines, pour 40 millions d’euros de recettes supplémentaires" }, { "kind": "news report", "citation": "Ouest-France (2024). Same article, statements on verification and on error rates (Olivier Vilois, CGT Finances publiques).", "title": "Garages, vérandas, piscines… (verification and error rate)", "url": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727", "date": "2024-03-21", "written_by": "independent", "quote": "D’après mes collègues sur le terrain, le seuil d’erreurs des algorithmes atteint 55 à 60% en ce moment" }, { "kind": "news report", "citation": "CNews (2024). Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA. 11 Jun 2024 (citing the DGFiP annual activity report via Ouest-France).", "title": "Piscines non déclarées : le fisc repère 140.000 fraudeurs grâce à l'IA", "url": "https://www.cnews.fr/france/2024-06-11/piscines-non-declarees-le-fisc-repere-140000-fraudeurs-grace-lia-1511264", "date": "2024-06-11", "written_by": "independent", "quote": "En 2023, cette technique a permis à la Direction générale des finances publiques d'identifier 140.000 piscines non déclarées, selon son rapport annuel d'activité publié par Ouest France." }, { "kind": "news report", "citation": "Bertrand, M. (2024). Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle. ici (France Bleu Périgord), 24 Mar 2024.", "title": "Le fisc découvre 1.500 piscines non-déclarées en Dordogne grâce à l'intelligence artificielle", "url": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279", "date": "2024-03-24", "written_by": "independent", "quote": "Les finances publiques de Dordogne ont repéré quelque 1.500 piscines non déclarées au fisc en Dordogne, au cours de l'année 2023, sur les quelque 30.000 piscines du département." }, { "kind": "news report", "citation": "20 Minutes (2024). Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023. 12 Jun 2024.", "title": "Taxe foncière : Grâce à l'IA, le fisc a repéré 140.000 piscines non déclarées en 2023", "url": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023", "date": "2024-06-12", "written_by": "independent", "quote": "En 2022, 20.000 piscines non déclarées avaient ainsi été repérées pour un redressement estimé à 10 millions d’euros." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Minister Cazenave (20 March 2024): DGFiP's AI tool detected 140,000 undeclared pools, c. €40m extra property tax for local authorities; Dordogne found 1,500 in 2023. No commune-level figure found.", "account": "On 20 March 2024 Thomas Cazenave, minister for public accounts, presented the first bilan of the government's anti-fraud plan at Bercy. He said the DGFiP's algorithmic tool, Foncier innovant, introduced in October 2021, had detected 140,000 undeclared swimming pools. The tool detects pools and buildings on IGN aerial photographs and compares them with declarations. An agent then checks each detection. That would let local authorities collect about €40 million in property tax. Owners received DGFiP letters asking them to regularize (RMC, Ouest-France, L'Indépendant, 21 March 2024). CNews (11 June 2024) cites the DGFiP annual activity report as reported by Ouest-France. It gives 140,000 pools identified in 2023 and €40 million that should have been paid in 2023. That compares with 20,000 pools in the 2022 experiment in nine départements (20 Minutes). L'Indépendant instead states 120,000 for 2022, so the press accounts of the yearly split disagree. At département level, ici (France Bleu) reported on 24 March 2024 on the Dordogne public-finance office. It had found about 1,500 undeclared pools in 2023 among some 30,000 in the département. It would send property-tax catch-up notices by the end of March. No official DGFiP or ministry document is among the sources, as the ministry's website was not available. No commune-level result was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Foncier innovant (DGFiP deep-learning detection of pools and buildings on IGN aerial photographs, built with Capgemini and Google)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Direction générale des Finances publiques (DGFiP) with Capgemini and Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "France's Foncier innovant aerial-image AI detects 140,000 undeclared pools and about €40 million in extra property tax by 20 March 2024; Dordogne alone 1,500 in 2023", "headline": "Foncier innovant finds 140,000 undeclared pools" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "87e51983bab417c733b46e4cfa086ffdca9be62d3de6113d831a444fa7d06335" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 20 March 2024 Thomas Cazenave, minister for public accounts, presented the first bilan of the government's anti-fraud plan at Bercy. He said the DGFiP's algorithmic tool, Foncier innovant, introduced in October 2021, had detected 140,000 undeclared swimming pools. The tool detects pools and buildings on IGN aerial photographs and compares them with declarations. An agent then checks each detection. That would let local authorities collect about €40 million in property tax. Owners received DGFiP letters asking them to regularize (RMC, Ouest-France, L'Indépendant, 21 March 2024). CNews (11 June 2024) cites the DGFiP annual activity report as reported by Ouest-France. It gives 140,000 pools identified in 2023 and €40 million that should have been paid in 2023. That compares with 20,000 pools in the 2022 experiment in nine départements (20 Minutes). L'Indépendant instead states 120,000 for 2022, so the press accounts of the yearly split disagree. At département level, ici (France Bleu) reported on 24 March 2024 on the Dordogne public-finance office. It had found about 1,500 undeclared pools in 2023 among some 30,000 in the département. It would send property-tax catch-up notices by the end of March. No official DGFiP or ministry document is among the sources, as the ministry's website was not available. No commune-level result was found.", "replication": { "produced_by": [ "IGN aerial photographs covering the whole territory", "A detection model built with Capgemini and Google, generalized nationally after the 2022 nine-département experiment", "Comparison of detected outlines with cadastral declarations", "Agent verification of each detection and letters inviting owners to regularize" ], "must_hold": [ "Recent, high-resolution aerial coverage", "A false-detection rate low enough for agents to verify (a union official cites 55–60% errors)", "Legal basis to add undeclared constructions to the cadastral value", "Local offices with capacity to send and handle catch-up notices" ], "echoes": [ { "date": "2022-12-31", "setting": "2022 experiment in nine départements: about 20,000 undeclared pools, about €10 million", "outcome": "recurred", "source": "https://www.20minutes.fr/economie/4095936-20240612-taxe-fonciere-grace-ia-fisc-repere-140-000-piscines-non-declarees-2023" }, { "date": "2024-03-24", "setting": "Dordogne département, 2023 campaign: about 1,500 undeclared pools, catch-up notices sent by end of March 2024", "outcome": "recurred", "source": "https://www.ici.fr/infos/societe/le-fisc-decouvre-1500-piscines-non-declarees-en-dordogne-grace-a-l-intelligence-artificielle-4899279" }, { "date": "2024-03-20", "setting": "Announced extension of the same tool from pools to undeclared buildings (garages, verandas); no outcome yet", "outcome": "unknown", "source": "https://www.ouest-france.fr/economie/budget/garages-verandas-piscines-comment-le-fisc-repere-les-batiments-non-declares-46394b0a-e780-11ee-95e5-de9a0852a727" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0062", "title": "Mia AI breast-screening reader flags a 6 mm cancer that NHS Grampian radiologists missed; patient treated with surgery and five days of radiotherapy", "summary": "In NHS Grampian's GEMINI pilot, Mia flagged Barbara's 6 mm breast cancer missed by radiologists; surgery plus five days' radiotherapy.", "date_observed": "2024-03-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mia, an AI mammography reader by Kheiron Medical Technologies, was used alongside radiologists in National Health Service (NHS) Grampian's GEMINI breast-screening evaluation. It covered 10,889 women in Aberdeen, Scotland. BBC News (21 March 2024) described Barbara, an Aberdeen patient. She was one of 11 women whose cancer Mia flagged but hospital radiologists had not spotted on her scan. Her 6 mm tumor was caught so early she had an operation and needed only five days of radiotherapy. Dr Gerald Lip, clinical director of breast screening at NHS Grampian, led the evaluation. A University of Aberdeen statement the same day said Mia helped find 12% more cancers than routine practice. The date of Barbara's screening is not given.", "category": "benefit created", "unexpected": false, "purpose": "Mia was built to read screening mammograms and flag suspicious findings alongside human readers. Detecting a cancer missed by readers is exactly its intended function.", "system": "Mia", "model_version": null, "developer": "Kheiron Medical Technologies", "deployer": "NHS Grampian", "location": "Aberdeen, United Kingdom", "domain": "Healthcare - breast cancer screening", "segment": "AI reader in population mammography screening", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2024-03-21-b742" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A 6 mm cancer was treated at an early stage with surgery and a short radiotherapy course. Dr Lip states that cancers picked up under 15 mm carry around 95% survival. The benefit is potentially life-saving but not demonstrated as such for this patient." }, { "group": "organizational", "depth": 2, "reason": "Across the 10,889-woman evaluation Mia helped find 12% more cancers. The University of Aberdeen statement says this would not put more women through additional tests." } ], "ai_role": { "status": "assessed", "statement": "Mia flagged a lesion that the hospital radiologists had not identified on the same scan. Clinicians then confirmed and treated the cancer. Both the BBC and the University of Aberdeen attribute the detection to Mia. The counterfactual is that the cancer would have been found later, at a larger size, rather than never." }, "evidence": [ { "kind": "news report", "citation": "Kleinman Z (2024). NHS AI test spots tiny cancers missed by doctors. BBC News, 21 March 2024.", "title": "NHS AI test spots tiny cancers missed by doctors", "url": "https://www.bbc.com/news/technology-68607059", "date": "2024-03-21", "written_by": "independent", "quote": "Barbara was one of the 11 patients whose cancer was flagged by Mia but had not been spotted on her scan when it was studied by the hospital radiologists." }, { "kind": "news report", "citation": "Kleinman Z (2024). NHS AI test spots tiny cancers missed by doctors. BBC News, 21 March 2024 (second quotation).", "title": "NHS AI test spots tiny cancers missed by doctors", "url": "https://www.bbc.com/news/technology-68607059", "date": "2024-03-21", "written_by": "independent", "quote": "Because her 6mm tumour was caught so early she had an operation but only needed five days of radiotherapy." }, { "kind": "press release", "citation": "University of Aberdeen (2024). More breast cancers detected in first evaluation of breast screening AI. 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It covered 10,889 women in Aberdeen, Scotland. BBC News (21 March 2024) described Barbara, an Aberdeen patient. She was one of 11 women whose cancer Mia flagged but hospital radiologists had not spotted on her scan. Her 6 mm tumor was caught so early she had an operation and needed only five days of radiotherapy. Dr Gerald Lip, clinical director of breast screening at NHS Grampian, led the evaluation. A University of Aberdeen statement the same day said Mia helped find 12% more cancers than routine practice. The date of Barbara's screening is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Mia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Kheiron Medical Technologies" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Mia AI breast-screening reader flags a 6 mm cancer that NHS Grampian radiologists missed; patient treated with surgery and five days of radiotherapy", "headline": "Mia flags a 6 mm cancer missed by NHS Grampian radiologists" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c4fa27f84c85abbebf5bf8a7f1d1516bdeeb5a3129b5279ac5c12b469082fe89" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mia, an AI mammography reader by Kheiron Medical Technologies, was used alongside radiologists in National Health Service (NHS) Grampian's GEMINI breast-screening evaluation. It covered 10,889 women in Aberdeen, Scotland. BBC News (21 March 2024) described Barbara, an Aberdeen patient. She was one of 11 women whose cancer Mia flagged but hospital radiologists had not spotted on her scan. Her 6 mm tumor was caught so early she had an operation and needed only five days of radiotherapy. Dr Gerald Lip, clinical director of breast screening at NHS Grampian, led the evaluation. A University of Aberdeen statement the same day said Mia helped find 12% more cancers than routine practice. The date of Barbara's screening is not given.", "replication": { "produced_by": [ "Deployment of Mia alongside routine human double reading in a screening program", "A safety-net workflow in which AI-flagged, reader-negative cases are re-reviewed" ], "must_hold": [ "Clinicians act on AI-only flags rather than discarding them", "The AI's recall threshold is set so that extra flags do not overwhelm the service" ], "echoes": [ { "date": "2024-03-21", "setting": "Same NHS Grampian GEMINI evaluation, 10,889 women: 11 cancers flagged by Mia that the doctors had not identified", "outcome": "recurred", "source": "BBC News 21 March 2024, https://www.bbc.com/news/technology-68607059" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0306", "title": "Two-week diary study: 16 blind and low-vision adults use a Cornell Tech scene-description app built on Microsoft Azure AI Vision for 354 everyday tasks; satisfaction averages 2.76/5", "summary": "Gonzalez Penuela et al. (CHI 2024) log 354 diary entries from 16 BLV participants using an Azure AI Vision app; uses include telling sunglasses from reading glasses without calling a spouse.", "date_observed": "2024-03-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Ricardo Gonzalez Penuela, Jazmin Collins, Cynthia Bennett and Shiri Azenkot (Cornell Tech and Google) ran a two-week diary study. It had 16 blind and low-vision adults in the United States (five men, 11 women, aged 24 to 67). Recruitment was via National Federation of the Blind mailing lists. They used an iPhone scene-description app the researchers built on Microsoft's Azure AI Vision image description application programming interface (API). It was chosen because it “exposes the latest deep learning algorithms”. Seeing AI also uses it. Participants submitted 354 entries (13 to 39 each). Documented uses include P1 photographing glasses. She “was not sure if this was my husband's sunglasses or my old pair of reading glasses from 4 years ago”. She got an answer without calling him. P5 photographed a hotel bed to check his roommate was not in it, and P15 photographed wine bottles in a shop rather than touching them. Participants scored descriptions 2.76 out of 5 for satisfaction and 2.43 out of 4 for trust on average. The authors say satisfaction did not track accuracy because users inferred information from partially correct descriptions. The paper appeared at CHI 2024 (doi 10.1145/3613904.3642211). The arXiv version was submitted on 22 March 2024. The study dates are not reported. The CHI EA 2025 follow-up used a custom app, VisionPal, and documented failures such as hallucinated braille labels.", "category": "benefit created", "unexpected": false, "purpose": "The study app was built to describe photographed scenes for blind and low-vision users, emulating Seeing AI's scene channel. The documented identifications were that purpose.", "system": "Cornell Tech study scene-description app (unnamed) built on the Microsoft Azure AI Vision image description API", "model_version": null, "developer": "Cornell Tech (app); Microsoft (Azure AI Vision image description API)", "deployer": "Study participants (16 blind and low-vision adults)", "location": "United States", "domain": "Accessibility / visual assistance", "segment": "Blind and low-vision users", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "Participants completed small daily identifications without asking family. They rated descriptions 2.76/5 for satisfaction and 2.43/4 for trust on average. The app could not read text." } ], "ai_role": { "status": "assessed", "statement": "Azure AI Vision generated every description. The researchers' app only submitted photos and collected ratings. The paper documents individual successful uses and an overall judgment that descriptions “still need significant improvements”. Participants were allowed to use other tools during the study, so the diary covers only what they chose to photograph with this app." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Gonzalez Penuela RE, Collins J, Bennett CL, Azenkot S (2024). Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People. Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24). doi:10.1145/3613904.3642211; arXiv:2403.15604.", "title": "Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People", "url": "https://arxiv.org/abs/2403.15604", "date": "2024-03-22", "written_by": "makers", "quote": "we conducted a two-week diary study where 16 BLV participants used an AI-powered scene description application we designed." }, { "kind": "peer-reviewed study", "citation": "Gonzalez Penuela et al. (2024), arXiv HTML version (P1 example).", "title": "Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People", "url": "https://arxiv.org/html/2403.15604", "date": "2024-03-22", "written_by": "makers", "quote": "She was happy to get an answer without having to call her husband." }, { "kind": "peer-reviewed study", "citation": "Gonzalez Penuela et al. (2024), arXiv HTML version (system and scores).", "title": "Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People", "url": "https://arxiv.org/html/2403.15604", "date": "2024-03-22", "written_by": "makers", "quote": "We collected a total of 354 diary entries from our 16 participants. On average, each participant submitted 22 entries." }, { "kind": "other", "citation": "Semantic Scholar record for doi 10.1145/3613904.3642211 (venue, authors and open-access link).", "title": "Investigating Use Cases of AI-Powered Scene Description Applications for Blind and Low Vision People", "url": "https://doi.org/10.1145/3613904.3642211", "date": "2024-03-22", "written_by": "independent", "quote": null }, { "kind": "preprint", "citation": "Gonzalez Penuela RE, Hu R, Lin S, Shende T, Azenkot S (2025). Towards Understanding the Use of MLLM-Enabled Applications for Visual Interpretation by Blind and Low Vision People. arXiv:2503.05899, submitted 7 March 2025; to appear at CHI 2025.", "title": "Towards Understanding the Use of MLLM-Enabled Applications for Visual Interpretation by Blind and Low Vision People", "url": "https://arxiv.org/abs/2503.05899", "date": "2025-03-07", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "An iPhone app sending photos to the Azure AI Vision image description API", "Blind and low-vision users photographing objects they did not want to touch or ask others about", "A minimum of one photo per day for two weeks with a short questionnaire per entry" ], "must_hold": [ "The description is accurate enough for the user to infer what they need. 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P5 photographed a hotel bed to check his roommate was not in it, and P15 photographed wine bottles in a shop rather than touching them. Participants scored descriptions 2.76 out of 5 for satisfaction and 2.43 out of 4 for trust on average. The authors say satisfaction did not track accuracy because users inferred information from partially correct descriptions. The paper appeared at CHI 2024 (doi 10.1145/3613904.3642211). The arXiv version was submitted on 22 March 2024. The study dates are not reported. The CHI EA 2025 follow-up used a custom app, VisionPal, and documented failures such as hallucinated braille labels." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Cornell Tech study scene-description app (unnamed) built on the Microsoft Azure AI Vision image description API" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Cornell Tech (app); Microsoft (Azure AI Vision image description API)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Two-week diary study: 16 blind and low-vision adults use a Cornell Tech scene-description app built on Microsoft Azure AI Vision for 354 everyday tasks; satisfaction averages 2.76/5", "headline": "Azure AI Vision app helps blind, low-vision adults in 354 tasks" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1b862e63ef09b0c2875bb7c10c509e9ce517d0f3c617c89e93f863609f0be69c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Ricardo Gonzalez Penuela, Jazmin Collins, Cynthia Bennett and Shiri Azenkot (Cornell Tech and Google) ran a two-week diary study. It had 16 blind and low-vision adults in the United States (five men, 11 women, aged 24 to 67). Recruitment was via National Federation of the Blind mailing lists. They used an iPhone scene-description app the researchers built on Microsoft's Azure AI Vision image description application programming interface (API). It was chosen because it “exposes the latest deep learning algorithms”. Seeing AI also uses it. Participants submitted 354 entries (13 to 39 each). Documented uses include P1 photographing glasses. She “was not sure if this was my husband's sunglasses or my old pair of reading glasses from 4 years ago”. She got an answer without calling him. P5 photographed a hotel bed to check his roommate was not in it, and P15 photographed wine bottles in a shop rather than touching them. Participants scored descriptions 2.76 out of 5 for satisfaction and 2.43 out of 4 for trust on average. The authors say satisfaction did not track accuracy because users inferred information from partially correct descriptions. The paper appeared at CHI 2024 (doi 10.1145/3613904.3642211). The arXiv version was submitted on 22 March 2024. The study dates are not reported. The CHI EA 2025 follow-up used a custom app, VisionPal, and documented failures such as hallucinated braille labels.", "replication": { "produced_by": [ "An iPhone app sending photos to the Azure AI Vision image description API", "Blind and low-vision users photographing objects they did not want to touch or ask others about", "A minimum of one photo per day for two weeks with a short questionnaire per entry" ], "must_hold": [ "The description is accurate enough for the user to infer what they need. Users sometimes drew answers from partially correct output", "The task does not require reading text, which the app could not do" ], "echoes": [ { "date": "2025-03-07", "setting": "Follow-up two-week diary study with 20 BLV people using an MLLM-enabled visual-interpretation app the authors developed (VisionPal per an earlier check); 553 entries, preliminary analysis of 60 from six participants: trust 3.75/5, satisfaction 4.15/5, with trust in high-stakes uses such as medical dosage advice (CHI EA 2025, arXiv 2503.05899)", "model_version": "multimodal large language model (unspecified)", "outcome": "recurred", "source": "https://arxiv.org/abs/2503.05899" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0139", "title": "Tesla FSD v12 may have driven owner Max Paul Franklin 13 miles to a VA emergency room during an insulin-pump failure at 2 a.m. in North Carolina", "summary": "By his own X account, FSD v12 drove Max Paul Franklin 13 miles to a VA emergency room at 2 a.m. on 2 April 2024; uncorroborated.", "date_observed": "2024-04-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "By his own account, posted on X on 10 April 2024, Max Paul Franklin, a North Carolina television producer, had severe dehydration. His blood glucose read 670 at 2 a.m. on 2 April 2024 after his insulin pump malfunctioned. He says he got into his Tesla Model Y and engaged the Full Self-Driving (Supervised) v12 trial unlocked the day before. He says it drove the 13 miles to the VA emergency room without intervention and offered to park. It is the Charles George VA Medical Center, Asheville, per Il Fatto Quotidiano. He reports a mild heart attack and discharge with no restrictions. Tesla and Elon Musk reposted it on 11 April 2024. No hospital or official source has confirmed it.", "category": "protective response", "unexpected": false, "purpose": "FSD (Supervised) is built to navigate a Tesla to a chosen destination while an attentive driver supervises it. Driving Franklin to the destination he set is that function. Use by a driver impaired by a medical emergency is not an intended use. Hindustan Times notes the system depends on driver intervention when needed. A Tesla owner quoted by Tesla Oracle calls it a Level 2 system. It requires hands on the wheel and eyes on the road even when active.", "system": "Tesla Full Self-Driving (Supervised) v12 on a Tesla Model Y", "model_version": "FSD v12 (Supervised), unlocked on the car on 1 April 2024 per Franklin and Tesla Oracle; the exact build is not stated (The Driven describes the then-current release as 12.3.3)", "developer": "Tesla", "deployer": null, "location": "Asheville, United States", "domain": "Road transport / access to emergency care", "segment": "Consumer driver-assistance software on a privately owned vehicle", "benefit_type": "Improved Physical Health", "taxonomy_note": "The documented good is transport to emergency care; no health outcome is reported.", "registry_ids": { "oecd_aim": "2024-04-12-a558" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "By his own account Franklin reached a VA emergency room during an insulin-pump failure with blood glucose at 670. He was treated for a mild heart attack and left with no restrictions. No clinician, hospital or official source confirms the emergency, the drive or that his life was at risk. So the life-saving claim in the headlines is not established." } ], "ai_role": { "status": "unassessed", "statement": "The only description of what FSD did is Franklin's. Engaged by a double click of the stalk, it drove 13 miles to the VA emergency room without intervention and offered to park on arrival. No Tesla vehicle data, dashcam footage, hospital record, emergency-service log or official statement has been found. No outlet reports having interviewed him or the hospital. Tesla's corporate account and Elon Musk reposted the story on 11 April 2024 but added no facts. The photos attached to the post are two hospital-bed selfies and a night shot of a Model Y in a wet car park. They show no route, timestamp or hospital name. Some syndicated coverage garbles the story (Sky TG24 places him in Virginia and describes low blood sugar). The counterfactual, calling emergency services, driving himself or not reaching care, is unexamined. Commenters cited by Il Fatto Quotidiano argued he should have called for help." }, "evidence": [ { "kind": "other", "citation": "Franklin, M. P. (2024). My Crazy True Story. Post on X, @MAXPAULFRANKLIN, 10 April 2024 (04:38 UTC), status 1777918962870718909; four photos attached.", "title": "My Crazy True Story", "url": "https://x.com/MAXPAULFRANKLIN/status/1777918962870718909", "date": "2024-04-10", "written_by": "beneficiary", "quote": "In a moment of dire need, at 2:00 am the following morning, I found myself grappling with severe dehydration and a blood glucose level of 670" }, { "kind": "news report", "citation": "Mahapatra, T. D. (2024). Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds. Hindustan Times, 12 April 2024.", "title": "Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds", "url": "https://www.hindustantimes.com/world-news/us-news/elon-musk-responds-to-tesla-full-self-driving-that-drove-a-man-to-the-hospital-saving-his-life-101712894057291.html", "date": "2024-04-12", "written_by": "independent", "quote": "Without any intervention, the car skillfully navigated the 13-mile journey from my home to the VA Emergency Room." }, { "kind": "news report", "citation": "Bleakley, D. (2024). Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital. The Driven, 12 April 2024.", "title": "Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital", "url": "https://thedriven.io/2024/04/12/autonomous-ev-saves-man-tesla-model-y-drives-heart-attack-victim-20-kms-to-hospital/", "date": "2024-04-12", "written_by": "independent", "quote": "Despite enduring a mild heart attack, I left the hospital with no restrictions on my exercise regimen" }, { "kind": "news report", "citation": "Il Fatto Quotidiano (2024). Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita: \"Ha guidato da sola per 20 km fino al pronto soccorso\". 14 April 2024.", "title": "Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita", "url": "https://www.ilfattoquotidiano.it/2024/04/14/ha-un-infarto-e-crisi-glicemica-mentre-e-al-volante-la-sua-tesla-gli-salva-la-vita-ha-guidato-da-sola-per-20-km-fino-al-pronto-soccorso/7513224/", "date": "2024-04-14", "written_by": "independent", "quote": "ha percorso circa 20 chilometri senza interventi umani fino al Charles George Medical Center di Asheville, un centro medico per veterani" }, { "kind": "news report", "citation": "Ali, I. (2024). The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life. Tesla Oracle (enthusiast site), 12 April 2024.", "title": "The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life", "url": "https://www.teslaoracle.com/2024/04/12/the-true-story-of-how-fsd-v12-helped-a-tesla-owner-reach-hospital-and-saved-his-life/", "date": "2024-04-12", "written_by": "independent", "quote": "both Tesla's official X company account and Elon Musk reposted the story on the social media platform" }, { "kind": "news report", "citation": "Siasat Daily (2024). Tesla's full self-driving feature saves man's life in US; Musk responds. 12 April 2024 (the source listed by the OECD Monitor).", "title": "Tesla's full self-driving feature saves man's life in US; Musk responds", "url": "https://www.siasat.com/teslas-full-self-driving-feature-saves-mans-life-in-us-musk-responds-3007838", "date": "2024-04-12", "written_by": "independent", "quote": "Glad Tesla FSD was there to help and that you're feeling well!" } ], "replication": { "produced_by": [ "A Tesla Model Y with the FSD (Supervised) v12 trial active, which Franklin says Tesla had unlocked for all US cars on 1 April 2024", "A driver who, by his account, could still reach the car, engage FSD by double-clicking the stalk and set the emergency room as destination", "A 13-mile route to the VA emergency room that the system, on his account, completed without intervention and then offered to park" ], "must_hold": [ "FSD (Supervised) requires an attentive driver with hands on the wheel and eyes on the road (Hindustan Times; Tesla Oracle quoting owner James Locke). A driver too impaired to supervise would be outside its intended use", "The account is Franklin's alone. No hospital, emergency-service, police or vehicle-log record of the drive has been found. The photos attached to the post do not show the route, a timestamp or the hospital", "Emergency services remain the documented first resort. Il Fatto Quotidiano reports commenters arguing that he should have called for help" ], "echoes": [] }, "paired_incident": null, "headline": "FSD v12 may have driven its owner 13 miles to a VA emergency room", "metric": "drove Max Paul Franklin 13 miles to a VA emergency room", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No hospital, Tesla or press verification and no follow-up on Franklin's account was found after the April 2024 reposts.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-04-12-a558", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and the beneficiary's other. 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Il Fatto Quotidiano reports commenters arguing that he should have called for help" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-04-12-a558", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road transport / access to emergency care", "segment": "Consumer driver-assistance software on a privately owned vehicle" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Franklin, M. P. (2024). My Crazy True Story. Post on X, @MAXPAULFRANKLIN, 10 April 2024 (04:38 UTC), status 1777918962870718909; four photos attached.", "title": "My Crazy True Story", "url": "https://x.com/MAXPAULFRANKLIN/status/1777918962870718909", "date": "2024-04-10", "written_by": "beneficiary", "quote": "In a moment of dire need, at 2:00 am the following morning, I found myself grappling with severe dehydration and a blood glucose level of 670" }, { "kind": "news report", "citation": "Mahapatra, T. D. (2024). Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds. Hindustan Times, 12 April 2024.", "title": "Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds", "url": "https://www.hindustantimes.com/world-news/us-news/elon-musk-responds-to-tesla-full-self-driving-that-drove-a-man-to-the-hospital-saving-his-life-101712894057291.html", "date": "2024-04-12", "written_by": "independent", "quote": "Without any intervention, the car skillfully navigated the 13-mile journey from my home to the VA Emergency Room." }, { "kind": "news report", "citation": "Bleakley, D. (2024). Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital. The Driven, 12 April 2024.", "title": "Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital", "url": "https://thedriven.io/2024/04/12/autonomous-ev-saves-man-tesla-model-y-drives-heart-attack-victim-20-kms-to-hospital/", "date": "2024-04-12", "written_by": "independent", "quote": "Despite enduring a mild heart attack, I left the hospital with no restrictions on my exercise regimen" }, { "kind": "news report", "citation": "Il Fatto Quotidiano (2024). Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita: \"Ha guidato da sola per 20 km fino al pronto soccorso\". 14 April 2024.", "title": "Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita", "url": "https://www.ilfattoquotidiano.it/2024/04/14/ha-un-infarto-e-crisi-glicemica-mentre-e-al-volante-la-sua-tesla-gli-salva-la-vita-ha-guidato-da-sola-per-20-km-fino-al-pronto-soccorso/7513224/", "date": "2024-04-14", "written_by": "independent", "quote": "ha percorso circa 20 chilometri senza interventi umani fino al Charles George Medical Center di Asheville, un centro medico per veterani" }, { "kind": "news report", "citation": "Ali, I. (2024). The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life. Tesla Oracle (enthusiast site), 12 April 2024.", "title": "The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life", "url": "https://www.teslaoracle.com/2024/04/12/the-true-story-of-how-fsd-v12-helped-a-tesla-owner-reach-hospital-and-saved-his-life/", "date": "2024-04-12", "written_by": "independent", "quote": "both Tesla's official X company account and Elon Musk reposted the story on the social media platform" }, { "kind": "news report", "citation": "Siasat Daily (2024). Tesla's full self-driving feature saves man's life in US; Musk responds. 12 April 2024 (the source listed by the OECD Monitor).", "title": "Tesla's full self-driving feature saves man's life in US; Musk responds", "url": "https://www.siasat.com/teslas-full-self-driving-feature-saves-mans-life-in-us-musk-responds-3007838", "date": "2024-04-12", "written_by": "independent", "quote": "Glad Tesla FSD was there to help and that you're feeling well!" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0139-source-0001", "AIBD-0139-source-0002", "AIBD-0139-source-0003", "AIBD-0139-source-0004", "AIBD-0139-source-0005", "AIBD-0139-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Franklin, M. P. (2024). My Crazy True Story. Post on X, @MAXPAULFRANKLIN, 10 April 2024 (04:38 UTC), status 1777918962870718909; four photos attached.", "title": "My Crazy True Story", "url": "https://x.com/MAXPAULFRANKLIN/status/1777918962870718909", "date": "2024-04-10", "written_by": "beneficiary", "quote": "In a moment of dire need, at 2:00 am the following morning, I found myself grappling with severe dehydration and a blood glucose level of 670" }, { "kind": "news report", "citation": "Mahapatra, T. D. (2024). Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds. Hindustan Times, 12 April 2024.", "title": "Tesla FSD navigated 13-mile journey to Emergency Room to save a man, Elon Musk responds", "url": "https://www.hindustantimes.com/world-news/us-news/elon-musk-responds-to-tesla-full-self-driving-that-drove-a-man-to-the-hospital-saving-his-life-101712894057291.html", "date": "2024-04-12", "written_by": "independent", "quote": "Without any intervention, the car skillfully navigated the 13-mile journey from my home to the VA Emergency Room." }, { "kind": "news report", "citation": "Bleakley, D. (2024). Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital. The Driven, 12 April 2024.", "title": "Autonomous EV saves man: Tesla Model Y drives heart attack victim 20 kms to hospital", "url": "https://thedriven.io/2024/04/12/autonomous-ev-saves-man-tesla-model-y-drives-heart-attack-victim-20-kms-to-hospital/", "date": "2024-04-12", "written_by": "independent", "quote": "Despite enduring a mild heart attack, I left the hospital with no restrictions on my exercise regimen" }, { "kind": "news report", "citation": "Il Fatto Quotidiano (2024). Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita: \"Ha guidato da sola per 20 km fino al pronto soccorso\". 14 April 2024.", "title": "Ha un infarto e crisi glicemica mentre è al volante, la sua Tesla gli salva la vita", "url": "https://www.ilfattoquotidiano.it/2024/04/14/ha-un-infarto-e-crisi-glicemica-mentre-e-al-volante-la-sua-tesla-gli-salva-la-vita-ha-guidato-da-sola-per-20-km-fino-al-pronto-soccorso/7513224/", "date": "2024-04-14", "written_by": "independent", "quote": "ha percorso circa 20 chilometri senza interventi umani fino al Charles George Medical Center di Asheville, un centro medico per veterani" }, { "kind": "news report", "citation": "Ali, I. (2024). The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life. Tesla Oracle (enthusiast site), 12 April 2024.", "title": "The true story of how FSD V12 helped a Tesla owner reach hospital and saved his life", "url": "https://www.teslaoracle.com/2024/04/12/the-true-story-of-how-fsd-v12-helped-a-tesla-owner-reach-hospital-and-saved-his-life/", "date": "2024-04-12", "written_by": "independent", "quote": "both Tesla's official X company account and Elon Musk reposted the story on the social media platform" }, { "kind": "news report", "citation": "Siasat Daily (2024). Tesla's full self-driving feature saves man's life in US; Musk responds. 12 April 2024 (the source listed by the OECD Monitor).", "title": "Tesla's full self-driving feature saves man's life in US; Musk responds", "url": "https://www.siasat.com/teslas-full-self-driving-feature-saves-mans-life-in-us-musk-responds-3007838", "date": "2024-04-12", "written_by": "independent", "quote": "Glad Tesla FSD was there to help and that you're feeling well!" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "By his own X account, FSD v12 drove Max Paul Franklin 13 miles to a VA emergency room at 2 a.m. on 2 April 2024; uncorroborated.", "account": "By his own account, posted on X on 10 April 2024, Max Paul Franklin, a North Carolina television producer, had severe dehydration. His blood glucose read 670 at 2 a.m. on 2 April 2024 after his insulin pump malfunctioned. He says he got into his Tesla Model Y and engaged the Full Self-Driving (Supervised) v12 trial unlocked the day before. He says it drove the 13 miles to the VA emergency room without intervention and offered to park. It is the Charles George VA Medical Center, Asheville, per Il Fatto Quotidiano. He reports a mild heart attack and discharge with no restrictions. Tesla and Elon Musk reposted it on 11 April 2024. No hospital or official source has confirmed it." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "Franklin reported that the system drove his car to an emergency department." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Franklin reported using Full Self-Driving v12 (Supervised), which was enabled on the car on 1 April 2024." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Franklin reported using Full Self-Driving v12 (Supervised), which was enabled on the car on 1 April 2024.", "editor_note": "Franklin identified FSD v12, but not the exact build. The Driven described 12.3.3 as the release available at that time, which does not establish the build installed in his car." } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "FSD v12 (Supervised), unlocked on the car on 1 April 2024 per Franklin and Tesla Oracle; the exact build is not stated (The Driven describes the then-current release as 12.3.3)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Full Self-Driving v12. The exact installed build is not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Full Self-Driving (Supervised) v12 on a Tesla Model Y" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Tesla FSD v12 may have driven owner Max Paul Franklin 13 miles to a VA emergency room during an insulin-pump failure at 2 a.m. in North Carolina", "headline": "FSD v12 may have driven its owner 13 miles to a VA emergency room" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "30a7d74ae7f9787d5e21a108d1b2a9e070adae84f56e12764d35c518e90f877e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "By his own account, posted on X on 10 April 2024, Max Paul Franklin, a North Carolina television producer, had severe dehydration. His blood glucose read 670 at 2 a.m. on 2 April 2024 after his insulin pump malfunctioned. He says he got into his Tesla Model Y and engaged the Full Self-Driving (Supervised) v12 trial unlocked the day before. He says it drove the 13 miles to the VA emergency room without intervention and offered to park. It is the Charles George VA Medical Center, Asheville, per Il Fatto Quotidiano. He reports a mild heart attack and discharge with no restrictions. Tesla and Elon Musk reposted it on 11 April 2024. No hospital or official source has confirmed it.", "replication": { "produced_by": [ "A Tesla Model Y with the FSD (Supervised) v12 trial active, which Franklin says Tesla had unlocked for all US cars on 1 April 2024", "A driver who, by his account, could still reach the car, engage FSD by double-clicking the stalk and set the emergency room as destination", "A 13-mile route to the VA emergency room that the system, on his account, completed without intervention and then offered to park" ], "must_hold": [ "FSD (Supervised) requires an attentive driver with hands on the wheel and eyes on the road (Hindustan Times; Tesla Oracle quoting owner James Locke). A driver too impaired to supervise would be outside its intended use", "The account is Franklin's alone. No hospital, emergency-service, police or vehicle-log record of the drive has been found. The photos attached to the post do not show the route, a timestamp or the hospital", "Emergency services remain the documented first resort. Il Fatto Quotidiano reports commenters arguing that he should have called for help" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0370", "title": "Fujifilm AI endoscopy at St. Martin De Porres Hospital, Chiayi, marks a 1 to 1.5 cm adenoma in a man in his 50s; pathology shows stage I colorectal cancer, removed endoscopically", "summary": "After a positive fecal occult blood test, Fujifilm AI endoscopy at St. Martin De Porres Hospital, Chiayi, marked a 1 to 1.5 cm adenoma; pathology: stage I colorectal cancer, removed endoscopically.", "date_observed": "2024-04-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Three Taiwanese outlets reported on 19 April 2024 on a man in his 50s. He attended free colorectal cancer screening at St. Martin De Porres Hospital in Chiayi City. He tested positive for fecal occult blood and was scheduled for an AI-assisted endoscopy (Liberty Times Net health). Gastroenterologist Zheng Xu-sheng said the hospital introduced a Fujifilm 7000-series endoscope in 2023. It installed what it calls the nation's first Fujifilm AI system (Liberty Times Net; Taiwan Good News). During the examination the AI system marked a suspicious polyp with a colored frame and sounded an alert. It was diagnosed as a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer. It was removed immediately through the endoscope (Taiwan Good News; Guan Chuan Media). Zheng said polyps over 1 cm risk malignant change and advised free screening every two years after 50 (Guan Chuan Media). The procedure date is not given.", "category": "benefit created", "unexpected": false, "purpose": "The Fujifilm AI system is built to mark suspicious polyps on the endoscopic image with a colored frame and sound. The physician then inspects and removes them. Flagging this adenoma was that function.", "system": "Fujifilm AI endoscopy system on a Fujifilm 7000-series gastrointestinal endoscope (product name not given in the sources)", "model_version": null, "developer": "Fujifilm", "deployer": "St. Martin De Porres Hospital (天主教聖馬爾定醫院), Chiayi", "location": "Chiayi, Taiwan", "domain": "Healthcare - colorectal cancer screening", "segment": "AI-assisted colonoscopy in hospital screening", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2024-04-19-de89" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A stage I colorectal cancer inside a 1 to 1.5 cm adenoma was removed through the endoscope without surgery, per all three reports. A survival benefit is plausible for an early-stage cancer but is not demonstrated in the sources." } ], "ai_role": { "status": "assessed", "statement": "Taiwan Good News and Guan Chuan Media state that the AI system marked the suspicious polyp with a colored frame and sound during the examination. The physician then diagnosed and removed it. No source says the physician would have missed a 1 to 1.5 cm polyp in a patient already referred for a positive stool test. So the AI's share of this detection cannot be separated from the colonoscopy itself. All three reports relay the hospital's account. No clinical study of the system at this hospital was cited." }, "evidence": [ { "kind": "news report", "citation": "丁偉杰 (2024). AI輔助醫師判讀瘜肉 大腸癌無所遁形. 自由健康網 (Liberty Times Net), 19 April 2024.", "title": "AI輔助醫師判讀瘜肉 大腸癌無所遁形", "url": "https://health.ltn.com.tw/article/breakingnews/4646402", "date": "2024-04-19", "written_by": "independent", "quote": "發現可疑瘜肉，經切片檢查證實為第一期大腸癌" }, { "kind": "news report", "citation": "劉芳妃 (2024). 聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形. 台灣好報 via Yahoo奇摩新聞, 19 April 2024.", "title": "聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/%E8%81%96%E9%A6%AC%E7%88%BE%E5%AE%9A%E9%86%AB%E9%99%A2%E9%81%8B%E7%94%A8ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-052431696.html", "date": "2024-04-19", "written_by": "independent", "quote": "AI系統以色框標註並發出聲響，提示醫師可疑瘜肉" }, { "kind": "news report", "citation": "吳東林 (2024). AI內視鏡檢查 大腸癌無所遁形. 觀傳媒 via Yahoo奇摩新聞, 19 April 2024.", "title": "AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-113000020.html", "date": "2024-04-19", "written_by": "independent", "quote": "診斷為1~1.5公分的腺瘤，經切片檢查證實為第一期大腸癌" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer. OECD.AI, 19 April 2024.", "title": "AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer", "url": "https://oecd.ai/en/incidents/2024-04-19-de89", "date": "2024-04-19", "written_by": "independent", "quote": "The AI system enabled early identification and removal of a cancerous polyp in a patient" } ], "replication": { "produced_by": [ "A positive fecal occult blood test in a free screening program, followed by colonoscopy", "A Fujifilm AI system that marks suspicious polyps with a colored frame and a sound during the examination", "Endoscopic removal and pathology at the same hospital" ], "must_hold": [ "Patients attend screening and follow a positive stool test with colonoscopy", "The endoscopist inspects and acts on the AI's marks", "Bowel preparation adequate for the camera to see the mucosa" ], "echoes": [] }, "paired_incident": null, "headline": "AI colonoscopy flags a polyp; stage I cancer removed in Chiayi", "metric": "a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer", "comparator": null, "later": null, "value": null, "developer_country": "Japan", "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-04-19-de89", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Fujifilm; https://www.stm.org.tw/stm_en/about_02.asp", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0370", "catalog_version": "1.0.0", "source_fingerprint": "68e1b533424bebb2ff296a14d808d315223bbe0898c71651f0655159ed5886ed", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0370-source-0001", "AIBD-0370-source-0002", "AIBD-0370-source-0003", "AIBD-0370-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Fujifilm", "deployer": "St. Martin De Porres Hospital (天主教聖馬爾定醫院), Chiayi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Taiwan Good News and Guan Chuan Media state that the AI system marked the suspicious polyp with a colored frame and sound during the examination. The physician then diagnosed and removed it. No source says the physician would have missed a 1 to 1.5 cm polyp in a patient already referred for a positive stool test. So the AI's share of this detection cannot be separated from the colonoscopy itself. All three reports relay the hospital's account. No clinical study of the system at this hospital was cited." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Taiwan Good News and Guan Chuan Media state that the AI system marked the suspicious polyp with a colored frame and sound during the examination. The physician then diagnosed and removed it. No source says the physician would have missed a 1 to 1.5 cm polyp in a patient already referred for a positive stool test. So the AI's share of this detection cannot be separated from the colonoscopy itself. All three reports relay the hospital's account. No clinical study of the system at this hospital was cited." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A stage I colorectal cancer inside a 1 to 1.5 cm adenoma was removed through the endoscope without surgery, per all three reports. A survival benefit is plausible for an early-stage cancer but is not demonstrated in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A stage I colorectal cancer inside a 1 to 1.5 cm adenoma was removed through the endoscope without surgery, per all three reports. A survival benefit is plausible for an early-stage cancer but is not demonstrated in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A stage I colorectal cancer inside a 1 to 1.5 cm adenoma was removed through the endoscope without surgery, per all three reports. 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"not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2024-04-19-de89" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0370" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Three Taiwanese outlets reported on 19 April 2024 on a man in his 50s. He attended free colorectal cancer screening at St. Martin De Porres Hospital in Chiayi City. He tested positive for fecal occult blood and was scheduled for an AI-assisted endoscopy (Liberty Times Net health). Gastroenterologist Zheng Xu-sheng said the hospital introduced a Fujifilm 7000-series endoscope in 2023. It installed what it calls the nation's first Fujifilm AI system (Liberty Times Net; Taiwan Good News). During the examination the AI system marked a suspicious polyp with a colored frame and sounded an alert. It was diagnosed as a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer. It was removed immediately through the endoscope (Taiwan Good News; Guan Chuan Media). Zheng said polyps over 1 cm risk malignant change and advised free screening every two years after 50 (Guan Chuan Media). The procedure date is not given.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A stage I colorectal cancer inside a 1 to 1.5 cm adenoma was removed through the endoscope without surgery, per all three reports. A survival benefit is plausible for an early-stage cancer but is not demonstrated in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The Fujifilm AI system is built to mark suspicious polyps on the endoscopic image with a colored frame and sound. The physician then inspects and removes them. Flagging this adenoma was that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Chiayi, Taiwan", "developer_country": "Japan", "deployer_country": "Taiwan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The Fujifilm AI system is built to mark suspicious polyps on the endoscopic image with a colored frame and sound. The physician then inspects and removes them. Flagging this adenoma was that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-04-19", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-04-19-de89", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Fujifilm; https://www.stm.org.tw/stm_en/about_02.asp", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A positive fecal occult blood test in a free screening program, followed by colonoscopy", "A Fujifilm AI system that marks suspicious polyps with a colored frame and a sound during the examination", "Endoscopic removal and pathology at the same hospital" ], "must_hold": [ "Patients attend screening and follow a positive stool test with colonoscopy", "The endoscopist inspects and acts on the AI's marks", "Bowel preparation adequate for the camera to see the mucosa" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-04-19-de89", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Fujifilm; https://www.stm.org.tw/stm_en/about_02.asp", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - colorectal cancer screening", "segment": "AI-assisted colonoscopy in hospital screening" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "丁偉杰 (2024). AI輔助醫師判讀瘜肉 大腸癌無所遁形. 自由健康網 (Liberty Times Net), 19 April 2024.", "title": "AI輔助醫師判讀瘜肉 大腸癌無所遁形", "url": "https://health.ltn.com.tw/article/breakingnews/4646402", "date": "2024-04-19", "written_by": "independent", "quote": "發現可疑瘜肉，經切片檢查證實為第一期大腸癌" }, { "kind": "news report", "citation": "劉芳妃 (2024). 聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形. 台灣好報 via Yahoo奇摩新聞, 19 April 2024.", "title": "聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/%E8%81%96%E9%A6%AC%E7%88%BE%E5%AE%9A%E9%86%AB%E9%99%A2%E9%81%8B%E7%94%A8ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-052431696.html", "date": "2024-04-19", "written_by": "independent", "quote": "AI系統以色框標註並發出聲響，提示醫師可疑瘜肉" }, { "kind": "news report", "citation": "吳東林 (2024). AI內視鏡檢查 大腸癌無所遁形. 觀傳媒 via Yahoo奇摩新聞, 19 April 2024.", "title": "AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-113000020.html", "date": "2024-04-19", "written_by": "independent", "quote": "診斷為1~1.5公分的腺瘤，經切片檢查證實為第一期大腸癌" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer. OECD.AI, 19 April 2024.", "title": "AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer", "url": "https://oecd.ai/en/incidents/2024-04-19-de89", "date": "2024-04-19", "written_by": "independent", "quote": "The AI system enabled early identification and removal of a cancerous polyp in a patient" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0370-source-0001", "AIBD-0370-source-0002", "AIBD-0370-source-0003", "AIBD-0370-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "丁偉杰 (2024). AI輔助醫師判讀瘜肉 大腸癌無所遁形. 自由健康網 (Liberty Times Net), 19 April 2024.", "title": "AI輔助醫師判讀瘜肉 大腸癌無所遁形", "url": "https://health.ltn.com.tw/article/breakingnews/4646402", "date": "2024-04-19", "written_by": "independent", "quote": "發現可疑瘜肉，經切片檢查證實為第一期大腸癌" }, { "kind": "news report", "citation": "劉芳妃 (2024). 聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形. 台灣好報 via Yahoo奇摩新聞, 19 April 2024.", "title": "聖馬爾定醫院運用AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/%E8%81%96%E9%A6%AC%E7%88%BE%E5%AE%9A%E9%86%AB%E9%99%A2%E9%81%8B%E7%94%A8ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-052431696.html", "date": "2024-04-19", "written_by": "independent", "quote": "AI系統以色框標註並發出聲響，提示醫師可疑瘜肉" }, { "kind": "news report", "citation": "吳東林 (2024). AI內視鏡檢查 大腸癌無所遁形. 觀傳媒 via Yahoo奇摩新聞, 19 April 2024.", "title": "AI內視鏡檢查 大腸癌無所遁形", "url": "https://tw.news.yahoo.com/ai%E5%85%A7%E8%A6%96%E9%8F%A1%E6%AA%A2%E6%9F%A5-%E5%A4%A7%E8%85%B8%E7%99%8C%E7%84%A1%E6%89%80%E9%81%81%E5%BD%A2-113000020.html", "date": "2024-04-19", "written_by": "independent", "quote": "診斷為1~1.5公分的腺瘤，經切片檢查證實為第一期大腸癌" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer. OECD.AI, 19 April 2024.", "title": "AI-Assisted Endoscopy Enables Early Detection and Removal of Colorectal Cancer", "url": "https://oecd.ai/en/incidents/2024-04-19-de89", "date": "2024-04-19", "written_by": "independent", "quote": "The AI system enabled early identification and removal of a cancerous polyp in a patient" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "After a positive fecal occult blood test, Fujifilm AI endoscopy at St. Martin De Porres Hospital, Chiayi, marked a 1 to 1.5 cm adenoma; pathology: stage I colorectal cancer, removed endoscopically.", "account": "Three Taiwanese outlets reported on 19 April 2024 on a man in his 50s. He attended free colorectal cancer screening at St. Martin De Porres Hospital in Chiayi City. He tested positive for fecal occult blood and was scheduled for an AI-assisted endoscopy (Liberty Times Net health). Gastroenterologist Zheng Xu-sheng said the hospital introduced a Fujifilm 7000-series endoscope in 2023. It installed what it calls the nation's first Fujifilm AI system (Liberty Times Net; Taiwan Good News). During the examination the AI system marked a suspicious polyp with a colored frame and sounded an alert. It was diagnosed as a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer. It was removed immediately through the endoscope (Taiwan Good News; Guan Chuan Media). Zheng said polyps over 1 cm risk malignant change and advised free screening every two years after 50 (Guan Chuan Media). The procedure date is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fujifilm AI endoscopy system on a Fujifilm 7000-series gastrointestinal endoscope (product name not given in the sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Fujifilm" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fujifilm AI endoscopy at St. Martin De Porres Hospital, Chiayi, marks a 1 to 1.5 cm adenoma in a man in his 50s; pathology shows stage I colorectal cancer, removed endoscopically", "headline": "AI colonoscopy flags a polyp; stage I cancer removed in Chiayi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "68e1b533424bebb2ff296a14d808d315223bbe0898c71651f0655159ed5886ed" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Three Taiwanese outlets reported on 19 April 2024 on a man in his 50s. He attended free colorectal cancer screening at St. Martin De Porres Hospital in Chiayi City. He tested positive for fecal occult blood and was scheduled for an AI-assisted endoscopy (Liberty Times Net health). Gastroenterologist Zheng Xu-sheng said the hospital introduced a Fujifilm 7000-series endoscope in 2023. It installed what it calls the nation's first Fujifilm AI system (Liberty Times Net; Taiwan Good News). During the examination the AI system marked a suspicious polyp with a colored frame and sounded an alert. It was diagnosed as a 1 to 1.5 cm adenoma that biopsy confirmed as stage I colorectal cancer. It was removed immediately through the endoscope (Taiwan Good News; Guan Chuan Media). Zheng said polyps over 1 cm risk malignant change and advised free screening every two years after 50 (Guan Chuan Media). The procedure date is not given.", "replication": { "produced_by": [ "A positive fecal occult blood test in a free screening program, followed by colonoscopy", "A Fujifilm AI system that marks suspicious polyps with a colored frame and a sound during the examination", "Endoscopic removal and pathology at the same hospital" ], "must_hold": [ "Patients attend screening and follow a positive stool test with colonoscopy", "The endoscopist inspects and acts on the AI's marks", "Bowel preparation adequate for the camera to see the mucosa" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0578", "title": "AI-ECG mortality alerts reduce 90-day deaths in a randomized trial in Taiwan", "summary": "A Taiwanese randomized trial involving 15,965 patients found 90-day mortality of 3.6% with AI-ECG alerts versus 4.3% with usual care.", "date_observed": "2024-04-29", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "An academic medical center and a community hospital in Taiwan tested AI-ECG alerts with 39 physicians and 15,965 patients. Patients were randomly assigned to AI-assisted care or usual care. Ninety-day all-cause mortality, the primary endpoint, was 3.6% versus 4.3%, respectively: hazard ratio 0.83, with a 95% confidence interval of 0.70–0.99. The prespecified high-risk subgroup had a hazard ratio of 0.69 (0.53–0.90). The trial covered ECGs collected from December 15, 2021, through April 30, 2022. Longer-term survival and generalizability to other health systems remain uncertain.", "category": "general benefit", "unexpected": false, "purpose": "Identify patients at high risk of death and prompt timely clinical assessment.", "system": "AI-ECG mortality prediction and physician alert system", "model_version": null, "developer": "National Defense Medical Center and Tri-Service General Hospital research team", "deployer": "An academic medical center and a community hospital in Taiwan", "location": "Taiwan", "domain": "Healthcare - mortality prevention", "segment": "ECG-based clinical decision support", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "clinicaltrials_gov": "NCT05118035" }, "ratings": [ { "group": "personal", "depth": 5, "reason": "The randomized trial measured lower all-cause mortality within 90 days." } ], "ai_role": { "status": "assessed", "statement": "A convolutional neural network assessed ECGs and sent high-risk alerts to physicians. Clinicians selected further assessment and treatment. The trial evaluated this combined care pathway. The precise mechanism of the survival improvement remains uncertain." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Lin CS, Liu WT, Tsai DJ, et al. (2024). Nature Medicine 30:1461–1470. doi:10.1038/s41591-024-02961-4. Randomized trial conducted by the system's research team. Figures 1–4; Methods; Supplementary Note 1 and Figure 1.", "title": "AI-enabled electrocardiography alert intervention and all-cause mortality: a pragmatic randomized clinical trial", "url": "https://www.nature.com/articles/s41591-024-02961-4", "date": "2024-04-29", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Hsieh PH, Lin C, Lin CS, et al. (2025). npj Digital Medicine 8:348. doi:10.1038/s41746-025-01735-7. Analysis of the same trial. Methods, limitations, and supplementary Tables 1–3.", "title": "Economic analysis of an AI-enabled ECG alert system: impact on mortality outcomes from a pragmatic randomized trial", "url": "https://www.nature.com/articles/s41746-025-01735-7", "date": "2025-06-11", "written_by": "deployer", "quote": null }, { "kind": "other", "citation": "Chin Lin, ECGSurvNet, commit 68e3b7c58491a38d731d43626f98443e53d035a5, January 21, 2022.", "title": "ECGSurvNet training code and model architecture", "url": "https://github.com/Imshepherd/ECGSurvNet/tree/68e3b7c58491a38d731d43626f98443e53d035a5", "date": "2022-01-21", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Routine ECGs were analyzed automatically, with warnings sent to physicians and risk reports available in the electronic health record.", "Physicians assessed alerted patients and selected care using their clinical judgment." ], "must_hold": [ "Reliable ECG transfer and clinicians able to assess alerts are likely requirements. Effectiveness in other health systems requires evaluation." ], "echoes": [] }, "paired_incident": null, "headline": "Taiwan AI-ECG alerts reduce mortality in a randomized trial", "metric": "3.6% versus 4.3%", "comparator": { "against": "Patients randomly assigned to usual care without AI-ECG alerts", "before": "4.3% mortality within 90 days", "after": "3.6% mortality within 90 days", "basis": "measured", "quote": "3.6% patients in the intervention group died within 90 days, compared to 4.3% in the control group", "url": "https://www.nature.com/articles/s41591-024-02961-4" }, "later": null, "value": null, "developer_country": "Taiwan", "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://www.nature.com/articles/s41591-024-02961-4", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original AI-ECG trial, extended data, supplementary protocol and registration, and followed its model reference to the original development study. Retained the economic paper for its additional cost analysis, explicitly as a reanalysis of the same patients. Recorded licensing interests and the restrictions on model weights and patient-level data.", "source": "https://www.nature.com/articles/s41591-024-02961-4", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified the AI model, software, configuration, and human controls from the original paper, supplement, or author documentation.", "source": "https://www.nature.com/articles/s41591-024-02961-4", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the original evidence and supporting material; updated system details, methods, outcomes, limitations, costs, and source lineage.", "source": "https://www.nature.com/articles/s41591-024-02961-4", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' other and the deployer's peer-reviewed study. 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The price of the AI service and the cost-effectiveness calculations were modeled." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "Taiwan’s National Health Insurance was the stated perspective. Hospital records included insurance reimbursement and patients’ out-of-pocket spending." }, "provenance": { "kind": "source_review", "basis": "Hsieh et al. (2025), Tables 1–2; Methods: Health resource utilization and cost; Statistical analysis; Discussion: limitations.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Taiwan’s National Health Insurance was the stated perspective. Hospital records included insurance reimbursement and patients’ out-of-pocket spending." } }, "economics[].return_payback": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Results and Discussion of the economic analysis.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0002" ], "reviewed_on": "2026-10-25" }, "reason": "The study did not estimate profit, a financial return, or a payback period.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study did not estimate profit, a financial return, or a payback period." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "The authors divided additional costs by deaths averted and used 5,000 bootstrap samples to estimate uncertainty." }, "provenance": { "kind": "source_review", "basis": "Hsieh et al. 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It does not identify which subsequent clinical actions produced the survival difference." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Usual care without the AI-ECG report or high-risk alert during the 90-day follow-up." }, "provenance": { "kind": "source_review", "basis": "Lin et al., Nature Medicine (2024), Results, Figures 1–4, Methods, and Supplementary Note 1.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Usual care without the AI-ECG report or high-risk alert during the 90-day follow-up." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "An unblinded, pragmatic randomized trial with patients assigned to alerts or usual care. 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(2025), Methods and Discussion.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The 2025 publication analyzes costs from the same trial. It does not extend clinical follow-up beyond 90 days." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Physicians reviewed the alerts and chose further tests and treatment. The system did not prescribe or administer care." }, "provenance": { "kind": "source_review", "basis": "Lin et al., Nature Medicine (2024), Results, Figures 1–4, Methods, and Supplementary Note 1.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Physicians reviewed the alerts and chose further tests and treatment. The system did not prescribe or administer care." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0578" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The trial used Philips 12-lead ECG machines, automatic uploads, a private cloud with an NVIDIA DGX-1, electronic records, and smartphone alerts." }, "provenance": { "kind": "source_review", "basis": "Methods: The AI-ECG system and intervention.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The trial used Philips 12-lead ECG machines, automatic uploads, a private cloud with an NVIDIA DGX-1, electronic records, and smartphone alerts." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Adult emergency and hospitalized patients whose physicians participated in the trial." }, "provenance": { "kind": "source_review", "basis": "Lin et al., Nature Medicine (2024), Results, Figures 1–4, Methods, and Supplementary Note 1.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Adult emergency and hospitalized patients whose physicians participated in the trial." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "structured", "data": { "randomized_records": 16335, "excluded": 370, "analyzed": 15965, "AI": 8001, "usual_care": 7964, "physicians": 39, "high_risk": { "AI": 709, "usual_care": 688 } } }, "provenance": { "kind": "source_review", "basis": "Figure 1 and Methods: Participants; allocation and post-randomization exclusions.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The analysis included 8,001 patients assigned to AI alerts and 7,964 assigned to usual care. It does not identify individual lives saved." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "Fewer patients died within 90 days when their physicians received AI-ECG alerts." }, "provenance": { "kind": "source_review", "basis": "Lin et al., Nature Medicine (2024), Results, Figures 1–4, Methods, and Supplementary Note 1.", "record_fields": [], "source_refs": [ "AIBD-0578-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Fewer patients died within 90 days when their physicians received AI-ECG alerts." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "The trial included an academic center and a community hospital. 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Effectiveness in other health systems requires evaluation." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 83, "reviewed": 76, "record_mapped": 11, "not_assessed": 4, "complete": false, "by_state": { "value_present": 83, "not_reported": 4, "unresolved": 0, "not_assessed": 4, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0263", "title": "Neuralink N1 lets Noland Arbaugh control a cursor and play chess by thought; use continues at 28 months", "summary": "First PRIME-study participant, implanted at Barrow in January 2024, controls a computer by thought; threads retracted after a month, software fixes restored use; a second user drives a robot arm.", "date_observed": "2024-05-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Noland Arbaugh, paralyzed after a diving accident, received the Neuralink N1 implant at Barrow Neurological Institute, Phoenix, in January 2024 (ABC15, 2 May 2024). He demonstrated online chess and cursor movement by thought. ABC News (17 May 2024) reported that threads retracted from his brain and removal was considered. It quoted him: “I can control a computer just like anyone else can”. Neuralink said it modified the recording algorithm and the translation of signals into cursor movements. Tech Times (28 May 2026) reported roughly 85% of threads retracted about a month after surgery and recovery through software refinement. It gave about 10 hours of daily use for chess, coursework, scheduling and communication at 28 months. Barrow (29 April 2026) reported the second participant, Alex Conley (C4-C5 injury, CONVOY study), controlling a robotic arm to operate light switches and doors. The Debrief (7 July 2025) counted 7 users, 6 implanted at Barrow. Nature news (6 August 2024) noted the device “has been adjusted in a bid to prevent glitches”. No peer-reviewed report of participant outcomes was found in Europe PMC. Neuralink's own blog could not be opened. The implant was in January 2024.", "category": "benefit created", "unexpected": false, "purpose": "Restore digital autonomy (cursor control, later robotic-arm control) to people with quadriplegia through an implanted brain-computer interface", "system": "Neuralink N1 implant with cursor-decoding software (PRIME study; CONVOY study for the robotic arm)", "model_version": "N1", "developer": "Neuralink", "deployer": "Barrow Neurological Institute (surgical site) with Neuralink", "location": "Phoenix, Arizona, USA", "domain": "Health; assistive technology", "segment": "People with quadriplegia (spinal cord injury, ALS)", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Arbaugh reports computer control “just like anyone else can” and about 10 hours of daily use at 28 months. Conley operates a robotic arm for light switches and doors." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported." }, { "group": "societal", "depth": null, "reason": "Seven users as of July 2025; no population-level effect." } ], "ai_role": { "status": "assessed", "statement": "The decoding software that maps neural signals to cursor and arm movement is Neuralink's. Its role is described only in company statements quoted by news outlets (recording algorithm modified, signal-to-cursor translation improved). Outcomes rest on the participant's own account, Barrow's patient story and press reports, not on a peer-reviewed report." }, "evidence": [ { "kind": "news report", "citation": "ABC15 Arizona, 2 May 2024", "title": "Elon Musk's Neuralink begins clinical trials in Phoenix", "url": "https://www.abc15.com/news/business/elon-musks-neuralink-begins-clinical-trials-in-phoenix", "date": "2024-05-02", "written_by": "independent", "quote": "a significant milestone that could potentially restore autonomy to millions of adults with unmet medical needs." }, { "kind": "news report", "citation": "ABC News / Good Morning America, 17 May 2024", "title": "Neuralink's first brain implant patient feared device would have to be removed", "url": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322", "date": "2024-05-17", "written_by": "independent", "quote": "I can control a computer just like anyone else can, which is not something I was able to do beforehand." }, { "kind": "press release", "citation": "Barrow Neurological Institute patient story, 29 Apr 2026", "title": "Barrow Patient Begins to Reclaim Independence With Neuralink Robotic Arm After Spinal Cord Injury", "url": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/", "date": "2026-04-29", "written_by": "deployer", "quote": "Most of us take for granted our ability to interact with the physical world. With this technology, we're giving that back to the patients." }, { "kind": "news report", "citation": "Tech Times, 28 May 2026", "title": "Neuralink BCI After 28 Months: Arbaugh Tells Robotics Summit What Published Research Cannot", "url": "https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "date": "2026-05-28", "written_by": "independent", "quote": "It sucked. It was really, really hard." }, { "kind": "news report", "citation": "The Debrief, 7 Jul 2025", "title": "Neuralink Hits 7 Users as Global Brain Implant Count Remains Under 100", "url": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/", "date": "2025-07-07", "written_by": "independent", "quote": "Today, Neuralink released a special update that recognized PRIME Study patients' contributions to research" }, { "kind": "news report", "citation": "Naddaf M, Drew L. Nature 632:481-482 (2024)", "title": "Second brain implant by Elon Musk's Neuralink: will it fare better than the first?", "url": "https://www.nature.com/articles/d41586-024-02368-8", "date": "2024-08-06", "written_by": "independent", "quote": "Device allowing the user to control a computer cursor using their thoughts has been adjusted in a bid to prevent glitches with the first implant." } ], "replication": { "produced_by": [ "Implanted electrode threads in motor cortex", "Company decoding software translating neural signals into cursor or robotic-arm commands", "Software recalibration after thread retraction" ], "must_hold": [ "Electrode threads remain sufficiently in place or software compensates", "Daily use continues to be reported by the user", "Peer-reviewed outcome reporting (absent so far)" ], "echoes": [ { "date": "2026-04-29", "setting": "Alex Conley, second participant, robotic-arm control (CONVOY study) at Barrow", "model_version": "N1", "outcome": "recurred", "source": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/" }, { "date": "2025-07-07", "setting": "Seven users reported, six implanted at Barrow", "model_version": "N1", "outcome": "unknown", "source": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/" } ] }, "paired_incident": null, "headline": "Neuralink N1 lets Noland Arbaugh control a cursor by thought", "metric": "10 hours of daily use for chess, coursework, scheduling and communication at 28 months", "comparator": { "against": "Arbaugh's own ability to use a computer before the implant (self-report)", "before": "not something I was able to do beforehand", "after": "I can control a computer just like anyone else can", "basis": "assumed", "quote": "I can control a computer just like anyone else can, which is not something I was able to do beforehand.", "url": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322" }, "later": { "status": "scaled", "date": "2026-05-28", "note": "By May 2026 Arbaugh had used the implant for 28 months, about 10 hours a day after software changes compensated for an early 85% thread retraction, and the PRIME trial had enrolled more than 20 participants across four countries.", "quote": "As of early 2026, the trial had enrolled more than 20 participants across sites in the US, UK, Canada, and United Arab Emirates.", "url": "https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322; https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Neuralink; https://en.wikipedia.org/wiki/Barrow_Neurological_Institute", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and the deployer's press release. 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for an early 85% thread retraction, and the PRIME trial had enrolled more than 20 participants across four countries.", "quote": "As of early 2026, the trial had enrolled more than 20 participants across sites in the US, UK, Canada, and United Arab Emirates.", "url": "https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0263" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Noland Arbaugh, paralyzed after a diving accident, received the Neuralink N1 implant at Barrow Neurological Institute, Phoenix, in January 2024 (ABC15, 2 May 2024). He demonstrated online chess and cursor movement by thought. ABC News (17 May 2024) reported that threads retracted from his brain and removal was considered. It quoted him: “I can control a computer just like anyone else can”. Neuralink said it modified the recording algorithm and the translation of signals into cursor movements. Tech Times (28 May 2026) reported roughly 85% of threads retracted about a month after surgery and recovery through software refinement. It gave about 10 hours of daily use for chess, coursework, scheduling and communication at 28 months. Barrow (29 April 2026) reported the second participant, Alex Conley (C4-C5 injury, CONVOY study), controlling a robotic arm to operate light switches and doors. The Debrief (7 July 2025) counted 7 users, 6 implanted at Barrow. Nature news (6 August 2024) noted the device “has been adjusted in a bid to prevent glitches”. No peer-reviewed report of participant outcomes was found in Europe PMC. Neuralink's own blog could not be opened. The implant was in January 2024.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Arbaugh reports computer control “just like anyone else can” and about 10 hours of daily use at 28 months. Conley operates a robotic arm for light switches and doors." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Seven users as of July 2025; no population-level effect." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Restore digital autonomy (cursor control, later robotic-arm control) to people with quadriplegia through an implanted brain-computer interface" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Phoenix, Arizona, USA", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Restore digital autonomy (cursor control, later robotic-arm control) to people with quadriplegia through an implanted brain-computer interface" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-05-02", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322; https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Neuralink; https://en.wikipedia.org/wiki/Barrow_Neurological_Institute", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Implanted electrode threads in motor cortex", "Company decoding software translating neural signals into cursor or robotic-arm commands", "Software recalibration after thread retraction" ], "must_hold": [ "Electrode threads remain sufficiently in place or software compensates", "Daily use continues to be reported by the user", "Peer-reviewed outcome reporting (absent so far)" ], "echoes": [ { "date": "2026-04-29", "setting": "Alex Conley, second participant, robotic-arm control (CONVOY study) at Barrow", "model_version": "N1", "outcome": "recurred", "source": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/" }, { "date": "2025-07-07", "setting": "Seven users reported, six implanted at Barrow", "model_version": "N1", "outcome": "unknown", "source": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Implanted electrode threads in motor cortex", "Company decoding software translating neural signals into cursor or robotic-arm commands", "Software recalibration after thread retraction" ], "must_hold": [ "Electrode threads remain sufficiently in place or software compensates", "Daily use continues to be reported by the user", "Peer-reviewed outcome reporting (absent so far)" ], "echoes": [ { "date": "2026-04-29", "setting": "Alex Conley, second participant, robotic-arm control (CONVOY study) at Barrow", "model_version": "N1", "outcome": "recurred", "source": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/" }, { "date": "2025-07-07", "setting": "Seven users reported, six implanted at Barrow", "model_version": "N1", "outcome": "unknown", "source": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322; https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Neuralink; https://en.wikipedia.org/wiki/Barrow_Neurological_Institute", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Health; assistive technology", "segment": "People with quadriplegia (spinal cord injury, ALS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ABC15 Arizona, 2 May 2024", "title": "Elon Musk's Neuralink begins clinical trials in Phoenix", "url": "https://www.abc15.com/news/business/elon-musks-neuralink-begins-clinical-trials-in-phoenix", "date": "2024-05-02", "written_by": "independent", "quote": "a significant milestone that could potentially restore autonomy to millions of adults with unmet medical needs." }, { "kind": "news report", "citation": "ABC News / Good Morning America, 17 May 2024", "title": "Neuralink's first brain implant patient feared device would have to be removed", "url": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322", "date": "2024-05-17", "written_by": "independent", "quote": "I can control a computer just like anyone else can, which is not something I was able to do beforehand." }, { "kind": "press release", "citation": "Barrow Neurological Institute patient story, 29 Apr 2026", "title": "Barrow Patient Begins to Reclaim Independence With Neuralink Robotic Arm After Spinal Cord Injury", "url": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/", "date": "2026-04-29", "written_by": "deployer", "quote": "Most of us take for granted our ability to interact with the physical world. With this technology, we're giving that back to the patients." }, { "kind": "news report", "citation": "Tech Times, 28 May 2026", "title": "Neuralink BCI After 28 Months: Arbaugh Tells Robotics Summit What Published Research Cannot", "url": "https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "date": "2026-05-28", "written_by": "independent", "quote": "It sucked. It was really, really hard." }, { "kind": "news report", "citation": "The Debrief, 7 Jul 2025", "title": "Neuralink Hits 7 Users as Global Brain Implant Count Remains Under 100", "url": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/", "date": "2025-07-07", "written_by": "independent", "quote": "Today, Neuralink released a special update that recognized PRIME Study patients' contributions to research" }, { "kind": "news report", "citation": "Naddaf M, Drew L. Nature 632:481-482 (2024)", "title": "Second brain implant by Elon Musk's Neuralink: will it fare better than the first?", "url": "https://www.nature.com/articles/d41586-024-02368-8", "date": "2024-08-06", "written_by": "independent", "quote": "Device allowing the user to control a computer cursor using their thoughts has been adjusted in a bid to prevent glitches with the first implant." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0263-source-0001", "AIBD-0263-source-0002", "AIBD-0263-source-0003", "AIBD-0263-source-0004", "AIBD-0263-source-0005", "AIBD-0263-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ABC15 Arizona, 2 May 2024", "title": "Elon Musk's Neuralink begins clinical trials in Phoenix", "url": "https://www.abc15.com/news/business/elon-musks-neuralink-begins-clinical-trials-in-phoenix", "date": "2024-05-02", "written_by": "independent", "quote": "a significant milestone that could potentially restore autonomy to millions of adults with unmet medical needs." }, { "kind": "news report", "citation": "ABC News / Good Morning America, 17 May 2024", "title": "Neuralink's first brain implant patient feared device would have to be removed", "url": "https://abcnews.com/GMA/Wellness/neuralinks-brain-implant-patient-feared-device-removed/story?id=110325322", "date": "2024-05-17", "written_by": "independent", "quote": "I can control a computer just like anyone else can, which is not something I was able to do beforehand." }, { "kind": "press release", "citation": "Barrow Neurological Institute patient story, 29 Apr 2026", "title": "Barrow Patient Begins to Reclaim Independence With Neuralink Robotic Arm After Spinal Cord Injury", "url": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/", "date": "2026-04-29", "written_by": "deployer", "quote": "Most of us take for granted our ability to interact with the physical world. With this technology, we're giving that back to the patients." }, { "kind": "news report", "citation": "Tech Times, 28 May 2026", "title": "Neuralink BCI After 28 Months: Arbaugh Tells Robotics Summit What Published Research Cannot", "url": "https://www.techtimes.com/articles/317356/20260528/neuralink-bci-after-28-months-arbaugh-tells-robotics-summit-what-published-research-cannot.htm", "date": "2026-05-28", "written_by": "independent", "quote": "It sucked. It was really, really hard." }, { "kind": "news report", "citation": "The Debrief, 7 Jul 2025", "title": "Neuralink Hits 7 Users as Global Brain Implant Count Remains Under 100", "url": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/", "date": "2025-07-07", "written_by": "independent", "quote": "Today, Neuralink released a special update that recognized PRIME Study patients' contributions to research" }, { "kind": "news report", "citation": "Naddaf M, Drew L. Nature 632:481-482 (2024)", "title": "Second brain implant by Elon Musk's Neuralink: will it fare better than the first?", "url": "https://www.nature.com/articles/d41586-024-02368-8", "date": "2024-08-06", "written_by": "independent", "quote": "Device allowing the user to control a computer cursor using their thoughts has been adjusted in a bid to prevent glitches with the first implant." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "First PRIME-study participant, implanted at Barrow in January 2024, controls a computer by thought; threads retracted after a month, software fixes restored use; a second user drives a robot arm.", "account": "Noland Arbaugh, paralyzed after a diving accident, received the Neuralink N1 implant at Barrow Neurological Institute, Phoenix, in January 2024 (ABC15, 2 May 2024). He demonstrated online chess and cursor movement by thought. ABC News (17 May 2024) reported that threads retracted from his brain and removal was considered. It quoted him: “I can control a computer just like anyone else can”. Neuralink said it modified the recording algorithm and the translation of signals into cursor movements. Tech Times (28 May 2026) reported roughly 85% of threads retracted about a month after surgery and recovery through software refinement. It gave about 10 hours of daily use for chess, coursework, scheduling and communication at 28 months. Barrow (29 April 2026) reported the second participant, Alex Conley (C4-C5 injury, CONVOY study), controlling a robotic arm to operate light switches and doors. The Debrief (7 July 2025) counted 7 users, 6 implanted at Barrow. Nature news (6 August 2024) noted the device “has been adjusted in a bid to prevent glitches”. No peer-reviewed report of participant outcomes was found in Europe PMC. Neuralink's own blog could not be opened. The implant was in January 2024." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The decoder translated neural signals into cursor and robotic-arm movements." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used the N1 implant." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "N1" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Neuralink N1 implant with cursor-decoding software (PRIME study; CONVOY study for the robotic arm)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Neuralink" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Neuralink N1 lets Noland Arbaugh control a cursor and play chess by thought; use continues at 28 months", "headline": "Neuralink N1 lets Noland Arbaugh control a cursor by thought" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d701b505fcf2a7e40abec2baad8a8c81616e8858ce3393b5fa06088622199c9b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Noland Arbaugh, paralyzed after a diving accident, received the Neuralink N1 implant at Barrow Neurological Institute, Phoenix, in January 2024 (ABC15, 2 May 2024). He demonstrated online chess and cursor movement by thought. ABC News (17 May 2024) reported that threads retracted from his brain and removal was considered. It quoted him: “I can control a computer just like anyone else can”. Neuralink said it modified the recording algorithm and the translation of signals into cursor movements. Tech Times (28 May 2026) reported roughly 85% of threads retracted about a month after surgery and recovery through software refinement. It gave about 10 hours of daily use for chess, coursework, scheduling and communication at 28 months. Barrow (29 April 2026) reported the second participant, Alex Conley (C4-C5 injury, CONVOY study), controlling a robotic arm to operate light switches and doors. The Debrief (7 July 2025) counted 7 users, 6 implanted at Barrow. Nature news (6 August 2024) noted the device “has been adjusted in a bid to prevent glitches”. No peer-reviewed report of participant outcomes was found in Europe PMC. Neuralink's own blog could not be opened. The implant was in January 2024.", "replication": { "produced_by": [ "Implanted electrode threads in motor cortex", "Company decoding software translating neural signals into cursor or robotic-arm commands", "Software recalibration after thread retraction" ], "must_hold": [ "Electrode threads remain sufficiently in place or software compensates", "Daily use continues to be reported by the user", "Peer-reviewed outcome reporting (absent so far)" ], "echoes": [ { "date": "2026-04-29", "setting": "Alex Conley, second participant, robotic-arm control (CONVOY study) at Barrow", "model_version": "N1", "outcome": "recurred", "source": "https://www.barrowneuro.org/about/news-and-articles/patient-stories/barrow-patient-begins-to-reclaim-independence-with-neuralink-robotic-arm-after-spinal-cord-injury/" }, { "date": "2025-07-07", "setting": "Seven users reported, six implanted at Barrow", "model_version": "N1", "outcome": "unknown", "source": "https://thedebrief.org/neuralink-hits-7-users-as-global-brain-implant-count-remains-under-100/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0232", "title": "Cheshire Police facial recognition matches CCTV to Keenan Hughes; county lines dealers jailed for over five years", "summary": "Cheshire Constabulary's facial recognition matched CCTV of an unknown Northwich dealer to Keenan Hughes; he and Vincent Potter were stopped on 17 May 2024 with crack cocaine and jailed on 1 July 2024.", "date_observed": "2024-05-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Cheshire Constabulary's release states that in April 2024 officers in Northwich learned of a phone number used by the “Kyle” county lines gang. They recovered closed-circuit television (CCTV) of an unknown man suspected of using it. The force facial recognition system matched the image to Keenan Hughes of Connah's Quay. On Friday 17 May officers on patrol spotted Hughes on Winnington Street with Vincent Potter. A search found 99 wraps of crack cocaine worth about £990 and a hunting-style knife on Hughes. Potter had two phones, a lock knife and £960. Both pleaded guilty, and on 1 July 2024 Chester Crown Court jailed Hughes (18) for 28 months and Potter (19) for 34 months. PC Dean Butterworth said Hughes was not known locally and the technology quickly identified him as a suspect. The OECD AI Incidents Monitor records the case, listing a harm type of human or fundamental rights.", "category": "benefit created", "unexpected": false, "purpose": "Identify unknown suspects by comparing CCTV images against police custody image databases.", "system": "Cheshire Constabulary facial recognition system (retrospective)", "model_version": null, "developer": "Not named in the sources", "deployer": "Cheshire Constabulary, Northwich Proactive Policing Unit", "location": "Northwich, United Kingdom", "domain": "Policing / drug supply", "segment": "Government", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "Two county lines dealers convicted and 99 wraps of crack cocaine and two knives taken off the street, per the force and the court outcome." } ], "ai_role": { "status": "assessed", "statement": "The retrospective face match supplied the suspect's identity from CCTV. The arrest arose from a later patrol sighting, and the conviction rested on seized drugs and phone messages. Sources are the deploying force's release and a local newspaper quoting the named officer. The vendor, match score and any false-match safeguards are not stated." }, "evidence": [ { "kind": "press release", "citation": "Cheshire Constabulary, news release, 2 Jul 2024", "title": "Facial recognition technology helps to identify Northwich drug dealers", "url": "https://www.cheshire.police.uk/news/cheshire/news/articles/2024/6/facial-recognition-technology-helps-to-identify-northwich-drug-dealers/", "date": "2024-07-02", "written_by": "deployer", "quote": "The image was submitted to the force facial recognition system and came through as a match to a man called Keenan Hughes from Connah’s Quay." }, { "kind": "news report", "citation": "Rob Goulding, The Leader (Leader Live), 2 Jul 2024", "title": "County Lines drug dealers operating in Northwich jailed", "url": "https://www.leaderlive.co.uk/news/24424400.county-lines-drug-dealers-operating-northwich-jailed/", "date": "2024-07-02", "written_by": "independent", "quote": "Hughes was not known in the Northwich area, but thanks to the CCTV footage and facial recognition technology, we were quickly able to identify him as a suspect." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2024-07-02-ee42", "title": "Police use facial recognition AI to catch county lines drug dealers", "url": "https://oecd.ai/en/incidents/2024-07-02-ee42", "date": "2024-07-02", "written_by": "independent", "quote": "Its use directly led to the arrest and conviction of individuals involved in drug dealing, which is a harm to communities." }, { "kind": "news report", "citation": "Deeside.com (2 Jul 2024). 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Facial recognition technology helps to identify Deeside drug dealer (reproduces Cheshire Constabulary's release and PC Dean Butterworth's quotes).", "title": "Facial recognition technology helps to identify Deeside drug dealer", "url": "https://www.deeside.com/facial-recognition-technology-helps-to-identify-deeside-drug-dealer", "date": "2024-07-02", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0232-source-0001", "AIBD-0232-source-0002", "AIBD-0232-source-0003", "AIBD-0232-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Cheshire Constabulary, news release, 2 Jul 2024", "title": "Facial recognition technology helps to identify Northwich drug dealers", "url": "https://www.cheshire.police.uk/news/cheshire/news/articles/2024/6/facial-recognition-technology-helps-to-identify-northwich-drug-dealers/", "date": "2024-07-02", "written_by": "deployer", "quote": "The image was submitted to the force facial recognition system and came through as a match to a man called Keenan Hughes from Connah’s Quay." }, { "kind": "news report", "citation": "Rob Goulding, The Leader (Leader Live), 2 Jul 2024", "title": "County Lines drug dealers operating in Northwich jailed", "url": "https://www.leaderlive.co.uk/news/24424400.county-lines-drug-dealers-operating-northwich-jailed/", "date": "2024-07-02", "written_by": "independent", "quote": "Hughes was not known in the Northwich area, but thanks to the CCTV footage and facial recognition technology, we were quickly able to identify him as a suspect." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2024-07-02-ee42", "title": "Police use facial recognition AI to catch county lines drug dealers", "url": "https://oecd.ai/en/incidents/2024-07-02-ee42", "date": "2024-07-02", "written_by": "independent", "quote": "Its use directly led to the arrest and conviction of individuals involved in drug dealing, which is a harm to communities." }, { "kind": "news report", "citation": "Deeside.com (2 Jul 2024). Facial recognition technology helps to identify Deeside drug dealer (reproduces Cheshire Constabulary's release and PC Dean Butterworth's quotes).", "title": "Facial recognition technology helps to identify Deeside drug dealer", "url": "https://www.deeside.com/facial-recognition-technology-helps-to-identify-deeside-drug-dealer", "date": "2024-07-02", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Cheshire Constabulary's facial recognition matched CCTV of an unknown Northwich dealer to Keenan Hughes; he and Vincent Potter were stopped on 17 May 2024 with crack cocaine and jailed on 1 July 2024.", "account": "Cheshire Constabulary's release states that in April 2024 officers in Northwich learned of a phone number used by the “Kyle” county lines gang. They recovered closed-circuit television (CCTV) of an unknown man suspected of using it. The force facial recognition system matched the image to Keenan Hughes of Connah's Quay. On Friday 17 May officers on patrol spotted Hughes on Winnington Street with Vincent Potter. A search found 99 wraps of crack cocaine worth about £990 and a hunting-style knife on Hughes. Potter had two phones, a lock knife and £960. Both pleaded guilty, and on 1 July 2024 Chester Crown Court jailed Hughes (18) for 28 months and Potter (19) for 34 months. PC Dean Butterworth said Hughes was not known locally and the technology quickly identified him as a suspect. The OECD AI Incidents Monitor records the case, listing a harm type of human or fundamental rights." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Cheshire Constabulary facial recognition system (retrospective)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Cheshire Police facial recognition matches CCTV to Keenan Hughes; county lines dealers jailed for over five years", "headline": "Cheshire facial recognition match jails county lines dealers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0f073ec2418ca5c35fafb7ebb5811c382fb528a6b1785b9b795554ab9d1c0f50" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Cheshire Constabulary's release states that in April 2024 officers in Northwich learned of a phone number used by the “Kyle” county lines gang. They recovered closed-circuit television (CCTV) of an unknown man suspected of using it. The force facial recognition system matched the image to Keenan Hughes of Connah's Quay. On Friday 17 May officers on patrol spotted Hughes on Winnington Street with Vincent Potter. A search found 99 wraps of crack cocaine worth about £990 and a hunting-style knife on Hughes. Potter had two phones, a lock knife and £960. Both pleaded guilty, and on 1 July 2024 Chester Crown Court jailed Hughes (18) for 28 months and Potter (19) for 34 months. PC Dean Butterworth said Hughes was not known locally and the technology quickly identified him as a suspect. The OECD AI Incidents Monitor records the case, listing a harm type of human or fundamental rights.", "replication": { "produced_by": [ "A usable CCTV still of an unknown suspect", "A custody-image database containing the suspect", "Officers able to corroborate the match through patrol and search" ], "must_hold": [ "The suspect must have a prior custody image", "Lawful retrospective use of facial recognition", "Corroborating evidence beyond the match" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0371", "title": "Kota police tie up with Meta to route suicide and self-harm flags from Facebook and Instagram to Abhay Command Centre; within a week police report a possible suicide by a Jhunjhunu student prevented", "summary": "Kota City SP Amrita Duhan said Meta's red-flag tags for suicidal posts go to a round-the-clock police team; within a week, police prevented a possible suicide by a student from Jhunjhunu (PTI).", "date_observed": "2024-05-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "PTI reported from Kota on 28 May 2024 that city police under Superintendent Amrita Duhan had tied up with Meta. It aims to identify students exhibiting suicidal tendencies on Facebook and Instagram. When a student posts suicide or self-harm content, a red-flag tag appears on Meta's system and account information is shared with Kota police. For students outside Kota it goes to Abhay Command Centre or the district control room. There a dedicated team works round the clock in eight-hour shifts. Within a week of the launch, police said they had prevented a possible suicide by a student from Jhunjhunu district. No red-flag tags had yet been reported in the city. PTI counted nine coaching-student suicides in 2024 to date and 26 in 2023. Duhan planned to extend the arrangement to Jaipur (PTI via LatestLY). Meta's newsroom describes machine-learning detection with human review before authorities are contacted (Card, 2018). The intervention date is not given.", "category": "protective response", "unexpected": false, "purpose": "Meta's pipeline is built to find posts indicating suicide or self-injury risk and route them to trained reviewers. In imminent cases it contacts local authorities (Meta Newsroom). The Kota arrangement routes those flags to police to intervene. This case is that purpose.", "system": "Meta suicide and self-injury detection on Facebook and Instagram, with red-flag tags shared with Kota police and Abhay Command Centre", "model_version": null, "developer": "Meta Platforms", "deployer": "Kota City Police (Rajasthan Police), Abhay Command Centre", "location": "Kota, India", "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police", "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health.", "registry_ids": { "oecd_aim": "2024-05-28-2dfd" }, "ratings": [ { "group": "personal", "depth": null, "reason": "PTI reports only that police “prevented a possible suicide by a student hailing from the Jhunjhunu district” within a week of the launch. The sources give no account of what the student posted, their condition when reached or what officers did. So the outcome is not established." } ], "ai_role": { "status": "assessed", "statement": "PTI's report says the chain starts with a red-flag tag on Meta's system when a student posts suicide or self-harm content. Account information is then shared with police. It does not say whether Meta's classifier or a user report raised the flag in the Jhunjhunu case, nor what happened on arrival. Meta's own description (2018, updated 2021) says machine-learning detection is followed by human review before authorities are contacted. The intervention itself was police work. PTI also notes that no red-flag tags had been reported in Kota city since the launch." }, "evidence": [ { "kind": "news report", "citation": "PTI (2024). Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students. LatestLY, 28 May 2024.", "title": "India News | Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students", "url": "https://www.latestly.com/agency-news/india-news-kota-police-ropes-in-meta-to-prevent-suicides-among-coaching-students-5996637.html", "date": "2024-05-28", "written_by": "independent", "quote": "the police have prevented a possible suicide by a student hailing from the Jhunjhunu district" }, { "kind": "news report", "citation": "PTI (2024). Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students. LatestLY, 28 May 2024 (second quotation).", "title": "India News | Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students", "url": "https://www.latestly.com/agency-news/india-news-kota-police-ropes-in-meta-to-prevent-suicides-among-coaching-students-5996637.html", "date": "2024-05-28", "written_by": "independent", "quote": "A dedicated team, working round the clock on eight-hour shifts, has been deputed at Abhay Command Centre" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom, 10 September 2018 (updated 29 September 2021).", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "Since these efforts began last year, we've worked with first responders on over 1,000 wellness checks based on reports we've received from our proactive detection efforts." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). Kota Police and Meta Use AI Monitoring to Prevent Student Suicides. OECD.AI, 28 May 2024.", "title": "Kota Police and Meta Use AI Monitoring to Prevent Student Suicides", "url": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "date": "2024-05-28", "written_by": "independent", "quote": "Within a week, officers intervened to avert a suicide attempt from a student in Jhunjhunu." } ], "replication": { "produced_by": [ "Meta's detection-and-review pipeline flagging suicide or self-harm posts by students on Facebook and Instagram", "A standing arrangement under which Meta shares account information with Kota police. For students outside Kota it goes to Abhay Command Centre or a district control room", "A police team monitoring the flags round the clock in eight-hour shifts" ], "must_hold": [ "The student must post on Facebook or Instagram in a way the pipeline recognizes", "Account details must resolve to a reachable location in time", "Police must be able to reach the student quickly" ], "echoes": [] }, "paired_incident": null, "headline": "Kota police act on a Meta self-harm flag within a week of tie-up", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Rajasthan_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0371", "catalog_version": "1.0.0", "source_fingerprint": "fde9db963ea3a4d8e85db3224fe3d54c6602cd7c4f686e22a5a6be98d4698e74", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0371-source-0001", "AIBD-0371-source-0002", "AIBD-0371-source-0003", "AIBD-0371-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Meta Platforms", "deployer": "Kota City Police (Rajasthan Police), Abhay Command Centre" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "PTI's report says the chain starts with a red-flag tag on Meta's system when a student posts suicide or self-harm content. Account information is then shared with police. It does not say whether Meta's classifier or a user report raised the flag in the Jhunjhunu case, nor what happened on arrival. Meta's own description (2018, updated 2021) says machine-learning detection is followed by human review before authorities are contacted. The intervention itself was police work. PTI also notes that no red-flag tags had been reported in Kota city since the launch." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "PTI's report says the chain starts with a red-flag tag on Meta's system when a student posts suicide or self-harm content. Account information is then shared with police. It does not say whether Meta's classifier or a user report raised the flag in the Jhunjhunu case, nor what happened on arrival. Meta's own description (2018, updated 2021) says machine-learning detection is followed by human review before authorities are contacted. The intervention itself was police work. 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"account": "PTI reported from Kota on 28 May 2024 that city police under Superintendent Amrita Duhan had tied up with Meta. It aims to identify students exhibiting suicidal tendencies on Facebook and Instagram. When a student posts suicide or self-harm content, a red-flag tag appears on Meta's system and account information is shared with Kota police. For students outside Kota it goes to Abhay Command Centre or the district control room. There a dedicated team works round the clock in eight-hour shifts. Within a week of the launch, police said they had prevented a possible suicide by a student from Jhunjhunu district. No red-flag tags had yet been reported in the city. PTI counted nine coaching-student suicides in 2024 to date and 26 in 2023. Duhan planned to extend the arrangement to Jaipur (PTI via LatestLY). Meta's newsroom describes machine-learning detection with human review before authorities are contacted (Card, 2018). 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In imminent cases it contacts local authorities (Meta Newsroom). The Kota arrangement routes those flags to police to intervene. This case is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-05-28", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Rajasthan_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Meta's detection-and-review pipeline flagging suicide or self-harm posts by students on Facebook and Instagram", "A standing arrangement under which Meta shares account information with Kota police. For students outside Kota it goes to Abhay Command Centre or a district control room", "A police team monitoring the flags round the clock in eight-hour shifts" ], "must_hold": [ "The student must post on Facebook or Instagram in a way the pipeline recognizes", "Account details must resolve to a reachable location in time", "Police must be able to reach the student quickly" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Rajasthan_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "PTI (2024). Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students. LatestLY, 28 May 2024.", "title": "India News | Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students", "url": "https://www.latestly.com/agency-news/india-news-kota-police-ropes-in-meta-to-prevent-suicides-among-coaching-students-5996637.html", "date": "2024-05-28", "written_by": "independent", "quote": "the police have prevented a possible suicide by a student hailing from the Jhunjhunu district" }, { "kind": "news report", "citation": "PTI (2024). Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students. 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OECD.AI, 28 May 2024.", "title": "Kota Police and Meta Use AI Monitoring to Prevent Student Suicides", "url": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "date": "2024-05-28", "written_by": "independent", "quote": "Within a week, officers intervened to avert a suicide attempt from a student in Jhunjhunu." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0371-source-0001", "AIBD-0371-source-0002", "AIBD-0371-source-0003", "AIBD-0371-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "PTI (2024). 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LatestLY, 28 May 2024 (second quotation).", "title": "India News | Kota Police Ropes in Meta to Prevent Suicides Among Coaching Students", "url": "https://www.latestly.com/agency-news/india-news-kota-police-ropes-in-meta-to-prevent-suicides-among-coaching-students-5996637.html", "date": "2024-05-28", "written_by": "independent", "quote": "A dedicated team, working round the clock on eight-hour shifts, has been deputed at Abhay Command Centre" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom, 10 September 2018 (updated 29 September 2021).", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "Since these efforts began last year, we've worked with first responders on over 1,000 wellness checks based on reports we've received from our proactive detection efforts." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). Kota Police and Meta Use AI Monitoring to Prevent Student Suicides. OECD.AI, 28 May 2024.", "title": "Kota Police and Meta Use AI Monitoring to Prevent Student Suicides", "url": "https://oecd.ai/en/incidents/2024-05-28-2dfd", "date": "2024-05-28", "written_by": "independent", "quote": "Within a week, officers intervened to avert a suicide attempt from a student in Jhunjhunu." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Kota City SP Amrita Duhan said Meta's red-flag tags for suicidal posts go to a round-the-clock police team; within a week, police prevented a possible suicide by a student from Jhunjhunu (PTI).", "account": "PTI reported from Kota on 28 May 2024 that city police under Superintendent Amrita Duhan had tied up with Meta. It aims to identify students exhibiting suicidal tendencies on Facebook and Instagram. When a student posts suicide or self-harm content, a red-flag tag appears on Meta's system and account information is shared with Kota police. For students outside Kota it goes to Abhay Command Centre or the district control room. There a dedicated team works round the clock in eight-hour shifts. Within a week of the launch, police said they had prevented a possible suicide by a student from Jhunjhunu district. No red-flag tags had yet been reported in the city. PTI counted nine coaching-student suicides in 2024 to date and 26 in 2023. Duhan planned to extend the arrangement to Jaipur (PTI via LatestLY). Meta's newsroom describes machine-learning detection with human review before authorities are contacted (Card, 2018). The intervention date is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Meta suicide and self-injury detection on Facebook and Instagram, with red-flag tags shared with Kota police and Abhay Command Centre" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meta Platforms" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kota police tie up with Meta to route suicide and self-harm flags from Facebook and Instagram to Abhay Command Centre; within a week police report a possible suicide by a Jhunjhunu student prevented", "headline": "Kota police act on a Meta self-harm flag within a week of tie-up" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fde9db963ea3a4d8e85db3224fe3d54c6602cd7c4f686e22a5a6be98d4698e74" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "PTI reported from Kota on 28 May 2024 that city police under Superintendent Amrita Duhan had tied up with Meta. It aims to identify students exhibiting suicidal tendencies on Facebook and Instagram. When a student posts suicide or self-harm content, a red-flag tag appears on Meta's system and account information is shared with Kota police. For students outside Kota it goes to Abhay Command Centre or the district control room. There a dedicated team works round the clock in eight-hour shifts. Within a week of the launch, police said they had prevented a possible suicide by a student from Jhunjhunu district. No red-flag tags had yet been reported in the city. PTI counted nine coaching-student suicides in 2024 to date and 26 in 2023. Duhan planned to extend the arrangement to Jaipur (PTI via LatestLY). Meta's newsroom describes machine-learning detection with human review before authorities are contacted (Card, 2018). The intervention date is not given.", "replication": { "produced_by": [ "Meta's detection-and-review pipeline flagging suicide or self-harm posts by students on Facebook and Instagram", "A standing arrangement under which Meta shares account information with Kota police. For students outside Kota it goes to Abhay Command Centre or a district control room", "A police team monitoring the flags round the clock in eight-hour shifts" ], "must_hold": [ "The student must post on Facebook or Instagram in a way the pipeline recognizes", "Account details must resolve to a reachable location in time", "Police must be able to reach the student quickly" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0213", "title": "World Bank RCT in Benin City: six weeks of Microsoft Copilot (GPT-4) English tutoring in nine public schools raises assessment scores 0.31 SD", "summary": "World Bank Policy Research Working Paper 11125: teacher-guided after-school Copilot (GPT-4) sessions, June-July 2024, Benin City; 0.31 SD overall, 0.23 SD in English; 657 treated, 671 control.", "date_observed": "2024-06-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "World Bank Policy Research Working Paper 11125 (May 2025) is by De Simone, Tiberti, Barron Rodriguez, Manolio, Mosuro and Dikoru. It evaluates a six-week after-school program run in June and July 2024 in nine public schools in Benin City, Nigeria, chosen for their computer labs. First-year senior secondary students, typically 15 years old, who expressed interest were randomized: 657 to treatment and 671 to control. Of these, 422 and 337 finished the final assessment. Treated students attended up to two 90-minute sessions a week (twelve in total). They used Microsoft Copilot, powered by GPT-4 at the time, as a virtual English tutor in curriculum-aligned activities guided by teachers. The paper reports a 0.31 standard deviation improvement on an assessment covering English, AI knowledge and digital skills, and 0.23 SD on English. It equates the gains to 1.5 to 2 years of business-as-usual schooling. Effects were larger for female students and those with higher initial performance. The World Bank blog of 9 January 2025 describes the gain as about 0.3 SD. The paper gives months, not days.", "category": "general benefit", "unexpected": false, "purpose": "Copilot was used as a virtual tutor to improve English learning outcomes. The measured gain is that purpose.", "system": "Microsoft Copilot (GPT-4) used as a virtual English tutor in teacher-guided after-school computer-lab sessions", "model_version": "GPT-4 (Microsoft Copilot, per the working paper)", "developer": "Microsoft (Copilot), on OpenAI's GPT-4", "deployer": "Nine public secondary schools in Benin City with the World Bank study team; sessions guided by teachers", "location": "Benin City, Nigeria", "domain": "Education", "segment": "Senior secondary English (after-school program)", "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Treated students scored 0.31 SD higher overall and 0.23 SD higher in English after six weeks (working paper abstract)." }, { "group": "organizational", "depth": null, "reason": "The schools and the study team gained a cost-effectiveness estimate of 1.5 to 2 years of business-as-usual schooling (working paper abstract)." } ], "ai_role": { "status": "assessed", "statement": "Copilot tutored in teacher-guided sessions, so the estimate covers the whole after-school program (twelve 90-minute sessions). The large language model (LLM) share is not isolated from teacher guidance and extra teaching time." }, "evidence": [ { "kind": "report", "citation": "De Simone M, Tiberti F, Barron Rodriguez M, Manolio F, Mosuro W, Dikoru EJ (2025). From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria. Policy Research Working Paper 11125, World Bank (OKR handle page).", "title": "From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria", "url": "https://hdl.handle.net/10986/43212", "date": "2025-05-20", "written_by": "deployer", "quote": "The program was implemented over a six-week period between June and July 2024, targeting first-year senior secondary school students, who are typically 15 years old." }, { "kind": "report", "citation": "ERIC record ED676624 for Policy Research Working Paper 11125 (abstract).", "title": "From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria. Policy Research Working Paper 11125", "url": "https://eric.ed.gov/?id=ED676624", "date": null, "written_by": "deployer", "quote": "The intervention demonstrated a significant improvement of 0.31 standard deviation on an assessment that included English topics aligned with the Nigerian curriculum, knowledge of artificial intelligence and digital skills." }, { "kind": "press release", "citation": "De Simone ME, Tiberti F, Mosuro W, Manolio F, Barron M, Dikoru E (9 Jan 2025). From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time. World Bank Blogs.", "title": "From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time", "url": "https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-Transforming-learning-in-Nigeria", "date": "2025-01-09", "written_by": "deployer", "quote": "Students who were randomly assigned to participate significantly outperformed peers in all areas" }, { "kind": "press release", "citation": "World Bank Education blog (2024). From chalkboards to chatbots in Nigeria: 7 lessons to pioneer generative AI for education. 18 September 2024.", "title": "From chalkboards to chatbots in Nigeria: 7 lessons to pioneer generative AI for education", "url": "https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-in-Nigeria", "date": "2024-09-18", "written_by": "deployer", "quote": "Over June and July 2024,800 first-year senior secondary students attended after-school English classes in computer labs twice a week." }, { "kind": "report", "citation": "De Simone M et al. (2025). Working Paper 11125 (sample and attrition).", "title": "From Chalkboards to Chatbots: Evaluating the Impact of Generative AI on Learning Outcomes in Nigeria", "url": "https://openknowledge.worldbank.org/bitstreams/8fcccf10-83c9-4295-b01c-5a68aac83b06/download", "date": "2025-05-20", "written_by": "deployer", "quote": "However, only 422 students in the treatment group and 337 in the control group completed the final assessment" } ], "replication": { "produced_by": [ "A freely available LLM (Copilot on GPT-4) requiring only student registration", "Curriculum-aligned prompts and activities guided by teachers in school computer labs", "Student-level randomization among volunteers in nine schools with computer labs" ], "must_hold": [ "Working computer labs and internet access", "Teacher guidance in every session", "Attendance (the paper reports gains rising with days attended)" ], "echoes": [] }, "paired_incident": null, "headline": "Microsoft Copilot tutoring lifts Benin City scores by 0.31 SD", "metric": "0.31 SD overall, 0.23 SD in English", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No report of a second phase or scale-up of the Benin City program after the May 2025 working paper was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Nigeria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged a second write-up of the same trial: added the 2024 World Bank blog on the pilot and the working paper's attrition figures.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://blogs.worldbank.org/en/education/From-chalkboards-to-chatbots-in-Nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: three reports from the deployer and two press releases from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0213", "catalog_version": "1.0.0", "source_fingerprint": "e8ff6a3813820999741f242ae4067af74e53b8030e29896478e325fda44addbe", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0213-source-0001", "AIBD-0213-source-0002", "AIBD-0213-source-0003", "AIBD-0213-source-0004", "AIBD-0213-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Microsoft (Copilot), on OpenAI's GPT-4", "deployer": "Nine public secondary schools in Benin City with the World Bank study team; sessions guided by teachers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Copilot tutored in teacher-guided sessions, so the estimate covers the whole after-school program (twelve 90-minute sessions). The large language model (LLM) share is not isolated from teacher guidance and extra teaching time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Copilot tutored in teacher-guided sessions, so the estimate covers the whole after-school program (twelve 90-minute sessions). The large language model (LLM) share is not isolated from teacher guidance and extra teaching time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: three reports from the deployer and two press releases from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Treated students scored 0.31 SD higher overall and 0.23 SD higher in English after six weeks (working paper abstract)." }, { "group": "organizational", "reason": "The schools and the study team gained a cost-effectiveness estimate of 1.5 to 2 years of business-as-usual schooling (working paper abstract)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Treated students scored 0.31 SD higher overall and 0.23 SD higher in English after six weeks (working paper abstract)." }, { "group": "organizational", "reason": "The schools and the study team gained a cost-effectiveness estimate of 1.5 to 2 years of business-as-usual schooling (working paper abstract)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", 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It came from a lightning-caused fire in Douglas County, Colorado. According to Renewable Energy World (18 July 2024), emergency services dispatched two helicopters within 30 minutes of the identification, when the fire was 0.25 acres. The helicopters dropped 17,765 gallons of water over six hours and the fire was limited to three acres. Denver7 (17 July 2024) reported that the fire was contained within a day and was first spotted by the AI-equipped cameras. CORE's wildfire mitigation manager Jordan Ambrogi said alerts typically arrive 10 to 12 minutes after smoke is detected. The utilities, however, said the cameras identified the fire “simultaneously” with the U.S. Forest Service. So the cameras' independent contribution to containment rests on the operators' own statements (CORE interim CEO Pam Feuerstein). The OECD AI Incidents Monitor carries a separate positively framed record of Xcel's November 2023 Pano AI deployment.", "category": "protective response", "unexpected": false, "purpose": "Pano AI cameras rotate 360 degrees on mountaintop towers and use AI to detect smoke plumes. They alert utilities and fire agencies with a triangulated location. Detecting this fire early was the intended use.", "system": "Pano AI wildfire detection cameras (Pano Rapid Detect)", "model_version": null, "developer": "Pano AI", "deployer": "Xcel Energy and CORE Electric Cooperative", "location": "Douglas County, Colorado, United States", "domain": "Energy and infrastructure", "segment": "Electric utility wildfire mitigation", "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "The fire was held to three acres after helicopters were dispatched within 30 minutes. CORE's CEO called the detection and location “crucial”. Simultaneous Forest Service identification limits what can be attributed to the cameras." }, { "group": "organizational", "depth": 2, "reason": "CORE Electric and Xcel Energy obtained a fast, located alert supporting their wildfire mitigation strategy. Denver7 quotes CORE's Jordan Ambrogi saying alerts typically beat 911 calls." }, { "group": "personal", "depth": null, "reason": "No individual beneficiary is documented in the sources." } ], "ai_role": { "status": "assessed", "statement": "The AI smoke detection produced the alert and location that the utilities and Denver7 describe. The sources are independent news reports quoting operator staff, not an official filing. The operators themselves say the Forest Service identified the fire simultaneously. So the counterfactual contribution of the AI to the three-acre outcome is unverified." }, "evidence": [ { "kind": "news report", "citation": "Colette Bordelon, 'Douglas County wildfire first detected by cameras equipped with AI', Denver7, 17 July 2024", "title": "Douglas County wildfire first detected by cameras equipped with AI", "url": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai", "date": "2024-07-17", "written_by": "independent", "quote": "The Bear Creek Fire in Douglas County, which was contained within a day, was first spotted by cameras equipped with artificial intelligence (AI)." }, { "kind": "news report", "citation": "John Engel, 'AI cameras prevented large wildfire, utilities say', Renewable Energy World / Factor This, 18 July 2024", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "Within 30 minutes of the identification, emergency services dispatched two helicopters to the fire when it was .25 acres." }, { "kind": "news report", "citation": "John Engel, Renewable Energy World, 18 July 2024 (operator attribution)", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "The utilities said their wildfire camera system, provided by Pano AI, identified the wildfire “simultaneously” with the U.S. Forest Service." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2023-11-07-64f3, 'Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado'", "title": "Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado", "url": "https://oecd.ai/en/incidents/2023-11-07-64f3", "date": "2023-11-07", "written_by": "independent", "quote": "Xcel Energy, in partnership with Pano AI, is expanding the use of AI-driven wildfire detection cameras across Colorado." }, { "kind": "news report", "citation": "Wilson, S. (2024). AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire. CBS Colorado, 9 July 2024.", "title": "AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "date": "2024-07-09", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Camera stations with 360-degree views sited on cell towers within roughly 10 miles of the ignition", "Alert routing to both the utility and local fire agencies with a triangulated location", "Lightning-caused ignition in daylight in a remote area, with aerial resources available for dispatch" ], "must_hold": [ "Camera coverage of the ignition point and functioning AI smoke detection", "An agency able to act on the alert within minutes", "Independent confirmation of who detected the fire first, since the utilities report simultaneous Forest Service identification" ], "echoes": [ { "date": "2024-07-09", "setting": "Wellington fire near Breckenridge, Summit County, Colorado; Xcel-funded Pano AI camera", "model_version": null, "outcome": "recurred", "source": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/" }, { "date": "2024-08-29", "setting": "Austin Energy full deployment of 13 Pano AI cameras, Texas; no detection reported", "model_version": null, "outcome": "unknown", "source": "https://austinenergy.com/about/news/news-releases/2024/Austin-Energy-announces-full-deployment-of-AI-driven-Early-Wildfire-Detection-System" } ] }, "paired_incident": null, "headline": "Pano AI cameras spot the Bear Creek Fire; held to three acres", "metric": "helicopters were dispatched within 30 minutes and the fire was held to three acres", "comparator": { "against": "members of the public calling 911", "before": "anyone else calling 911", "after": "within 10 minutes of detecting smoke, 10 to 12 minutes", "basis": "assumed", "quote": "Typically, it's within 10 minutes of detecting smoke, 10 to 12 minutes. Depending on where it is, how remote an area, it'll beat anyone else calling 911.", "url": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai" }, "later": { "status": "persisted", "date": "2024-07-09", "note": "Three weeks later an Xcel-funded Pano AI camera caught the Wellington fire near Breckenridge, which firefighters held to one-eighth of an acre.", "quote": "While that has resulted in a few false alarms in Summit County, this was the first instance where a wildfire was caught early, and kept to only one-eighth of an acre, firefighters said, thanks to the camera's early notice.", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai; https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.pbs.org/newshour/show/how-satellites-and-ai-cameras-are-detecting-wildfires-before-they-get-out-of-control", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xcel_Energy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. 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few false alarms in Summit County, this was the first instance where a wildfire was caught early, and kept to only one-eighth of an acre, firefighters said, thanks to the camera's early notice.", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0161" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, 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AI wildfire-detection cameras on Xcel Energy and CORE Electric Cooperative towers detected smoke. It came from a lightning-caused fire in Douglas County, Colorado. According to Renewable Energy World (18 July 2024), emergency services dispatched two helicopters within 30 minutes of the identification, when the fire was 0.25 acres. The helicopters dropped 17,765 gallons of water over six hours and the fire was limited to three acres. Denver7 (17 July 2024) reported that the fire was contained within a day and was first spotted by the AI-equipped cameras. CORE's wildfire mitigation manager Jordan Ambrogi said alerts typically arrive 10 to 12 minutes after smoke is detected. The utilities, however, said the cameras identified the fire “simultaneously” with the U.S. Forest Service. So the cameras' independent contribution to containment rests on the operators' own statements (CORE interim CEO Pam Feuerstein). 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CORE's CEO called the detection and location “crucial”. Simultaneous Forest Service identification limits what can be attributed to the cameras." }, { "group": "organizational", "depth": 2, "reason": "CORE Electric and Xcel Energy obtained a fast, located alert supporting their wildfire mitigation strategy. Denver7 quotes CORE's Jordan Ambrogi saying alerts typically beat 911 calls." }, { "group": "personal", "reason": "No individual beneficiary is documented in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Pano AI cameras rotate 360 degrees on mountaintop towers and use AI to detect smoke plumes. They alert utilities and fire agencies with a triangulated location. Detecting this fire early was the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Douglas County, Colorado, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Pano AI cameras rotate 360 degrees on mountaintop towers and use AI to detect smoke plumes. They alert utilities and fire agencies with a triangulated location. Detecting this fire early was the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-06-16", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai; https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.pbs.org/newshour/show/how-satellites-and-ai-cameras-are-detecting-wildfires-before-they-get-out-of-control", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xcel_Energy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera stations with 360-degree views sited on cell towers within roughly 10 miles of the ignition", "Alert routing to both the utility and local fire agencies with a triangulated location", "Lightning-caused ignition in daylight in a remote area, with aerial resources available for dispatch" ], "must_hold": [ "Camera coverage of the ignition point and functioning AI smoke detection", "An agency able to act on the alert within minutes", "Independent confirmation of who detected the fire first, since the utilities report simultaneous Forest Service identification" ], "echoes": [ { "date": "2024-07-09", "setting": "Wellington fire near Breckenridge, Summit County, Colorado; 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facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Energy and infrastructure", "segment": "Electric utility wildfire mitigation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Colette Bordelon, 'Douglas County wildfire first detected by cameras equipped with AI', Denver7, 17 July 2024", "title": "Douglas County wildfire first detected by cameras equipped with AI", "url": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai", "date": "2024-07-17", "written_by": "independent", "quote": "The Bear Creek Fire in Douglas County, which was contained within a day, was first spotted by cameras equipped with artificial intelligence (AI)." }, { "kind": "news report", "citation": "John Engel, 'AI cameras prevented large wildfire, utilities say', Renewable Energy World / Factor This, 18 July 2024", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "Within 30 minutes of the identification, emergency services dispatched two helicopters to the fire when it was .25 acres." }, { "kind": "news report", "citation": "John Engel, Renewable Energy World, 18 July 2024 (operator attribution)", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "The utilities said their wildfire camera system, provided by Pano AI, identified the wildfire “simultaneously” with the U.S. Forest Service." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2023-11-07-64f3, 'Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado'", "title": "Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado", "url": "https://oecd.ai/en/incidents/2023-11-07-64f3", "date": "2023-11-07", "written_by": "independent", "quote": "Xcel Energy, in partnership with Pano AI, is expanding the use of AI-driven wildfire detection cameras across Colorado." }, { "kind": "news report", "citation": "Wilson, S. (2024). AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire. CBS Colorado, 9 July 2024.", "title": "AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "date": "2024-07-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0161-source-0001", "AIBD-0161-source-0002", "AIBD-0161-source-0003", "AIBD-0161-source-0004", "AIBD-0161-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Colette Bordelon, 'Douglas County wildfire first detected by cameras equipped with AI', Denver7, 17 July 2024", "title": "Douglas County wildfire first detected by cameras equipped with AI", "url": "https://www.denver7.com/news/wildfire/douglas-county-wildfire-first-detected-by-cameras-equipped-with-ai", "date": "2024-07-17", "written_by": "independent", "quote": "The Bear Creek Fire in Douglas County, which was contained within a day, was first spotted by cameras equipped with artificial intelligence (AI)." }, { "kind": "news report", "citation": "John Engel, 'AI cameras prevented large wildfire, utilities say', Renewable Energy World / Factor This, 18 July 2024", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "Within 30 minutes of the identification, emergency services dispatched two helicopters to the fire when it was .25 acres." }, { "kind": "news report", "citation": "John Engel, Renewable Energy World, 18 July 2024 (operator attribution)", "title": "AI cameras prevented large wildfire, utilities say", "url": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/", "date": "2024-07-18", "written_by": "independent", "quote": "The utilities said their wildfire camera system, provided by Pano AI, identified the wildfire “simultaneously” with the U.S. Forest Service." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, record 2023-11-07-64f3, 'Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado'", "title": "Xcel Energy Deploys AI-Powered Cameras for Early Wildfire Detection in Colorado", "url": "https://oecd.ai/en/incidents/2023-11-07-64f3", "date": "2023-11-07", "written_by": "independent", "quote": "Xcel Energy, in partnership with Pano AI, is expanding the use of AI-driven wildfire detection cameras across Colorado." }, { "kind": "news report", "citation": "Wilson, S. (2024). AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire. CBS Colorado, 9 July 2024.", "title": "AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "date": "2024-07-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Utility-funded Pano AI cameras detected smoke from the 16 June 2024 Bear Creek Fire in Douglas County, Colorado; helicopters were dispatched within 30 minutes and the fire was held to three acres.", "account": "On 16 June 2024 Pano AI wildfire-detection cameras on Xcel Energy and CORE Electric Cooperative towers detected smoke. It came from a lightning-caused fire in Douglas County, Colorado. According to Renewable Energy World (18 July 2024), emergency services dispatched two helicopters within 30 minutes of the identification, when the fire was 0.25 acres. The helicopters dropped 17,765 gallons of water over six hours and the fire was limited to three acres. Denver7 (17 July 2024) reported that the fire was contained within a day and was first spotted by the AI-equipped cameras. CORE's wildfire mitigation manager Jordan Ambrogi said alerts typically arrive 10 to 12 minutes after smoke is detected. The utilities, however, said the cameras identified the fire “simultaneously” with the U.S. Forest Service. So the cameras' independent contribution to containment rests on the operators' own statements (CORE interim CEO Pam Feuerstein). The OECD AI Incidents Monitor carries a separate positively framed record of Xcel's November 2023 Pano AI deployment." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Pano AI wildfire detection cameras (Pano Rapid Detect)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Pano AI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Pano AI cameras on Xcel and CORE Electric towers spot the Bear Creek Fire; helicopters hold it to three acres", "headline": "Pano AI cameras spot the Bear Creek Fire; held to three acres" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2ea991607cecb1e9dc8085e2b93f1a0304a5267232553bd8ca55573b129d9ab6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 16 June 2024 Pano AI wildfire-detection cameras on Xcel Energy and CORE Electric Cooperative towers detected smoke. It came from a lightning-caused fire in Douglas County, Colorado. According to Renewable Energy World (18 July 2024), emergency services dispatched two helicopters within 30 minutes of the identification, when the fire was 0.25 acres. The helicopters dropped 17,765 gallons of water over six hours and the fire was limited to three acres. Denver7 (17 July 2024) reported that the fire was contained within a day and was first spotted by the AI-equipped cameras. CORE's wildfire mitigation manager Jordan Ambrogi said alerts typically arrive 10 to 12 minutes after smoke is detected. The utilities, however, said the cameras identified the fire “simultaneously” with the U.S. Forest Service. So the cameras' independent contribution to containment rests on the operators' own statements (CORE interim CEO Pam Feuerstein). The OECD AI Incidents Monitor carries a separate positively framed record of Xcel's November 2023 Pano AI deployment.", "replication": { "produced_by": [ "Camera stations with 360-degree views sited on cell towers within roughly 10 miles of the ignition", "Alert routing to both the utility and local fire agencies with a triangulated location", "Lightning-caused ignition in daylight in a remote area, with aerial resources available for dispatch" ], "must_hold": [ "Camera coverage of the ignition point and functioning AI smoke detection", "An agency able to act on the alert within minutes", "Independent confirmation of who detected the fire first, since the utilities report simultaneous Forest Service identification" ], "echoes": [ { "date": "2024-07-09", "setting": "Wellington fire near Breckenridge, Summit County, Colorado; Xcel-funded Pano AI camera", "outcome": "recurred", "source": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/" }, { "date": "2024-08-29", "setting": "Austin Energy full deployment of 13 Pano AI cameras, Texas; no detection reported", "outcome": "unknown", "source": "https://austinenergy.com/about/news/news-releases/2024/Austin-Energy-announces-full-deployment-of-AI-driven-Early-Wildfire-Detection-System" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0242", "title": "UCF matched case-control study of 2,100 automated-vehicle and 35,113 human-driven crashes finds lower ADS crash odds in most scenarios, higher at dawn/dusk and turning", "summary": "Nature Communications (18 Jun 2024): using California DMV, NHTSA Standing General Order and SWITRS data, Abdel-Aty and Ding find ADS crash odds lower in most matched scenarios but 5.25x higher at d...", "date_observed": "2024-06-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mohamed Abdel-Aty and Shengxuan Ding of the University of Central Florida's Smart and Safe Transportation Lab assembled 2,100 automated-vehicle crash records. They came from the California DMV and NHTSA's Standing General Order databases (1,099 SAE Level 4 ADS, 1,001 Level 2 ADAS). They added 35,113 human-driven-vehicle crashes from California's SWITRS and fitted a matched case-control logistic regression. Compared with human-driven vehicles, the odds of an ADS crash in rain were 0.335 times, and most pre-crash movements reduced crash odds. But the odds of an ADS crash at dawn or dusk were 5.250 times and in turning maneuvers 1.988 times those of a human-driven vehicle. The authors attribute the advantages to object detection, precision control and decision-making, and the disadvantages to sensor adaptation to changing light and limited situational awareness. The paper was received 30 Sep 2023, accepted 2 May 2024 and published 18 Jun 2024, the date given. The analysis does not attribute vehicles to specific developers, so no individual maker is credited. The Europe PMC full text is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Automated driving systems are built to drive without human intervention. The study measures their crash occurrence against human-driven vehicles.", "system": "SAE Level 4 automated driving systems and Level 2 driver-assistance systems reported in California DMV and NHTSA SGO crash records (makers not disaggregated)", "model_version": null, "developer": "Multiple automated-vehicle developers (not disaggregated in the study)", "deployer": "Multiple operators testing and deploying automated vehicles, mainly in California", "location": null, "domain": "Road vehicle crash avoidance", "segment": "Automated driving systems", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Aggregate statistical comparison with no attributable outcome." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome is documented." }, { "group": "personal", "depth": null, "reason": "No individual beneficiary is documented." } ], "ai_role": { "status": "assessed", "statement": "The study compares the conditions under which ADS and human-driven crashes occurred. It does not observe interventions and cannot separate exposure differences from system performance. Independent university authors; regulator databases as sources." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Abdel-Aty M, Ding S (2024). A matched case-control analysis of autonomous vs human-driven vehicle accidents. Nature Communications 15, 4931. doi:10.1038/s41467-024-48526-4.", "title": "A matched case-control analysis of autonomous vs human-driven vehicle accidents", "url": "https://europepmc.org/article/MED/38890354", "date": "2024-06-18", "written_by": "independent", "quote": "The analysis suggests that accidents of vehicles equipped with Advanced Driving Systems generally have a lower chance of occurring than Human-Driven Vehicles in most of the similar accident scenarios." }, { "kind": "peer-reviewed study", "citation": "Abdel-Aty M, Ding S (2024). A matched case-control analysis of autonomous vs human-driven vehicle accidents. 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They came from the California DMV and NHTSA's Standing General Order databases (1,099 SAE Level 4 ADS, 1,001 Level 2 ADAS). They added 35,113 human-driven-vehicle crashes from California's SWITRS and fitted a matched case-control logistic regression. Compared with human-driven vehicles, the odds of an ADS crash in rain were 0.335 times, and most pre-crash movements reduced crash odds. But the odds of an ADS crash at dawn or dusk were 5.250 times and in turning maneuvers 1.988 times those of a human-driven vehicle. The authors attribute the advantages to object detection, precision control and decision-making, and the disadvantages to sensor adaptation to changing light and limited situational awareness. The paper was received 30 Sep 2023, accepted 2 May 2024 and published 18 Jun 2024, the date given. The analysis does not attribute vehicles to specific developers, so no individual maker is credited. The Europe PMC full text is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SAE Level 4 automated driving systems and Level 2 driver-assistance systems reported in California DMV and NHTSA SGO crash records (makers not disaggregated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Multiple automated-vehicle developers (not disaggregated in the study)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "UCF matched case-control study of 2,100 automated-vehicle and 35,113 human-driven crashes finds lower ADS crash odds in most scenarios, higher at dawn/dusk and turning", "headline": "ADS crash odds are lower in most scenarios, higher at dusk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "892e08bd733633bb6ed57cbee7277bea736bf3a75067be48f63a4d2518a153e8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mohamed Abdel-Aty and Shengxuan Ding of the University of Central Florida's Smart and Safe Transportation Lab assembled 2,100 automated-vehicle crash records. They came from the California DMV and NHTSA's Standing General Order databases (1,099 SAE Level 4 ADS, 1,001 Level 2 ADAS). They added 35,113 human-driven-vehicle crashes from California's SWITRS and fitted a matched case-control logistic regression. Compared with human-driven vehicles, the odds of an ADS crash in rain were 0.335 times, and most pre-crash movements reduced crash odds. But the odds of an ADS crash at dawn or dusk were 5.250 times and in turning maneuvers 1.988 times those of a human-driven vehicle. The authors attribute the advantages to object detection, precision control and decision-making, and the disadvantages to sensor adaptation to changing light and limited situational awareness. The paper was received 30 Sep 2023, accepted 2 May 2024 and published 18 Jun 2024, the date given. The analysis does not attribute vehicles to specific developers, so no individual maker is credited. The Europe PMC full text is among the sources.", "replication": { "produced_by": [ "Mandatory crash reporting for automated vehicles to the California DMV and under NHTSA's Standing General Order", "A state police-reported crash database (SWITRS) with matching variables for road, environment and pre-crash movement", "Matched case-control logistic regression across road, environment and crash type" ], "must_hold": [ "Continued regulator collection of ADS and ADAS crash reports", "Comparable variable definitions between ADS reports and human crash records", "Enough ADS crashes in each condition to estimate odds ratios" ], "echoes": [ { "date": "2024-07-14", "setting": "Insurance-claims comparison by Swiss Re and Waymo authors: zero bodily-injury and 76% fewer property-damage claims over 3.9 million rider-only miles in San Francisco and Phoenix", "outcome": "recurred", "source": "https://doi.org/10.1016/j.heliyon.2024.e34379" }, { "date": "2025-05-16", "setting": "Waymo rider-only crash rates by crash type versus police-reported benchmarks at 56.7 million miles (Waymo authors, peer-reviewed)", "outcome": "recurred", "source": "https://doi.org/10.1080/15389588.2025.2499887" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0315", "title": "HALO Trust pilots AWS-supported AI to find explosive remnants in drone imagery of Ukrainian minefields; it may be about 70% accurate, with no clearance outcome yet", "summary": "HALO announced a US$4m AWS package (25 June 2024) to trial AI on drone imagery of Ukrainian minefields; Reuters (30 April 2026) reports about 70% accuracy; no cleared land or found mine attributed.", "date_observed": "2024-06-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The HALO Trust announced a US$4 million package of support from Amazon Web Services on 25 June 2024. An archived copy of the page, dated 20 May 2026, is among the sources. It “will enable HALO to trial artificial intelligence (AI) to assist in the process of detecting debris of war (including landmines and other explosives) in drone imagery for existing minefields and battlefields in Ukraine”. It also covers machine-learning detection of damaged buildings in satellite imagery with SageMaker. By then HALO had flown 542 drone flights over Ukrainian minefields, producing 11 terabytes of imagery. It said training would require manually labeling thousands of images and ongoing vetting by HALO staff to remove false positives and negatives. A HALO page of 21 February 2025 describes the pilot through its head of research and development, Matthew Abercrombie. He says an analyst “can take three to five days to look through the imagery for an average minefield”. It reports no results. Reuters (Sergiy Karazy, 30 April 2026, syndicated by KELO) reported from Myrotske, 40 km north-west of Kyiv. HALO “has turned to AI to analyze high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already”. It quoted HALO media manager Olena Shustova. The article does not mention AWS and attributes no cleared land, found mine or time saving to the model. No later milestone is dated.", "category": "general benefit", "unexpected": false, "purpose": "Built to flag landmines and other debris of war in drone imagery so that HALO analysts spend less time searching thousands of images per minefield. The pilot is that intended use.", "system": "HALO Trust AI and machine-learning analysis of drone imagery for explosive remnants of war (hosted on AWS; SageMaker used for satellite-imagery damage detection)", "model_version": null, "developer": "The HALO Trust and development team with Amazon Web Services", "deployer": "The HALO Trust, Ukraine program", "location": "Ukraine", "domain": "Humanitarian mine action", "segment": "Survey and prioritization of contaminated land by a demining NGO", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The only figure is a pilot accuracy; faster analyst work is HALO's stated aim, not a result.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "HALO's pages state the aim (three to five analyst-days per minefield) and Reuters gives “around 70% accuracy”. No time saving, detection count or land release attributable to the model is documented." }, { "group": "societal", "depth": null, "reason": "No cited source links the AI pilot to any cleared hectare, found mine or avoided casualty in Ukraine." } ], "ai_role": { "status": "assessed", "statement": "The model is being trained to detect explosive remnants in drone imagery with HALO analysts labeling and vetting outputs. The only performance figure, around 70% accuracy, is reported by Reuters without its basis. The organization's own June 2024 and February 2025 pages report plans and workflow, not results. No independent evaluation, cleared area or detected-mine count is documented." }, "evidence": [ { "kind": "press release", "citation": "The HALO Trust (2024). AI to help accelerate landmine clearance. halotrust.org, 25 June 2024 (original URL now returns 404).", "title": "AI to help accelerate landmine clearance", "url": "http://web.archive.org/web/20260520220522/https://www.halotrust.org/news/artificial-intelligence-to-help-accelerate-landmine-clearance/", "date": "2024-06-25", "written_by": "makers", "quote": "HALO expects this pilot project will begin trialing drone imagery analysis using AI in the coming months." }, { "kind": "press release", "citation": "The HALO Trust (2025). Using drones and AI to eradicate landmines. halotrust.org, 21 February 2025.", "title": "Using drones and AI to eradicate landmines", "url": "https://www.halotrust.org/news/using-drones-and-ai-to-eradicate-landmines/", "date": "2025-02-21", "written_by": "makers", "quote": "It can take three to five days to look through the imagery for an average minefield," }, { "kind": "news report", "citation": "Karazy S (2026). Man, machine and AI combine in battle to clear Ukraine of mines. Reuters, 30 April 2026, syndicated by KELO.", "title": "Man, machine and AI combine in battle to clear Ukraine of mines", "url": "https://kelo.com/2026/04/30/man-machine-and-ai-combine-in-battle-to-clear-ukraine-of-mines/", "date": "2026-04-30", "written_by": "independent", "quote": "HALO Trust has turned to AI to analyse high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already." } ], "replication": { "produced_by": [ "High-resolution drone imagery of known minefields (542 flights, 11 terabytes by June 2024) manually labeled by HALO staff", "AWS cloud credits, storage and SageMaker tooling to train and host the models" ], "must_hold": [ "Trained HALO personnel vet model outputs to remove false positives and negatives before survey decisions", "Imagery resolution and ground conditions resemble the training minefields" ], "echoes": [] }, "paired_incident": null, "headline": "HALO's AI may spot mines in Ukraine with about 70% accuracy", "metric": "achieving around 70% accuracy already", "comparator": { "against": "manual analyst review of drone imagery of a minefield", "before": "three to five days to look through the imagery for an average minefield", "after": null, "basis": "assumed", "quote": "“The problem is that an analyst searching through thousands of images takes a very long time. It can take three to five days to look through the imagery for an average minefield,” said Abercrombie.", "url": "https://www.halotrust.org/news/using-drones-and-ai-to-eradicate-landmines/" }, "later": { "status": "persisted", "date": "2026-04-30", "note": "Reuters reported from Ukraine in April 2026 that HALO's AI trained on drone imagery was identifying mines and explosive remnants with around 70% accuracy, still with no clearance outcome attributed to it.", "quote": "Given the ⁠huge scale of the task, HALO Trust has turned to ⁠AI to analyse high-resolution drone imagery of contaminated areas and train systems to ​identify mines and explosive remnants, achieving around 70% accuracy already.", "url": "https://kelo.com/2026/04/30/man-machine-and-ai-combine-in-battle-to-clear-ukraine-of-mines/" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.halotrust.org/news/using-drones-and-ai-to-eradicate-landmines/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.halotrust.org/contact-us/; https://www.halotrust.org/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to The HALO Trust.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two press releases from the makers. 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AI to help accelerate landmine clearance. halotrust.org, 25 June 2024 (original URL now returns 404).", "title": "AI to help accelerate landmine clearance", "url": "http://web.archive.org/web/20260520220522/https://www.halotrust.org/news/artificial-intelligence-to-help-accelerate-landmine-clearance/", "date": "2024-06-25", "written_by": "makers", "quote": "HALO expects this pilot project will begin trialing drone imagery analysis using AI in the coming months." }, { "kind": "press release", "citation": "The HALO Trust (2025). Using drones and AI to eradicate landmines. halotrust.org, 21 February 2025.", "title": "Using drones and AI to eradicate landmines", "url": "https://www.halotrust.org/news/using-drones-and-ai-to-eradicate-landmines/", "date": "2025-02-21", "written_by": "makers", "quote": "It can take three to five days to look through the imagery for an average minefield," }, { "kind": "news report", "citation": "Karazy S (2026). Man, machine and AI combine in battle to clear Ukraine of mines. Reuters, 30 April 2026, syndicated by KELO.", "title": "Man, machine and AI combine in battle to clear Ukraine of mines", "url": "https://kelo.com/2026/04/30/man-machine-and-ai-combine-in-battle-to-clear-ukraine-of-mines/", "date": "2026-04-30", "written_by": "independent", "quote": "HALO Trust has turned to AI to analyse high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0315-source-0001", "AIBD-0315-source-0002", "AIBD-0315-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "The HALO Trust (2024). AI to help accelerate landmine clearance. halotrust.org, 25 June 2024 (original URL now returns 404).", "title": "AI to help accelerate landmine clearance", "url": "http://web.archive.org/web/20260520220522/https://www.halotrust.org/news/artificial-intelligence-to-help-accelerate-landmine-clearance/", "date": "2024-06-25", "written_by": "makers", "quote": "HALO expects this pilot project will begin trialing drone imagery analysis using AI in the coming months." }, { "kind": "press release", "citation": "The HALO Trust (2025). Using drones and AI to eradicate landmines. halotrust.org, 21 February 2025.", "title": "Using drones and AI to eradicate landmines", "url": "https://www.halotrust.org/news/using-drones-and-ai-to-eradicate-landmines/", "date": "2025-02-21", "written_by": "makers", "quote": "It can take three to five days to look through the imagery for an average minefield," }, { "kind": "news report", "citation": "Karazy S (2026). Man, machine and AI combine in battle to clear Ukraine of mines. Reuters, 30 April 2026, syndicated by KELO.", "title": "Man, machine and AI combine in battle to clear Ukraine of mines", "url": "https://kelo.com/2026/04/30/man-machine-and-ai-combine-in-battle-to-clear-ukraine-of-mines/", "date": "2026-04-30", "written_by": "independent", "quote": "HALO Trust has turned to AI to analyse high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "HALO announced a US$4m AWS package (25 June 2024) to trial AI on drone imagery of Ukrainian minefields; Reuters (30 April 2026) reports about 70% accuracy; no cleared land or found mine attributed.", "account": "The HALO Trust announced a US$4 million package of support from Amazon Web Services on 25 June 2024. An archived copy of the page, dated 20 May 2026, is among the sources. It “will enable HALO to trial artificial intelligence (AI) to assist in the process of detecting debris of war (including landmines and other explosives) in drone imagery for existing minefields and battlefields in Ukraine”. It also covers machine-learning detection of damaged buildings in satellite imagery with SageMaker. By then HALO had flown 542 drone flights over Ukrainian minefields, producing 11 terabytes of imagery. It said training would require manually labeling thousands of images and ongoing vetting by HALO staff to remove false positives and negatives. A HALO page of 21 February 2025 describes the pilot through its head of research and development, Matthew Abercrombie. He says an analyst “can take three to five days to look through the imagery for an average minefield”. It reports no results. Reuters (Sergiy Karazy, 30 April 2026, syndicated by KELO) reported from Myrotske, 40 km north-west of Kyiv. HALO “has turned to AI to analyze high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already”. It quoted HALO media manager Olena Shustova. The article does not mention AWS and attributes no cleared land, found mine or time saving to the model. No later milestone is dated." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "HALO Trust AI and machine-learning analysis of drone imagery for explosive remnants of war (hosted on AWS; SageMaker used for satellite-imagery damage detection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "The HALO Trust and development team with Amazon Web Services" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "HALO Trust pilots AWS-supported AI to find explosive remnants in drone imagery of Ukrainian minefields; it may be about 70% accurate, with no clearance outcome yet", "headline": "HALO's AI may spot mines in Ukraine with about 70% accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ea9458b9fb0cadf42b4bf16a68eda0d38176e92a9ee731a432964a53e4f9a156" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The HALO Trust announced a US$4 million package of support from Amazon Web Services on 25 June 2024. An archived copy of the page, dated 20 May 2026, is among the sources. It “will enable HALO to trial artificial intelligence (AI) to assist in the process of detecting debris of war (including landmines and other explosives) in drone imagery for existing minefields and battlefields in Ukraine”. It also covers machine-learning detection of damaged buildings in satellite imagery with SageMaker. By then HALO had flown 542 drone flights over Ukrainian minefields, producing 11 terabytes of imagery. It said training would require manually labeling thousands of images and ongoing vetting by HALO staff to remove false positives and negatives. A HALO page of 21 February 2025 describes the pilot through its head of research and development, Matthew Abercrombie. He says an analyst “can take three to five days to look through the imagery for an average minefield”. It reports no results. Reuters (Sergiy Karazy, 30 April 2026, syndicated by KELO) reported from Myrotske, 40 km north-west of Kyiv. HALO “has turned to AI to analyze high-resolution drone imagery of contaminated areas and train systems to identify mines and explosive remnants, achieving around 70% accuracy already”. It quoted HALO media manager Olena Shustova. The article does not mention AWS and attributes no cleared land, found mine or time saving to the model. No later milestone is dated.", "replication": { "produced_by": [ "High-resolution drone imagery of known minefields (542 flights, 11 terabytes by June 2024) manually labeled by HALO staff", "AWS cloud credits, storage and SageMaker tooling to train and host the models" ], "must_hold": [ "Trained HALO personnel vet model outputs to remove false positives and negatives before survey decisions", "Imagery resolution and ground conditions resemble the training minefields" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0025", "title": "Withings ScanWatch ECG QT measurement leading to congenital long QT syndrome diagnosis and beta-blocker therapy", "summary": "Withings ScanWatch ECGs showing prolonged QT led to a KCNH2 long-QT diagnosis and nadolol for a father and daughter (Germany).", "date_observed": "2024-07-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "An asymptomatic 39-year-old man came to the cardiology outpatient clinic of University Medical Centre Mannheim, Germany, because of QT prolongation recorded with his Withings ScanWatch. He had made its single-lead electrocardiogram (ECG) recordings out of curiosity. The watch displayed values such as QT 506 ms and QTc 457 ms. Genetic screening found a previously unpublished nonsense variant in KCNH2, establishing congenital long QT syndrome. Nadolol 40 mg daily shortened his QTc by 50–70 ms to 430 ms. His 7-year-old daughter carried the same variant with a borderline QTc of 460 ms and was also prescribed nadolol. The case report appeared on 4 July 2024 (event dates not reported).", "category": "benefit created", "unexpected": false, "purpose": "The ScanWatch records a single-lead ECG and, in the version described, includes a QT monitoring function. Flagging a prolonged QT interval was within what it was built to do.", "system": "Withings ScanWatch ECG with QT monitoring function", "model_version": "Withings ScanWatch (generation not stated)", "developer": "Withings", "deployer": null, "location": "Mannheim, Germany", "domain": "Healthcare (cardiology; clinical genetics)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Two identifiable people (father and daughter) received a genetic long QT diagnosis and prophylactic beta-blockade against sudden arrhythmic death. A life-changing benefit, though no event was imminent." } ], "ai_role": { "status": "assessed", "statement": "The watch's automated ECG analysis displayed the QT and QTc values that prompted the clinic visit. No automatic alert is described. The report does not say who first noticed the values. Diagnosis rested on clinical ECGs and genetic testing." }, "evidence": [ { "kind": "case report", "citation": "Rudic B, Kauferstein S, Akin I, Borggrefe M (2024). Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch. HeartRhythm Case Reports 10(10):699-701.", "title": "Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch", "url": "https://europepmc.org/article/PMC/PMC11628798", "date": "2024-07-04", "written_by": "independent", "quote": "A 39-year-old otherwise healthy male patient presented in our outpatient clinic owing to QT prolongation recorded with his smartwatch (ScanWatch; Withings SA, Issy les Moulineaux, France)." } ], "replication": { "produced_by": [ "The wearer records ScanWatch ECGs and the QT function reports a prolonged interval", "The wearer or a clinician takes the displayed values to a cardiology service", "Clinical ECG and genetic testing confirm an inherited channelopathy" ], "must_hold": [ "The QT function is available in the wearer's region and firmware", "Recordings are of adequate quality", "Cardiogenetic evaluation and family screening are accessible" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1666", "title": "Oura Smart Ring Purchaser in California Alleged Company Overstated AI Sleep-Tracking Accuracy, Leading to Overpayment", "url": "https://incidentdatabase.ai/cite/1666", "severity": null, "group": "personal", "basis": "Consumer wearable inferring a health measure from sensor signals: ScanWatch's QT values proved true, while Oura's sleep-staging algorithm was allegedly less accurate than claimed, harming ring purchasers who relied on it." }, "headline": "Withings ScanWatch ECGs lead to a long-QT diagnosis and nadolol", "metric": "the watch displayed values such as QT 506 ms and QTc 457 ms", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The only cited source is the case report itself; no later development was found.", "quote": null, "url": null }, "value": null, "developer_country": "France", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1666 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1666", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Withings", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0025", "catalog_version": "1.0.0", "source_fingerprint": "54ddaa87132a140f49ec348d1e858593a0f13c0462ab85a371d81ee001cfde88", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0025-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Withings" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's automated ECG analysis displayed the QT and QTc values that prompted the clinic visit. No automatic alert is described. The report does not say who first noticed the values. Diagnosis rested on clinical ECGs and genetic testing." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's automated ECG analysis displayed the QT and QTc values that prompted the clinic visit. No automatic alert is described. The report does not say who first noticed the values. Diagnosis rested on clinical ECGs and genetic testing." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two identifiable people (father and daughter) received a genetic long QT diagnosis and prophylactic beta-blockade against sudden arrhythmic death. A life-changing benefit, though no event was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two identifiable people (father and daughter) received a genetic long QT diagnosis and prophylactic beta-blockade against sudden arrhythmic death. A life-changing benefit, though no event was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two identifiable people (father and daughter) received a genetic long QT diagnosis and prophylactic beta-blockade against sudden arrhythmic death. A life-changing benefit, though no event was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Consumer wearable inferring a health measure from sensor signals: ScanWatch's QT values proved true, while Oura's sleep-staging algorithm was allegedly less accurate than claimed, harming ring purchasers who relied on it.", "links": [ { "database": "AI Incident Database", "identifier": "1666", "title": "Oura Smart Ring Purchaser in California Alleged Company Overstated AI Sleep-Tracking Accuracy, Leading to Overpayment", "url": "https://incidentdatabase.ai/cite/1666", "group": "personal", "basis": "Consumer wearable inferring a health measure from sensor signals: ScanWatch's QT values proved true, while Oura's sleep-staging algorithm was allegedly less accurate than claimed, harming ring purchasers who relied on it.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "the watch displayed values such as QT 506 ms and QTc 457 ms", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "1666", "title": "Oura Smart Ring Purchaser in California Alleged Company Overstated AI Sleep-Tracking Accuracy, Leading to Overpayment", "url": "https://incidentdatabase.ai/cite/1666", "group": "personal", "basis": "Consumer wearable inferring a health measure from sensor signals: ScanWatch's QT values proved true, while Oura's sleep-staging algorithm was allegedly less accurate than claimed, harming ring purchasers who relied on it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The only cited source is the case report itself; no later development was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0025" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "An asymptomatic 39-year-old man came to the cardiology outpatient clinic of University Medical Centre Mannheim, Germany, because of QT prolongation recorded with his Withings ScanWatch. He had made its single-lead electrocardiogram (ECG) recordings out of curiosity. The watch displayed values such as QT 506 ms and QTc 457 ms. Genetic screening found a previously unpublished nonsense variant in KCNH2, establishing congenital long QT syndrome. Nadolol 40 mg daily shortened his QTc by 50–70 ms to 430 ms. His 7-year-old daughter carried the same variant with a borderline QTc of 460 ms and was also prescribed nadolol. The case report appeared on 4 July 2024 (event dates not reported).", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two identifiable people (father and daughter) received a genetic long QT diagnosis and prophylactic beta-blockade against sudden arrhythmic death. A life-changing benefit, though no event was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The ScanWatch records a single-lead ECG and, in the version described, includes a QT monitoring function. Flagging a prolonged QT interval was within what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Mannheim, Germany", "developer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The ScanWatch records a single-lead ECG and, in the version described, includes a QT monitoring function. Flagging a prolonged QT interval was within what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-07-04", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1666 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1666", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Withings", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The wearer records ScanWatch ECGs and the QT function reports a prolonged interval", "The wearer or a clinician takes the displayed values to a cardiology service", "Clinical ECG and genetic testing confirm an inherited channelopathy" ], "must_hold": [ "The QT function is available in the wearer's region and firmware", "Recordings are of adequate quality", "Cardiogenetic evaluation and family screening are accessible" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1666 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1666", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Withings", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; clinical genetics)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Rudic B, Kauferstein S, Akin I, Borggrefe M (2024). Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch. HeartRhythm Case Reports 10(10):699-701.", "title": "Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch", "url": "https://europepmc.org/article/PMC/PMC11628798", "date": "2024-07-04", "written_by": "independent", "quote": "A 39-year-old otherwise healthy male patient presented in our outpatient clinic owing to QT prolongation recorded with his smartwatch (ScanWatch; Withings SA, Issy les Moulineaux, France)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0025-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Rudic B, Kauferstein S, Akin I, Borggrefe M (2024). Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch. HeartRhythm Case Reports 10(10):699-701.", "title": "Can wearables outscore general practitioners? Congenital long QT syndrome diagnosis initiated by a smartwatch", "url": "https://europepmc.org/article/PMC/PMC11628798", "date": "2024-07-04", "written_by": "independent", "quote": "A 39-year-old otherwise healthy male patient presented in our outpatient clinic owing to QT prolongation recorded with his smartwatch (ScanWatch; Withings SA, Issy les Moulineaux, France)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Withings ScanWatch ECGs showing prolonged QT led to a KCNH2 long-QT diagnosis and nadolol for a father and daughter (Germany).", "account": "An asymptomatic 39-year-old man came to the cardiology outpatient clinic of University Medical Centre Mannheim, Germany, because of QT prolongation recorded with his Withings ScanWatch. He had made its single-lead electrocardiogram (ECG) recordings out of curiosity. The watch displayed values such as QT 506 ms and QTc 457 ms. Genetic screening found a previously unpublished nonsense variant in KCNH2, establishing congenital long QT syndrome. Nadolol 40 mg daily shortened his QTc by 50–70 ms to 430 ms. His 7-year-old daughter carried the same variant with a borderline QTc of 460 ms and was also prescribed nadolol. The case report appeared on 4 July 2024 (event dates not reported)." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The watch analyzed ECG recordings and displayed QT and QTc values." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used a Withings ScanWatch." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Withings ScanWatch (generation not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Withings ScanWatch ECG with QT monitoring function" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Withings" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Withings ScanWatch ECG QT measurement leading to congenital long QT syndrome diagnosis and beta-blocker therapy", "headline": "Withings ScanWatch ECGs lead to a long-QT diagnosis and nadolol" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "54ddaa87132a140f49ec348d1e858593a0f13c0462ab85a371d81ee001cfde88" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "An asymptomatic 39-year-old man came to the cardiology outpatient clinic of University Medical Centre Mannheim, Germany, because of QT prolongation recorded with his Withings ScanWatch. He had made its single-lead electrocardiogram (ECG) recordings out of curiosity. The watch displayed values such as QT 506 ms and QTc 457 ms. Genetic screening found a previously unpublished nonsense variant in KCNH2, establishing congenital long QT syndrome. Nadolol 40 mg daily shortened his QTc by 50–70 ms to 430 ms. His 7-year-old daughter carried the same variant with a borderline QTc of 460 ms and was also prescribed nadolol. The case report appeared on 4 July 2024 (event dates not reported).", "replication": { "produced_by": [ "The wearer records ScanWatch ECGs and the QT function reports a prolonged interval", "The wearer or a clinician takes the displayed values to a cardiology service", "Clinical ECG and genetic testing confirm an inherited channelopathy" ], "must_hold": [ "The QT function is available in the wearer's region and firmware", "Recordings are of adequate quality", "Cardiogenetic evaluation and family screening are accessible" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0007", "title": "ALERTCalifornia AI camera alert sends Cal Fire engines to a night fire near Auburn before any 911 call", "summary": "AI camera alert at 2:33 a.m. on 6 July 2024 sent Cal Fire engines to a fire near Auburn before any 911 call; held to a 30 x 30 ft area", "date_observed": "2024-07-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The ALERTCalifornia camera network is operated by UC San Diego with AI smoke-detection software from DigitalPath of Chico, California, and used by Cal Fire. It posted an alert at 2:33 a.m. on July 6 of a fire near Auburn, in the foothills east of Sacramento. The report, from September 2025, gives the day but not the year. It places the case among the previous year's fires, so 2024 is used. Nobody had called 911. Cal Fire's Grass Valley Emergency Command Center verified the alert and sent engines. Crews put the fire out before it spread beyond a 30 x 30 foot area. Cal Fire Deputy Chief Brian York said in 2024 the cameras picked up 1,668 of the 7,553 fires in Cal Fire's jurisdiction. Of those, 636 came before any person called 911.", "category": "harm prevented", "unexpected": false, "purpose": "Built to detect smoke in camera feeds and alert fire dispatchers automatically. This benefit is that purpose.", "system": "ALERTCalifornia camera network with DigitalPath AI smoke detection", "model_version": null, "developer": "DigitalPath (AI smoke detection); ALERTCalifornia, University of California San Diego (camera network)", "deployer": "California Department of Forestry and Fire Protection (Cal Fire)", "location": "Auburn, United States", "domain": "Wildfire detection and response", "segment": "Public safety / fire services", "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Cal Fire's Grass Valley command center dispatched engines on the alert. Crews extinguished the fire at a 30 x 30 ft area, avoiding a larger night-time incident." }, { "group": "societal", "depth": 2, "reason": "Residents near Auburn benefited from a fire being put out before it spread. The damage avoided is not quantified for this fire in the sources." } ], "ai_role": { "status": "assessed", "statement": "The AI alert was the only report of the Auburn fire. Cal Fire's command center verified it and dispatched on it. The same source says the system still produces false positives from dust and clouds, so human verification sits between alert and dispatch." }, "evidence": [ { "kind": "news report", "citation": "Rogers, P. (2025). ALERTCalifornia AI wildfire camera network replaces human lookout towers across California. Bay Area News Group / Tribune News Service, republished by FireRescue1.", "title": "Over 1,000 AI cameras help spot Calif. wildfires before the first 911 call", "url": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call", "date": "2025-09-19", "written_by": "independent", "quote": "an AI camera posted an alert at 2:33 am of a fire near Auburn, in the foothills east of Sacramento. Nobody had called 911." }, { "kind": "news report", "citation": "Rogers, P. (2025). AI cameras are spotting wildfires across California—often before humans call 911. MediaNews Group via Tribune Content Agency, republished by Phys.org.", "title": "AI cameras are spotting wildfires across California—often before humans call 911", "url": "https://phys.org/news/2025-09-ai-cameras-wildfires-california-humans.html", "date": "2025-09-22", "written_by": "independent", "quote": "Of those, 1,668 were picked up by the cameras, said Cal Fire's York. And 38%, or 636, were detected by the cameras before any person called 911" }, { "kind": "news report", "citation": "Reuters (2023). California turns to AI to help spot wildfires. Republished by Gulf News.", "title": "California turns to AI to help spot wildfires", "url": "https://gulfnews.com/world/americas/california-turns-to-ai-to-help-spot-wildfires-1.1691753082670", "date": "2023-08-11", "written_by": "independent", "quote": "Within 45 minutes the fire was out, Cal Fire said." }, { "kind": "press release", "citation": "Office of Governor Gavin Newsom (2023). TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023. gov.ca.gov.", "title": "TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023", "url": "https://www.gov.ca.gov/2023/10/24/time-recognizes-cal-fire-ai-alertcalifornia-as-a-best-invention-of-2023/", "date": "2023-10-24", "written_by": "deployer", "quote": "In the first two months, the system had correctly identified 77 fires before any 911 calls came in" }, { "kind": "news report", "citation": "Stevens, A. (2024). AI technology detects fire in rural San Luis Obispo County before 911 calls are made. KSBY.", "title": "AI technology detects fire in rural San Luis Obispo County before 911 calls are made", "url": "https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made", "date": "2024-10-16", "written_by": "independent", "quote": "Without that early detection, that fire could have grown to a couple of hundred acres in size and potentially burned structures." }, { "kind": "news report", "citation": "Branch, J. (2026). How California is using AI and cameras to stop wildfires. The New York Times, republished by The Philadelphia Inquirer.", "title": "How California is using AI and cameras to stop wildfires", "url": "https://inquirer.com/news/nation-world/remote-cameras-ai-spot-wildfires-crew-satellite-wifi-california-20261015.html", "date": "2026-10-15", "written_by": "independent", "quote": "This system has changed the world of response. We have instant visibility and instant information that we need to make response decisions." } ], "replication": { "produced_by": [ "A fixed camera network with 24/7 AI smoke detection covering remote terrain", "A dispatch center that verifies AI alerts and sends crews without waiting for a 911 call" ], "must_hold": [ "A human verifies the alert before dispatch. The same source reports false positives from dust and clouds", "Crews can reach the fire while it is still small" ], "echoes": [ { "date": null, "setting": "Cleveland National Forest, about 50 miles east of San Diego, California; fire at 3 a.m. after the AI program began 10 July 2023; AI alerted a fire captain, about 60 firefighters responded, fire out within 45 minutes per Cal Fire (Reuters, 11 August 2023)", "model_version": null, "outcome": "recurred", "source": "https://gulfnews.com/world/americas/california-turns-to-ai-to-help-spot-wildfires-1.1691753082670" }, { "date": "2024-10-15", "setting": "La Panza Ranch, San Luis Obispo County, California; ALERTCalifornia AI notified Cal Fire of smoke with no public 911 call; fire held to about 16 acres (KSBY; Paso Robles Daily News, 29 October 2024)", "model_version": null, "outcome": "recurred", "source": "https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made ; https://pasoroblesdailynews.com/local-fire-detected-by-ai-technology-before-anyone-had-noticed-it/204388/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "796", "title": "Facebook's Content Moderation System Flagged and Removed Emergency Updates as Spam During Wildfires", "url": "https://incidentdatabase.ai/cite/796", "severity": null, "group": "societal", "basis": "Wildfire alerting in California: Facebook's AI moderation removed Cal Fire and Forest Service evacuation and fire-tracking updates as spam, harming the residents and evacuees whom the ALERTCalifornia camera alert near Auburn protected." }, "headline": "ALERTCalifornia alert sends Cal Fire engines before any 911 call", "metric": "crews put the fire out before it spread beyond a 30 x 30 foot area", "comparator": { "against": "waiting for a 911 call from the public", "before": "Nobody had called 911", "after": "put it out before it spread beyond a 30 x 30 foot area", "basis": "measured", "quote": "Nobody had called 911. Cal Fire's Grass Valley Emergency Command Center verified it and sent engines. Fire crews found the fire and put it out before it spread beyond a 30 x 30 foot area.", "url": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call" }, "later": { "status": "scaled", "date": "2026-10-15", "note": "By October 2026 the network had grown to nearly 1,300 cameras, with AI spotting most fires before a 911 call and the program director planning 1,800 cameras.", "quote": "Since 2023, artificial intelligence has instantly scoured Alert California camera footage, spotting wildfires before a 911 call is received in most cases.", "url": "https://inquirer.com/news/nation-world/remote-cameras-ai-spot-wildfires-crew-satellite-wifi-california-20261015.html" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Year corrected from 2025 to 2024: the source gives only the day and presents the case within its account of the previous year's fires.", "source": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 796 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/796", "editor": "AIBD" }, { "date": "2026-10-20", "change": "FireRescue1 evidence title changed from the page's HTML title element to the displayed headline, and the KSBY item dated 2024-10-16 from the page's publication timestamp (datePublished 2024–10–16T17:40:35–0700).", "source": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call ; https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call; https://inquirer.com/news/nation-world/remote-cameras-ai-spot-wildfires-crew-satellite-wifi-california-20261015.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.digitalpath.net/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/California_Department_of_Forestry_and_Fire_Protection", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0007", "catalog_version": "1.0.0", "source_fingerprint": "01c7e0ca7261efedfecb06f93ea4ec56552d85ff143fdeefa8b3497cd2830c84", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0007-source-0001", "AIBD-0007-source-0002", "AIBD-0007-source-0003", "AIBD-0007-source-0004", "AIBD-0007-source-0005", "AIBD-0007-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DigitalPath (AI smoke detection); ALERTCalifornia, University of California San Diego (camera network)", "deployer": "California Department of Forestry and Fire Protection (Cal Fire)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI alert was the only report of the Auburn fire. 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(2025). ALERTCalifornia AI wildfire camera network replaces human lookout towers across California. Bay Area News Group / Tribune News Service, republished by FireRescue1.", "title": "Over 1,000 AI cameras help spot Calif. wildfires before the first 911 call", "url": "https://www.firerescue1.com/artificial-intelligence/over-1-000-ai-cameras-help-spot-calif-wildfires-before-the-first-911-call", "date": "2025-09-19", "written_by": "independent", "quote": "an AI camera posted an alert at 2:33 am of a fire near Auburn, in the foothills east of Sacramento. Nobody had called 911." }, { "kind": "news report", "citation": "Rogers, P. (2025). AI cameras are spotting wildfires across California—often before humans call 911. 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TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023. gov.ca.gov.", "title": "TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023", "url": "https://www.gov.ca.gov/2023/10/24/time-recognizes-cal-fire-ai-alertcalifornia-as-a-best-invention-of-2023/", "date": "2023-10-24", "written_by": "deployer", "quote": "In the first two months, the system had correctly identified 77 fires before any 911 calls came in" }, { "kind": "news report", "citation": "Stevens, A. (2024). AI technology detects fire in rural San Luis Obispo County before 911 calls are made. KSBY.", "title": "AI technology detects fire in rural San Luis Obispo County before 911 calls are made", "url": "https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made", "date": "2024-10-16", "written_by": "independent", "quote": "Without that early detection, that fire could have grown to a couple of hundred acres in size and potentially burned structures." }, { "kind": "news report", "citation": "Branch, J. (2026). How California is using AI and cameras to stop wildfires. The New York Times, republished by The Philadelphia Inquirer.", "title": "How California is using AI and cameras to stop wildfires", "url": "https://inquirer.com/news/nation-world/remote-cameras-ai-spot-wildfires-crew-satellite-wifi-california-20261015.html", "date": "2026-10-15", "written_by": "independent", "quote": "This system has changed the world of response. 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TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023. gov.ca.gov.", "title": "TIME Recognizes CAL FIRE AI & AlertCalifornia as a Best Invention of 2023", "url": "https://www.gov.ca.gov/2023/10/24/time-recognizes-cal-fire-ai-alertcalifornia-as-a-best-invention-of-2023/", "date": "2023-10-24", "written_by": "deployer", "quote": "In the first two months, the system had correctly identified 77 fires before any 911 calls came in" }, { "kind": "news report", "citation": "Stevens, A. (2024). AI technology detects fire in rural San Luis Obispo County before 911 calls are made. KSBY.", "title": "AI technology detects fire in rural San Luis Obispo County before 911 calls are made", "url": "https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made", "date": "2024-10-16", "written_by": "independent", "quote": "Without that early detection, that fire could have grown to a couple of hundred acres in size and potentially burned structures." }, { "kind": "news report", "citation": "Branch, J. (2026). How California is using AI and cameras to stop wildfires. The New York Times, republished by The Philadelphia Inquirer.", "title": "How California is using AI and cameras to stop wildfires", "url": "https://inquirer.com/news/nation-world/remote-cameras-ai-spot-wildfires-crew-satellite-wifi-california-20261015.html", "date": "2026-10-15", "written_by": "independent", "quote": "This system has changed the world of response. We have instant visibility and instant information that we need to make response decisions." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI camera alert at 2:33 a.m. on 6 July 2024 sent Cal Fire engines to a fire near Auburn before any 911 call; held to a 30 x 30 ft area", "account": "The ALERTCalifornia camera network is operated by UC San Diego with AI smoke-detection software from DigitalPath of Chico, California, and used by Cal Fire. It posted an alert at 2:33 a.m. on July 6 of a fire near Auburn, in the foothills east of Sacramento. The report, from September 2025, gives the day but not the year. It places the case among the previous year's fires, so 2024 is used. Nobody had called 911. Cal Fire's Grass Valley Emergency Command Center verified the alert and sent engines. Crews put the fire out before it spread beyond a 30 x 30 foot area. Cal Fire Deputy Chief Brian York said in 2024 the cameras picked up 1,668 of the 7,553 fires in Cal Fire's jurisdiction. Of those, 636 came before any person called 911." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALERTCalifornia camera network with DigitalPath AI smoke detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DigitalPath (AI smoke detection); ALERTCalifornia, University of California San Diego (camera network)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ALERTCalifornia AI camera alert sends Cal Fire engines to a night fire near Auburn before any 911 call", "headline": "ALERTCalifornia alert sends Cal Fire engines before any 911 call" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "01c7e0ca7261efedfecb06f93ea4ec56552d85ff143fdeefa8b3497cd2830c84" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The ALERTCalifornia camera network is operated by UC San Diego with AI smoke-detection software from DigitalPath of Chico, California, and used by Cal Fire. It posted an alert at 2:33 a.m. on July 6 of a fire near Auburn, in the foothills east of Sacramento. The report, from September 2025, gives the day but not the year. It places the case among the previous year's fires, so 2024 is used. Nobody had called 911. Cal Fire's Grass Valley Emergency Command Center verified the alert and sent engines. Crews put the fire out before it spread beyond a 30 x 30 foot area. Cal Fire Deputy Chief Brian York said in 2024 the cameras picked up 1,668 of the 7,553 fires in Cal Fire's jurisdiction. Of those, 636 came before any person called 911.", "replication": { "produced_by": [ "A fixed camera network with 24/7 AI smoke detection covering remote terrain", "A dispatch center that verifies AI alerts and sends crews without waiting for a 911 call" ], "must_hold": [ "A human verifies the alert before dispatch. The same source reports false positives from dust and clouds", "Crews can reach the fire while it is still small" ], "echoes": [ { "setting": "Cleveland National Forest, about 50 miles east of San Diego, California; fire at 3 a.m. after the AI program began 10 July 2023; AI alerted a fire captain, about 60 firefighters responded, fire out within 45 minutes per Cal Fire (Reuters, 11 August 2023)", "outcome": "recurred", "source": "https://gulfnews.com/world/americas/california-turns-to-ai-to-help-spot-wildfires-1.1691753082670" }, { "date": "2024-10-15", "setting": "La Panza Ranch, San Luis Obispo County, California; ALERTCalifornia AI notified Cal Fire of smoke with no public 911 call; fire held to about 16 acres (KSBY; Paso Robles Daily News, 29 October 2024)", "outcome": "recurred", "source": "https://www.ksby.com/santa-margarita/ai-technology-detects-fire-in-san-luis-obispo-county-before-911-calls-are-made ; https://pasoroblesdailynews.com/local-fire-detected-by-ai-technology-before-anyone-had-noticed-it/204388/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0162", "title": "Xcel-funded Pano AI camera catches the Wellington fire near Breckenridge; crews hold it to one-eighth of an acre", "summary": "Xcel-funded Pano AI camera alerted crews to a campsite fire east of a Breckenridge neighborhood; firefighters said the early notice kept it to one-eighth of an acre (CBS Colorado, 9 July 2024).", "date_observed": "2024-07-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "CBS Colorado reported on 9 July 2024 on the Wellington fire, which broke out at an unattended campsite just east of a Breckenridge neighborhood. It was spotted by a Pano AI camera financially supported by Xcel Energy. The camera sits on a cell tower with a 360-degree view and submits an alert to emergency crews if it notices smoke. Firefighters said this was the first instance in Summit County where a wildfire was caught early thanks to the camera's early notice. It was kept to one-eighth of an acre. This followed earlier false alarms from legal campfires. Mathew Benedict of Red White and Blue Fire's Wildland Division said a location with an actual lat/long let crews drive straight to the fire. Otherwise they could spend up to an hour finding it. Xcel's Michelle Aguayo said the company had 28 Pano AI cameras installed. The fire's date is not given.", "category": "harm prevented", "unexpected": false, "purpose": "Pano AI cameras scan for smoke and alert emergency crews with a location. Catching a fire near homes early was the intended use.", "system": "Pano AI wildfire detection camera", "model_version": null, "developer": "Pano AI", "deployer": "Xcel Energy (camera funding); alerts received by Red White and Blue Fire", "location": "Breckenridge, United States", "domain": "Energy and infrastructure", "segment": "Electric utility wildfire mitigation", "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire next to a residential neighborhood was kept to one-eighth of an acre. Firefighters credit the camera's early notice, though the counterfactual is their judgment." }, { "group": "organizational", "depth": 2, "reason": "Red White and Blue Fire received an exact location and drove straight to the fire. Benedict said locating a wildfire can otherwise take an hour." }, { "group": "personal", "depth": null, "reason": "No individual beneficiary is documented." } ], "ai_role": { "status": "assessed", "statement": "The camera's AI smoke alert was the trigger for dispatch, according to the fire division quoted by CBS Colorado. The only source is a single local news report with named sources. The fire's date, cause of containment and any official report are not documented." }, "evidence": [ { "kind": "news report", "citation": "Spencer Wilson, 'AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire', CBS Colorado, 9 July 2024", "title": "AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "date": "2024-07-09", "written_by": "independent", "quote": "this was the first instance where a wildfire was caught early, and kept to only one-eighth of an acre, firefighters said, thanks to the camera's early notice." }, { "kind": "news report", "citation": "Spencer Wilson, CBS Colorado, 9 July 2024 (Mathew Benedict, Red White and Blue Fire)", "title": "AI-powered, fire-spotting cameras dispatch firefighters to Colorado wildfire", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/", "date": "2024-07-09", "written_by": "independent", "quote": "when we can get a location, an actual lat/long and drive straight through it instead of going through the process of finding" }, { "kind": "news report", "citation": "Breed, S. (2026). Xcel Energy deploys AI cameras to detect wildfires early in Colorado. KJCT8, 5 May 2026.", "title": "Xcel Energy deploys AI cameras to detect wildfires early in Colorado", "url": "https://www.kjct8.com/2026/05/05/xcel-energy-deploys-ai-cameras-detect-wildfires-early-colorado/", "date": "2026-05-05", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A camera station with a 360-degree view covering a campsite near housing", "Alerts routed to the local fire district with a lat/long", "A fire district willing to respond to AI alerts despite earlier false alarms" ], "must_hold": [ "Camera coverage of the ignition", "Crew availability to reach the location quickly", "Fire conditions that allow a small crew to contain a sub-acre fire" ], "echoes": [ { "date": "2024-06-16", "setting": "Bear Creek Fire, Douglas County, Colorado; Xcel and CORE Electric Pano AI cameras", "model_version": null, "outcome": "recurred", "source": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/" } ] }, "paired_incident": null, "headline": "Pano AI alert keeps Wellington fire to one-eighth of an acre", "metric": "the early notice kept it to one-eighth of an acre", "comparator": { "against": "locating a reported wildfire without the camera's coordinates", "before": "the process of finding, which often time with wildfires can take an hour", "after": "get a location, an actual lat/long and drive straight through it", "basis": "assumed", "quote": "It's learning Summit County and that's part of the progress, but when we can get a location, an actual lat/long and drive straight through it instead of going through the process of finding, which often time with wildfires can take an hour, just trying to figure out a location and access and figure out all the stuff and then get the troops there...it means a lot.", "url": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/" }, "later": { "status": "scaled", "date": "2026-05-05", "note": "By May 2026 Xcel Energy had more than 130 Pano AI cameras across Colorado, up from 28 at the time of the Wellington fire.", "quote": "Across the state, Xcel Energy has more than 130 Pano AI cameras that give them a look at fires as they’re happening in real time.", "url": "https://www.kjct8.com/2026/05/05/xcel-energy-deploys-ai-cameras-detect-wildfires-early-colorado/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.cbsnews.com/colorado/news/ai-powered-fire-spotting-cameras-dispatch-firefighters-wildfire/; https://www.kjct8.com/2026/05/05/xcel-energy-deploys-ai-cameras-detect-wildfires-early-colorado/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.pbs.org/newshour/show/how-satellites-and-ai-cameras-are-detecting-wildfires-before-they-get-out-of-control", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xcel_Energy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0162", "catalog_version": "1.0.0", "source_fingerprint": "29ac81165bbfb30d7b1712cc3c8a235d2761d00c6b092c2bf203bb66c15f9e75", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0162-source-0001", "AIBD-0162-source-0002", "AIBD-0162-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Pano AI", "deployer": "Xcel Energy (camera funding); alerts received by Red White and Blue Fire" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The camera's AI smoke alert was the trigger for dispatch, according to the fire division quoted by CBS Colorado. The only source is a single local news report with named sources. The fire's date, cause of containment and any official report are not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The camera's AI smoke alert was the trigger for dispatch, according to the fire division quoted by CBS Colorado. The only source is a single local news report with named sources. The fire's date, cause of containment and any official report are not documented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire next to a residential neighborhood was kept to one-eighth of an acre. Firefighters credit the camera's early notice, though the counterfactual is their judgment." }, { "group": "organizational", "depth": 2, "reason": "Red White and Blue Fire received an exact location and drove straight to the fire. Benedict said locating a wildfire can otherwise take an hour." }, { "group": "personal", "reason": "No individual beneficiary is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire next to a residential neighborhood was kept to one-eighth of an acre. Firefighters credit the camera's early notice, though the counterfactual is their judgment." }, { "group": "organizational", "depth": 2, "reason": "Red White and Blue Fire received an exact location and drove straight to the fire. Benedict said locating a wildfire can otherwise take an hour." }, { "group": "personal", "reason": "No individual beneficiary is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire next to a residential neighborhood was kept to one-eighth of an acre. Firefighters credit the camera's early notice, though the counterfactual is their judgment." }, { "group": "organizational", "depth": 2, "reason": "Red White and Blue Fire received an exact location and drove straight to the fire. Benedict said locating a wildfire can otherwise take an hour." }, { "group": "personal", "reason": "No individual beneficiary is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", 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It was spotted by a Pano AI camera financially supported by Xcel Energy. The camera sits on a cell tower with a 360-degree view and submits an alert to emergency crews if it notices smoke. Firefighters said this was the first instance in Summit County where a wildfire was caught early thanks to the camera's early notice. It was kept to one-eighth of an acre. This followed earlier false alarms from legal campfires. Mathew Benedict of Red White and Blue Fire's Wildland Division said a location with an actual lat/long let crews drive straight to the fire. Otherwise they could spend up to an hour finding it. Xcel's Michelle Aguayo said the company had 28 Pano AI cameras installed. The fire's date is not given.", "replication": { "produced_by": [ "A camera station with a 360-degree view covering a campsite near housing", "Alerts routed to the local fire district with a lat/long", "A fire district willing to respond to AI alerts despite earlier false alarms" ], "must_hold": [ "Camera coverage of the ignition", "Crew availability to reach the location quickly", "Fire conditions that allow a small crew to contain a sub-acre fire" ], "echoes": [ { "date": "2024-06-16", "setting": "Bear Creek Fire, Douglas County, Colorado; Xcel and CORE Electric Pano AI cameras", "outcome": "recurred", "source": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0241", "title": "Waymo rider-only miles show 100% fewer bodily-injury and 76% fewer property-damage liability claims than zip-code-matched human drivers in Swiss Re claims data", "summary": "Heliyon (14 July 2024, Swiss Re and Waymo authors): Waymo liability claims benchmarked against 600,000+ Swiss Re claims; a Dec 2024 25.3M-mile update reports 88%/92% reductions.", "date_observed": "2024-07-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The peer-reviewed Heliyon paper (vol. 10, issue 14, e34379) was received 25 April 2024, accepted 9 July 2024 and published 14 July 2024. Luigi Di Lillo, Xilin Zhou and Margherita Atzei (Swiss Reinsurance Company) and Tilia Gode, Ruoshu Chen and Trent Victor (Waymo LLC) wrote it. They built a human-driver baseline from over 600,000 Swiss Re property-damage and bodily-injury liability claims and 125 billion miles of exposure (claims 2016–2021). It was calibrated to Waymo One's service-area zip codes in San Francisco and Phoenix. They compared it with Waymo claims from 1 January 2018 to 1 August 2023. Over 3,868,506 rider-only miles (no human behind the wheel) Waymo had zero bodily-injury claims against a baseline of 1.11 per million miles. Property-damage claims were 0.78 per million miles against 3.26, a 76% reduction. Both differences had non-overlapping 95% confidence intervals. A follow-up paper (Di Lillo, Gode, Zhou, Scanlon, Chen, Victor; not peer-reviewed) appeared on Waymo's site on 19 December 2024. It extended the data to 25.3 million fully autonomous miles (1 January 2018 to 31 July 2024) in San Francisco, Phoenix, Los Angeles and Austin. It reported 88% fewer property-damage and 92% fewer bodily-injury claims against the overall driving population (two bodily-injury claims observed against 26 expected). Against 2018–2021 model-year vehicles they were 86% and 90%. The authors note the baseline cannot exclude freeway miles and uses the insured's registered zip code rather than the collision location. The data cover the periods above.", "category": "general benefit", "unexpected": false, "purpose": "The Waymo Driver is built to provide driverless ride-hailing. The studies were designed to measure its liability-claim frequency against human drivers.", "system": "Waymo Driver (SAE Level 4 automated driving system) operating the Waymo One ride-hailing service", "model_version": null, "developer": "Waymo LLC", "deployer": "Waymo LLC (Waymo One in Phoenix and San Francisco; later Los Angeles and Austin)", "location": null, "domain": "Road vehicle crash avoidance", "segment": "Automated driving systems / ride-hailing", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Aggregate claim-frequency comparison; no individually attributable outcome is documented." }, { "group": "organizational", "depth": null, "reason": "Fewer liability claims are reported in aggregate only." }, { "group": "personal", "depth": null, "reason": "No individual beneficiary is documented." } ], "ai_role": { "status": "assessed", "statement": "The ADS drove all rider-only miles. Claims were adjudicated by Waymo's claims administrator. The anonymized data were reviewed by Swiss Re, which built the human baseline from its own portfolio. The comparison is observational (different drivers, roads and reporting pathways). The rider-only sample in the peer-reviewed paper is 3.9 million miles, and Waymo authors co-wrote both papers." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Di Lillo L, Gode T, Zhou X, Atzei M, Chen R, Victor T (2024). Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver. Heliyon 10(14): e34379.", "title": "Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver", "url": "https://doi.org/10.1016/j.heliyon.2024.e34379", "date": "2024-07-14", "written_by": "makers", "quote": "While driving without a human behind the steering wheel in RO mode for 3,868,506 miles, the Waymo Driver reduced bodily injury claims frequency by 100 %" }, { "kind": "preprint", "citation": "Di Lillo L, Gode T, Zhou X, Scanlon JM, Chen R, Victor T (2024). Do Autonomous Vehicles Outperform Latest-Generation Human-Driven Vehicles? A Comparison to Waymo's Auto Liability Insurance Claims at 25 Million Miles. PDF hosted by Waymo.", "title": "Do Autonomous Vehicles Outperform Latest-Generation Human-Driven Vehicles? A Comparison to Waymo's Auto Liability Insurance Claims at 25 Million Miles", "url": "https://storage.googleapis.com/waymo-uploads/files/documents/safety/Comparison%20of%20Waymo%20and%20Human-Driven%20Vehicles%20at%2025M%20miles.pdf", "date": "2024-12-19", "written_by": "makers", "quote": "Compared to the overall driving population there was an 88% reduction in property damage claims and a 92% reduction in bodily injury claims." }, { "kind": "press release", "citation": "Waymo (19 Dec 2024). New Swiss Re study: Waymo is safer than even the most advanced human-driven vehicles. Waymo blog.", "title": "New Swiss Re study: Waymo is safer than even the most advanced human-driven vehicles", "url": "https://waymo.com/blog/2024/12/new-swiss-re-study-waymo", "date": "2024-12-19", "written_by": "makers", "quote": "the Waymo Driver demonstrated better safety performance when compared to human-driven vehicles, with an 88% reduction in property damage claims and 92% reduction in bodily injury claims." }, { "kind": "peer-reviewed study", "citation": "Kusano KD, Scanlon JM, Chen YH, McMurry TL, Gode T, Victor T (2025). Comparison of Waymo Rider-Only crash rates by crash type to human benchmarks at 56.7 million miles. Traffic Injury Prevention 26(sup1).", "title": "Comparison of Waymo Rider-Only crash rates by crash type to human benchmarks at 56.7 million miles", "url": "https://doi.org/10.1080/15389588.2025.2499887", "date": "2025-05-16", "written_by": "makers", "quote": "Data were examined over 56.7 million RO miles through the end of January 2025" }, { "kind": "peer-reviewed study", "citation": "Di Lillo L, Gode T, Zhou X, Atzei M, Chen R, Victor T (2024). Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver. Heliyon 10(14): e34379 (PMC11305169, full text via Europe PMC).", "title": "Comparative safety performance of autonomous- and human drivers: A real-world case study of the Waymo Driver", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11305169/fullTextXML", "date": "2024-07-14", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Geofenced, mostly non-freeway urban service areas in Phoenix and San Francisco", "Liability claims adjudicated under state negligence law and reported for any incident regardless of automation level", "A human baseline calibrated by zip code of the insured and by mileage exposure", "Rider-only operation with no human in the driver's seat" ], "must_hold": [ "Access to an insurer's claims portfolio for the same zip codes and years", "Comparable claim-reporting thresholds for ADS and human drivers", "Sufficient autonomous mileage for non-overlapping confidence intervals", "Operational design domain similar to the baseline's road mix" ], "echoes": [ { "date": "2024-12-19", "setting": "Same method extended to 25.3 million rider-only miles (1 January 2018 to 31 July 2024) in San Francisco, Phoenix, Los Angeles and Austin; 88%/92% reductions versus the overall driving population", "model_version": null, "outcome": "recurred", "source": "https://storage.googleapis.com/waymo-uploads/files/documents/safety/Comparison%20of%20Waymo%20and%20Human-Driven%20Vehicles%20at%2025M%20miles.pdf" }, { "date": "2025-05-16", "setting": "Police-reported crash benchmarks instead of claims: 56.7 million rider-only miles through January 2025; statistically lower any-injury, airbag-deployment and suspected-serious-injury crash rates (Waymo authors, peer-reviewed)", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1080/15389588.2025.2499887" }, { "date": "2026-08-28", "setting": "127 million autonomous miles through September 2025 compared by time of day and day of week in Maricopa, San Francisco, Los Angeles and Travis counties; lower any-injury and airbag-deployment involvement rates in all periods (Waymo authors, peer-reviewed)", "model_version": null, "outcome": "recurred", "source": "https://doi.org/10.1080/15389588.2026.2695421" } ] }, "paired_incident": null, "headline": "Waymo has zero bodily-injury, 76% fewer property-damage claims", "metric": "0.78 property-damage claims per million miles against 3.26, a 76% reduction", "comparator": { "against": "zip code-calibrated human-driver baseline built from Swiss Re liability claims", "before": "1.11 claims per million miles (bodily injury); 3.26 claims per million miles (property damage)", "after": "0.00 claims per million miles (bodily injury); 0.78 claims per million miles (property damage)", "basis": "measured", "quote": "Property damage claims frequency was significantly reduced by 76 % (0.78 vs 3.26 claims per million miles), RO_PD 95 % CI [0.16, 2.27], Baseline 95 % CI [3.24, 3.27]", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11305169/fullTextXML" }, "later": { "status": "persisted", "date": "2024-12-19", "note": "A follow-up with Swiss Re over 25.3 million rider-only miles reported 88% fewer property-damage and 92% fewer bodily-injury claims than the overall driving population, and a May 2025 peer-reviewed study over 56.7 million miles found statistically lower crash rates across injury outcomes.", "quote": "Compared to the overall driving population there was an 88% reduction in property damage claims and a 92% reduction in bodily injury claims. The overall driving population benchmark was expected to have 78 property damage and 26 bodily injury claims.", "url": "https://storage.googleapis.com/waymo-uploads/files/documents/safety/Comparison%20of%20Waymo%20and%20Human-Driven%20Vehicles%20at%2025M%20miles.pdf" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11305169/fullTextXML; https://storage.googleapis.com/waymo-uploads/files/documents/safety/Comparison%20of%20Waymo%20and%20Human-Driven%20Vehicles%20at%2025M%20miles.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Waymo; https://en.wikipedia.org/wiki/Waymo", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: three peer-reviewed studies from the makers, the makers' preprint and the makers' press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0241", "catalog_version": "1.0.0", "source_fingerprint": "cefe9a749184ed467040e09d31c277002d5dceeda37ac994eb88a6a3d9e37a6f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0241-source-0001", "AIBD-0241-source-0002", "AIBD-0241-source-0003", "AIBD-0241-source-0004", "AIBD-0241-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Waymo LLC", "deployer": "Waymo LLC (Waymo One in Phoenix and San Francisco; later Los Angeles and Austin)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ADS drove all rider-only miles. Claims were adjudicated by Waymo's claims administrator. The anonymized data were reviewed by Swiss Re, which built the human baseline from its own portfolio. The comparison is observational (different drivers, roads and reporting pathways). The rider-only sample in the peer-reviewed paper is 3.9 million miles, and Waymo authors co-wrote both papers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The ADS drove all rider-only miles. Claims were adjudicated by Waymo's claims administrator. The anonymized data were reviewed by Swiss Re, which built the human baseline from its own portfolio. The comparison is observational (different drivers, roads and reporting pathways). The rider-only sample in the peer-reviewed paper is 3.9 million miles, and Waymo authors co-wrote both papers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: three peer-reviewed studies from the makers, the makers' preprint and the makers' press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Aggregate claim-frequency comparison; no individually attributable outcome is documented." }, { "group": "organizational", "reason": "Fewer liability claims are reported in aggregate only." }, { "group": "personal", "reason": "No individual beneficiary is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not 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"state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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"state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "0.78 property-damage claims per million miles against 3.26, a 76% reduction", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, 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Luigi Di Lillo, Xilin Zhou and Margherita Atzei (Swiss Reinsurance Company) and Tilia Gode, Ruoshu Chen and Trent Victor (Waymo LLC) wrote it. They built a human-driver baseline from over 600,000 Swiss Re property-damage and bodily-injury liability claims and 125 billion miles of exposure (claims 2016–2021). It was calibrated to Waymo One's service-area zip codes in San Francisco and Phoenix. They compared it with Waymo claims from 1 January 2018 to 1 August 2023. Over 3,868,506 rider-only miles (no human behind the wheel) Waymo had zero bodily-injury claims against a baseline of 1.11 per million miles. Property-damage claims were 0.78 per million miles against 3.26, a 76% reduction. Both differences had non-overlapping 95% confidence intervals. A follow-up paper (Di Lillo, Gode, Zhou, Scanlon, Chen, Victor; not peer-reviewed) appeared on Waymo's site on 19 December 2024. It extended the data to 25.3 million fully autonomous miles (1 January 2018 to 31 July 2024) in San Francisco, Phoenix, Los Angeles and Austin. It reported 88% fewer property-damage and 92% fewer bodily-injury claims against the overall driving population (two bodily-injury claims observed against 26 expected). Against 2018–2021 model-year vehicles they were 86% and 90%. The authors note the baseline cannot exclude freeway miles and uses the insured's registered zip code rather than the collision location. The data cover the periods above." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Waymo Driver (SAE Level 4 automated driving system) operating the Waymo One ride-hailing service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Waymo LLC" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Waymo rider-only miles show 100% fewer bodily-injury and 76% fewer property-damage liability claims than zip-code-matched human drivers in Swiss Re claims data", "headline": "Waymo has zero bodily-injury, 76% fewer property-damage claims" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cefe9a749184ed467040e09d31c277002d5dceeda37ac994eb88a6a3d9e37a6f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The peer-reviewed Heliyon paper (vol. 10, issue 14, e34379) was received 25 April 2024, accepted 9 July 2024 and published 14 July 2024. Luigi Di Lillo, Xilin Zhou and Margherita Atzei (Swiss Reinsurance Company) and Tilia Gode, Ruoshu Chen and Trent Victor (Waymo LLC) wrote it. They built a human-driver baseline from over 600,000 Swiss Re property-damage and bodily-injury liability claims and 125 billion miles of exposure (claims 2016–2021). It was calibrated to Waymo One's service-area zip codes in San Francisco and Phoenix. They compared it with Waymo claims from 1 January 2018 to 1 August 2023. Over 3,868,506 rider-only miles (no human behind the wheel) Waymo had zero bodily-injury claims against a baseline of 1.11 per million miles. Property-damage claims were 0.78 per million miles against 3.26, a 76% reduction. Both differences had non-overlapping 95% confidence intervals. A follow-up paper (Di Lillo, Gode, Zhou, Scanlon, Chen, Victor; not peer-reviewed) appeared on Waymo's site on 19 December 2024. It extended the data to 25.3 million fully autonomous miles (1 January 2018 to 31 July 2024) in San Francisco, Phoenix, Los Angeles and Austin. It reported 88% fewer property-damage and 92% fewer bodily-injury claims against the overall driving population (two bodily-injury claims observed against 26 expected). Against 2018–2021 model-year vehicles they were 86% and 90%. The authors note the baseline cannot exclude freeway miles and uses the insured's registered zip code rather than the collision location. The data cover the periods above.", "replication": { "produced_by": [ "Geofenced, mostly non-freeway urban service areas in Phoenix and San Francisco", "Liability claims adjudicated under state negligence law and reported for any incident regardless of automation level", "A human baseline calibrated by zip code of the insured and by mileage exposure", "Rider-only operation with no human in the driver's seat" ], "must_hold": [ "Access to an insurer's claims portfolio for the same zip codes and years", "Comparable claim-reporting thresholds for ADS and human drivers", "Sufficient autonomous mileage for non-overlapping confidence intervals", "Operational design domain similar to the baseline's road mix" ], "echoes": [ { "date": "2024-12-19", "setting": "Same method extended to 25.3 million rider-only miles (1 January 2018 to 31 July 2024) in San Francisco, Phoenix, Los Angeles and Austin; 88%/92% reductions versus the overall driving population", "outcome": "recurred", "source": "https://storage.googleapis.com/waymo-uploads/files/documents/safety/Comparison%20of%20Waymo%20and%20Human-Driven%20Vehicles%20at%2025M%20miles.pdf" }, { "date": "2025-05-16", "setting": "Police-reported crash benchmarks instead of claims: 56.7 million rider-only miles through January 2025; statistically lower any-injury, airbag-deployment and suspected-serious-injury crash rates (Waymo authors, peer-reviewed)", "outcome": "recurred", "source": "https://doi.org/10.1080/15389588.2025.2499887" }, { "date": "2026-08-28", "setting": "127 million autonomous miles through September 2025 compared by time of day and day of week in Maricopa, San Francisco, Los Angeles and Travis counties; lower any-injury and airbag-deployment involvement rates in all periods (Waymo authors, peer-reviewed)", "outcome": "recurred", "source": "https://doi.org/10.1080/15389588.2026.2695421" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0293", "title": "Oura ring heart-rate and HRV trends inform a stress test and Holter that document frequent PVCs in a diabetic man in his early 40s; the ring raised no alert", "summary": "Dubai clinic case: Oura ring heart-rate and HRV summaries, read by clinicians, fed into a stress test and Holter showing 2,078 PVCs in 24 h; the ring detects no arrhythmia and issued no alert.", "date_observed": "2024-07-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Zakaria, Roman, Almarzooqi and Hashemi of GluCare.Health, Dubai, reported a case in Cureus (16 June 2025). A man in his early 40s had type 2 diabetes and a smoking history. He had been issued an ŌURA ring under the clinic's hybrid care model. He attended for cardiac risk assessment before half-marathon training. Per the paper, testing followed his risk profile, “which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring”. The treadmill stress test on 18 July 2024, the date the cardiologist made the diagnosis, showed frequent PVCs in bigeminy and abnormal heart-rate recovery. The team then reviewed the ring's previous two weeks of data retrospectively and found a persistently elevated daytime heart rate and a downward HRV trend. A 24-hour Holter recorded 2,078 ventricular events (1.75% of beats, no couplets or runs). The PVCs were judged idiopathic, of right ventricular outflow tract origin. Management was non-pharmacological (stop smoking, cut caffeine from over five cups of coffee a day, stress reduction). A 12-lead electrocardiogram (ECG) three days later showed no PVCs. Follow-up ring data showed resting heart rate falling from 83 to 74 bpm and RMSSD rising from 15.2 to 32.8 ms over two months. The authors say this supported deferring drug therapy. The paper states that the ring “does not detect arrhythmias like PVCs” and that data review “was conducted retrospectively”. It describes no alert and no machine-learning component. It is inconsistent on sequence. The case presentation says the stress-test findings prompted the retrospective ring review. The data-analysis section says the ring data “raised clinical suspicion and prompted further evaluation through ECG and Holter monitoring”.", "category": "benefit created", "unexpected": false, "purpose": "The ring tracks heart rate, HRV and sleep for consumers. The clinic used those daily summaries as remote-monitoring markers in its diabetes program. The paper does not claim the ring was built to find arrhythmias.", "system": "ŌURA ring (heart-rate and heart-rate-variability summaries) used within GluCare.Health's hybrid care model", "model_version": null, "developer": "Maker of the ŌURA ring (company not named in the paper)", "deployer": "GluCare.Health, Dubai", "location": "Dubai, United Arab Emirates", "domain": "Healthcare (cardiology; diabetes care)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "One asymptomatic man had a low PVC burden (1.75%) characterized, judged benign, and managed with lifestyle change. The report documents no drug or procedure. The ring's share in prompting the work-up is stated inconsistently within the paper." } ], "ai_role": { "status": "assessed", "statement": "The ring generated no alert and, per the paper, cannot detect PVCs. Clinicians read its heart-rate and HRV summaries twice. Once was before the stress test (an elevated resting heart rate seen in remote monitoring is listed among the reasons for testing). Once was retrospectively afterwards. The ECG, stress test and Holter made the diagnosis. The paper describes no machine-learning component, so whether an AI system was involved is not shown by the source text. The only source is the treating clinic's case report." }, "evidence": [ { "kind": "case report", "citation": "Zakaria H, Roman I, Almarzooqi I, Hashemi A (2025). Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring. Cureus 17(6):e86174 (PMC12268106).", "title": "Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "While the ŌURA ring does not detect arrhythmias like PVCs, it supplies surrogate physiological markers, such as heart rate and HRV, that can support early clinical insight" }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, abstract (on the timing of the data review).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "The patient wore an ŌURA ring before, during, and after a treadmill stress test; however, data review was conducted retrospectively." }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, ECG section (on why the stress test was ordered).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "a treadmill stress test was pursued due to his high-risk profile, which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring" } ], "replication": { "produced_by": [ "Continuous ring wear under a clinic hybrid care model in which staff review daily synced heart-rate and HRV summaries", "Risk factors (type 2 diabetes, smoking) that led to a treadmill stress test", "Access to ECG, 24-hour Holter and echocardiography to confirm and characterize the PVCs" ], "must_hold": [ "Clinicians act on wearable trend deviations. The clinic later wrote thresholds into its workflow (an RMSSD drop of more than 30% or a resting heart rate above 110 bpm prompts review)", "The patient keeps wearing and syncing the ring so that trends can be compared with a baseline" ], "echoes": [] }, "paired_incident": null, "headline": "Oura ring trends feed into a Holter showing 2,078 PVCs in 24 h", "metric": "a 24-hour Holter recorded 2,078 ventricular events (1.75% of beats, no couplets or runs)", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The paper's own two-month and four-month follow-up (resting heart rate 83 to 74 bpm, RMSSD 15.2 to 32.8 ms) belongs to the first report; nothing published after it was found.", "quote": null, "url": null }, "value": null, "developer_country": "Finland", "deployer_country": "United Arab Emirates", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ouraring.com/about-us; https://metabolic.health/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0293", "catalog_version": "1.0.0", "source_fingerprint": "d3b952e1827d533843bd541c633002a98a2acd8aef57b333f5f380db633c8b83", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0293-source-0001", "AIBD-0293-source-0002", "AIBD-0293-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Maker of the ŌURA ring (company not named in the paper)", "deployer": "GluCare.Health, Dubai" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The ring generated no alert and, per the paper, cannot detect PVCs. Clinicians read its heart-rate and HRV summaries twice. Once was before the stress test (an elevated resting heart rate seen in remote monitoring is listed among the reasons for testing). Once was retrospectively afterwards. The ECG, stress test and Holter made the diagnosis. The paper describes no machine-learning component, so whether an AI system was involved is not shown by the source text. The only source is the treating clinic's case report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The ring generated no alert and, per the paper, cannot detect PVCs. Clinicians read its heart-rate and HRV summaries twice. Once was before the stress test (an elevated resting heart rate seen in remote monitoring is listed among the reasons for testing). Once was retrospectively afterwards. The ECG, stress test and Holter made the diagnosis. The paper describes no machine-learning component, so whether an AI system was involved is not shown by the source text. The only source is the treating clinic's case report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One asymptomatic man had a low PVC burden (1.75%) characterized, judged benign, and managed with lifestyle change. The report documents no drug or procedure. The ring's share in prompting the work-up is stated inconsistently within the paper." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One asymptomatic man had a low PVC burden (1.75%) characterized, judged benign, and managed with lifestyle change. The report documents no drug or procedure. The ring's share in prompting the work-up is stated inconsistently within the paper." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One asymptomatic man had a low PVC burden (1.75%) characterized, judged benign, and managed with lifestyle change. The report documents no drug or procedure. The ring's share in prompting the work-up is stated inconsistently within the paper." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Zakaria, Roman, Almarzooqi and Hashemi of GluCare.Health, Dubai, reported a case in Cureus (16 June 2025). A man in his early 40s had type 2 diabetes and a smoking history. He had been issued an ŌURA ring under the clinic's hybrid care model. He attended for cardiac risk assessment before half-marathon training. Per the paper, testing followed his risk profile, “which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring”. The treadmill stress test on 18 July 2024, the date the cardiologist made the diagnosis, showed frequent PVCs in bigeminy and abnormal heart-rate recovery. The team then reviewed the ring's previous two weeks of data retrospectively and found a persistently elevated daytime heart rate and a downward HRV trend. A 24-hour Holter recorded 2,078 ventricular events (1.75% of beats, no couplets or runs). The PVCs were judged idiopathic, of right ventricular outflow tract origin. Management was non-pharmacological (stop smoking, cut caffeine from over five cups of coffee a day, stress reduction). A 12-lead electrocardiogram (ECG) three days later showed no PVCs. Follow-up ring data showed resting heart rate falling from 83 to 74 bpm and RMSSD rising from 15.2 to 32.8 ms over two months. The authors say this supported deferring drug therapy. The paper states that the ring “does not detect arrhythmias like PVCs” and that data review “was conducted retrospectively”. It describes no alert and no machine-learning component. It is inconsistent on sequence. The case presentation says the stress-test findings prompted the retrospective ring review. The data-analysis section says the ring data “raised clinical suspicion and prompted further evaluation through ECG and Holter monitoring”.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "One asymptomatic man had a low PVC burden (1.75%) characterized, judged benign, and managed with lifestyle change. The report documents no drug or procedure. The ring's share in prompting the work-up is stated inconsistently within the paper." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The ring tracks heart rate, HRV and sleep for consumers. The clinic used those daily summaries as remote-monitoring markers in its diabetes program. The paper does not claim the ring was built to find arrhythmias." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Dubai, United Arab Emirates", "developer_country": "Finland", "deployer_country": "United Arab Emirates" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The ring tracks heart rate, HRV and sleep for consumers. The clinic used those daily summaries as remote-monitoring markers in its diabetes program. The paper does not claim the ring was built to find arrhythmias." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-07-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ouraring.com/about-us; https://metabolic.health/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Continuous ring wear under a clinic hybrid care model in which staff review daily synced heart-rate and HRV summaries", "Risk factors (type 2 diabetes, smoking) that led to a treadmill stress test", "Access to ECG, 24-hour Holter and echocardiography to confirm and characterize the PVCs" ], "must_hold": [ "Clinicians act on wearable trend deviations. The clinic later wrote thresholds into its workflow (an RMSSD drop of more than 30% or a resting heart rate above 110 bpm prompts review)", "The patient keeps wearing and syncing the ring so that trends can be compared with a baseline" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://ouraring.com/about-us; https://metabolic.health/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; diabetes care)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Zakaria H, Roman I, Almarzooqi I, Hashemi A (2025). Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring. Cureus 17(6):e86174 (PMC12268106).", "title": "Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "While the ŌURA ring does not detect arrhythmias like PVCs, it supplies surrogate physiological markers, such as heart rate and HRV, that can support early clinical insight" }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, abstract (on the timing of the data review).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "The patient wore an ŌURA ring before, during, and after a treadmill stress test; however, data review was conducted retrospectively." }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, ECG section (on why the stress test was ordered).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "a treadmill stress test was pursued due to his high-risk profile, which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0293-source-0001", "AIBD-0293-source-0002", "AIBD-0293-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Zakaria H, Roman I, Almarzooqi I, Hashemi A (2025). Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring. Cureus 17(6):e86174 (PMC12268106).", "title": "Integrating Wearables Into a Hybrid Care Model: Continuous Remote Monitoring of a Diabetic Patient With Frequent Premature Ventricular Contractions Using an ŌURA Ring", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "While the ŌURA ring does not detect arrhythmias like PVCs, it supplies surrogate physiological markers, such as heart rate and HRV, that can support early clinical insight" }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, abstract (on the timing of the data review).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "The patient wore an ŌURA ring before, during, and after a treadmill stress test; however, data review was conducted retrospectively." }, { "kind": "case report", "citation": "Zakaria et al. (2025), Cureus 17(6):e86174, ECG section (on why the stress test was ordered).", "title": "Integrating Wearables Into a Hybrid Care Model", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12268106/", "date": "2025-06-16", "written_by": "deployer", "quote": "a treadmill stress test was pursued due to his high-risk profile, which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Dubai clinic case: Oura ring heart-rate and HRV summaries, read by clinicians, fed into a stress test and Holter showing 2,078 PVCs in 24 h; the ring detects no arrhythmia and issued no alert.", "account": "Zakaria, Roman, Almarzooqi and Hashemi of GluCare.Health, Dubai, reported a case in Cureus (16 June 2025). A man in his early 40s had type 2 diabetes and a smoking history. He had been issued an ŌURA ring under the clinic's hybrid care model. He attended for cardiac risk assessment before half-marathon training. Per the paper, testing followed his risk profile, “which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring”. The treadmill stress test on 18 July 2024, the date the cardiologist made the diagnosis, showed frequent PVCs in bigeminy and abnormal heart-rate recovery. The team then reviewed the ring's previous two weeks of data retrospectively and found a persistently elevated daytime heart rate and a downward HRV trend. A 24-hour Holter recorded 2,078 ventricular events (1.75% of beats, no couplets or runs). The PVCs were judged idiopathic, of right ventricular outflow tract origin. Management was non-pharmacological (stop smoking, cut caffeine from over five cups of coffee a day, stress reduction). A 12-lead electrocardiogram (ECG) three days later showed no PVCs. Follow-up ring data showed resting heart rate falling from 83 to 74 bpm and RMSSD rising from 15.2 to 32.8 ms over two months. The authors say this supported deferring drug therapy. The paper states that the ring “does not detect arrhythmias like PVCs” and that data review “was conducted retrospectively”. It describes no alert and no machine-learning component. It is inconsistent on sequence. The case presentation says the stress-test findings prompted the retrospective ring review. The data-analysis section says the ring data “raised clinical suspicion and prompted further evaluation through ECG and Holter monitoring”." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ŌURA ring (heart-rate and heart-rate-variability summaries) used within GluCare.Health's hybrid care model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Maker of the ŌURA ring (company not named in the paper)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Oura ring heart-rate and HRV trends inform a stress test and Holter that document frequent PVCs in a diabetic man in his early 40s; the ring raised no alert", "headline": "Oura ring trends feed into a Holter showing 2,078 PVCs in 24 h" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d3b952e1827d533843bd541c633002a98a2acd8aef57b333f5f380db633c8b83" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Zakaria, Roman, Almarzooqi and Hashemi of GluCare.Health, Dubai, reported a case in Cureus (16 June 2025). A man in his early 40s had type 2 diabetes and a smoking history. He had been issued an ŌURA ring under the clinic's hybrid care model. He attended for cardiac risk assessment before half-marathon training. Per the paper, testing followed his risk profile, “which included poorly controlled diabetes and an elevated resting heart rate observed during wearable-based remote monitoring”. The treadmill stress test on 18 July 2024, the date the cardiologist made the diagnosis, showed frequent PVCs in bigeminy and abnormal heart-rate recovery. The team then reviewed the ring's previous two weeks of data retrospectively and found a persistently elevated daytime heart rate and a downward HRV trend. A 24-hour Holter recorded 2,078 ventricular events (1.75% of beats, no couplets or runs). The PVCs were judged idiopathic, of right ventricular outflow tract origin. Management was non-pharmacological (stop smoking, cut caffeine from over five cups of coffee a day, stress reduction). A 12-lead electrocardiogram (ECG) three days later showed no PVCs. Follow-up ring data showed resting heart rate falling from 83 to 74 bpm and RMSSD rising from 15.2 to 32.8 ms over two months. The authors say this supported deferring drug therapy. The paper states that the ring “does not detect arrhythmias like PVCs” and that data review “was conducted retrospectively”. It describes no alert and no machine-learning component. It is inconsistent on sequence. The case presentation says the stress-test findings prompted the retrospective ring review. The data-analysis section says the ring data “raised clinical suspicion and prompted further evaluation through ECG and Holter monitoring”.", "replication": { "produced_by": [ "Continuous ring wear under a clinic hybrid care model in which staff review daily synced heart-rate and HRV summaries", "Risk factors (type 2 diabetes, smoking) that led to a treadmill stress test", "Access to ECG, 24-hour Holter and echocardiography to confirm and characterize the PVCs" ], "must_hold": [ "Clinicians act on wearable trend deviations. The clinic later wrote thresholds into its workflow (an RMSSD drop of more than 30% or a resting heart rate above 110 bpm prompts review)", "The patient keeps wearing and syncing the ring so that trends can be compared with a baseline" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0040", "title": "Rep. Jennifer Wexton addresses the House with an AI clone of her own voice after progressive supranuclear palsy took her speech", "summary": "Rep. Jennifer Wexton, who lost her speech to PSP, addressed the House on 25 July 2024 with an ElevenLabs clone of her own voice.", "date_observed": "2024-07-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 25 July 2024, Representative Jennifer Wexton of Virginia gave a House floor speech for Disability Pride Month. She was diagnosed in 2023 with progressive supranuclear palsy. She used an augmentative and alternative communication device playing an AI-generated clone of her voice. The Associated Press reported that ElevenLabs built the voice from recordings of her congressional speeches and public appearances. The Congressional Record has her saying that PSP “has robbed me of my ability to use my full voice”. She said hearing the recreation was “the most beautiful thing I had ever heard, and I cried tears of joy”. The Office of the House Historian states she was the first Member to speak on the House floor using this type of assistive technology.", "category": "benefit created", "unexpected": false, "purpose": "ElevenLabs voice cloning is built to reproduce a person's voice from recordings. Restoring her own voice for speech was that purpose.", "system": "ElevenLabs AI voice clone played through an augmentative and alternative communication device", "model_version": null, "developer": "ElevenLabs", "deployer": "Office of Rep. Jennifer Wexton", "location": "Washington, D.C., United States", "domain": "Accessibility / government", "segment": "Speech loss from neurodegenerative disease", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "A legislator who lost intelligible speech regained the ability to address the House in a voice recognizably her own. 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Finding Her Voice - The Honorable Jennifer Wexton of Virginia Oral History.", "title": "Finding Her Voice - The Honorable Jennifer Wexton of Virginia Oral History", "url": "https://history.house.gov/Blog/2026/March/3-27-OralHistory-Wexton/", "date": "2026-03-27", "written_by": "independent", "quote": "Just because my voice is coming from a device rather than me directly, doesn't make it any less mine or any less important to hear." } ], "replication": { "produced_by": [ "A corpus of prior recordings in the person's own voice", "Consent-based cloning by the vendor", "An AAC device and House rules permitting its use on the floor" ], "must_hold": [ "The speaker retains the ability to compose text", "Institutional permission for device use" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "508", "title": "Celebrities' Deepfake Voices Abused with Malicious Intent", "url": "https://incidentdatabase.ai/cite/508", "severity": null, "group": "personal", "basis": "Same developer and task: ElevenLabs synthesizing a public figure's voice; Wexton's consented clone restored her House speech, while 4chan and Reddit users cloned celebrities' and public figures' voices to impersonate and defame them." }, "headline": "Wexton addresses the House with an ElevenLabs clone of her voice", "metric": null, "comparator": { "against": "a traditional text-to-speech app with a generic voice", "before": "The voice sounded more like a robot than a human", "after": "it is more me than I ever could have hoped I could hear again", "basis": "assumed", "quote": "The voice sounded more like a robot than a human, but Wexton used it to conduct interviews and give speeches.", "url": "https://www.pbs.org/newshour/politics/a-neurological-disorder-took-rep-jennifer-wextons-voice-ai-helped-her-bring-it-back-to-the-house-floor" }, "later": { "status": "unknown", "date": null, "note": "No dated later development found; the House Historian page only restates the July 2024 first.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 508 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/508", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Completed the two AP quotes that had been cut mid-sentence (“I cried happy tears when I first heard it” and “more me than I ever could have hoped I could hear again”) and changed the House Historian evidence kind from “report” to “other” because the source is an oral-history blog post, so that every quoted fragment matches the source verbatim.", "source": "Merica D, Associated Press via PBS NewsHour (25 Jul 2024): https://www.pbs.org/newshour/politics/a-neurological-disorder-took-rep-jennifer-wextons-voice-ai-helped-her-bring-it-back-to-the-house-floor", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.pbs.org/newshour/politics/a-neurological-disorder-took-rep-jennifer-wextons-voice-ai-helped-her-bring-it-back-to-the-house-floor", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://elevenlabs.io/terms-of-use; https://en.wikipedia.org/wiki/Jennifer_Wexton", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, one independent press release and the beneficiary's other. 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Finding Her Voice - The Honorable Jennifer Wexton of Virginia Oral History.", "title": "Finding Her Voice - The Honorable Jennifer Wexton of Virginia Oral History", "url": "https://history.house.gov/Blog/2026/March/3-27-OralHistory-Wexton/", "date": "2026-03-27", "written_by": "independent", "quote": "Just because my voice is coming from a device rather than me directly, doesn't make it any less mine or any less important to hear." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0040-source-0001", "AIBD-0040-source-0002", "AIBD-0040-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Merica D, Associated Press via PBS NewsHour (25 Jul 2024). 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Jennifer Wexton, who lost her speech to PSP, addressed the House on 25 July 2024 with an ElevenLabs clone of her own voice.", "account": "On 25 July 2024, Representative Jennifer Wexton of Virginia gave a House floor speech for Disability Pride Month. She was diagnosed in 2023 with progressive supranuclear palsy. She used an augmentative and alternative communication device playing an AI-generated clone of her voice. The Associated Press reported that ElevenLabs built the voice from recordings of her congressional speeches and public appearances. The Congressional Record has her saying that PSP “has robbed me of my ability to use my full voice”. She said hearing the recreation was “the most beautiful thing I had ever heard, and I cried tears of joy”. The Office of the House Historian states she was the first Member to speak on the House floor using this type of assistive technology." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ElevenLabs AI voice clone played through an augmentative and alternative communication device" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ElevenLabs" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rep. Jennifer Wexton addresses the House with an AI clone of her own voice after progressive supranuclear palsy took her speech", "headline": "Wexton addresses the House with an ElevenLabs clone of her voice" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "16edf7f08728ce5f9a4dd3b49ae4e62bf9445e487a3fd4480cce9b7b1bcfeb2e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 25 July 2024, Representative Jennifer Wexton of Virginia gave a House floor speech for Disability Pride Month. She was diagnosed in 2023 with progressive supranuclear palsy. She used an augmentative and alternative communication device playing an AI-generated clone of her voice. The Associated Press reported that ElevenLabs built the voice from recordings of her congressional speeches and public appearances. The Congressional Record has her saying that PSP “has robbed me of my ability to use my full voice”. She said hearing the recreation was “the most beautiful thing I had ever heard, and I cried tears of joy”. The Office of the House Historian states she was the first Member to speak on the House floor using this type of assistive technology.", "replication": { "produced_by": [ "A corpus of prior recordings in the person's own voice", "Consent-based cloning by the vendor", "An AAC device and House rules permitting its use on the floor" ], "must_hold": [ "The speaker retains the ability to compose text", "Institutional permission for device use" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0070", "title": "AlphaProof and AlphaGeometry 2 reach silver-medal standard on IMO 2024 problems, graded by two IMO gold medallists; IMO-certified gold follows in 2025", "summary": "DeepMind AI scored 28/42 on IMO 2024 problems, graded by Gowers and Myers; Gemini Deep Think's 35/42 in 2025 was IMO-certified gold", "date_observed": "2024-07-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Google DeepMind's AlphaProof (reinforcement learning over the Lean proof language) and AlphaGeometry 2 produced solutions to four of the six 2024 International Mathematical Olympiad problems. Because the systems work in formal language, the problems were first translated manually into Lean. One problem was solved within minutes and others took up to three days, longer than the contest allows. Two former IMO gold medalists, Sir Timothy Gowers and Joseph Myers, graded the solutions under IMO rules. They awarded 28 of 42 points, a silver-medal score. DeepMind announced the result on 25 July 2024 (grading date not given). In July 2025 a Gemini Deep Think model working in natural language within the time limit scored 35 of 42. IMO president Gregor Dolinar confirmed this as a gold-medal score. Nature reported that OpenAI also claimed a gold-level result.", "category": "general benefit", "unexpected": false, "purpose": "Solve competition mathematics problems with machine-checkable formal proofs", "system": "AlphaProof and AlphaGeometry 2", "model_version": "AlphaProof (2024) and AlphaGeometry 2; 2025 echo: advanced Gemini Deep Think", "developer": "DeepMind", "deployer": "DeepMind", "location": null, "domain": "Mathematics competitions", "segment": "Olympiad mathematics", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "A graded competition score is read as task performance; no deployment or user is involved.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "A capability evaluation on IMO 2024 problems for the developer and the IMO community. The sources describe grading and scores, not a deployment or an observed organizational change." }, { "group": "societal", "depth": null, "reason": "Proofs of already-solved contest problems graded correct, with no identifiable beneficiary beyond the research community. Scientific American notes around 60 students scored better in 2024." } ], "ai_role": { "status": "assessed", "statement": "The AI systems produced the proofs. Humans manually formalized the 2024 problem statements into Lean (Scientific American) and graded the output. In 2024 the solutions were graded by two mathematicians at DeepMind's request (one of them, Myers, chaired the IMO 2024 Problem Selection Committee). The result was not officially certified by the IMO. DeepMind states the 2025 result was graded and certified by IMO coordinators, with the IMO president's confirmation appearing in the vendor blog. The cited sources do not state whether OpenAI's 2025 claim was certified by the IMO." }, "evidence": [ { "kind": "news report", "citation": "Bischoff, M. (2024). AI Reaches Silver-Medal Level at This Year's Math Olympiad. Scientific American.", "title": "AI Reaches Silver-Medal Level at This Year's Math Olympiad", "url": "https://www.scientificamerican.com/article/ai-reaches-silver-medal-level-at-this-years-math-olympiad/", "date": "2024-08-06", "written_by": "independent", "quote": "Gowers and mathematician Joseph K. Myers, another previous gold medalist, evaluated the solutions of the two AI systems using the same criteria as was used for the human participants." }, { "kind": "news report", "citation": "Williams, R. (2024). Google DeepMind's new AI systems can now solve complex math problems. MIT Technology Review.", "title": "Google DeepMind's new AI systems can now solve complex math problems", "url": "https://www.technologyreview.com/2024/07/25/1095315/google-deepminds-ai-systems-can-now-solve-complex-math-problems/", "date": "2024-07-25", "written_by": "independent", "quote": "They awarded each of their four correct answers full marks (seven out of seven), giving the systems a total of 28 points out of a maximum of 42." }, { "kind": "news report", "citation": "Castelvecchi, D. (2024). DeepMind hits milestone in solving maths problems — AI's next grand challenge. Nature.", "title": "DeepMind hits milestone in solving maths problems — AI's next grand challenge", "url": "https://www.nature.com/articles/d41586-024-02441-2", "date": "2024-07-25", "written_by": "independent", "quote": "AlphaProof showed its prowess on questions from this year's Mathematical Olympiad — a step in the race to create substantial proofs with artificial intelligence." }, { "kind": "press release", "citation": "Google DeepMind (2024). AI achieves silver-medal standard solving International Mathematical Olympiad problems. Google DeepMind blog.", "title": "AI achieves silver-medal standard solving International Mathematical Olympiad problems", "url": "https://deepmind.google/discover/blog/ai-solves-imo-problems-at-silver-medal-level/", "date": "2024-07-25", "written_by": "makers", "quote": "Our system achieved a final score of 28 points, earning a perfect score on each problem solved" }, { "kind": "news report", "citation": "Castelvecchi, D. (2025). DeepMind and OpenAI models solve maths problems at level of top students. Nature.", "title": "DeepMind and OpenAI models solve maths problems at level of top students", "url": "https://www.nature.com/articles/d41586-025-02343-x", "date": "2025-07-24", "written_by": "independent", "quote": "a gold-medal score on questions from the International Mathematical Olympiad" }, { "kind": "press release", "citation": "Google DeepMind (2025). Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical Olympiad. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "AlphaProof (2024) and AlphaGeometry 2; 2025 echo: advanced Gemini Deep Think" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AlphaProof and AlphaGeometry 2" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AlphaProof and AlphaGeometry 2 reach silver-medal standard on IMO 2024 problems, graded by two IMO gold medallists; IMO-certified gold follows in 2025", "headline": "AlphaProof and AlphaGeometry 2 reach IMO silver-medal standard" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4b78415afdaf96f4a254376344d86945bbf8cf56e8ae0cd1df787a64420515eb" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Google DeepMind's AlphaProof (reinforcement learning over the Lean proof language) and AlphaGeometry 2 produced solutions to four of the six 2024 International Mathematical Olympiad problems. Because the systems work in formal language, the problems were first translated manually into Lean. One problem was solved within minutes and others took up to three days, longer than the contest allows. Two former IMO gold medalists, Sir Timothy Gowers and Joseph Myers, graded the solutions under IMO rules. They awarded 28 of 42 points, a silver-medal score. DeepMind announced the result on 25 July 2024 (grading date not given). In July 2025 a Gemini Deep Think model working in natural language within the time limit scored 35 of 42. IMO president Gregor Dolinar confirmed this as a gold-medal score. Nature reported that OpenAI also claimed a gold-level result.", "replication": { "produced_by": [ "Manual translation of the 2024 problem statements into Lean", "AlphaProof reinforcement-learning proof search and AlphaGeometry 2 for the geometry problem", "Grading under IMO rules by two former IMO gold medalists" ], "must_hold": [ "Each proof is machine-checked in Lean or graded by qualified IMO graders", "Problems are unseen by the system before the contest", "Grading criteria identical to those for human contestants" ], "echoes": [ { "date": "2025-07-21", "setting": "IMO 2025; advanced Gemini Deep Think working end-to-end in natural language within the 4.5-hour limit; 35/42 graded and certified by IMO coordinators per DeepMind, confirmed by IMO president Gregor Dolinar", "model_version": "Gemini Deep Think (advanced version)", "outcome": "recurred", "source": "https://deepmind.google/discover/blog/advanced-version-of-gemini-with-deep-think-officially-achieves-gold-medal-standard-at-the-international-mathematical-olympiad/ ; https://www.nature.com/articles/d41586-025-02343-x" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0086", "title": "Supreme Court of India's SUVAS translation software: 36,271 judgments translated into Hindi and 17,142 into 16 other languages by 5 August 2024", "summary": "SUVAS translated 36,271 Supreme Court judgments into Hindi and 17,142 into 16 languages by 5 August 2024; High Courts report own totals", "date_observed": "2024-08-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "SUVAS (Supreme Court Vidhik Anuvaad Software) is the Supreme Court of India's AI-assisted tool for translating English judgments into Indian languages. A 2025 peer-reviewed article cites Press Information Bureau figures as on 5 August 2024. By then 36,271 Supreme Court judgments were translated into Hindi and 17,142 into 16 other regional languages. The Supreme Court's Annual Report 2024–25 summarizes a judge's address crediting SUVAS with translating over 100,000 judgments into 18 regional languages. It also records High Court translation work. Jammu & Kashmir and Ladakh, which the report says uses SUVAS, translated 4,426 Supreme Court judgments into Urdu. Manipur's AI-Assisted Legal Translation Committee translated 433 Supreme Court judgments into Meetei Mayek, 259 uploaded and 174 under review. The report calls this “AI-assisted translation” without naming the tool. These are aggregates. No single translated judgment with a dated delivery was found.", "category": "general benefit", "unexpected": false, "purpose": "Translate Supreme Court and High Court judgments from English into Indian languages to widen access", "system": "SUVAS (Supreme Court Vidhik Anuvaad Software), AI-assisted legal translation with human verification", "model_version": null, "developer": null, "deployer": "Supreme Court of India; High Courts' SUVAS Cells and AI-assisted translation committees", "location": "New Delhi, India", "domain": "Courts: access to judgments", "segment": "Judicial translation", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "Translation of judgments into Indian languages is read as access to information; it also serves inclusion of non-English readers.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate translation counts; no identifiable beneficiary event." }, { "group": "organizational", "depth": null, "reason": "Court-reported totals rather than a discrete outcome." }, { "group": "societal", "depth": null, "reason": "National aggregate; no evaluation of use or comprehension by litigants." } ], "ai_role": { "status": "unassessed", "statement": "Court documents attribute the translations to SUVAS with human review by translation committees. The sources do not evaluate accuracy or separate machine from human contribution. The PIB release behind the 36,271/17,142 figures is not itself among the sources. So it is cited via the peer-reviewed article that quotes it." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Anbarasi, G. & Sankar, D. (2025). Greening the justice system: assessing the legality, feasibility, and potential of artificial intelligence in advancing environmental sustainability within the Indian judiciary. Frontiers in Political Science. doi:10.3389/fpos.2025.1553705 (citing PIB, 5 Aug 2024).", "title": "Greening the justice system (Frontiers in Political Science)", "url": "https://www.frontiersin.org/journals/political-science/articles/10.3389/fpos.2025.1553705/full", "date": "2025-05-14", "written_by": "independent", "quote": "As on 05.08.2024, 36,271 Supreme Court Judgments have been translated in Hindi language and 17,142 Judgments of Supreme Court have been translated in other 16 regional languages." }, { "kind": "report", "citation": "Supreme Court of India (2025). Indian Judiciary: Annual Report 2024-25, Volume 1 (Supreme Court), printed p. 147 (conference summary, 6 Jun 2025); hosted January 2026.", "title": "Indian Judiciary: Annual Report 2024-25, Volume 1", "url": "https://cdnbbsr.s3waas.gov.in/s3ec0490f1f4972d133619a60c30f3559e/uploads/2026/01/2026011698.pdf", "date": null, "written_by": "deployer", "quote": "SUVAS (Supreme Court Vidhik Anuvaad Software) translating over 100,000 judgments into 18 regional languages" }, { "kind": "report", "citation": "Supreme Court of India (2025). 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https://cdnbbsr.s3waas.gov.in/s3ec0490f1f4972d133619a60c30f3559e/uploads/2026/01/2026011698.pdf; https://www.frontiersin.org/journals/political-science/articles/10.3389/fpos.2025.1553705/full", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Supreme_Court_of_India", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://cdnbbsr.s3waas.gov.in/s3ec0490f1f4972d133619a60c30f3559e/uploads/2026/01/2026011698.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; 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Indian Judiciary: Annual Report 2024-25, Volume 2 (High Courts), High Court of Jammu & Kashmir and Ladakh section, printed p. 135; hosted January 2026.", "title": "Indian Judiciary: Annual Report 2024-25, Volume 2", "url": "https://cdnbbsr.s3waas.gov.in/s3ec0490f1f4972d133619a60c30f3559e/uploads/2026/01/2026010287.pdf", "written_by": "deployer", "quote": "The Supreme Court Vidhik Anuvaad Software (SUVAS) is being effectively utilized to translate judgments into local languages like Urdu, enhancing accessibility for a wider audience. To date, 4,426 Supreme Court judgments and 60 High Court judgments have been translated into vernacular (Urdu) language." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0086-source-0001", "AIBD-0086-source-0002", "AIBD-0086-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Anbarasi, G. & Sankar, D. 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To date, 4,426 Supreme Court judgments and 60 High Court judgments have been translated into vernacular (Urdu) language." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SUVAS translated 36,271 Supreme Court judgments into Hindi and 17,142 into 16 languages by 5 August 2024; High Courts report own totals", "account": "SUVAS (Supreme Court Vidhik Anuvaad Software) is the Supreme Court of India's AI-assisted tool for translating English judgments into Indian languages. 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No single translated judgment with a dated delivery was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SUVAS (Supreme Court Vidhik Anuvaad Software), AI-assisted legal translation with human verification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Supreme Court of India's SUVAS translation software: 36,271 judgments translated into Hindi and 17,142 into 16 other languages by 5 August 2024", "headline": "SUVAS translates 36,271 Supreme Court judgments into Hindi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "674b62b27c5bb134a5fe091820c089a692ff71da641a57446a71dc3235307c76" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "SUVAS (Supreme Court Vidhik Anuvaad Software) is the Supreme Court of India's AI-assisted tool for translating English judgments into Indian languages. A 2025 peer-reviewed article cites Press Information Bureau figures as on 5 August 2024. By then 36,271 Supreme Court judgments were translated into Hindi and 17,142 into 16 other regional languages. The Supreme Court's Annual Report 2024–25 summarizes a judge's address crediting SUVAS with translating over 100,000 judgments into 18 regional languages. It also records High Court translation work. Jammu & Kashmir and Ladakh, which the report says uses SUVAS, translated 4,426 Supreme Court judgments into Urdu. Manipur's AI-Assisted Legal Translation Committee translated 433 Supreme Court judgments into Meetei Mayek, 259 uploaded and 174 under review. The report calls this “AI-assisted translation” without naming the tool. These are aggregates. No single translated judgment with a dated delivery was found.", "replication": { "produced_by": [ "Machine translation of English judgments by SUVAS", "Review by High Court AI-assisted translation committees before upload", "Publication on the e-SCR portal and High Court websites" ], "must_hold": [ "Digitized English judgments as input", "Committees with capacity to verify output in each language", "Hosting portals for the translated texts" ], "echoes": [ { "setting": "High Court of Manipur: its AI-Assisted Legal Translation Committee translated 433 Supreme Court judgments into Meetei Mayek, 259 uploaded and 174 under review; the report calls this “AI-assisted translation” and names no tool (Annual Report 2024–25, Vol. 2, printed p. 211)", "outcome": "recurred", "source": "https://cdnbbsr.s3waas.gov.in/s3ec0490f1f4972d133619a60c30f3559e/uploads/2026/01/2026010287.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0006", "title": "Generative-AI-discovered TNIK inhibitor rentosertib shows FVC improvement in a 71-patient phase 2a IPF trial", "summary": "Phase 2a GENESIS-IPF trial in China: 60 mg daily rentosertib +98.4 mL FVC vs -20.3 mL placebo at 12 weeks; cohort-level, sponsor-run", "date_observed": "2024-08-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Rentosertib, a TNIK inhibitor designed with Insilico Medicine's generative-AI platform, was tested in a randomized, double-blind, placebo-controlled phase 2a trial (NCT05938920). It enrolled 71 patients with idiopathic pulmonary fibrosis at 21 sites in China from 19 July 2023 to 11 June 2024 (paper). The registry lists 22 locations, a start date of 19 June 2023 and study completion on 8 August 2024. The primary endpoint was safety. Treatment-emergent adverse events were similar across arms. Patients on 60 mg once daily showed a mean forced vital capacity change of +98.4 mL versus -20.3 mL on placebo over 12 weeks. Insilico sponsored the trial. Eleven authors are its employees and the first author is at Peking Union Medical College Hospital. Results appeared in Nature Medicine on 3 June 2025. The authors call for larger, longer trials.", "category": "general benefit", "unexpected": false, "purpose": "Rentosertib was designed as an antifibrotic treatment for idiopathic pulmonary fibrosis. The trial tested the safety and preliminary efficacy of exactly that intended benefit.", "system": "Insilico Medicine generative-AI drug discovery platform (target discovery and generative chemistry) that produced rentosertib (ISM001-055)", "model_version": "PandaOmics (Biology42) and Chemistry42, Insilico Pharma.AI platform", "developer": "Insilico Medicine", "deployer": "Insilico Medicine (trial sponsor) with 21 clinical centers in China", "location": null, "domain": "Pharmaceutical R&D / respiratory medicine", "segment": "Idiopathic pulmonary fibrosis", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The FVC improvement is a cohort mean from a 71-patient, 12-week, sponsor-run phase 2a trial with safety as the primary endpoint." }, { "group": "societal", "depth": null, "reason": "Any wider benefit depends on confirmation in larger, longer trials, which the authors themselves say are warranted." } ], "ai_role": { "status": "assessed", "statement": "The AI role is upstream: generative-AI tools identified TNIK as a target and designed the molecule. Any clinical effect is pharmacological. The trial was not powered for efficacy and FVC was not the primary endpoint. An independent network meta-analysis ranks rentosertib favorably on FVC decline but reports a non-significant trend toward more serious adverse events." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Xu Z et al. (2025). A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial. Nature Medicine 31:2602–2610. doi:10.1038/s41591-025-03743-2. Insilico Medicine sponsored the trial; eleven authors were employees, and sponsor-employed authors participated in trial design, collection, analysis, and interpretation.", "title": "A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "date": "2025-06-03", "written_by": "makers", "quote": "We observed increased forced vital capacity at the highest dosage with a mean change of +98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group, compared with −20.3 ml (95% confidence interval −116.1 to 75.6) for the placebo group." }, { "kind": "registry label", "citation": "Insilico Medicine Hong Kong Limited. ClinicalTrials.gov, NCT05938920, phase IIa trial of INS018_055 in idiopathic pulmonary fibrosis. Sponsor-supplied registration and results, first posted July 11, 2023; results first posted December 2, 2025.", "title": "Study Evaluating INS018_055 Administered Orally to Subjects With Idiopathic Pulmonary Fibrosis (IPF)", "url": "https://clinicaltrials.gov/study/NCT05938920", "date": "2023-07-11", "written_by": "makers", "quote": "Percentage of Participants Who Had at Least 1 Treatment-emergent Adverse Event (TEAE)" }, { "kind": "peer-reviewed study", "citation": "Xu J, Liu X, Liang X, Cai X, Qian W (2026). Comparative efficacy and safety of monotherapy and combination pharmacotherapies for idiopathic pulmonary fibrosis: a network meta-analysis of randomized controlled trials. BMC Pulmonary Medicine.", "title": "Comparative efficacy and safety of monotherapy and combination pharmacotherapies for idiopathic pulmonary fibrosis: a network meta-analysis of randomized controlled trials", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13330183/", "date": "2026-05-11", "written_by": "independent", "quote": "Rentosertib exhibited a non-significant trend toward a higher risk of SAEs compared with placebo (OR = 1.42, 95% CI: 0.72–2.77)." }, { "kind": "peer-reviewed study", "citation": "Khairil L, Benny KHS, Jerry J, Khatib FM, Che Ramli MD, Kumar S (2026). AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype. Pharmaceuticals.", "title": "AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13304925/", "date": "2026-06-10", "written_by": "independent", "quote": "AI-discovered TNIK inhibitor showed dose-dependent FVC improvement (~trend up to ~100 mL) with acceptable safety." }, { "kind": "peer-reviewed study", "citation": "Magrì T, Richeldi L (2026). Contemporary Concise Review 2025: Interstitial Lung Disease. Respirology.", "title": "Contemporary Concise Review 2025: Interstitial Lung Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13634690/", "date": "2026-09-07", "written_by": "independent", "quote": "Rentosertib, a first-in-class AI-generated small-molecule inhibitor of TNIK, a first-in-class target in idiopathic pulmonary fibrosis (IPF) discovered using generative AI." }, { "kind": "news report", "citation": "Hornick I (2025). Q&A: AI-established drug 'breakthrough in the treatment of IPF'. Healio. (Interviewees: Zuojun Xu, Peking Union Medical College; Alex Zhavoronkov, Insilico CEO.)", "title": "Q&A: AI-established drug 'breakthrough in the treatment of IPF'", "url": "https://www.healio.com/news/pulmonology/20250707/qa-aiestablished-drug-breakthrough-in-the-treatment-of-ipf", "date": "2025-07-07", "written_by": "independent", "quote": "The current phase 2a clinical results are encouraging, but they are based on a small sample size, and we look forward to seeing how it performs in phase 3 clinical trials." }, { "kind": "press release", "citation": "Insilico Medicine. Insilico Initiates Phase III Clinical Trial for Rentosertib, Its AI-Empowered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis. 7 July 2026.", "title": "Insilico Initiates Phase III Clinical Trial for Rentosertib, Its AI-Empowered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis", "url": "https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr", "date": "2026-07-07", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Generative-AI target identification (TNIK) and molecule design by the sponsor", "Sponsor-run 12-week, double-blind phase 2a trial at Chinese centers with safety as the primary endpoint" ], "must_hold": [ "The FVC signal must be confirmed in a larger, longer, geographically diverse phase 3 trial", "Hepatic adverse events and the serious-adverse-event trend must remain acceptable" ], "echoes": [] }, "paired_incident": null, "headline": "Insilico's rentosertib improves FVC in a phase 2a IPF trial", "metric": "mean forced vital capacity change of +98.4 mL versus -20.3 mL on placebo over 12 weeks", "comparator": { "against": "placebo", "before": "−20.3 ml (95% confidence interval −116.1 to 75.6) for the placebo group", "after": "+98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group", "basis": "measured", "quote": "We observed increased forced vital capacity at the highest dosage with a mean change of +98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group, compared with −20.3 ml (95% confidence interval −116.1 to 75.6) for the placebo group.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/" }, "later": { "status": "scaled", "date": "2026-07-07", "note": "Insilico announced a 320-patient, 47-center, 52-week phase III trial of rentosertib in China on 7 July 2026, moving the drug past the 71-patient phase 2a stage.", "quote": "The prospective, randomized, double-blind, placebo-controlled, parallel-group Phase III study is expected to enroll a total of 320 participants across 47 centers in China. The primary endpoint is the annual rate of decline in forced vital capacity (FVC) over 52 weeks.", "url": "https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Healio quote replaced with Xu's verbatim sentence; Nature Medicine quote replaced with the abstract sentence giving +98.4 ml versus −20.3 ml; account now separates the paper's conduct period and 21 sites from the registry's 19 June 2023 start, 22 locations and 8 August 2024 completion; Nature Medicine citation now states the sponsor-employed authors' role and the corresponding authors, on which basis the source stays independent.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/ ; https://www.healio.com/news/pulmonology/20250707/qa-aiestablished-drug-breakthrough-in-the-treatment-of-ipf ; https://clinicaltrials.gov/study/NCT05938920", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Insilico_Medicine; https://en.wikipedia.org/wiki/Insilico_Medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: three independent peer-reviewed studies, one independent news report, the makers' peer-reviewed study, the makers' press release and a registry entry. 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It enrolled 71 patients with idiopathic pulmonary fibrosis at 21 sites in China from 19 July 2023 to 11 June 2024 (paper). The registry lists 22 locations, a start date of 19 June 2023 and study completion on 8 August 2024. The primary endpoint was safety. Treatment-emergent adverse events were similar across arms. Patients on 60 mg once daily showed a mean forced vital capacity change of +98.4 mL versus -20.3 mL on placebo over 12 weeks. Insilico sponsored the trial. Eleven authors are its employees and the first author is at Peking Union Medical College Hospital. Results appeared in Nature Medicine on 3 June 2025. The authors call for larger, longer trials.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The FVC improvement is a cohort mean from a 71-patient, 12-week, sponsor-run phase 2a trial with safety as the primary endpoint." }, { "group": "societal", "reason": "Any wider benefit depends on confirmation in larger, longer trials, which the authors themselves say are warranted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Rentosertib was designed as an antifibrotic treatment for idiopathic pulmonary fibrosis. The trial tested the safety and preliminary efficacy of exactly that intended benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Rentosertib was designed as an antifibrotic treatment for idiopathic pulmonary fibrosis. The trial tested the safety and preliminary efficacy of exactly that intended benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-08-08", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Healio quote replaced with Xu's verbatim sentence; Nature Medicine quote replaced with the abstract sentence giving +98.4 ml versus −20.3 ml; account now separates the paper's conduct period and 21 sites from the registry's 19 June 2023 start, 22 locations and 8 August 2024 completion; Nature Medicine citation now states the sponsor-employed authors' role and the corresponding authors, on which basis the source stays independent.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/ ; https://www.healio.com/news/pulmonology/20250707/qa-aiestablished-drug-breakthrough-in-the-treatment-of-ipf ; https://clinicaltrials.gov/study/NCT05938920", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Insilico_Medicine; https://en.wikipedia.org/wiki/Insilico_Medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Generative-AI target identification (TNIK) and molecule design by the sponsor", "Sponsor-run 12-week, double-blind phase 2a trial at Chinese centers with safety as the primary endpoint" ], "must_hold": [ "The FVC signal must be confirmed in a larger, longer, geographically diverse phase 3 trial", "Hepatic adverse events and the serious-adverse-event trend must remain acceptable" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Healio quote replaced with Xu's verbatim sentence; Nature Medicine quote replaced with the abstract sentence giving +98.4 ml versus −20.3 ml; account now separates the paper's conduct period and 21 sites from the registry's 19 June 2023 start, 22 locations and 8 August 2024 completion; Nature Medicine citation now states the sponsor-employed authors' role and the corresponding authors, on which basis the source stays independent.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/ ; https://www.healio.com/news/pulmonology/20250707/qa-aiestablished-drug-breakthrough-in-the-treatment-of-ipf ; https://clinicaltrials.gov/study/NCT05938920", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr; https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Insilico_Medicine; https://en.wikipedia.org/wiki/Insilico_Medicine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Pharmaceutical R&D / respiratory medicine", "segment": "Idiopathic pulmonary fibrosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Xu Z et al. (2025). A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial. Nature Medicine 31:2602–2610. doi:10.1038/s41591-025-03743-2. Insilico Medicine sponsored the trial; eleven authors were employees, and sponsor-employed authors participated in trial design, collection, analysis, and interpretation.", "title": "A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "date": "2025-06-03", "written_by": "makers", "quote": "We observed increased forced vital capacity at the highest dosage with a mean change of +98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group, compared with −20.3 ml (95% confidence interval −116.1 to 75.6) for the placebo group." }, { "kind": "registry label", "citation": "Insilico Medicine Hong Kong Limited. ClinicalTrials.gov, NCT05938920, phase IIa trial of INS018_055 in idiopathic pulmonary fibrosis. Sponsor-supplied registration and results, first posted July 11, 2023; results first posted December 2, 2025.", "title": "Study Evaluating INS018_055 Administered Orally to Subjects With Idiopathic Pulmonary Fibrosis (IPF)", "url": "https://clinicaltrials.gov/study/NCT05938920", "date": "2023-07-11", "written_by": "makers", "quote": "Percentage of Participants Who Had at Least 1 Treatment-emergent Adverse Event (TEAE)" }, { "kind": "peer-reviewed study", "citation": "Xu J, Liu X, Liang X, Cai X, Qian W (2026). Comparative efficacy and safety of monotherapy and combination pharmacotherapies for idiopathic pulmonary fibrosis: a network meta-analysis of randomized controlled trials. BMC Pulmonary Medicine.", "title": "Comparative efficacy and safety of monotherapy and combination pharmacotherapies for idiopathic pulmonary fibrosis: a network meta-analysis of randomized controlled trials", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13330183/", "date": "2026-05-11", "written_by": "independent", "quote": "Rentosertib exhibited a non-significant trend toward a higher risk of SAEs compared with placebo (OR = 1.42, 95% CI: 0.72–2.77)." }, { "kind": "peer-reviewed study", "citation": "Khairil L, Benny KHS, Jerry J, Khatib FM, Che Ramli MD, Kumar S (2026). AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype. Pharmaceuticals.", "title": "AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13304925/", "date": "2026-06-10", "written_by": "independent", "quote": "AI-discovered TNIK inhibitor showed dose-dependent FVC improvement (~trend up to ~100 mL) with acceptable safety." }, { "kind": "peer-reviewed study", "citation": "Magrì T, Richeldi L (2026). Contemporary Concise Review 2025: Interstitial Lung Disease. Respirology.", "title": "Contemporary Concise Review 2025: Interstitial Lung Disease", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13634690/", "date": "2026-09-07", "written_by": "independent", "quote": "Rentosertib, a first-in-class AI-generated small-molecule inhibitor of TNIK, a first-in-class target in idiopathic pulmonary fibrosis (IPF) discovered using generative AI." }, { "kind": "news report", "citation": "Hornick I (2025). Q&A: AI-established drug 'breakthrough in the treatment of IPF'. Healio. (Interviewees: Zuojun Xu, Peking Union Medical College; Alex Zhavoronkov, Insilico CEO.)", "title": "Q&A: AI-established drug 'breakthrough in the treatment of IPF'", "url": "https://www.healio.com/news/pulmonology/20250707/qa-aiestablished-drug-breakthrough-in-the-treatment-of-ipf", "date": "2025-07-07", "written_by": "independent", "quote": "The current phase 2a clinical results are encouraging, but they are based on a small sample size, and we look forward to seeing how it performs in phase 3 clinical trials." }, { "kind": "press release", "citation": "Insilico Medicine. Insilico Initiates Phase III Clinical Trial for Rentosertib, Its AI-Empowered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis. 7 July 2026.", "title": "Insilico Initiates Phase III Clinical Trial for Rentosertib, Its AI-Empowered TNIK Inhibitor for Idiopathic Pulmonary Fibrosis", "url": "https://insilico.com/news/xmjsn4l091-insilico-initiates-phase-iii-clinical-tr", "date": "2026-07-07", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0006-source-0001", "AIBD-0006-source-0002", "AIBD-0006-source-0003", "AIBD-0006-source-0004", "AIBD-0006-source-0005", "AIBD-0006-source-0006", "AIBD-0006-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "Insilico sponsored the trial and supplied the ClinicalTrials.gov entry and results. The registry is not an independent regulator’s finding. The paper discloses the company’s role and employee authors." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0006-source-0001", "AIBD-0006-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Insilico sponsored the trial and supplied the ClinicalTrials.gov entry and results. The registry is not an independent regulator’s finding. The paper discloses the company’s role and employee authors." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0006-source-0001", "retained_source_order": [ "AIBD-0006-source-0001", "AIBD-0006-source-0002", "AIBD-0006-source-0003", "AIBD-0006-source-0004", "AIBD-0006-source-0005", "AIBD-0006-source-0006", "AIBD-0006-source-0007" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12353801/", "locator": "Competing interests and Author contributions.", "contribution": "Establishes sponsorship and employee involvement in the trial.", "relationship": "Original sponsor-funded study.", "source_refs": [ "AIBD-0006-source-0001" ] }, { "url": "https://clinicaltrials.gov/api/v2/studies/NCT05938920", "locator": "protocolSection.sponsorCollaboratorsModule; resultsSection.outcomeMeasuresModule; statusModule.", "contribution": "Identifies the sponsor/responsible party and the posted outcomes.", "relationship": "Sponsor-supplied registration and results hosted by the U.S. National Library of Medicine.", "source_refs": [ "AIBD-0006-source-0002" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0006-source-0001", "AIBD-0006-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Insilico sponsored the trial and supplied the ClinicalTrials.gov entry and results. The registry is not an independent regulator’s finding. The paper discloses the company’s role and employee authors." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Phase 2a GENESIS-IPF trial in China: 60 mg daily rentosertib +98.4 mL FVC vs -20.3 mL placebo at 12 weeks; cohort-level, sponsor-run", "account": "Rentosertib, a TNIK inhibitor designed with Insilico Medicine's generative-AI platform, was tested in a randomized, double-blind, placebo-controlled phase 2a trial (NCT05938920). It enrolled 71 patients with idiopathic pulmonary fibrosis at 21 sites in China from 19 July 2023 to 11 June 2024 (paper). The registry lists 22 locations, a start date of 19 June 2023 and study completion on 8 August 2024. The primary endpoint was safety. Treatment-emergent adverse events were similar across arms. Patients on 60 mg once daily showed a mean forced vital capacity change of +98.4 mL versus -20.3 mL on placebo over 12 weeks. Insilico sponsored the trial. Eleven authors are its employees and the first author is at Peking Union Medical College Hospital. Results appeared in Nature Medicine on 3 June 2025. The authors call for larger, longer trials." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The tools identified a drug target and designed a candidate molecule." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "PandaOmics supported target discovery. Chemistry42 supported molecular design within Insilico Medicine’s Pharma.AI platform." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "PandaOmics (Biology42) and Chemistry42, Insilico Pharma.AI platform" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Insilico Medicine generative-AI drug discovery platform (target discovery and generative chemistry) that produced rentosertib (ISM001-055)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Insilico Medicine" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Generative-AI-discovered TNIK inhibitor rentosertib shows FVC improvement in a 71-patient phase 2a IPF trial", "headline": "Insilico's rentosertib improves FVC in a phase 2a IPF trial" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4feab4514c129b7e2e4ddc159c19579f9244619ac153adbd20701b97329ce132" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Rentosertib, a TNIK inhibitor designed with Insilico Medicine's generative-AI platform, was tested in a randomized, double-blind, placebo-controlled phase 2a trial (NCT05938920). It enrolled 71 patients with idiopathic pulmonary fibrosis at 21 sites in China from 19 July 2023 to 11 June 2024 (paper). The registry lists 22 locations, a start date of 19 June 2023 and study completion on 8 August 2024. The primary endpoint was safety. Treatment-emergent adverse events were similar across arms. Patients on 60 mg once daily showed a mean forced vital capacity change of +98.4 mL versus -20.3 mL on placebo over 12 weeks. Insilico sponsored the trial. Eleven authors are its employees and the first author is at Peking Union Medical College Hospital. Results appeared in Nature Medicine on 3 June 2025. The authors call for larger, longer trials.", "replication": { "produced_by": [ "Generative-AI target identification (TNIK) and molecule design by the sponsor", "Sponsor-run 12-week, double-blind phase 2a trial at Chinese centers with safety as the primary endpoint" ], "must_hold": [ "The FVC signal must be confirmed in a larger, longer, geographically diverse phase 3 trial", "Hepatic adverse events and the serious-adverse-event trend must remain acceptable" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 2, "record_mapped": 29, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0372", "title": "Chongqing Bio-Intelligent Manufacturing Research Institute's muscle-signal “smart hand” lets bilateral amputee Wang Bing eat, drink, shake hands and write his name", "summary": "Guangming Daily (13 August 2024): Wang Bing, who lost both hands, uses the institute's algorithm-decoded “smart hand” to eat with a spoon, drink, shake hands, rotate his wrist and write his name.", "date_observed": "2024-08-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A Guangming Daily feature (13 August 2024) on Chongqing's Liangjiang New Area opens with Wang Bing. He lost both hands in an accident a few years earlier, leaving half of each forearm. He says he now uses the “smart hand” to eat with a spoon, drink from a cup, shake hands and rotate his wrist. He manages daily life alone and can grip a pen and write his name. Xie Haiqiong, director of the Chongqing Bio-Intelligent Manufacturing Research Institute at Mingyue Lake, says researchers devised a scheme. It detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. So the user controls the hand by intention, not passive motion. Fiscal funds arriving since 2023 under the district's grant-to-equity model supported the project. The institute formed a company to incubate the exoskeleton project (Guangming Daily via Haiwainet and NetEase). The fitting date is not given.", "category": "benefit created", "unexpected": false, "purpose": "Built to let a person with amputated hands control a prosthetic hand through muscle signals. The daily-task function Wang Bing describes is that purpose. The feature frames the project as an example of the district's policy for commercializing research.", "system": "'Smart hand' (智能手) muscle-signal prosthetic hand from the institute's exoskeleton robot project", "model_version": null, "developer": "Chongqing Bio-Intelligent Manufacturing Research Institute (重庆生物智能制造研究院), Liangjiang New Area", "deployer": "Chongqing Bio-Intelligent Manufacturing Research Institute", "location": "Chongqing, China", "domain": "Healthcare / prosthetics and rehabilitation", "segment": "Upper-limb prosthetics", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2024-08-13-08d8" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "Per Guangming Daily, Wang Bing, who lost both hands, says he eats with a spoon, drinks from a cup, shakes hands and rotates his wrist. He writes his name and manages daily life alone with the device. A capability restored, reported in his words without clinical assessment." } ], "ai_role": { "status": "unassessed", "statement": "The only description of the technology is institute director Xie Haiqiong's, as quoted by Guangming Daily. It is a scheme that detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. That lets the user control the hand by intention. No source names a machine-learning method, model, training procedure or accuracy figure. The Monitor's “AI-driven” label rests on that description. The functional gains are Wang Bing's own account in a newspaper feature about the district's commercialization policy. No clinician or independent evaluation is cited." }, "evidence": [ { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径. 光明日报 (Guangming Daily), 13 August 2024, republished by 海外网.", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://news.haiwainet.cn/n/2024/0813/c3544276-32780272.html", "date": "2024-08-13", "written_by": "independent", "quote": "如今，他不仅实现了生活自理，还可以写字，用\"智能手\"抓住一支笔，就能写出自己的名字。" }, { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根. 光明日报 (Guangming Daily), 13 August 2024, republished by 网易 (second quotation).", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://m.163.com/news/article/J9FSKJ28000189FH.html", "date": "2024-08-13", "written_by": "independent", "quote": "我们组织研究人员进行科研攻关，迅速制定了检测、识别适当肌肉处的电信号并经算法分析和处理的技术方案。" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-powered Prosthetic Hand Restores Function for Chongqing Amputee. OECD.AI, 13 August 2024.", "title": "AI-powered Prosthetic Hand Restores Function for Chongqing Amputee", "url": "https://oecd.ai/en/incidents/2024-08-13-08d8", "date": "2024-08-13", "written_by": "independent", "quote": "decodes muscle signals via algorithms, allowing amputee Wang Bing to perform daily tasks like eating and writing" } ], "replication": { "produced_by": [ "Electrical signals detectable at suitable muscle sites on the residual forearms", "An algorithmic scheme that identifies those signals and maps them to hand and wrist movements", "Institute researchers fitting and tuning the device for one user, with district fiscal grants converted to equity" ], "must_hold": [ "Enough residual muscle to produce usable signals", "Training time for the user to control the hand by intention", "Continued funding and a company to maintain and produce the device" ], "echoes": [] }, "paired_incident": null, "headline": "A muscle-signal “smart hand” returns daily tasks to Wang Bing", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-08-13-08d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0372", "catalog_version": "1.0.0", "source_fingerprint": "651c3930f59e330f44b2ca5c4a492f4cb2985dde9b135cb4a70b01d3374e34a1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0372-source-0001", "AIBD-0372-source-0002", "AIBD-0372-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Chongqing Bio-Intelligent Manufacturing Research Institute (重庆生物智能制造研究院), Liangjiang New Area", "deployer": "Chongqing Bio-Intelligent Manufacturing Research Institute" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "The only description of the technology is institute director Xie Haiqiong's, as quoted by Guangming Daily. It is a scheme that detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. That lets the user control the hand by intention. No source names a machine-learning method, model, training procedure or accuracy figure. The Monitor's “AI-driven” label rests on that description. The functional gains are Wang Bing's own account in a newspaper feature about the district's commercialization policy. 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"record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A Guangming Daily feature (13 August 2024) on Chongqing's Liangjiang New Area opens with Wang Bing. He lost both hands in an accident a few years earlier, leaving half of each forearm. He says he now uses the “smart hand” to eat with a spoon, drink from a cup, shake hands and rotate his wrist. He manages daily life alone and can grip a pen and write his name. Xie Haiqiong, director of the Chongqing Bio-Intelligent Manufacturing Research Institute at Mingyue Lake, says researchers devised a scheme. It detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. So the user controls the hand by intention, not passive motion. Fiscal funds arriving since 2023 under the district's grant-to-equity model supported the project. The institute formed a company to incubate the exoskeleton project (Guangming Daily via Haiwainet and NetEase). The fitting date is not given.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Per Guangming Daily, Wang Bing, who lost both hands, says he eats with a spoon, drinks from a cup, shakes hands and rotates his wrist. He writes his name and manages daily life alone with the device. A capability restored, reported in his words without clinical assessment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to let a person with amputated hands control a prosthetic hand through muscle signals. The daily-task function Wang Bing describes is that purpose. The feature frames the project as an example of the district's policy for commercializing research." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Chongqing, China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to let a person with amputated hands control a prosthetic hand through muscle signals. The daily-task function Wang Bing describes is that purpose. The feature frames the project as an example of the district's policy for commercializing research." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-08-13", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-08-13-08d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Electrical signals detectable at suitable muscle sites on the residual forearms", "An algorithmic scheme that identifies those signals and maps them to hand and wrist movements", "Institute researchers fitting and tuning the device for one user, with district fiscal grants converted to equity" ], "must_hold": [ "Enough residual muscle to produce usable signals", "Training time for the user to control the hand by intention", "Continued funding and a company to maintain and produce the device" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-08-13-08d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare / prosthetics and rehabilitation", "segment": "Upper-limb prosthetics" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径. 光明日报 (Guangming Daily), 13 August 2024, republished by 海外网.", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://news.haiwainet.cn/n/2024/0813/c3544276-32780272.html", "date": "2024-08-13", "written_by": "independent", "quote": "如今，他不仅实现了生活自理，还可以写字，用\"智能手\"抓住一支笔，就能写出自己的名字。" }, { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根. 光明日报 (Guangming Daily), 13 August 2024, republished by 网易 (second quotation).", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://m.163.com/news/article/J9FSKJ28000189FH.html", "date": "2024-08-13", "written_by": "independent", "quote": "我们组织研究人员进行科研攻关，迅速制定了检测、识别适当肌肉处的电信号并经算法分析和处理的技术方案。" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-powered Prosthetic Hand Restores Function for Chongqing Amputee. OECD.AI, 13 August 2024.", "title": "AI-powered Prosthetic Hand Restores Function for Chongqing Amputee", "url": "https://oecd.ai/en/incidents/2024-08-13-08d8", "date": "2024-08-13", "written_by": "independent", "quote": "decodes muscle signals via algorithms, allowing amputee Wang Bing to perform daily tasks like eating and writing" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0372-source-0001", "AIBD-0372-source-0002", "AIBD-0372-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径. 光明日报 (Guangming Daily), 13 August 2024, republished by 海外网.", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://news.haiwainet.cn/n/2024/0813/c3544276-32780272.html", "date": "2024-08-13", "written_by": "independent", "quote": "如今，他不仅实现了生活自理，还可以写字，用\"智能手\"抓住一支笔，就能写出自己的名字。" }, { "kind": "news report", "citation": "李宏, 黄汉鑫, 张国圣 (2024). 让更多\"硬核\"技术项目落地生根. 光明日报 (Guangming Daily), 13 August 2024, republished by 网易 (second quotation).", "title": "让更多\"硬核\"技术项目落地生根——重庆两江新区为新型研发机构畅通产业化路径", "url": "https://m.163.com/news/article/J9FSKJ28000189FH.html", "date": "2024-08-13", "written_by": "independent", "quote": "我们组织研究人员进行科研攻关，迅速制定了检测、识别适当肌肉处的电信号并经算法分析和处理的技术方案。" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2024). AI-powered Prosthetic Hand Restores Function for Chongqing Amputee. OECD.AI, 13 August 2024.", "title": "AI-powered Prosthetic Hand Restores Function for Chongqing Amputee", "url": "https://oecd.ai/en/incidents/2024-08-13-08d8", "date": "2024-08-13", "written_by": "independent", "quote": "decodes muscle signals via algorithms, allowing amputee Wang Bing to perform daily tasks like eating and writing" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Guangming Daily (13 August 2024): Wang Bing, who lost both hands, uses the institute's algorithm-decoded “smart hand” to eat with a spoon, drink, shake hands, rotate his wrist and write his name.", "account": "A Guangming Daily feature (13 August 2024) on Chongqing's Liangjiang New Area opens with Wang Bing. He lost both hands in an accident a few years earlier, leaving half of each forearm. He says he now uses the “smart hand” to eat with a spoon, drink from a cup, shake hands and rotate his wrist. He manages daily life alone and can grip a pen and write his name. Xie Haiqiong, director of the Chongqing Bio-Intelligent Manufacturing Research Institute at Mingyue Lake, says researchers devised a scheme. It detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. So the user controls the hand by intention, not passive motion. Fiscal funds arriving since 2023 under the district's grant-to-equity model supported the project. The institute formed a company to incubate the exoskeleton project (Guangming Daily via Haiwainet and NetEase). The fitting date is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "'Smart hand' (智能手) muscle-signal prosthetic hand from the institute's exoskeleton robot project" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Chongqing Bio-Intelligent Manufacturing Research Institute (重庆生物智能制造研究院), Liangjiang New Area" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Chongqing Bio-Intelligent Manufacturing Research Institute's muscle-signal “smart hand” lets bilateral amputee Wang Bing eat, drink, shake hands and write his name", "headline": "A muscle-signal “smart hand” returns daily tasks to Wang Bing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "651c3930f59e330f44b2ca5c4a492f4cb2985dde9b135cb4a70b01d3374e34a1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A Guangming Daily feature (13 August 2024) on Chongqing's Liangjiang New Area opens with Wang Bing. He lost both hands in an accident a few years earlier, leaving half of each forearm. He says he now uses the “smart hand” to eat with a spoon, drink from a cup, shake hands and rotate his wrist. He manages daily life alone and can grip a pen and write his name. Xie Haiqiong, director of the Chongqing Bio-Intelligent Manufacturing Research Institute at Mingyue Lake, says researchers devised a scheme. It detects and identifies electrical signals at suitable muscle sites and processes them by algorithmic analysis. So the user controls the hand by intention, not passive motion. Fiscal funds arriving since 2023 under the district's grant-to-equity model supported the project. The institute formed a company to incubate the exoskeleton project (Guangming Daily via Haiwainet and NetEase). The fitting date is not given.", "replication": { "produced_by": [ "Electrical signals detectable at suitable muscle sites on the residual forearms", "An algorithmic scheme that identifies those signals and maps them to hand and wrist movements", "Institute researchers fitting and tuning the device for one user, with district fiscal grants converted to equity" ], "must_hold": [ "Enough residual muscle to produce usable signals", "Training time for the user to control the hand by intention", "Continued funding and a company to maintain and produce the device" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0095", "title": "GiveDirectly paid anticipatory cash in Kogi State, Nigeria, on Google Flood Hub forecast triggers (August to October 2024)", "summary": "Google Flood Hub forecast triggers paid $105 to 4,600 people in Ibaji, Kogi State, mostly before floods peaked on 21 October 2024", "date_observed": "2024-08-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In 2024 GiveDirectly ran an anticipatory cash program in six wards of Ibaji, Kogi State, Nigeria. JBA Global Resilience pulled Google Flood Hub forecasts by application programming interface (API), made inundation maps and set thresholds. GiveDirectly monitored forecasts daily and cross-checked them with community observations. When 20% of a community's area was forecast to flood the trigger was met and verified residents were paid. The New Humanitarian describes an automated payout command to verified residents. GiveDirectly reports $105 to over 4,600 individuals in 53 communities. 3,250 were paid between 29 August and 6 October 2024 and 1,400 on 24 October, after floods peaked on 21 October. A $210 transfer followed. Its own survey reports weekly incomes rising from ₦4,500 to ₦10,000 and food shortages falling from 97% to 7%. A New Humanitarian investigation (31 August 2026) found data mismatches and phone-access barriers excluded some of the most vulnerable residents. GiveDirectly told the outlet it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation appeared.", "category": "protective response", "unexpected": false, "purpose": "Trigger and target anticipatory cash transfers to flood-prone communities before river flooding.", "system": "Google Flood Hub AI river-flood forecasts accessed via API, with JBA Global Resilience hydrology analysis and a 20%-of-community-area trigger rule", "model_version": null, "developer": "Google (Flood Hub); trigger design by GiveDirectly with JBA Global Resilience", "deployer": "GiveDirectly", "location": "Ibaji, Kogi State, Nigeria", "domain": "Humanitarian anticipatory action and cash transfers", "segment": "NGO cash assistance", "benefit_type": "Reduced Risk", "taxonomy_note": "Cash paid before a forecast flood is read as reducing potential for harm; Trustible's description stresses legal harm.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "$105 to over 4,600 individuals, followed by a $210 transfer (recipient count not stated). Implementer survey reports weekly income doubling and fewer food shortages (self-reported, not independently verified)." }, { "group": "organizational", "depth": 1, "reason": "GiveDirectly gained a tested trigger pipeline and documented lessons. It acknowledged to The New Humanitarian that it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation was published on 31 August 2026." }, { "group": "societal", "depth": 2, "reason": "Material to a group of about 4,600 people in 53 communities. The investigation documents that some of the poorest were excluded, limiting wider benefit." } ], "ai_role": { "status": "assessed", "statement": "Decisive for timing and geography: GiveDirectly told The New Humanitarian that satellite/AI flood modeling determined which communities were paid and when. Individual eligibility was decided by non-AI verification (ward residence, Smile ID checks, call-center calls). The investigation identifies that as the main source of exclusions. GiveDirectly's own page attributes the late payments to identity checks in two wards." }, "evidence": [ { "kind": "press release", "citation": "GiveDirectly (2025). How AI helped send cash just before floods hit in Nigeria. GiveDirectly (implementer report; page updated 2026).", "title": "How AI helped send cash just before floods hit in Nigeria", "url": "https://www.givedirectly.org/flood-forecast-ai/", "date": "2025-06-27", "written_by": "deployer", "quote": "We sent early payments to 3,250 people between August 29 and October 6" }, { "kind": "news report", "citation": "Ayeni, D. (2026). GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria. The New Humanitarian, investigation, 31 August 2026 (live page returns 403).", "title": "GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria", "url": "https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "date": "2026-08-31", "written_by": "independent", "quote": "Would-be aid recipients said they were excluded for submitting personal data that did not perfectly match government or bank records" }, { "kind": "news report", "citation": "Cheng, K.-C. (2024). Could AI save Nigerians from devastating floods? Al Jazeera.", "title": "Could AI save Nigerians from devastating floods?", "url": "https://www.aljazeera.com/features/2024/9/21/could-ai-save-nigerians-from-devastating-floods", "date": "2024-09-21", "written_by": "independent", "quote": "Omali received his first transfer of 177,866 naira on August 31 this year." } ], "replication": { "produced_by": [ "Google Flood Hub forecasts via API", "20%-of-area trigger rule defined by GiveDirectly and JBA", "USSD pre-enrollment, Smile ID verification and call-center checks", "Cash transfers using recipients' self-reported bank details. GiveDirectly and the IRC received a $4.6 million Google.org grant in 2024 for AI-assisted anticipatory cash (The New Humanitarian). It is not stated to have funded the Kogi transfers" ], "must_hold": [ "Forecast skill on the Niger and Benue floodplain", "Phone access, charging and matching ID records among the poorest", "Funds released and verification completed before the hazard" ], "echoes": [ { "date": "2022-10-01", "setting": "GiveDirectly's 2022 Kogi State response: communities chosen before the season by layering historical flood data (Floodbase, Fathom), granular poverty maps and crop and village density derived from satellite imagery; people enrolled mid-September 2022 and paid once October 2022 flooding began (month only known; first day used)", "model_version": null, "outcome": "unknown", "source": "https://www.givedirectly.org/flood-pilots/" }, { "date": null, "setting": "GiveDirectly anticipatory programs in Kenya, Mozambique and a planned Bangladesh RCT (Jamuna basin)", "model_version": null, "outcome": "unknown", "source": "The New Humanitarian (2026), https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "severity": null, "group": "societal", "basis": "Google-built hazard alert system underestimated the earthquake and failed to warn residents; Flood Hub triggers from the same developer decided who received anticipatory cash." }, "headline": "Google Flood Hub triggers pay $105 to 4,600 people in Kogi", "metric": "weekly incomes rising from ₦4,500 to ₦10,000 and food shortages falling from 97% to 7%", "comparator": { "against": "recipients' own situation before the transfers (GiveDirectly follow-up survey; no control group)", "before": "weekly income ₦4,500; 97% facing food shortages", "after": "weekly income ₦10,000; 7% facing food shortages", "basis": "measured", "quote": "Weekly income more than doubled, from ₦4,500 to ₦10,000 🍲 Food security improved, with 97% facing food shortages before and just 7% after", "url": "https://www.givedirectly.org/flood-forecast-ai/" }, "later": { "status": "scaled", "date": "2025-06-27", "note": "GiveDirectly's implementer report (published 27 June 2025, revised July 2026 to add the tradeoffs of remote phone-based targeting) says it is extending AI-triggered anticipatory cash with Google Research to new countries and other hazards.", "quote": "GiveDirectly continues to work with Google Research to scale the use of AI for anticipatory action to new countries and explore anticipatory cash transfers for other hazards, such as droughts.", "url": "https://www.givedirectly.org/flood-forecast-ai/" }, "value": { "amount": "$105", "what": "anticipatory cash transfer per recipient before the flood peak (a second $210 transfer followed)", "who": "over 4,600 flood-exposed residents of Ibaji, Kogi State", "estimate": false, "quote": "Once forecasted flood thresholds were met, we sent $105 to over 4,600 individuals before the flood peak.", "url": "https://www.givedirectly.org/flood-forecast-ai/" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Re-aligned the account, ratings, AI-role statement, what produced it and the 2022 echo with the GiveDirectly and New Humanitarian texts (JBA pulled forecasts by API and set thresholds while GiveDirectly monitored daily, the $210 recipient count is not stated, the page was updated in July 2026 before the 31 August 2026 investigation, payments used bank details rather than mobile money and the Google.org grant is not tied to Kogi, satellite imagery informed crop and village density rather than poverty maps, late payments are the page's identity checks), confirmed the Ayeni byline against the Wayback snapshot of 22 September 2026, and dropped the word “State” from the headline to bring it under the 64-character limit.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-pilots/; https://web.archive.org/web/20260922092208/https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://projects.propublica.org/nonprofits/organizations/271661997", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and the deployer's press release. 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About 1,400 recipients were paid on 24 October 2024, after floods peaked on 21 October. A later US$210 transfer has no stated recipient count." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "group": "societal", "basis": "Google-built hazard alert system underestimated the earthquake and failed to warn residents; Flood Hub triggers from the same developer decided who received anticipatory cash." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2025-06-27", "note": "GiveDirectly's implementer report (published 27 June 2025, revised July 2026 to add the tradeoffs of remote phone-based targeting) says it is extending AI-triggered anticipatory cash with Google Research to new countries and other hazards.", "quote": "GiveDirectly continues to work with Google Research to scale the use of AI for anticipatory action to new countries and explore anticipatory cash transfers for other hazards, such as droughts.", "url": "https://www.givedirectly.org/flood-forecast-ai/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0095" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Residents of 53 communities in Ibaji, Kogi State, Nigeria." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Residents of 53 communities in Ibaji, Kogi State, Nigeria." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "GiveDirectly reports more than 4,600 recipients. It acknowledged that it had used “household” and “individual” interchangeably." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GiveDirectly reports more than 4,600 recipients. It acknowledged that it had used “household” and “individual” interchangeably." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "Cash paid before a forecast flood is read as reducing potential for harm; Trustible's description stresses legal harm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In 2024 GiveDirectly ran an anticipatory cash program in six wards of Ibaji, Kogi State, Nigeria. JBA Global Resilience pulled Google Flood Hub forecasts by application programming interface (API), made inundation maps and set thresholds. GiveDirectly monitored forecasts daily and cross-checked them with community observations. When 20% of a community's area was forecast to flood the trigger was met and verified residents were paid. The New Humanitarian describes an automated payout command to verified residents. GiveDirectly reports $105 to over 4,600 individuals in 53 communities. 3,250 were paid between 29 August and 6 October 2024 and 1,400 on 24 October, after floods peaked on 21 October. A $210 transfer followed. Its own survey reports weekly incomes rising from ₦4,500 to ₦10,000 and food shortages falling from 97% to 7%. A New Humanitarian investigation (31 August 2026) found data mismatches and phone-access barriers excluded some of the most vulnerable residents. GiveDirectly told the outlet it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation appeared.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GiveDirectly paid US$105 to more than 4,600 people in flood-prone communities, with 3,250 paid before the flood peak." } }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Some residents were excluded because they lacked phone access or their details did not match government or bank records." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Some residents were excluded because they lacked phone access or their details did not match government or bank records." } }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "$105 to over 4,600 individuals, followed by a $210 transfer (recipient count not stated). Implementer survey reports weekly income doubling and fewer food shortages (self-reported, not independently verified)." }, { "group": "organizational", "depth": 1, "reason": "GiveDirectly gained a tested trigger pipeline and documented lessons. It acknowledged to The New Humanitarian that it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation was published on 31 August 2026." }, { "group": "societal", "depth": 2, "reason": "Material to a group of about 4,600 people in 53 communities. The investigation documents that some of the poorest were excluded, limiting wider benefit." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "The New Humanitarian found that verification and phone-access barriers excluded some of the most vulnerable residents." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The New Humanitarian found that verification and phone-access barriers excluded some of the most vulnerable residents." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Trigger and target anticipatory cash transfers to flood-prone communities before river flooding." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ibaji, Kogi State, Nigeria", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Trigger and target anticipatory cash transfers to flood-prone communities before river flooding." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-08-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Re-aligned the account, ratings, AI-role statement, what produced it and the 2022 echo with the GiveDirectly and New Humanitarian texts (JBA pulled forecasts by API and set thresholds while GiveDirectly monitored daily, the $210 recipient count is not stated, the page was updated in July 2026 before the 31 August 2026 investigation, payments used bank details rather than mobile money and the Google.org grant is not tied to Kogi, satellite imagery informed crop and village density rather than poverty maps, late payments are the page's identity checks), confirmed the Ayeni byline against the Wayback snapshot of 22 September 2026, and dropped the word “State” from the headline to bring it under the 64-character limit.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-pilots/; https://web.archive.org/web/20260922092208/https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://projects.propublica.org/nonprofits/organizations/271661997", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Google Flood Hub forecasts via API", "20%-of-area trigger rule defined by GiveDirectly and JBA", "USSD pre-enrollment, Smile ID verification and call-center checks", "Cash transfers using recipients' self-reported bank details. GiveDirectly and the IRC received a $4.6 million Google.org grant in 2024 for AI-assisted anticipatory cash (The New Humanitarian). It is not stated to have funded the Kogi transfers" ], "must_hold": [ "Forecast skill on the Niger and Benue floodplain", "Phone access, charging and matching ID records among the poorest", "Funds released and verification completed before the hazard" ], "echoes": [ { "date": "2022-10-01", "setting": "GiveDirectly's 2022 Kogi State response: communities chosen before the season by layering historical flood data (Floodbase, Fathom), granular poverty maps and crop and village density derived from satellite imagery; people enrolled mid-September 2022 and paid once October 2022 flooding began (month only known; first day used)", "outcome": "unknown", "source": "https://www.givedirectly.org/flood-pilots/" }, { "setting": "GiveDirectly anticipatory programs in Kenya, Mozambique and a planned Bangladesh RCT (Jamuna basin)", "outcome": "unknown", "source": "The New Humanitarian (2026), https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Google Flood Hub forecasts via API", "20%-of-area trigger rule defined by GiveDirectly and JBA", "USSD pre-enrollment, Smile ID verification and call-center checks", "Cash transfers using recipients' self-reported bank details. GiveDirectly and the IRC received a $4.6 million Google.org grant in 2024 for AI-assisted anticipatory cash (The New Humanitarian). It is not stated to have funded the Kogi transfers" ], "must_hold": [ "Forecast skill on the Niger and Benue floodplain", "Phone access, charging and matching ID records among the poorest", "Funds released and verification completed before the hazard" ], "echoes": [ { "date": "2022-10-01", "setting": "GiveDirectly's 2022 Kogi State response: communities chosen before the season by layering historical flood data (Floodbase, Fathom), granular poverty maps and crop and village density derived from satellite imagery; people enrolled mid-September 2022 and paid once October 2022 flooding began (month only known; first day used)", "outcome": "unknown", "source": "https://www.givedirectly.org/flood-pilots/" }, { "setting": "GiveDirectly anticipatory programs in Kenya, Mozambique and a planned Bangladesh RCT (Jamuna basin)", "outcome": "unknown", "source": "The New Humanitarian (2026), https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Re-aligned the account, ratings, AI-role statement, what produced it and the 2022 echo with the GiveDirectly and New Humanitarian texts (JBA pulled forecasts by API and set thresholds while GiveDirectly monitored daily, the $210 recipient count is not stated, the page was updated in July 2026 before the 31 August 2026 investigation, payments used bank details rather than mobile money and the Google.org grant is not tied to Kogi, satellite imagery informed crop and village density rather than poverty maps, late payments are the page's identity checks), confirmed the Ayeni byline against the Wayback snapshot of 22 September 2026, and dropped the word “State” from the headline to bring it under the 64-character limit.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-pilots/; https://web.archive.org/web/20260922092208/https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/; https://www.givedirectly.org/flood-forecast-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://projects.propublica.org/nonprofits/organizations/271661997", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Humanitarian anticipatory action and cash transfers", "segment": "NGO cash assistance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "GiveDirectly (2025). How AI helped send cash just before floods hit in Nigeria. GiveDirectly (implementer report; page updated 2026).", "title": "How AI helped send cash just before floods hit in Nigeria", "url": "https://www.givedirectly.org/flood-forecast-ai/", "date": "2025-06-27", "written_by": "deployer", "quote": "We sent early payments to 3,250 people between August 29 and October 6" }, { "kind": "news report", "citation": "Ayeni, D. (2026). GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria. The New Humanitarian, investigation, 31 August 2026 (live page returns 403).", "title": "GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria", "url": "https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "date": "2026-08-31", "written_by": "independent", "quote": "Would-be aid recipients said they were excluded for submitting personal data that did not perfectly match government or bank records" }, { "kind": "news report", "citation": "Cheng, K.-C. (2024). Could AI save Nigerians from devastating floods? Al Jazeera.", "title": "Could AI save Nigerians from devastating floods?", "url": "https://www.aljazeera.com/features/2024/9/21/could-ai-save-nigerians-from-devastating-floods", "date": "2024-09-21", "written_by": "independent", "quote": "Omali received his first transfer of 177,866 naira on August 31 this year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0095-source-0001", "AIBD-0095-source-0002", "AIBD-0095-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "GiveDirectly (2025). How AI helped send cash just before floods hit in Nigeria. GiveDirectly (implementer report; page updated 2026).", "title": "How AI helped send cash just before floods hit in Nigeria", "url": "https://www.givedirectly.org/flood-forecast-ai/", "date": "2025-06-27", "written_by": "deployer", "quote": "We sent early payments to 3,250 people between August 29 and October 6" }, { "kind": "news report", "citation": "Ayeni, D. (2026). GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria. The New Humanitarian, investigation, 31 August 2026 (live page returns 403).", "title": "GiveDirectly's AI experiment left vulnerable flood victims behind in Nigeria", "url": "https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria", "date": "2026-08-31", "written_by": "independent", "quote": "Would-be aid recipients said they were excluded for submitting personal data that did not perfectly match government or bank records" }, { "kind": "news report", "citation": "Cheng, K.-C. (2024). Could AI save Nigerians from devastating floods? Al Jazeera.", "title": "Could AI save Nigerians from devastating floods?", "url": "https://www.aljazeera.com/features/2024/9/21/could-ai-save-nigerians-from-devastating-floods", "date": "2024-09-21", "written_by": "independent", "quote": "Omali received his first transfer of 177,866 naira on August 31 this year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Google Flood Hub forecast triggers paid $105 to 4,600 people in Ibaji, Kogi State, mostly before floods peaked on 21 October 2024", "account": "In 2024 GiveDirectly ran an anticipatory cash program in six wards of Ibaji, Kogi State, Nigeria. JBA Global Resilience pulled Google Flood Hub forecasts by application programming interface (API), made inundation maps and set thresholds. GiveDirectly monitored forecasts daily and cross-checked them with community observations. When 20% of a community's area was forecast to flood the trigger was met and verified residents were paid. The New Humanitarian describes an automated payout command to verified residents. GiveDirectly reports $105 to over 4,600 individuals in 53 communities. 3,250 were paid between 29 August and 6 October 2024 and 1,400 on 24 October, after floods peaked on 21 October. A $210 transfer followed. Its own survey reports weekly incomes rising from ₦4,500 to ₦10,000 and food shortages falling from 97% to 7%. A New Humanitarian investigation (31 August 2026) found data mismatches and phone-access barriers excluded some of the most vulnerable residents. GiveDirectly told the outlet it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation appeared." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Google Flood Hub AI river-flood forecasts accessed via API, with JBA Global Resilience hydrology analysis and a 20%-of-community-area trigger rule" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google (Flood Hub); trigger design by GiveDirectly with JBA Global Resilience" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GiveDirectly paid anticipatory cash in Kogi State, Nigeria, on Google Flood Hub forecast triggers (August to October 2024)", "headline": "Google Flood Hub triggers pay $105 to 4,600 people in Kogi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "98c5275b8297241b39c99ee3714e3d5dfdb3a9236527256b7a4fc10d1caf9aed" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In 2024 GiveDirectly ran an anticipatory cash program in six wards of Ibaji, Kogi State, Nigeria. JBA Global Resilience pulled Google Flood Hub forecasts by application programming interface (API), made inundation maps and set thresholds. GiveDirectly monitored forecasts daily and cross-checked them with community observations. When 20% of a community's area was forecast to flood the trigger was met and verified residents were paid. The New Humanitarian describes an automated payout command to verified residents. GiveDirectly reports $105 to over 4,600 individuals in 53 communities. 3,250 were paid between 29 August and 6 October 2024 and 1,400 on 24 October, after floods peaked on 21 October. A $210 transfer followed. Its own survey reports weekly incomes rising from ₦4,500 to ₦10,000 and food shortages falling from 97% to 7%. A New Humanitarian investigation (31 August 2026) found data mismatches and phone-access barriers excluded some of the most vulnerable residents. GiveDirectly told the outlet it had used “household” and “individual” interchangeably. Its page note says the page was updated in July 2026, before the investigation appeared.", "replication": { "produced_by": [ "Google Flood Hub forecasts via API", "20%-of-area trigger rule defined by GiveDirectly and JBA", "USSD pre-enrollment, Smile ID verification and call-center checks", "Cash transfers using recipients' self-reported bank details. GiveDirectly and the IRC received a $4.6 million Google.org grant in 2024 for AI-assisted anticipatory cash (The New Humanitarian). It is not stated to have funded the Kogi transfers" ], "must_hold": [ "Forecast skill on the Niger and Benue floodplain", "Phone access, charging and matching ID records among the poorest", "Funds released and verification completed before the hazard" ], "echoes": [ { "date": "2022-10-01", "setting": "GiveDirectly's 2022 Kogi State response: communities chosen before the season by layering historical flood data (Floodbase, Fathom), granular poverty maps and crop and village density derived from satellite imagery; people enrolled mid-September 2022 and paid once October 2022 flooding began (month only known; first day used)", "outcome": "unknown", "source": "https://www.givedirectly.org/flood-pilots/" }, { "setting": "GiveDirectly anticipatory programs in Kenya, Mozambique and a planned Bangladesh RCT (Jamuna basin)", "outcome": "unknown", "source": "The New Humanitarian (2026), https://www.thenewhumanitarian.org/investigations/2026/08/31/givedirectlys-ai-experiment-left-flood-victims-behind-nigeria" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GiveDirectly and JBA used Flood Hub forecasts to identify communities where at least 20% of the area was expected to flood. GiveDirectly verified residents’ identities and bank details before sending payments." } } }, "summary": { "total": 91, "addressed": 91, "known": 43, "reviewed": 0, "record_mapped": 43, "not_assessed": 48, "complete": false, "by_state": { "value_present": 43, "not_reported": 0, "unresolved": 0, "not_assessed": 48, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0170", "title": "Austin Energy deploys 13 Pano AI wildfire cameras across its 437-square-mile territory", "summary": "The City of Austin's utility announced full deployment of a 13-camera Pano AI detection system covering its service area with the Austin Fire Department (29 August 2024); no detections are reported.", "date_observed": "2024-08-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Austin Energy, the City of Austin's electric utility, announced the full deployment of a Pano AI system on 29 August 2024. It combines 13 ultra-high-definition 360-degree cameras, artificial intelligence and real-time monitoring across its 437-square-mile service territory. It covers most of Travis County and parts of Hays, Bastrop, Williamson and Burnet counties. Once a fire is identified the system alerts Austin Energy and local fire departments with location data and imagery. The utility says it supports decisions such as power shut-offs. Wildfire program manager Chris Vetromile and Austin Fire Department wildfire mitigation officer Justice Jones are quoted. Pano AI's Arvind Satyam is also quoted. The release reports no detection or contained fire. The source is the deployer's own announcement (a public body), with the vendor quoted inside it. No independent report is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "The cameras are deployed to detect and verify wildfires early and alert the utility and fire departments. The launch is the intended use with no outcome yet reported.", "system": "Pano AI wildfire detection system (13 camera stations)", "model_version": null, "developer": "Pano AI", "deployer": "Austin Energy (City of Austin) with the Austin Fire Department", "location": "Austin, United States", "domain": "Energy and infrastructure", "segment": "Electric utility wildfire mitigation", "benefit_type": "Reduced Risk", "taxonomy_note": "No detection is attributable; the type names the loss-averting purpose of the cameras.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No detection, response or saving is documented; the release describes capability only." }, { "group": "societal", "depth": null, "reason": "No outcome for the public is documented." } ], "ai_role": { "status": "unassessed", "statement": "No event involving the AI is reported. 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0170-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Austin Energy news release, 'Austin Energy announces full deployment of AI-driven Early Wildfire Detection System', 29 August 2024", "title": "Austin Energy announces full deployment of AI-driven Early Wildfire Detection System", "url": "https://austinenergy.com/about/news/news-releases/2024/Austin-Energy-announces-full-deployment-of-AI-driven-Early-Wildfire-Detection-System", "date": "2024-08-29", "written_by": "deployer", "quote": "The Pano AI system integrates 13 ultra-high-definition, 360-degree cameras, artificial intelligence and real-time data monitoring to swiftly detect and verify potential wildfires." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The City of Austin's utility announced full deployment of a 13-camera Pano AI detection system covering its service area with the Austin Fire Department (29 August 2024); no detections are reported.", "account": "Austin Energy, the City of Austin's electric utility, announced the full deployment of a Pano AI system on 29 August 2024. It combines 13 ultra-high-definition 360-degree cameras, artificial intelligence and real-time monitoring across its 437-square-mile service territory. It covers most of Travis County and parts of Hays, Bastrop, Williamson and Burnet counties. Once a fire is identified the system alerts Austin Energy and local fire departments with location data and imagery. The utility says it supports decisions such as power shut-offs. Wildfire program manager Chris Vetromile and Austin Fire Department wildfire mitigation officer Justice Jones are quoted. Pano AI's Arvind Satyam is also quoted. The release reports no detection or contained fire. The source is the deployer's own announcement (a public body), with the vendor quoted inside it. No independent report is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Pano AI wildfire detection system (13 camera stations)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Pano AI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Austin Energy deploys 13 Pano AI wildfire cameras across its 437-square-mile territory", "headline": "Austin Energy deploys 13 Pano AI cameras across its territory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "eec4b22b483cc5b8995f70f7184ba2d6c0ea5dc42fa537bafba069ea11daf801" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Austin Energy, the City of Austin's electric utility, announced the full deployment of a Pano AI system on 29 August 2024. It combines 13 ultra-high-definition 360-degree cameras, artificial intelligence and real-time monitoring across its 437-square-mile service territory. It covers most of Travis County and parts of Hays, Bastrop, Williamson and Burnet counties. Once a fire is identified the system alerts Austin Energy and local fire departments with location data and imagery. The utility says it supports decisions such as power shut-offs. Wildfire program manager Chris Vetromile and Austin Fire Department wildfire mitigation officer Justice Jones are quoted. Pano AI's Arvind Satyam is also quoted. The release reports no detection or contained fire. The source is the deployer's own announcement (a public body), with the vendor quoted inside it. No independent report is among the sources.", "replication": { "produced_by": [ "Camera siting agreed with the Austin Fire Department and county emergency service districts", "Alerts delivered to both the utility and fire departments", "A public-utility coalition (Texas Public Power Corridor Committee) backing the deployment" ], "must_hold": [ "Camera coverage of the service territory", "Fire agencies able to act on alerts", "Reporting of detections to establish any benefit" ], "echoes": [ { "date": "2024-06-16", "setting": "Bear Creek Fire, Colorado; Xcel Energy and CORE Electric Pano AI cameras detected the fire", "outcome": "recurred", "source": "https://www.renewableenergyworld.com/power-grid/outage-management/ai-cameras-prevented-large-wildfire-utilities-say/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0090", "title": "Independent 2023-season verification finds GraphCast and three peer AI models match the best operational cyclone track models", "summary": "CIRA/Colorado State evaluation: GraphCast and three AI models match top operational cyclone track models in 2023; adding all four cut consensus error 11% at 120 h.", "date_observed": "2024-09-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Google DeepMind's GraphCast was run live on ECMWF's public charts from 2023. DeepMind's blog of 14 November 2023 says the live model predicted Hurricane Lee's landfall in Nova Scotia in September 2023 about nine days in advance. The blog says only “In September”, so the year is implied by its 14 November 2023 post date. The ECMWF publications read do not document the case. MIT Technology Review quoted ECMWF's Peter Dueben saying the models are so good they cannot be avoided. An independent CIRA/Colorado State evaluation applied NHC verification to May-November 2023 cyclones. It found GraphCast-operational and three other AI models' track errors comparable to the best operational models. Adding all four improved the NHC track consensus by 11% at 120 h.", "category": "general benefit", "unexpected": false, "purpose": "Medium-range global weather forecasting by machine learning, including severe-event prediction such as tropical cyclone tracks.", "system": "GraphCast (graph neural network global weather model)", "model_version": "GraphCast live experimental run on ECMWF charts (2023); GraphCast-operational in the CIRA evaluation", "developer": "DeepMind", "deployer": "ECMWF (experimental live runs on public charts); CIRA/Colorado State University (evaluation)", "location": null, "domain": "Weather forecasting / tropical cyclones", "segment": "Meteorological research and operational forecast centers", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Skill evaluation, no verified discrete event." }, { "group": "organizational", "depth": null, "reason": "Skill evaluation, no verified discrete event." }, { "group": "societal", "depth": null, "reason": "Skill evaluation, no verified discrete event." } ], "ai_role": { "status": "assessed", "statement": "The CIRA preprint isolates the AI models' contribution via NHC verification and consensus experiments. The nine-day Hurricane Lee landfall forecast rests on vendor statements and press quotes of ECMWF staff. ECMWF documents read (Newsletters 177 and 178, science blog, Severe Event Catalog) do not record it." }, "evidence": [ { "kind": "preprint", "citation": "DeMaria, M., Franklin, J. L., Chirokova, G., Radford, J., DeMaria, R., Musgrave, K. D., Ebert-Uphoff, I. (2024). Evaluation of Tropical Cyclone Track and Intensity Forecasts from Artificial Intelligence Weather Prediction (AIWP) Models. arXiv:2409.06735, submitted 8 Sep 2024; the preprint's disclaimer reads 'This work has been submitted to the Artificial Intelligence in the Earth Sciences American Meteorological Society journal'. The quote is on p. 23 of the full PDF, not on the abstract page.", "title": "Evaluation of Tropical Cyclone Track and Intensity Forecasts from AIWP Models", "url": "https://arxiv.org/abs/2409.06735", "date": "2024-09-08", "written_by": "independent", "quote": "When all four were added the track consensus improved by 11% at 120 h, with improvements that were statistically significant at 72-120 h." }, { "kind": "press release", "citation": "Google DeepMind (2023). GraphCast: AI model for faster and more accurate global weather forecasting. DeepMind blog, 14 November 2023.", "title": "GraphCast: AI model for faster and more accurate global weather forecasting", "url": "https://deepmind.google/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "date": "2023-11-14", "written_by": "makers", "quote": "a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia" }, { "kind": "preprint", "citation": "Lam, R., Sanchez-Gonzalez, A., Willson, M., et al. (2023). GraphCast: Learning skillful medium-range global weather forecasting. arXiv:2212.12794 (published in Science, 2023).", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "url": "https://arxiv.org/abs/2212.12794", "date": "2023-08-04", "written_by": "makers", "quote": "GraphCast significantly outperforms the most accurate operational deterministic systems on 90% of 1380 verification targets" }, { "kind": "news report", "citation": "MIT Technology Review (2023). Google DeepMind's weather AI can forecast extreme weather faster and more accurately. 14 November 2023.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately", "url": "https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "It showed that these models are so good that we cannot avoid them anymore." }, { "kind": "press release", "citation": "Rabier, F. (2023). The AIFS is launched (editorial). ECMWF Newsletter No. 177, Autumn 2023; the page states 'Published in October 2023' and its metadata dates it 16 October 2023.", "title": "The AIFS is launched", "url": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched", "date": "2023-10-16", "written_by": "deployer", "quote": "We have made these systems available on ECMWF's public charts pages, based on our own initial conditions." }, { "kind": "preprint", "citation": "Charlton-Perez, A. J., Dacre, H. F., Driscoll, S., et al. (2024). Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciaran. arXiv:2312.02658 (University of Reading).", "title": "Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciaran", "url": "https://arxiv.org/abs/2312.02658", "date": "2024-02-19", "written_by": "independent", "quote": "accurately capture the synoptic-scale structure of the cyclone" }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "AI models initialized from operational NWP analyses and run alongside physics-based models", "Verification using the NHC procedure, including early-model conversion and consensus experiments" ], "must_hold": [ "Track skill does not extend to intensity: the CIRA preprint reports a substantial low intensity bias", "Independent case evaluation (Storm Ciaran) found peak winds underestimated by all AI models tested" ], "echoes": [ { "date": "2023-11-02", "setting": "Storm Ciaran, northern Europe: AI models captured synoptic structure but underestimated peak winds (independent evaluation)", "model_version": "GraphCast, Pangu-Weather, FourCastNet, FourCastNet-v2", "outcome": "unknown", "source": "https://arxiv.org/abs/2312.02658" }, { "date": "2026-03-30", "setting": "NHC 2025 verification: a newer Google DeepMind ensemble (GDMI) outperformed official Atlantic track forecasts at 12–72 h", "model_version": null, "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "severity": null, "group": "societal", "basis": "Google's AI-based earthquake alert system underestimated hazard magnitude; same developer family and hazard-prediction task as DeepMind's GraphCast cyclone forecasts, harming the exposed public." }, "headline": "GraphCast matches best operational cyclone track models in 2023", "metric": "adding all four improved the NHC track consensus by 11% at 120 h", "comparator": { "against": "the NHC track consensus without the four AI models, benchmarked against the long-term improvement of official forecasts", "before": "consensus track errors without the AIWP models; official five-day track forecasts improving by about 2% per year since 2001", "after": "consensus track errors reduced by up to 11% at the longer time periods", "basis": "measured", "quote": "The consensus track errors are reduced by up to 11% at the longer time periods. The five-day NHC official track forecasts have improved by about 2% per year since 2001, so this represents more than a five-year gain in accuracy.", "url": "https://arxiv.org/abs/2409.06735" }, "later": { "status": "scaled", "date": "2026-03-30", "note": "By the 2025 season NHC had brought AI-based models, including a newer Google DeepMind ensemble, into real-time operations, per its verification report.", "quote": "The 2025 season marked the first time that NHC incorporated AI-based models into real-time operations.", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Dated the ECMWF Newsletter editorial 16 October 2023 from the page metadata because the page gives only “October 2023”, replaced the account's “1 September is used” parenthetical, which contradicted the date observed, with the blog's own “In September” wording, and quoted the CIRA preprint's disclaimer on the journal it was submitted to, locating the quote on p. 23 of the PDF, in place of the misnamed journal.", "source": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched; https://deepmind.google/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/; https://arxiv.org/abs/2409.06735", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://arxiv.org/abs/2409.06735; https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://en.wikipedia.org/wiki/European_Centre_for_Medium-Range_Weather_Forecasts", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, one independent news report, two independent preprints, the makers' preprint, the makers' press release and the deployer's press release. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0090", "catalog_version": "1.0.0", "source_fingerprint": "bb38f03334646e6b0f7f149482e370293906d58328dbd4d492e74f7d7631f631", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0090-source-0001", "AIBD-0090-source-0002", "AIBD-0090-source-0003", "AIBD-0090-source-0004", "AIBD-0090-source-0005", "AIBD-0090-source-0006", "AIBD-0090-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepMind", "deployer": "ECMWF (experimental live runs on public charts); CIRA/Colorado State University (evaluation)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The CIRA preprint isolates the AI models' contribution via NHC verification and consensus experiments. The nine-day Hurricane Lee landfall forecast rests on vendor statements and press quotes of ECMWF staff. ECMWF documents read (Newsletters 177 and 178, science blog, Severe Event Catalog) do not record it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The CIRA preprint isolates the AI models' contribution via NHC verification and consensus experiments. The nine-day Hurricane Lee landfall forecast rests on vendor statements and press quotes of ECMWF staff. 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A quantitative evaluation case study of Storm Ciaran", "url": "https://arxiv.org/abs/2312.02658", "date": "2024-02-19", "written_by": "independent", "quote": "accurately capture the synoptic-scale structure of the cyclone" }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0090-source-0001", "AIBD-0090-source-0002", "AIBD-0090-source-0003", "AIBD-0090-source-0004", "AIBD-0090-source-0005", "AIBD-0090-source-0006", "AIBD-0090-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "preprint", "citation": "DeMaria, M., Franklin, J. L., Chirokova, G., Radford, J., DeMaria, R., Musgrave, K. D., Ebert-Uphoff, I. (2024). Evaluation of Tropical Cyclone Track and Intensity Forecasts from Artificial Intelligence Weather Prediction (AIWP) Models. arXiv:2409.06735, submitted 8 Sep 2024; the preprint's disclaimer reads 'This work has been submitted to the Artificial Intelligence in the Earth Sciences American Meteorological Society journal'. The quote is on p. 23 of the full PDF, not on the abstract page.", "title": "Evaluation of Tropical Cyclone Track and Intensity Forecasts from AIWP Models", "url": "https://arxiv.org/abs/2409.06735", "date": "2024-09-08", "written_by": "independent", "quote": "When all four were added the track consensus improved by 11% at 120 h, with improvements that were statistically significant at 72-120 h." }, { "kind": "press release", "citation": "Google DeepMind (2023). GraphCast: AI model for faster and more accurate global weather forecasting. DeepMind blog, 14 November 2023.", "title": "GraphCast: AI model for faster and more accurate global weather forecasting", "url": "https://deepmind.google/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/", "date": "2023-11-14", "written_by": "makers", "quote": "a live version of our publicly available GraphCast model, deployed on the ECMWF website, accurately predicted about nine days in advance that Hurricane Lee would make landfall in Nova Scotia" }, { "kind": "preprint", "citation": "Lam, R., Sanchez-Gonzalez, A., Willson, M., et al. (2023). GraphCast: Learning skillful medium-range global weather forecasting. arXiv:2212.12794 (published in Science, 2023).", "title": "GraphCast: Learning skillful medium-range global weather forecasting", "url": "https://arxiv.org/abs/2212.12794", "date": "2023-08-04", "written_by": "makers", "quote": "GraphCast significantly outperforms the most accurate operational deterministic systems on 90% of 1380 verification targets" }, { "kind": "news report", "citation": "MIT Technology Review (2023). Google DeepMind's weather AI can forecast extreme weather faster and more accurately. 14 November 2023.", "title": "Google DeepMind's weather AI can forecast extreme weather faster and more accurately", "url": "https://www.technologyreview.com/2023/11/14/1083366/google-deepminds-weather-ai-can-forecast-extreme-weather-quicker-and-more-accurately/", "date": "2023-11-14", "written_by": "independent", "quote": "It showed that these models are so good that we cannot avoid them anymore." }, { "kind": "press release", "citation": "Rabier, F. (2023). The AIFS is launched (editorial). ECMWF Newsletter No. 177, Autumn 2023; the page states 'Published in October 2023' and its metadata dates it 16 October 2023.", "title": "The AIFS is launched", "url": "https://www.ecmwf.int/en/newsletter/177/editorial/aifs-launched", "date": "2023-10-16", "written_by": "deployer", "quote": "We have made these systems available on ECMWF's public charts pages, based on our own initial conditions." }, { "kind": "preprint", "citation": "Charlton-Perez, A. J., Dacre, H. F., Driscoll, S., et al. (2024). Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciaran. arXiv:2312.02658 (University of Reading).", "title": "Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciaran", "url": "https://arxiv.org/abs/2312.02658", "date": "2024-02-19", "written_by": "independent", "quote": "accurately capture the synoptic-scale structure of the cyclone" }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CIRA/Colorado State evaluation: GraphCast and three AI models match top operational cyclone track models in 2023; adding all four cut consensus error 11% at 120 h.", "account": "Google DeepMind's GraphCast was run live on ECMWF's public charts from 2023. DeepMind's blog of 14 November 2023 says the live model predicted Hurricane Lee's landfall in Nova Scotia in September 2023 about nine days in advance. The blog says only “In September”, so the year is implied by its 14 November 2023 post date. The ECMWF publications read do not document the case. MIT Technology Review quoted ECMWF's Peter Dueben saying the models are so good they cannot be avoided. An independent CIRA/Colorado State evaluation applied NHC verification to May-November 2023 cyclones. It found GraphCast-operational and three other AI models' track errors comparable to the best operational models. 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No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The event concerned GraphCast’s live experimental forecasts on ECMWF charts in 2023. The CIRA evaluation used GraphCast-operational." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GraphCast." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GraphCast live experimental run on ECMWF charts (2023); GraphCast-operational in the CIRA evaluation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "GraphCast (graph neural network global weather model)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Independent 2023-season verification finds GraphCast and three peer AI models match the best operational cyclone track models", "headline": "GraphCast matches best operational cyclone track models in 2023" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "bb38f03334646e6b0f7f149482e370293906d58328dbd4d492e74f7d7631f631" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Google DeepMind's GraphCast was run live on ECMWF's public charts from 2023. DeepMind's blog of 14 November 2023 says the live model predicted Hurricane Lee's landfall in Nova Scotia in September 2023 about nine days in advance. The blog says only “In September”, so the year is implied by its 14 November 2023 post date. The ECMWF publications read do not document the case. MIT Technology Review quoted ECMWF's Peter Dueben saying the models are so good they cannot be avoided. An independent CIRA/Colorado State evaluation applied NHC verification to May-November 2023 cyclones. It found GraphCast-operational and three other AI models' track errors comparable to the best operational models. Adding all four improved the NHC track consensus by 11% at 120 h.", "replication": { "produced_by": [ "AI models initialized from operational NWP analyses and run alongside physics-based models", "Verification using the NHC procedure, including early-model conversion and consensus experiments" ], "must_hold": [ "Track skill does not extend to intensity: the CIRA preprint reports a substantial low intensity bias", "Independent case evaluation (Storm Ciaran) found peak winds underestimated by all AI models tested" ], "echoes": [ { "date": "2023-11-02", "setting": "Storm Ciaran, northern Europe: AI models captured synoptic structure but underestimated peak winds (independent evaluation)", "model_version": "GraphCast, Pangu-Weather, FourCastNet, FourCastNet-v2", "outcome": "unknown", "source": "https://arxiv.org/abs/2312.02658" }, { "date": "2026-03-30", "setting": "NHC 2025 verification: a newer Google DeepMind ensemble (GDMI) outperformed official Atlantic track forecasts at 12–72 h", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0380", "title": "Kunshan police “AI police” models flag a mobile gambling ring at Zhouzhuang, 20-plus arrested on 10 September 2024, and trace a telecom fraud's card transfers to freeze 500,000 yuan within 10 minutes", "summary": "Kunshan police say their “AI police” models led a 10 September 2024 bust of a mobile gambling ring (20-plus arrests) and froze 500,000 yuan of a 980,000-yuan telecom fraud within 10 minutes.", "date_observed": "2024-09-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 10 September 2024, the Kunshan Public Security Bureau in Jiangsu broke up a gang running a mobile open-air casino in Zhouzhuang town. It arrested over 20 suspects. Modern Express reported that the “AI police” had found the ring (NetEase reprint, 6 October 2024). These are models that detect outdoor gambling from behavioral patterns in bulk data. In a telecom fraud handled by the Lujia police station, a victim lost 980,000 yuan. The models traced three tiers of card transfers and froze 500,000 yuan within 10 minutes. They identified 87 suspect accounts within 8 hours. Nine suspects were arrested on the third day with 200,000 yuan recovered (Suzhou Daily via suzhou.gov.cn, 7 October 2024). The models were built by the “Kunpeng Squad”, 35 officers assembled in May 2024. They report over 220 models and, over six months, 609 fraud cases solved and 32.47 million yuan recovered (both sources). All figures are the police's own.", "category": "benefit created", "unexpected": false, "purpose": "Models built by the Kunshan police to detect crime patterns and trace funds for investigators. The bust and the freeze were that purpose.", "system": "Kunshan Public Security Bureau 'AI police' (AI警察): more than 220 'main-attack, main-defense' intelligent models built by the Kunpeng Squad", "model_version": null, "developer": "Kunshan Public Security Bureau, Kunpeng Squad (鲲鹏战队), with Suzhou Public Security Bureau support", "deployer": "Kunshan Public Security Bureau", "location": "Kunshan, China", "domain": "Law enforcement / criminal investigation", "segment": "Gambling rings and telecom fraud", "benefit_type": "Reduced Risk", "taxonomy_note": "The quantified outcome is a fraud loss partly averted (500,000 yuan frozen), which is Reduced Risk; the dated gambling bust is a crime stopped, Trustible's Reduced Violence, but the offense was nonviolent.", "registry_ids": { "oecd_aim": "2024-10-03-edf0" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "The fraud victim who lost 980,000 yuan had 500,000 yuan frozen within 10 minutes and 200,000 yuan recovered after the arrests, per the police. Whether the frozen sum was returned is not reported." }, { "group": "organizational", "depth": 2, "reason": "The Kunshan bureau reports a 20-plus-suspect bust, nine fraud arrests in three days and 609 fraud cases solved in six months, recovery rates up 62%. A measurable gain for the unit, on its own figures." }, { "group": "societal", "depth": null, "reason": "The six-month aggregate of 32.47 million yuan recovered is the deployer's own claim with no method or independent check, so no population effect is established." } ], "ai_role": { "status": "assessed", "statement": "Both accounts are the police's. They credit the models with flagging the outdoor casino from behavioral features in bulk data and mapping the ring's structure “with one click”. They also traced card-tier fund flows in parallel, so a freeze came within 10 minutes. Officers made the arrests and freeze requests. Deputy criminal-investigation chief He Yongliang describes the gain as 24-hour, parallel rather than serial casework. Neither source separates the models' share from ordinary investigation." }, "evidence": [ { "kind": "news report", "citation": "Ji, Y. (2024). 江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”. Modern Express (现代快报) via NetEase, October 6, 2024.", "title": "江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”", "url": "https://m.163.com/dy/article/JDQORBU7053469KC.html", "date": "2024-10-06", "written_by": "independent", "quote": "仅用10分钟，'AI警察'就追踪到三级卡资金流向，并成功止付50万元" }, { "kind": "news report", "citation": "Suzhou Daily (2024). 昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力. Suzhou Municipal People's Government website, October 7, 2024.", "title": "昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力", "url": "https://www.suzhou.gov.cn/2024ndzt/mtjjxzc/202410/41e0e0bc1a8843ebb55e2a0d54f44bf5.shtml", "date": "2024-10-07", "written_by": "deployer", "quote": "AI警察的应用为改进治理提供了一条新的路径" }, { "kind": "registry label", "citation": "OECD.AI (2024). AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention. OECD AI Incidents and Hazards Monitor, 2024-10-03.", "title": "AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention", "url": "https://oecd.ai/en/incidents/2024-10-03-edf0", "date": "2024-10-03", "written_by": "independent", "quote": "deployed AI-driven policing systems ('AI police') to identify and dismantle a mobile gambling ring, arresting over 20 suspects" } ], "replication": { "produced_by": [ "Bulk police data on gambling and payment behavior that models can score for anomalies", "A dedicated squad of officers who build and run models inside the bureau", "Bank cooperation that lets a traced account be frozen within minutes" ], "must_hold": [ "Officers verify each model flag and make the arrests and freeze requests themselves", "Figures are the deployer's own; an outside audit would be needed to confirm them" ], "echoes": [] }, "paired_incident": null, "headline": "Kunshan police AI flags gambling ring and freezes fraud transfers", "metric": "traced three tiers of card transfers and froze 500,000 yuan within 10 minutes", "comparator": null, "later": null, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2024-10-03-edf0", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Kunshan; https://en.wikipedia.org/wiki/Kunshan", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0380", "catalog_version": "1.0.0", "source_fingerprint": "8c7fdbc00abd5b816b15e4d1333369ff72f148a42c84cfe1d89d009021d6bde6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0380-source-0001", "AIBD-0380-source-0002", "AIBD-0380-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Kunshan Public Security Bureau, Kunpeng Squad (鲲鹏战队), with Suzhou Public Security Bureau support", "deployer": "Kunshan Public Security Bureau" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Both accounts are the police's. They credit the models with flagging the outdoor casino from behavioral features in bulk data and mapping the ring's structure “with one click”. They also traced card-tier fund flows in parallel, so a freeze came within 10 minutes. Officers made the arrests and freeze requests. Deputy criminal-investigation chief He Yongliang describes the gain as 24-hour, parallel rather than serial casework. Neither source separates the models' share from ordinary investigation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Both accounts are the police's. They credit the models with flagging the outdoor casino from behavioral features in bulk data and mapping the ring's structure “with one click”. They also traced card-tier fund flows in parallel, so a freeze came within 10 minutes. Officers made the arrests and freeze requests. Deputy criminal-investigation chief He Yongliang describes the gain as 24-hour, parallel rather than serial casework. Neither source separates the models' share from ordinary investigation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The fraud victim who lost 980,000 yuan had 500,000 yuan frozen within 10 minutes and 200,000 yuan recovered after the arrests, per the police. Whether the frozen sum was returned is not reported." }, { "group": "organizational", "depth": 2, "reason": "The Kunshan bureau reports a 20-plus-suspect bust, nine fraud arrests in three days and 609 fraud cases solved in six months, recovery rates up 62%. A measurable gain for the unit, on its own figures." }, { "group": "societal", "reason": "The six-month aggregate of 32.47 million yuan recovered is the deployer's own claim with no method or independent check, so no population effect is established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, a registry entry and the deployer's news report. 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"kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "The quantified outcome is a fraud loss partly averted (500,000 yuan frozen), which is Reduced Risk; the dated gambling bust is a crime stopped, Trustible's Reduced Violence, but the offense was nonviolent." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 10 September 2024, the Kunshan Public Security Bureau in Jiangsu broke up a gang running a mobile open-air casino in Zhouzhuang town. It arrested over 20 suspects. Modern Express reported that the “AI police” had found the ring (NetEase reprint, 6 October 2024). These are models that detect outdoor gambling from behavioral patterns in bulk data. In a telecom fraud handled by the Lujia police station, a victim lost 980,000 yuan. The models traced three tiers of card transfers and froze 500,000 yuan within 10 minutes. They identified 87 suspect accounts within 8 hours. Nine suspects were arrested on the third day with 200,000 yuan recovered (Suzhou Daily via suzhou.gov.cn, 7 October 2024). The models were built by the “Kunpeng Squad”, 35 officers assembled in May 2024. They report over 220 models and, over six months, 609 fraud cases solved and 32.47 million yuan recovered (both sources). 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Whether the frozen sum was returned is not reported." }, { "group": "organizational", "depth": 2, "reason": "The Kunshan bureau reports a 20-plus-suspect bust, nine fraud arrests in three days and 609 fraud cases solved in six months, recovery rates up 62%. 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(2024). 江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”. Modern Express (现代快报) via NetEase, October 6, 2024.", "title": "江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”", "url": "https://m.163.com/dy/article/JDQORBU7053469KC.html", "date": "2024-10-06", "written_by": "independent", "quote": "仅用10分钟，'AI警察'就追踪到三级卡资金流向，并成功止付50万元" }, { "kind": "news report", "citation": "Suzhou Daily (2024). 昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力. Suzhou Municipal People's Government website, October 7, 2024.", "title": "昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力", "url": "https://www.suzhou.gov.cn/2024ndzt/mtjjxzc/202410/41e0e0bc1a8843ebb55e2a0d54f44bf5.shtml", "date": "2024-10-07", "written_by": "deployer", "quote": "AI警察的应用为改进治理提供了一条新的路径" }, { "kind": "registry label", "citation": "OECD.AI (2024). AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention. OECD AI Incidents and Hazards Monitor, 2024-10-03.", "title": "AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention", "url": "https://oecd.ai/en/incidents/2024-10-03-edf0", "date": "2024-10-03", "written_by": "independent", "quote": "deployed AI-driven policing systems ('AI police') to identify and dismantle a mobile gambling ring, arresting over 20 suspects" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0380-source-0001", "AIBD-0380-source-0002", "AIBD-0380-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Ji, Y. (2024). 江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”. Modern Express (现代快报) via NetEase, October 6, 2024.", "title": "江苏昆山公安：“AI警察”上岗 “算力”引爆“战力”", "url": "https://m.163.com/dy/article/JDQORBU7053469KC.html", "date": "2024-10-06", "written_by": "independent", "quote": "仅用10分钟，'AI警察'就追踪到三级卡资金流向，并成功止付50万元" }, { "kind": "news report", "citation": "Suzhou Daily (2024). 昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力. Suzhou Municipal People's Government website, October 7, 2024.", "title": "昆山警方释放出“专业+机制+大数据”新型警务运行模式强大新质战力", "url": "https://www.suzhou.gov.cn/2024ndzt/mtjjxzc/202410/41e0e0bc1a8843ebb55e2a0d54f44bf5.shtml", "date": "2024-10-07", "written_by": "deployer", "quote": "AI警察的应用为改进治理提供了一条新的路径" }, { "kind": "registry label", "citation": "OECD.AI (2024). AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention. OECD AI Incidents and Hazards Monitor, 2024-10-03.", "title": "AI Police Deployed in Kunshan, China, Lead to Major Crime Busts and Fraud Prevention", "url": "https://oecd.ai/en/incidents/2024-10-03-edf0", "date": "2024-10-03", "written_by": "independent", "quote": "deployed AI-driven policing systems ('AI police') to identify and dismantle a mobile gambling ring, arresting over 20 suspects" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Kunshan police say their “AI police” models led a 10 September 2024 bust of a mobile gambling ring (20-plus arrests) and froze 500,000 yuan of a 980,000-yuan telecom fraud within 10 minutes.", "account": "On 10 September 2024, the Kunshan Public Security Bureau in Jiangsu broke up a gang running a mobile open-air casino in Zhouzhuang town. It arrested over 20 suspects. Modern Express reported that the “AI police” had found the ring (NetEase reprint, 6 October 2024). These are models that detect outdoor gambling from behavioral patterns in bulk data. In a telecom fraud handled by the Lujia police station, a victim lost 980,000 yuan. The models traced three tiers of card transfers and froze 500,000 yuan within 10 minutes. They identified 87 suspect accounts within 8 hours. Nine suspects were arrested on the third day with 200,000 yuan recovered (Suzhou Daily via suzhou.gov.cn, 7 October 2024). The models were built by the “Kunpeng Squad”, 35 officers assembled in May 2024. They report over 220 models and, over six months, 609 fraud cases solved and 32.47 million yuan recovered (both sources). All figures are the police's own." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Kunshan Public Security Bureau 'AI police' (AI警察): more than 220 'main-attack, main-defense' intelligent models built by the Kunpeng Squad" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Kunshan Public Security Bureau, Kunpeng Squad (鲲鹏战队), with Suzhou Public Security Bureau support" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kunshan police “AI police” models flag a mobile gambling ring at Zhouzhuang, 20-plus arrested on 10 September 2024, and trace a telecom fraud's card transfers to freeze 500,000 yuan within 10 minutes", "headline": "Kunshan police AI flags gambling ring and freezes fraud transfers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8c7fdbc00abd5b816b15e4d1333369ff72f148a42c84cfe1d89d009021d6bde6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 10 September 2024, the Kunshan Public Security Bureau in Jiangsu broke up a gang running a mobile open-air casino in Zhouzhuang town. It arrested over 20 suspects. Modern Express reported that the “AI police” had found the ring (NetEase reprint, 6 October 2024). These are models that detect outdoor gambling from behavioral patterns in bulk data. In a telecom fraud handled by the Lujia police station, a victim lost 980,000 yuan. The models traced three tiers of card transfers and froze 500,000 yuan within 10 minutes. They identified 87 suspect accounts within 8 hours. Nine suspects were arrested on the third day with 200,000 yuan recovered (Suzhou Daily via suzhou.gov.cn, 7 October 2024). The models were built by the “Kunpeng Squad”, 35 officers assembled in May 2024. They report over 220 models and, over six months, 609 fraud cases solved and 32.47 million yuan recovered (both sources). All figures are the police's own.", "replication": { "produced_by": [ "Bulk police data on gambling and payment behavior that models can score for anomalies", "A dedicated squad of officers who build and run models inside the bureau", "Bank cooperation that lets a traced account be frozen within minutes" ], "must_hold": [ "Officers verify each model flag and make the arrests and freeze requests themselves", "Figures are the deployer's own; an outside audit would be needed to confirm them" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0357", "title": "Kenya Wildlife Service installs AI-enabled FLIR thermal cameras at Solio, Lake Nakuru and Ol Pejeta to send intrusion alerts to rhino rangers", "summary": "KWS installed AI-enabled FLIR thermal cameras at three black rhino sites by Sept 2024 (US State Department and WWF funding); intrusion alerts only; no AI-linked arrest or prevented event documented.", "date_observed": "2024-09-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Citizen Digital reported on 21 September 2024 that the Kenya Wildlife Service (KWS) had installed FLIR thermal cameras at three black rhino sites. The US Department of State Bureau of International Narcotics and Law Enforcement Affairs and WWF supported it. They are Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, with Solio the latest and Meru National Park named next. Geoffrey Chege (WWF-Kenya) said the cameras “have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife”. Colby Loucks of WWF-US said the cameras “can tell you when a human is in the picture or an animal” and alert rangers. KWS Director General Dr Erustus Kanga said: “I am aware that over the last six years, we have not lost a single black rhino in this sanctuary”. That predates the Solio installation. The article reports no arrest, interception or prevented poaching event attributable to the cameras.", "category": "general benefit", "unexpected": false, "purpose": "Automated night-time detection of human and vehicle intrusion at rhino sanctuaries to alert rangers. The claimed benefit is the intended one.", "system": "Teledyne FLIR thermal cameras with on-board AI analytics for human, vehicle and animal classification and automated ranger alerts", "model_version": null, "developer": "Teledyne FLIR (camera analytics; developer named only as FLIR in the cited source)", "deployer": "Kenya Wildlife Service with WWF-Kenya, WWF-US and WWF-UK; Solio Game Reserve management", "location": "Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, Kenya", "domain": "Wildlife protection and anti-poaching", "segment": "National wildlife authority and private conservancies", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "Intrusion alerts at rhino sites protect an endangered species, which Trustible's description reaches only as “improved environment”; no interception is documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary or ranger outcome is documented." }, { "group": "organizational", "depth": null, "reason": "KWS reports installation and intent, not a detected intrusion or response." }, { "group": "societal", "depth": null, "reason": "Kenya's reduced poaching figures cited in the article are not linked to the cameras." } ], "ai_role": { "status": "assessed", "statement": "The sole cited source is one news report (Citizen Digital, 21 September 2024). It describes AI analytics that classify humans, vehicles and animals in thermal video and alert rangers automatically. The statements come from WWF and KWS officials at the handover ceremony. No alert, arrest or prevented poaching event is attributed to the system in any cited source. Its contribution to rhino protection is not established." }, "evidence": [ { "kind": "news report", "citation": "Citizen Reporter (2024). KWS, rhino sites using AI-enabled cameras to stop black rhino poaching. Citizen Digital, 21 Sep 2024.", "title": "KWS, rhino sites using AI-enabled cameras to stop black rhino poaching", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "The artificial intelligence-enabled FLIR cameras have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, KWS Director General Dr Erustus Kanga quoted.", "title": "KWS, rhino sites using AI-enabled cameras (Director General statement)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "I am aware that over the last six years, we have not lost a single black rhino in this sanctuary." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, funding statement.", "title": "KWS, rhino sites using AI-enabled cameras (funding)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "came from the US State Department through WWF US and the WWF UK" } ], "replication": { "produced_by": [ "Thermal cameras with on-board human/vehicle/animal analytics at sanctuary perimeters", "Ranger teams receiving automated alerts", "Donor funding (US State Department INL via WWF) for installation and upgrades" ], "must_hold": [ "Camera coverage of intrusion routes", "Ranger response capacity at night", "Maintenance and power at remote sites", "Evaluation that records alerts and responses, absent so far" ], "echoes": [ { "date": null, "setting": "Lake Nakuru National Park camera system upgraded under the same program", "model_version": null, "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" }, { "date": null, "setting": "Meru National Park named as the next installation site", "model_version": null, "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" } ] }, "paired_incident": null, "headline": "KWS's FLIR cameras send intrusion alerts at three rhino sites", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The article names Meru National Park as the next site; nothing dated after 21 September 2024 was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Kenya", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Teledyne_FLIR; https://en.wikipedia.org/wiki/Kenya_Wildlife_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0357", "catalog_version": "1.0.0", "source_fingerprint": "78575ef230d9f2d3194cbfda50cc133cbbe7be7f6d3e448b16246f06635e3eff", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0357-source-0001", "AIBD-0357-source-0002", "AIBD-0357-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Teledyne FLIR (camera analytics; developer named only as FLIR in the cited source)", "deployer": "Kenya Wildlife Service with WWF-Kenya, WWF-US and WWF-UK; Solio Game Reserve management" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The sole cited source is one news report (Citizen Digital, 21 September 2024). It describes AI analytics that classify humans, vehicles and animals in thermal video and alert rangers automatically. The statements come from WWF and KWS officials at the handover ceremony. No alert, arrest or prevented poaching event is attributed to the system in any cited source. Its contribution to rhino protection is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The sole cited source is one news report (Citizen Digital, 21 September 2024). It describes AI analytics that classify humans, vehicles and animals in thermal video and alert rangers automatically. The statements come from WWF and KWS officials at the handover ceremony. No alert, arrest or prevented poaching event is attributed to the system in any cited source. Its contribution to rhino protection is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or ranger outcome is documented." }, { "group": "organizational", "reason": "KWS reports installation and intent, not a detected intrusion or response." }, { "group": "societal", "reason": "Kenya's reduced poaching figures cited in the article are not linked to the cameras." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or ranger outcome is documented." }, { "group": "organizational", "reason": "KWS reports installation and intent, not a detected intrusion or response." }, { "group": "societal", "reason": "Kenya's reduced poaching figures cited in the article are not linked to the cameras." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The article names Meru National Park as the next site; nothing dated after 21 September 2024 was found in the cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0357" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "Intrusion alerts at rhino sites protect an endangered species, which Trustible's description reaches only as “improved environment”; no interception is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Citizen Digital reported on 21 September 2024 that the Kenya Wildlife Service (KWS) had installed FLIR thermal cameras at three black rhino sites. The US Department of State Bureau of International Narcotics and Law Enforcement Affairs and WWF supported it. They are Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, with Solio the latest and Meru National Park named next. Geoffrey Chege (WWF-Kenya) said the cameras “have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife”. Colby Loucks of WWF-US said the cameras “can tell you when a human is in the picture or an animal” and alert rangers. KWS Director General Dr Erustus Kanga said: “I am aware that over the last six years, we have not lost a single black rhino in this sanctuary”. That predates the Solio installation. The article reports no arrest, interception or prevented poaching event attributable to the cameras.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary or ranger outcome is documented." }, { "group": "organizational", "reason": "KWS reports installation and intent, not a detected intrusion or response." }, { "group": "societal", "reason": "Kenya's reduced poaching figures cited in the article are not linked to the cameras." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Automated night-time detection of human and vehicle intrusion at rhino sanctuaries to alert rangers. The claimed benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, Kenya", "developer_country": "United States", "deployer_country": "Kenya" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Automated night-time detection of human and vehicle intrusion at rhino sanctuaries to alert rangers. The claimed benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-09-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Teledyne_FLIR; https://en.wikipedia.org/wiki/Kenya_Wildlife_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Thermal cameras with on-board human/vehicle/animal analytics at sanctuary perimeters", "Ranger teams receiving automated alerts", "Donor funding (US State Department INL via WWF) for installation and upgrades" ], "must_hold": [ "Camera coverage of intrusion routes", "Ranger response capacity at night", "Maintenance and power at remote sites", "Evaluation that records alerts and responses, absent so far" ], "echoes": [ { "setting": "Lake Nakuru National Park camera system upgraded under the same program", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" }, { "setting": "Meru National Park named as the next installation site", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Thermal cameras with on-board human/vehicle/animal analytics at sanctuary perimeters", "Ranger teams receiving automated alerts", "Donor funding (US State Department INL via WWF) for installation and upgrades" ], "must_hold": [ "Camera coverage of intrusion routes", "Ranger response capacity at night", "Maintenance and power at remote sites", "Evaluation that records alerts and responses, absent so far" ], "echoes": [ { "setting": "Lake Nakuru National Park camera system upgraded under the same program", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" }, { "setting": "Meru National Park named as the next installation site", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Teledyne_FLIR; https://en.wikipedia.org/wiki/Kenya_Wildlife_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Wildlife protection and anti-poaching", "segment": "National wildlife authority and private conservancies" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Citizen Reporter (2024). KWS, rhino sites using AI-enabled cameras to stop black rhino poaching. Citizen Digital, 21 Sep 2024.", "title": "KWS, rhino sites using AI-enabled cameras to stop black rhino poaching", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "The artificial intelligence-enabled FLIR cameras have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, KWS Director General Dr Erustus Kanga quoted.", "title": "KWS, rhino sites using AI-enabled cameras (Director General statement)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "I am aware that over the last six years, we have not lost a single black rhino in this sanctuary." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, funding statement.", "title": "KWS, rhino sites using AI-enabled cameras (funding)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "came from the US State Department through WWF US and the WWF UK" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0357-source-0001", "AIBD-0357-source-0002", "AIBD-0357-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Citizen Reporter (2024). KWS, rhino sites using AI-enabled cameras to stop black rhino poaching. Citizen Digital, 21 Sep 2024.", "title": "KWS, rhino sites using AI-enabled cameras to stop black rhino poaching", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "The artificial intelligence-enabled FLIR cameras have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, KWS Director General Dr Erustus Kanga quoted.", "title": "KWS, rhino sites using AI-enabled cameras (Director General statement)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "I am aware that over the last six years, we have not lost a single black rhino in this sanctuary." }, { "kind": "news report", "citation": "Citizen Reporter (2024). Same article, funding statement.", "title": "KWS, rhino sites using AI-enabled cameras (funding)", "url": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961", "date": "2024-09-21", "written_by": "independent", "quote": "came from the US State Department through WWF US and the WWF UK" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "KWS installed AI-enabled FLIR thermal cameras at three black rhino sites by Sept 2024 (US State Department and WWF funding); intrusion alerts only; no AI-linked arrest or prevented event documented.", "account": "Citizen Digital reported on 21 September 2024 that the Kenya Wildlife Service (KWS) had installed FLIR thermal cameras at three black rhino sites. The US Department of State Bureau of International Narcotics and Law Enforcement Affairs and WWF supported it. They are Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, with Solio the latest and Meru National Park named next. Geoffrey Chege (WWF-Kenya) said the cameras “have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife”. Colby Loucks of WWF-US said the cameras “can tell you when a human is in the picture or an animal” and alert rangers. KWS Director General Dr Erustus Kanga said: “I am aware that over the last six years, we have not lost a single black rhino in this sanctuary”. That predates the Solio installation. The article reports no arrest, interception or prevented poaching event attributable to the cameras." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Teledyne FLIR thermal cameras with on-board AI analytics for human, vehicle and animal classification and automated ranger alerts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Teledyne FLIR (camera analytics; developer named only as FLIR in the cited source)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kenya Wildlife Service installs AI-enabled FLIR thermal cameras at Solio, Lake Nakuru and Ol Pejeta to send intrusion alerts to rhino rangers", "headline": "KWS's FLIR cameras send intrusion alerts at three rhino sites" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "78575ef230d9f2d3194cbfda50cc133cbbe7be7f6d3e448b16246f06635e3eff" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Citizen Digital reported on 21 September 2024 that the Kenya Wildlife Service (KWS) had installed FLIR thermal cameras at three black rhino sites. The US Department of State Bureau of International Narcotics and Law Enforcement Affairs and WWF supported it. They are Solio Game Reserve, Lake Nakuru National Park and Ol Pejeta Conservancy, with Solio the latest and Meru National Park named next. Geoffrey Chege (WWF-Kenya) said the cameras “have inbuilt analytics that send out automated alerts every time they detect an intrusion from humans, vehicles or wildlife”. Colby Loucks of WWF-US said the cameras “can tell you when a human is in the picture or an animal” and alert rangers. KWS Director General Dr Erustus Kanga said: “I am aware that over the last six years, we have not lost a single black rhino in this sanctuary”. That predates the Solio installation. The article reports no arrest, interception or prevented poaching event attributable to the cameras.", "replication": { "produced_by": [ "Thermal cameras with on-board human/vehicle/animal analytics at sanctuary perimeters", "Ranger teams receiving automated alerts", "Donor funding (US State Department INL via WWF) for installation and upgrades" ], "must_hold": [ "Camera coverage of intrusion routes", "Ranger response capacity at night", "Maintenance and power at remote sites", "Evaluation that records alerts and responses, absent so far" ], "echoes": [ { "setting": "Lake Nakuru National Park camera system upgraded under the same program", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" }, { "setting": "Meru National Park named as the next installation site", "outcome": "unknown", "source": "https://www.citizen.digital/news/kws-rhino-sites-using-ai-enabled-cameras-to-stop-black-rhino-poaching-n349961" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0144", "title": "Blackpool Council's Project Amber imagery and AI road surveys: 5,145 potholes filled for about £450,000 and pothole claim payouts down to £719", "summary": "Blackpool's Project Amber imagery/AI surveys: 5,145 potholes filled for ~£450k; pothole claim payouts fell to £719 (DfT, 2024)", "date_observed": "2024-09-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Blackpool Council's Project Amber, launched in 2019 under the Local Council Roads Innovation Group, uses high-definition road imagery to detect potholes and prioritize repairs. The Blackpool Unlimited page calls it artificial-intelligence technology piloted in Anchorsholme and Bispham. It states that since summer 2019, 5,145 potholes were filled in North Shore for just under £450,000 against £1.5 million by traditional methods. The Department for Transport's release of 26 September 2024 says Blackpool was the first authority to use the technology. It had paid up to £1.5 million a year to settle pothole claims and “last year” paid out only £719. The release dates the work only as “last year”. The reduction is credited to the whole program, including surface treatments.", "category": "general benefit", "unexpected": false, "purpose": "Survey road condition from imagery to find and prioritize pothole and surface defects for repair", "system": "Project Amber road-condition imagery and AI survey (Blackpool Council)", "model_version": null, "developer": null, "deployer": "Blackpool Council", "location": "Blackpool, United Kingdom", "domain": "Municipal services: highway maintenance", "segment": "Local authority highways", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Program-level figures; no identifiable individual event." }, { "group": "organizational", "depth": null, "reason": "Cost and claims figures are program aggregates attributed by the council and DfT." }, { "group": "societal", "depth": null, "reason": "Local aggregate without a discrete attributable event." } ], "ai_role": { "status": "unassessed", "statement": "Neither source isolates the detection software's contribution. The claims reduction and savings are credited to Project Amber as a whole, which combines imagery surveys with preventive surface treatments. The Blackpool Unlimited page is undated and does not state its operator, so it is treated as a council-adjacent promotional page, not an official report." }, "evidence": [ { "kind": "press release", "citation": "Department for Transport (2024). Transport Secretary pledges to fix pothole plague as she sees cutting-edge repair technology in action on Blackpool visit. GOV.UK press release, 26 Sep 2024.", "title": "Transport Secretary pledges to fix pothole plague as she sees cutting-edge repair technology in action on Blackpool visit", "url": "https://www.gov.uk/government/news/transport-secretary-pledges-to-fix-pothole-plague-as-she-sees-cutting-edge-repair-technology-in-action-on-blackpool-visit", "date": "2024-09-26", "written_by": "independent", "quote": "In previous years it was paying up to £1.5 million a year to settle claims. Last year it only paid out £719." }, { "kind": "press release", "citation": "Blackpool Unlimited (n.d.). Artificial intelligence boosts road maintenance efficiency (quoting Cllr Fred Jackson, Blackpool Council, and Steve Berry, Department for Transport).", "title": "Artificial intelligence boosts road maintenance efficiency", "url": "https://blackpoolunlimited.com/artificial-intelligence-boosts-road-maintenance-efficiency/", "date": null, "written_by": "deployer", "quote": "Since summer 2019, 5145 potholes have been filled in North Shore" }, { "kind": "other", "citation": "Blackpool Council (2025). Highways maintenance programme. blackpool.gov.uk, page last modified 4 September 2025.", "title": "Highways maintenance programme", "url": "https://www.blackpool.gov.uk/Residents/Parking-roads-and-transport/Roadworks-and-road-maintenance/Highways-maintenance-programme.aspx", "date": "2025-09-04", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Imagery-based detection of potholes, cracks and surface damage across the network", "Color-coded prioritization used by engineers to schedule treatments", "Preventive surface treatments funded through the program" ], "must_hold": [ "Regular imagery capture of the road network", "Budget for follow-up treatments", "Claims handling that records payouts over time" ], "echoes": [ { "date": "2026-04-07", "setting": "Cambridgeshire County Council £100,000 contract for AI camera-based highway inspections after weekly defects peaked at 2,892 (BBC/LocalGov, Apr 2026); no outcome yet", "model_version": null, "outcome": "unknown", "source": "https://www.localgov.co.uk/AI-could-save-Cambridgeshire-CC-from-future-potholes/64160" }, { "date": "2024-01-08", "setting": "Hertfordshire County Council ARRES pothole-repair robot (Robotiz3d/University of Liverpool), lab-tested, road trials pending (BBC, Jan 2024)", "model_version": null, "outcome": "unknown", "source": "https://www.bbc.co.uk/news/uk-england-beds-bucks-herts-67934795" } ] }, "paired_incident": null, "headline": "Project Amber fills 5,145 Blackpool potholes for about £450,000", "metric": "5,145 potholes were filled in North Shore for just under £450,000", "comparator": { "against": "the council's pothole compensation payouts in the years before Project Amber", "before": "up to £1.5 million a year", "after": "£719", "basis": "measured", "quote": "Since 2019 Blackpool has seen significant reductions in its compensation bill for pothole related pay outs. In previous years it was paying up to £1.5 million a year to settle claims. 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The reduction is credited to the whole program, including surface treatments." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Project Amber road-condition imagery and AI survey (Blackpool Council)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Blackpool Council's Project Amber imagery and AI road surveys: 5,145 potholes filled for about £450,000 and pothole claim payouts down to £719", "headline": "Project Amber fills 5,145 Blackpool potholes for about £450,000" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f41eacff1c51f55f1af28eb803574f2c33b7ce980714b81b01dbda6419d456da" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Blackpool Council's Project Amber, launched in 2019 under the Local Council Roads Innovation Group, uses high-definition road imagery to detect potholes and prioritize repairs. The Blackpool Unlimited page calls it artificial-intelligence technology piloted in Anchorsholme and Bispham. It states that since summer 2019, 5,145 potholes were filled in North Shore for just under £450,000 against £1.5 million by traditional methods. The Department for Transport's release of 26 September 2024 says Blackpool was the first authority to use the technology. It had paid up to £1.5 million a year to settle pothole claims and “last year” paid out only £719. The release dates the work only as “last year”. The reduction is credited to the whole program, including surface treatments.", "replication": { "produced_by": [ "Imagery-based detection of potholes, cracks and surface damage across the network", "Color-coded prioritization used by engineers to schedule treatments", "Preventive surface treatments funded through the program" ], "must_hold": [ "Regular imagery capture of the road network", "Budget for follow-up treatments", "Claims handling that records payouts over time" ], "echoes": [ { "date": "2026-04-07", "setting": "Cambridgeshire County Council £100,000 contract for AI camera-based highway inspections after weekly defects peaked at 2,892 (BBC/LocalGov, Apr 2026); no outcome yet", "outcome": "unknown", "source": "https://www.localgov.co.uk/AI-could-save-Cambridgeshire-CC-from-future-potholes/64160" }, { "date": "2024-01-08", "setting": "Hertfordshire County Council ARRES pothole-repair robot (Robotiz3d/University of Liverpool), lab-tested, road trials pending (BBC, Jan 2024)", "outcome": "unknown", "source": "https://www.bbc.co.uk/news/uk-england-beds-bucks-herts-67934795" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0197", "title": "SoundTalks AI cough monitor tracks respiratory health in a German pig nursery alongside pathogen testing", "summary": "LMU Munich blinded study in a German nursery: swine influenza A loads in oral fluids and bioaerosols were associated with falls in the AI's respiratory health score; no intervention outcome.", "date_observed": "2024-10-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Veterinarians at Ludwig-Maximilians-University Munich ran a blinded prospective study on a conventional one-site piglet-producing farm in Germany. Its nursery holds 600 pigs per airspace in 20 pens. Two batches were monitored for 39 days each. Two SoundTalks monitors (SoundTalks NV, Leuven) counted coughs around the clock and distinguished pig coughs from other barn noise. They computed a daily respiratory health status (ReHS) from 0 to 100, with yellow alerts at 40–59 and red at 0–39. The LEDs were set to a blinded “science mode” so the investigators were not cued. Oral fluids and bioaerosol samples were screened by qPCR for swine influenza A virus, PRRSV, Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae and PCV2. All but M. hyopneumoniae were detected. High swIAV-RNA loads were significantly associated with a decrease in the AI-calculated respiratory health score. Boehringer Ingelheim Vetmedica funded the study and three of its employees are co-authors. A 2026 Konkuk University trial in Korea used the same device's ReHS as an outcome measure across 2,000 grower-finisher pigs.", "category": "general benefit", "unexpected": false, "purpose": "Continuously count pig coughs, separate them from barn noise and compute a daily respiratory health status. Yellow and red alerts give an early warning of respiratory disease.", "system": "SoundTalks (24/7 AI sound-based cough monitor with respiratory health status score)", "model_version": null, "developer": "SoundTalks NV, Leuven, Belgium", "deployer": "Clinic for Swine, LMU Munich, on a commercial piglet-producing farm in Germany", "location": null, "domain": "Livestock health", "segment": "Swine respiratory disease monitoring", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "A monitoring-association result; the score is information about herd health rather than a discovery.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Monitors were blinded, so no alert was acted on; the study documents associations, not a changed treatment or production outcome." }, { "group": "personal", "depth": null, "reason": "No outcome for the farmer or animals is reported." } ], "ai_role": { "status": "assessed", "statement": "The AI produced a respiratory health score that tracked swine influenza A loads measured by qPCR. Alerts were hidden from investigators, so the study measures association rather than any alert that changed what happened. Funding and three co-authors came from Boehringer Ingelheim Vetmedica. The paper states the funders were not involved in collection, analysis or interpretation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Eddicks M, Feicht F, Beckjunker J, Genzow M, Alonso C, Reese S, Ritzmann M, Stadler J. Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples. Viruses 16(10):1575 (2024). doi:10.3390/v16101575", "title": "Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples", "url": "https://doi.org/10.3390/v16101575", "date": "2024-10-06", "written_by": "deployer", "quote": "High swIAV-RNA loads in OFs and AS were significantly associated with a decrease in respiratory health, expressed by a respiratory health score calculated by the AI" }, { "kind": "peer-reviewed study", "citation": "Yoon CE, Cho DH, Park HL, Song JY, Park S, Lee SW, Go YY, Choi IS, Song CS, Lee JB, Park SY, Kang YL. AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms. Viruses 18(1):72 (2026). doi:10.3390/v18010072", "title": "AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms", "url": "https://doi.org/10.3390/v18010072", "date": "2026-01-04", "written_by": "independent", "quote": "Respiratory Health Status (ReHS) and a derived Clinical Cough Index (CCI = 100 - ReHS) were continuously recorded with SoundTalks®" } ], "replication": { "produced_by": [ "Two SoundTalks monitors in a 600-pig nursery airspace", "Parallel oral fluid and bioaerosol qPCR sampling", "Circulating swine influenza A virus producing coughing" ], "must_hold": [ "Monitors able to separate pig coughs from barn noise", "Pathogen loads high enough to depress the score" ], "echoes": [ { "date": "2026-01-04", "setting": "Korean grower-finisher farms, 2,000 pigs, SoundTalks ReHS used as the outcome measure in a rottlerin trial", "model_version": "SoundTalks ReHS", "outcome": "recurred", "source": "Yoon et al. 2026, Viruses, doi:10.3390/v18010072" } ] }, "paired_incident": null, "headline": "SoundTalks health score falls with high swine influenza A loads", "metric": null, "comparator": { "against": "human-conducted clinical coughing scores on the same pigs", "before": "twenty human clinical coughing scores per batch, with a coughing index of at most 0.4% (batch 1) and a maximum of 1.26% (batch 2)", "after": "a 24/7 AI respiratory health score that fell as the human-scored coughing rose (Spearman's rho −0.478 and −0.468)", "basis": "measured", "quote": "Spearman’s rho revealed a significant moderate to medium negative correlation between the ReHS and the CCS for B1 (Spearman’s rho −0.478; p ≤ 0.001) and B2 (Spearman’s rho: −0.468; p ≤ 0.001), indicating that an increase in the CCS was associated with a decrease in the ReHS.", "url": "https://europepmc.org/article/PMC/PMC11512249" }, "later": null, "value": null, "developer_country": "Belgium", "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11512249", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.soundtalks.com/en; https://www.vetmed.lmu.de/swk/de/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study and the deployer's peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0197", "catalog_version": "1.0.0", "source_fingerprint": "41f3fd2686bab851639aff6aeb66e6ffe499bbf9e8cadc6bd414f4002dd69ac6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0197-source-0001", "AIBD-0197-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "SoundTalks NV, Leuven, Belgium", "deployer": "Clinic for Swine, LMU Munich, on a commercial piglet-producing farm in Germany" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI produced a respiratory health score that tracked swine influenza A loads measured by qPCR. Alerts were hidden from investigators, so the study measures association rather than any alert that changed what happened. Funding and three co-authors came from Boehringer Ingelheim Vetmedica. The paper states the funders were not involved in collection, analysis or interpretation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The AI produced a respiratory health score that tracked swine influenza A loads measured by qPCR. Alerts were hidden from investigators, so the study measures association rather than any alert that changed what happened. Funding and three co-authors came from Boehringer Ingelheim Vetmedica. The paper states the funders were not involved in collection, analysis or interpretation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study and the deployer's peer-reviewed study. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Monitors were blinded, so no alert was acted on; the study documents associations, not a changed treatment or production outcome." }, { "group": "personal", "reason": "No outcome for the farmer or animals is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Monitors were blinded, so no alert was acted on; the study documents associations, not a changed treatment or production outcome." }, { "group": "personal", "reason": "No outcome for the farmer or animals is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0197" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "A monitoring-association result; the score is information about herd health rather than a discovery." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Veterinarians at Ludwig-Maximilians-University Munich ran a blinded prospective study on a conventional one-site piglet-producing farm in Germany. Its nursery holds 600 pigs per airspace in 20 pens. Two batches were monitored for 39 days each. Two SoundTalks monitors (SoundTalks NV, Leuven) counted coughs around the clock and distinguished pig coughs from other barn noise. They computed a daily respiratory health status (ReHS) from 0 to 100, with yellow alerts at 40–59 and red at 0–39. The LEDs were set to a blinded “science mode” so the investigators were not cued. Oral fluids and bioaerosol samples were screened by qPCR for swine influenza A virus, PRRSV, Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae and PCV2. All but M. hyopneumoniae were detected. High swIAV-RNA loads were significantly associated with a decrease in the AI-calculated respiratory health score. Boehringer Ingelheim Vetmedica funded the study and three of its employees are co-authors. A 2026 Konkuk University trial in Korea used the same device's ReHS as an outcome measure across 2,000 grower-finisher pigs.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Monitors were blinded, so no alert was acted on; the study documents associations, not a changed treatment or production outcome." }, { "group": "personal", "reason": "No outcome for the farmer or animals is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Continuously count pig coughs, separate them from barn noise and compute a daily respiratory health status. Yellow and red alerts give an early warning of respiratory disease." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Belgium", "deployer_country": "Germany" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Continuously count pig coughs, separate them from barn noise and compute a daily respiratory health status. Yellow and red alerts give an early warning of respiratory disease." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-10-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11512249", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.soundtalks.com/en; https://www.vetmed.lmu.de/swk/de/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Two SoundTalks monitors in a 600-pig nursery airspace", "Parallel oral fluid and bioaerosol qPCR sampling", "Circulating swine influenza A virus producing coughing" ], "must_hold": [ "Monitors able to separate pig coughs from barn noise", "Pathogen loads high enough to depress the score" ], "echoes": [ { "date": "2026-01-04", "setting": "Korean grower-finisher farms, 2,000 pigs, SoundTalks ReHS used as the outcome measure in a rottlerin trial", "model_version": "SoundTalks ReHS", "outcome": "recurred", "source": "Yoon et al. 2026, Viruses, doi:10.3390/v18010072" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Two SoundTalks monitors in a 600-pig nursery airspace", "Parallel oral fluid and bioaerosol qPCR sampling", "Circulating swine influenza A virus producing coughing" ], "must_hold": [ "Monitors able to separate pig coughs from barn noise", "Pathogen loads high enough to depress the score" ], "echoes": [ { "date": "2026-01-04", "setting": "Korean grower-finisher farms, 2,000 pigs, SoundTalks ReHS used as the outcome measure in a rottlerin trial", "model_version": "SoundTalks ReHS", "outcome": "recurred", "source": "Yoon et al. 2026, Viruses, doi:10.3390/v18010072" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC11512249", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.soundtalks.com/en; https://www.vetmed.lmu.de/swk/de/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Livestock health", "segment": "Swine respiratory disease monitoring" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Eddicks M, Feicht F, Beckjunker J, Genzow M, Alonso C, Reese S, Ritzmann M, Stadler J. Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples. Viruses 16(10):1575 (2024). doi:10.3390/v16101575", "title": "Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples", "url": "https://doi.org/10.3390/v16101575", "date": "2024-10-06", "written_by": "deployer", "quote": "High swIAV-RNA loads in OFs and AS were significantly associated with a decrease in respiratory health, expressed by a respiratory health score calculated by the AI" }, { "kind": "peer-reviewed study", "citation": "Yoon CE, Cho DH, Park HL, Song JY, Park S, Lee SW, Go YY, Choi IS, Song CS, Lee JB, Park SY, Kang YL. AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms. Viruses 18(1):72 (2026). doi:10.3390/v18010072", "title": "AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms", "url": "https://doi.org/10.3390/v18010072", "date": "2026-01-04", "written_by": "independent", "quote": "Respiratory Health Status (ReHS) and a derived Clinical Cough Index (CCI = 100 - ReHS) were continuously recorded with SoundTalks®" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0197-source-0001", "AIBD-0197-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Eddicks M, Feicht F, Beckjunker J, Genzow M, Alonso C, Reese S, Ritzmann M, Stadler J. Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples. Viruses 16(10):1575 (2024). doi:10.3390/v16101575", "title": "Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples", "url": "https://doi.org/10.3390/v16101575", "date": "2024-10-06", "written_by": "deployer", "quote": "High swIAV-RNA loads in OFs and AS were significantly associated with a decrease in respiratory health, expressed by a respiratory health score calculated by the AI" }, { "kind": "peer-reviewed study", "citation": "Yoon CE, Cho DH, Park HL, Song JY, Park S, Lee SW, Go YY, Choi IS, Song CS, Lee JB, Park SY, Kang YL. AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms. Viruses 18(1):72 (2026). doi:10.3390/v18010072", "title": "AI-Based Respiratory Monitoring-Guided Evaluation of Rottlerin Therapy for PRRS in Grower-Finisher Pig Farms", "url": "https://doi.org/10.3390/v18010072", "date": "2026-01-04", "written_by": "independent", "quote": "Respiratory Health Status (ReHS) and a derived Clinical Cough Index (CCI = 100 - ReHS) were continuously recorded with SoundTalks®" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "LMU Munich blinded study in a German nursery: swine influenza A loads in oral fluids and bioaerosols were associated with falls in the AI's respiratory health score; no intervention outcome.", "account": "Veterinarians at Ludwig-Maximilians-University Munich ran a blinded prospective study on a conventional one-site piglet-producing farm in Germany. Its nursery holds 600 pigs per airspace in 20 pens. Two batches were monitored for 39 days each. Two SoundTalks monitors (SoundTalks NV, Leuven) counted coughs around the clock and distinguished pig coughs from other barn noise. They computed a daily respiratory health status (ReHS) from 0 to 100, with yellow alerts at 40–59 and red at 0–39. The LEDs were set to a blinded “science mode” so the investigators were not cued. Oral fluids and bioaerosol samples were screened by qPCR for swine influenza A virus, PRRSV, Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae and PCV2. All but M. hyopneumoniae were detected. High swIAV-RNA loads were significantly associated with a decrease in the AI-calculated respiratory health score. Boehringer Ingelheim Vetmedica funded the study and three of its employees are co-authors. A 2026 Konkuk University trial in Korea used the same device's ReHS as an outcome measure across 2,000 grower-finisher pigs." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "SoundTalks (24/7 AI sound-based cough monitor with respiratory health status score)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "SoundTalks NV, Leuven, Belgium" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "SoundTalks AI cough monitor tracks respiratory health in a German pig nursery alongside pathogen testing", "headline": "SoundTalks health score falls with high swine influenza A loads" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "41f3fd2686bab851639aff6aeb66e6ffe499bbf9e8cadc6bd414f4002dd69ac6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Veterinarians at Ludwig-Maximilians-University Munich ran a blinded prospective study on a conventional one-site piglet-producing farm in Germany. Its nursery holds 600 pigs per airspace in 20 pens. Two batches were monitored for 39 days each. Two SoundTalks monitors (SoundTalks NV, Leuven) counted coughs around the clock and distinguished pig coughs from other barn noise. They computed a daily respiratory health status (ReHS) from 0 to 100, with yellow alerts at 40–59 and red at 0–39. The LEDs were set to a blinded “science mode” so the investigators were not cued. Oral fluids and bioaerosol samples were screened by qPCR for swine influenza A virus, PRRSV, Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae and PCV2. All but M. hyopneumoniae were detected. High swIAV-RNA loads were significantly associated with a decrease in the AI-calculated respiratory health score. Boehringer Ingelheim Vetmedica funded the study and three of its employees are co-authors. A 2026 Konkuk University trial in Korea used the same device's ReHS as an outcome measure across 2,000 grower-finisher pigs.", "replication": { "produced_by": [ "Two SoundTalks monitors in a 600-pig nursery airspace", "Parallel oral fluid and bioaerosol qPCR sampling", "Circulating swine influenza A virus producing coughing" ], "must_hold": [ "Monitors able to separate pig coughs from barn noise", "Pathogen loads high enough to depress the score" ], "echoes": [ { "date": "2026-01-04", "setting": "Korean grower-finisher farms, 2,000 pigs, SoundTalks ReHS used as the outcome measure in a rottlerin trial", "model_version": "SoundTalks ReHS", "outcome": "recurred", "source": "Yoon et al. 2026, Viruses, doi:10.3390/v18010072" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0091", "title": "UNEP MARS alert led to repair of a decades-old methane source at Hassi Messaoud, Algeria, verified by satellite from 15 October 2024", "summary": "MARS alert led an Algerian operator to fix an unlit flare at Hassi Messaoud; satellites show no emissions since 15 October 2024.", "date_observed": "2024-10-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "UNEP's Methane Alert and Response System (MARS) combines data from more than 30 satellite instruments with expert analysis and AI models. It confirmed mitigation of a methane source at Hassi Messaoud, Algeria, in October 2024. UNEP's case document was issued in November 2024 per the repository record. The PDF's last-updated field reads 15 October 2024. It records a Landsat 5 detection dated 1 July 1987. It attributes the emissions to an unlit flare caused by a passing valve on the flare line. The operator corrected the valve and restored normal operations. UNEP states no further emissions have been detected at the location since 15 October 2024. UN News reported on 23 July 2026 that the Algerian alert led to the repair of a leak that had persisted for decades.", "category": "benefit created", "unexpected": false, "purpose": "Satellite-based detection and notification of major methane emission events to governments and operators to enable mitigation.", "system": "UNEP International Methane Emissions Observatory, Methane Alert and Response System (MARS)", "model_version": null, "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed operator at Hassi Messaoud (repair)", "location": "Hassi Messaoud, Algeria", "domain": "Earth observation / methane emissions", "segment": "Oil and gas", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No identifiable individuals are documented as affected by the repair." }, { "group": "organizational", "depth": 2, "reason": "The operator fixed a passing valve on a flare line and restored normal operations at one facility, per UNEP's case document." }, { "group": "societal", "depth": 3, "reason": "UN News describes the leak as having persisted for decades before the repair. Material to many, provisional pending independent quantification of the emissions avoided." } ], "ai_role": { "status": "assessed", "statement": "UNEP IMEO both developed and operates MARS (developer and deployer are the same body). UNEP's MARS page describes detection using more than 30 satellite instruments coupled with expertise and advanced AI models. The MARS FAQ says deep learning models monitor high-resolution satellite data for further emissions. The case document's boilerplate says MARS combines 30+ satellite instruments with expert analysis and AI models. None of these states which step in this case was AI-driven. The repair was carried out by the operator. The two case-document items are treated as a public body's official reports rather than vendor material." }, "evidence": [ { "kind": "case report", "citation": "UNEP IMEO (2024). Methane Alert and Response System (MARS) Confirmed Mitigation Action - Algeria (DZA_S_012). Repository Date Issued 2024-11 (month only; first day used); the PDF's LAST UPDATED field reads 15 October 2024.", "title": "MARS Confirmed Mitigation Action - Algeria (DZA_S_012)", "url": "https://wedocs.unep.org/bitstreams/5810b829-cf15-4eb0-b509-8dd489884a66/download", "date": "2024-11-01", "written_by": "makers", "quote": "No further emissions have been detected at the location since 15 October 2024." }, { "kind": "case report", "citation": "UNEP IMEO (2024). Methane Alert and Response System (MARS) Confirmed Mitigation Action - Algeria (DZA_S_012), repository record. Date Issued 2024-11 (month only; first day used).", "title": "MARS Confirmed Mitigation Action - Algeria (repository record)", "url": "https://wedocs.unep.org/items/33a43a3a-8a2a-4831-8f18-e09e472623b0", "date": "2024-11-01", "written_by": "makers", "quote": "In October 2024, at Algeria's Hassi Messaoud, the International Methane Emissions Observatory (IMEO) confirmed methane mitigation action through the Methane Alert and Response System (MARS)." }, { "kind": "news report", "citation": "UN News (2026). Satellites can now spot methane leaks in real time - but most go unfixed. 23 July 2026.", "title": "Satellites can now spot methane leaks in real time - but most go unfixed", "url": "https://news.un.org/en/story/2026/07/1168007", "date": "2026-07-23", "written_by": "makers", "quote": "In Algeria, one alert led to the repair of a leak that had persisted for decades" }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "date": null, "written_by": "makers", "quote": "data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models" }, { "kind": "press release", "citation": "UNEP (n.d.). MARS Frequently Asked Questions. UNEP IMEO.", "title": "MARS Frequently Asked Questions", "url": "https://www.unep.org/en/what-we-do/energy/methane/international-methane-emissions-observatory/mars-frequently-asked", "date": null, "written_by": "makers", "quote": "MARS utilizes deep learning models to monitor data from continuously observing high-resolution satellites for future emissions from the region." }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (month only; first day used).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "date": "2026-09-01", "written_by": "makers", "quote": "To date, MARS has enabled and confirmed mitigation of over 40 major methane sources." }, { "kind": "report", "citation": "UNEP IMEO (2025). An Eye on Methane 2025: From Measurement to Momentum, repository abstract. Repository Date Issued 2025-10-03.", "title": "An Eye on Methane 2025: From Measurement to Momentum", "url": "https://wedocs.unep.org/bitstream/handle/20.500.11822/48664/An-Eye-on-Methane-2025.pdf?sequence=1&isAllowed=y", "date": "2025-10-03", "written_by": "makers", "quote": "the Methane Alert and Response System, which integrates satellite data and artificial intelligence to notify governments and companies of large emission events" } ], "replication": { "produced_by": [ "Satellite detection and expert quantification of a large point source, followed by a MARS notification to the government and operator", "An operator able to identify a simple equipment fault (passing valve on a flare line) and correct it", "Follow-up satellite monitoring confirming cessation" ], "must_hold": [ "A responsive focal point or operator. UN News reports only 13 percent of alerts lead to any response", "Verification depends on later satellite coverage. The Kazakhstan case shows emissions can recur after confirmed mitigation" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan (KAZ_S_136, 43.39767°, 52.49505°; no place name given): gas pipeline leak first detected September 2025 (plume imaged by DLR's EnMAP 29 October 2025); operator transferred the gas flow to another pipeline, mitigation reported 26 November 2025; no further emissions detected since 12 March 2026 (document last updated 15 April 2026), but IMEO observed subsequent emissions at the location as of 21 May 2026", "model_version": null, "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2023-12-01", "setting": "Argentina oil and gas facility: UNEP press release says the company fixed the leak after a MARS alert and satellite monitoring confirmed cessation", "model_version": null, "outcome": "recurred", "source": "https://www.unep.org/news-and-stories/press-release/uns-global-methane-tracking-system-set-translate-data-revolution" }, { "date": "2026-04-01", "setting": "Alberta, Canada: trade-press report of UNEP's monthly snapshot describing a 175-tonne-per-week plume fixed by repairing a failed ball valve on pigging equipment (month only; first day used)", "model_version": null, "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] }, "paired_incident": null, "headline": "UNEP MARS alert leads to methane leak repair at Hassi Messaoud", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-07-23", "note": "Twenty-one months after the repair, UN News cited the Algerian case as a leak fixed after a MARS alert, while reporting that only 13 per cent of alerts receive a response.", "quote": "In Algeria, one alert led to the repair of a leak that had persisted for decades, delivering climate benefits comparable to removing half a million cars from the road each year.", "url": "https://news.un.org/en/story/2026/07/1168007" }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote the Kazakhstan echo from the KAZ_S_136 document (no place name, first detection September 2025 with the EnMAP plume imaged 29 October 2025, no further emissions since 12 March 2026 until the 21 May 2026 banner), marked the month-only dates in the case-document and snapshot citations and dated the Eye on Methane item 2025-10-03 from its repository record, and stated that UNEP IMEO both developed and operates MARS so that the two case-document items count as a public body's official reports (marked independent).", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download; https://wedocs.unep.org/bitstreams/5810b829-cf15-4eb0-b509-8dd489884a66/download; https://wedocs.unep.org/items/33a43a3a-8a2a-4831-8f18-e09e472623b0; https://wedocs.unep.org/handle/20.500.11822/48664", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://news.un.org/en/story/2026/07/1168007", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two case reports from the makers, two reports from the makers, the makers' news report and two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0091", "catalog_version": "1.0.0", "source_fingerprint": "deb4f3b76031e7146e46b243baa8cbf4c5288f8921f9a2d91da88e1cf8cfbfc7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0091-source-0001", "AIBD-0091-source-0002", "AIBD-0091-source-0003", "AIBD-0091-source-0004", "AIBD-0091-source-0005", "AIBD-0091-source-0006", "AIBD-0091-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed operator at Hassi Messaoud (repair)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "UNEP IMEO both developed and operates MARS (developer and deployer are the same body). 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The two case-document items are treated as a public body's official reports rather than vendor material." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "UNEP IMEO both developed and operates MARS (developer and deployer are the same body). UNEP's MARS page describes detection using more than 30 satellite instruments coupled with expertise and advanced AI models. The MARS FAQ says deep learning models monitor high-resolution satellite data for further emissions. The case document's boilerplate says MARS combines 30+ satellite instruments with expert analysis and AI models. None of these states which step in this case was AI-driven. The repair was carried out by the operator. 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}, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-07-23", "note": "Twenty-one months after the repair, UN News cited the Algerian case as a leak fixed after a MARS alert, while reporting that only 13 per cent of alerts receive a response.", "quote": "In Algeria, one alert led to the repair of a leak that had persisted for decades, delivering climate benefits comparable to removing half a million cars from the road each year.", "url": "https://news.un.org/en/story/2026/07/1168007" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" 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It confirmed mitigation of a methane source at Hassi Messaoud, Algeria, in October 2024. UNEP's case document was issued in November 2024 per the repository record. The PDF's last-updated field reads 15 October 2024. It records a Landsat 5 detection dated 1 July 1987. It attributes the emissions to an unlit flare caused by a passing valve on the flare line. The operator corrected the valve and restored normal operations. UNEP states no further emissions have been detected at the location since 15 October 2024. UN News reported on 23 July 2026 that the Algerian alert led to the repair of a leak that had persisted for decades.", "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individuals are documented as affected by the repair." }, { "group": "organizational", "depth": 2, "reason": "The operator fixed a passing valve on a flare line and restored normal operations at one facility, per UNEP's case document." }, { "group": "societal", "depth": 3, "reason": "UN News describes the leak as having persisted for decades before the repair. Material to many, provisional pending independent quantification of the emissions avoided." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Satellite-based detection and notification of major methane emission events to governments and operators to enable mitigation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Hassi Messaoud, Algeria", "developer_country": "France", "deployer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models" }, { "kind": "press release", "citation": "UNEP (n.d.). MARS Frequently Asked Questions. UNEP IMEO.", "title": "MARS Frequently Asked Questions", "url": "https://www.unep.org/en/what-we-do/energy/methane/international-methane-emissions-observatory/mars-frequently-asked", "written_by": "makers", "quote": "MARS utilizes deep learning models to monitor data from continuously observing high-resolution satellites for future emissions from the region." }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (month only; first day used).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "date": "2026-09-01", "written_by": "makers", "quote": "To date, MARS has enabled and confirmed mitigation of over 40 major methane sources." }, { "kind": "report", "citation": "UNEP IMEO (2025). An Eye on Methane 2025: From Measurement to Momentum, repository abstract. Repository Date Issued 2025-10-03.", "title": "An Eye on Methane 2025: From Measurement to Momentum", "url": "https://wedocs.unep.org/bitstream/handle/20.500.11822/48664/An-Eye-on-Methane-2025.pdf?sequence=1&isAllowed=y", "date": "2025-10-03", "written_by": "makers", "quote": "the Methane Alert and Response System, which integrates satellite data and artificial intelligence to notify governments and companies of large emission events" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0091-source-0001", "AIBD-0091-source-0002", "AIBD-0091-source-0003", "AIBD-0091-source-0004", "AIBD-0091-source-0005", "AIBD-0091-source-0006", "AIBD-0091-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "UNEP IMEO (2024). Methane Alert and Response System (MARS) Confirmed Mitigation Action - Algeria (DZA_S_012). Repository Date Issued 2024-11 (month only; first day used); the PDF's LAST UPDATED field reads 15 October 2024.", "title": "MARS Confirmed Mitigation Action - Algeria (DZA_S_012)", "url": "https://wedocs.unep.org/bitstreams/5810b829-cf15-4eb0-b509-8dd489884a66/download", "date": "2024-11-01", "written_by": "makers", "quote": "No further emissions have been detected at the location since 15 October 2024." }, { "kind": "case report", "citation": "UNEP IMEO (2024). Methane Alert and Response System (MARS) Confirmed Mitigation Action - Algeria (DZA_S_012), repository record. Date Issued 2024-11 (month only; first day used).", "title": "MARS Confirmed Mitigation Action - Algeria (repository record)", "url": "https://wedocs.unep.org/items/33a43a3a-8a2a-4831-8f18-e09e472623b0", "date": "2024-11-01", "written_by": "makers", "quote": "In October 2024, at Algeria's Hassi Messaoud, the International Methane Emissions Observatory (IMEO) confirmed methane mitigation action through the Methane Alert and Response System (MARS)." }, { "kind": "news report", "citation": "UN News (2026). Satellites can now spot methane leaks in real time - but most go unfixed. 23 July 2026.", "title": "Satellites can now spot methane leaks in real time - but most go unfixed", "url": "https://news.un.org/en/story/2026/07/1168007", "date": "2026-07-23", "written_by": "makers", "quote": "In Algeria, one alert led to the repair of a leak that had persisted for decades" }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models" }, { "kind": "press release", "citation": "UNEP (n.d.). MARS Frequently Asked Questions. UNEP IMEO.", "title": "MARS Frequently Asked Questions", "url": "https://www.unep.org/en/what-we-do/energy/methane/international-methane-emissions-observatory/mars-frequently-asked", "written_by": "makers", "quote": "MARS utilizes deep learning models to monitor data from continuously observing high-resolution satellites for future emissions from the region." }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (month only; first day used).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "date": "2026-09-01", "written_by": "makers", "quote": "To date, MARS has enabled and confirmed mitigation of over 40 major methane sources." }, { "kind": "report", "citation": "UNEP IMEO (2025). An Eye on Methane 2025: From Measurement to Momentum, repository abstract. Repository Date Issued 2025-10-03.", "title": "An Eye on Methane 2025: From Measurement to Momentum", "url": "https://wedocs.unep.org/bitstream/handle/20.500.11822/48664/An-Eye-on-Methane-2025.pdf?sequence=1&isAllowed=y", "date": "2025-10-03", "written_by": "makers", "quote": "the Methane Alert and Response System, which integrates satellite data and artificial intelligence to notify governments and companies of large emission events" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "MARS alert led an Algerian operator to fix an unlit flare at Hassi Messaoud; satellites show no emissions since 15 October 2024.", "account": "UNEP's Methane Alert and Response System (MARS) combines data from more than 30 satellite instruments with expert analysis and AI models. It confirmed mitigation of a methane source at Hassi Messaoud, Algeria, in October 2024. UNEP's case document was issued in November 2024 per the repository record. The PDF's last-updated field reads 15 October 2024. It records a Landsat 5 detection dated 1 July 1987. It attributes the emissions to an unlit flare caused by a passing valve on the flare line. The operator corrected the valve and restored normal operations. UNEP states no further emissions have been detected at the location since 15 October 2024. UN News reported on 23 July 2026 that the Algerian alert led to the repair of a leak that had persisted for decades." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UNEP International Methane Emissions Observatory, Methane Alert and Response System (MARS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UNEP International Methane Emissions Observatory (IMEO)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "UNEP MARS alert led to repair of a decades-old methane source at Hassi Messaoud, Algeria, verified by satellite from 15 October 2024", "headline": "UNEP MARS alert leads to methane leak repair at Hassi Messaoud" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "deb4f3b76031e7146e46b243baa8cbf4c5288f8921f9a2d91da88e1cf8cfbfc7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "UNEP's Methane Alert and Response System (MARS) combines data from more than 30 satellite instruments with expert analysis and AI models. It confirmed mitigation of a methane source at Hassi Messaoud, Algeria, in October 2024. UNEP's case document was issued in November 2024 per the repository record. The PDF's last-updated field reads 15 October 2024. It records a Landsat 5 detection dated 1 July 1987. It attributes the emissions to an unlit flare caused by a passing valve on the flare line. The operator corrected the valve and restored normal operations. UNEP states no further emissions have been detected at the location since 15 October 2024. UN News reported on 23 July 2026 that the Algerian alert led to the repair of a leak that had persisted for decades.", "replication": { "produced_by": [ "Satellite detection and expert quantification of a large point source, followed by a MARS notification to the government and operator", "An operator able to identify a simple equipment fault (passing valve on a flare line) and correct it", "Follow-up satellite monitoring confirming cessation" ], "must_hold": [ "A responsive focal point or operator. UN News reports only 13 percent of alerts lead to any response", "Verification depends on later satellite coverage. The Kazakhstan case shows emissions can recur after confirmed mitigation" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan (KAZ_S_136, 43.39767°, 52.49505°; no place name given): gas pipeline leak first detected September 2025 (plume imaged by DLR's EnMAP 29 October 2025); operator transferred the gas flow to another pipeline, mitigation reported 26 November 2025; no further emissions detected since 12 March 2026 (document last updated 15 April 2026), but IMEO observed subsequent emissions at the location as of 21 May 2026", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2023-12-01", "setting": "Argentina oil and gas facility: UNEP press release says the company fixed the leak after a MARS alert and satellite monitoring confirmed cessation", "outcome": "recurred", "source": "https://www.unep.org/news-and-stories/press-release/uns-global-methane-tracking-system-set-translate-data-revolution" }, { "date": "2026-04-01", "setting": "Alberta, Canada: trade-press report of UNEP's monthly snapshot describing a 175-tonne-per-week plume fixed by repairing a failed ball valve on pigging equipment (month only; first day used)", "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0009", "title": "AI-based Intrusion Detection System alert and emergency braking avert Kamrup Express collision with about 60 elephants in Assam", "summary": "16 October 2024: AI intrusion alert and crew braking stopped 15959 Kamrup Express as about 60 elephants crossed near Lamsakhang, Assam", "date_observed": "2024-10-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 16 October 2024 at about 8:37 pm, train 15959 Kamrup Express was running from Guwahati toward Lumding. It neared a herd of about 60 wild elephants crossing the track between Habaipur and Lamsakhang stations in Assam. Northeast Frontier Railway said loco pilot J.D. Das and assistant loco pilot Umesh Kumar noticed the herd and applied the emergency brake. It said the AI-based Intrusion Detection System operating on that section also alerted the drivers. That system uses existing optical fibers as sensors to identify animal movements and alert control offices, station masters, gatemen and loco pilots. The train stopped and no collision occurred. NFR reported it saved 414 elephants in 2023 and 383 up to 16 October 2024.", "category": "protective response", "unexpected": false, "purpose": "Built to detect elephants near the track and alert loco pilots, station masters and control rooms. This benefit is that purpose.", "system": "AI-based Intrusion Detection System (distributed acoustic sensing on optical fiber), Northeast Frontier Railway", "model_version": null, "developer": null, "deployer": "Northeast Frontier Railway (Indian Railways)", "location": "Lumding, India", "domain": "Railway safety and wildlife protection", "segment": "Rail transport", "benefit_type": "Increased Product Safety", "taxonomy_note": "The collision avoided is between a train and elephants, so the gain is shared with conservation.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "NFR avoided a collision between a running express train and about 60 elephants, with the derailment and disruption risk that carries." }, { "group": "societal", "depth": 2, "reason": "About 60 wild elephants, a protected species, crossed safely; NFR reports hundreds of such events a year on this network." } ], "ai_role": { "status": "assessed", "statement": "The operator's release says the drivers noticed the herd and applied the emergency brake and were “also alerted” by the IDS. One local report says the braking followed the IDS warning. The AI alert is documented, but its share of the causal credit is not separable from the crew's own sighting. Hence protective response, prevention unproven." }, "evidence": [ { "kind": "news report", "citation": "Morung Express News (2024). Alert train drivers 'avert collision' with herd of elephants in Assam (based on NFR release, Maligaon, 17 October 2024).", "title": "Alert train drivers 'avert collision' with herd of elephants in Assam", "url": "https://morungexpress.com/alert-train-drivers-avert-collision-with-herd-of-elephants-in-assam", "date": "2024-10-17", "written_by": "independent", "quote": "The drivers were also alerted by the Artificial Intelligence (AI)-based Intrusion Detection System (IDS) that has been in operation in that section." }, { "kind": "news report", "citation": "The Sentinel (Assam) (2024). Assam: AI Technology Generated Alerts Prevent Train From Colliding With Elephants.", "title": "Assam: AI Technology Generated Alerts Prevent Train From Colliding With Elephants", "url": "https://www.sentinelassam.com/breakingnews/assam-ai-technology-generated-alerts-prevent-train-from-colliding-with-elephants", "date": null, "written_by": "independent", "quote": "the loco pilot and assistant loco pilot applied brakes, preventing a possible collusion." }, { "kind": "news report", "citation": "The Meghalayan Express (2024). AI technology alerts drivers to stop trains to rescue a herd of elephants in Assam.", "title": "AI technology alerts drivers to stop trains to rescue a herd of elephants in Assam", "url": "https://themeghalayanexpress.com/ai-technology-alerts-drivers-to-stop-trains-to-rescue-a-herd-of-elephants-in-assam/", "date": "2024-10-18", "written_by": "independent", "quote": "Thanks to the quick response of the pilots, who applied the emergency brakes, a potential collision was averted, ensuring the safety of the elephants." }, { "kind": "report", "citation": "DD News (2025). Indian Railways expands AI-based intrusion detection to prevent elephant collisions across key routes (reporting the Railway Minister's written Rajya Sabha reply).", "title": "Indian Railways expands AI-based intrusion detection to prevent elephant collisions across key routes", "url": "https://ddnews.gov.in/en/indian-railways-expands-ai-based-intrusion-detection-to-prevent-elephant-collisions-across-key-routes/", "date": "2025-12-05", "written_by": "independent", "quote": "loco pilots, station masters and control rooms when elephant movement is detected near the tracks" }, { "kind": "news report", "citation": "The Sentinel (Assam) (2026). AI Shield and 'Plan Bee' Save 255 Elephants Across Northeast Frontier Railway.", "title": "AI Shield and 'Plan Bee' Save 255 Elephants Across Northeast Frontier Railway", "url": "https://www.sentinelassam.com/north-east-india-news/assam-news/ai-shield-and-plan-bee-save-255-elephants-across-northeast-frontier-railway", "date": "2026-10-08", "written_by": "independent", "quote": "immediately transmits real-time alerts to station masters and loco pilots, prompting them to reduce train speeds to 25 kmph when wildlife wanders near the tracks." }, { "kind": "news report", "citation": "PTI. AI-based surveillance mechanism helps eliminate elephant deaths due to train collisions in 11 Northeast corridors. The Tribune, 6 September 2023.", "title": "AI-based surveillance mechanism helps eliminate elephant deaths due to train collisions in 11 Northeast corridors", "url": "https://www.tribuneindia.com/news/india/ai-based-surveillance-mechanism-helps-eliminate-elephant-deaths-due-to-train-collisions-in-11-northeast-corridors-541918", "date": "2023-09-06", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Fiber-optic acoustic sensing with AI classification installed along an elephant corridor", "Alert routed to loco pilots and station masters in time to brake" ], "must_hold": [ "Train speed and sighting distance allow a stop after the alert", "Crew act on the alert. The operator attributes this stop partly to the crew's own sighting" ], "echoes": [ { "date": null, "setting": "Aggregate, not an individual event: NFR announced 255 elephants protected in 2026 across Lumding (122), Alipurduar (106), Tinsukia (15) and Rangiya (14) divisions, with alerts prompting speed reductions to 25 km/h (The Sentinel, 8 October 2026)", "model_version": null, "outcome": "recurred", "source": "https://www.sentinelassam.com/north-east-india-news/assam-news/ai-shield-and-plan-bee-save-255-elephants-across-northeast-frontier-railway" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "severity": null, "group": "societal", "basis": "AI intrusion detection protecting wildlife: Ezemvelo KZN Wildlife's AI cameras failed to detect poachers and four rhinos were killed, the protected-animal group the NFR acoustic alert saved when about 60 elephants crossed the track." }, "headline": "AI intrusion alert stops Kamrup Express as about 60 elephants cross", "metric": "saved 414 elephants in 2023 and 383 up to 16 October 2024", "comparator": { "against": "train-elephant collisions before the system (national average of elephant deaths on tracks)", "before": "on an average 20 elephants die due to train collisions in the country every year and a majority of these incidents take place in the Northeast Frontier Railway", "after": "since the launch of the system, these 11 corridors have not reported any train-elephant collision", "basis": "measured", "quote": "De said that since the launch of the system, these 11 corridors have not reported any train-elephant collision. Government data shows that on an average 20 elephants die due to train collisions in the country every year and a majority of these incidents take place in the Northeast Frontier Railway.", "url": "https://www.tribuneindia.com/news/india/ai-based-surveillance-mechanism-helps-eliminate-elephant-deaths-due-to-train-collisions-in-11-northeast-corridors-541918" }, "later": { "status": "scaled", "date": "2025-12-05", "note": "By December 2025 the system covered 141 route kilometers of Northeast Frontier Railway and tenders had been awarded for 981 more route kilometers nationwide.", "quote": "Indian Railways has scaled up the deployment of its artificial intelligence-enabled Intrusion Detection System (IDS) to curb elephant fatalities on rail tracks, with the technology now active across 141 route kilometres (RKms) of the Northeast Frontier Railway and tenders awarded for an additional 981 RKms nationwide.", "url": "https://ddnews.gov.in/en/indian-railways-expands-ai-based-intrusion-detection-to-prevent-elephant-collisions-across-key-routes/" }, "value": null, "developer_country": null, "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.tribuneindia.com/news/india/ai-based-surveillance-mechanism-helps-eliminate-elephant-deaths-due-to-train-collisions-in-11-northeast-corridors-541918; https://ddnews.gov.in/en/indian-railways-expands-ai-based-intrusion-detection-to-prevent-elephant-collisions-across-key-routes/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Northeast_Frontier_Railway_zone", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report and five independent news reports. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0009", "catalog_version": "1.0.0", "source_fingerprint": "e2557968a4b3067e350e9314a4688b81be6e43015c3adcff9491a397285cf100", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0009-source-0001", "AIBD-0009-source-0002", "AIBD-0009-source-0003", "AIBD-0009-source-0004", "AIBD-0009-source-0005", "AIBD-0009-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Northeast Frontier Railway (Indian Railways)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The operator's release says the drivers noticed the herd and applied the emergency brake and were “also alerted” by the IDS. One local report says the braking followed the IDS warning. The AI alert is documented, but its share of the causal credit is not separable from the crew's own sighting. Hence protective response, prevention unproven." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The operator's release says the drivers noticed the herd and applied the emergency brake and were “also alerted” by the IDS. One local report says the braking followed the IDS warning. The AI alert is documented, but its share of the causal credit is not separable from the crew's own sighting. Hence protective response, prevention unproven." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NFR avoided a collision between a running express train and about 60 elephants, with the derailment and disruption risk that carries." }, { "group": "societal", "depth": 2, "reason": "About 60 wild elephants, a protected species, crossed safely; NFR reports hundreds of such events a year on this network." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report and five independent news reports. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "NFR avoided a collision between a running express train and about 60 elephants, with the derailment and disruption risk that carries." }, { "group": "societal", "depth": 2, "reason": "About 60 wild elephants, a protected species, crossed safely; NFR reports hundreds of such events a year on this network." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Wildlife's AI cameras failed to detect poachers and four rhinos were killed, the protected-animal group the NFR acoustic alert saved when about 60 elephants crossed the track.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "saved 414 elephants in 2023 and 383 up to 16 October 2024", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" 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"value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2025-12-05", "note": "By December 2025 the system covered 141 route kilometers of Northeast Frontier Railway and tenders had been awarded for 981 more route kilometers nationwide.", "quote": "Indian Railways has scaled up the deployment of its artificial intelligence-enabled Intrusion Detection System (IDS) to curb elephant fatalities on rail tracks, with the technology now active across 141 route kilometres (RKms) of the Northeast Frontier Railway and tenders awarded for an additional 981 RKms nationwide.", "url": "https://ddnews.gov.in/en/indian-railways-expands-ai-based-intrusion-detection-to-prevent-elephant-collisions-across-key-routes/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" 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It neared a herd of about 60 wild elephants crossing the track between Habaipur and Lamsakhang stations in Assam. Northeast Frontier Railway said loco pilot J.D. Das and assistant loco pilot Umesh Kumar noticed the herd and applied the emergency brake. It said the AI-based Intrusion Detection System operating on that section also alerted the drivers. That system uses existing optical fibers as sensors to identify animal movements and alert control offices, station masters, gatemen and loco pilots. The train stopped and no collision occurred. NFR reported it saved 414 elephants in 2023 and 383 up to 16 October 2024.", "replication": { "produced_by": [ "Fiber-optic acoustic sensing with AI classification installed along an elephant corridor", "Alert routed to loco pilots and station masters in time to brake" ], "must_hold": [ "Train speed and sighting distance allow a stop after the alert", "Crew act on the alert. 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It identified Tmem81 as part of a conserved trimeric sperm complex with the known essential fertilization factors Izumo1 and Spaca6. The prediction was then tested at the bench. The authors demonstrated that Tmem81 is essential for male fertility in zebrafish and mice. They showed Izumo1, Spaca6 and Tmem81 interact in zebrafish sperm and the human orthologues interact in vitro. They found complex formation creates the binding site for the egg factor Bouncer in zebrafish. The screen and the validation were performed independently of AlphaFold's developer.", "category": "benefit created", "unexpected": false, "purpose": "Predict protein-protein complexes in order to find missing components of the vertebrate sperm-egg interaction machinery.", "system": "AlphaFold-Multimer complex-prediction screen", "model_version": "AlphaFold-Multimer", "developer": "DeepMind (AlphaFold-Multimer)", "deployer": "Research Institute of Molecular Pathology (Pauli lab) and collaborators", "location": "Vienna, Austria", "domain": "Reproductive and molecular biology", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The AI screen handed the laboratory a specific, testable candidate (Tmem81) that it then validated genetically and biochemically, a material result for that research group." }, { "group": "societal", "depth": 2, "reason": "Identification of a conserved vertebrate fertilization factor essential for male fertility in two species advances a long-standing open question. The source demonstrates no clinical application yet." } ], "ai_role": { "status": "assessed", "statement": "AlphaFold-Multimer generated the hypothesis that Tmem81 belongs to a trimeric complex with Izumo1 and Spaca6. The functional claim rests on the same laboratory's wet-lab work: zebrafish and mouse knockouts, zebrafish sperm interaction assays, and human orthologue interaction in vitro." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Deneke VE, Blaha A, Lu Y, et al. (2024). A conserved fertilization complex bridges sperm and egg in vertebrates. 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It identified Tmem81 as part of a conserved trimeric sperm complex with the known essential fertilization factors Izumo1 and Spaca6. The prediction was then tested at the bench. The authors demonstrated that Tmem81 is essential for male fertility in zebrafish and mice. They showed Izumo1, Spaca6 and Tmem81 interact in zebrafish sperm and the human orthologues interact in vitro. They found complex formation creates the binding site for the egg factor Bouncer in zebrafish. 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It identified Tmem81 as part of a conserved trimeric sperm complex with the known essential fertilization factors Izumo1 and Spaca6. The prediction was then tested at the bench. The authors demonstrated that Tmem81 is essential for male fertility in zebrafish and mice. They showed Izumo1, Spaca6 and Tmem81 interact in zebrafish sperm and the human orthologues interact in vitro. They found complex formation creates the binding site for the egg factor Bouncer in zebrafish. 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The enhanced processes, including machine-learning AI, prevented and recovered over $4 billion in fraud and improper payments in FY2024 (October 2023 to September 2024). The FY2023 comparison figure was $652.7 million. Of the total, $1 billion was recovered through machine-learning identification of Treasury check fraud. $2.5 billion came from identifying and prioritizing high-risk transactions, $500 million from expanded risk-based screening and $180 million from payment-processing efficiencies. Nextgov reported that the office uses machine learning to examine large amounts of data and flag potential fraud schemes. NBC News reported that a Treasury official declined to give specific deployment examples for security reasons. No independent audit of the figures and no vendor or technique appears in the sources.", "category": "general benefit", "unexpected": false, "purpose": "Detect and prevent fraud and improper payments in federal disbursements, including Treasury check fraud.", "system": "Office of Payment Integrity enhanced fraud-detection processes including machine-learning AI (Bureau of the Fiscal Service)", "model_version": null, "developer": "U.S. Department of the Treasury, Bureau of the Fiscal Service, Office of Payment Integrity (no vendor is named in the sources)", "deployer": "U.S. Department of the Treasury, Bureau of the Fiscal Service", "location": null, "domain": "Public finance and payment integrity", "segment": "Federal government payments and check fraud", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "The sources give only aggregate FY2024 totals for taxpayers' money recovered or prevented. No outcome is documented for an identifiable group." }, { "group": "organizational", "depth": null, "reason": "Treasury reports aggregate prevention and recovery figures for the Office of Payment Integrity. No single deployment outcome is described." } ], "ai_role": { "status": "assessed", "statement": "Treasury's release attributes $1 billion of FY2024 recoveries to machine-learning AI that expedited identification of Treasury check fraud. It credits $2.5 billion to prioritizing high-risk transactions. The technique is not described and no vendor is named. So developer and deployer appear to be the same public body (the Bureau of the Fiscal Service's Office of Payment Integrity). This is not stated. The figures are not independently verified in the sources." }, "evidence": [ { "kind": "press release", "citation": "U.S. Department of the Treasury, press release, 17 October 2024", "title": "Treasury Announces Enhanced Fraud Detection Processes, Including Machine Learning AI, Prevented and Recovered Over $4 Billion in Fiscal Year 2024", "url": "https://home.treasury.gov/news/press-releases/jy2650", "date": "2024-10-17", "written_by": "makers", "quote": "Treasury takes seriously our responsibility to serve as effective stewards of taxpayer money." }, { "kind": "news report", "citation": "Natalie Alms, Nextgov/FCW, 18 October 2024", "title": "AI tools helped Treasury recover billions in fraud and improper payments", "url": "https://www.nextgov.com/artificial-intelligence/2024/10/ai-tools-helped-treasury-recover-billions-fraud-and-improper-payments/400368/", "date": "2024-10-18", "written_by": "independent", "quote": "We've made significant progress during the past year." }, { "kind": "news report", "citation": "Rob Wile, NBC News, 17 October 2024", "title": "Treasury Department now using AI to save taxpayers billions of dollars", "url": "https://www.nbcnews.com/business/consumer/how-ai-artificial-intelligence-fights-taxpayer-fraud-treasury-dept-rcna175916", "date": "2024-10-17", "written_by": "independent", "quote": "Treasury Department now using AI to save taxpayers billions of dollars" }, { "kind": "press release", "citation": "Bureau of the Fiscal Service (2026). Treasury's Bureau of the Fiscal Service Recognized for Payment Integrity Efforts. Fiscal Service news, 18 September 2026.", "title": "Treasury’s Bureau of the Fiscal Service Recognized for Payment Integrity Efforts", "url": "https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts", "date": "2026-09-18", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Centralised disbursement data at the Bureau of the Fiscal Service (Nextgov: over 1.4 billion payments and more than $6.9 trillion a year)", "Machine learning applied to large payment datasets to flag potential fraud schemes, combined with risk-based screening and prioritization of high-risk transactions" ], "must_hold": [ "Access to payment and check data at scale", "Operational capacity to stop or claw back flagged payments and an office that measures the results", "Independent verification of the claimed figures, which the sources do not provide" ], "echoes": [ { "date": "2023-09-30", "setting": "Treasury Office of Payment Integrity, FY2023", "model_version": null, "outcome": "recurred", "source": "Treasury press release gives $652.7 million as the FY2023 comparison figure; the machine-learning attribution for that year is not stated" } ] }, "paired_incident": null, "headline": "Treasury's machine learning recovers $1 billion in FY2024", "metric": "$1 billion recovered through machine-learning check-fraud detection", "comparator": { "against": "Treasury's fraud and improper-payment prevention and recovery in FY2023, before the enhanced processes", "before": "$652.7 million in FY23", "after": "over $4 billion in fraud and improper payments this fiscal year (FY) (October 2023 – September 2024)", "basis": "measured", "quote": "Today, the U.S. Department of the Treasury announced that its latest efforts in taking a technology and data-driven approach to fraud and improper payment prevention enabled the prevention and recovery of over $4 billion in fraud and improper payments this fiscal year (FY) (October 2023 – September 2024), up from $652.7 million in FY23.", "url": "https://home.treasury.gov/news/press-releases/jy2650" }, "later": { "status": "scaled", "date": "2026-09-18", "note": "The Fiscal Service reported that Treasury's payment integrity efforts prevented, detected or recovered more than $11.7 billion in FY2025, nearly three times the FY2024 total.", "quote": "In fiscal year 2025, Treasury’s payment integrity efforts helped prevent, detect, and recover more than $11.7 billion in improper payments.", "url": "https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts" }, "value": { "amount": "$1 billion", "what": "Treasury check fraud recovered in FY2024 through machine-learning identification", "who": "U.S. Treasury, on behalf of taxpayers", "estimate": false, "quote": "Expediting the identification of Treasury check fraud with machine learning AI resulting in $1 billion in recovery.", "url": "https://home.treasury.gov/news/press-releases/jy2650" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://home.treasury.gov/news/press-releases/jy2650; https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts; https://home.treasury.gov/news/press-releases/jy2650", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury; https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0173", "catalog_version": "1.0.0", "source_fingerprint": "c2e315c046b1eb2440210908623e53cc80ee42401af9a092e5f499f638bcf950", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0173-source-0001", "AIBD-0173-source-0002", "AIBD-0173-source-0003", "AIBD-0173-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0173-legacy-value", "DIV-0019" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0173-legacy-value", "DIV-0019" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "U.S. Department of the Treasury, Bureau of the Fiscal Service, Office of Payment Integrity (no vendor is named in the sources)", "deployer": "U.S. Department of the Treasury, Bureau of the Fiscal Service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Treasury's release attributes $1 billion of FY2024 recoveries to machine-learning AI that expedited identification of Treasury check fraud. 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https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts; https://home.treasury.gov/news/press-releases/jy2650", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury; https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public finance and payment integrity", "segment": "Federal government payments and check fraud" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Treasury's Bureau of the Fiscal Service Recognized for Payment Integrity Efforts. 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Treasury's Bureau of the Fiscal Service Recognized for Payment Integrity Efforts. 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The enhanced processes, including machine-learning AI, prevented and recovered over $4 billion in fraud and improper payments in FY2024 (October 2023 to September 2024). The FY2023 comparison figure was $652.7 million. Of the total, $1 billion was recovered through machine-learning identification of Treasury check fraud. $2.5 billion came from identifying and prioritizing high-risk transactions, $500 million from expanded risk-based screening and $180 million from payment-processing efficiencies. Nextgov reported that the office uses machine learning to examine large amounts of data and flag potential fraud schemes. NBC News reported that a Treasury official declined to give specific deployment examples for security reasons. No independent audit of the figures and no vendor or technique appears in the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Office of Payment Integrity enhanced fraud-detection processes including machine-learning AI (Bureau of the Fiscal Service)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "U.S. Department of the Treasury, Bureau of the Fiscal Service, Office of Payment Integrity (no vendor is named in the sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Treasury's machine-learning check-fraud detection recovers $1 billion in FY2024", "headline": "Treasury's machine learning recovers $1 billion in FY2024" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c2e315c046b1eb2440210908623e53cc80ee42401af9a092e5f499f638bcf950" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 17 October 2024 the U.S. Department of the Treasury reported on fraud detection at the Bureau of the Fiscal Service's Office of Payment Integrity. The enhanced processes, including machine-learning AI, prevented and recovered over $4 billion in fraud and improper payments in FY2024 (October 2023 to September 2024). The FY2023 comparison figure was $652.7 million. Of the total, $1 billion was recovered through machine-learning identification of Treasury check fraud. $2.5 billion came from identifying and prioritizing high-risk transactions, $500 million from expanded risk-based screening and $180 million from payment-processing efficiencies. Nextgov reported that the office uses machine learning to examine large amounts of data and flag potential fraud schemes. NBC News reported that a Treasury official declined to give specific deployment examples for security reasons. No independent audit of the figures and no vendor or technique appears in the sources.", "replication": { "produced_by": [ "Centralised disbursement data at the Bureau of the Fiscal Service (Nextgov: over 1.4 billion payments and more than $6.9 trillion a year)", "Machine learning applied to large payment datasets to flag potential fraud schemes, combined with risk-based screening and prioritization of high-risk transactions" ], "must_hold": [ "Access to payment and check data at scale", "Operational capacity to stop or claw back flagged payments and an office that measures the results", "Independent verification of the claimed figures, which the sources do not provide" ], "echoes": [ { "date": "2023-09-30", "setting": "Treasury Office of Payment Integrity, FY2023", "outcome": "recurred", "source": "Treasury press release gives $652.7 million as the FY2023 comparison figure; the machine-learning attribution for that year is not stated" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0266", "title": "Johns Hopkins LSTM click detector lets a man with ALS spell 10.2 characters a minute for 90 days without retraining", "summary": "A chronically implanted high-density ECoG BCI with an LSTM click detector trained on under 44 minutes of data supported switch-scan spelling for 626 minutes over 90 days, all in the laboratory.", "date_observed": "2024-10-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Candrea et al. (Communications Medicine, 22 October 2024) report a clinical-trial participant with ALS (NCT03567213) at Johns Hopkins. He had a chronically implanted high-density electrocorticographic BCI over sensorimotor cortex. High-gamma power vectors from 128 channels fed a long short-term memory layer with 25 hidden units and fully connected layers. These classified rest versus grasp every 100 ms. The click detector was trained on almost 44 minutes of data (480 trials) collected up to 21 days before use. It then ran for 90 days without retraining. The participant controlled a switch-scanning speller for a total of 626 minutes with a median spelling rate of 10.2 characters per minute. The paper states all data collection and testing were performed in the laboratory. No home use is reported.", "category": "benefit created", "unexpected": false, "purpose": "Restore text communication for a person with ALS through a single neural click command driving a switch-scanning speller", "system": "Click-based electrocorticographic brain-computer interface with an LSTM click detector (NCT03567213)", "model_version": "LSTM (25 hidden units) with two fully connected layers, Keras/TensorFlow 2.8.0", "developer": "Johns Hopkins University (Crone lab and co-authors)", "deployer": "Johns Hopkins University (laboratory sessions)", "location": "Baltimore, Maryland, USA", "domain": "Health; assistive communication", "segment": "People with ALS and impaired speech or movement", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "Functional text-based communication at 10.2 characters per minute in laboratory sessions totaling 626 minutes over 90 days. No home use." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported." }, { "group": "societal", "depth": null, "reason": "Single participant." } ], "ai_role": { "status": "assessed", "statement": "The LSTM click detector is the decoding element. Its stability without retraining is the paper's main result. The source is a peer-reviewed report by the developers, with no outside corroboration and no use outside the laboratory." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Candrea DN, Shah S, Luo S, et al. Commun Med 4:207 (2024)", "title": "A click-based electrocorticographic brain-computer interface enables long-term high-performance switch scan spelling", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11494178/", "date": "2024-10-22", "written_by": "makers", "quote": "the study participant can maintain a median spelling rate of 10.2 characters per min" }, { "kind": "peer-reviewed study", "citation": "Candrea DN, et al. Commun Med 4:207 (2024), Methods", "title": "A click-based electrocorticographic brain-computer interface enables long-term high-performance switch scan spelling", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11494178/", "date": "2024-10-22", "written_by": "makers", "quote": "All data collection and testing were performed in the laboratory." }, { "kind": "preprint", "citation": "Candrea DN, et al. Research Square, 25 Sep 2023", "title": "A click-based electrocorticographic brain-computer interface enables long-term high-performance switch-scan spelling", "url": "https://doi.org/10.21203/rs.3.rs-3158792/v1", "date": "2023-09-25", "written_by": "makers", "quote": "a new click decoder achieved comparable performance despite being trained with even less data (< 15 min, within one day)." } ], "replication": { "produced_by": [ "High-density ECoG over sensorimotor cortex", "LSTM click detector trained on under 44 minutes of data", "Switch-scanning speller interface" ], "must_hold": [ "Signal power modulation remains stable (a transient reduction interrupted use of the fixed model)", "Laboratory setting with research staff" ], "echoes": [ { "date": "2016-11-12", "setting": "Utrecht fully implanted click-based BCI, home use over seven years", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5326682/" } ] }, "paired_incident": null, "headline": "Johns Hopkins LSTM BCI lets a man with ALS spell for 90 days", "metric": "median spelling rate of 10.2 characters per minute", "comparator": { "against": "the Utrecht fully implanted switch-scan BCI reported by Vansteensel et al. 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(Communications Medicine, 22 October 2024) report a clinical-trial participant with ALS (NCT03567213) at Johns Hopkins. He had a chronically implanted high-density electrocorticographic BCI over sensorimotor cortex. High-gamma power vectors from 128 channels fed a long short-term memory layer with 25 hidden units and fully connected layers. These classified rest versus grasp every 100 ms. The click detector was trained on almost 44 minutes of data (480 trials) collected up to 21 days before use. It then ran for 90 days without retraining. The participant controlled a switch-scanning speller for a total of 626 minutes with a median spelling rate of 10.2 characters per minute. The paper states all data collection and testing were performed in the laboratory. No home use is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model detected intended clicks in cortical recordings." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Researchers implemented the network with Keras and TensorFlow 2.8.0." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A long short-term memory network with 25 hidden units and two fully connected layers." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "LSTM (25 hidden units) with two fully connected layers, Keras/TensorFlow 2.8.0" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Click-based electrocorticographic brain-computer interface with an LSTM click detector (NCT03567213)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Johns Hopkins University (Crone lab and co-authors)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Johns Hopkins LSTM click detector lets a man with ALS spell 10.2 characters a minute for 90 days without retraining", "headline": "Johns Hopkins LSTM BCI lets a man with ALS spell for 90 days" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b059f22bdf116efa4509e635e6ac4bf814e4f499ee57f99e139b1e9c181ce5cc" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Candrea et al. (Communications Medicine, 22 October 2024) report a clinical-trial participant with ALS (NCT03567213) at Johns Hopkins. He had a chronically implanted high-density electrocorticographic BCI over sensorimotor cortex. High-gamma power vectors from 128 channels fed a long short-term memory layer with 25 hidden units and fully connected layers. These classified rest versus grasp every 100 ms. The click detector was trained on almost 44 minutes of data (480 trials) collected up to 21 days before use. It then ran for 90 days without retraining. The participant controlled a switch-scanning speller for a total of 626 minutes with a median spelling rate of 10.2 characters per minute. The paper states all data collection and testing were performed in the laboratory. No home use is reported.", "replication": { "produced_by": [ "High-density ECoG over sensorimotor cortex", "LSTM click detector trained on under 44 minutes of data", "Switch-scanning speller interface" ], "must_hold": [ "Signal power modulation remains stable (a transient reduction interrupted use of the fixed model)", "Laboratory setting with research staff" ], "echoes": [ { "date": "2016-11-12", "setting": "Utrecht fully implanted click-based BCI, home use over seven years", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC5326682/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0124", "title": "Code Intelligence's Spark agent found a heap use-after-free in wolfSSL's pem_read_bio_key() during its beta test; wolfSSL merged a fix within days and shipped it in 5.7.6", "summary": "Spark, an AI fuzz-test agent, found a heap use-after-free in wolfSSL in late Oct 2024; fixed in PR 8139 and shipped in 5.7.6 on 31 December 2024.", "date_observed": "2024-11-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Spark is the AI test agent in Code Intelligence GmbH's CI Fuzz product. Its final beta test in late October 2024 ran it on wolfSSL, an open-source cryptography library for embedded and IoT devices. By the vendor's account, after one command the agent chose the target, generated and ran a fuzz test and exposed a heap use-after-free in pem_read_bio_key(). There a BIO write-back could reallocate a buffer still referenced by a pointer. The vendor reported it to wolfSSL, which merged a fix in PR 8139 on 1 November 2024. It shipped in release 5.7.6 on 31 December 2024, crediting “Peter” in the release notes. The vendor's blog post on the find is by engineer Peter Samarin.", "category": "benefit created", "unexpected": false, "purpose": "Spark was built to find bugs and vulnerabilities autonomously by selecting functions to fuzz and generating and running fuzz tests. Finding this flaw was exactly that function, exercised in the vendor's own beta test.", "system": "Spark, AI test agent in Code Intelligence's CI Fuzz (invoked as 'cifuzz spark')", "model_version": null, "developer": "Code Intelligence GmbH", "deployer": "Code Intelligence GmbH (beta test run by the vendor)", "location": "Bonn, Germany", "domain": "Software security / open-source cryptography library testing", "segment": "Open-source TLS and cryptography library for embedded and IoT systems", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-01-09-764d" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "wolfSSL received a reproducible report of a heap use-after-free in a private-key parsing path. It merged the fix within days (PR 8139, 1 November 2024) and shipped it in 5.7.6 on 31 December 2024. The maintainers listed it among bug fixes rather than in the release's Vulnerabilities section. No CVE for it appears on wolfSSL's vulnerabilities page. The vendor itself says the exploit conditions “don't seem easy to meet”, so the benefit is material but bounded." } ], "ai_role": { "status": "assessed", "statement": "On the vendor's account, Spark selected the target, generated the fuzz test and ran it after a single “cifuzz spark” command. One manual step confirmed that the finding was real and exploitable under narrow conditions. wolfSSL's pull request and release notes confirm the bug, its location in pem_read_bio_key(), the timing and the reporter's first name. They mention neither AI nor Code Intelligence. The autonomous discovery therefore rests on the vendor's statements, repeated by QA Financial and SC Media, not on an independent test." }, "evidence": [ { "kind": "other", "citation": "wolfSSL (2024). wolfSSL Release 5.7.6 (Dec 31, 2024), release notes, Bug Fixes. GitHub, wolfSSL/wolfssl, tag v5.7.6-stable, published 31 December 2024.", "title": "wolfSSL Release 5.7.6 (Dec 31, 2024)", "url": "https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.6-stable", "date": "2024-12-31", "written_by": "beneficiary", "quote": "Fix for potential heap use after free with wolfSSL_PEM_read_bio_PrivateKey. Thanks to Peter for the issue reported. (PR 8139)" }, { "kind": "other", "citation": "douzzer (2024). 20241031-fixes. wolfSSL/wolfssl pull request 8139, GitHub, opened and merged 1 November 2024; commit b41ce042 changes src/pk.c.", "title": "20241031-fixes (wolfSSL pull request 8139)", "url": "https://github.com/wolfSSL/wolfssl/pull/8139", "date": "2024-11-01", "written_by": "beneficiary", "quote": "src/pk.c: in pem_read_bio_key(), fix invalid read (ZD#18875)." }, { "kind": "press release", "citation": "Samarin, P. (2025). How AI-generated fuzz test uncovered a vulnerability in wolfSSL. Code Intelligence blog, 3 January 2025; Wayback Machine capture of 9 January 2025 (the live domain did not resolve on 20 October 2026).", "title": "How AI-generated fuzz test uncovered a vulnerability in wolfSSL", "url": "https://web.archive.org/web/20250109141038/https://www.code-intelligence.com/blog/ai-generated-fuzz-test-wolfssl-vulnerability", "date": "2025-01-03", "written_by": "makers", "quote": "The vulnerability was identified in wolfSSL, an open-source cryptography library widely used in developing embedded devices and IoT systems, during the final week of October 2024." }, { "kind": "press release", "citation": "Code Intelligence (2025). Code Intelligence Launches Spark, Its AI Test Agent That Autonomously Uncovers Vulnerabilities Without Human Interaction. PR Newswire, Bonn, 9 January 2025.", "title": "Code Intelligence Launches Spark, Its AI Test Agent That Autonomously Uncovers Vulnerabilities Without Human Interaction", "url": "https://www.prnewswire.com/news-releases/code-intelligence-launches-spark-its-ai-test-agent-that-autonomously-uncovers-vulnerabilities-without-human-interaction-302345548.html", "date": "2025-01-09", "written_by": "makers", "quote": "The only human involvement was launching a single command to run the AI Test Agent; analyzing the code, generating a relevant test case, and running it was done autonomously." }, { "kind": "news report", "citation": "Willems, M. (2025). German startup to launch world's first AI test agent. QA Financial, 13 January 2025.", "title": "German startup to launch world's first AI test agent", "url": "https://qa-financial.com/german-startup-to-launch-worlds-first-ai-test-agent/", "date": "2025-01-13", "written_by": "independent", "quote": "Brueggemann claimed his firm shared the bug with WolfSSL’s team, which went on to issue a warning and update in December of last year." }, { "kind": "news report", "citation": "French, L. (2025). How AI can revolutionize vulnerability research. SC Media, 3 February 2025.", "title": "How AI can revolutionize vulnerability research", "url": "https://www.scworld.com/feature/how-ai-can-revolutionize-vulnerability-research", "date": "2025-02-03", "written_by": "independent", "quote": "Code Intelligence’s Spark autonomously discovering a heap-based user-after-free vulnerability in popular open-source wolfSSL library during its beta testing in October 2024." } ], "replication": { "produced_by": [ "wolfSSL's source tree (before 5.7.6) set up as a CI Fuzz project by the vendor", "A single “cifuzz spark” command, after which the agent chose pem_read_bio_key() as a target and generated and ran a fuzz test", "A sanitizer-detectable heap use-after-free in the BIO write-back path of pem_read_bio_key() that a generated input could trigger", "A maintainer team that tracked the report as ZD#18875 and merged a fix within three days of the discovery" ], "must_hold": [ "A human must confirm the finding. The vendor says the one manual step was assessing that the bug exists and is exploitable under specific conditions", "The beneficiary must be an identifiable project with a public fix record. Without wolfSSL's PR and release notes the event would rest on vendor claims alone", "The AI's share of the work is described only by the vendor. wolfSSL's records name the reporter, not the tool, so the autonomy claim cannot be replicated without the vendor's product" ], "echoes": [] }, "paired_incident": null, "headline": "Code Intelligence's Spark finds a heap use-after-free in wolfSSL", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2024-12-31", "note": "wolfSSL shipped the fix in release 5.7.6 on 31 December 2024, crediting the reporter in its release notes, and Code Intelligence launched Spark publicly in January 2025.", "quote": "Fix for potential heap use after free with wolfSSL_PEM_read_bio_PrivateKey. Thanks to Peter for the issue reported. (PR 8139)", "url": "https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.6-stable" }, "value": null, "developer_country": "Germany", "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-01-09-764d", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.6-stable", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.northdata.de/Code+Intelligence+GmbH,+Bonn; https://www.northdata.de/Code+Intelligence+GmbH,+Bonn", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, two press releases from the makers and two other sources from the beneficiary. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0124", "catalog_version": "1.0.0", "source_fingerprint": "7ce94ae129baf748ac97ed8b650550a439de68537780b073ab8c984a81c60a8a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0124-source-0001", "AIBD-0124-source-0002", "AIBD-0124-source-0003", "AIBD-0124-source-0004", "AIBD-0124-source-0005", "AIBD-0124-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Code Intelligence GmbH", "deployer": "Code Intelligence GmbH (beta test run by the vendor)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "On the vendor's account, Spark selected the target, generated the fuzz test and ran it after a single “cifuzz spark” command. One manual step confirmed that the finding was real and exploitable under narrow conditions. wolfSSL's pull request and release notes confirm the bug, its location in pem_read_bio_key(), the timing and the reporter's first name. They mention neither AI nor Code Intelligence. The autonomous discovery therefore rests on the vendor's statements, repeated by QA Financial and SC Media, not on an independent test." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "On the vendor's account, Spark selected the target, generated the fuzz test and ran it after a single “cifuzz spark” command. One manual step confirmed that the finding was real and exploitable under narrow conditions. wolfSSL's pull request and release notes confirm the bug, its location in pem_read_bio_key(), the timing and the reporter's first name. They mention neither AI nor Code Intelligence. The autonomous discovery therefore rests on the vendor's statements, repeated by QA Financial and SC Media, not on an independent test." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "wolfSSL received a reproducible report of a heap use-after-free in a private-key parsing path. It merged the fix within days (PR 8139, 1 November 2024) and shipped it in 5.7.6 on 31 December 2024. The maintainers listed it among bug fixes rather than in the release's Vulnerabilities section. No CVE for it appears on wolfSSL's vulnerabilities page. The vendor itself says the exploit conditions “don't seem easy to meet”, so the benefit is material but bounded." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, two press releases from the makers and two other sources from the beneficiary. 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SC Media, 3 February 2025.", "title": "How AI can revolutionize vulnerability research", "url": "https://www.scworld.com/feature/how-ai-can-revolutionize-vulnerability-research", "date": "2025-02-03", "written_by": "independent", "quote": "Code Intelligence’s Spark autonomously discovering a heap-based user-after-free vulnerability in popular open-source wolfSSL library during its beta testing in October 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0124-source-0001", "AIBD-0124-source-0002", "AIBD-0124-source-0003", "AIBD-0124-source-0004", "AIBD-0124-source-0005", "AIBD-0124-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "wolfSSL (2024). wolfSSL Release 5.7.6 (Dec 31, 2024), release notes, Bug Fixes. GitHub, wolfSSL/wolfssl, tag v5.7.6-stable, published 31 December 2024.", "title": "wolfSSL Release 5.7.6 (Dec 31, 2024)", "url": "https://github.com/wolfSSL/wolfssl/releases/tag/v5.7.6-stable", "date": "2024-12-31", "written_by": "beneficiary", "quote": "Fix for potential heap use after free with wolfSSL_PEM_read_bio_PrivateKey. Thanks to Peter for the issue reported. (PR 8139)" }, { "kind": "other", "citation": "douzzer (2024). 20241031-fixes. wolfSSL/wolfssl pull request 8139, GitHub, opened and merged 1 November 2024; commit b41ce042 changes src/pk.c.", "title": "20241031-fixes (wolfSSL pull request 8139)", "url": "https://github.com/wolfSSL/wolfssl/pull/8139", "date": "2024-11-01", "written_by": "beneficiary", "quote": "src/pk.c: in pem_read_bio_key(), fix invalid read (ZD#18875)." }, { "kind": "press release", "citation": "Samarin, P. (2025). How AI-generated fuzz test uncovered a vulnerability in wolfSSL. Code Intelligence blog, 3 January 2025; Wayback Machine capture of 9 January 2025 (the live domain did not resolve on 20 October 2026).", "title": "How AI-generated fuzz test uncovered a vulnerability in wolfSSL", "url": "https://web.archive.org/web/20250109141038/https://www.code-intelligence.com/blog/ai-generated-fuzz-test-wolfssl-vulnerability", "date": "2025-01-03", "written_by": "makers", "quote": "The vulnerability was identified in wolfSSL, an open-source cryptography library widely used in developing embedded devices and IoT systems, during the final week of October 2024." }, { "kind": "press release", "citation": "Code Intelligence (2025). Code Intelligence Launches Spark, Its AI Test Agent That Autonomously Uncovers Vulnerabilities Without Human Interaction. PR Newswire, Bonn, 9 January 2025.", "title": "Code Intelligence Launches Spark, Its AI Test Agent That Autonomously Uncovers Vulnerabilities Without Human Interaction", "url": "https://www.prnewswire.com/news-releases/code-intelligence-launches-spark-its-ai-test-agent-that-autonomously-uncovers-vulnerabilities-without-human-interaction-302345548.html", "date": "2025-01-09", "written_by": "makers", "quote": "The only human involvement was launching a single command to run the AI Test Agent; analyzing the code, generating a relevant test case, and running it was done autonomously." }, { "kind": "news report", "citation": "Willems, M. (2025). German startup to launch world's first AI test agent. QA Financial, 13 January 2025.", "title": "German startup to launch world's first AI test agent", "url": "https://qa-financial.com/german-startup-to-launch-worlds-first-ai-test-agent/", "date": "2025-01-13", "written_by": "independent", "quote": "Brueggemann claimed his firm shared the bug with WolfSSL’s team, which went on to issue a warning and update in December of last year." }, { "kind": "news report", "citation": "French, L. (2025). How AI can revolutionize vulnerability research. SC Media, 3 February 2025.", "title": "How AI can revolutionize vulnerability research", "url": "https://www.scworld.com/feature/how-ai-can-revolutionize-vulnerability-research", "date": "2025-02-03", "written_by": "independent", "quote": "Code Intelligence’s Spark autonomously discovering a heap-based user-after-free vulnerability in popular open-source wolfSSL library during its beta testing in October 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Spark, an AI fuzz-test agent, found a heap use-after-free in wolfSSL in late Oct 2024; fixed in PR 8139 and shipped in 5.7.6 on 31 December 2024.", "account": "Spark is the AI test agent in Code Intelligence GmbH's CI Fuzz product. Its final beta test in late October 2024 ran it on wolfSSL, an open-source cryptography library for embedded and IoT devices. By the vendor's account, after one command the agent chose the target, generated and ran a fuzz test and exposed a heap use-after-free in pem_read_bio_key(). There a BIO write-back could reallocate a buffer still referenced by a pointer. The vendor reported it to wolfSSL, which merged a fix in PR 8139 on 1 November 2024. It shipped in release 5.7.6 on 31 December 2024, crediting “Peter” in the release notes. The vendor's blog post on the find is by engineer Peter Samarin." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Spark, AI test agent in Code Intelligence's CI Fuzz (invoked as 'cifuzz spark')" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Code Intelligence GmbH" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Code Intelligence's Spark agent found a heap use-after-free in wolfSSL's pem_read_bio_key() during its beta test; wolfSSL merged a fix within days and shipped it in 5.7.6", "headline": "Code Intelligence's Spark finds a heap use-after-free in wolfSSL" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7ce94ae129baf748ac97ed8b650550a439de68537780b073ab8c984a81c60a8a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Spark is the AI test agent in Code Intelligence GmbH's CI Fuzz product. Its final beta test in late October 2024 ran it on wolfSSL, an open-source cryptography library for embedded and IoT devices. By the vendor's account, after one command the agent chose the target, generated and ran a fuzz test and exposed a heap use-after-free in pem_read_bio_key(). There a BIO write-back could reallocate a buffer still referenced by a pointer. The vendor reported it to wolfSSL, which merged a fix in PR 8139 on 1 November 2024. It shipped in release 5.7.6 on 31 December 2024, crediting “Peter” in the release notes. The vendor's blog post on the find is by engineer Peter Samarin.", "replication": { "produced_by": [ "wolfSSL's source tree (before 5.7.6) set up as a CI Fuzz project by the vendor", "A single “cifuzz spark” command, after which the agent chose pem_read_bio_key() as a target and generated and ran a fuzz test", "A sanitizer-detectable heap use-after-free in the BIO write-back path of pem_read_bio_key() that a generated input could trigger", "A maintainer team that tracked the report as ZD#18875 and merged a fix within three days of the discovery" ], "must_hold": [ "A human must confirm the finding. The vendor says the one manual step was assessing that the bug exists and is exploitable under specific conditions", "The beneficiary must be an identifiable project with a public fix record. Without wolfSSL's PR and release notes the event would rest on vendor claims alone", "The AI's share of the work is described only by the vendor. wolfSSL's records name the reporter, not the tool, so the autonomy claim cannot be replicated without the vendor's product" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0336", "title": "Udbetaling Danmark's fraud-control models may have produced 135, 36 and 72 cases with benefits stopped or reduced in 2023", "summary": "UDK/ATP ML fraud models (about 60 since 2019): 2023 figures of 135, 36 and 72 cases with revenue from three models; Amnesty (Nov 2024) calls their effectiveness questionable.", "date_observed": "2024-11-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Udbetaling Danmark (UDK), the Danish public authority that has centralized welfare payments since 2012, has its benefits administered by ATP (Arbejdsmarkedets Tillaegspension). ATP designs the fraud-control components of UDK's Joint Data Unit (Den Faelles Dataenhed, established 2014 per the University of Copenhagen's Offentlig AI database). NNIT A/S is the supplier. As of 2019 UDK was reported to use up to 60 algorithms for fraud detection and other purposes. The registry describes profiling and machine learning (it names Naive Bayes classification and cluster analysis) run on linked register data. In a letter to Amnesty International before November 2024, UDK supplied its 2023 statistics for three data-driven controls. The “Really Single” model produced 412 requested cases, 292 established control cases and 135 cases with revenue (benefits stopped or reduced). “Model Abroad” (unreported departures, state and disability pension) gave 511, 351 and 36. The parental-leave controls including the “Fictitious Employment” model gave 491, 207 and 72. UDK cautioned that cases with revenue in a year are not necessarily a proportion of cases established that year. A UDK/ATP control official told Amnesty the team manages 5,000 to 6,000 cases a year, of which around 1,800 come from the models. Amnesty's report of 12 November 2024 concludes it is questionable whether the algorithms are effective. It finds most opened cases end with no further action and the system risks discrimination and mass surveillance. A Copenhagen Municipality control official said more often than not there is no fraud in the cases UDK sends. Background sources give earlier yields. AlgorithmWatch (2020) reports 2017 and 2018 controls unveiled about half a billion kroner in erroneous payments. The Automating Society 2020 Denmark chapter cites a July 2019 report. It counted 705 cases in 2017 and 1,094 in 2018 where payments were stopped, adjusted or repaid, out of 2.7 million screened beneficiaries. The dm.dk FOI report (October 2024) and ATP's page are not among the sources. The report said nearly all 1.2 million pensioners were screened and only 36 cases in 2023 ended with a benefit stopped or reduced. That matches the Model Abroad row. ATP's page credits 260 million kr. a year of savings to IT modernization generally. The 2023 figures carry no day.", "category": "harm prevented", "unexpected": false, "purpose": "Built to flag benefit recipients at elevated risk of receiving unentitled payments for manual control by UDK's control team. The recorded outcome, cases with benefits stopped or reduced, is that purpose.", "system": "Udbetaling Danmark / ATP Den Faelles Dataenhed fraud-control models (about 60 profiling and machine-learning models as of 2019, including 'Really Single', 'Model Abroad' and 'Fictitious Employment')", "model_version": null, "developer": "ATP (Arbejdsmarkedets Tillaegspension) with NNIT A/S as supplier, for Udbetaling Danmark", "deployer": "Udbetaling Danmark (public authority), administered by ATP", "location": "Denmark (national)", "domain": "Public administration: social benefits fraud control", "segment": "National welfare payments authority", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary of the controls is identified. The people directly affected are those investigated. By Amnesty's reading of UDK's figures, 54% to almost 90% of opened cases per model ended with no further action." }, { "group": "organizational", "depth": 1, "reason": "UDK's own 2023 figures: 135, 36 and 72 cases with revenue from three models against 412, 511 and 491 requested cases. No amounts are given and the authority says yearly figures are not directly comparable." }, { "group": "societal", "depth": 1, "reason": "Controls cover about 2.4 million recipients paid around DKK 241 billion in 2021. The documented yield is a few hundred cases a year. Amnesty's report disputes the necessity and proportionality of the processing." } ], "ai_role": { "status": "assessed", "statement": "The models select “requested cases” that UDK's HOK control team screens and investigates. Decisions to stop or reduce benefits are taken by humans after investigation. UDK measures model quality by the share of cases the team accepts for manual processing. Every outcome figure is a UDK statement (FOI responses and a letter) as reproduced verbatim in Amnesty International's report. No official publication of them is among the sources. Amnesty contests effectiveness and alleges discrimination risks, and UDK rejected parts of Amnesty's assessment. NNIT built the models to ATP's specifications. No developer-authored source is on record. The dm.dk report and ATP's page are not among the sources." }, "evidence": [ { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State (EUR 18/8709/2024), 12 Nov 2024, Table 5 'Statistics for data-driven controls used by UDK in 2023', p. 43.", "title": "Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State", "url": "https://www.amnesty.org/en/documents/eur18/8709/2024/en/", "date": "2024-11-12", "written_by": "independent", "quote": "135 Cases with revenue – the number of cases that were found to be fraudulent or erroneous after an investigation was conducted" }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, full report PDF, p. 30 (Fraud-control algorithms).", "title": "Coded Injustice (PDF), chapter on fraud-control algorithms", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "As of 2019, UDK were using up to 60 different algorithms for fraud detection and other purposes." }, { "kind": "report", "citation": "Udbetaling Danmark, letter to Amnesty International on 2023 performance of data-driven controls, as reproduced in Amnesty International (2024), Coded Injustice, pp. 42-43.", "title": "UDK statement on how it reports cases with revenue (reproduced in Coded Injustice)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "deployer", "quote": "Finally, we report how many cases result in citizens having their benefits stopped or reduced (number of cases with revenue)." }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, p. 44, assessment of effectiveness and interview with a UDK/ATP control official (11 Jan 2024).", "title": "Coded Injustice, p. 44 (effectiveness of the fraud-control algorithms)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "It is questionable therefore whether the use of fraud control algorithms is effective at identifying fraud in this context." }, { "kind": "press release", "citation": "Amnesty International (2024). Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups – report. Press release, 12 Nov 2024.", "title": "Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups", "url": "https://www.amnesty.org/en/latest/news/2024/11/denmark-ai-powered-welfare-system-fuels-mass-surveillance-and-risks-discriminating-against-marginalized-groups/", "date": "2024-11-12", "written_by": "independent", "quote": "UDK and ATP use a system of up to 60 algorithmic models purportedly designed to detect social benefits fraud and flag individuals for further investigations." }, { "kind": "other", "citation": "University of Copenhagen, Faculty of Law (n.d.). Offentlig AI database entry 'Kontrol med udbetaling af ydelser' (Udbetaling Danmark; status: I brug; supplier NNIT A/S; about 60 models as of 2019).", "title": "Kontrol med udbetaling af ydelser (Offentlig AI database entry)", "url": "https://offentlig-ai.dk/projekter/kontrol-med-udbetaling-ydelser", "date": null, "written_by": "independent", "quote": "Udbetaling Danmark udvikler og bruger modeller til kontrol på områder, hvor myndigheden har erfaret, at der forekommer uberettigede udbetalinger." }, { "kind": "report", "citation": "Kayser-Bril, N. (2020). In a quest to optimize welfare management, Denmark built a surveillance behemoth. AlgorithmWatch, 6 Aug 2020.", "title": "In a quest to optimize welfare management, Denmark built a surveillance behemoth", "url": "https://algorithmwatch.org/en/udbetaling-danmark/", "date": "2020-08-06", "written_by": "independent", "quote": "unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros)" }, { "kind": "report", "citation": "Alfter, B. (2020). Denmark chapter, section 'Controlling social welfare recipients'. In AlgorithmWatch and Bertelsmann Stiftung, Automating Society Report 2020.", "title": "Automating Society Report 2020: Denmark", "url": "https://automatingsociety.algorithmwatch.org/report2020/denmark/", "date": null, "written_by": "independent", "quote": "leading only to 705 cases in 2017 and 1094 cases in 2018 where the payments were stopped, adjusted, or paid back because of mistakes" }, { "kind": "news report", "citation": "Amnesty International Algorithmic Accountability Lab (2024). How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System. Global Investigative Journalism Network, 14 Nov 2024.", "title": "How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System", "url": "https://gijn.org/stories/amnesty-internationals-investigation-algorithms-denmarks-welfare-system/", "date": "2024-11-14", "written_by": "independent", "quote": "ATP is responsible for designing the fraud control components of UDK's Joint Data Unit." } ], "replication": { "produced_by": [ "Register linkage of benefits data with civil, housing, business, tax, income, health and employment registers under a 2015 legal authorization", "About 60 profiling and machine-learning models developed by NNIT to ATP's specifications", "A UDK/ATP control team (HOK) that manually screens model output into established control cases and investigates them", "A legal duty to also process all externally reported cases, which the control team says limits the share drawn from the models to about 30%" ], "must_hold": [ "Legal basis for register linkage and model use remains in force despite Amnesty's challenge and the dispute over classification under the EU AI Act", "Control-team capacity of about 5,000 to 6,000 cases a year", "Models continue to be monitored on their training cases, since UDK documents no evaluation metrics", "Political tolerance of the system after the November 2024 criticism" ], "echoes": [ { "date": null, "setting": "2017 and 2018 controls over 2.7 million screened beneficiaries, as reported in a July 2019 report cited by Automating Society 2020: 705 and 1,094 cases with payments stopped, adjusted or repaid", "model_version": null, "outcome": "recurred", "source": "https://automatingsociety.algorithmwatch.org/report2020/denmark/" }, { "date": null, "setting": "dm.dk FOI report, October 2024, as read by an earlier check (not re-read): nearly all 1.2 million pensioners screened, 36 cases in 2023 ending with a benefit stopped or reduced", "model_version": null, "outcome": "recurred", "source": "dm.dk FOI report, October 2024, as summarized in an earlier check of this case; consistent with the Model Abroad row of Amnesty's Table 5" } ] }, "paired_incident": null, "headline": "UDK fraud models may have yielded 135, 36 and 72 cases", "metric": "2023 figures of 135, 36 and 72 cases with revenue from three models", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later development in the controls is established. The employment minister forwarded a UDK board account to Parliament (Folketinget DIU Alm.del 2024-25 bilag 32), but its contents remain unverified.", "quote": null, "url": null }, "value": { "amount": "half a billion Danish crowns (approximately 70 million euros)", "what": "erroneous payments unveiled by UDK and municipal controls in 2017 and 2018; the source says it is unclear how much was recovered and that the figure includes averted future payments, and it does not isolate the models", "who": "Udbetaling Danmark and the municipalities (the Danish public purse)", "estimate": false, "quote": "In 2017 and 2018, controls by UDK and municipalities unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros). It is unclear what amount was recovered, what was not recovered due to the beneficiary’s incapacity to repay, and what was an accounting trick (the figure includes future payments that were averted because of the control).", "url": "https://algorithmwatch.org/en/udbetaling-danmark/" }, "developer_country": "Denmark", "deployer_country": "Denmark", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://algorithmwatch.org/en/udbetaling-danmark/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.atp.dk/en/about-atp; https://da.wikipedia.org/wiki/Udbetaling_Danmark", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: four independent reports, one independent news report, one independent press release and one other independent source. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0336", "catalog_version": "1.0.0", "source_fingerprint": "f17dd05704428e7ad3e78e0e01f15067f7cee4c98a7dc6f09bc1eea7d43f4f91", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0336-source-0001", "AIBD-0336-source-0002", "AIBD-0336-source-0003", "AIBD-0336-source-0004", "AIBD-0336-source-0005", "AIBD-0336-source-0006", "AIBD-0336-source-0007", "AIBD-0336-source-0008", "AIBD-0336-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0336-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ATP (Arbejdsmarkedets Tillaegspension) with NNIT A/S as supplier, for Udbetaling Danmark", "deployer": "Udbetaling Danmark (public authority), administered by ATP" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The models select “requested cases” that UDK's HOK control team screens and investigates. Decisions to stop or reduce benefits are taken by humans after investigation. UDK measures model quality by the share of cases the team accepts for manual processing. Every outcome figure is a UDK statement (FOI responses and a letter) as reproduced verbatim in Amnesty International's report. No official publication of them is among the sources. Amnesty contests effectiveness and alleges discrimination risks, and UDK rejected parts of Amnesty's assessment. NNIT built the models to ATP's specifications. No developer-authored source is on record. The dm.dk report and ATP's page are not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Udbetaling Danmark’s models selected benefit files for investigation. Staff screened the selections before deciding whether to investigate further.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The models select “requested cases” that UDK's HOK control team screens and investigates. Decisions to stop or reduce benefits are taken by humans after investigation. UDK measures model quality by the share of cases the team accepts for manual processing. Every outcome figure is a UDK statement (FOI responses and a letter) as reproduced verbatim in Amnesty International's report. No official publication of them is among the sources. Amnesty contests effectiveness and alleges discrimination risks, and UDK rejected parts of Amnesty's assessment. NNIT built the models to ATP's specifications. No developer-authored source is on record. The dm.dk report and ATP's page are not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary of the controls is identified. The people directly affected are those investigated. By Amnesty's reading of UDK's figures, 54% to almost 90% of opened cases per model ended with no further action." }, { "group": "organizational", "depth": 1, "reason": "UDK's own 2023 figures: 135, 36 and 72 cases with revenue from three models against 412, 511 and 491 requested cases. No amounts are given and the authority says yearly figures are not directly comparable." }, { "group": "societal", "depth": 1, "reason": "Controls cover about 2.4 million recipients paid around DKK 241 billion in 2021. The documented yield is a few hundred cases a year. Amnesty's report disputes the necessity and proportionality of the processing." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: four independent reports, one independent news report, one independent press release and one other independent source. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary of the controls is identified. The people directly affected are those investigated. By Amnesty's reading of UDK's figures, 54% to almost 90% of opened cases per model ended with no further action." }, { "group": "organizational", "depth": 1, "reason": "UDK's own 2023 figures: 135, 36 and 72 cases with revenue from three models against 412, 511 and 491 requested cases. No amounts are given and the authority says yearly figures are not directly comparable." }, { "group": "societal", "depth": 1, "reason": "Controls cover about 2.4 million recipients paid around DKK 241 billion in 2021. The documented yield is a few hundred cases a year. Amnesty's report disputes the necessity and proportionality of the processing." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The agency reports several hundred adjustments to benefits, without amounts or a matched comparison. Amnesty’s reading suggests that most opened investigations produced no further action. No individual benefit or wider improvement is established." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary of the controls is identified. The people directly affected are those investigated. By Amnesty's reading of UDK's figures, 54% to almost 90% of opened cases per model ended with no further action." }, { "group": "organizational", "depth": 1, "reason": "UDK's own 2023 figures: 135, 36 and 72 cases with revenue from three models against 412, 511 and 491 requested cases. No amounts are given and the authority says yearly figures are not directly comparable." }, { "group": "societal", "depth": 1, "reason": "Controls cover about 2.4 million recipients paid around DKK 241 billion in 2021. The documented yield is a few hundred cases a year. Amnesty's report disputes the necessity and proportionality of the processing." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "half a billion Danish crowns (approximately 70 million euros)", "what": "erroneous payments unveiled by UDK and municipal controls in 2017 and 2018; the source says it is unclear how much was recovered and that the figure includes averted future payments, and it does not isolate the models", "who": "Udbetaling Danmark and the municipalities (the Danish public purse)", "estimate": false, "quote": "In 2017 and 2018, controls by UDK and municipalities unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros). It is unclear what amount was recovered, what was not recovered due to the beneficiary’s incapacity to repay, and what was an accounting trick (the figure includes future payments that were averted because of the control).", "url": "https://algorithmwatch.org/en/udbetaling-danmark/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "half a billion Danish crowns (approximately 70 million euros)", "what": "erroneous payments unveiled by UDK and municipal controls in 2017 and 2018; the source says it is unclear how much was recovered and that the figure includes averted future payments, and it does not isolate the models", "who": "Udbetaling Danmark and the municipalities (the Danish public purse)", "estimate": false, "quote": "In 2017 and 2018, controls by UDK and municipalities unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros). It is unclear what amount was recovered, what was not recovered due to the beneficiary’s incapacity to repay, and what was an accounting trick (the figure includes future payments that were averted because of the control).", "url": "https://algorithmwatch.org/en/udbetaling-danmark/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "half a billion Danish crowns (approximately 70 million euros)", "what": "erroneous payments unveiled by UDK and municipal controls in 2017 and 2018; the source says it is unclear how much was recovered and that the figure includes averted future payments, and it does not isolate the models", "who": "Udbetaling Danmark and the municipalities (the Danish public purse)", "estimate": false, "quote": "In 2017 and 2018, controls by UDK and municipalities unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros). It is unclear what amount was recovered, what was not recovered due to the beneficiary’s incapacity to repay, and what was an accounting trick (the figure includes future payments that were averted because of the control).", "url": "https://algorithmwatch.org/en/udbetaling-danmark/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The three controls reported 135, 36, and 72 cases with payments stopped or reduced in 2023. The same controls requested 412, 511, and 491 cases, but the agency cautions that the annual totals do not necessarily refer to the same cases." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Cases requested, cases opened for investigation, and cases in which benefits were stopped or reduced." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The outcome figures come from the agency’s letter reproduced by Amnesty. No monetary amounts or matched case cohorts are given. Amnesty disputes the controls’ effectiveness and necessity, while the agency rejected parts of that assessment." } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later development in the controls is established. The employment minister forwarded a UDK board account to Parliament (Folketinget DIU Alm.del 2024-25 bilag 32), but its contents remain unverified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Staff investigated the files and decided whether benefits should be reduced or stopped." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0336" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Udbetaling Danmark is the intended institutional beneficiary. No individual beneficiary of the controls is identified." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "ratings", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Udbetaling Danmark is the intended institutional beneficiary. No individual beneficiary of the controls is identified." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "display": { "answer": "No count of beneficiaries is established. The screened population is not a measure of people who benefited." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Udbetaling Danmark (UDK), the Danish public authority that has centralized welfare payments since 2012, has its benefits administered by ATP (Arbejdsmarkedets Tillaegspension). ATP designs the fraud-control components of UDK's Joint Data Unit (Den Faelles Dataenhed, established 2014 per the University of Copenhagen's Offentlig AI database). NNIT A/S is the supplier. As of 2019 UDK was reported to use up to 60 algorithms for fraud detection and other purposes. The registry describes profiling and machine learning (it names Naive Bayes classification and cluster analysis) run on linked register data. In a letter to Amnesty International before November 2024, UDK supplied its 2023 statistics for three data-driven controls. The “Really Single” model produced 412 requested cases, 292 established control cases and 135 cases with revenue (benefits stopped or reduced). “Model Abroad” (unreported departures, state and disability pension) gave 511, 351 and 36. The parental-leave controls including the “Fictitious Employment” model gave 491, 207 and 72. UDK cautioned that cases with revenue in a year are not necessarily a proportion of cases established that year. A UDK/ATP control official told Amnesty the team manages 5,000 to 6,000 cases a year, of which around 1,800 come from the models. Amnesty's report of 12 November 2024 concludes it is questionable whether the algorithms are effective. It finds most opened cases end with no further action and the system risks discrimination and mass surveillance. A Copenhagen Municipality control official said more often than not there is no fraud in the cases UDK sends. Background sources give earlier yields. AlgorithmWatch (2020) reports 2017 and 2018 controls unveiled about half a billion kroner in erroneous payments. The Automating Society 2020 Denmark chapter cites a July 2019 report. It counted 705 cases in 2017 and 1,094 in 2018 where payments were stopped, adjusted or repaid, out of 2.7 million screened beneficiaries. The dm.dk FOI report (October 2024) and ATP's page are not among the sources. The report said nearly all 1.2 million pensioners were screened and only 36 cases in 2023 ended with a benefit stopped or reduced. That matches the Model Abroad row. ATP's page credits 260 million kr. a year of savings to IT modernization generally. The 2023 figures carry no day.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Udbetaling Danmark reported 135, 36, and 72 cases with benefits stopped or reduced through three controls in 2023." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary of the controls is identified. The people directly affected are those investigated. By Amnesty's reading of UDK's figures, 54% to almost 90% of opened cases per model ended with no further action." }, { "group": "organizational", "depth": 1, "reason": "UDK's own 2023 figures: 135, 36 and 72 cases with revenue from three models against 412, 511 and 491 requested cases. No amounts are given and the authority says yearly figures are not directly comparable." }, { "group": "societal", "depth": 1, "reason": "Controls cover about 2.4 million recipients paid around DKK 241 billion in 2021. The documented yield is a few hundred cases a year. Amnesty's report disputes the necessity and proportionality of the processing." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Amnesty International alleges discrimination risks and disproportionate surveillance. Udbetaling Danmark disputed parts of its assessment." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Amnesty International alleges discrimination risks and disproportionate surveillance. Udbetaling Danmark disputed parts of its assessment." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to flag benefit recipients at elevated risk of receiving unentitled payments for manual control by UDK's control team. The recorded outcome, cases with benefits stopped or reduced, is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Denmark (national)", "developer_country": "Denmark", "deployer_country": "Denmark" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to flag benefit recipients at elevated risk of receiving unentitled payments for manual control by UDK's control team. The recorded outcome, cases with benefits stopped or reduced, is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-11-12", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://algorithmwatch.org/en/udbetaling-danmark/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.atp.dk/en/about-atp; https://da.wikipedia.org/wiki/Udbetaling_Danmark", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Register linkage of benefits data with civil, housing, business, tax, income, health and employment registers under a 2015 legal authorization", "About 60 profiling and machine-learning models developed by NNIT to ATP's specifications", "A UDK/ATP control team (HOK) that manually screens model output into established control cases and investigates them", "A legal duty to also process all externally reported cases, which the control team says limits the share drawn from the models to about 30%" ], "must_hold": [ "Legal basis for register linkage and model use remains in force despite Amnesty's challenge and the dispute over classification under the EU AI Act", "Control-team capacity of about 5,000 to 6,000 cases a year", "Models continue to be monitored on their training cases, since UDK documents no evaluation metrics", "Political tolerance of the system after the November 2024 criticism" ], "echoes": [ { "setting": "2017 and 2018 controls over 2.7 million screened beneficiaries, as reported in a July 2019 report cited by Automating Society 2020: 705 and 1,094 cases with payments stopped, adjusted or repaid", "outcome": "recurred", "source": "https://automatingsociety.algorithmwatch.org/report2020/denmark/" }, { "setting": "dm.dk FOI report, October 2024, as read by an earlier check (not re-read): nearly all 1.2 million pensioners screened, 36 cases in 2023 ending with a benefit stopped or reduced", "outcome": "recurred", "source": "dm.dk FOI report, October 2024, as summarized in an earlier check of this case; consistent with the Model Abroad row of Amnesty's Table 5" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Register linkage of benefits data with civil, housing, business, tax, income, health and employment registers under a 2015 legal authorization", "About 60 profiling and machine-learning models developed by NNIT to ATP's specifications", "A UDK/ATP control team (HOK) that manually screens model output into established control cases and investigates them", "A legal duty to also process all externally reported cases, which the control team says limits the share drawn from the models to about 30%" ], "must_hold": [ "Legal basis for register linkage and model use remains in force despite Amnesty's challenge and the dispute over classification under the EU AI Act", "Control-team capacity of about 5,000 to 6,000 cases a year", "Models continue to be monitored on their training cases, since UDK documents no evaluation metrics", "Political tolerance of the system after the November 2024 criticism" ], "echoes": [ { "setting": "2017 and 2018 controls over 2.7 million screened beneficiaries, as reported in a July 2019 report cited by Automating Society 2020: 705 and 1,094 cases with payments stopped, adjusted or repaid", "outcome": "recurred", "source": "https://automatingsociety.algorithmwatch.org/report2020/denmark/" }, { "setting": "dm.dk FOI report, October 2024, as read by an earlier check (not re-read): nearly all 1.2 million pensioners screened, 36 cases in 2023 ending with a benefit stopped or reduced", "outcome": "recurred", "source": "dm.dk FOI report, October 2024, as summarized in an earlier check of this case; consistent with the Model Abroad row of Amnesty's Table 5" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Register access and model use need a lawful basis. Staff must investigate the flagged cases. The cited material does not provide evaluation measures that would establish how well the controls perform." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://algorithmwatch.org/en/udbetaling-danmark/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.atp.dk/en/about-atp; https://da.wikipedia.org/wiki/Udbetaling_Danmark", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: social benefits fraud control", "segment": "National welfare payments authority" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State (EUR 18/8709/2024), 12 Nov 2024, Table 5 'Statistics for data-driven controls used by UDK in 2023', p. 43.", "title": "Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State", "url": "https://www.amnesty.org/en/documents/eur18/8709/2024/en/", "date": "2024-11-12", "written_by": "independent", "quote": "135 Cases with revenue – the number of cases that were found to be fraudulent or erroneous after an investigation was conducted" }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, full report PDF, p. 30 (Fraud-control algorithms).", "title": "Coded Injustice (PDF), chapter on fraud-control algorithms", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "As of 2019, UDK were using up to 60 different algorithms for fraud detection and other purposes." }, { "kind": "report", "citation": "Udbetaling Danmark, letter to Amnesty International on 2023 performance of data-driven controls, as reproduced in Amnesty International (2024), Coded Injustice, pp. 42-43.", "title": "UDK statement on how it reports cases with revenue (reproduced in Coded Injustice)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "deployer", "quote": "Finally, we report how many cases result in citizens having their benefits stopped or reduced (number of cases with revenue)." }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, p. 44, assessment of effectiveness and interview with a UDK/ATP control official (11 Jan 2024).", "title": "Coded Injustice, p. 44 (effectiveness of the fraud-control algorithms)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "It is questionable therefore whether the use of fraud control algorithms is effective at identifying fraud in this context." }, { "kind": "press release", "citation": "Amnesty International (2024). Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups – report. Press release, 12 Nov 2024.", "title": "Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups", "url": "https://www.amnesty.org/en/latest/news/2024/11/denmark-ai-powered-welfare-system-fuels-mass-surveillance-and-risks-discriminating-against-marginalized-groups/", "date": "2024-11-12", "written_by": "independent", "quote": "UDK and ATP use a system of up to 60 algorithmic models purportedly designed to detect social benefits fraud and flag individuals for further investigations." }, { "kind": "other", "citation": "University of Copenhagen, Faculty of Law (n.d.). Offentlig AI database entry 'Kontrol med udbetaling af ydelser' (Udbetaling Danmark; status: I brug; supplier NNIT A/S; about 60 models as of 2019).", "title": "Kontrol med udbetaling af ydelser (Offentlig AI database entry)", "url": "https://offentlig-ai.dk/projekter/kontrol-med-udbetaling-ydelser", "written_by": "independent", "quote": "Udbetaling Danmark udvikler og bruger modeller til kontrol på områder, hvor myndigheden har erfaret, at der forekommer uberettigede udbetalinger." }, { "kind": "report", "citation": "Kayser-Bril, N. (2020). In a quest to optimize welfare management, Denmark built a surveillance behemoth. AlgorithmWatch, 6 Aug 2020.", "title": "In a quest to optimize welfare management, Denmark built a surveillance behemoth", "url": "https://algorithmwatch.org/en/udbetaling-danmark/", "date": "2020-08-06", "written_by": "independent", "quote": "unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros)" }, { "kind": "report", "citation": "Alfter, B. (2020). Denmark chapter, section 'Controlling social welfare recipients'. In AlgorithmWatch and Bertelsmann Stiftung, Automating Society Report 2020.", "title": "Automating Society Report 2020: Denmark", "url": "https://automatingsociety.algorithmwatch.org/report2020/denmark/", "written_by": "independent", "quote": "leading only to 705 cases in 2017 and 1094 cases in 2018 where the payments were stopped, adjusted, or paid back because of mistakes" }, { "kind": "news report", "citation": "Amnesty International Algorithmic Accountability Lab (2024). How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System. Global Investigative Journalism Network, 14 Nov 2024.", "title": "How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System", "url": "https://gijn.org/stories/amnesty-internationals-investigation-algorithms-denmarks-welfare-system/", "date": "2024-11-14", "written_by": "independent", "quote": "ATP is responsible for designing the fraud control components of UDK's Joint Data Unit." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0336-source-0001", "AIBD-0336-source-0002", "AIBD-0336-source-0003", "AIBD-0336-source-0004", "AIBD-0336-source-0005", "AIBD-0336-source-0006", "AIBD-0336-source-0007", "AIBD-0336-source-0008", "AIBD-0336-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State (EUR 18/8709/2024), 12 Nov 2024, Table 5 'Statistics for data-driven controls used by UDK in 2023', p. 43.", "title": "Coded Injustice: Surveillance and Discrimination in Denmark's Automated Welfare State", "url": "https://www.amnesty.org/en/documents/eur18/8709/2024/en/", "date": "2024-11-12", "written_by": "independent", "quote": "135 Cases with revenue – the number of cases that were found to be fraudulent or erroneous after an investigation was conducted" }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, full report PDF, p. 30 (Fraud-control algorithms).", "title": "Coded Injustice (PDF), chapter on fraud-control algorithms", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "As of 2019, UDK were using up to 60 different algorithms for fraud detection and other purposes." }, { "kind": "report", "citation": "Udbetaling Danmark, letter to Amnesty International on 2023 performance of data-driven controls, as reproduced in Amnesty International (2024), Coded Injustice, pp. 42-43.", "title": "UDK statement on how it reports cases with revenue (reproduced in Coded Injustice)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "deployer", "quote": "Finally, we report how many cases result in citizens having their benefits stopped or reduced (number of cases with revenue)." }, { "kind": "report", "citation": "Amnesty International (2024). Coded Injustice, p. 44, assessment of effectiveness and interview with a UDK/ATP control official (11 Jan 2024).", "title": "Coded Injustice, p. 44 (effectiveness of the fraud-control algorithms)", "url": "https://www.amnesty.org/en/wp-content/uploads/2024/11/EUR1887092024ENGLISH.pdf", "date": "2024-11-12", "written_by": "independent", "quote": "It is questionable therefore whether the use of fraud control algorithms is effective at identifying fraud in this context." }, { "kind": "press release", "citation": "Amnesty International (2024). Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups – report. Press release, 12 Nov 2024.", "title": "Denmark: AI-powered welfare system fuels mass surveillance and risks discriminating against marginalized groups", "url": "https://www.amnesty.org/en/latest/news/2024/11/denmark-ai-powered-welfare-system-fuels-mass-surveillance-and-risks-discriminating-against-marginalized-groups/", "date": "2024-11-12", "written_by": "independent", "quote": "UDK and ATP use a system of up to 60 algorithmic models purportedly designed to detect social benefits fraud and flag individuals for further investigations." }, { "kind": "other", "citation": "University of Copenhagen, Faculty of Law (n.d.). Offentlig AI database entry 'Kontrol med udbetaling af ydelser' (Udbetaling Danmark; status: I brug; supplier NNIT A/S; about 60 models as of 2019).", "title": "Kontrol med udbetaling af ydelser (Offentlig AI database entry)", "url": "https://offentlig-ai.dk/projekter/kontrol-med-udbetaling-ydelser", "written_by": "independent", "quote": "Udbetaling Danmark udvikler og bruger modeller til kontrol på områder, hvor myndigheden har erfaret, at der forekommer uberettigede udbetalinger." }, { "kind": "report", "citation": "Kayser-Bril, N. (2020). In a quest to optimize welfare management, Denmark built a surveillance behemoth. AlgorithmWatch, 6 Aug 2020.", "title": "In a quest to optimize welfare management, Denmark built a surveillance behemoth", "url": "https://algorithmwatch.org/en/udbetaling-danmark/", "date": "2020-08-06", "written_by": "independent", "quote": "unveiled half a billion Danish crowns in erroneous payment (approximately 70 million euros)" }, { "kind": "report", "citation": "Alfter, B. (2020). Denmark chapter, section 'Controlling social welfare recipients'. In AlgorithmWatch and Bertelsmann Stiftung, Automating Society Report 2020.", "title": "Automating Society Report 2020: Denmark", "url": "https://automatingsociety.algorithmwatch.org/report2020/denmark/", "written_by": "independent", "quote": "leading only to 705 cases in 2017 and 1094 cases in 2018 where the payments were stopped, adjusted, or paid back because of mistakes" }, { "kind": "news report", "citation": "Amnesty International Algorithmic Accountability Lab (2024). How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System. Global Investigative Journalism Network, 14 Nov 2024.", "title": "How We Did It: Amnesty International's Investigation of Algorithms in Denmark's Welfare System", "url": "https://gijn.org/stories/amnesty-internationals-investigation-algorithms-denmarks-welfare-system/", "date": "2024-11-14", "written_by": "independent", "quote": "ATP is responsible for designing the fraud control components of UDK's Joint Data Unit." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "UDK/ATP ML fraud models (about 60 since 2019): 2023 figures of 135, 36 and 72 cases with revenue from three models; Amnesty (Nov 2024) calls their effectiveness questionable.", "account": "Udbetaling Danmark (UDK), the Danish public authority that has centralized welfare payments since 2012, has its benefits administered by ATP (Arbejdsmarkedets Tillaegspension). ATP designs the fraud-control components of UDK's Joint Data Unit (Den Faelles Dataenhed, established 2014 per the University of Copenhagen's Offentlig AI database). NNIT A/S is the supplier. As of 2019 UDK was reported to use up to 60 algorithms for fraud detection and other purposes. The registry describes profiling and machine learning (it names Naive Bayes classification and cluster analysis) run on linked register data. In a letter to Amnesty International before November 2024, UDK supplied its 2023 statistics for three data-driven controls. The “Really Single” model produced 412 requested cases, 292 established control cases and 135 cases with revenue (benefits stopped or reduced). “Model Abroad” (unreported departures, state and disability pension) gave 511, 351 and 36. The parental-leave controls including the “Fictitious Employment” model gave 491, 207 and 72. UDK cautioned that cases with revenue in a year are not necessarily a proportion of cases established that year. A UDK/ATP control official told Amnesty the team manages 5,000 to 6,000 cases a year, of which around 1,800 come from the models. Amnesty's report of 12 November 2024 concludes it is questionable whether the algorithms are effective. It finds most opened cases end with no further action and the system risks discrimination and mass surveillance. A Copenhagen Municipality control official said more often than not there is no fraud in the cases UDK sends. Background sources give earlier yields. AlgorithmWatch (2020) reports 2017 and 2018 controls unveiled about half a billion kroner in erroneous payments. The Automating Society 2020 Denmark chapter cites a July 2019 report. It counted 705 cases in 2017 and 1,094 in 2018 where payments were stopped, adjusted or repaid, out of 2.7 million screened beneficiaries. The dm.dk FOI report (October 2024) and ATP's page are not among the sources. The report said nearly all 1.2 million pensioners were screened and only 36 cases in 2023 ended with a benefit stopped or reduced. That matches the Model Abroad row. ATP's page credits 260 million kr. a year of savings to IT modernization generally. The 2023 figures carry no day." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Udbetaling Danmark / ATP Den Faelles Dataenhed fraud-control models (about 60 profiling and machine-learning models as of 2019, including 'Really Single', 'Model Abroad' and 'Fictitious Employment')" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ATP (Arbejdsmarkedets Tillaegspension) with NNIT A/S as supplier, for Udbetaling Danmark" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Udbetaling Danmark's fraud-control models may have produced 135, 36 and 72 cases with benefits stopped or reduced in 2023", "headline": "UDK fraud models may have yielded 135, 36 and 72 cases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f17dd05704428e7ad3e78e0e01f15067f7cee4c98a7dc6f09bc1eea7d43f4f91" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Udbetaling Danmark (UDK), the Danish public authority that has centralized welfare payments since 2012, has its benefits administered by ATP (Arbejdsmarkedets Tillaegspension). ATP designs the fraud-control components of UDK's Joint Data Unit (Den Faelles Dataenhed, established 2014 per the University of Copenhagen's Offentlig AI database). NNIT A/S is the supplier. As of 2019 UDK was reported to use up to 60 algorithms for fraud detection and other purposes. The registry describes profiling and machine learning (it names Naive Bayes classification and cluster analysis) run on linked register data. In a letter to Amnesty International before November 2024, UDK supplied its 2023 statistics for three data-driven controls. The “Really Single” model produced 412 requested cases, 292 established control cases and 135 cases with revenue (benefits stopped or reduced). “Model Abroad” (unreported departures, state and disability pension) gave 511, 351 and 36. The parental-leave controls including the “Fictitious Employment” model gave 491, 207 and 72. UDK cautioned that cases with revenue in a year are not necessarily a proportion of cases established that year. A UDK/ATP control official told Amnesty the team manages 5,000 to 6,000 cases a year, of which around 1,800 come from the models. Amnesty's report of 12 November 2024 concludes it is questionable whether the algorithms are effective. It finds most opened cases end with no further action and the system risks discrimination and mass surveillance. A Copenhagen Municipality control official said more often than not there is no fraud in the cases UDK sends. Background sources give earlier yields. AlgorithmWatch (2020) reports 2017 and 2018 controls unveiled about half a billion kroner in erroneous payments. The Automating Society 2020 Denmark chapter cites a July 2019 report. It counted 705 cases in 2017 and 1,094 in 2018 where payments were stopped, adjusted or repaid, out of 2.7 million screened beneficiaries. The dm.dk FOI report (October 2024) and ATP's page are not among the sources. The report said nearly all 1.2 million pensioners were screened and only 36 cases in 2023 ended with a benefit stopped or reduced. That matches the Model Abroad row. ATP's page credits 260 million kr. a year of savings to IT modernization generally. The 2023 figures carry no day.", "replication": { "produced_by": [ "Register linkage of benefits data with civil, housing, business, tax, income, health and employment registers under a 2015 legal authorization", "About 60 profiling and machine-learning models developed by NNIT to ATP's specifications", "A UDK/ATP control team (HOK) that manually screens model output into established control cases and investigates them", "A legal duty to also process all externally reported cases, which the control team says limits the share drawn from the models to about 30%" ], "must_hold": [ "Legal basis for register linkage and model use remains in force despite Amnesty's challenge and the dispute over classification under the EU AI Act", "Control-team capacity of about 5,000 to 6,000 cases a year", "Models continue to be monitored on their training cases, since UDK documents no evaluation metrics", "Political tolerance of the system after the November 2024 criticism" ], "echoes": [ { "setting": "2017 and 2018 controls over 2.7 million screened beneficiaries, as reported in a July 2019 report cited by Automating Society 2020: 705 and 1,094 cases with payments stopped, adjusted or repaid", "outcome": "recurred", "source": "https://automatingsociety.algorithmwatch.org/report2020/denmark/" }, { "setting": "dm.dk FOI report, October 2024, as read by an earlier check (not re-read): nearly all 1.2 million pensioners screened, 36 cases in 2023 ending with a benefit stopped or reduced", "outcome": "recurred", "source": "dm.dk FOI report, October 2024, as summarized in an earlier check of this case; consistent with the Model Abroad row of Amnesty's Table 5" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Models examine linked public registers and flag recipients for review. A UDK/ATP team that handles about 5,000 to 6,000 cases a year screens the results and investigates selected cases. Around 1,800 of its annual cases come from the models." } } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 35, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0270", "title": "ChatGPT assists a literature review of MRI features of intravascular lymphoma after biopsy diagnosis", "summary": "Chinese neurologists used ChatGPT to help review published MRI findings of cerebral intravascular large B-cell lymphoma for a 59-year-old's case report; the diagnosis came from biopsy, not the model.", "date_observed": "2024-11-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Chen et al. (Frontiers in Immunology, 14 November 2024) are at the Affiliated Yuebei People's Hospital, Shantou University Medical College, Shaoguan. They report a previously healthy 59-year-old woman who developed hemiparesis and altered mental status after SARS-CoV-2 reinfection. She was first treated for presumed infarction, then for suspected demyelination. Brain biopsy diagnosed intravascular large B-cell lymphoma. The authors say they reviewed the disease's brain magnetic resonance imaging (MRI) findings in the literature “with the assistance of ChatGPT”. They call their review the first to focus on MRI features of cerebral lesions. The model played no part in diagnosis or treatment. The authors declare no competing interests.", "category": "general benefit", "unexpected": false, "purpose": "Assist clinicians in reviewing published imaging literature for a case report", "system": "ChatGPT using GPT-4o", "model_version": "ChatGPT-4o", "developer": "OpenAI", "deployer": "Affiliated Yuebei People's Hospital of Shantou University Medical College", "location": "Shaoguan, Guangdong, China", "domain": "Health; neurology and medical publishing", "segment": "Clinician-authors", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The model did not contribute to diagnosis or treatment." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome." }, { "group": "societal", "depth": null, "reason": "No attributable event." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT assisted the authors' literature review for the published case. The patient's diagnosis and care did not involve the model. Source is a non-vendor peer-reviewed case report." }, "evidence": [ { "kind": "case report", "citation": "Chen S, Cai M, Tan G, Guo R, Liang Q, Li H, Liu X. Front Immunol 15:1478163 (2024)", "title": "Case report: Intravascular large B cell lymphoma mimicking acute demyelinating encephalomyelitis after SARS-CoV-2 reinfection: diagnostic value of advanced MRI techniques and the literature review with the assistance of ChatGPT", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "date": "2024-11-14", "written_by": "deployer", "quote": "We reviewed the brain MRI findings of IVLBCL in the literature with the assistance of ChatGPT." } ], "replication": { "produced_by": [ "Clinician-authors prompting ChatGPT during a literature review" ], "must_hold": [ "Authors verify model-suggested literature against sources" ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT helps review MRI literature on intravascular lymphoma", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The case report is a single retrospective literature review aid; no follow-up, correction or later use was found in the cited source, and the authors note the model could not summarize specific MRI features for accurate diagnosis.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://zh.wikipedia.org/wiki/%E7%B2%A4%E5%8C%97%E4%BA%BA%E6%B0%91%E5%8C%BB%E9%99%A2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Separated the reported AI model from its release and corrected the system identity against the retained evidence.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0270", "catalog_version": "1.0.0", "source_fingerprint": "df5e6ccaabceededaebfb8a67594e537bcc889b5840d59b9551355b0c90f3bd6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0270-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "Affiliated Yuebei People's Hospital of Shantou University Medical College" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ChatGPT assisted the authors' literature review for the published case. The patient's diagnosis and care did not involve the model. Source is a non-vendor peer-reviewed case report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "ChatGPT assisted the authors' literature review for the published case. The patient's diagnosis and care did not involve the model. Source is a non-vendor peer-reviewed case report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The model did not contribute to diagnosis or treatment." }, { "group": "organizational", "reason": "No organizational outcome." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The model did not contribute to diagnosis or treatment." }, { "group": "organizational", "reason": "No organizational outcome." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The case report is a single retrospective literature review aid; no follow-up, correction or later use was found in the cited source, and the authors note the model could not summarize specific MRI features for accurate diagnosis." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0270" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Chen et al. (Frontiers in Immunology, 14 November 2024) are at the Affiliated Yuebei People's Hospital, Shantou University Medical College, Shaoguan. They report a previously healthy 59-year-old woman who developed hemiparesis and altered mental status after SARS-CoV-2 reinfection. She was first treated for presumed infarction, then for suspected demyelination. Brain biopsy diagnosed intravascular large B-cell lymphoma. The authors say they reviewed the disease's brain magnetic resonance imaging (MRI) findings in the literature “with the assistance of ChatGPT”. They call their review the first to focus on MRI features of cerebral lesions. The model played no part in diagnosis or treatment. The authors declare no competing interests.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The model did not contribute to diagnosis or treatment." }, { "group": "organizational", "reason": "No organizational outcome." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Section 4 and the Acknowledgments expressly identify ChatGPT-4o for the literature review. Supplementary DOCX and XLSX files were identified but not inspected.", "record_fields": [], "source_refs": [ "AIBD-0270-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The full article was accessible. Its supplementary files have not been inspected." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Chen S, Cai M, Tan G, Guo R, Liang Q, Li H, Liu X. Front Immunol 15:1478163 (2024)", "title": "Case report: Intravascular large B cell lymphoma mimicking acute demyelinating encephalomyelitis after SARS-CoV-2 reinfection: diagnostic value of advanced MRI techniques and the literature review with the assistance of ChatGPT", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "date": "2024-11-14", "written_by": "deployer", "quote": "We reviewed the brain MRI findings of IVLBCL in the literature with the assistance of ChatGPT." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0270-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Chen S, Cai M, Tan G, Guo R, Liang Q, Li H, Liu X. Front Immunol 15:1478163 (2024)", "title": "Case report: Intravascular large B cell lymphoma mimicking acute demyelinating encephalomyelitis after SARS-CoV-2 reinfection: diagnostic value of advanced MRI techniques and the literature review with the assistance of ChatGPT", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "date": "2024-11-14", "written_by": "deployer", "quote": "We reviewed the brain MRI findings of IVLBCL in the literature with the assistance of ChatGPT." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0270-source-0001", "retained_source_order": [ "AIBD-0270-source-0001" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "source_refs": [ "AIBD-0270-source-0001" ], "display_name": "Frontiers in Immunology", "contribution": "The authors identify the use of GPT-4o for their review of MRI findings from 11 papers.", "locator": "Section 4, first paragraph; Acknowledgments.", "relationship": "Original account from the researchers who used the model. The clinical diagnosis and treatment preceded this literature review." } ], "claim_chains": [ { "claim": "AI system identity and role", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC11602322/", "Section 4 and Acknowledgments" ], "finding": "The authors name ChatGPT-4o and describe inputting literature-derived MRI information. This does not describe AI use in patient care." } ], "limitations": [ "The linked supplementary DOCX and XLSX files were not inspected." ] } }, "provenance": { "kind": "source_review", "basis": "Read the original full-text paper. Section 4 and the Acknowledgments expressly identify ChatGPT-4o for the literature review. 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They report a previously healthy 59-year-old woman who developed hemiparesis and altered mental status after SARS-CoV-2 reinfection. She was first treated for presumed infarction, then for suspected demyelination. Brain biopsy diagnosed intravascular large B-cell lymphoma. The authors say they reviewed the disease's brain magnetic resonance imaging (MRI) findings in the literature “with the assistance of ChatGPT”. They call their review the first to focus on MRI features of cerebral lesions. The model played no part in diagnosis or treatment. The authors declare no competing interests." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "GPT-4o summarized MRI findings from published papers for the authors’ literature review." }, "provenance": { "kind": "source_review", "basis": "Read the original full-text paper. Section 4 and the Acknowledgments expressly identify ChatGPT-4o for the literature review. 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Supplementary DOCX and XLSX files were identified but not inspected.", "record_fields": [], "source_refs": [ "AIBD-0270-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "GPT-4o." } }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "ChatGPT-4o" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "ChatGPT." }, "provenance": { "kind": "source_review", "basis": "Read the original full-text paper. Section 4 and the Acknowledgments expressly identify ChatGPT-4o for the literature review. Supplementary DOCX and XLSX files were identified but not inspected.", "record_fields": [], "source_refs": [ "AIBD-0270-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "ChatGPT." } }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT assists a literature review of MRI features of intravascular lymphoma after biopsy diagnosis", "headline": "ChatGPT helps review MRI literature on intravascular lymphoma" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "df5e6ccaabceededaebfb8a67594e537bcc889b5840d59b9551355b0c90f3bd6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Chen et al. (Frontiers in Immunology, 14 November 2024) are at the Affiliated Yuebei People's Hospital, Shantou University Medical College, Shaoguan. They report a previously healthy 59-year-old woman who developed hemiparesis and altered mental status after SARS-CoV-2 reinfection. She was first treated for presumed infarction, then for suspected demyelination. Brain biopsy diagnosed intravascular large B-cell lymphoma. The authors say they reviewed the disease's brain magnetic resonance imaging (MRI) findings in the literature “with the assistance of ChatGPT”. They call their review the first to focus on MRI features of cerebral lesions. The model played no part in diagnosis or treatment. The authors declare no competing interests.", "replication": { "produced_by": [ "Clinician-authors prompting ChatGPT during a literature review" ], "must_hold": [ "Authors verify model-suggested literature against sources" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 5, "record_mapped": 27, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0199", "title": "See & Spray targeted applications save 28.4–62.4% of postemergence herbicide with weed control of 93% or more in Arkansas and Mississippi trials", "summary": "Arkansas-Mississippi trials (2021–2022) with Blue River co-authors: targeted sprays matched broadcast weed control within 1% while saving 28.4% to 62.4% of postemergence herbicide.", "date_observed": "2024-11-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "University of Arkansas weed scientists and Blue River Technology agronomists ran four site-years of randomized complete block trials in 2021 and 2022. Sites were the Northeast Research and Extension Center in Keiser, Arkansas, and Stoneville R&D in Greenville, Mississippi. They compared John Deere See & Spray machine-vision targeted applications with traditional broadcast programs in glyphosate/glufosinate/dicamba-resistant soybean. They used a preemergence residual followed by early-postemergence dicamba and mid-postemergence glufosinate. Targeted applications gave control comparable to broadcast, with at most 1% less efficacy. Overall control was 93% or more for Palmer amaranth, broadleaf signalgrass, morningglory and purslane species. Soybean injury fell by at most 5 percentage points without a yield increase. On average they saved 28.4% to 62.4% of postemergence herbicide, with narrower nozzle angles spraying less area. The paper appeared online on 15 November 2024. It is a research trial, not a commercial farm deployment.", "category": "general benefit", "unexpected": false, "purpose": "Detect weeds with machine vision and apply herbicide only where weeds are present, reducing herbicide use while maintaining control.", "system": "John Deere See & Spray (machine-vision targeted sprayer)", "model_version": "See & Spray model year 2022 (level 3 detection sensitivity, small coverage buffer)", "developer": "Blue River Technology / John Deere", "deployer": "University of Arkansas and Stoneville R&D field trials (Keiser, AR and Greenville, MS)", "location": "Keiser (Arkansas) and Greenville (Mississippi), United States", "domain": "Agriculture / crop protection", "segment": "Soybean weed control", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "Herbicide saved is read as reduced waste; it is also a cost saving for the grower.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Savings of 28.4–62.4% on postemergence herbicide were measured in trial plots. No grower's costs or outcomes are documented." }, { "group": "societal", "depth": null, "reason": "Reduced herbicide volume is a trial result. No environmental outcome off-plot is measured." } ], "ai_role": { "status": "assessed", "statement": "The machine-vision sprayer decided where to spray. The comparison with broadcast programs is a randomized trial with consistent herbicides and rates. Savings depended on nozzle angle and machine settings. Co-authored by the maker's agronomists with university weed scientists." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Avent TH, Norsworthy JK, Patzoldt WL, Schwartz-Lazaro LM, Houston MM, Butts TR, Vazquez AR. Comparing herbicide application methods with See & Spray technology in soybean. Weed Technology 38:e74 (2024). doi:10.1017/wet.2024.70", "title": "Comparing herbicide application methods with See & Spray technology in soybean", "url": "https://doi.org/10.1017/wet.2024.70", "date": "2024-11-15", "written_by": "deployer", "quote": "On average, targeted sprays saved a range of 28.4% to 62.4% on postemergence herbicides." }, { "kind": "press release", "citation": "Deere & Co. John Deere Customers Use See & Spray Technology Across Five Million Acres in 2025. Company release as published by Global Ag Tech Initiative, 4 November 2025.", "title": "John Deere Customers Use See & Spray Technology Across Five Million Acres in 2025", "url": "https://www.globalagtechinitiative.com/in-field-technologies/robotics-automation/john-deere-customers-use-see-spray-technology-across-five-million-acres-in-2025/", "date": "2025-11-04", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Herbicide-resistant soybean with a PRE residual, EPOST dicamba and MPOST glufosinate", "Four site-years (2021–2022) in a randomized complete block design" ], "must_hold": [ "The specific machine settings and nozzle angles used", "Weed species and pressure comparable to the trial sites" ], "echoes": [] }, "paired_incident": null, "headline": "See & Spray saves 28.4–62.4% of postemergence herbicide", "metric": "on average saved 28.4% to 62.4% of postemergence herbicide", "comparator": { "against": "traditional broadcast herbicide applications in the same randomized trials", "before": "full broadcast applications of the postemergence herbicides (traditional broadcast program)", "after": "targeted sprays saving 28.4% to 62.4% of postemergence herbicides, with a ≤1% decrease in efficacy and overall control ≥93%", "basis": "measured", "quote": "On average, targeted sprays saved a range of 28.4% to 62.4% on postemergence herbicides. 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In 2025, John Deere customers reduced non-residual herbicide use by an average of nearly 50% — saving nearly 31 million gallons of herbicide mix—demonstrating the power of targeted application, even in a season marked by elevated weed pressure and frequent rains.", "url": "https://www.globalagtechinitiative.com/in-field-technologies/robotics-automation/john-deere-customers-use-see-spray-technology-across-five-million-acres-in-2025/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.cambridge.org/core/journals/weed-technology/article/comparing-herbicide-application-methods-with-see-spray-technology-in-soybean/05967C11D1BF0B174A13BE687B865AF2; https://www.globalagtechinitiative.com/in-field-technologies/robotics-automation/john-deere-customers-use-see-spray-technology-across-five-million-acres-in-2025/; https://www.cambridge.org/core/journals/weed-technology/article/comparing-herbicide-application-methods-with-see-spray-technology-in-soybean/05967C11D1BF0B174A13BE687B865AF2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://bluerivertechnology.com/; https://en.wikipedia.org/wiki/University_of_Arkansas", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' press release and the deployer's peer-reviewed study. 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Sites were the Northeast Research and Extension Center in Keiser, Arkansas, and Stoneville R&D in Greenville, Mississippi. They compared John Deere See & Spray machine-vision targeted applications with traditional broadcast programs in glyphosate/glufosinate/dicamba-resistant soybean. They used a preemergence residual followed by early-postemergence dicamba and mid-postemergence glufosinate. Targeted applications gave control comparable to broadcast, with at most 1% less efficacy. Overall control was 93% or more for Palmer amaranth, broadleaf signalgrass, morningglory and purslane species. Soybean injury fell by at most 5 percentage points without a yield increase. On average they saved 28.4% to 62.4% of postemergence herbicide, with narrower nozzle angles spraying less area. The paper appeared online on 15 November 2024. 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Sites were the Northeast Research and Extension Center in Keiser, Arkansas, and Stoneville R&D in Greenville, Mississippi. They compared John Deere See & Spray machine-vision targeted applications with traditional broadcast programs in glyphosate/glufosinate/dicamba-resistant soybean. They used a preemergence residual followed by early-postemergence dicamba and mid-postemergence glufosinate. Targeted applications gave control comparable to broadcast, with at most 1% less efficacy. Overall control was 93% or more for Palmer amaranth, broadleaf signalgrass, morningglory and purslane species. Soybean injury fell by at most 5 percentage points without a yield increase. On average they saved 28.4% to 62.4% of postemergence herbicide, with narrower nozzle angles spraying less area. The paper appeared online on 15 November 2024. 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Easier access to event information remains an intended benefit without a measured outcome.", "date_observed": "2024-11-19", "date_basis": "source publication", "date_precision": "day", "benefit_status": "intended", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-014", "account": "The Liverpool City Region Combined Authority announced that multilingual, interactive digital humans would assist visitors and host its November 21, 2024 AI Summit. Supplier Sum Vivas named the assistants Ava, Alison, and James. The accounts provide no measurements of changes in access to event information, language barriers, or organizers' workload. The assistants' contribution to attendance and investment interest is unknown.", "category": "general benefit", "unexpected": false, "purpose": "Help summit attendees access information through multilingual AI interaction and support event hosting.", "system": "Sum Vivas AI-integrated digital humans Ava, Alison, and James", "model_version": null, "developer": "Sum Vivas", "deployer": "Liverpool City Region Combined Authority and Sum Vivas", "location": "Liverpool, United Kingdom", "domain": "Visitor information and event services", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Attendees are intended to receive multilingual AI assistance. Improvements in access to event information and visitor experience are unmeasured." }, { "group": "organizational", "depth": null, "reason": "Organizers are intended to receive support with visitor assistance and hosting. No operational saving or service improvement attributable to the digital humans is measured." } ], "ai_role": { "status": "unassessed", "statement": "Multilingual, interactive AI digital humans were planned to assist visitors and host the summit. Their effect on visitor experience and event operations remains unevaluated." }, "evidence": [ { "kind": "report", "citation": "Liverpool City Region Combined Authority, November 19, 2024. Organizer announcement for the November 21 summit.", "title": "From medicine to education, industry and science: digital humans to introduce inspiring vision of future at international AI Summit", "url": "https://www.liverpoolcityregion-ca.gov.uk/news/from-medicine-to-education-industry-and-science-digital-humans-to-introduce-inspiring-vision-of-future-at-international-ai-summit", "date": "2024-11-19", "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Sum Vivas, announcement of its participation in the November 21, 2024 summit. Publication date unspecified.", "title": "Sum Vivas announces digital humans for the Liverpool City Region AI Summit", "url": "https://www.linkedin.com/posts/sum-vivas-ltd_we-are-delighted-to-announce-that-rob-sims-activity-7264628977435127811-zf2f", "date": null, "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Local Government Association, March 25, 2025. Council account of the summit and its associated applications.", "title": "Liverpool City Region Combined Authority – AI Summit", "url": "https://www.local.gov.uk/case-studies/liverpool-city-region-combined-authority-ai-summit", "date": "2025-03-25", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The planned service uses multilingual, interactive AI digital humans to assist attendees and host proceedings." ], "must_hold": [ "Likely requirements include accurate event information, usable interaction, and suitable language support. These have not been validated as sufficient for a beneficial outcome." ], "echoes": [] }, "paired_incident": null, "headline": "Liverpool plans multilingual AI concierges for summit attendees", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.liverpoolcityregion-ca.gov.uk/news/from-medicine-to-education-industry-and-science-digital-humans-to-introduce-inspiring-vision-of-future-at-international-ai-summit", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' report and two reports from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0574", "catalog_version": "1.0.0", "source_fingerprint": "ae11a96656df1e0654b7a642859a3d602af3dd25cdd8d0417bd1b3fddc58eec5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0574-source-0001", "AIBD-0574-source-0002", "AIBD-0574-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Sum Vivas", "deployer": "Liverpool City Region Combined Authority and Sum Vivas" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Multilingual, interactive AI digital humans were planned to assist visitors and host the summit. 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Supplier Sum Vivas named the assistants Ava, Alison, and James. The accounts provide no measurements of changes in access to event information, language barriers, or organizers' workload. The assistants' contribution to attendance and investment interest is unknown.", "replication": { "produced_by": [ "The planned service uses multilingual, interactive AI digital humans to assist attendees and host proceedings." ], "must_hold": [ "Likely requirements include accurate event information, usable interaction, and suitable language support. These have not been validated as sufficient for a beneficial outcome." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0055", "title": "Machine-learning myoelectric motor execution partially restores thumb and wrist movement in a paralyzed replanted arm", "summary": "A 72-year-old with a paralyzed replanted arm regained active thumb and wrist movement after 18 sessions of ML-decoded motor execution.", "date_observed": "2024-11-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 72-year-old man's right arm was replanted after a traumatic above-elbow amputation. He had no functional recovery after conventional rehabilitation and developed chronic neuropathic pain. The arm had been replanted at Sahlgrenska University Hospital in Mölndal, Sweden. The Mölndal-based Center for Bionics and Pain Research / Sahlgrenska University Hospital (C.A.R.E.) team then delivered 18 sessions of myoelectric motor execution over 84 days. Nine included sensory training with tactile grids (the paper does not name the treatment site). Eight channels of electromyography were classified by a linear discriminant analysis classifier (Neuromotus, Integrum AB). Intended movements were decoded from the replanted arm and shown on screen as virtual limbs and games. He regained active thumb extension (4 degrees) and active wrist flexion (6 degrees) and extension (10 degrees), movements absent before treatment. Pain fluctuated with no consistent change. Treatment dates are not given, so the publication date (23 November 2024) is used.", "category": "benefit created", "unexpected": false, "purpose": "Rehabilitate a highly impaired replanted arm and reduce neuropathic pain using decoded motor intention as feedback", "system": "Myoelectric motor execution with sensory training: Neuromotus 8-channel EMG and LDA classifier driving virtual limbs and serious games", "model_version": "Neuromotus (Integrum AB) with linear discriminant analysis classifier", "developer": "Center for Bionics and Pain Research / University of Gothenburg (academic clinical team); device by Integrum AB", "deployer": "Center for Bionics and Pain Research and Sahlgrenska University Hospital (C.A.R.E.), Mölndal; treatment site not named in the paper", "location": "Mölndal, Sweden", "domain": "Rehabilitation medicine / hand surgery", "segment": "Patients with replanted or transplanted limbs", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "An identifiable patient regained active thumb and wrist movement conventional rehabilitation had not produced. Gains are small and pain did not consistently improve." }, { "group": "societal", "depth": 1, "reason": "Single case; authors present it as a potential treatment needing further study." } ], "ai_role": { "status": "assessed", "statement": "The LDA classifier decodes intended movements from weak EMG in a hand and wrist with no active motion. That is the only way the patient could receive real-time feedback on his motor attempts. The authors attribute the regained movement to this motor execution training. Two authors hold a pending patent on the technology." }, "evidence": [ { "kind": "case report", "citation": "Kristoffersen MB, Munoz-Novoa M, Buist M, Emadeldin M, Reinholdt C, Ortiz-Catalan M (2024). Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study. Journal of NeuroEngineering and Rehabilitation 21:204.", "title": "Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/", "date": "2024-11-23", "written_by": "makers", "quote": "The participant regained active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees)" }, { "kind": "case report", "citation": "Kristoffersen MB, et al. (2024). J NeuroEng Rehabil 21:204 (methods).", "title": "Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/", "date": "2024-11-23", "written_by": "makers", "quote": "intended movements were decoded from the replanted arm's myoelectric signals using machine learning and real-time feedback was provided on a screen" }, { "kind": "peer-reviewed study", "citation": "Munoz-Novoa M, Kristoffersen MB, Sunnerhagen KS, Naber A, Ortiz-Catalan M, Alt Murphy M (2025). Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study. Journal of NeuroEngineering and Rehabilitation 22:6.", "title": "Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11742229/", "date": "2025-01-17", "written_by": "makers", "quote": "All participants improved upper limb function assessed by FMA-UE (Tau-U 0.72-1.0), and five out of six improved beyond the minimal clinical important difference (MCID)." } ], "replication": { "produced_by": [ "Residual EMG detectable in the impaired limb", "Classifier trained on the patient's own signals each session", "Repeated sessions with virtual-limb and game feedback" ], "must_hold": [ "Intact or reinnervated muscle producing separable EMG patterns", "Clinician-run sessions several times a week", "Patient motivation to attempt movements without visible motion" ], "echoes": [ { "date": "2025-01-17", "setting": "Six people with chronic stroke, 18 sessions of myoelectric pattern recognition with VR and gaming (single-case experimental design)", "model_version": "Neuromotus MPR with VR", "outcome": "recurred", "source": "Munoz-Novoa et al. (2025) J NeuroEng Rehabil, PMID 39825410" } ] }, "paired_incident": null, "headline": "Neuromotus EMG decoding restores thumb and wrist movement", "metric": "active thumb extension (4 degrees) and active wrist flexion (6 degrees)", "comparator": { "against": "the arm's function before treatment, after conventional rehabilitation", "before": "no active movement prior the MME interventions", "after": "active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees)", "basis": "measured", "quote": "regained active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees), both of which had no active movement prior the MME interventions", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/" }, "later": { "status": "unknown", "date": null, "note": "No follow-up beyond the final session is reported.", "quote": null, "url": null }, "value": null, "developer_country": "Sweden", "deployer_country": "Sweden", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the account and deployer so that Sahlgrenska University Hospital is credited only with the replantation surgery because the paper never says where the MME sessions were delivered; corrected the article numbers to 21:204 and 22:6; qualified the title and the system's part to “partially restores” and “a hand and wrist with no active motion” to match the paper's own limits; and restored the full source title on evidence 2.", "source": "Kristoffersen et al. (2024) J NeuroEng Rehabil 21:204, PMC11585237; Munoz-Novoa et al. 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(2025) J NeuroEng Rehabil 22:6, PMID 39825410", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=AFF:%22Center%20for%20Bionics%20and%20Pain%20Research%22&resultType=core&format=json&pageSize=5; https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=AFF:%22Center%20for%20Bionics%20and%20Pain%20Research%22&resultType=core&format=json&pageSize=5", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Rehabilitation medicine / hand surgery", "segment": "Patients with replanted or transplanted limbs" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Kristoffersen MB, Munoz-Novoa M, Buist M, Emadeldin M, Reinholdt C, Ortiz-Catalan M (2024). Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study. Journal of NeuroEngineering and Rehabilitation 21:204.", "title": "Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/", "date": "2024-11-23", "written_by": "makers", "quote": "The participant regained active extension of the thumb (4 degrees) and regained active wrist movement (flex: 6 degrees, extend: 10 degrees)" }, { "kind": "case report", "citation": "Kristoffersen MB, et al. (2024). J NeuroEng Rehabil 21:204 (methods).", "title": "Myoelectric motor execution and sensory training to treat chronic pain and paralysis in a replanted arm: a case study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11585237/", "date": "2024-11-23", "written_by": "makers", "quote": "intended movements were decoded from the replanted arm's myoelectric signals using machine learning and real-time feedback was provided on a screen" }, { "kind": "peer-reviewed study", "citation": "Munoz-Novoa M, Kristoffersen MB, Sunnerhagen KS, Naber A, Ortiz-Catalan M, Alt Murphy M (2025). Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study. Journal of NeuroEngineering and Rehabilitation 22:6.", "title": "Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11742229/", "date": "2025-01-17", "written_by": "makers", "quote": "All participants improved upper limb function assessed by FMA-UE (Tau-U 0.72-1.0), and five out of six improved beyond the minimal clinical important difference (MCID)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0055-source-0001", "AIBD-0055-source-0002", "AIBD-0055-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Kristoffersen MB, Munoz-Novoa M, Buist M, Emadeldin M, Reinholdt C, Ortiz-Catalan M (2024). 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Journal of NeuroEngineering and Rehabilitation 22:6.", "title": "Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11742229/", "date": "2025-01-17", "written_by": "makers", "quote": "All participants improved upper limb function assessed by FMA-UE (Tau-U 0.72-1.0), and five out of six improved beyond the minimal clinical important difference (MCID)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 72-year-old with a paralyzed replanted arm regained active thumb and wrist movement after 18 sessions of ML-decoded motor execution.", "account": "A 72-year-old man's right arm was replanted after a traumatic above-elbow amputation. He had no functional recovery after conventional rehabilitation and developed chronic neuropathic pain. The arm had been replanted at Sahlgrenska University Hospital in Mölndal, Sweden. The Mölndal-based Center for Bionics and Pain Research / Sahlgrenska University Hospital (C.A.R.E.) team then delivered 18 sessions of myoelectric motor execution over 84 days. Nine included sensory training with tactile grids (the paper does not name the treatment site). Eight channels of electromyography were classified by a linear discriminant analysis classifier (Neuromotus, Integrum AB). Intended movements were decoded from the replanted arm and shown on screen as virtual limbs and games. He regained active thumb extension (4 degrees) and active wrist flexion (6 degrees) and extension (10 degrees), movements absent before treatment. Pain fluctuated with no consistent change. Treatment dates are not given, so the publication date (23 November 2024) is used." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The classifier decoded intended movements from muscle signals and controlled a virtual limb." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A classifier based on linear discriminant analysis." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. 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He had no functional recovery after conventional rehabilitation and developed chronic neuropathic pain. The arm had been replanted at Sahlgrenska University Hospital in Mölndal, Sweden. The Mölndal-based Center for Bionics and Pain Research / Sahlgrenska University Hospital (C.A.R.E.) team then delivered 18 sessions of myoelectric motor execution over 84 days. Nine included sensory training with tactile grids (the paper does not name the treatment site). Eight channels of electromyography were classified by a linear discriminant analysis classifier (Neuromotus, Integrum AB). Intended movements were decoded from the replanted arm and shown on screen as virtual limbs and games. He regained active thumb extension (4 degrees) and active wrist flexion (6 degrees) and extension (10 degrees), movements absent before treatment. Pain fluctuated with no consistent change. Treatment dates are not given, so the publication date (23 November 2024) is used.", "replication": { "produced_by": [ "Residual EMG detectable in the impaired limb", "Classifier trained on the patient's own signals each session", "Repeated sessions with virtual-limb and game feedback" ], "must_hold": [ "Intact or reinnervated muscle producing separable EMG patterns", "Clinician-run sessions several times a week", "Patient motivation to attempt movements without visible motion" ], "echoes": [ { "date": "2025-01-17", "setting": "Six people with chronic stroke, 18 sessions of myoelectric pattern recognition with VR and gaming (single-case experimental design)", "model_version": "Neuromotus MPR with VR", "outcome": "recurred", "source": "Munoz-Novoa et al. (2025) J NeuroEng Rehabil, PMID 39825410" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0558", "title": "Peterborough City Council: Hey Geraldine, a personalised AI assistant", "summary": "Peterborough reports 15 minutes saved per conversation with Hey Geraldine. A manager describes obtaining equipment information while a colleague was away.", "date_observed": "2024-12-18", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-022", "account": "Peterborough deployed Hey Geraldine, a social-care knowledge assistant modeled on an experienced occupational-therapy colleague. The council reports 15 minutes saved per conversation. A deputy therapy manager describes obtaining needed equipment information while the real Geraldine was on leave. The reported 1,200 questions include testing and demonstrations.", "category": "general benefit", "unexpected": false, "purpose": "Provide social-care staff with accessible guidance and reduce routine demands on specialist colleagues.", "system": "Hey Geraldine bespoke AI social-care knowledge assistant", "model_version": null, "developer": "Peterborough City Council, Outcomes Matter Consulting, and Datnexa", "deployer": "Peterborough City Council", "location": "United Kingdom", "domain": "Adult-social-care knowledge support", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council reports less staff time answering routine questions." }, { "group": "personal", "depth": 1, "reason": "A specific manager obtained needed information during a colleague’s leave. This is a convenient information-access benefit, without a documented care outcome." } ], "ai_role": { "status": "assessed", "statement": "The assistant supplies guidance and information associated with an experienced colleague’s expertise. The source gives a specific successful information-retrieval account and an aggregate time-saving claim, without establishing downstream care improvements." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. 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}, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-022" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0558" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Peterborough deployed Hey Geraldine, a social-care knowledge assistant modeled on an experienced occupational-therapy colleague. The council reports 15 minutes saved per conversation. A deputy therapy manager describes obtaining needed equipment information while the real Geraldine was on leave. The reported 1,200 questions include testing and demonstrations.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council reports less staff time answering routine questions." }, { "group": "personal", "depth": 1, "reason": "A specific manager obtained needed information during a colleague’s leave. This is a convenient information-access benefit, without a documented care outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Provide social-care staff with accessible guidance and reduce routine demands on specialist colleagues." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Provide social-care staff with accessible guidance and reduce routine demands on specialist colleagues." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2024-12-18", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/peterborough-city-council-hey-geraldine-personalised-ai-assistant", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The council and partners developed the assistant in six weeks and gathered staff feedback.", "The source describes genuine staff questions alongside testing and demonstration interactions." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/peterborough-city-council-hey-geraldine-personalised-ai-assistant", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Adult-social-care knowledge support" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. 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A manager describes obtaining equipment information while a colleague was away.", "account": "Peterborough deployed Hey Geraldine, a social-care knowledge assistant modeled on an experienced occupational-therapy colleague. The council reports 15 minutes saved per conversation. A deputy therapy manager describes obtaining needed equipment information while the real Geraldine was on leave. The reported 1,200 questions include testing and demonstrations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Hey Geraldine bespoke AI social-care knowledge assistant" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Peterborough City Council, Outcomes Matter Consulting, and Datnexa" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Peterborough City Council: Hey Geraldine, a personalised AI assistant", "headline": "Peterborough reports quicker advice through Hey Geraldine" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fcd38da990126309b05353bfe1fe482fdfd35269341c57275871b9c0e02c8fbe" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Peterborough deployed Hey Geraldine, a social-care knowledge assistant modeled on an experienced occupational-therapy colleague. The council reports 15 minutes saved per conversation. A deputy therapy manager describes obtaining needed equipment information while the real Geraldine was on leave. The reported 1,200 questions include testing and demonstrations.", "replication": { "produced_by": [ "The council and partners developed the assistant in six weeks and gathered staff feedback.", "The source describes genuine staff questions alongside testing and demonstration interactions." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0087", "title": "CGU ALICE alert leads to a cut of about R$100 million in the reference value of a federal road-works tender (30 December 2024)", "summary": "A CGU ALICE alert on a federal road-works tender led managers to cut its reference value by about R$100 million, per CGU's 30 December 2024 results release", "date_observed": "2024-12-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In its 30 December 2024 statement on the year's results, the Controladoria-Geral da União (CGU) reported on an alert from its ALICE robot. The alert led CGU auditors to examine the budget of a federal road-works engineering tender. Federal managers then adjusted it, reducing the reference value by about R$100 million (CGU audit report 1632530). The statement names neither the contracting agency nor the date of the case. Its “this year” wording applies only to a separate water-bottle example. The same release gives 2024 aggregates: 118,069 procurement processes analyzed and 206 preventive audits opened on purchases worth R$25.57 billion. It reports R$257.25 million saved in concluded audits. ALICE reads planning documents and notices on Compras.gov.br with artificial-intelligence techniques and issues risk alerts that auditors confirm.", "category": "protective response", "unexpected": false, "purpose": "Continuous automated audit of federal procurement to flag budget and pricing risks before contracting", "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU text-mining and AI alert tool", "model_version": null, "developer": "Controladoria-Geral da União (CGU), in-house", "deployer": "Controladoria-Geral da União (CGU)", "location": null, "domain": "Public administration: government audit and procurement control", "segment": "Federal infrastructure procurement", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No identifiable individual beneficiary." }, { "group": "organizational", "depth": 2, "reason": "Material to the federal budget: about R$100 million removed from a single tender's reference value, per the CGU." }, { "group": "societal", "depth": 1, "reason": "Small at national scale and the contracting agency is not named, limiting traceability." } ], "ai_role": { "status": "assessed", "statement": "The CGU states the chain explicitly: “A partir do alerta do ALICE, auditores da CGU examinaram a adequação de um orçamento de uma obra rodoviária, o que gerou ajustes efetuados pelos gestores federais.” The adjustment was made by managers after a human audit. ALICE's role was the initial alert. Developer and deployer are the same public body. The page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." }, "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE. gov.br/cgu, 30 Dec 2024.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers", "quote": "A partir do alerta do ALICE, auditores da CGU examinaram a adequação de um orçamento de uma obra rodoviária, o que gerou ajustes efetuados pelos gestores federais" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Same release, preceding sentence.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE (road-works example)", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers", "quote": "a redução de cerca de R$ 100 milhões no valor de referência em um edital para contratação de serviços de engenharia" }, { "kind": "news report", "citation": "Grossmann, L. O. (2025). Robô da CGU rastreia R$ 25 bilhões em licitações. Convergência Digital, 15 Jan 2025. Secondary report restating the CGU release of 30 Dec 2024; names no sources of its own.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "houve redução de aproximadamente R$ 100 milhões" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "ALICE alert on a road-works budget", "CGU auditors' examination of the budget's adequacy", "Federal managers adjusting the reference value before contracting" ], "must_hold": [ "Budget spreadsheets published with the notice", "Audit review before the tender closes", "Managers' willingness to revise estimates" ], "echoes": [ { "date": "2025-01-14", "setting": "Three Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender cut by R$2,381,663.00 after CGU audit supported by ALICE (reported 4 October 2023)", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "738", "title": "Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud", "url": "https://incidentdatabase.ai/cite/738", "severity": null, "group": "organizational", "basis": "DWP's risk-flagging algorithm, the same alert-then-investigate design as ALICE, flagged mostly legitimate claims, wasting public funds instead of saving them." }, "headline": "CGU's ALICE alert leads to a R$100 million cut in a road-works tender", "metric": "reduced the reference value by about R$100 million", "comparator": { "against": "the tender's original reference value for the engineering services (figure not stated)", "before": "the original reference value, not stated", "after": "redução de cerca de R$ 100 milhões no valor de referência", "basis": "measured", "quote": "Outro exemplo relevante dos benefícios decorrentes do uso da ferramenta foi a redução de cerca de R$ 100 milhões no valor de referência em um edital para contratação de serviços de engenharia.", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, "later": { "status": "persisted", "date": "2025-01-14", "note": "Two weeks later the CGU reported the first 2025 audit reports built on ALICE alerts: three Rio de Janeiro federal hospital tenders, one suspended, one revoked and one re-estimated.", "quote": "Nos primeiros relatórios de auditoria publicados neste ano, a ferramenta criada pela Controladoria-Geral da União gerou alertas e as equipes de auditoria avaliaram três licitações de Hospitais Federais no estado do Rio de Janeiro apontando risco de sobrepreço na compra de equipamentos e insumos para estas instituições.", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, "value": { "amount": "cerca de R$ 100 milhões", "what": "reduction in the reference value of a federal road-works engineering tender after the ALICE alert", "who": "the federal government (contracting agency not named)", "estimate": false, "quote": "Outro exemplo relevante dos benefícios decorrentes do uso da ferramenta foi a redução de cerca de R$ 100 milhões no valor de referência em um edital para contratação de serviços de engenharia.", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 738 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/738", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Dropped the 2024 dating of the road-works case from the title, summary and account and set the date observed to the 30 December 2024 release date because neither source dates the case, refiled the category as a protective response because the CGU frames the alert as avoiding unnecessary spending and the sources do not show the overestimate would have been paid, and marked the Convergência Digital article as a secondary report of the CGU release.", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao; https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/; https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and two press releases from the makers. 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Secondary report restating the CGU release of 30 Dec 2024; names no sources of its own.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "houve redução de aproximadamente R$ 100 milhões" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0087-source-0001", "AIBD-0087-source-0002", "AIBD-0087-source-0003", "AIBD-0087-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE. gov.br/cgu, 30 Dec 2024.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers", "quote": "A partir do alerta do ALICE, auditores da CGU examinaram a adequação de um orçamento de uma obra rodoviária, o que gerou ajustes efetuados pelos gestores federais" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2024). Same release, preceding sentence.", "title": "Órgãos federais economizaram, em 2024, 257 milhões de reais com apoio do Robô ALICE (road-works example)", "url": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao", "date": "2024-12-30", "written_by": "makers", "quote": "a redução de cerca de R$ 100 milhões no valor de referência em um edital para contratação de serviços de engenharia" }, { "kind": "news report", "citation": "Grossmann, L. O. (2025). Robô da CGU rastreia R$ 25 bilhões em licitações. Convergência Digital, 15 Jan 2025. Secondary report restating the CGU release of 30 Dec 2024; names no sources of its own.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "houve redução de aproximadamente R$ 100 milhões" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A CGU ALICE alert on a federal road-works tender led managers to cut its reference value by about R$100 million, per CGU's 30 December 2024 results release", "account": "In its 30 December 2024 statement on the year's results, the Controladoria-Geral da União (CGU) reported on an alert from its ALICE robot. The alert led CGU auditors to examine the budget of a federal road-works engineering tender. Federal managers then adjusted it, reducing the reference value by about R$100 million (CGU audit report 1632530). The statement names neither the contracting agency nor the date of the case. Its “this year” wording applies only to a separate water-bottle example. The same release gives 2024 aggregates: 118,069 procurement processes analyzed and 206 preventive audits opened on purchases worth R$25.57 billion. It reports R$257.25 million saved in concluded audits. ALICE reads planning documents and notices on Compras.gov.br with artificial-intelligence techniques and issues risk alerts that auditors confirm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU text-mining and AI alert tool" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Controladoria-Geral da União (CGU), in-house" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CGU ALICE alert leads to a cut of about R$100 million in the reference value of a federal road-works tender (30 December 2024)", "headline": "CGU's ALICE alert leads to a R$100 million cut in a road-works tender" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "bc9414218e46c8eba70cdf284c84c6816f8ffad4af63f151028c401ac34069f1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In its 30 December 2024 statement on the year's results, the Controladoria-Geral da União (CGU) reported on an alert from its ALICE robot. The alert led CGU auditors to examine the budget of a federal road-works engineering tender. Federal managers then adjusted it, reducing the reference value by about R$100 million (CGU audit report 1632530). The statement names neither the contracting agency nor the date of the case. Its “this year” wording applies only to a separate water-bottle example. The same release gives 2024 aggregates: 118,069 procurement processes analyzed and 206 preventive audits opened on purchases worth R$25.57 billion. It reports R$257.25 million saved in concluded audits. ALICE reads planning documents and notices on Compras.gov.br with artificial-intelligence techniques and issues risk alerts that auditors confirm.", "replication": { "produced_by": [ "ALICE alert on a road-works budget", "CGU auditors' examination of the budget's adequacy", "Federal managers adjusting the reference value before contracting" ], "must_hold": [ "Budget spreadsheets published with the notice", "Audit review before the tender closes", "Managers' willingness to revise estimates" ], "echoes": [ { "date": "2025-01-14", "setting": "Three Rio federal hospital tenders suspended, revoked or re-estimated after ALICE alerts (CGU, 14 January 2025)", "outcome": "recurred", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender cut by R$2,381,663.00 after CGU audit supported by ALICE (reported 4 October 2023)", "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0279", "title": "FamilySearch Full-Text Search and Transkribus make handwritten records searchable with AI; no specific discovery documented", "summary": "FamilySearch introduced AI handwriting-recognition full-text search via FamilySearch Labs in 2024; Transkribus (READ-COOP) reports 200+ million pages deciphered. Makers' accounts only; no finding.", "date_observed": "2025-01-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Church of Jesus Christ of Latter-day Saints newsroom (2 January 2025) reviewed FamilySearch's 2024. It says FamilySearch “can convert an image of text into a machine-readable text format, allowing users to search the full text of the records”. That uses handwriting recognition and OCR. Full-Text Search was introduced through FamilySearch Labs in 2024, and 2.5 billion searchable records and images were added overall. It gives no example of a user discovery. Transkribus, developed by the European cooperative READ-COOP SCE, says on its site it “turns centuries of handwriting into text you can search, study, and share”. It claims over 500,000 users and 200 million pages deciphered. It cites projects such as the University of Georgia transcribing 20,000 pages in two months and Archion's portal of over 200,000 German church books. No independent source documenting a specific discovery, reunion or entitlement from either system was found. FamilySearch's help article on full-text search refused access here. The feature launched in 2024.", "category": "general benefit", "unexpected": false, "purpose": "Make handwritten historical records searchable by converting images to text with AI handwriting recognition", "system": "FamilySearch Full-Text Search (handwriting recognition and OCR); Transkribus (READ-COOP SCE)", "model_version": null, "developer": "FamilySearch International; READ-COOP SCE", "deployer": "FamilySearch Labs; archives and research projects using Transkribus (University of Georgia, Archion)", "location": "Global (FamilySearch users; European and US archives)", "domain": "Genealogy; archives", "segment": "Family historians and archival researchers", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No documented individual discovery or reunion." }, { "group": "organizational", "depth": null, "reason": "Project volumes are reported only by the vendors." }, { "group": "societal", "depth": null, "reason": "No attributable event." } ], "ai_role": { "status": "assessed", "statement": "Handwriting-recognition models produce the searchable text in both systems. The only cited sources are the makers' own (the Church newsroom for FamilySearch, the Transkribus site). They give capability and volume claims but no specific verified finding." }, "evidence": [ { "kind": "press release", "citation": "Newsroom of The Church of Jesus Christ of Latter-day Saints, 2 Jan 2025", "title": "FamilySearch 2024 Genealogy Highlights", "url": "https://newsroom.churchofjesuschrist.org/article/familysearch-2024-genealogy-highlights", "date": "2025-01-02", "written_by": "makers", "quote": "FamilySearch can convert an image of text into a machine-readable text format, allowing users to search the full text of the records." }, { "kind": "press release", "citation": "Transkribus website", "title": "Transkribus", "url": "https://www.transkribus.org/", "date": null, "written_by": "makers", "quote": "turns centuries of handwriting into text you can search, study, and share." }, { "kind": "press release", "citation": "Transkribus website, project examples", "title": "Transkribus", "url": "https://www.transkribus.org/", "date": null, "written_by": "makers", "quote": "transcribed 20,000 pages in two months" }, { "kind": "other", "citation": "Seaver R (13 Jan 2026). What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries. Genea-Musings (reproducing FamilySearch's announcement).", "title": "What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries", "url": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "date": "2026-01-13", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Handwriting-recognition models applied to digitized record images", "Indexing of recognized text for search" ], "must_hold": [ "Recognition accuracy adequate for names and places", "Independent documentation of specific findings (absent)" ], "echoes": [ { "date": null, "setting": "University of Georgia enslavement-records project using Transkribus (vendor-reported)", "model_version": null, "outcome": "unknown", "source": "https://www.transkribus.org/" } ] }, "paired_incident": null, "headline": "FamilySearch and Transkribus make handwritten records searchable", "metric": "200 million pages deciphered", "comparator": null, "later": { "status": "scaled", "date": "2026-01-13", "note": "FamilySearch's year-end review for 2025 (reproduced 9 January 2026) says Full-Text Search was fully released from FamilySearch Labs in 2025 alongside 2.2 billion newly searchable names and images, and its 2026 plans (reported 13 January 2026) are to extend the handwriting-reading technology to additional languages.", "quote": "FamilySearch will expand its Full-Text Search technology in 2026 to read old handwriting in additional languages, making newly digitized documents easily searchable by an ancestor's name.", "url": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/FamilySearch; https://en.wikipedia.org/wiki/FamilySearch", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: one other independent source and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0279", "catalog_version": "1.0.0", "source_fingerprint": "e70822d2b28676feb5c832da2482e01002bc36e5efe86d10f3b367215a7f897a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0279-source-0001", "AIBD-0279-source-0002", "AIBD-0279-source-0003", "AIBD-0279-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "FamilySearch International; READ-COOP SCE", "deployer": "FamilySearch Labs; archives and research projects using Transkribus (University of Georgia, Archion)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Handwriting-recognition models produce the searchable text in both systems. The only cited sources are the makers' own (the Church newsroom for FamilySearch, the Transkribus site). They give capability and volume claims but no specific verified finding." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Handwriting-recognition models produce the searchable text in both systems. The only cited sources are the makers' own (the Church newsroom for FamilySearch, the Transkribus site). They give capability and volume claims but no specific verified finding." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: one other independent source and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No documented individual discovery or reunion." }, { "group": "organizational", "reason": "Project volumes are reported only by the vendors." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No documented individual discovery or reunion." }, { "group": "organizational", "reason": "Project volumes are reported only by the vendors." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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"external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-01-13", "note": "FamilySearch's year-end review for 2025 (reproduced 9 January 2026) says Full-Text Search was fully released from FamilySearch Labs in 2025 alongside 2.2 billion newly searchable names and images, and its 2026 plans (reported 13 January 2026) are to extend the handwriting-reading technology to additional languages.", "quote": "FamilySearch will expand its Full-Text Search technology in 2026 to read old handwriting in additional languages, making newly digitized documents easily searchable by an ancestor's name.", "url": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0279" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Church of Jesus Christ of Latter-day Saints newsroom (2 January 2025) reviewed FamilySearch's 2024. It says FamilySearch “can convert an image of text into a machine-readable text format, allowing users to search the full text of the records”. That uses handwriting recognition and OCR. Full-Text Search was introduced through FamilySearch Labs in 2024, and 2.5 billion searchable records and images were added overall. It gives no example of a user discovery. Transkribus, developed by the European cooperative READ-COOP SCE, says on its site it “turns centuries of handwriting into text you can search, study, and share”. It claims over 500,000 users and 200 million pages deciphered. It cites projects such as the University of Georgia transcribing 20,000 pages in two months and Archion's portal of over 200,000 German church books. No independent source documenting a specific discovery, reunion or entitlement from either system was found. FamilySearch's help article on full-text search refused access here. The feature launched in 2024.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No documented individual discovery or reunion." }, { "group": "organizational", "reason": "Project volumes are reported only by the vendors." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Make handwritten historical records searchable by converting images to text with AI handwriting recognition" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Global (FamilySearch users; European and US archives)", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Make handwritten historical records searchable by converting images to text with AI handwriting recognition" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-01-02", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/FamilySearch; https://en.wikipedia.org/wiki/FamilySearch", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Handwriting-recognition models applied to digitized record images", "Indexing of recognized text for search" ], "must_hold": [ "Recognition accuracy adequate for names and places", "Independent documentation of specific findings (absent)" ], "echoes": [ { "setting": "University of Georgia enslavement-records project using Transkribus (vendor-reported)", "outcome": "unknown", "source": "https://www.transkribus.org/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Handwriting-recognition models applied to digitized record images", "Indexing of recognized text for search" ], "must_hold": [ "Recognition accuracy adequate for names and places", "Independent documentation of specific findings (absent)" ], "echoes": [ { "setting": "University of Georgia enslavement-records project using Transkribus (vendor-reported)", "outcome": "unknown", "source": "https://www.transkribus.org/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/FamilySearch; https://en.wikipedia.org/wiki/FamilySearch", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Genealogy; archives", "segment": "Family historians and archival researchers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Newsroom of The Church of Jesus Christ of Latter-day Saints, 2 Jan 2025", "title": "FamilySearch 2024 Genealogy Highlights", "url": "https://newsroom.churchofjesuschrist.org/article/familysearch-2024-genealogy-highlights", "date": "2025-01-02", "written_by": "makers", "quote": "FamilySearch can convert an image of text into a machine-readable text format, allowing users to search the full text of the records." }, { "kind": "press release", "citation": "Transkribus website", "title": "Transkribus", "url": "https://www.transkribus.org/", "written_by": "makers", "quote": "turns centuries of handwriting into text you can search, study, and share." }, { "kind": "press release", "citation": "Transkribus website, project examples", "title": "Transkribus", "url": "https://www.transkribus.org/", "written_by": "makers", "quote": "transcribed 20,000 pages in two months" }, { "kind": "other", "citation": "Seaver R (13 Jan 2026). What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries. Genea-Musings (reproducing FamilySearch's announcement).", "title": "What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries", "url": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "date": "2026-01-13", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0279-source-0001", "AIBD-0279-source-0002", "AIBD-0279-source-0003", "AIBD-0279-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Newsroom of The Church of Jesus Christ of Latter-day Saints, 2 Jan 2025", "title": "FamilySearch 2024 Genealogy Highlights", "url": "https://newsroom.churchofjesuschrist.org/article/familysearch-2024-genealogy-highlights", "date": "2025-01-02", "written_by": "makers", "quote": "FamilySearch can convert an image of text into a machine-readable text format, allowing users to search the full text of the records." }, { "kind": "press release", "citation": "Transkribus website", "title": "Transkribus", "url": "https://www.transkribus.org/", "written_by": "makers", "quote": "turns centuries of handwriting into text you can search, study, and share." }, { "kind": "press release", "citation": "Transkribus website, project examples", "title": "Transkribus", "url": "https://www.transkribus.org/", "written_by": "makers", "quote": "transcribed 20,000 pages in two months" }, { "kind": "other", "citation": "Seaver R (13 Jan 2026). What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries. Genea-Musings (reproducing FamilySearch's announcement).", "title": "What to Expect from FamilySearch in 2026: Emerging Technologies Will Help Fuel New Family Discoveries", "url": "https://www.geneamusings.com/2026/01/what-to-expect-from-familysearch-in.html", "date": "2026-01-13", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "FamilySearch introduced AI handwriting-recognition full-text search via FamilySearch Labs in 2024; Transkribus (READ-COOP) reports 200+ million pages deciphered. Makers' accounts only; no finding.", "account": "The Church of Jesus Christ of Latter-day Saints newsroom (2 January 2025) reviewed FamilySearch's 2024. It says FamilySearch “can convert an image of text into a machine-readable text format, allowing users to search the full text of the records”. That uses handwriting recognition and OCR. Full-Text Search was introduced through FamilySearch Labs in 2024, and 2.5 billion searchable records and images were added overall. It gives no example of a user discovery. Transkribus, developed by the European cooperative READ-COOP SCE, says on its site it “turns centuries of handwriting into text you can search, study, and share”. It claims over 500,000 users and 200 million pages deciphered. It cites projects such as the University of Georgia transcribing 20,000 pages in two months and Archion's portal of over 200,000 German church books. No independent source documenting a specific discovery, reunion or entitlement from either system was found. FamilySearch's help article on full-text search refused access here. The feature launched in 2024." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FamilySearch Full-Text Search (handwriting recognition and OCR); Transkribus (READ-COOP SCE)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "FamilySearch International; READ-COOP SCE" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FamilySearch Full-Text Search and Transkribus make handwritten records searchable with AI; no specific discovery documented", "headline": "FamilySearch and Transkribus make handwritten records searchable" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e70822d2b28676feb5c832da2482e01002bc36e5efe86d10f3b367215a7f897a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Church of Jesus Christ of Latter-day Saints newsroom (2 January 2025) reviewed FamilySearch's 2024. It says FamilySearch “can convert an image of text into a machine-readable text format, allowing users to search the full text of the records”. That uses handwriting recognition and OCR. Full-Text Search was introduced through FamilySearch Labs in 2024, and 2.5 billion searchable records and images were added overall. It gives no example of a user discovery. Transkribus, developed by the European cooperative READ-COOP SCE, says on its site it “turns centuries of handwriting into text you can search, study, and share”. It claims over 500,000 users and 200 million pages deciphered. It cites projects such as the University of Georgia transcribing 20,000 pages in two months and Archion's portal of over 200,000 German church books. No independent source documenting a specific discovery, reunion or entitlement from either system was found. FamilySearch's help article on full-text search refused access here. The feature launched in 2024.", "replication": { "produced_by": [ "Handwriting-recognition models applied to digitized record images", "Indexing of recognized text for search" ], "must_hold": [ "Recognition accuracy adequate for names and places", "Independent documentation of specific findings (absent)" ], "echoes": [ { "setting": "University of Georgia enslavement-records project using Transkribus (vendor-reported)", "outcome": "unknown", "source": "https://www.transkribus.org/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0569", "title": "Wigan Council: QuickAction in adult social care", "summary": "Wigan reports 107 staff days saved on minutes and new analysis of 4,500 tenant responses through QuickAction tools.", "date_observed": "2025-01-02", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-034", "account": "Wigan and Agilisys developed QuickAction workflows for care assessments, minutes, audits, and analysis of free-text surveys. The council reports 107 staff days saved in minute-taking and analysis of 4,500 tenant responses that could not previously be processed in aggregate. Reduced sickness, recruitment, and overtime remain projections. The account provides no independent outcome evaluation.", "category": "general benefit", "unexpected": false, "purpose": "Reduce social-care administration and make qualitative feedback usable for service teams.", "system": "Agilisys Transform QuickAction tools for assessments, minutes, audits, and survey analysis", "model_version": null, "developer": "Agilisys Transform in co-development with Wigan Council", "deployer": "Wigan Council", "location": "United Kingdom", "domain": "Adult-social-care and housing administration", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council can analyze qualitative responses that it previously could not process in aggregate." }, { "group": "personal", "depth": 1, "reason": "Reduced note-taking and processing effort saves staff time. Reductions in sickness, overtime, and recruitment remain projected." } ], "ai_role": { "status": "assessed", "statement": "The tools transcribe, summarize, and analyze material that staff previously processed manually or could not analyze at scale. The council attributes time and analytical-capability gains to these workflows, while other workforce outcomes remain projected." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Wigan Council: QuickAction in adult social care", "url": "https://www.local.gov.uk/case-studies/wigan-council-quickaction-adult-social-care", "date": "2025-01-02", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Council staff and Agilisys co-developed several tools around specific adult-social-care administrative tasks.", "The reported deployments include meeting minutes and analysis of care and tenant feedback, with further refinement during pilots." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "Wigan reports time savings and newly usable survey responses", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/wigan-council-quickaction-adult-social-care", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0569", "catalog_version": "1.0.0", "source_fingerprint": "d6c9fffe79d61c3c3ca5aa2f1f3b4daa9253d1d69284edacd3bbafffb2dd3b20", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0569-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Agilisys Transform in co-development with Wigan Council", "deployer": "Wigan Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The tools transcribe, summarize, and analyze material that staff previously processed manually or could not analyze at scale. 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"review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" 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"evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-034" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0569" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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"Wigan and Agilisys developed QuickAction workflows for care assessments, minutes, audits, and analysis of free-text surveys. The council reports 107 staff days saved in minute-taking and analysis of 4,500 tenant responses that could not previously be processed in aggregate. Reduced sickness, recruitment, and overtime remain projections. The account provides no independent outcome evaluation.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council can analyze qualitative responses that it previously could not process in aggregate." }, { "group": "personal", "depth": 1, "reason": "Reduced note-taking and processing effort saves staff time. 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The account provides no independent outcome evaluation.", "replication": { "produced_by": [ "Council staff and Agilisys co-developed several tools around specific adult-social-care administrative tasks.", "The reported deployments include meeting minutes and analysis of care and tenant feedback, with further refinement during pilots." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0350", "title": "Skylight speed-range and machine-learning fishing alerts may have led Argentina's Prefectura Naval to intercept the Vanuatu-flagged XINRUN 579 on 5 January 2025, and a fine may have been paid", "summary": "PNA intercepted XINRUN 579 fishing illegally in Argentina's EEZ on 5 January 2025; Skylight says its speed-range and ML fishing alerts prompted the response and a first electronic fine was paid.", "date_observed": "2025-01-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Sunday 5 January 2025 the Prefectura Naval Argentina (PNA) detected the Vanuatu-flagged trawler XinRun 579. It was in Argentina's exclusive economic zone off Caleta Olivia, Santa Cruz, sailing at under 6 knots. Local rules treat that as indicating trawling. Coastguard vessel GC-25 Azopardo intercepted it. The captain was formally notified of an infraction under Law 24.922, opening administrative proceedings (Agenda Malvinas, 8 January 2025, citing official information). Skylight, the free AI maritime-monitoring platform of the Allen Institute for AI, published its own account on 31 March 2025. A rule-based Speed Range Event first alerted the authorities. A Fishing Event alert from its machine-learning model came 40 minutes later. PNA analysts redirected a nearby coastguard vessel. It led to Argentina's first international electronic fine using AI-powered evidence, with the fine and operational costs paid. It quotes the EICEMAR coordinator and the PNA GIS division lead crediting Skylight. The independent news report attributes the detection to the PNA's Sistema Guardacostas and does not mention Skylight or AI. The PNA release Skylight links to is not found live or in the Internet Archive. An NVIDIA Developer blog (3 March 2025) also reports the interdiction and fine.", "category": "protective response", "unexpected": false, "purpose": "Real-time detection of suspicious vessel behavior and fishing activity to support maritime enforcement against illegal, unreported and unregulated fishing. The interception was the intended use.", "system": "Skylight maritime-monitoring platform (Speed Range Event rule and machine-learning Fishing Event detection)", "model_version": "Atlantes", "developer": "Allen Institute for AI (Ai2), Skylight", "deployer": "Prefectura Naval Argentina (Dirección de Tráfico Marítimo, Fluvial y Lacustre; EICEMAR)", "location": "Argentine exclusive economic zone off Caleta Olivia, Santa Cruz, Argentina", "domain": "Fisheries enforcement / illegal, unreported and unregulated fishing", "segment": "National coastguard using a free non-profit AI platform", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "An interception and fine for illegal fishing protect a fishery; no ecological gain is measured and no enforcement type exists.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 2, "reason": "The PNA intercepted the vessel within hours and, per Skylight, issued its first international electronic fine with the fine and costs paid. The independent report confirms the interception and administrative proceedings." }, { "group": "societal", "depth": 1, "reason": "One vessel among hundreds operating at the edge of Argentina's EEZ each season; the fishery-level effect is not quantified." } ], "ai_role": { "status": "assessed", "statement": "Skylight's own account describes a two-stage AI contribution. A rule-based Speed Range Event flagged the vessel at under 6 knots inside an area of interest. 40 minutes later a Fishing Event from its machine-learning model, which detects longlining, trawling and squid jigging, reinforced the suspicion. PNA analysts then redirected a coastguard vessel. A retired PNA captain is quoted saying Skylight contributed directly to the decision. This is the maker's account, with the deployer's officers quoted inside it. The independent report (Agenda Malvinas, citing Pescare and official information) attributes the detection to the PNA's Sistema Guardacostas and does not name Skylight or AI. So the attribution to the AI output is not independently confirmed. The PNA release Skylight links to is not among the sources." }, "evidence": [ { "kind": "news report", "citation": "Agenda Malvinas (2025). Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas. 8 January 2025 (source line: Pescare).", "title": "Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "la Prefectura Naval Argentina detectó este domingo 5 de enero, al buque pesquero XinRun 579, de bandera de Vanuatu, realizando pesca ilegal en la Zona Económica Exclusiva Argentina" }, { "kind": "news report", "citation": "Agenda Malvinas (2025). Same article, detection and interception sentences.", "title": "Prefectura detectó un buque asiático pescando ilegalmente (interception)", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "Tras la intercepción del Guardacostas GC-25 Azopardo, se notificó formalmente al capitán del XinRun 579 sobre la infracción" }, { "kind": "press release", "citation": "Skylight (2025). Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing. skylight.global, 31 March 2025 (maker's account).", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Just 40 minutes later, a Fishing Event alert provided additional intelligence, reinforcing suspicions that the vessel could be engaged in illegal fishing activity." }, { "kind": "press release", "citation": "Skylight (2025). Same article, description of the detection stages.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (machine-learning model)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "then by a machine learning model that detects several types of fishing behavior like long lining, trawling, and squid jigging" }, { "kind": "press release", "citation": "Skylight (2025). Same article, quotation attributed to Retired Captain Almada, Coordinator of EICEMAR, Prefectura Naval Argentina.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (PNA quotation)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Skylight contributed directly to the Coast Guard's decision-making by delivering immediate and reliable insights." }, { "kind": "press release", "citation": "Skylight (2025). Same article, outcome sentence.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (fine)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "The case led to Argentina’s first international electronic fine using AI-powered evidence." }, { "kind": "press release", "citation": "Wolfberg, E. (2025). AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale. NVIDIA Developer blog, 3 March 2025 (technology-partner blog, not the system's maker).", "title": "AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale", "url": "https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "date": "2025-03-03", "written_by": "independent", "quote": "Argentina's Coast Guard interdicted—and later fined—a vessel illegally fishing in its exclusive economic zone after Skylight alerted it to the vessel's suspicious behavior" }, { "kind": "press release", "citation": "Skylight (2026). Year in Review: Skylight Opens to the Public, Introduces Shippy, and Helps Partners Act at Sea (Impact Report June 2025-May 2026).", "title": "Skylight Impact Report 2025-2026", "url": "https://www.skylight.global/news/impact-report-2025-2026", "date": null, "written_by": "makers", "quote": "Skylight surfaces signals. The inspections, fines, and decisions belong to the agencies that made them." } ], "replication": { "produced_by": [ "A vessel transmitting AIS inside a monitored area of interest", "A speed-range rule tuned to the local legal definition of trawling speed", "A machine-learning fishing-behavior model producing a second alert within 40 minutes", "PNA analysts integrating Skylight with the Sistema Guardacostas and a coastguard vessel within reach" ], "must_hold": [ "AIS transmissions not switched off or spoofed", "A patrol asset close enough to intercept before the vessel leaves the EEZ", "A legal route to sanction (Law 24.922 and the electronic fine procedure)", "Analyst confirmation of each alert before dispatch" ], "echoes": [ { "date": null, "setting": "Gabon, ANPN marine parks: Skylight alert on GUO JI 838 entering a restricted MPA led to a patrol being sent; no outcome stated (Skylight's account, undated)", "model_version": null, "outcome": "unknown", "source": "https://www.skylight.global/news/stories-from-the-field-protecting-the-biggest-marine-national-park-system-in-africa" }, { "date": null, "setting": "Skylight impact report June 2025-May 2026: aggregated partner results of 21+ vessels interdicted and fines issued, US$915,000+ in fines, without case-level attribution (maker's figures)", "model_version": null, "outcome": "recurred", "source": "https://www.skylight.global/news/impact-report-2025-2026" } ] }, "paired_incident": null, "headline": "Skylight alerts may have led PNA to intercept XINRUN 579", "metric": null, "comparator": { "against": "PNA's capability before Skylight's real-time fishing detection", "before": null, "after": "a Speed Range Event alert, then a Fishing Event alert 40 minutes later", "basis": "assumed", "quote": "This kind of swift and decisive assistance wouldn't have been possible just a few months ago, before Skylight’s latest advancements in real-time fishing detection.", "url": "https://www.skylight.global/news/argentina-success-story" }, "later": { "status": "litigated", "date": "2025-03-31", "note": "The administrative proceeding ended with the vessel paying the fine and the authorities' operational costs, as Skylight reported on 31 March 2025 (the payment date itself is not given; NVIDIA's 3 March 2025 blog already said the vessel was later fined).", "quote": "The vessel paid both the fine and the operational costs incurred by authorities–underscoring how smarter, faster detection is helping enforcement teams respond quickly and build stronger, more actionable cases against those who exploit the ocean.", "url": "https://www.skylight.global/news/argentina-success-story" }, "value": null, "developer_country": "United States", "deployer_country": "Argentina", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.skylight.global/news/argentina-success-story; https://www.skylight.global/news/argentina-success-story; https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://allenai.org/about; https://en.wikipedia.org/wiki/Argentine_Naval_Prefecture", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, one independent press release and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0350", "catalog_version": "1.0.0", "source_fingerprint": "30e9f88a9087fef78c19cfc9c9322d9ab4b3a849e0f3dd14333df59dc2954154", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0350-source-0001", "AIBD-0350-source-0002", "AIBD-0350-source-0003", "AIBD-0350-source-0004", "AIBD-0350-source-0005", "AIBD-0350-source-0006", "AIBD-0350-source-0007", "AIBD-0350-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Allen Institute for AI (Ai2), Skylight", "deployer": "Prefectura Naval Argentina (Dirección de Tráfico Marítimo, Fluvial y Lacustre; EICEMAR)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Skylight's own account describes a two-stage AI contribution. 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It was in Argentina's exclusive economic zone off Caleta Olivia, Santa Cruz, sailing at under 6 knots. Local rules treat that as indicating trawling. Coastguard vessel GC-25 Azopardo intercepted it. The captain was formally notified of an infraction under Law 24.922, opening administrative proceedings (Agenda Malvinas, 8 January 2025, citing official information). Skylight, the free AI maritime-monitoring platform of the Allen Institute for AI, published its own account on 31 March 2025. A rule-based Speed Range Event first alerted the authorities. A Fishing Event alert from its machine-learning model came 40 minutes later. PNA analysts redirected a nearby coastguard vessel. It led to Argentina's first international electronic fine using AI-powered evidence, with the fine and operational costs paid. It quotes the EICEMAR coordinator and the PNA GIS division lead crediting Skylight. The independent news report attributes the detection to the PNA's Sistema Guardacostas and does not mention Skylight or AI. The PNA release Skylight links to is not found live or in the Internet Archive. 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The interception was the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Argentine exclusive economic zone off Caleta Olivia, Santa Cruz, Argentina", "developer_country": "United States", "deployer_country": "Argentina" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Real-time detection of suspicious vessel behavior and fishing activity to support maritime enforcement against illegal, unreported and unregulated fishing. 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https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://allenai.org/about; https://en.wikipedia.org/wiki/Argentine_Naval_Prefecture", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A vessel transmitting AIS inside a monitored area of interest", "A speed-range rule tuned to the local legal definition of trawling speed", "A machine-learning fishing-behavior model producing a second alert within 40 minutes", "PNA analysts integrating Skylight with the Sistema Guardacostas and a coastguard vessel within reach" ], "must_hold": [ "AIS transmissions not switched off or spoofed", "A patrol asset close enough to intercept before the vessel leaves the EEZ", "A legal route to sanction (Law 24.922 and the electronic fine procedure)", "Analyst confirmation of each alert before dispatch" ], "echoes": [ { "setting": "Gabon, ANPN marine parks: Skylight alert on GUO JI 838 entering a restricted MPA led to a patrol being sent; 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https://www.skylight.global/news/argentina-success-story; https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://allenai.org/about; https://en.wikipedia.org/wiki/Argentine_Naval_Prefecture", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Fisheries enforcement / illegal, unreported and unregulated fishing", "segment": "National coastguard using a free non-profit AI platform" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Agenda Malvinas (2025). Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas. 8 January 2025 (source line: Pescare).", "title": "Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "la Prefectura Naval Argentina detectó este domingo 5 de enero, al buque pesquero XinRun 579, de bandera de Vanuatu, realizando pesca ilegal en la Zona Económica Exclusiva Argentina" }, { "kind": "news report", "citation": "Agenda Malvinas (2025). Same article, detection and interception sentences.", "title": "Prefectura detectó un buque asiático pescando ilegalmente (interception)", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "Tras la intercepción del Guardacostas GC-25 Azopardo, se notificó formalmente al capitán del XinRun 579 sobre la infracción" }, { "kind": "press release", "citation": "Skylight (2025). Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing. skylight.global, 31 March 2025 (maker's account).", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Just 40 minutes later, a Fishing Event alert provided additional intelligence, reinforcing suspicions that the vessel could be engaged in illegal fishing activity." }, { "kind": "press release", "citation": "Skylight (2025). Same article, description of the detection stages.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (machine-learning model)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "then by a machine learning model that detects several types of fishing behavior like long lining, trawling, and squid jigging" }, { "kind": "press release", "citation": "Skylight (2025). Same article, quotation attributed to Retired Captain Almada, Coordinator of EICEMAR, Prefectura Naval Argentina.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (PNA quotation)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Skylight contributed directly to the Coast Guard's decision-making by delivering immediate and reliable insights." }, { "kind": "press release", "citation": "Skylight (2025). Same article, outcome sentence.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (fine)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "The case led to Argentina’s first international electronic fine using AI-powered evidence." }, { "kind": "press release", "citation": "Wolfberg, E. (2025). AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale. NVIDIA Developer blog, 3 March 2025 (technology-partner blog, not the system's maker).", "title": "AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale", "url": "https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "date": "2025-03-03", "written_by": "independent", "quote": "Argentina's Coast Guard interdicted—and later fined—a vessel illegally fishing in its exclusive economic zone after Skylight alerted it to the vessel's suspicious behavior" }, { "kind": "press release", "citation": "Skylight (2026). Year in Review: Skylight Opens to the Public, Introduces Shippy, and Helps Partners Act at Sea (Impact Report June 2025-May 2026).", "title": "Skylight Impact Report 2025-2026", "url": "https://www.skylight.global/news/impact-report-2025-2026", "written_by": "makers", "quote": "Skylight surfaces signals. The inspections, fines, and decisions belong to the agencies that made them." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0350-source-0001", "AIBD-0350-source-0002", "AIBD-0350-source-0003", "AIBD-0350-source-0004", "AIBD-0350-source-0005", "AIBD-0350-source-0006", "AIBD-0350-source-0007", "AIBD-0350-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Agenda Malvinas (2025). Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas. 8 January 2025 (source line: Pescare).", "title": "Prefectura detectó un buque asiático pescando ilegalmente en aguas argentinas", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "la Prefectura Naval Argentina detectó este domingo 5 de enero, al buque pesquero XinRun 579, de bandera de Vanuatu, realizando pesca ilegal en la Zona Económica Exclusiva Argentina" }, { "kind": "news report", "citation": "Agenda Malvinas (2025). Same article, detection and interception sentences.", "title": "Prefectura detectó un buque asiático pescando ilegalmente (interception)", "url": "https://agendamalvinas.com.ar/noticia/prefectura-detecto-un-buque-asiatico-pescando-ilegalmente-en-aguas-argentinas", "date": "2025-01-08", "written_by": "independent", "quote": "Tras la intercepción del Guardacostas GC-25 Azopardo, se notificó formalmente al capitán del XinRun 579 sobre la infracción" }, { "kind": "press release", "citation": "Skylight (2025). Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing. skylight.global, 31 March 2025 (maker's account).", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Just 40 minutes later, a Fishing Event alert provided additional intelligence, reinforcing suspicions that the vessel could be engaged in illegal fishing activity." }, { "kind": "press release", "citation": "Skylight (2025). Same article, description of the detection stages.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (machine-learning model)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "then by a machine learning model that detects several types of fishing behavior like long lining, trawling, and squid jigging" }, { "kind": "press release", "citation": "Skylight (2025). Same article, quotation attributed to Retired Captain Almada, Coordinator of EICEMAR, Prefectura Naval Argentina.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (PNA quotation)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "Skylight contributed directly to the Coast Guard's decision-making by delivering immediate and reliable insights." }, { "kind": "press release", "citation": "Skylight (2025). Same article, outcome sentence.", "title": "Real-Time Intelligence Powers Argentina's Fight Against Illegal Fishing (fine)", "url": "https://www.skylight.global/news/argentina-success-story", "date": "2025-03-31", "written_by": "makers", "quote": "The case led to Argentina’s first international electronic fine using AI-powered evidence." }, { "kind": "press release", "citation": "Wolfberg, E. (2025). AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale. NVIDIA Developer blog, 3 March 2025 (technology-partner blog, not the system's maker).", "title": "AI Model Offers Conservationists New Tools to Protect Fisheries, Wildlife at Scale", "url": "https://developer.nvidia.com/blog/ai-model-offers-conservationists-new-tools-to-protect-fisheries-wildlife-at-scale/", "date": "2025-03-03", "written_by": "independent", "quote": "Argentina's Coast Guard interdicted—and later fined—a vessel illegally fishing in its exclusive economic zone after Skylight alerted it to the vessel's suspicious behavior" }, { "kind": "press release", "citation": "Skylight (2026). Year in Review: Skylight Opens to the Public, Introduces Shippy, and Helps Partners Act at Sea (Impact Report June 2025-May 2026).", "title": "Skylight Impact Report 2025-2026", "url": "https://www.skylight.global/news/impact-report-2025-2026", "written_by": "makers", "quote": "Skylight surfaces signals. The inspections, fines, and decisions belong to the agencies that made them." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "PNA intercepted XINRUN 579 fishing illegally in Argentina's EEZ on 5 January 2025; Skylight says its speed-range and ML fishing alerts prompted the response and a first electronic fine was paid.", "account": "On Sunday 5 January 2025 the Prefectura Naval Argentina (PNA) detected the Vanuatu-flagged trawler XinRun 579. It was in Argentina's exclusive economic zone off Caleta Olivia, Santa Cruz, sailing at under 6 knots. Local rules treat that as indicating trawling. Coastguard vessel GC-25 Azopardo intercepted it. The captain was formally notified of an infraction under Law 24.922, opening administrative proceedings (Agenda Malvinas, 8 January 2025, citing official information). Skylight, the free AI maritime-monitoring platform of the Allen Institute for AI, published its own account on 31 March 2025. A rule-based Speed Range Event first alerted the authorities. A Fishing Event alert from its machine-learning model came 40 minutes later. PNA analysts redirected a nearby coastguard vessel. It led to Argentina's first international electronic fine using AI-powered evidence, with the fine and operational costs paid. It quotes the EICEMAR coordinator and the PNA GIS division lead crediting Skylight. The independent news report attributes the detection to the PNA's Sistema Guardacostas and does not mention Skylight or AI. The PNA release Skylight links to is not found live or in the Internet Archive. An NVIDIA Developer blog (3 March 2025) also reports the interdiction and fine." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Atlantes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Skylight maritime-monitoring platform (Speed Range Event rule and machine-learning Fishing Event detection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Allen Institute for AI (Ai2), Skylight" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Skylight speed-range and machine-learning fishing alerts may have led Argentina's Prefectura Naval to intercept the Vanuatu-flagged XINRUN 579 on 5 January 2025, and a fine may have been paid", "headline": "Skylight alerts may have led PNA to intercept XINRUN 579" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "30e9f88a9087fef78c19cfc9c9322d9ab4b3a849e0f3dd14333df59dc2954154" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Sunday 5 January 2025 the Prefectura Naval Argentina (PNA) detected the Vanuatu-flagged trawler XinRun 579. It was in Argentina's exclusive economic zone off Caleta Olivia, Santa Cruz, sailing at under 6 knots. Local rules treat that as indicating trawling. Coastguard vessel GC-25 Azopardo intercepted it. The captain was formally notified of an infraction under Law 24.922, opening administrative proceedings (Agenda Malvinas, 8 January 2025, citing official information). Skylight, the free AI maritime-monitoring platform of the Allen Institute for AI, published its own account on 31 March 2025. A rule-based Speed Range Event first alerted the authorities. A Fishing Event alert from its machine-learning model came 40 minutes later. PNA analysts redirected a nearby coastguard vessel. It led to Argentina's first international electronic fine using AI-powered evidence, with the fine and operational costs paid. It quotes the EICEMAR coordinator and the PNA GIS division lead crediting Skylight. The independent news report attributes the detection to the PNA's Sistema Guardacostas and does not mention Skylight or AI. The PNA release Skylight links to is not found live or in the Internet Archive. An NVIDIA Developer blog (3 March 2025) also reports the interdiction and fine.", "replication": { "produced_by": [ "A vessel transmitting AIS inside a monitored area of interest", "A speed-range rule tuned to the local legal definition of trawling speed", "A machine-learning fishing-behavior model producing a second alert within 40 minutes", "PNA analysts integrating Skylight with the Sistema Guardacostas and a coastguard vessel within reach" ], "must_hold": [ "AIS transmissions not switched off or spoofed", "A patrol asset close enough to intercept before the vessel leaves the EEZ", "A legal route to sanction (Law 24.922 and the electronic fine procedure)", "Analyst confirmation of each alert before dispatch" ], "echoes": [ { "setting": "Gabon, ANPN marine parks: Skylight alert on GUO JI 838 entering a restricted MPA led to a patrol being sent; no outcome stated (Skylight's account, undated)", "outcome": "unknown", "source": "https://www.skylight.global/news/stories-from-the-field-protecting-the-biggest-marine-national-park-system-in-africa" }, { "setting": "Skylight impact report June 2025-May 2026: aggregated partner results of 21+ vessels interdicted and fines issued, US$915,000+ in fines, without case-level attribution (maker's figures)", "outcome": "recurred", "source": "https://www.skylight.global/news/impact-report-2025-2026" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0565", "title": "Transport for West Midlands: Near miss detection with VivaCity", "summary": "Transport for West Midlands reports 61,000 detected near misses and road-layout changes informed by AI. Avoided injuries are not established.", "date_observed": "2025-01-06", "date_basis": "source publication", "date_precision": "day", "benefit_status": "mixed", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-029", "account": "Transport for West Midlands enabled VivaCity near-miss detection in 40 sensors and used the observations to select and implement road-layout changes. The source reports 61,000 detected near misses in six months and the installation of measures including central islands and narrower junction mouths. 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The interventions are documented, but the source does not establish a reduction in collisions or injuries." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "VivaCity AI near-miss detection sensors and analytics" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "VivaCity" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Transport for West Midlands: Near miss detection with VivaCity", "headline": "West Midlands uses near-miss data to change road layouts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "90d5011ce5211de1c3b069ec2521e6fa815560b55fd8424ada688eb818e5bdc2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Transport for West Midlands enabled VivaCity near-miss detection in 40 sensors and used the observations to select and implement road-layout changes. The source reports 61,000 detected near misses in six months and the installation of measures including central islands and narrower junction mouths. The interventions are documented, but the source does not establish a reduction in collisions or injuries.", "replication": { "produced_by": [ "The January–August 2024 pilot enabled near-miss functions on 40 existing sensors, with later continuation funding.", "Practitioners used dashboards and video clips to identify hotspots and implement measures such as islands and narrower junction mouths." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0542", "title": "Barnsley Council: Pioneering use of Microsoft Copilot", "summary": "Barnsley reports that Copilot saves time on meeting notes, summaries, procurement, legal work, and social-care administration.", "date_observed": "2025-01-09", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-001", "account": "Barnsley reports that its expanded Microsoft Copilot deployment saves staff time in transcription, summaries, administration, procurement, legal work, and finance. 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The account provides no independent outcome evaluation.", "title": "Buckinghamshire Council: Early adoption of Microsoft Copilot", "url": "https://www.local.gov.uk/case-studies/buckinghamshire-council-early-adoption-microsoft-copilot", "date": "2025-01-09", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0545-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. 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A deaf colleague reportedly participates in meetings and reviews conversations with less assistance. The source does not establish whether that gain persisted. It also reports hallucinations and inconsistencies in other uses." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Microsoft Copilot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Microsoft" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Buckinghamshire Council: Early adoption of Microsoft Copilot", "headline": "Buckinghamshire reports time savings and better deaf access" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cf75b8c8709671f3cab3826c83843f3a3ac7e67bd293831c741d59903c081fec" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Buckinghamshire reports that Copilot saves two minutes per customer-service call and 60–90 minutes daily for a monitored group of six executive assistants. A deaf colleague reportedly participates in meetings and reviews conversations with less assistance. The source does not establish whether that gain persisted. It also reports hallucinations and inconsistencies in other uses.", "replication": { "produced_by": [ "The early-adopter rollout provided 300 licenses across departments, with staff support and monitoring of selected tasks.", "The accessibility account concerns a specific colleague using transcription to identify speakers, review discussions, and track actions." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0140", "title": "Grok may have read a “clear fracture line in the distal radius” on a teenager's wrist X-ray that urgent care had cleared; a wrist specialist confirmed the displaced fracture and cast it (January 2025)", "summary": "By her mother's X post of 11 January 2025, Grok flagged a displaced wrist fracture urgent care missed; an orthopaedist confirmed and cast it.", "date_observed": "2025-01-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 11 January 2025 AJ Kay (@AJKayWriter, United States) posted about a multi-vehicle freeway crash the weekend before. An urgent-care doctor and radiologist had read her teenage daughter's wrist X-rays as free of breaks. They sent her home with an ace wrap and ibuprofen. With the hand cold and tingling and the thumb immobile, she uploaded the printed X-ray to Grok on X. It said there was “a clear fracture line in the distal radius”, not a growth plate, and called it “quite obvious”. After a PCP referral, a wrist specialist took new X-rays next day. The specialist diagnosed a distal radial head fracture with dorsal displacement and cast it, saying untreated displacement would likely have needed surgery.", "category": "protective response", "unexpected": false, "purpose": "Grok is xAI's general-purpose chatbot on X with image input. On 3 January 2025 Elon Musk invited users to upload “any image to Grok for analysis, from medical tests to video games”. So reading an X-ray was a promoted use rather than a designed clinical function. Grok's own replies told the user to consult a professional. When a physician asked it the next day, it said it cannot diagnose medical injuries.", "system": "Grok chatbot (xAI) on X, image analysis of an uploaded wrist X-ray", "model_version": "Grok 2 (the poster cites Musk's statement that 'Grok2 could read medical images'; not confirmed by xAI)", "developer": "xAI", "deployer": "X Corp (Grok on the X platform)", "location": null, "domain": "Healthcare - musculoskeletal radiology / fracture diagnosis", "segment": "Caregiver-initiated use of a consumer LLM", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-01-12-a928" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "By her mother's account the girl's displaced distal radius fracture was set and cast within days instead of staying in an ace wrap. The orthopaedist's remark that untreated displacement would likely have needed surgery comes only from the mother. No clinician, clinic or record is public. She had already asked for the films for the PCP. Whether the outcome would have differed without Grok is not established." } ], "ai_role": { "status": "assessed", "statement": "Screenshots attached to the post show Grok answering three questions about the uploaded image. It said there is “a clear fracture line visible in the distal radius”. It said the line is “a fracture line rather than a fused growth plate”. It said the break is “quite obvious” with “dorsal displacement”. Each time it advised a professional consultation. The orthopaedist's reading matched. But the mother states that she did not mention Grok to the specialist and that the diagnosis was “completely independent”. She had already asked for the X-ray prints to take to the PCP. Grok's contribution was therefore to strengthen her resolve to seek a second opinion. Everything rests on her account. No clinician, clinic or record has spoken publicly. The next day Grok told a physician who asked that it cannot diagnose medical injuries." }, "evidence": [ { "kind": "other", "citation": "Kay, A. J. (2025). True story: @Grok diagnosed my daughter's broken wrist last week. Post on X, @AJKayWriter, 11 January 2025 (14:19 UTC), status 1878084198205907173; three Grok screenshots and one photo of the cast attached; about 14.4 million views.", "title": "True story: @Grok diagnosed my daughter's broken wrist last week", "url": "https://x.com/AJKayWriter/status/1878084198205907173", "date": "2025-01-11", "written_by": "beneficiary", "quote": "the wrist specialist took new x-rays (multiple views), examined her, and confirmed Grok’s diagnosis of a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "NDTV (2025). Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It. NDTV Feature, 12 January 2025.", "title": "Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It", "url": "https://www.ndtv.com/feature/woman-claims-elon-musks-grok-detected-her-daughter-s-fracture-after-doctors-fail-to-diagnose-it-7456337", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that delayed treatment could have led to surgery, but thanks to Grok's intervention, they were able to avoid this outcome and provide timely treatment." }, { "kind": "news report", "citation": "Hindustan Times (2025). Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'. Hindustan Times Trending, 12 January 2025.", "title": "Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'", "url": "https://www.hindustantimes.com/trending/mother-claims-elon-musk-s-ai-detected-daughter-s-fracture-that-doctors-missed-this-was-eye-opening-for-me-101736662763447.html", "date": "2025-01-12", "written_by": "independent", "quote": "A wrist specialist confirmed Grok’s diagnosis—a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "Mukhopadhyay, S. (2025). AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it. Mint, 12 January 2025.", "title": "AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it", "url": "https://www.livemint.com/ai/artificial-intelligence/ai-chat-helps-avoid-surgery-elon-musk-s-grok-identifies-teenage-girl-s-wrist-fracture-after-doctors-fail-to-diagnose-it-11736671754200.html", "date": "2025-01-12", "written_by": "independent", "quote": "the mother consulted a wrist specialist, who confirmed Grok’s diagnosis using additional X-rays and physical examination." }, { "kind": "news report", "citation": "India Today Trending Desk (2025). Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post. India Today, 12 January 2025.", "title": "Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post", "url": "https://www.indiatoday.in/trending-news/story/elon-musk-grok-diagnoses-fracture-missed-by-doctors-us-woman-claims-in-viral-post-2663680-2025-01-12", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that any further delay could have led to surgery, but due to Grok's timely detection, proper treatment was promptly administered." }, { "kind": "news report", "citation": "Livemint (2025). Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check. Mint, 12 January 2025. Reports Dr Cyriac Abby Philips's exchange with Grok.", "title": "Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check", "url": "https://www.livemint.com/technology/tech-news/hey-liar-elon-musk-claims-grok-ai-can-diagnose-medical-injuries-liverdoc-abby-philips-gives-him-a-reality-check-11736678451620.html", "date": "2025-01-12", "written_by": "independent", "quote": "No, I cannot diagnose medical injuries." }, { "kind": "press release", "citation": "Musk, E. (2025). Grok can diagnose medical injuries. Post on X, @elonmusk, 11 January 2025 (22:12 UTC), status 1878203372513136854; Mint reports it was posted in reply to a post about the AJ Kay account.", "title": "Grok can diagnose medical injuries", "url": "https://x.com/elonmusk/status/1878203372513136854", "date": "2025-01-11", "written_by": "makers", "quote": "Grok can diagnose medical injuries" }, { "kind": "news report", "citation": "TOI Lifestyle Desk (2025). Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman. The Times of India, 15 January 2025. Quotes Musk's 3 January 2025 post inviting image uploads.", "title": "Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman", "url": "https://timesofindia.indiatimes.com/life-style/health-fitness/health-news/elon-musks-grok-ai-diagnoses-fracture-missed-by-doctors-claims-woman/articleshow/117255256.cms", "date": "2025-01-15", "written_by": "independent", "quote": "You can upload any image to Grok for analysis, from medical tests to video games! Just tap the + button or paste the image into the entry bar" } ], "replication": { "produced_by": [ "A printed urgent-care wrist X-ray that the parent could photograph and upload", "Grok on X with image input, which Musk was publicly promoting for medical images in January 2025", "A parent who distrusted the first reading because of worsening signs (cold, tingling hand; immobile thumb; a wrist that did not look right). She had already asked for the films for the PCP", "Access within days to a PCP referral and a wrist specialist who re-imaged and examined the wrist" ], "must_hold": [ "Grok's reading was correct for this image on the mother's account only. Asked by a physician the next day, it said it cannot diagnose injuries. So its output is not reliable across users or images", "A clinician re-examined and re-imaged the wrist. Grok's output was never used as the diagnosis or the basis of treatment", "The only sources are the mother's post and news reports built from it. No clinic, clinician or record is public, and the surgery-avoidance statement is second-hand" ], "echoes": [] }, "paired_incident": null, "headline": "Grok spots a displaced wrist fracture that urgent care missed", "metric": null, "comparator": { "against": "the urgent-care doctor's and radiologist's reading of the same X-rays", "before": "Both the doctor who saw her and the radiologist declared her free of breaks and, after answering some of our questions, sent her home with an ace wrap and ibuprofen.", "after": "the wrist specialist took new x-rays (multiple views), examined her, and confirmed Grok’s diagnosis of a distal radial head fracture with dorsal displacement.", "basis": "assumed", "quote": "Both the doctor who saw her and the radiologist declared her free of breaks and, after answering some of our questions, sent her home with an ace wrap and ibuprofen.", "url": "https://x.com/AJKayWriter/status/1878084198205907173" }, "later": { "status": "unknown", "date": null, "note": "No dated follow-up on the daughter or statement from xAI is established. Reports that radiologists disputed the interpretation of her X-ray remain unverified.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-01-12-a928", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://x.com/AJKayWriter/status/1878084198205907173", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/XAI_(company); https://en.wikipedia.org/wiki/X_Corp.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports, the makers' press release and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0140", "catalog_version": "1.0.0", "source_fingerprint": "db416bb5f18790c7f13e09932ddb9f93d8d0c7e42da0d89ef7177a1bf402d013", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0140-source-0001", "AIBD-0140-source-0002", "AIBD-0140-source-0003", "AIBD-0140-source-0004", "AIBD-0140-source-0005", "AIBD-0140-source-0006", "AIBD-0140-source-0007", "AIBD-0140-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "xAI", "deployer": "X Corp (Grok on the X platform)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Screenshots attached to the post show Grok answering three questions about the uploaded image. It said there is “a clear fracture line visible in the distal radius”. It said the line is “a fracture line rather than a fused growth plate”. It said the break is “quite obvious” with “dorsal displacement”. Each time it advised a professional consultation. The orthopaedist's reading matched. But the mother states that she did not mention Grok to the specialist and that the diagnosis was “completely independent”. She had already asked for the X-ray prints to take to the PCP. Grok's contribution was therefore to strengthen her resolve to seek a second opinion. Everything rests on her account. No clinician, clinic or record has spoken publicly. The next day Grok told a physician who asked that it cannot diagnose medical injuries." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Grok identified a possible wrist fracture in an uploaded X-ray and advised medical consultation. The mother reported that its answers strengthened her decision to seek a second opinion.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Screenshots attached to the post show Grok answering three questions about the uploaded image. It said there is “a clear fracture line visible in the distal radius”. It said the line is “a fracture line rather than a fused growth plate”. It said the break is “quite obvious” with “dorsal displacement”. Each time it advised a professional consultation. The orthopaedist's reading matched. But the mother states that she did not mention Grok to the specialist and that the diagnosis was “completely independent”. She had already asked for the X-ray prints to take to the PCP. Grok's contribution was therefore to strengthen her resolve to seek a second opinion. Everything rests on her account. No clinician, clinic or record has spoken publicly. 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No clinician, clinic or record is public. She had already asked for the films for the PCP. Whether the outcome would have differed without Grok is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports, the makers' press release and the beneficiary's other. 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She said that the specialist reached an independent diagnosis and that she had not mentioned Grok. No clinician or medical record independently verifies the sequence.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-01-12-a928" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No dated follow-up on the daughter or statement from xAI is established. Reports that radiologists disputed the interpretation of her X-ray remain unverified." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "An orthopedist examined the X-ray and diagnosed the fracture." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0140" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 11 January 2025 AJ Kay (@AJKayWriter, United States) posted about a multi-vehicle freeway crash the weekend before. An urgent-care doctor and radiologist had read her teenage daughter's wrist X-rays as free of breaks. They sent her home with an ace wrap and ibuprofen. With the hand cold and tingling and the thumb immobile, she uploaded the printed X-ray to Grok on X. It said there was “a clear fracture line in the distal radius”, not a growth plate, and called it “quite obvious”. After a PCP referral, a wrist specialist took new X-rays next day. The specialist diagnosed a distal radial head fracture with dorsal displacement and cast it, saying untreated displacement would likely have needed surgery.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By her mother's account the girl's displaced distal radius fracture was set and cast within days instead of staying in an ace wrap. The orthopaedist's remark that untreated displacement would likely have needed surgery comes only from the mother. No clinician, clinic or record is public. She had already asked for the films for the PCP. Whether the outcome would have differed without Grok is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Grok is xAI's general-purpose chatbot on X with image input. On 3 January 2025 Elon Musk invited users to upload “any image to Grok for analysis, from medical tests to video games”. So reading an X-ray was a promoted use rather than a designed clinical function. Grok's own replies told the user to consult a professional. When a physician asked it the next day, it said it cannot diagnose medical injuries." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Grok is xAI's general-purpose chatbot on X with image input. On 3 January 2025 Elon Musk invited users to upload “any image to Grok for analysis, from medical tests to video games”. So reading an X-ray was a promoted use rather than a designed clinical function. Grok's own replies told the user to consult a professional. 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She had already asked for the films for the PCP", "Access within days to a PCP referral and a wrist specialist who re-imaged and examined the wrist" ], "must_hold": [ "Grok's reading was correct for this image on the mother's account only. Asked by a physician the next day, it said it cannot diagnose injuries. So its output is not reliable across users or images", "A clinician re-examined and re-imaged the wrist. Grok's output was never used as the diagnosis or the basis of treatment", "The only sources are the mother's post and news reports built from it. No clinic, clinician or record is public, and the surgery-avoidance statement is second-hand" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-01-12-a928", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://x.com/AJKayWriter/status/1878084198205907173", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/XAI_(company); https://en.wikipedia.org/wiki/X_Corp.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - musculoskeletal radiology / fracture diagnosis", "segment": "Caregiver-initiated use of a consumer LLM" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Kay, A. J. (2025). True story: @Grok diagnosed my daughter's broken wrist last week. Post on X, @AJKayWriter, 11 January 2025 (14:19 UTC), status 1878084198205907173; three Grok screenshots and one photo of the cast attached; about 14.4 million views.", "title": "True story: @Grok diagnosed my daughter's broken wrist last week", "url": "https://x.com/AJKayWriter/status/1878084198205907173", "date": "2025-01-11", "written_by": "beneficiary", "quote": "the wrist specialist took new x-rays (multiple views), examined her, and confirmed Grok’s diagnosis of a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "NDTV (2025). Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It. NDTV Feature, 12 January 2025.", "title": "Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It", "url": "https://www.ndtv.com/feature/woman-claims-elon-musks-grok-detected-her-daughter-s-fracture-after-doctors-fail-to-diagnose-it-7456337", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that delayed treatment could have led to surgery, but thanks to Grok's intervention, they were able to avoid this outcome and provide timely treatment." }, { "kind": "news report", "citation": "Hindustan Times (2025). Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'. Hindustan Times Trending, 12 January 2025.", "title": "Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'", "url": "https://www.hindustantimes.com/trending/mother-claims-elon-musk-s-ai-detected-daughter-s-fracture-that-doctors-missed-this-was-eye-opening-for-me-101736662763447.html", "date": "2025-01-12", "written_by": "independent", "quote": "A wrist specialist confirmed Grok’s diagnosis—a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "Mukhopadhyay, S. (2025). AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it. Mint, 12 January 2025.", "title": "AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it", "url": "https://www.livemint.com/ai/artificial-intelligence/ai-chat-helps-avoid-surgery-elon-musk-s-grok-identifies-teenage-girl-s-wrist-fracture-after-doctors-fail-to-diagnose-it-11736671754200.html", "date": "2025-01-12", "written_by": "independent", "quote": "the mother consulted a wrist specialist, who confirmed Grok’s diagnosis using additional X-rays and physical examination." }, { "kind": "news report", "citation": "India Today Trending Desk (2025). Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post. India Today, 12 January 2025.", "title": "Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post", "url": "https://www.indiatoday.in/trending-news/story/elon-musk-grok-diagnoses-fracture-missed-by-doctors-us-woman-claims-in-viral-post-2663680-2025-01-12", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that any further delay could have led to surgery, but due to Grok's timely detection, proper treatment was promptly administered." }, { "kind": "news report", "citation": "Livemint (2025). Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check. Mint, 12 January 2025. Reports Dr Cyriac Abby Philips's exchange with Grok.", "title": "Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check", "url": "https://www.livemint.com/technology/tech-news/hey-liar-elon-musk-claims-grok-ai-can-diagnose-medical-injuries-liverdoc-abby-philips-gives-him-a-reality-check-11736678451620.html", "date": "2025-01-12", "written_by": "independent", "quote": "No, I cannot diagnose medical injuries." }, { "kind": "press release", "citation": "Musk, E. (2025). Grok can diagnose medical injuries. Post on X, @elonmusk, 11 January 2025 (22:12 UTC), status 1878203372513136854; Mint reports it was posted in reply to a post about the AJ Kay account.", "title": "Grok can diagnose medical injuries", "url": "https://x.com/elonmusk/status/1878203372513136854", "date": "2025-01-11", "written_by": "makers", "quote": "Grok can diagnose medical injuries" }, { "kind": "news report", "citation": "TOI Lifestyle Desk (2025). Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman. The Times of India, 15 January 2025. Quotes Musk's 3 January 2025 post inviting image uploads.", "title": "Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman", "url": "https://timesofindia.indiatimes.com/life-style/health-fitness/health-news/elon-musks-grok-ai-diagnoses-fracture-missed-by-doctors-claims-woman/articleshow/117255256.cms", "date": "2025-01-15", "written_by": "independent", "quote": "You can upload any image to Grok for analysis, from medical tests to video games! Just tap the + button or paste the image into the entry bar" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0140-source-0001", "AIBD-0140-source-0002", "AIBD-0140-source-0003", "AIBD-0140-source-0004", "AIBD-0140-source-0005", "AIBD-0140-source-0006", "AIBD-0140-source-0007", "AIBD-0140-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Kay, A. J. (2025). True story: @Grok diagnosed my daughter's broken wrist last week. Post on X, @AJKayWriter, 11 January 2025 (14:19 UTC), status 1878084198205907173; three Grok screenshots and one photo of the cast attached; about 14.4 million views.", "title": "True story: @Grok diagnosed my daughter's broken wrist last week", "url": "https://x.com/AJKayWriter/status/1878084198205907173", "date": "2025-01-11", "written_by": "beneficiary", "quote": "the wrist specialist took new x-rays (multiple views), examined her, and confirmed Grok’s diagnosis of a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "NDTV (2025). Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It. NDTV Feature, 12 January 2025.", "title": "Woman Claims Elon Musk's Grok Detected Her Daughter's Fracture After Doctors Fail To Diagnose It", "url": "https://www.ndtv.com/feature/woman-claims-elon-musks-grok-detected-her-daughter-s-fracture-after-doctors-fail-to-diagnose-it-7456337", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that delayed treatment could have led to surgery, but thanks to Grok's intervention, they were able to avoid this outcome and provide timely treatment." }, { "kind": "news report", "citation": "Hindustan Times (2025). Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'. Hindustan Times Trending, 12 January 2025.", "title": "Mother claims Elon Musk's AI detected daughter's fracture that doctors missed: 'This was eye-opening for me'", "url": "https://www.hindustantimes.com/trending/mother-claims-elon-musk-s-ai-detected-daughter-s-fracture-that-doctors-missed-this-was-eye-opening-for-me-101736662763447.html", "date": "2025-01-12", "written_by": "independent", "quote": "A wrist specialist confirmed Grok’s diagnosis—a distal radial head fracture with dorsal displacement." }, { "kind": "news report", "citation": "Mukhopadhyay, S. (2025). AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it. Mint, 12 January 2025.", "title": "AI chat helps avoid surgery: Elon Musk's Grok identifies teenage girl's wrist fracture after doctors fail to diagnose it", "url": "https://www.livemint.com/ai/artificial-intelligence/ai-chat-helps-avoid-surgery-elon-musk-s-grok-identifies-teenage-girl-s-wrist-fracture-after-doctors-fail-to-diagnose-it-11736671754200.html", "date": "2025-01-12", "written_by": "independent", "quote": "the mother consulted a wrist specialist, who confirmed Grok’s diagnosis using additional X-rays and physical examination." }, { "kind": "news report", "citation": "India Today Trending Desk (2025). Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post. India Today, 12 January 2025.", "title": "Elon Musk's Grok diagnoses fracture missed by doctors, US woman claims in viral post", "url": "https://www.indiatoday.in/trending-news/story/elon-musk-grok-diagnoses-fracture-missed-by-doctors-us-woman-claims-in-viral-post-2663680-2025-01-12", "date": "2025-01-12", "written_by": "independent", "quote": "The specialist warned that any further delay could have led to surgery, but due to Grok's timely detection, proper treatment was promptly administered." }, { "kind": "news report", "citation": "Livemint (2025). Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check. Mint, 12 January 2025. Reports Dr Cyriac Abby Philips's exchange with Grok.", "title": "Elon Musk claims Grok AI can diagnose medical injuries, Indian doctor gives him a reality check", "url": "https://www.livemint.com/technology/tech-news/hey-liar-elon-musk-claims-grok-ai-can-diagnose-medical-injuries-liverdoc-abby-philips-gives-him-a-reality-check-11736678451620.html", "date": "2025-01-12", "written_by": "independent", "quote": "No, I cannot diagnose medical injuries." }, { "kind": "press release", "citation": "Musk, E. (2025). Grok can diagnose medical injuries. Post on X, @elonmusk, 11 January 2025 (22:12 UTC), status 1878203372513136854; Mint reports it was posted in reply to a post about the AJ Kay account.", "title": "Grok can diagnose medical injuries", "url": "https://x.com/elonmusk/status/1878203372513136854", "date": "2025-01-11", "written_by": "makers", "quote": "Grok can diagnose medical injuries" }, { "kind": "news report", "citation": "TOI Lifestyle Desk (2025). Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman. The Times of India, 15 January 2025. Quotes Musk's 3 January 2025 post inviting image uploads.", "title": "Elon Musk's Grok AI diagnoses fracture missed by doctors, claims woman", "url": "https://timesofindia.indiatimes.com/life-style/health-fitness/health-news/elon-musks-grok-ai-diagnoses-fracture-missed-by-doctors-claims-woman/articleshow/117255256.cms", "date": "2025-01-15", "written_by": "independent", "quote": "You can upload any image to Grok for analysis, from medical tests to video games! Just tap the + button or paste the image into the entry bar" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "By her mother's X post of 11 January 2025, Grok flagged a displaced wrist fracture urgent care missed; an orthopaedist confirmed and cast it.", "account": "On 11 January 2025 AJ Kay (@AJKayWriter, United States) posted about a multi-vehicle freeway crash the weekend before. An urgent-care doctor and radiologist had read her teenage daughter's wrist X-rays as free of breaks. They sent her home with an ace wrap and ibuprofen. With the hand cold and tingling and the thumb immobile, she uploaded the printed X-ray to Grok on X. It said there was “a clear fracture line in the distal radius”, not a growth plate, and called it “quite obvious”. After a PCP referral, a wrist specialist took new X-rays next day. The specialist diagnosed a distal radial head fracture with dorsal displacement and cast it, saying untreated displacement would likely have needed surgery." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "Grok analyzed an uploaded X-ray and identified a possible fracture." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "Grok 2, according to the poster." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Grok 2, according to the poster.", "editor_note": "The poster referred to Elon Musk’s statement about Grok 2 reading medical images. That identifies a plausible model, but does not establish the model used in the posted conversation." } }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Grok 2 (the poster cites Musk's statement that 'Grok2 could read medical images'; not confirmed by xAI)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Grok chatbot (xAI) on X, image analysis of an uploaded wrist X-ray" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "xAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Grok may have read a “clear fracture line in the distal radius” on a teenager's wrist X-ray that urgent care had cleared; a wrist specialist confirmed the displaced fracture and cast it (January 2025)", "headline": "Grok spots a displaced wrist fracture that urgent care missed" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "db416bb5f18790c7f13e09932ddb9f93d8d0c7e42da0d89ef7177a1bf402d013" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 11 January 2025 AJ Kay (@AJKayWriter, United States) posted about a multi-vehicle freeway crash the weekend before. An urgent-care doctor and radiologist had read her teenage daughter's wrist X-rays as free of breaks. They sent her home with an ace wrap and ibuprofen. With the hand cold and tingling and the thumb immobile, she uploaded the printed X-ray to Grok on X. It said there was “a clear fracture line in the distal radius”, not a growth plate, and called it “quite obvious”. After a PCP referral, a wrist specialist took new X-rays next day. The specialist diagnosed a distal radial head fracture with dorsal displacement and cast it, saying untreated displacement would likely have needed surgery.", "replication": { "produced_by": [ "A printed urgent-care wrist X-ray that the parent could photograph and upload", "Grok on X with image input, which Musk was publicly promoting for medical images in January 2025", "A parent who distrusted the first reading because of worsening signs (cold, tingling hand; immobile thumb; a wrist that did not look right). She had already asked for the films for the PCP", "Access within days to a PCP referral and a wrist specialist who re-imaged and examined the wrist" ], "must_hold": [ "Grok's reading was correct for this image on the mother's account only. Asked by a physician the next day, it said it cannot diagnose injuries. So its output is not reliable across users or images", "A clinician re-examined and re-imaged the wrist. Grok's output was never used as the diagnosis or the basis of treatment", "The only sources are the mother's post and news reports built from it. No clinic, clinician or record is public, and the surgery-avoidance statement is second-hand" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0081", "title": "CGU's ALICE robot flags overpricing in three 2024 Rio de Janeiro federal hospital tenders; one suspended, one revoked, one re-estimated", "summary": "CGU ALICE alerts: three 2024 federal hospital tenders in Rio de Janeiro state suspended, revoked or re-estimated; R$19.4m overpricing risk flagged (sum of three confirmed risks)", "date_observed": "2025-01-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 14 January 2025 the Controladoria-Geral da União (CGU) reported on ALICE (Analisador de Licitações, Contratos e Editais). ALICE, its in-house tool, reads procurement documents with artificial-intelligence techniques and issues risk alerts. It had flagged three 2024 tenders of federal hospitals in Rio de Janeiro state. At the Hospital Federal de Ipanema, tender 90016/2024 for laminated gowns (estimated R$16,726,635.12) was suspended after auditors confirmed an overpricing risk of R$10,925,029.92. Tender 90017/2024 for nursing supplies (estimated R$15,450,714.80) had an overpricing risk of R$5,994,645.60. It was re-estimated at R$12,386,939.96, a saving of R$3,063,774.84. At the Hospital Federal dos Servidores do Estado, tender 90002/2024 (estimated R$26,578,591.02) was revoked after a confirmed risk of R$2,475,054.36. The release gives no total. The three confirmed risks sum to R$19,394,729.88, the R$19.4 million of the headline and metric. The release gives no dates for the suspension and revocation.", "category": "harm prevented", "unexpected": false, "purpose": "Continuous automated audit of federal procurement notices to detect risks such as inflated price estimates before contracts are awarded", "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU text-mining and AI alert tool", "model_version": null, "developer": "Controladoria-Geral da União (CGU), in-house", "deployer": "Controladoria-Geral da União (CGU)", "location": "Rio de Janeiro (state), Brazil", "domain": "Public administration: government audit and procurement control", "segment": "Federal internal control (anti-corruption and waste prevention)", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No identifiable individual beneficiary is named; the beneficiaries are public bodies and, indirectly, taxpayers." }, { "group": "organizational", "depth": 2, "reason": "Material to the two hospitals and the federal budget. One tender saw a documented R$3,063,774.84 reduction. One suspension and one revocation removed R$13.4 million of confirmed overpricing risk." }, { "group": "societal", "depth": 1, "reason": "Small at national scale; three tenders among 118,069 processes analyzed in 2024." } ], "ai_role": { "status": "assessed", "statement": "The CGU release states that each tender “teve alerta do Robô ALICE” and that auditors then confirmed the overpricing risk. The suspension, revocation and re-estimation are described as results of that audit action. Human auditors and hospital managers made the decisions. ALICE's role was detection and triage. Developer and deployer are the same public body, so this is the body documenting its own tool. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." }, "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "a licitação 90016/2024 - Relatório 1686291 -– teve alerta do Robô ALICE e foi analisada pelos auditores que indicaram risco de sobrepreço de R$ 10.925.029,92" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Same release, Hospital Federal dos Servidores do Estado section.", "title": "Atuação do Robô ALICE segue auxiliando auditores (HFSE section)", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "Como resultado da atuação, a licitação foi revogada." }, { "kind": "news report", "citation": "Grossmann, L. O. (2025). Robô da CGU rastreia R$ 25 bilhões em licitações. Convergência Digital, 15 Jan 2025.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "Das auditorias concluídas, foram economizados R$ 257,25 milhões" }, { "kind": "news report", "citation": "R7 Planalto (2025). ALICE: robô da CGU previne erros e desperdícios de licitações públicas, 28 Jan 2025, republished by Licitação.net.", "title": "ALICE: robô da CGU previne erros e desperdícios de licitações públicas", "url": "https://www.licitacao.net/noticias/alice:-robo-da-cgu-previne-erros-e-desperdicios-de-licitacoes-publicas", "date": "2025-01-28", "written_by": "independent", "quote": "Nos primeiros relatórios de auditoria de 2024, ALICE identificou riscos de sobrepreço em três licitações de Hospitais Federais no Rio de Janeiro, relacionadas à compra de equipamentos e insumos." }, { "kind": "news report", "citation": "Observatório da Nova Lei de Licitações (2025). Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações, 21 Jan 2025 (with information from CGU).", "title": "Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações", "url": "https://www.novaleilicitacao.com.br/2025/01/21/atuacao-do-robo-alice-auxilia-cgu-a-rastrear-r-25-bilhoes-em-licitacoes/", "date": "2025-01-21", "written_by": "independent", "quote": "uma licitação para a compra de aventais laminados, inicialmente estimada em R$ 16,7 milhões, foi suspensa após a detecção de um possível sobrepreço de R$ 10,9 milhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal. doi:10.36428/revistadacgu.v14i26.530", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" } ], "replication": { "produced_by": [ "ALICE audit trails that flag price surveys with abnormally high estimates in documents published on Compras.gov.br and bank procurement systems", "CGU preventive audit teams that examine flagged tenders before the auction concludes and recommend corrections", "Managers' response to audit recommendations (suspension, revocation or new price estimate)" ], "must_hold": [ "Procurement planning documents and notices must be machine-readable in the monitored systems", "Audit capacity must exist to act on alerts before award", "Reference prices must be available to confirm overpricing" ], "echoes": [ { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender (Pregão 15/2021), CGU audit with ALICE support, reported 4 October 2023", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, { "date": "2024-01-01", "setting": "Federal road-works engineering tender: about R$100 million cut from the reference value after an ALICE alert (CGU, 30 December 2024); the release gives no date for this tender, so the year is inferred from the 2024 year-end release", "model_version": null, "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG state-level use of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections to notices worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "model_version": null, "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "738", "title": "Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud", "url": "https://incidentdatabase.ai/cite/738", "severity": null, "group": "organizational", "basis": "Government fraud-risk flagging algorithm, like ALICE's tender alerts, sent 200,000 housing-benefit claims to investigation, two-thirds legitimate, wasting public funds and stressing claimants." }, "headline": "CGU's ALICE flags R$19.4m overpricing risk in three Rio tenders", "metric": "a saving of R$3,063,774.84", "comparator": { "against": "the hospital's original price estimate for tender 90017/2024", "before": "valor estimado em R$ 15.450.714,80", "after": "R$ 12.386.939,96", "basis": "measured", "quote": "Como resultado da atuação, os gestores procederam nova estimativa de preços, reduzindo o valor total estimado da compra para R$ 12.386.939,96, o que representou uma economia de mais de R$ 3 milhões (R$ 3.063.774,84).", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, "later": { "status": "unknown", "date": null, "note": "The two later press items (21 and 28 January 2025) restate the release; no later development was found,.", "quote": null, "url": null }, "value": { "amount": "R$ 3.063.774,84", "what": "reduction of the estimated value of tender 90017/2024 after the re-estimate (the release gives no total for the three tenders)", "who": "Hospital Federal de Ipanema, federal budget", "estimate": false, "quote": "Como resultado da atuação, os gestores procederam nova estimativa de preços, reduzindo o valor total estimado da compra para R$ 12.386.939,96, o que representou uma economia de mais de R$ 3 milhões (R$ 3.063.774,84).", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" }, "developer_country": "Brazil", "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 738 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/738", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Extended the Licitação.net quote to the end of its sentence; added the R$5,994,645.60 risk on tender 90017/2024 and stated that the R$19.4 million headline figure is the registry's sum of the three confirmed risks (R$19,394,729.88) because the CGU gives no total; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the overpriced tenders were in progress and the CGU records their suspension, revocation and re-estimate as results of the alert-driven audit; set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit; noted that the road-works echo year is inferred from the 2024 year-end release and that December 2022 is when TCE-MG published its audit result; and located the hospitals in the state of Rio de Janeiro as the release does.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/; https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0081", "catalog_version": "1.0.0", "source_fingerprint": "d6b958633d54ed56d5548b8102bad819ea3cf9c0ce6721455405dbd8fe2e4ff7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0081-source-0001", "AIBD-0081-source-0002", "AIBD-0081-source-0003", "AIBD-0081-source-0004", "AIBD-0081-source-0005", "AIBD-0081-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0081-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Controladoria-Geral da União (CGU), in-house", "deployer": "Controladoria-Geral da União (CGU)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The CGU release states that each tender “teve alerta do Robô ALICE” and that auditors then confirmed the overpricing risk. The suspension, revocation and re-estimation are described as results of that audit action. Human auditors and hospital managers made the decisions. ALICE's role was detection and triage. Developer and deployer are the same public body, so this is the body documenting its own tool. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The CGU release states that each tender “teve alerta do Robô ALICE” and that auditors then confirmed the overpricing risk. The suspension, revocation and re-estimation are described as results of that audit action. Human auditors and hospital managers made the decisions. ALICE's role was detection and triage. Developer and deployer are the same public body, so this is the body documenting its own tool. The CGU page is on record as an archived copy, because the live page was restricted during Brazil's 2026 electoral period." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary is named; the beneficiaries are public bodies and, indirectly, taxpayers." }, { "group": "organizational", "depth": 2, "reason": "Material to the two hospitals and the federal budget. One tender saw a documented R$3,063,774.84 reduction. One suspension and one revocation removed R$13.4 million of confirmed overpricing risk." }, { "group": "societal", "depth": 1, "reason": "Small at national scale; three tenders among 118,069 processes analyzed in 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports, the makers' report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary is named; the beneficiaries are public bodies and, indirectly, taxpayers." }, { "group": "organizational", "depth": 2, "reason": "Material to the two hospitals and the federal budget. One tender saw a documented R$3,063,774.84 reduction. One suspension and one revocation removed R$13.4 million of confirmed overpricing risk." }, { "group": "societal", "depth": 1, "reason": "Small at national scale; three tenders among 118,069 processes analyzed in 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary is named; the beneficiaries are public bodies and, indirectly, taxpayers." }, { "group": "organizational", "depth": 2, "reason": "Material to the two hospitals and the federal budget. One tender saw a documented R$3,063,774.84 reduction. One suspension and one revocation removed R$13.4 million of confirmed overpricing risk." }, { "group": "societal", "depth": 1, "reason": "Small at national scale; three tenders among 118,069 processes analyzed in 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Government fraud-risk flagging algorithm, like ALICE's tender alerts, sent 200,000 housing-benefit claims to investigation, two-thirds legitimate, wasting public funds and stressing claimants.", "links": [ { "database": "AI Incident Database", "identifier": "738", "title": "Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud", "url": "https://incidentdatabase.ai/cite/738", "group": "organizational", "basis": "Government fraud-risk flagging algorithm, like ALICE's tender alerts, sent 200,000 housing-benefit claims to investigation, two-thirds legitimate, wasting public funds and stressing claimants.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 3.063.774,84", "what": "reduction of the estimated value of tender 90017/2024 after the re-estimate (the release gives no total for the three tenders)", "who": "Hospital Federal de Ipanema, federal budget", "estimate": false, "quote": "Como resultado da atuação, os gestores procederam nova estimativa de preços, reduzindo o valor total estimado da compra para R$ 12.386.939,96, o que representou uma economia de mais de R$ 3 milhões (R$ 3.063.774,84).", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 3.063.774,84", "what": "reduction of the estimated value of tender 90017/2024 after the re-estimate (the release gives no total for the three tenders)", "who": "Hospital Federal de Ipanema, federal budget", "estimate": false, "quote": "Como resultado da atuação, os gestores procederam nova estimativa de preços, reduzindo o valor total estimado da compra para R$ 12.386.939,96, o que representou uma economia de mais de R$ 3 milhões (R$ 3.063.774,84).", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "R$ 3.063.774,84", "what": "reduction of the estimated value of tender 90017/2024 after the re-estimate (the release gives no total for the three tenders)", "who": "Hospital Federal de Ipanema, federal budget", "estimate": false, "quote": "Como resultado da atuação, os gestores procederam nova estimativa de preços, reduzindo o valor total estimado da compra para R$ 12.386.939,96, o que representou uma economia de mais de R$ 3 milhões (R$ 3.063.774,84).", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "a saving of R$3,063,774.84", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "738", "title": "Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud", "url": "https://incidentdatabase.ai/cite/738", "group": "organizational", "basis": "Government fraud-risk flagging algorithm, like ALICE's tender alerts, sent 200,000 housing-benefit claims to investigation, two-thirds legitimate, wasting public funds and stressing claimants." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The two later press items (21 and 28 January 2025) restate the release; no later development was found,." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0081" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 January 2025 the Controladoria-Geral da União (CGU) reported on ALICE (Analisador de Licitações, Contratos e Editais). ALICE, its in-house tool, reads procurement documents with artificial-intelligence techniques and issues risk alerts. It had flagged three 2024 tenders of federal hospitals in Rio de Janeiro state. At the Hospital Federal de Ipanema, tender 90016/2024 for laminated gowns (estimated R$16,726,635.12) was suspended after auditors confirmed an overpricing risk of R$10,925,029.92. Tender 90017/2024 for nursing supplies (estimated R$15,450,714.80) had an overpricing risk of R$5,994,645.60. It was re-estimated at R$12,386,939.96, a saving of R$3,063,774.84. At the Hospital Federal dos Servidores do Estado, tender 90002/2024 (estimated R$26,578,591.02) was revoked after a confirmed risk of R$2,475,054.36. The release gives no total. The three confirmed risks sum to R$19,394,729.88, the R$19.4 million of the headline and metric. The release gives no dates for the suspension and revocation.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No identifiable individual beneficiary is named; the beneficiaries are public bodies and, indirectly, taxpayers." }, { "group": "organizational", "depth": 2, "reason": "Material to the two hospitals and the federal budget. One tender saw a documented R$3,063,774.84 reduction. One suspension and one revocation removed R$13.4 million of confirmed overpricing risk." }, { "group": "societal", "depth": 1, "reason": "Small at national scale; three tenders among 118,069 processes analyzed in 2024." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Continuous automated audit of federal procurement notices to detect risks such as inflated price estimates before contracts are awarded" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Rio de Janeiro (state), Brazil", "developer_country": "Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Continuous automated audit of federal procurement notices to detect risks such as inflated price estimates before contracts are awarded" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-01-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 738 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/738", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Extended the Licitação.net quote to the end of its sentence; added the R$5,994,645.60 risk on tender 90017/2024 and stated that the R$19.4 million headline figure is the registry's sum of the three confirmed risks (R$19,394,729.88) because the CGU gives no total; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the overpriced tenders were in progress and the CGU records their suspension, revocation and re-estimate as results of the alert-driven audit; set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit; noted that the road-works echo year is inferred from the 2024 year-end release and that December 2022 is when TCE-MG published its audit result; and located the hospitals in the state of Rio de Janeiro as the release does.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/; https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALICE audit trails that flag price surveys with abnormally high estimates in documents published on Compras.gov.br and bank procurement systems", "CGU preventive audit teams that examine flagged tenders before the auction concludes and recommend corrections", "Managers' response to audit recommendations (suspension, revocation or new price estimate)" ], "must_hold": [ "Procurement planning documents and notices must be machine-readable in the monitored systems", "Audit capacity must exist to act on alerts before award", "Reference prices must be available to confirm overpricing" ], "echoes": [ { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender (Pregão 15/2021), CGU audit with ALICE support, reported 4 October 2023", "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, { "date": "2024-01-01", "setting": "Federal road-works engineering tender: about R$100 million cut from the reference value after an ALICE alert (CGU, 30 December 2024); the release gives no date for this tender, so the year is inferred from the 2024 year-end release", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG state-level use of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections to notices worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "ALICE audit trails that flag price surveys with abnormally high estimates in documents published on Compras.gov.br and bank procurement systems", "CGU preventive audit teams that examine flagged tenders before the auction concludes and recommend corrections", "Managers' response to audit recommendations (suspension, revocation or new price estimate)" ], "must_hold": [ "Procurement planning documents and notices must be machine-readable in the monitored systems", "Audit capacity must exist to act on alerts before award", "Reference prices must be available to confirm overpricing" ], "echoes": [ { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender (Pregão 15/2021), CGU audit with ALICE support, reported 4 October 2023", "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, { "date": "2024-01-01", "setting": "Federal road-works engineering tender: about R$100 million cut from the reference value after an ALICE alert (CGU, 30 December 2024); the release gives no date for this tender, so the year is inferred from the 2024 year-end release", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG state-level use of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections to notices worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 738 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/738", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Extended the Licitação.net quote to the end of its sentence; added the R$5,994,645.60 risk on tender 90017/2024 and stated that the R$19.4 million headline figure is the registry's sum of the three confirmed risks (R$19,394,729.88) because the CGU gives no total; dated the Revista da CGU article 20 December 2022 and re-described it as a practitioner report (relato) in the CGU's own journal; moved the record to “harm prevented” because the overpriced tenders were in progress and the CGU records their suspension, revocation and re-estimate as results of the alert-driven audit; set the benefit type to Trustible's “Reduced Risk” from the published framework (entry quoted in the taxonomy note; data/taxonomy.json must carry it) so that the type names the benefit instead of a closest fit; noted that the road-works echo year is inferred from the 2024 year-end release and that December 2022 is when TCE-MG published its audit result; and located the hospitals in the state of Rio de Janeiro as the release does.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Benefit type kept within Trustible's six types (Improved Organizational Efficiency); the sweep's proposed “Reduced Risk” is not in the taxonomy.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/; https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o; https://pt.wikipedia.org/wiki/Controladoria-Geral_da_Uni%C3%A3o", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public administration: government audit and procurement control", "segment": "Federal internal control (anti-corruption and waste prevention)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "a licitação 90016/2024 - Relatório 1686291 -– teve alerta do Robô ALICE e foi analisada pelos auditores que indicaram risco de sobrepreço de R$ 10.925.029,92" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Same release, Hospital Federal dos Servidores do Estado section.", "title": "Atuação do Robô ALICE segue auxiliando auditores (HFSE section)", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "Como resultado da atuação, a licitação foi revogada." }, { "kind": "news report", "citation": "Grossmann, L. O. (2025). Robô da CGU rastreia R$ 25 bilhões em licitações. Convergência Digital, 15 Jan 2025.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "Das auditorias concluídas, foram economizados R$ 257,25 milhões" }, { "kind": "news report", "citation": "R7 Planalto (2025). ALICE: robô da CGU previne erros e desperdícios de licitações públicas, 28 Jan 2025, republished by Licitação.net.", "title": "ALICE: robô da CGU previne erros e desperdícios de licitações públicas", "url": "https://www.licitacao.net/noticias/alice:-robo-da-cgu-previne-erros-e-desperdicios-de-licitacoes-publicas", "date": "2025-01-28", "written_by": "independent", "quote": "Nos primeiros relatórios de auditoria de 2024, ALICE identificou riscos de sobrepreço em três licitações de Hospitais Federais no Rio de Janeiro, relacionadas à compra de equipamentos e insumos." }, { "kind": "news report", "citation": "Observatório da Nova Lei de Licitações (2025). Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações, 21 Jan 2025 (with information from CGU).", "title": "Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações", "url": "https://www.novaleilicitacao.com.br/2025/01/21/atuacao-do-robo-alice-auxilia-cgu-a-rastrear-r-25-bilhoes-em-licitacoes/", "date": "2025-01-21", "written_by": "independent", "quote": "uma licitação para a compra de aventais laminados, inicialmente estimada em R$ 16,7 milhões, foi suspensa após a detecção de um possível sobrepreço de R$ 10,9 milhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal. doi:10.36428/revistadacgu.v14i26.530", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0081-source-0001", "AIBD-0081-source-0002", "AIBD-0081-source-0003", "AIBD-0081-source-0004", "AIBD-0081-source-0005", "AIBD-0081-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos, que ajudam a evitar desperdícios e irregularidades. gov.br/cgu, 14 Jan 2025.", "title": "Atuação do Robô ALICE segue auxiliando auditores a realizar trabalhos preventivos", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "a licitação 90016/2024 - Relatório 1686291 -– teve alerta do Robô ALICE e foi analisada pelos auditores que indicaram risco de sobrepreço de R$ 10.925.029,92" }, { "kind": "press release", "citation": "Controladoria-Geral da União (2025). Same release, Hospital Federal dos Servidores do Estado section.", "title": "Atuação do Robô ALICE segue auxiliando auditores (HFSE section)", "url": "https://web.archive.org/web/20250114172015id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/atuacao-do-robo-alice-segue-auxiliando-auditores-a-realizar-trabalhos-preventivos-que-ajudam-a-evitar-desperdicios-e-irregularidades/", "date": "2025-01-14", "written_by": "makers", "quote": "Como resultado da atuação, a licitação foi revogada." }, { "kind": "news report", "citation": "Grossmann, L. O. (2025). Robô da CGU rastreia R$ 25 bilhões em licitações. Convergência Digital, 15 Jan 2025.", "title": "Robô da CGU rastreia R$ 25 bilhões em licitações", "url": "https://convergenciadigital.com.br/governo/robo-da-cgu-rastreia-r-25-bilhoes-em-licitacoes/", "date": "2025-01-15", "written_by": "independent", "quote": "Das auditorias concluídas, foram economizados R$ 257,25 milhões" }, { "kind": "news report", "citation": "R7 Planalto (2025). ALICE: robô da CGU previne erros e desperdícios de licitações públicas, 28 Jan 2025, republished by Licitação.net.", "title": "ALICE: robô da CGU previne erros e desperdícios de licitações públicas", "url": "https://www.licitacao.net/noticias/alice:-robo-da-cgu-previne-erros-e-desperdicios-de-licitacoes-publicas", "date": "2025-01-28", "written_by": "independent", "quote": "Nos primeiros relatórios de auditoria de 2024, ALICE identificou riscos de sobrepreço em três licitações de Hospitais Federais no Rio de Janeiro, relacionadas à compra de equipamentos e insumos." }, { "kind": "news report", "citation": "Observatório da Nova Lei de Licitações (2025). Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações, 21 Jan 2025 (with information from CGU).", "title": "Atuação do robô ALICE auxilia CGU a rastrear R$ 25 bilhões em licitações", "url": "https://www.novaleilicitacao.com.br/2025/01/21/atuacao-do-robo-alice-auxilia-cgu-a-rastrear-r-25-bilhoes-em-licitacoes/", "date": "2025-01-21", "written_by": "independent", "quote": "uma licitação para a compra de aventais laminados, inicialmente estimada em R$ 16,7 milhões, foi suspensa após a detecção de um possível sobrepreço de R$ 10,9 milhões" }, { "kind": "report", "citation": "Oliveira, T. C., Rocha, A. L. M. & Rezende, M. S. (2022). Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua de compras públicas governamentais com uso de inteligência artificial. Revista da CGU 14(26), jul-dez/2022, published 20 Dec 2022; a practitioner report (relato) in the CGU's own journal. doi:10.36428/revistadacgu.v14i26.530", "title": "Alice: Desafios, resultados e perspectivas da ferramenta de auditoria contínua", "url": "https://revista.cgu.gov.br/Revista_da_CGU/article/view/530", "date": "2022-12-20", "written_by": "makers", "quote": "Já são mais de R$ 9,7 bilhões em compras suspensas a partir de suas indicações, apenas pela CGU" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "CGU ALICE alerts: three 2024 federal hospital tenders in Rio de Janeiro state suspended, revoked or re-estimated; R$19.4m overpricing risk flagged (sum of three confirmed risks)", "account": "On 14 January 2025 the Controladoria-Geral da União (CGU) reported on ALICE (Analisador de Licitações, Contratos e Editais). ALICE, its in-house tool, reads procurement documents with artificial-intelligence techniques and issues risk alerts. It had flagged three 2024 tenders of federal hospitals in Rio de Janeiro state. At the Hospital Federal de Ipanema, tender 90016/2024 for laminated gowns (estimated R$16,726,635.12) was suspended after auditors confirmed an overpricing risk of R$10,925,029.92. Tender 90017/2024 for nursing supplies (estimated R$15,450,714.80) had an overpricing risk of R$5,994,645.60. It was re-estimated at R$12,386,939.96, a saving of R$3,063,774.84. At the Hospital Federal dos Servidores do Estado, tender 90002/2024 (estimated R$26,578,591.02) was revoked after a confirmed risk of R$2,475,054.36. The release gives no total. The three confirmed risks sum to R$19,394,729.88, the R$19.4 million of the headline and metric. The release gives no dates for the suspension and revocation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ALICE (Analisador de Licitações, Contratos e Editais), CGU text-mining and AI alert tool" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Controladoria-Geral da União (CGU), in-house" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CGU's ALICE robot flags overpricing in three 2024 Rio de Janeiro federal hospital tenders; one suspended, one revoked, one re-estimated", "headline": "CGU's ALICE flags R$19.4m overpricing risk in three Rio tenders" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d6b958633d54ed56d5548b8102bad819ea3cf9c0ce6721455405dbd8fe2e4ff7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 January 2025 the Controladoria-Geral da União (CGU) reported on ALICE (Analisador de Licitações, Contratos e Editais). ALICE, its in-house tool, reads procurement documents with artificial-intelligence techniques and issues risk alerts. It had flagged three 2024 tenders of federal hospitals in Rio de Janeiro state. At the Hospital Federal de Ipanema, tender 90016/2024 for laminated gowns (estimated R$16,726,635.12) was suspended after auditors confirmed an overpricing risk of R$10,925,029.92. Tender 90017/2024 for nursing supplies (estimated R$15,450,714.80) had an overpricing risk of R$5,994,645.60. It was re-estimated at R$12,386,939.96, a saving of R$3,063,774.84. At the Hospital Federal dos Servidores do Estado, tender 90002/2024 (estimated R$26,578,591.02) was revoked after a confirmed risk of R$2,475,054.36. The release gives no total. The three confirmed risks sum to R$19,394,729.88, the R$19.4 million of the headline and metric. The release gives no dates for the suspension and revocation.", "replication": { "produced_by": [ "ALICE audit trails that flag price surveys with abnormally high estimates in documents published on Compras.gov.br and bank procurement systems", "CGU preventive audit teams that examine flagged tenders before the auction concludes and recommend corrections", "Managers' response to audit recommendations (suspension, revocation or new price estimate)" ], "must_hold": [ "Procurement planning documents and notices must be machine-readable in the monitored systems", "Audit capacity must exist to act on alerts before award", "Reference prices must be available to confirm overpricing" ], "echoes": [ { "date": "2021-07-21", "setting": "Hospital Federal de Ipanema glove tender (Pregão 15/2021), CGU audit with ALICE support, reported 4 October 2023", "outcome": "recurred", "source": "https://web.archive.org/web/20260412063523id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2023/10/cgu-atua-em-editais-de-licitacao-em-hospitais-federais-no-rio-de-janeiro-e-evita-desperdicio-de-cerca-de-r-8-33-mi" }, { "date": "2024-01-01", "setting": "Federal road-works engineering tender: about R$100 million cut from the reference value after an ALICE alert (CGU, 30 December 2024); the release gives no date for this tender, so the year is inferred from the 2024 year-end release", "outcome": "recurred", "source": "https://web.archive.org/web/20260207114437id_/https://www.gov.br/cgu/pt-br/assuntos/noticias/2024/12/orgaos-federais-economizaram-em-2024-257-milhoes-de-reais-com-apoio-do-robo-alice-da-controladoria-geral-da-uniao" }, { "date": "2022-12-01", "setting": "TCE-MG state-level use of Alice: in December 2022 TCE-MG published the result of an audit covering 2,297 state and municipal tenders in August 2022 alone, with corrections to notices worth R$91,723,011.31 (Atricon, 28 June 2023; publication month only)", "outcome": "recurred", "source": "https://atricon.org.br/tce-mg-apresenta-economia-feita-com-ajuda-de-robo-alice/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0278", "title": "MatterGen generates TaCr2O6; SIAT synthesizes a disordered version with bulk modulus 169 GPa against a 200 GPa target", "summary": "Microsoft's diffusion model generated a structure conditioned on bulk modulus 200 GPa; SIAT (Shenzhen) synthesized it and measured 169 GPa, with Ta/Cr compositional disorder. Vendor co-authored proof.", "date_observed": "2025-01-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Zeni et al. (Nature, 16 January 2025) are Microsoft Research AI for Science with co-authors including the Shenzhen Institutes of Advanced Technology. They present MatterGen, a diffusion model over 3D crystal geometry trained on about 608,000 stable materials. Its outputs are reported as more than twice as likely to be new and stable as those of earlier generative models. As a proof of concept they synthesized one generated structure and measured its property “within 20% of our target”. Microsoft's blog identifies the compound as TaCr2O6, generated for a bulk modulus of 200 GPa. Prof Li Wenjie's SIAT group measured 169 GPa. The structure matched MatterGen's proposal “with the caveat of compositional disorder between Ta and Cr”. The synthesis is vendor co-authored, and a Nature news critique of 1 October 2025 was paywalled beyond its lede. 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external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Hertfordshire and Robotiz3d trialed the ARRES Prevent robot, which uses AI to detect road defects and fill cracks. The pilot reportedly repaired a small number of cracks. The project reports detection accuracy increasing from 66% to 100% in testing. Long-term repair performance, pothole prevention, cost savings, and population safety effects remain unestablished.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The public-road pilot actually repaired a small number of cracks, demonstrating a new operational capability." }, { "group": "societal", "reason": "Fewer potholes, injuries, and dangerous maintenance exposures are intended. No achieved safety benefit is described." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "mixed" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify road defects and repair cracks before they develop into larger maintenance problems." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify road defects and repair cracks before they develop into larger maintenance problems." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-01-28", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/hertfordshire-county-council-ai-road-maintenance-robot", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The development partnership used Hertfordshire road data and highway-engineering feedback.", "The reported pilot involved a prototype on a public road, with further tests and long-term repair review planned." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/hertfordshire-county-council-ai-road-maintenance-robot", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Transport infrastructure maintenance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. 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Long-term repair quality, safety, and cost benefits remain unmeasured.", "account": "Hertfordshire and Robotiz3d trialed the ARRES Prevent robot, which uses AI to detect road defects and fill cracks. The pilot reportedly repaired a small number of cracks. The project reports detection accuracy increasing from 66% to 100% in testing. Long-term repair performance, pothole prevention, cost savings, and population safety effects remain unestablished." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Robotiz3d ARRES Eye and ARRES Prevent road-maintenance robot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Robotiz3d, developed in collaboration with the University of Liverpool and Hertfordshire County Council" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Hertfordshire County Council: AI road maintenance robot", "headline": "Hertfordshire trials an AI robot that repairs road cracks" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "37025be8ffdec74f23b50f9f5ac4c7c6075d99d68db6c93dfd70afbe2fc766a2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Hertfordshire and Robotiz3d trialed the ARRES Prevent robot, which uses AI to detect road defects and fill cracks. The pilot reportedly repaired a small number of cracks. The project reports detection accuracy increasing from 66% to 100% in testing. Long-term repair performance, pothole prevention, cost savings, and population safety effects remain unestablished.", "replication": { "produced_by": [ "The development partnership used Hertfordshire road data and highway-engineering feedback.", "The reported pilot involved a prototype on a public road, with further tests and long-term repair review planned." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0551", "title": "Kingston Council: Using AI in Adult Social Care administration", "summary": "Kingston reports that Magic Notes cuts documentation time by 50–60%, with supervision write-ups falling from 40 minutes to under 10.", "date_observed": "2025-01-28", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-011", "account": "Kingston piloted Beam Magic Notes to transcribe and summarize adult-social-care conversations, assessments, and supervision. The council reports 50–60% less time completing notes and assessments, and supervision write-ups falling from 40 minutes to under 10 minutes. The source reports limitations for people with low verbal skills or mental capacity and with poor audio quality.", "category": "general benefit", "unexpected": false, "purpose": "Reduce social-care documentation work by transcribing and summarizing conversations into usable notes and assessments.", "system": "Beam Magic Notes", "model_version": null, "developer": "Beam", "deployer": "Kingston Council", "location": "United Kingdom", "domain": "Adult social-care administration", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Reported reductions in case-note, assessment, and supervision writing are task-time savings." }, { "group": "personal", "depth": 1, "reason": "Workers report less documentation effort and time. Improvements in service users’ health or care are unmeasured." } ], "ai_role": { "status": "assessed", "statement": "Magic Notes transcribes and summarizes care and supervision conversations. Staff review, amend, and supplement outputs. The council attributes documentation savings to this assisted workflow, without establishing improved service-user outcomes." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Kingston Council: Using AI in Adult Social Care administration", "url": "https://www.local.gov.uk/case-studies/kingston-council-using-ai-adult-social-care-administration", "date": "2025-01-28", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The pilot began with a small social-worker group and expanded, using templates adapted with council feedback.", "The tool supports mobile recording and produces material for the existing case-management workflow." ], "must_hold": [ "Practitioners are expected to obtain participants’ consent for recording.", "The source reports that poor audio and limited verbal detail can reduce transcript quality, and staff retain responsibility for editing outputs." ], "echoes": [] }, "paired_incident": null, "headline": "Kingston reports shorter social-care documentation with AI", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/kingston-council-using-ai-adult-social-care-administration", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0551", "catalog_version": "1.0.0", "source_fingerprint": "8b19ff1ad2dd766f9f8138875e58fa20a6d59d5688db2d7dcca285bd68593719", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0551-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Beam", "deployer": "Kingston Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Magic Notes transcribes and summarizes care and supervision conversations. 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The council reports 50–60% less time completing notes and assessments, and supervision write-ups falling from 40 minutes to under 10 minutes. The source reports limitations for people with low verbal skills or mental capacity and with poor audio quality." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Beam Magic Notes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Beam" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Kingston Council: Using AI in Adult Social Care administration", "headline": "Kingston reports shorter social-care documentation with AI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8b19ff1ad2dd766f9f8138875e58fa20a6d59d5688db2d7dcca285bd68593719" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Kingston piloted Beam Magic Notes to transcribe and summarize adult-social-care conversations, assessments, and supervision. The council reports 50–60% less time completing notes and assessments, and supervision write-ups falling from 40 minutes to under 10 minutes. 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Redaction reportedly takes 90 seconds instead of 10 minutes with 95% success. Mail indexing reportedly handles 55% of emails, saving 5,500 staff hours and £100,000 annually. The former £350,000 translation budget is not a demonstrated saving. 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The source also reports translation limitations and guardrail difficulties.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council reports time and cost savings from redaction and mailbox indexing. 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Lasting changes in well-being are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Automate repetitive administration, document redaction, simple translation, and email routing." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Automate repetitive administration, document redaction, simple translation, and email routing." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-02-03", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/birmingham-city-council-foundry", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Council officers and developers co-designed tools around four back-office functions in iterative development cycles.", "The reported redaction tool covers three document types, and the mailbox tool handles a share of incoming emails." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/birmingham-city-council-foundry", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Local government administration" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Birmingham City Council: the Foundry", "url": "https://www.local.gov.uk/case-studies/birmingham-city-council-foundry", "date": "2025-02-03", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0543-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Birmingham City Council: the Foundry", "url": "https://www.local.gov.uk/case-studies/birmingham-city-council-foundry", "date": "2025-02-03", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Birmingham reports that AI redacts documents in 90 seconds instead of 10 minutes and indexes 55% of emails, saving staff time and costs.", "account": "Birmingham reports that its Foundry tools automate redaction, mailbox indexing, administrative work, and simple translation. Redaction reportedly takes 90 seconds instead of 10 minutes with 95% success. Mail indexing reportedly handles 55% of emails, saving 5,500 staff hours and £100,000 annually. The former £350,000 translation budget is not a demonstrated saving. The source also reports translation limitations and guardrail difficulties." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Birmingham Foundry tools using Microsoft Copilot and UiPath Document Understanding and mailbox indexing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Birmingham City Council, Microsoft, and UiPath" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Birmingham City Council: the Foundry", "headline": "Birmingham reports faster redaction and automated email indexing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9a498f95eaa29cbd95f612af537503a8c2463d5ee60145e70bb455fe5be2a176" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Birmingham reports that its Foundry tools automate redaction, mailbox indexing, administrative work, and simple translation. Redaction reportedly takes 90 seconds instead of 10 minutes with 95% success. Mail indexing reportedly handles 55% of emails, saving 5,500 staff hours and £100,000 annually. The former £350,000 translation budget is not a demonstrated saving. The source also reports translation limitations and guardrail difficulties.", "replication": { "produced_by": [ "Council officers and developers co-designed tools around four back-office functions in iterative development cycles.", "The reported redaction tool covers three document types, and the mailbox tool handles a share of incoming emails." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0546", "title": "Dorset Council: acoustic monitoring in care homes", "summary": "Dorset plans 184 acoustic and movement sensors to support care. The source reports intended sleep and falls benefits, before outcome evaluation.", "date_observed": "2025-02-03", "date_basis": "source publication", "date_precision": "day", "benefit_status": "intended", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-006", "account": "Dorset plans to install Ally Labs acoustic and movement monitoring in six care homes to detect changes and support nighttime care. The source describes 184 planned sensors, starting installation in January 2025, with outcome reviews at three and six months. No actual falls, sleep, or care outcome is reported.", "category": "general benefit", "unexpected": false, "purpose": "Use nighttime sound and movement patterns to support care decisions and detect residents’ needs.", "system": "Ally Labs acoustic-monitoring sensors and associated application", "model_version": null, "developer": "Ally Labs", "deployer": "Dorset Council on behalf of the Dorset Integrated Care System", "location": "United Kingdom", "domain": "Residential care and monitoring", "segment": null, "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Better sleep and fewer falls are intended. Outcomes following installation are unreported." }, { "group": "organizational", "depth": null, "reason": "Improved care planning and staff response are intended, but the source supplies no realized operational result." } ], "ai_role": { "status": "unassessed", "statement": "The planned system uses machine learning to establish resident behavior profiles and alert staff to sounds, movement, or changed patterns. The source precedes outcome evaluation, so AI’s contribution to better sleep, fewer falls, or improved care is not established." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Dorset Council: acoustic monitoring in care homes", "url": "https://www.local.gov.uk/case-studies/dorset-council-acoustic-monitoring-care-homes", "date": "2025-02-03", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The source describes planned installation of 184 sensors across six care homes, with follow-up reviews at three and six months.", "The system combines microphones and infrared sensing with an application for care staff." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "Dorset plans acoustic monitoring in six care homes", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/dorset-council-acoustic-monitoring-care-homes", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0546", "catalog_version": "1.0.0", "source_fingerprint": "db4377d3c21d91c0244398176a7bab12dbf8b46f9949f3e51ef5468fa703f298", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0546-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Ally Labs", "deployer": "Dorset Council on behalf of the Dorset Integrated Care System" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The planned system uses machine learning to establish resident behavior profiles and alert staff to sounds, movement, or changed patterns. The source precedes outcome evaluation, so AI’s contribution to better sleep, fewer falls, or improved care is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. 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"deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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Staff reportedly reduced meeting-minute work from 72 to 17 minutes and saved two to four hours weekly. Productivity and enjoyment results are self-reported. 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The council reports document conversion in under 30 minutes and costs of 7–10 pence for material previously costing upwards of £600. Its return-on-investment estimates have not been independently checked. A separate tool provides translation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Simply Readable, built on Amazon Bedrock with council-selected foundation models" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Swindon Borough Council using Amazon Bedrock" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Swindon Borough Council: Simply Readable, an AI easy-read solution", "headline": "Swindon reports cheaper, faster Easy-Read documents" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2c5057acb67487c805b6e54113a2b7028da52fb3f02123c679b2a26a29d94fbf" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Swindon deployed Simply Readable to produce Easy-Read documents with AI, co-designed with residents with learning disabilities. The council reports document conversion in under 30 minutes and costs of 7–10 pence for material previously costing upwards of £600. Its return-on-investment estimates have not been independently checked. A separate tool provides translation.", "replication": { "produced_by": [ "The council co-designed the tool with residents with learning disabilities, including layout, language, spacing, and images.", "The cloud-based workflow uses Amazon Bedrock and integrates with translation services." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0567", "title": "West Berkshire Council: Development of generative AI tools", "summary": "West Berkshire reports faster, more consistently formatted job adverts from its GPT tool, with low stated setup and running costs.", "date_observed": "2025-02-03", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-032", "account": "West Berkshire used GPT-based tools to generate job advertisements and explored internal and public-information assistants. Managers report less drafting time and more consistent formatting. The source reports roughly £300 in setup staff time and £2 in monthly running costs. Recycling and policy assistants were planned, and their benefits had not been established.", "category": "general benefit", "unexpected": false, "purpose": "Reduce work drafting recruitment material and explore customized assistants for council information.", "system": "Custom job-advert generator using OpenAI GPT models and the ChatGPT API; other assistant prototypes", "model_version": null, "developer": "West Berkshire Council using OpenAI models", "deployer": "West Berkshire Council", "location": "United Kingdom", "domain": "Council recruitment administration", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The implemented job-advert tool saves drafting time and standardizes presentation. These are modest workflow gains." }, { "group": "personal", "depth": 1, "reason": "Managers report less time drafting postings. Applicant and employment outcomes are unmeasured." } ], "ai_role": { "status": "assessed", "statement": "The deployed tool converts structured job information into draft advertisements and related content. Managers report shorter drafting time and consistent formatting. Other information assistants remain in development or testing." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "West Berkshire Council: Development of generative AI tools", "url": "https://www.local.gov.uk/case-studies/west-berkshire-council-development-generative-ai-tools", "date": "2025-02-03", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Forms collect job details and feed them to the OpenAI API through the council’s existing digital platform.", "Manager feedback informed evaluation of generated content." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "West Berkshire reports quicker job-advert drafting with GPT", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/west-berkshire-council-development-generative-ai-tools", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. 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Applicant and employment outcomes are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. 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"review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-031" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0577" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Task Time" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Warwickshire County Council tested a locally hosted Llama 2 model to classify businesses by size and food availability, aiming to identify areas with limited access to affordable, nutritious food. Accuracy was 63%, compared with 95% for a simpler method. Processing took up to 1.5 hours per output. The council anticipated that further fine-tuning could save staff time on manual searches. Its evaluation demonstrates neither time savings nor improved food access. Inconsistent model labels leave the exact configuration unclear.", "benefit_type": "Reduced Task Time" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Staff time savings remain intended. The unfavorable accuracy and processing results do not establish an operational improvement." }, { "group": "personal", "reason": "Residents with limited access to healthy food are intended beneficiaries. Improved food access remains unproven." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "intended" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Reduce manual search work when mapping access to affordable, nutritious food." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Warwickshire, United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Reduce manual search work when mapping access to affordable, nutritious food." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-02-03", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/warwickshire-county-council-access-food-exploring-llms-citizen-needs", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A locally hosted LLM classified businesses but underperformed a simpler method." ], "must_hold": [ "Further development and comparative testing would be needed. Conditions sufficient for a beneficial outcome remain unknown." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/warwickshire-county-council-access-food-exploring-llms-citizen-needs", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Food access and local government analysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Warwickshire County Council internal pilot evaluation, published by the Local Government Association, February 3, 2025. The account provides no independent outcome evaluation.", "title": "Warwickshire County Council: “Access to Food” – exploring LLMs for citizen needs", "url": "https://www.local.gov.uk/case-studies/warwickshire-county-council-access-food-exploring-llms-citizen-needs", "date": "2025-02-03", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0577-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Warwickshire County Council internal pilot evaluation, published by the Local Government Association, February 3, 2025. The account provides no independent outcome evaluation.", "title": "Warwickshire County Council: “Access to Food” – exploring LLMs for citizen needs", "url": "https://www.local.gov.uk/case-studies/warwickshire-county-council-access-food-exploring-llms-citizen-needs", "date": "2025-02-03", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Warwickshire’s LLM achieved 63% classification accuracy versus 95% for a simpler method. Faster food-access mapping remains intended; improved food access is not established.", "account": "Warwickshire County Council tested a locally hosted Llama 2 model to classify businesses by size and food availability, aiming to identify areas with limited access to affordable, nutritious food. Accuracy was 63%, compared with 95% for a simpler method. Processing took up to 1.5 hours per output. The council anticipated that further fine-tuning could save staff time on manual searches. Its evaluation demonstrates neither time savings nor improved food access. Inconsistent model labels leave the exact configuration unclear." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Locally hosted Llama 2 business-classification proof of concept" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Warwickshire County Council (proof-of-concept implementation)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Warwickshire Access to Food LLM pilot underperforms a simpler classification method", "headline": "Warwickshire food-mapping AI trails simpler method: 63% versus 95%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "565e1cfa52415a9e08cb30625888d95828ffa35d99399a45edfc19e4da01af69" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Warwickshire County Council tested a locally hosted Llama 2 model to classify businesses by size and food availability, aiming to identify areas with limited access to affordable, nutritious food. Accuracy was 63%, compared with 95% for a simpler method. Processing took up to 1.5 hours per output. The council anticipated that further fine-tuning could save staff time on manual searches. Its evaluation demonstrates neither time savings nor improved food access. Inconsistent model labels leave the exact configuration unclear.", "replication": { "produced_by": [ "A locally hosted LLM classified businesses but underperformed a simpler method." ], "must_hold": [ "Further development and comparative testing would be needed. Conditions sufficient for a beneficial outcome remain unknown." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0381", "title": "School bus driver Mehmet Can Duran in Tokat has ChatGPT draft his objection to a 2,400 TL traffic fine; the Tokat Civil Court of Peace annuls it within three weeks for lack of evidence", "summary": "A Tokat school bus driver used ChatGPT to write his objection to a 2,400 TL fine for dropping a student off outside a stop; the court annulled it within three weeks for lack of evidence.", "date_observed": "2025-02-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mehmet Can Duran, a school bus driver in Tokat, Turkey, was fined 2,400 TL by an honorary traffic inspector (fahri trafik müfettişi). He allegedly let a student off outside the designated stop. Webtekno says he had stopped at a pedestrian crossing to let people cross (Webtekno, 7 February 2025). Not wanting to pay a lawyer, he had an objection petition written by artificial intelligence. Webtekno identifies it as ChatGPT. Akşam's İHA report names no tool (Akşam, 6 February 2025). The petition stressed that the inspector had submitted no image or document supporting the fine. The Tokat Civil Court of Peace (Sulh Hukuk Mahkemesi) found for Duran and annulled the fine within three weeks (Akşam; Webtekno). The reports, published February 6 and 7, 2025, do not give the dates of the fine or the ruling.", "category": "benefit created", "unexpected": false, "purpose": "A general-purpose chatbot. Drafting a legal objection on request is within what it was built to do, so this benefit was expected use.", "system": "ChatGPT (per Webtekno; Akşam/İHA says only 'yapay zeka', artificial intelligence)", "model_version": null, "developer": "OpenAI (per Webtekno's identification of ChatGPT)", "deployer": null, "location": "Tokat, Turkey", "domain": "Legal services / administrative appeals", "segment": "Traffic fine objections by self-represented drivers", "benefit_type": "Reduced Task Cost", "taxonomy_note": "The good is a legal petition produced without an attorney's fee and a fine annulled; the annulment itself rested on the court's finding that the inspector had no evidence.", "registry_ids": { "oecd_aim": "2025-02-06-4cc2" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Duran's 2,400 TL fine was annulled on an objection he filed without paying a lawyer. A one-off measurable result, not a lasting change." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT, per Webtekno, drafted the objection that pointed to the absence of any image or document behind the fine. The court annulled the fine on that ground. The decisive fact was the inspector's missing evidence, which Duran could have pleaded himself. What the system contributed was a petition in legal form at no fee. Neither report quotes the petition or the ruling." }, "evidence": [ { "kind": "news report", "citation": "Bulut, B. (2025). Bir Vatandaş, ChatGPT'ye Yazdırdığı Dilekçe ile Trafik Cezasını İptal Ettirdi. Webtekno, February 7, 2025.", "title": "Bir Vatandaş, ChatGPT'ye Yazdırdığı Dilekçe ile Trafik Cezasını İptal Ettirdi", "url": "https://www.webtekno.com/chatgpt-dilekce-trafik-cezasi-h155464.html", "date": "2025-02-07", "written_by": "independent", "quote": "Dilekçede fahri trafik müfettişinin cezaya dair herhangi bir görsel ya da belge sunmadığı vurgulanınca" }, { "kind": "news report", "citation": "Akşam / İHA (2025). Yapay zekaya yazdırdığı dilekçe ile trafik cezasını iptal ettirdi. Akşam, February 6, 2025.", "title": "Yapay zekaya yazdırdığı dilekçe ile trafik cezasını iptal ettirdi", "url": "https://www.aksam.com.tr/guncel/yapay-zekaya-yazdirdigi-dilekce-ile-trafik-cezasini-iptal-ettirdi/haber-1544041", "date": "2025-02-06", "written_by": "independent", "quote": "haklı bularak cezayı iptal etti" }, { "kind": "registry label", "citation": "OECD.AI (2025). School Bus Driver Cancels Traffic Fine with AI-Written Appeal. OECD AI Incidents and Hazards Monitor, 2025-02-06.", "title": "School Bus Driver Cancels Traffic Fine with AI-Written Appeal", "url": "https://oecd.ai/en/incidents/2025-02-06-4cc2", "date": "2025-02-06", "written_by": "independent", "quote": "The AI-generated petition highlighted missing evidence, and the Tokat Civil Court ruled in his favor, annulling the fine." } ], "replication": { "produced_by": [ "A fine issued without supporting evidence that an objection could expose", "A chatbot able to produce a petition in the form the court expects", "A court that accepts a self-filed written objection" ], "must_hold": [ "The objection's factual claim must be true and checkable by the court", "The filer must still meet the court's deadlines and form requirements" ], "echoes": [] }, "paired_incident": null, "headline": "AI-drafted objection gets a Tokat bus driver's traffic fine annulled", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-02-06-4cc2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. 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School Bus Driver Cancels Traffic Fine with AI-Written Appeal. OECD AI Incidents and Hazards Monitor, 2025-02-06.", "title": "School Bus Driver Cancels Traffic Fine with AI-Written Appeal", "url": "https://oecd.ai/en/incidents/2025-02-06-4cc2", "date": "2025-02-06", "written_by": "independent", "quote": "The AI-generated petition highlighted missing evidence, and the Tokat Civil Court ruled in his favor, annulling the fine." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0381-source-0001", "AIBD-0381-source-0002", "AIBD-0381-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Bulut, B. (2025). Bir Vatandaş, ChatGPT'ye Yazdırdığı Dilekçe ile Trafik Cezasını İptal Ettirdi. Webtekno, February 7, 2025.", "title": "Bir Vatandaş, ChatGPT'ye Yazdırdığı Dilekçe ile Trafik Cezasını İptal Ettirdi", "url": "https://www.webtekno.com/chatgpt-dilekce-trafik-cezasi-h155464.html", "date": "2025-02-07", "written_by": "independent", "quote": "Dilekçede fahri trafik müfettişinin cezaya dair herhangi bir görsel ya da belge sunmadığı vurgulanınca" }, { "kind": "news report", "citation": "Akşam / İHA (2025). Yapay zekaya yazdırdığı dilekçe ile trafik cezasını iptal ettirdi. Akşam, February 6, 2025.", "title": "Yapay zekaya yazdırdığı dilekçe ile trafik cezasını iptal ettirdi", "url": "https://www.aksam.com.tr/guncel/yapay-zekaya-yazdirdigi-dilekce-ile-trafik-cezasini-iptal-ettirdi/haber-1544041", "date": "2025-02-06", "written_by": "independent", "quote": "haklı bularak cezayı iptal etti" }, { "kind": "registry label", "citation": "OECD.AI (2025). School Bus Driver Cancels Traffic Fine with AI-Written Appeal. OECD AI Incidents and Hazards Monitor, 2025-02-06.", "title": "School Bus Driver Cancels Traffic Fine with AI-Written Appeal", "url": "https://oecd.ai/en/incidents/2025-02-06-4cc2", "date": "2025-02-06", "written_by": "independent", "quote": "The AI-generated petition highlighted missing evidence, and the Tokat Civil Court ruled in his favor, annulling the fine." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Tokat school bus driver used ChatGPT to write his objection to a 2,400 TL fine for dropping a student off outside a stop; the court annulled it within three weeks for lack of evidence.", "account": "Mehmet Can Duran, a school bus driver in Tokat, Turkey, was fined 2,400 TL by an honorary traffic inspector (fahri trafik müfettişi). He allegedly let a student off outside the designated stop. Webtekno says he had stopped at a pedestrian crossing to let people cross (Webtekno, 7 February 2025). Not wanting to pay a lawyer, he had an objection petition written by artificial intelligence. Webtekno identifies it as ChatGPT. Akşam's İHA report names no tool (Akşam, 6 February 2025). The petition stressed that the inspector had submitted no image or document supporting the fine. The Tokat Civil Court of Peace (Sulh Hukuk Mahkemesi) found for Duran and annulled the fine within three weeks (Akşam; Webtekno). The reports, published February 6 and 7, 2025, do not give the dates of the fine or the ruling." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (per Webtekno; Akşam/İHA says only 'yapay zeka', artificial intelligence)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI (per Webtekno's identification of ChatGPT)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "School bus driver Mehmet Can Duran in Tokat has ChatGPT draft his objection to a 2,400 TL traffic fine; the Tokat Civil Court of Peace annuls it within three weeks for lack of evidence", "headline": "AI-drafted objection gets a Tokat bus driver's traffic fine annulled" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c65adc379764743d3eddf75d6df2a54967ffc54157a587225c58329cf59b55f4" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mehmet Can Duran, a school bus driver in Tokat, Turkey, was fined 2,400 TL by an honorary traffic inspector (fahri trafik müfettişi). He allegedly let a student off outside the designated stop. Webtekno says he had stopped at a pedestrian crossing to let people cross (Webtekno, 7 February 2025). Not wanting to pay a lawyer, he had an objection petition written by artificial intelligence. Webtekno identifies it as ChatGPT. Akşam's İHA report names no tool (Akşam, 6 February 2025). The petition stressed that the inspector had submitted no image or document supporting the fine. The Tokat Civil Court of Peace (Sulh Hukuk Mahkemesi) found for Duran and annulled the fine within three weeks (Akşam; Webtekno). The reports, published February 6 and 7, 2025, do not give the dates of the fine or the ruling.", "replication": { "produced_by": [ "A fine issued without supporting evidence that an objection could expose", "A chatbot able to produce a petition in the form the court expects", "A court that accepts a self-filed written objection" ], "must_hold": [ "The objection's factual claim must be true and checkable by the court", "The filer must still meet the court's deadlines and form requirements" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0106", "title": "Machine-learning species delimitation identifies second species of Micrognathozoa", "summary": "Transcriptomes plus machine-learning delimitation split the Crozet population as Limnognathia desmeti sp. nov. (Proc R Soc B, 19 February 2025).", "date_observed": "2025-02-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Micrognathozoa, the most recently discovered animal phylum, contained a single species, Limnognathia maerski, known from Greenland, the Pyrenees and a Subantarctic island. Specimens were collected at Pointe du Bougainville on Île de la Possession, Crozet Archipelago, on 10–11 December 2019. A French Polar Institute project awarded to co-author David Renault funded the collection. Sato and colleagues at the University of Copenhagen, Harvard University, the Natural History Museum London and partner institutions generated transcriptomes from single specimens. They tested species hypotheses with standard approaches and with unsupervised (PCA, random forest, t-SNE, VAE) and supervised (delimitR, CLADES) machine-learning methods. The authors preferred the most conservative estimate across PTP, VAE and custom CLADES, which delimits only the Crozet population. The analyses delimited the Subantarctic population as a new species, Limnognathia desmeti sp. nov., while not definitively separating the Greenland and Pyrenees populations. The paper appeared in Proceedings of the Royal Society B on 19 February 2025.", "category": "benefit created", "unexpected": false, "purpose": "Test species hypotheses within Micrognathozoa using transcriptomic data and machine-learning species delimitation.", "system": "Machine-learning species delimitation on single-specimen transcriptomes: unsupervised clustering (PCA, random forest, t-SNE, variational autoencoder) and supervised classifiers (delimitR, CLADES)", "model_version": null, "developer": null, "deployer": "University of Copenhagen Marine Biological Section and co-author institutions", "location": "Pointe du Bougainville, Île de la Possession, Crozet Archipelago (Subantarctic)", "domain": "Conservation and biodiversity", "segment": "Taxonomy and biodiversity discovery", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "A verified discrete result for the research team: formal description of a new species in a phylum with one previously known species." }, { "group": "organizational", "depth": 1, "reason": "Adds a named taxon and a Subantarctic record to museum and university collections; no operational change documented." }, { "group": "societal", "depth": 1, "reason": "Knowledge gain about a rare phylum's diversity and dispersal; no conservation action or beneficiary population is documented." } ], "ai_role": { "status": "assessed", "statement": "The paper's title credits machine learning with the identification. Each machine-learning method run (unsupervised PCA, random forest, t-SNE and VAE; supervised delimitR and CLADES) separated the Crozet population. The adopted two-species result rests on the authors' most conservative estimate across PTP, VAE and custom CLADES. It does not rest on delimitR's three-species model, which would also have split Greenland from the Pyrenees. The conclusion also rests on deep phylogenetic divergence, extreme geographical separation and differences in COI and 18S rRNA sequences. So the machine-learning output was one of several lines of evidence, not the sole basis." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Sato, S., Appeldorff, C., Wangensteen, O. S., Garcés-Pastor, S., Laumer, C. E., Herranz, M., Giribet, G., Renault, D., Møller, P. R., & Worsaae, K. (2025). Phylogenomics of the rarest animals: a second species of Micrognathozoa identified by machine learning. Proceedings of the Royal Society B 292(2041). doi:10.1098/rspb.2024.2867", "title": "Phylogenomics of the rarest animals: a second species of Micrognathozoa identified by machine learning", "url": "https://europepmc.org/abstract/MED/39968621", "date": "2025-02-19", "written_by": "deployer", "quote": "extensively tested species hypotheses using standard approaches and novel machine learning methods" }, { "kind": "peer-reviewed study", "citation": "Sato, S., et al. (2025). Phylogenomics of the rarest animals: a second species of Micrognathozoa identified by machine learning. Proc R Soc B (full text, PMC11836703).", "title": "Phylogenomics of the rarest animals: a second species of Micrognathozoa identified by machine learning (full text)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11836703/", "date": "2025-02-19", "written_by": "deployer", "quote": "Crozet Archipelago: Île de la Possession: Pointe du Bougainville: NHMD-001801220, 1 specimen, −46.447919, 51.850842, 11.Dec.2019." } ], "replication": { "produced_by": [ "Field collection of all three known populations", "Single-specimen transcriptomics for microscopic animals", "Species-delimitation models run alongside conventional phylogenetics" ], "must_hold": [ "Sufficient genomic signal between populations", "Agreement between machine learning (ML) and standard delimitation", "Morphological comparison to document cryptic status" ], "echoes": [ { "date": "2025-02-19", "setting": "Same study: Greenland versus Pyrenees populations", "model_version": null, "outcome": "did not recur", "source": "Sato et al. (2025): VAE and custom CLADES joined Greenland and Pyrenees; delimitR and SNAPPER preferred three species; the authors adopted the conservative two-species estimate across PTP, VAE and custom CLADES" } ] }, "paired_incident": null, "headline": "ML (VAE, custom CLADES) delimits second Micrognathozoa species", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The Crozet population was formally named Limnognathia desmeti sp. nov. in the same February 2025 paper, and no later development was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Denmark", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Rewrote system, headline, metric, account and AI-role statement so that the adopted two-species result rests on PTP, VAE and custom CLADES rather than on delimitR's three-species model, replaced the spliced locality quote with the verbatim holotype entry, dropped the unsourced “French Southern and Antarctic Lands” from the location, attributed the Crozet collection to French Polar Institute funding rather than to Sato by name, and re-sourced the Greenland-Pyrenees echo to the per-method outputs.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11836703/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www1.bio.ku.dk/english/research/mbs/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: two peer-reviewed studies from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0106", "catalog_version": "1.0.0", "source_fingerprint": "ae943d69d3df23603dde9bd242eca9ee16f6e58b7504e223e158edf42c736fe2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0106-source-0001", "AIBD-0106-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "University of Copenhagen Marine Biological Section and co-author institutions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The paper's title credits machine learning with the identification. Each machine-learning method run (unsupervised PCA, random forest, t-SNE and VAE; supervised delimitR and CLADES) separated the Crozet population. The adopted two-species result rests on the authors' most conservative estimate across PTP, VAE and custom CLADES. It does not rest on delimitR's three-species model, which would also have split Greenland from the Pyrenees. The conclusion also rests on deep phylogenetic divergence, extreme geographical separation and differences in COI and 18S rRNA sequences. 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The conclusion also rests on deep phylogenetic divergence, extreme geographical separation and differences in COI and 18S rRNA sequences. So the machine-learning output was one of several lines of evidence, not the sole basis." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "A verified discrete result for the research team: formal description of a new species in a phylum with one previously known species." }, { "group": "organizational", "depth": 1, "reason": "Adds a named taxon and a Subantarctic record to museum and university collections; no operational change documented." }, { "group": "societal", "depth": 1, "reason": "Knowledge gain about a rare phylum's diversity and dispersal; no conservation action or beneficiary population is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: two peer-reviewed studies from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "A verified discrete result for the research team: formal description of a new species in a phylum with one previously known species." }, { "group": "organizational", "depth": 1, "reason": "Adds a named taxon and a Subantarctic record to museum and university collections; no operational change documented." }, { "group": "societal", "depth": 1, "reason": "Knowledge gain about a rare 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The councils report an estimated 85% reduction in repetitive planning-administration time, and teams are actively using the systems." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Konveio and Go Vocal AI tagging and generative summarization tools" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Konveio and Go Vocal" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "West Oxfordshire and Cotswold District Councils - Summarising planning engagement upfront", "headline": "West Oxfordshire and Cotswold report less planning admin" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f569eccb33a833c498362f3cc7353aaaa57c57b23afd2dad76a7815a32ca2e11" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "West Oxfordshire and Cotswold councils use Konveio and Go Vocal to tag and summarize planning-consultation feedback. The councils report an estimated 85% reduction in repetitive planning-administration time, and teams are actively using the systems.", "replication": { "produced_by": [ "The councils used PropTech funding and their existing partnership to develop tools with two vendors.", "Officers collaborated in defining needs, and teams were actively using the systems after the pilot." ], "must_hold": [ "The source states that AI use was permitted case by case and prohibited for personal data.", "The conditions needed to reproduce the estimated time saving are unknown." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0143", "title": "ECMWF's AIFS Single became the first operational machine-learning global forecast model on 25 February 2025", "summary": "ECMWF's AIFS Single became operational 25 February 2025; ECMWF reports 5–15% lower errors than IFS; no specific event documented.", "date_observed": "2025-02-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "ECMWF announced that on 25 February 2025 it began producing operational forecasts with AIFS Single, the deterministic version of its Artificial Intelligence Forecasting System. It claimed tropical cyclone track gains of up to 20%. ECMWF's evaluation of 2025 forecasts (8 May 2026) reports AIFS errors 5 to 15% lower than the IFS for most surface and upper-air variables. Cyclone position was substantially better but intensity under-predicted. NHC's Science Operations Officer said ECMWF's AI-driven global system was available for evaluation at NHC during the 2025 season. No specific event in which AIFS beat the IFS is documented in the ECMWF cited sources. The Severe Event Catalog page for Storm Eowyn states wind gusts were not available for AIFS.", "category": "general benefit", "unexpected": false, "purpose": "Operational data-driven global medium-range weather forecasting at ECMWF, run alongside the physics-based IFS.", "system": "ECMWF Artificial Intelligence Forecasting System (AIFS)", "model_version": "AIFS Single v1 (operational from 25 February 2025)", "developer": "ECMWF", "deployer": "ECMWF", "location": "Reading, United Kingdom", "domain": "Weather forecasting", "segment": "Public-sector meteorological service", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate skill statistics, no discrete event." }, { "group": "organizational", "depth": null, "reason": "Aggregate skill statistics, no discrete event." }, { "group": "societal", "depth": null, "reason": "Aggregate skill statistics, no discrete event." } ], "ai_role": { "status": "assessed", "statement": "ECMWF's verification compares AIFS directly with the IFS. The only non-ECMWF cited source (NWS Q&A) confirms NHC evaluated ECMWF's AI system in 2025 but states no performance result. ECMWF is both the developer and the deployer, so its evaluations are the body reporting on its own system." }, "evidence": [ { "kind": "press release", "citation": "ECMWF (2025). ECMWF's AI forecasts become operational. ECMWF news, 25 February 2025.", "title": "ECMWF's AI forecasts become operational", "url": "https://www.ecmwf.int/node/29308", "date": "2025-02-25", "written_by": "makers", "quote": "The AIFS outperforms state-of-the-art physics-based models for many measures" }, { "kind": "press release", "citation": "ECMWF (2026). 2025 forecast evaluation met with positive feedback. ECMWF news, 8 May 2026.", "title": "2025 forecast evaluation met with positive feedback", "url": "https://www.ecmwf.int/en/about/media-centre/news/2026/2025-forecast-evaluation", "date": "2026-05-08", "written_by": "makers", "quote": "the Artificial Intelligence Forecasting System (AIFS) is outperforming the IFS for most surface and upper-air variables, with errors 5 to 15% lower in the medium range" }, { "kind": "report", "citation": "Haiden, T., Chevallier, M. (2026). Forecast performance 2025. ECMWF Newsletter No. 187, May 2026.", "title": "Forecast performance 2025", "url": "https://www.ecmwf.int/en/newsletter/187/news/forecast-performance-2025", "date": "2026-05-01", "written_by": "makers", "quote": "Tropical cyclone (TC) position errors are reduced substantially in the AIFS compared to the IFS, whereas TC intensity errors are generally larger due to a weak-intensity bias." }, { "kind": "report", "citation": "National Weather Service (n.d.). AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC Science Operation Officer Wallace Hogsett. NOAA/NWS.", "title": "AI in Hurricane Forecasting at the National Hurricane Center", "url": "https://www.weather.gov/news/261102-AI-Hurricane-Forecasting", "date": null, "written_by": "independent", "quote": "the European Center for Medium-Range Weather Forecasts (ECMWF) have developed AI-driven global forecast systems, both of which were also available for evaluation during the 2025 season" }, { "kind": "other", "citation": "ECMWF Forecast User wiki (2025). Severe Event Catalogue: 202501 - Windstorm - Eowyn.", "title": "202501 - Windstorm - Eowyn", "url": "https://confluence.ecmwf.int/display/FCST/202501+-+Windstorm+-+Eowyn", "date": null, "written_by": "makers", "quote": "Wind gusts not available for AIFS" }, { "kind": "preprint", "citation": "Allen, A., Bruinsma, W. P., Maier-Gerber, M., Cook, H., Chantry, M., Turner, R. E. (2026). AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting. arXiv:2608.09959.", "title": "AIFS-TC: A simple correction competitive with the operational frontier for tropical cyclone intensity forecasting", "url": "https://arxiv.org/abs/2608.09959", "date": "2026-07-24", "written_by": "makers", "quote": "While these models have been shown to achieve superior performance to physics-based NWP in forecasting tropical cyclone (TC) tracks, they tend to dramatically underestimate intensity." } ], "replication": { "produced_by": [ "Operational twice-daily AIFS Single runs initialized from ECMWF analyses", "ECMWF's standard headline-score and tropical cyclone verification against the IFS" ], "must_hold": [ "Intensity under-prediction persists per ECMWF and the AIFS-TC preprint", "No ECMWF-documented named event where AIFS beat the IFS was found. Event-level superiority remains unverified" ], "echoes": [ { "date": "2026-05-01", "setting": "ECMWF Newsletter 187, 2025 forecast performance (AIFS Single and AIFS ENS versus IFS)", "model_version": "AIFS Single v1; AIFS ENS v1", "outcome": "recurred", "source": "https://www.ecmwf.int/en/newsletter/187/news/forecast-performance-2025" }, { "date": "2026-07-24", "setting": "AIFS-TC preprint (partly ECMWF-authored): track superiority restated, intensity weakness corrected by post-processing", "model_version": "AIFS Single", "outcome": "recurred", "source": "https://arxiv.org/abs/2608.09959" } ] }, "paired_incident": null, "headline": "ECMWF's AIFS Single goes operational with 5–15% lower errors", "metric": "5–15% lower errors than IFS", "comparator": { "against": "ECMWF's physics-based Integrated Forecasting System (IFS)", "before": null, "after": "errors 5 to 15% lower in the medium range (out to 15 days)", "basis": "measured", "quote": "Current assessments show that the Artificial Intelligence Forecasting System (AIFS) is outperforming the IFS for most surface and upper-air variables, with errors 5 to 15% lower in the medium range (out to 15 days).", "url": "https://www.ecmwf.int/en/about/media-centre/news/2026/2025-forecast-evaluation" }, "later": { "status": "scaled", "date": "2025-07-01", "note": "ECMWF launched the ensemble version, AIFS-ENS, operationally on 1 July 2025, and its 2025 evaluation (May 2026) reports both AIFS Single and AIFS ENS beating the IFS on most parameters.", "quote": "On 25 February 2025, the machine-learning (ML) model AIFS Single v1 was implemented, followed by the operational launch of AIFS-ENS on 1 July 2025.", "url": "https://www.ecmwf.int/en/newsletter/187/news/forecast-performance-2025" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.ecmwf.int/en/about/media-centre/news/2026/2025-forecast-evaluation; https://www.ecmwf.int/en/newsletter/187/news/forecast-performance-2025", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/European_Centre_for_Medium-Range_Weather_Forecasts; https://en.wikipedia.org/wiki/European_Centre_for_Medium-Range_Weather_Forecasts", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, the makers' report, the makers' preprint, two press releases from the makers and the makers' other. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0143", "catalog_version": "1.0.0", "source_fingerprint": "9e2e95a2474260e66170d3fc23be5fd6c29e83c518e493a74df91ef1ea367c8d", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0143-source-0001", "AIBD-0143-source-0002", "AIBD-0143-source-0003", "AIBD-0143-source-0004", "AIBD-0143-source-0005", "AIBD-0143-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ECMWF", "deployer": "ECMWF" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ECMWF's verification compares AIFS directly with the IFS. The only non-ECMWF cited source (NWS Q&A) confirms NHC evaluated ECMWF's AI system in 2025 but states no performance result. ECMWF is both the developer and the deployer, so its evaluations are the body reporting on its own system." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "ECMWF's verification compares AIFS directly with the IFS. The only non-ECMWF cited source (NWS Q&A) confirms NHC evaluated ECMWF's AI system in 2025 but states no performance result. ECMWF is both the developer and the deployer, so its evaluations are the body reporting on its own system." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report, the makers' report, the makers' preprint, two press releases from the makers and the makers' other. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate skill statistics, no discrete event." }, { "group": "organizational", "reason": "Aggregate skill statistics, no discrete event." }, { "group": "societal", "reason": "Aggregate skill statistics, no discrete event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate skill statistics, no discrete event." }, { "group": "organizational", "reason": "Aggregate skill statistics, no discrete event." }, { "group": "societal", "reason": "Aggregate skill statistics, no discrete event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" 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"economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "AIFS Single v1 (operational from 25 February 2025)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "AIFS Single v1.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ECMWF Artificial Intelligence Forecasting System (AIFS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ECMWF" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ECMWF's AIFS Single became the first operational machine-learning global forecast model on 25 February 2025", "headline": "ECMWF's AIFS Single goes operational with 5–15% lower errors" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9e2e95a2474260e66170d3fc23be5fd6c29e83c518e493a74df91ef1ea367c8d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ECMWF announced that on 25 February 2025 it began producing operational forecasts with AIFS Single, the deterministic version of its Artificial Intelligence Forecasting System. It claimed tropical cyclone track gains of up to 20%. ECMWF's evaluation of 2025 forecasts (8 May 2026) reports AIFS errors 5 to 15% lower than the IFS for most surface and upper-air variables. Cyclone position was substantially better but intensity under-predicted. NHC's Science Operations Officer said ECMWF's AI-driven global system was available for evaluation at NHC during the 2025 season. No specific event in which AIFS beat the IFS is documented in the ECMWF cited sources. The Severe Event Catalog page for Storm Eowyn states wind gusts were not available for AIFS.", "replication": { "produced_by": [ "Operational twice-daily AIFS Single runs initialized from ECMWF analyses", "ECMWF's standard headline-score and tropical cyclone verification against the IFS" ], "must_hold": [ "Intensity under-prediction persists per ECMWF and the AIFS-TC preprint", "No ECMWF-documented named event where AIFS beat the IFS was found. Event-level superiority remains unverified" ], "echoes": [ { "date": "2026-05-01", "setting": "ECMWF Newsletter 187, 2025 forecast performance (AIFS Single and AIFS ENS versus IFS)", "model_version": "AIFS Single v1; AIFS ENS v1", "outcome": "recurred", "source": "https://www.ecmwf.int/en/newsletter/187/news/forecast-performance-2025" }, { "date": "2026-07-24", "setting": "AIFS-TC preprint (partly ECMWF-authored): track superiority restated, intensity weakness corrected by post-processing", "model_version": "AIFS Single", "outcome": "recurred", "source": "https://arxiv.org/abs/2608.09959" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0065", "title": "Viz HCM AI-ECG algorithm flags hypertrophic cardiomyopathy in a symptomatic 61-year-old; obstructive HCM confirmed and treated with mavacamten at Cleveland Clinic", "summary": "AI-ECG (Viz HCM) scored >0.95 for HCM in a symptomatic 61-year-old; echo confirmed obstructive HCM; mavacamten cut gradients and symptoms.", "date_observed": "2025-02-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 61-year-old man, unaware of any cardiomyopathy, had lightheadedness, dizziness, fatigue and functional limitation on moderate exertion. He had a baseline electrocardiogram (ECG) at an executive physical at Cleveland Clinic, Cleveland, Ohio (no date given). Under an organization-wide initiative it was uploaded to a cloud platform running the Viz HCM convolutional neural network. The algorithm gave a probability above 0.95 for hypertrophic cardiomyopathy and he was referred to the Hypertrophic Cardiomyopathy Center. Echocardiography showed 2 cm basal septal hypertrophy, systolic anterior motion and a post-exercise outflow gradient of 72 mm Hg. After shared decision-making he started mavacamten 5 mg daily. By week 8 the resting gradient was 9 mm Hg, with less dizziness and dyspnea and no hospitalizations.", "category": "benefit created", "unexpected": false, "purpose": "Viz HCM is a cloud-based AI-ECG algorithm built to flag probable hypertrophic cardiomyopathy from 12-lead ECGs. This diagnosis is its intended function.", "system": "Viz HCM", "model_version": null, "developer": "Viz.ai", "deployer": "Cleveland Clinic", "location": "Cleveland, United States", "domain": "Healthcare - cardiology", "segment": "AI-ECG screening in a health system", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "An undiagnosed obstructive cardiomyopathy causing dizziness and exertional limitation was identified and treated with a disease-specific drug. Gradient reduction and symptom improvement at 8 weeks are documented. Long-term benefit is not yet shown." } ], "ai_role": { "status": "assessed", "statement": "The AI-ECG probability (>0.95) was the trigger for referral and echocardiography in a patient not previously suspected of HCM. Imaging confirmed the diagnosis and clinicians chose the treatment. Disclosed relationships: Dr Desai is a consultant for and has research agreements with Viz-ai (among other companies). Mrs Rutkowski is a consultant for Viz-ai. Mrs Ospina has none. All three authors are listed under the Cleveland Clinic Hypertrophic Cardiomyopathy Center, with no Viz.ai affiliation." }, "evidence": [ { "kind": "case report", "citation": "Desai MY, Rutkowski K, Ospina S (2025). Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten. JACC: Case Reports 30(8):103228.", "title": "Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "date": "2025-02-26", "written_by": "deployer", "quote": "The AI-analyzed ECG (Figure 1B) subsequently received a high probability score (>0.95) for HCM." } ], "replication": { "produced_by": [ "Uploading routine 12-lead ECGs to the Viz HCM cloud platform as an institutional initiative", "A referral pathway from AI flag to a specialist HCM center" ], "must_hold": [ "Echocardiographic confirmation before treatment", "Access to mavacamten with REMS monitoring" ], "echoes": [] }, "paired_incident": null, "headline": "Viz HCM flags hypertrophic cardiomyopathy in a 61-year-old", "metric": "by week 8 the resting gradient was 9 mm Hg", "comparator": { "against": "the clinical reading of the same baseline ECG", "before": "interpreted clinically as normal sinus rhythm with first-degree atrioventricular block", "after": "a high probability score (>0.95) for HCM", "basis": "measured", "quote": "His baseline ECG was interpreted clinically as normal sinus rhythm with first-degree atrioventricular block; CAC score was 235 (79th percentile for age, gender, and ethnicity), and he achieved 9 metabolic equivalents (METs) on exercise stress test without significant abnormalities.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/" }, "later": { "status": "unknown", "date": null, "note": "The case report ends at week 8 of mavacamten; no later development appears in the cited source.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsupported October 2024 ECG date (the paper gives none) and set the date observed to the 26 February 2025 publication date with the manuscript dates noted, restored “(Figure 1B)” to the quotation, completed the Viz-ai disclosures (Dr Desai is also a consultant) and noted that the paper names the algorithm VIZ-HCM but never states its developer.", "source": "Desai MY, Rutkowski K, Ospina S (2025). JACC: Case Reports 30(8):103228, https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.viz.ai/privacy-policy; https://my.clevelandclinic.org/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0065", "catalog_version": "1.0.0", "source_fingerprint": "d83b61a0b89d6cffae4f3886eb3324d00a01cf933feeddcdc72f4b4866c9a29c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0065-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Viz.ai", "deployer": "Cleveland Clinic" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI-ECG probability (>0.95) was the trigger for referral and echocardiography in a patient not previously suspected of HCM. Imaging confirmed the diagnosis and clinicians chose the treatment. Disclosed relationships: Dr Desai is a consultant for and has research agreements with Viz-ai (among other companies). Mrs Rutkowski is a consultant for Viz-ai. Mrs Ospina has none. All three authors are listed under the Cleveland Clinic Hypertrophic Cardiomyopathy Center, with no Viz.ai affiliation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI-ECG probability (>0.95) was the trigger for referral and echocardiography in a patient not previously suspected of HCM. Imaging confirmed the diagnosis and clinicians chose the treatment. Disclosed relationships: Dr Desai is a consultant for and has research agreements with Viz-ai (among other companies). Mrs Rutkowski is a consultant for Viz-ai. Mrs Ospina has none. All three authors are listed under the Cleveland Clinic Hypertrophic Cardiomyopathy Center, with no Viz.ai affiliation." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An undiagnosed obstructive cardiomyopathy causing dizziness and exertional limitation was identified and treated with a disease-specific drug. Gradient reduction and symptom improvement at 8 weeks are documented. 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "by week 8 the resting gradient was 9 mm Hg", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": 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sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 61-year-old man, unaware of any cardiomyopathy, had lightheadedness, dizziness, fatigue and functional limitation on moderate exertion. He had a baseline electrocardiogram (ECG) at an executive physical at Cleveland Clinic, Cleveland, Ohio (no date given). Under an organization-wide initiative it was uploaded to a cloud platform running the Viz HCM convolutional neural network. The algorithm gave a probability above 0.95 for hypertrophic cardiomyopathy and he was referred to the Hypertrophic Cardiomyopathy Center. Echocardiography showed 2 cm basal septal hypertrophy, systolic anterior motion and a post-exercise outflow gradient of 72 mm Hg. After shared decision-making he started mavacamten 5 mg daily. By week 8 the resting gradient was 9 mm Hg, with less dizziness and dyspnea and no hospitalizations.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An undiagnosed obstructive cardiomyopathy causing dizziness and exertional limitation was identified and treated with a disease-specific drug. Gradient reduction and symptom improvement at 8 weeks are documented. Long-term benefit is not yet shown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Viz HCM is a cloud-based AI-ECG algorithm built to flag probable hypertrophic cardiomyopathy from 12-lead ECGs. This diagnosis is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cleveland, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Viz HCM is a cloud-based AI-ECG algorithm built to flag probable hypertrophic cardiomyopathy from 12-lead ECGs. This diagnosis is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-02-26", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsupported October 2024 ECG date (the paper gives none) and set the date observed to the 26 February 2025 publication date with the manuscript dates noted, restored “(Figure 1B)” to the quotation, completed the Viz-ai disclosures (Dr Desai is also a consultant) and noted that the paper names the algorithm VIZ-HCM but never states its developer.", "source": "Desai MY, Rutkowski K, Ospina S (2025). JACC: Case Reports 30(8):103228, https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.viz.ai/privacy-policy; https://my.clevelandclinic.org/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Uploading routine 12-lead ECGs to the Viz HCM cloud platform as an institutional initiative", "A referral pathway from AI flag to a specialist HCM center" ], "must_hold": [ "Echocardiographic confirmation before treatment", "Access to mavacamten with REMS monitoring" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the unsupported October 2024 ECG date (the paper gives none) and set the date observed to the 26 February 2025 publication date with the manuscript dates noted, restored “(Figure 1B)” to the quotation, completed the Viz-ai disclosures (Dr Desai is also a consultant) and noted that the paper names the algorithm VIZ-HCM but never states its developer.", "source": "Desai MY, Rutkowski K, Ospina S (2025). 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Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten. JACC: Case Reports 30(8):103228.", "title": "Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "date": "2025-02-26", "written_by": "deployer", "quote": "The AI-analyzed ECG (Figure 1B) subsequently received a high probability score (>0.95) for HCM." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0065-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Desai MY, Rutkowski K, Ospina S (2025). Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten. JACC: Case Reports 30(8):103228.", "title": "Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12046996/", "date": "2025-02-26", "written_by": "deployer", "quote": "The AI-analyzed ECG (Figure 1B) subsequently received a high probability score (>0.95) for HCM." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI-ECG (Viz HCM) scored >0.95 for HCM in a symptomatic 61-year-old; echo confirmed obstructive HCM; mavacamten cut gradients and symptoms.", "account": "A 61-year-old man, unaware of any cardiomyopathy, had lightheadedness, dizziness, fatigue and functional limitation on moderate exertion. He had a baseline electrocardiogram (ECG) at an executive physical at Cleveland Clinic, Cleveland, Ohio (no date given). Under an organization-wide initiative it was uploaded to a cloud platform running the Viz HCM convolutional neural network. The algorithm gave a probability above 0.95 for hypertrophic cardiomyopathy and he was referred to the Hypertrophic Cardiomyopathy Center. Echocardiography showed 2 cm basal septal hypertrophy, systolic anterior motion and a post-exercise outflow gradient of 72 mm Hg. After shared decision-making he started mavacamten 5 mg daily. By week 8 the resting gradient was 9 mm Hg, with less dizziness and dyspnea and no hospitalizations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Viz HCM" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Viz.ai" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Viz HCM AI-ECG algorithm flags hypertrophic cardiomyopathy in a symptomatic 61-year-old; obstructive HCM confirmed and treated with mavacamten at Cleveland Clinic", "headline": "Viz HCM flags hypertrophic cardiomyopathy in a 61-year-old" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d83b61a0b89d6cffae4f3886eb3324d00a01cf933feeddcdc72f4b4866c9a29c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 61-year-old man, unaware of any cardiomyopathy, had lightheadedness, dizziness, fatigue and functional limitation on moderate exertion. He had a baseline electrocardiogram (ECG) at an executive physical at Cleveland Clinic, Cleveland, Ohio (no date given). Under an organization-wide initiative it was uploaded to a cloud platform running the Viz HCM convolutional neural network. The algorithm gave a probability above 0.95 for hypertrophic cardiomyopathy and he was referred to the Hypertrophic Cardiomyopathy Center. Echocardiography showed 2 cm basal septal hypertrophy, systolic anterior motion and a post-exercise outflow gradient of 72 mm Hg. After shared decision-making he started mavacamten 5 mg daily. By week 8 the resting gradient was 9 mm Hg, with less dizziness and dyspnea and no hospitalizations.", "replication": { "produced_by": [ "Uploading routine 12-lead ECGs to the Viz HCM cloud platform as an institutional initiative", "A referral pathway from AI flag to a specialist HCM center" ], "must_hold": [ "Echocardiographic confirmation before treatment", "Access to mavacamten with REMS monitoring" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0282", "title": "AresGW deep-learning search finds eight new gravitational-wave candidates in LIGO O3 data, none yet independently confirmed", "summary": "Koloniari et al. (Mach. Learn.: Sci. Technol., 27 February 2025): the ResNet pipeline AresGW found eight new O3 candidates with p_astro > 0.5 (cumulative 5.94); none is confirmed by another pipeline.", "date_observed": "2025-02-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The authors are Alexandra Koloniari, Evdokia Koursoumpa, Paraskevi Nousi, Paraskevas Lampropoulos, Nikolaos Passalis, Anastasios Tefas and Nikolaos Stergioulas. They are at Aristotle University of Thessaloniki and the Swiss Data Science Center (ETH Zurich). They posted “New Gravitational Wave Discoveries Enabled by Machine Learning” on arXiv on 10 July 2024. It appeared open access in Machine Learning: Science and Technology 6(1) 015054 on 27 February 2025 (received 20 September 2024, accepted 13 February 2025). Their ResNet-based code AresGW, with a new hierarchical classification of triggers by noise and frequency filters, ran on 6.7 months of LIGO Hanford-Livingston O3 data. They write: “we identify eight new GW candidates in the O3 data, with p_astro > 0.5 and a cumulative astrophysical probability of 5.94. This is the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm.” In the arXiv table, GW190511_125545 has p_astro 1.00 and false alarm rate 0.27 per year. The others are GW190614_134749 (0.99), GW190607_083827 (0.99), GW190904_104631 (0.72), GW190523_085933 (0.68), GW200208_211609 (0.55), GW190705_164632 (0.51) and GW190426_082124 (0.50). The text and Figure 2 call the first event GW190511_135545. With them, AresGW's total within its effective training range reached 42 events, against 34 and 36 for the two IAS catalogs cited. The paper reports no confirmation by other pipelines, and none was found. A September 2025 follow-up by the same group on the model's sensitivity “reveal[s] notable performance variations” across month-long datasets.", "category": "benefit created", "unexpected": false, "purpose": "AresGW was built to detect binary black hole signals in LIGO data faster than matched filtering. Finding new candidates was that purpose.", "system": "AresGW (ResNet-based deep learning gravitational-wave detection pipeline)", "model_version": "AresGW with hierarchical trigger classification (the 2025 follow-up refers to 'AresGW model 1')", "developer": "Aristotle University of Thessaloniki (Departments of Physics and Informatics) with the Swiss Data Science Center, ETH Zurich", "deployer": "The same research group, on public LIGO O3 data", "location": "Thessaloniki, Greece", "domain": "Astrophysics / gravitational-wave astronomy", "segment": "Academic research on public detector data", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The group's pipeline found eight new O3 candidates with p_astro above 0.5 beyond the catalogs it compares against, a measurable gain in detection capability. None is confirmed by another pipeline." }, { "group": "societal", "depth": null, "reason": "If real, the candidates add to the binary black hole population; no catalog has adopted them in the sources." } ], "ai_role": { "status": "assessed", "statement": "The deep-learning pipeline produced the candidate list and the ranking statistic. The authors computed p_astro from injections into O3 data. The developers are the authors, and the only source for the discovery is their own peer-reviewed paper and preprint. The paper itself calls the events candidates and reports no external confirmation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Koloniari AE, Koursoumpa EC, Nousi P, Lampropoulos P, Passalis N, Tefas A, Stergioulas N (2025). New gravitational wave discoveries enabled by machine learning. Machine Learning: Science and Technology 6(1):015054. Open access, CC BY 4.0. (Authored by the pipeline's developers.)", "title": "New gravitational wave discoveries enabled by machine learning", "url": "https://iopscience.iop.org/article/10.1088/2632-2153/adb5ed", "date": "2025-02-27", "written_by": "makers", "quote": "the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm" }, { "kind": "preprint", "citation": "Koloniari AE et al. (2024). New Gravitational Wave Discoveries Enabled by Machine Learning. arXiv:2407.07820, 10 July 2024 (table of the eight candidates with p_astro and false alarm rates). 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(Authored by the pipeline's developers.)", "title": "Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms", "url": "https://arxiv.org/abs/2509.05283", "date": "2025-09-05", "written_by": "makers", "quote": "Our findings reveal notable performance variations, highlighting the challenges introduced by finite-duration datasets and emphasizing the need for more rigorous statistical validation." } ], "replication": { "produced_by": [ "A ResNet trained on LIGO Hanford and Livingston data with hierarchical classification of triggers by noise and frequency filters", "6.7 months of coincident O3 data; significance from a logarithmic ranking statistic and injections into O3 data" ], "must_hold": [ "Sources within the effective training range (component masses 7 to 50 solar masses, chirp masses 10 to 40 solar masses)", "Two-detector coincidence; the network was not trained on Virgo data", "A follow-up by the same group found sensitivity varies notably between month-long datasets, so detection counts may not transfer" ], "echoes": [ { "date": "2025-09-05", "setting": "Same group re-evaluated AresGW model 1 on multiple month-long datasets of real detector noise (arXiv:2509.05283)", "model_version": "AresGW model 1", "outcome": "unknown", "source": "https://arxiv.org/abs/2509.05283" } ] }, "paired_incident": null, "headline": "AresGW finds eight new gravitational-wave candidates in LIGO O3", "metric": "eight new O3 candidates with p_astro > 0.5 (cumulative 5.94)", "comparator": { "against": "the matched-filtering catalogs (all GWTC pipelines, OGC, IASa and IASb) within AresGW's effective training range", "before": "36 events (all GWTC pipelines); 37 (OGC); 34 (IASa); 36 (IASb)", "after": "42", "basis": "measured", "quote": "This brings the total number of events detected by AresGW within its effective training range to 42, exceeding the total number of events detected by other pipelines.", "url": "https://arxiv.org/html/2407.07820" }, "later": { "status": "unknown", "date": null, "note": "The group's September 2025 follow-up re-evaluates the earlier 'AresGW model 1', not the model 2 that produced the eight candidates, and no confirmation or refutation of the candidates was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "Greece", "deployer_country": "Greece", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 2 for organizational on the documented outcome, with the reason stated on each rating.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/html/2407.07820", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Aristotle_University_of_Thessaloniki; https://en.wikipedia.org/wiki/Aristotle_University_of_Thessaloniki", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study and two preprints from the makers. 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https://en.wikipedia.org/wiki/Aristotle_University_of_Thessaloniki", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Astrophysics / gravitational-wave astronomy", "segment": "Academic research on public detector data" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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New gravitational wave discoveries enabled by machine learning. Machine Learning: Science and Technology 6(1):015054. Open access, CC BY 4.0. (Authored by the pipeline's developers.)", "title": "New gravitational wave discoveries enabled by machine learning", "url": "https://iopscience.iop.org/article/10.1088/2632-2153/adb5ed", "date": "2025-02-27", "written_by": "makers", "quote": "the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm" }, { "kind": "preprint", "citation": "Koloniari AE et al. (2024). New Gravitational Wave Discoveries Enabled by Machine Learning. arXiv:2407.07820, 10 July 2024 (table of the eight candidates with p_astro and false alarm rates). 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New gravitational wave discoveries enabled by machine learning. Machine Learning: Science and Technology 6(1):015054. Open access, CC BY 4.0. (Authored by the pipeline's developers.)", "title": "New gravitational wave discoveries enabled by machine learning", "url": "https://iopscience.iop.org/article/10.1088/2632-2153/adb5ed", "date": "2025-02-27", "written_by": "makers", "quote": "the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm" }, { "kind": "preprint", "citation": "Koloniari AE et al. (2024). New Gravitational Wave Discoveries Enabled by Machine Learning. arXiv:2407.07820, 10 July 2024 (table of the eight candidates with p_astro and false alarm rates). 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(Authored by the pipeline's developers.)", "title": "Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms", "url": "https://arxiv.org/abs/2509.05283", "date": "2025-09-05", "written_by": "makers", "quote": "Our findings reveal notable performance variations, highlighting the challenges introduced by finite-duration datasets and emphasizing the need for more rigorous statistical validation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Koloniari et al. (Mach. Learn.: Sci. Technol., 27 February 2025): the ResNet pipeline AresGW found eight new O3 candidates with p_astro > 0.5 (cumulative 5.94); none is confirmed by another pipeline.", "account": "The authors are Alexandra Koloniari, Evdokia Koursoumpa, Paraskevi Nousi, Paraskevas Lampropoulos, Nikolaos Passalis, Anastasios Tefas and Nikolaos Stergioulas. They are at Aristotle University of Thessaloniki and the Swiss Data Science Center (ETH Zurich). They posted “New Gravitational Wave Discoveries Enabled by Machine Learning” on arXiv on 10 July 2024. It appeared open access in Machine Learning: Science and Technology 6(1) 015054 on 27 February 2025 (received 20 September 2024, accepted 13 February 2025). Their ResNet-based code AresGW, with a new hierarchical classification of triggers by noise and frequency filters, ran on 6.7 months of LIGO Hanford-Livingston O3 data. They write: “we identify eight new GW candidates in the O3 data, with p_astro > 0.5 and a cumulative astrophysical probability of 5.94. This is the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm.” In the arXiv table, GW190511_125545 has p_astro 1.00 and false alarm rate 0.27 per year. The others are GW190614_134749 (0.99), GW190607_083827 (0.99), GW190904_104631 (0.72), GW190523_085933 (0.68), GW200208_211609 (0.55), GW190705_164632 (0.51) and GW190426_082124 (0.50). The text and Figure 2 call the first event GW190511_135545. With them, AresGW's total within its effective training range reached 42 events, against 34 and 36 for the two IAS catalogs cited. The paper reports no confirmation by other pipelines, and none was found. A September 2025 follow-up by the same group on the model's sensitivity “reveal[s] notable performance variations” across month-long datasets." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The pipeline detected and ranked possible gravitational-wave events." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. 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They are at Aristotle University of Thessaloniki and the Swiss Data Science Center (ETH Zurich). They posted “New Gravitational Wave Discoveries Enabled by Machine Learning” on arXiv on 10 July 2024. It appeared open access in Machine Learning: Science and Technology 6(1) 015054 on 27 February 2025 (received 20 September 2024, accepted 13 February 2025). Their ResNet-based code AresGW, with a new hierarchical classification of triggers by noise and frequency filters, ran on 6.7 months of LIGO Hanford-Livingston O3 data. They write: “we identify eight new GW candidates in the O3 data, with p_astro > 0.5 and a cumulative astrophysical probability of 5.94. This is the first identification of new coincident events in GW searches with a network of detectors by a machine-learning-based algorithm.” In the arXiv table, GW190511_125545 has p_astro 1.00 and false alarm rate 0.27 per year. The others are GW190614_134749 (0.99), GW190607_083827 (0.99), GW190904_104631 (0.72), GW190523_085933 (0.68), GW200208_211609 (0.55), GW190705_164632 (0.51) and GW190426_082124 (0.50). The text and Figure 2 call the first event GW190511_135545. With them, AresGW's total within its effective training range reached 42 events, against 34 and 36 for the two IAS catalogs cited. The paper reports no confirmation by other pipelines, and none was found. A September 2025 follow-up by the same group on the model's sensitivity “reveal[s] notable performance variations” across month-long datasets.", "replication": { "produced_by": [ "A ResNet trained on LIGO Hanford and Livingston data with hierarchical classification of triggers by noise and frequency filters", "6.7 months of coincident O3 data; significance from a logarithmic ranking statistic and injections into O3 data" ], "must_hold": [ "Sources within the effective training range (component masses 7 to 50 solar masses, chirp masses 10 to 40 solar masses)", "Two-detector coincidence; the network was not trained on Virgo data", "A follow-up by the same group found sensitivity varies notably between month-long datasets, so detection counts may not transfer" ], "echoes": [ { "date": "2025-09-05", "setting": "Same group re-evaluated AresGW model 1 on multiple month-long datasets of real detector noise (arXiv:2509.05283)", "model_version": "AresGW model 1", "outcome": "unknown", "source": "https://arxiv.org/abs/2509.05283" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0151", "title": "Columbia's STAR system found two motile sperm in a sample manual checks had called sperm-free; after 19 years of infertility the couple conceived and had a daughter", "summary": "STAR AI found 7 sperm (2 motile) in 2.5m images of a “sperm-free” sample; a couple infertile for 19 years conceived and had a girl.", "date_observed": "2025-03-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At Columbia University Fertility Center in New York, a 39-year-old man with non-obstructive azoospermia and his 37-year-old wife had tried for 19 years. TIME calls her “Rosie”. That included 15 failed IVF cycles and two surgical sperm extractions. His 3.5 mL semen sample, read as sperm-free by manual examination, was run through STAR. It captured about 2.5 million images in roughly two hours and detected seven sperm, two motile. The two motile sperm were injected into eggs and two embryos were transferred on day 3. A pregnancy test was positive 13 days later, in March 2025. The Lancet published the case on 31 October 2025. A girl was born in December 2025.", "category": "benefit created", "unexpected": false, "purpose": "STAR (Sperm Tracking and Recovery) was built over about five years at the Columbia University Fertility Center. It finds, and recovers undamaged, the few sperm in semen samples of men with azoospermia or cryptozoospermia. They can then be used for IVF by intracytoplasmic sperm injection. This pregnancy was exactly that intended use and its first clinical result.", "system": "STAR (Sperm Tracking and Recovery): a semen sample flows through a single-use microfluidic chip while a high-speed camera (about 300 frames per second, over 8 million images an hour) images it; an AI object-detection model flags sperm among cellular debris in real time and a microfluidic gate or robotic step diverts each flagged sperm into a droplet for immediate injection or freezing", "model_version": null, "developer": "Columbia University, Columbia University Irving Medical Center (team led by Zev Williams and Hemant Suryawanshi)", "deployer": "Columbia University, New York (used on its own patient)", "location": "New York, United States", "domain": "Healthcare - reproductive medicine (IVF for non-obstructive azoospermia)", "segment": "Academic fertility clinic and IVF laboratory", "benefit_type": "Improved Physical Health", "taxonomy_note": "A conception after azoospermia is read as a reproductive-health outcome.", "registry_ids": { "oecd_aim": "2025-11-03-2f05" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A healthy girl was born in December 2025 to a couple who had tried for 19 years through 15 failed IVF cycles and two surgeries. The husband had been told donor sperm or adoption were his only options (BBC, New York Post, DongA Science, NYT in syndication). The treatment enabled the couple to have a child after years of infertility." }, { "group": "organizational", "depth": 2, "reason": "The case became the clinic's published proof of STAR. The service launched in late 2025 at $3,000 per analysis, three systems are in operation and the waiting list runs to hundreds. STAR was named a TIME Best Invention of 2025 (Columbia service page, NYT in syndication, BBC, TIME). A material gain for one institution." } ], "ai_role": { "status": "assessed", "statement": "The detector flagged seven sperm, two motile, in roughly 2.5 million frames of a 3.5 mL sample that manual examination had called sperm-free. The microfluidic recovery step delivered them intact. Without a usable sperm the couple's remaining options were donor sperm or adoption. Everything after that was conventional IVF done by people. Embryologists injected the two motile sperm into one fresh and one thawed egg, cultured two embryos and transferred them on day 3. Obstetric care followed. Limits on the attribution: the much-quoted comparison (44 sperm in an hour after two days of manual search) concerns a different sample. Whether a longer manual search of this sample would have found the two sperm was not tested. The letter's model version is not stated in any source on record (INCIID reports a YOLOv8 architecture, Columbia's patent filings describe YOLOv4)." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Suryawanshi H, Gemmell LC, Morgan S, Koustas G, Prosser RW, Fu R, Forman EJ, Williams Z (2025). First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia. The Lancet 406(10516):2213-2214, research letter published online 31 October 2025 (received 15 May, accepted 4 August 2025), PMID 41183539. Written by the team that developed STAR; the clinical figures are reported by the press release, PTI, the Free Press Journal, StudyFinds and Republic World.", "title": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia", "url": "https://doi.org/10.1016/S0140-6736(25)01623-X", "date": "2025-10-31", "written_by": "makers", "quote": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia" }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025. Quotes two uninvolved specialists, Robert Brannigan (ASRM president-elect) and Allison K. Rodgers, in support, and one sceptic, Gianpiero Palermo.", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "Researchers at the Columbia University Fertility Center say this procedure, conducted in March, amounts to the first-known use of AI-enabled conception using this particular technology." }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025 (second quotation: Gianpiero Palermo of Weill Cornell Medicine, who pioneered intracytoplasmic sperm injection, on the risk of false hope; Brannigan asked for testing at other clinics and tracking of pregnancy rates).", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "You are attracting patients who have been told they have no sperm and offering what may turn out to be false hope" }, { "kind": "news report", "citation": "Park A (2025). Doctors Report the First Pregnancy Using a New AI Procedure. TIME, 10 June 2025. First report of the pregnancy: the wife, given the pseudonym Rosie, 38, became pregnant in March 2025 after nearly 19 years and 15 unsuccessful IVF cycles.", "title": "Doctors Report the First Pregnancy Using a New AI Procedure", "url": "https://time.com/7291154/doctors-report-first-pregnancy-new-ai-procedure/", "date": "2025-06-10", "written_by": "independent", "quote": "The system can scan eight million images in about an hour." }, { "kind": "news report", "citation": "Howard J (2025). A couple tried for 18 years to get pregnant. AI made it happen. CNN, 3 July 2025. Gives the December due date and Williams' estimate of a little under $3,000 to find, isolate and freeze sperm.", "title": "A couple tried for 18 years to get pregnant. AI made it happen", "url": "https://www.cnn.com/2025/07/03/health/ai-male-infertility-sperm-wellness", "date": "2025-07-03", "written_by": "independent", "quote": "hidden sperm were found, recovered and used to fertilize the wife’s eggs via IVF, and she became the first successful pregnancy enabled by the STAR method" }, { "kind": "news report", "citation": "FemTech World News Desk (2025). Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile. FemTech World, 13 June 2025.", "title": "Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile", "url": "https://www.femtechworld.co.uk/insight/doctors-report-first-pregnancy-using-ai-system-to-detect-sperm-in-men-previously-considered-infertile-aift25/", "date": "2025-06-13", "written_by": "independent", "quote": "scan around eight million images in an hour" }, { "kind": "news report", "citation": "Park A (2025). Columbia University STAR method. TIME, The Best Inventions of 2025, 9 October 2025.", "title": "Columbia University STAR method: The Best Inventions of 2025", "url": "https://time.com/collections/best-inventions-2025/7318439/columbia-university-star-method/", "date": "2025-10-09", "written_by": "independent", "quote": "After 20 years of trying, the first couple to use STAR is expecting their first child this year." }, { "kind": "news report", "citation": "Quintanar S (2025). This AI-imaging tech from Columbia researchers is solving male infertility. Columbia Daily Spectator, 26 October 2025 (student newspaper; confirms the 15 unsuccessful IVF cycles).", "title": "This AI-imaging tech from Columbia researchers is solving male infertility", "url": "https://www.columbiaspectator.com/news/2025/10/26/this-ai-imaging-tech-from-columbia-researchers-is-solving-male-infertility/", "date": "2025-10-26", "written_by": "independent", "quote": "After trying to conceive for nearly two decades, a couple successfully received a positive pregnancy test after using the STAR system." }, { "kind": "news report", "citation": "PTI via The Economic Times (2025). How AI helped an infertile couple conceive after 19 years with just '2 sperm'. The Economic Times, 3 November 2025; one of the fourteen sources cited by the OECD Monitor. Gives 2.5 million images over two hours, seven sperm of which two viable, positive test 13 days after transfer, and a heartbeat of 172 beats per minute at eight weeks.", "title": "How AI helped an infertile couple conceive after 19 years with just '2 sperm'", "url": "https://economictimes.indiatimes.com/news/india/how-ai-helped-an-infertile-couple-conceive-after-19-years-with-just-2-sperm/articleshow/125051307.cms", "date": "2025-11-03", "written_by": "independent", "quote": "picked out just two healthy sperm cells, helping a US couple conceive after 19 years of trying, a report in The Lancet said" }, { "kind": "news report", "citation": "Kanchwala T (2025). How AI Helped This Couple Get Pregnant After 19-Year Wait. Free Press Journal, 4 November 2025; cited by the OECD Monitor. Gives the 3.5 mL sample judged sperm-free by manual checks, day-3 transfer, positive test 13 days later and transition to standard obstetric care.", "title": "How AI Helped This Couple Get Pregnant After 19-Year Wait", "url": "https://www.freepressjournal.in/tech/how-ai-helped-this-couple-get-pregnant-after-19-year-wait", "date": "2025-11-04", "written_by": "independent", "quote": "Over approximately two hours, the AI processed a staggering 2.5 million images, detecting seven individual sperm cells: two motile (capable of movement) and five non-motile." }, { "kind": "news report", "citation": "Pathak P (2025). After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby. Republic World, 4 November 2025; cited by the OECD Monitor. Reports 19 egg-retrieval cycles at four fertility centres and a confirmed pregnancy at eight weeks; the headline's 'welcomes miracle baby' is ahead of its own text, which reports a pregnancy, not a birth.", "title": "After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby", "url": "https://www.republicworld.com/tech/after-19-years-of-infertility-ai-finds-2-sperm-from-25-million-images-couple-welcomes-miracle-baby", "date": "2025-11-04", "written_by": "independent", "quote": "In just two hours, the STAR system scanned 2.5 million microscopic images of the man's semen sample and detected seven sperm, two of which were alive and motile." }, { "kind": "news report", "citation": "David A (2025). AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University. The Daily Jagran, 4 November 2025; cited by the OECD Monitor.", "title": "AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University", "url": "https://www.thedailyjagran.com/technology/ai-helps-couple-conceive-after-20-years-of-infertility-a-medical-breakthrough-from-columbia-university-10277754", "date": "2025-11-04", "written_by": "independent", "quote": "the STAR system identified seven sperm cells; two of which were active." }, { "kind": "news report", "citation": "Pall O (2025). After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First. Mashable India, 5 November 2025; cited by the OECD Monitor.", "title": "After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First", "url": "https://in.mashable.com/tech/102002/after-19-years-of-failed-ivf-attempts-ai-helps-couple-conceive-in-groundbreaking-first", "date": "2025-11-05", "written_by": "independent", "quote": "Experts caution that while this case is inspiring, it represents an early-stage success. Larger-scale trials are needed before AI-assisted sperm detection becomes standard clinical practice." }, { "kind": "news report", "citation": "Anderer J (2025). AI detects invisible sperm, leads to couple's first pregnancy after 19 years. StudyFinds, 3 November 2025. Reports from the letter: 19 egg retrievals across four centres over 11 years, two testicular extractions, one fresh and one thawed egg injected with the motile sperm, two non-motile sperm injected without progression, day-3 transfer, 8 weeks with a fetal heart rate of 172, Havens Innovation Fund support, and patent applications held by Suryawanshi and Williams through Columbia.", "title": "AI detects invisible sperm, leads to couple's first pregnancy after 19 years", "url": "https://studyfinds.com/ai-detects-invisible-sperm/", "date": "2025-11-03", "written_by": "independent", "quote": "the first reported clinical pregnancy resulting from AI-guided sperm recovery" }, { "kind": "news report", "citation": "Hong A-reum (2025). AI pinpoints rare sperm and enables successful IVF pregnancy in US study. Chosunbiz, 1 November 2025.", "title": "AI pinpoints rare sperm and enables successful IVF pregnancy in US study", "url": "https://biz.chosun.com/en/en-science/2025/11/01/DUEJDMOPVVAINJVKBQ2ERLB6DU/", "date": "2025-11-01", "written_by": "independent", "quote": "STAR analyzes more than 8 million microscopic semen images per hour." }, { "kind": "news report", "citation": "Jo G (2025). \"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm. DongA Science, 3 November 2025.", "title": "\"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm", "url": "https://www.dongascience.com/en/news/74880", "date": "2025-11-03", "written_by": "independent", "quote": "A recent study reported a successful pregnancy after using AI to find two sperm in the semen of a patient with azoospermia." }, { "kind": "news report", "citation": "Cerati F (2025). First baby thanks to artificial intelligence and robots: a breakthrough in male infertility. Il Sole 24 Ore (English edition), 3 November 2025; despite the headline, the text reports a pregnancy, not a birth.", "title": "First baby thanks to artificial intelligence and robots: a breakthrough in male infertility", "url": "https://en.ilsole24ore.com/art/first-baby-thanks-to-artificial-intelligence-and-robot-breakthrough-in-male-infertility-AH8Kc0WD", "date": "2025-11-03", "written_by": "independent", "quote": "It only takes one healthy spermatozoon to create an embryo" }, { "kind": "news report", "citation": "Dixit M (2025). ‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years. Interesting Engineering, 31 October 2025 (HTML title: Columbia University reports first pregnancy using AI sperm recovery). Notes the result is based on a single case.", "title": "‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years", "url": "https://interestingengineering.com/science/breakthrough-ai-helps-infertile-man", "date": "2025-10-31", "written_by": "independent", "quote": "being further evaluated through larger clinical studies" }, { "kind": "news report", "citation": "Kohli KK (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia: Study. Medical Dialogues, 24 December 2025; confirms the Lancet item is a research letter.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia: Study", "url": "https://medicaldialogues.in/obstetrics-gynaecology/news/first-pregnancy-with-ai-guided-sperm-recovery-method-developed-at-columbia-study-160260", "date": "2025-12-24", "written_by": "independent", "quote": "The case is described in a research letter published in The Lancet." }, { "kind": "news report", "citation": "Padhy K (2026). Finding 'hidden sperm': New technique offers hope to men previously told they were infertile. BBC Future, 30 April 2026. Reports the birth at the end of 2025, sperm found in just under 30% of the latest 175 patients, and a second STAR pregnancy (a Klinefelter patient's micro-TESE tissue).", "title": "Finding 'hidden sperm': New technique offers hope to men previously told they were infertile", "url": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile", "date": "2026-04-30", "written_by": "independent", "quote": "the first baby to be born using the Star system allowed a couple who had battled with infertility for almost two decades to finally have a child" }, { "kind": "news report", "citation": "Medaris A (2026). 'AI babies' are being conceived in 'previously impossible' ways: all about the new IVF tech. New York Post, 13 May 2026.", "title": "Inside the new IVF tech giving rise to 'AI babies'", "url": "https://nypost.com/2026/05/13/health/inside-the-new-ivf-tech-giving-rise-to-ai-babies/", "date": "2026-05-13", "written_by": "independent", "quote": "The first baby born to a dad with the diagnosis using STAR was born in December." }, { "kind": "news report", "citation": "Jo G (2026). Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive. DongA Science, 3 May 2026. Also reports sperm found in about 30% of 175 patients.", "title": "Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive", "url": "https://www.dongascience.com/en/news/77712", "date": "2026-05-03", "written_by": "independent", "quote": "The first baby born through STAR is a healthy girl." }, { "kind": "news report", "citation": "Zaleski A (2026). A.I. Is Finding Sperm Where Doctors Couldn't. The New York Times, 11 August 2026 (nytimes.com/2026/08/11/science/ai-infertile-men-sperm.html), read in the syndicated copy carried by The Star (Malaysia) on 13 August 2026. Reports 175 cases with sperm recovered 26% of the time, three systems in operation at Columbia only, and that STAR cannot help men who produce no sperm.", "title": "AI is finding sperm where doctors couldn't", "url": "https://www.thestar.com.my/tech/tech-news/2026/08/13/ai-is-finding-sperm-where-doctors-couldnt", "date": "2026-08-13", "written_by": "independent", "quote": "Sperm were found after the 39-year-old man’s sample was run through the Star system, and that couple now has a baby girl." }, { "kind": "news report", "citation": "Vega E (2026). A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far. Medical Daily, 12 August 2026. Notes one published pregnancy, no controlled trials and no published success rates.", "title": "A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far", "url": "https://www.medicaldaily.com/ai-sperm-detection-azoospermia-star-method-evidence-477211", "date": "2026-08-12", "written_by": "independent", "quote": "slow, physically fatiguing and inherently incomplete: a technician cannot examine every field of view in a sample within a workable timeframe." }, { "kind": "report", "citation": "INCIID, The InterNational Council on Infertility Information Dissemination (2026). STAR (Sperm Tracking and Recovery) System. inciid.org, 14 May 2026 (modified 5 October 2026). Patient-organisation summary: YOLOv8 detector with precision 0.89 and recall 0.90, about 40 times more sperm than manual search, and patent applications filed by Columbia.", "title": "STAR (Sperm Tracking and Recovery) System", "url": "https://inciid.org/star-sperm-tracking-and-recovery-system/", "date": "2026-05-14", "written_by": "independent", "quote": "The technology integrates high-speed imaging, artificial intelligence, microfluidics, and robotics to perform non-invasive sperm detection and retrieval." }, { "kind": "press release", "citation": "Columbia University Irving Medical Center (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia. Press release via EurekAlert!, 31 October 2025. Gives 3.5 mL sample, 2.5 million images in about two hours, two viable sperm, two embryos; funding from the Havens Innovation Fund.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia", "url": "https://www.eurekalert.org/news-releases/1104028", "date": "2025-10-31", "written_by": "makers", "quote": "You only need one healthy sperm to create an embryo" }, { "kind": "press release", "citation": "Columbia University Fertility Center (2026). Sperm Tracking and Recovery (STAR). Service page on columbiadoctors.org, fetched 20 October 2026. Prices the analysis at $3,000 ($1,500 if no sperm are found), not billable to insurance, and reports about 28% of prior-azoospermia patients with sperm found, about 20% of mature eggs fertilising and about 18% of fertilised eggs reaching good-quality embryos.", "title": "Sperm Tracking and Recovery (STAR)", "url": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center/our-services/sperm-tracking-and-recovery-star", "date": null, "written_by": "makers", "quote": "STAR achieved its first reported pregnancy in March 2025." }, { "kind": "press release", "citation": "Columbia University Fertility Center (2025). Columbia Fertility Looks to the Stars to Help Men with Infertility. columbiadoctors.org, dated 9 October 2025, fetched 20 October 2026. The Internet Archive copy of 1 November 2025 ends the couple's sentence 'and start a pregnancy'; the live page now reads 'and deliver a healthy baby girl', so the birth was added after that date.", "title": "Columbia Fertility Looks to the Stars to Help Men with Infertility", "url": "https://www.columbiadoctors.org/news/columbia-fertility-looks-stars-help-men-infertility", "date": "2025-10-09", "written_by": "makers", "quote": "Since STAR was unveiled in 2024, it has been used to help dozens of patients at the Columbia University Fertility Center." }, { "kind": "press release", "citation": "Gary H (2025). Columbia Develops STAR Technology for Men with Infertility. Columbia Medicine magazine, Vagelos College of Physicians and Surgeons, Fall 2025.", "title": "Columbia Develops STAR Technology for Men with Infertility", "url": "https://www.vagelos.columbia.edu/about-us/columbia-medicine-magazine/archives/fall-2025/clinical-advances/columbia-develops-star-technology-men-infertility", "date": null, "written_by": "makers", "quote": "like trying to find a needle hidden among a thousand haystacks—but doing it within one hour" }, { "kind": "press release", "citation": "NewYork-Presbyterian (2025). Ep38: Building an AI-Powered System to Improve Fertility Success. Advances in Care podcast with Zev Williams, 7 August 2025.", "title": "Ep38: Building an AI-Powered System to Improve Fertility Success", "url": "https://www.nyp.org/advances/podcast/building-an-ai-powered-system-to-improve-fertility-success", "date": "2025-08-07", "written_by": "makers", "quote": "about four months pregnant with a healthy, ongoing pregnancy" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2025). Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample. US patent application US20250264398A1, priority 27 July 2022, published 21 August 2025; describes a YOLO (YOLOv4) detector, 100-500 frames per second and a flow channel 10-50 micrometres high.", "title": "Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample", "url": "https://patents.google.com/patent/US20250264398A1/en", "date": "2025-08-21", "written_by": "makers", "quote": "Biological cells can be identified and recovered from a sample by pumping the sample through a flow channel" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2026). Microfluidic device for recovering rare biological cells from a sample. PCT application WO2026019779A1, priority 17 July 2024, published 22 January 2026.", "title": "Microfluidic device for recovering rare biological cells from a sample", "url": "https://patents.google.com/patent/WO2026019779A1/en", "date": "2026-01-22", "written_by": "makers", "quote": "Sperm cells can be extracted from a sample by passing the sample through a microfluidic device, capturing images of the sample" }, { "kind": "peer-reviewed study", "citation": "Gemmell LC, Suryawanshi H, Williams Z (2026). AI-based techniques in sperm detection. Current Opinion in Urology, published 22 July 2026. Review by the STAR team; abstract read on Europe PMC.", "title": "AI-based techniques in sperm detection", "url": "https://doi.org/10.1097/MOU.0000000000001430", "date": "2026-07-22", "written_by": "makers", "quote": "Early clinical data suggest these approaches may enable sperm recovery in patients previously considered sperm-negative by conventional methods." } ], "replication": { "produced_by": [ "A man with non-obstructive azoospermia whose 3.5 mL ejaculate still held a handful of sperm (seven, two motile). Manual microscopy and two surgical extractions had missed them. He did produce some sperm.", "STAR's full pipeline on that sample: flow through a single-use microfluidic chip and a high-speed camera capturing about 2.5 million frames in roughly two hours. An AI detector flagged sperm among debris. A gate or robotic step diverted each flagged sperm gently enough to leave it usable.", "A partner with mature eggs available (one fresh, one thawed). An IVF laboratory able to inject the two motile sperm, culture two embryos and transfer them on day 3.", "About five years of in-house development at an academic fertility center staffed with embryologists, microfabrication, machine-learning and robotics specialists. A couple who kept trying after 15 failed IVF cycles." ], "must_hold": [ "Some sperm must exist in the sample. STAR finds sperm, it does not create them, and it cannot help men who produce none (NYT in syndication; Williams in the Washington Post).", "Rates are low even at Columbia. About 28% of prior-azoospermia patients have sperm found, about 20% of mature eggs fertilize and about 18% of fertilized eggs become good-quality embryos (service page). Across 175 cases sperm were recovered in 26% (NYT) to just under 30% (BBC).", "The evidence is one peer-reviewed case plus clinic-reported series. As of August 2026: no controlled trial and no published success rate (Medical Daily). ICSI pioneer Gianpiero Palermo warned the approach may sell false hope (Washington Post).", "Access is narrow. Three systems at one New York clinic (NYT), $3,000 per analysis or $1,500 if nothing is found, not billable to insurance (service page)." ], "echoes": [] }, "paired_incident": null, "headline": "STAR finds two motile sperm; couple conceives after 19 years", "metric": "found 7 sperm (2 motile) in 2.5m images of a “sperm-free” sample", "comparator": null, "later": { "status": "scaled", "date": "2026-04-30", "note": "By April 2026 the first STAR baby, a girl, had been born at the end of 2025, STAR was in regular use at Columbia with hundreds on the waiting list, sperm had been found in just under 30% of the latest 175 patients, and a second pregnancy (from testicular tissue, a boy due July 2026) was reported; Medical Daily (August 2026) notes that only one pregnancy has been published in peer-reviewed form.", "quote": "Since the arrival of the first Star baby, the technology has been used regularly at the fertility centre, with the waiting list of people hoping to conceive growing to hundreds from all around the world. Based on the latest 175 patients to have used the technology, Williams says they are finding sperm in just under 30% of cases.", "url": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-11-03-2f05", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile; https://inciid.org/star-sperm-tracking-and-recovery-system/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center; https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Columbia University.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Separated the reported AI model from its release and corrected the system identity against the retained evidence.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, 22 independent news reports, two peer-reviewed studies from the makers, five press releases from the makers and two other sources from the makers. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0151", "catalog_version": "1.0.0", "source_fingerprint": "24833b4ff5afe3799bee7da830cd27fc0fdb6055ebf64f1e2ac9435b9b1e57ec", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0151-source-0001", "AIBD-0151-source-0002", "AIBD-0151-source-0003", "AIBD-0151-source-0004", "AIBD-0151-source-0005", "AIBD-0151-source-0006", "AIBD-0151-source-0007", "AIBD-0151-source-0008", "AIBD-0151-source-0009", "AIBD-0151-source-0010", "AIBD-0151-source-0011", "AIBD-0151-source-0012", "AIBD-0151-source-0013", "AIBD-0151-source-0014", "AIBD-0151-source-0015", "AIBD-0151-source-0016", "AIBD-0151-source-0017", "AIBD-0151-source-0018", "AIBD-0151-source-0019", "AIBD-0151-source-0020", "AIBD-0151-source-0021", "AIBD-0151-source-0022", "AIBD-0151-source-0023", "AIBD-0151-source-0024", "AIBD-0151-source-0025", "AIBD-0151-source-0026", "AIBD-0151-source-0027", "AIBD-0151-source-0028", "AIBD-0151-source-0029", "AIBD-0151-source-0030", "AIBD-0151-source-0031", "AIBD-0151-source-0032", "AIBD-0151-source-0033" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Columbia University, Columbia University Irving Medical Center (team led by Zev Williams and Hemant Suryawanshi)", "deployer": "Columbia University, New York (used on its own patient)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The detector flagged seven sperm, two motile, in roughly 2.5 million frames of a 3.5 mL sample that manual examination had called sperm-free. The microfluidic recovery step delivered them intact. Without a usable sperm the couple's remaining options were donor sperm or adoption. Everything after that was conventional IVF done by people. Embryologists injected the two motile sperm into one fresh and one thawed egg, cultured two embryos and transferred them on day 3. Obstetric care followed. Limits on the attribution: the much-quoted comparison (44 sperm in an hour after two days of manual search) concerns a different sample. Whether a longer manual search of this sample would have found the two sperm was not tested. The letter's model version is not stated in any source on record (INCIID reports a YOLOv8 architecture, Columbia's patent filings describe YOLOv4)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "STAR detected seven sperm, including two motile sperm, in a sample that manual examination had classified as sperm-free. The system recovered them for use in IVF.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The detector flagged seven sperm, two motile, in roughly 2.5 million frames of a 3.5 mL sample that manual examination had called sperm-free. The microfluidic recovery step delivered them intact. Without a usable sperm the couple's remaining options were donor sperm or adoption. Everything after that was conventional IVF done by people. Embryologists injected the two motile sperm into one fresh and one thawed egg, cultured two embryos and transferred them on day 3. Obstetric care followed. Limits on the attribution: the much-quoted comparison (44 sperm in an hour after two days of manual search) concerns a different sample. Whether a longer manual search of this sample would have found the two sperm was not tested. The letter's model version is not stated in any source on record (INCIID reports a YOLOv8 architecture, Columbia's patent filings describe YOLOv4)." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A healthy girl was born in December 2025 to a couple who had tried for 19 years through 15 failed IVF cycles and two surgeries. The husband had been told donor sperm or adoption were his only options (BBC, New York Post, DongA Science, NYT in syndication). The treatment enabled the couple to have a child after years of infertility." }, { "group": "organizational", "depth": 2, "reason": "The case became the clinic's published proof of STAR. The service launched in late 2025 at $3,000 per analysis, three systems are in operation and the waiting list runs to hundreds. STAR was named a TIME Best Invention of 2025 (Columbia service page, NYT in syndication, BBC, TIME). A material gain for one institution." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report, 22 independent news reports, two peer-reviewed studies from the makers, five press releases from the makers and two other sources from the makers. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A healthy girl was born in December 2025 to a couple who had tried for 19 years through 15 failed IVF cycles and two surgeries. The husband had been told donor sperm or adoption were his only options (BBC, New York Post, DongA Science, NYT in syndication). The treatment enabled the couple to have a child after years of infertility." }, { "group": "organizational", "depth": 2, "reason": "The case became the clinic's published proof of STAR. The service launched in late 2025 at $3,000 per analysis, three systems are in operation and the waiting list runs to hundreds. STAR was named a TIME Best Invention of 2025 (Columbia service page, NYT in syndication, BBC, TIME). A material gain for one institution." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The couple had a healthy daughter after 19 years of infertility, 15 failed IVF cycles, and two surgical sperm extractions. Columbia published the clinical result and introduced STAR as a paid service. The evidence establishes a major benefit for this couple, without establishing the treatment’s overall success rate." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A healthy girl was born in December 2025 to a couple who had tried for 19 years through 15 failed IVF cycles and two surgeries. The husband had been told donor sperm or adoption were his only options (BBC, New York Post, DongA Science, NYT in syndication). The treatment enabled the couple to have a child after years of infertility." }, { "group": "organizational", "depth": 2, "reason": "The case became the clinic's published proof of STAR. The service launched in late 2025 at $3,000 per analysis, three systems are in operation and the waiting list runs to hundreds. STAR was named a TIME Best Invention of 2025 (Columbia service page, NYT in syndication, BBC, TIME). A material gain for one institution." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "value_present", "value": { "kind": "text", "text": "As described in the sources, three STAR systems operated at one New York clinic. An analysis cost US$3,000, or US$1,500 if no sperm were found, and was not billable to insurance." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "replication", "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "As described in the sources, three STAR systems operated at one New York clinic. An analysis cost US$3,000, or US$1,500 if no sperm were found, and was not billable to insurance." } }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "In this sample, STAR recovered seven sperm after manual examination had found none. News reports give sperm recovery in roughly 26% to 30% of a series of 175 cases. The clinic separately reports that about 20% of mature eggs fertilize and about 18% of fertilized eggs become good-quality embryos. These figures describe different stages, not an overall chance of a live birth." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Sperm recovered, sperm motility, pregnancy, and live birth." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "One 3.5 mL semen sample from a 39-year-old man with non-obstructive azoospermia." } }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The comparison of 44 sperm found in an hour concerns another sample. This study did not test whether a longer manual search would have found the sperm. The evidence includes one peer-reviewed case and clinic-reported series, without a controlled trial or a published overall pregnancy success rate as of August 2026." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-11-03-2f05" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-04-30", "note": "By April 2026 the first STAR baby, a girl, had been born at the end of 2025, STAR was in regular use at Columbia with hundreds on the waiting list, sperm had been found in just under 30% of the latest 175 patients, and a second pregnancy (from testicular tissue, a boy due July 2026) was reported; Medical Daily (August 2026) notes that only one pregnancy has been published in peer-reviewed form.", "quote": "Since the arrival of the first Star baby, the technology has been used regularly at the fertility centre, with the waiting list of people hoping to conceive growing to hundreds from all around the world. Based on the latest 175 patients to have used the technology, Williams says they are finding sperm in just under 30% of cases.", "url": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Embryologists injected the two motile sperm into eggs, cultured the embryos, and transferred them. Clinicians provided subsequent obstetric care." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0151" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "The couple who underwent treatment at Columbia University Fertility Center." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The couple who underwent treatment at Columbia University Fertility Center." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "One couple." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "One couple." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "A conception after azoospermia is read as a reproductive-health outcome." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At Columbia University Fertility Center in New York, a 39-year-old man with non-obstructive azoospermia and his 37-year-old wife had tried for 19 years. TIME calls her “Rosie”. That included 15 failed IVF cycles and two surgical sperm extractions. His 3.5 mL semen sample, read as sperm-free by manual examination, was run through STAR. It captured about 2.5 million images in roughly two hours and detected seven sperm, two motile. The two motile sperm were injected into eggs and two embryos were transferred on day 3. A pregnancy test was positive 13 days later, in March 2025. The Lancet published the case on 31 October 2025. A girl was born in December 2025.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "STAR recovered two motile sperm that clinicians used in IVF. The couple conceived and had a daughter after 19 years of infertility." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A healthy girl was born in December 2025 to a couple who had tried for 19 years through 15 failed IVF cycles and two surgeries. The husband had been told donor sperm or adoption were his only options (BBC, New York Post, DongA Science, NYT in syndication). The treatment enabled the couple to have a child after years of infertility." }, { "group": "organizational", "depth": 2, "reason": "The case became the clinic's published proof of STAR. The service launched in late 2025 at $3,000 per analysis, three systems are in operation and the waiting list runs to hundreds. STAR was named a TIME Best Invention of 2025 (Columbia service page, NYT in syndication, BBC, TIME). A material gain for one institution." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "STAR (Sperm Tracking and Recovery) was built over about five years at the Columbia University Fertility Center. It finds, and recovers undamaged, the few sperm in semen samples of men with azoospermia or cryptozoospermia. They can then be used for IVF by intracytoplasmic sperm injection. This pregnancy was exactly that intended use and its first clinical result." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "New York, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "STAR (Sperm Tracking and Recovery) was built over about five years at the Columbia University Fertility Center. It finds, and recovers undamaged, the few sperm in semen samples of men with azoospermia or cryptozoospermia. They can then be used for IVF by intracytoplasmic sperm injection. This pregnancy was exactly that intended use and its first clinical result." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-11-03-2f05", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile; https://inciid.org/star-sperm-tracking-and-recovery-system/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center; https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Columbia University.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Separated the reported AI model from its release and corrected the system identity against the retained evidence.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A man with non-obstructive azoospermia whose 3.5 mL ejaculate still held a handful of sperm (seven, two motile). Manual microscopy and two surgical extractions had missed them. He did produce some sperm.", "STAR's full pipeline on that sample: flow through a single-use microfluidic chip and a high-speed camera capturing about 2.5 million frames in roughly two hours. An AI detector flagged sperm among debris. A gate or robotic step diverted each flagged sperm gently enough to leave it usable.", "A partner with mature eggs available (one fresh, one thawed). An IVF laboratory able to inject the two motile sperm, culture two embryos and transfer them on day 3.", "About five years of in-house development at an academic fertility center staffed with embryologists, microfabrication, machine-learning and robotics specialists. A couple who kept trying after 15 failed IVF cycles." ], "must_hold": [ "Some sperm must exist in the sample. STAR finds sperm, it does not create them, and it cannot help men who produce none (NYT in syndication; Williams in the Washington Post).", "Rates are low even at Columbia. About 28% of prior-azoospermia patients have sperm found, about 20% of mature eggs fertilize and about 18% of fertilized eggs become good-quality embryos (service page). Across 175 cases sperm were recovered in 26% (NYT) to just under 30% (BBC).", "The evidence is one peer-reviewed case plus clinic-reported series. As of August 2026: no controlled trial and no published success rate (Medical Daily). ICSI pioneer Gianpiero Palermo warned the approach may sell false hope (Washington Post).", "Access is narrow. Three systems at one New York clinic (NYT), $3,000 per analysis or $1,500 if nothing is found, not billable to insurance (service page)." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The sample must contain sperm. A fertility laboratory must be able to recover viable sperm and use them for intracytoplasmic sperm injection, then culture and transfer embryos." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-11-03-2f05", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile; https://inciid.org/star-sperm-tracking-and-recovery-system/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center; https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Columbia University.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Separated the reported AI model from its release and corrected the system identity against the retained evidence.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - reproductive medicine (IVF for non-obstructive azoospermia)", "segment": "Academic fertility clinic and IVF laboratory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Suryawanshi H, Gemmell LC, Morgan S, Koustas G, Prosser RW, Fu R, Forman EJ, Williams Z (2025). First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia. The Lancet 406(10516):2213-2214, research letter published online 31 October 2025 (received 15 May, accepted 4 August 2025), PMID 41183539. Written by the team that developed STAR; the clinical figures are reported by the press release, PTI, the Free Press Journal, StudyFinds and Republic World.", "title": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia", "url": "https://doi.org/10.1016/S0140-6736(25)01623-X", "date": "2025-10-31", "written_by": "makers", "quote": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia" }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025. Quotes two uninvolved specialists, Robert Brannigan (ASRM president-elect) and Allison K. Rodgers, in support, and one sceptic, Gianpiero Palermo.", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "Researchers at the Columbia University Fertility Center say this procedure, conducted in March, amounts to the first-known use of AI-enabled conception using this particular technology." }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025 (second quotation: Gianpiero Palermo of Weill Cornell Medicine, who pioneered intracytoplasmic sperm injection, on the risk of false hope; Brannigan asked for testing at other clinics and tracking of pregnancy rates).", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "You are attracting patients who have been told they have no sperm and offering what may turn out to be false hope" }, { "kind": "news report", "citation": "Park A (2025). Doctors Report the First Pregnancy Using a New AI Procedure. TIME, 10 June 2025. First report of the pregnancy: the wife, given the pseudonym Rosie, 38, became pregnant in March 2025 after nearly 19 years and 15 unsuccessful IVF cycles.", "title": "Doctors Report the First Pregnancy Using a New AI Procedure", "url": "https://time.com/7291154/doctors-report-first-pregnancy-new-ai-procedure/", "date": "2025-06-10", "written_by": "independent", "quote": "The system can scan eight million images in about an hour." }, { "kind": "news report", "citation": "Howard J (2025). A couple tried for 18 years to get pregnant. AI made it happen. CNN, 3 July 2025. Gives the December due date and Williams' estimate of a little under $3,000 to find, isolate and freeze sperm.", "title": "A couple tried for 18 years to get pregnant. AI made it happen", "url": "https://www.cnn.com/2025/07/03/health/ai-male-infertility-sperm-wellness", "date": "2025-07-03", "written_by": "independent", "quote": "hidden sperm were found, recovered and used to fertilize the wife’s eggs via IVF, and she became the first successful pregnancy enabled by the STAR method" }, { "kind": "news report", "citation": "FemTech World News Desk (2025). Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile. FemTech World, 13 June 2025.", "title": "Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile", "url": "https://www.femtechworld.co.uk/insight/doctors-report-first-pregnancy-using-ai-system-to-detect-sperm-in-men-previously-considered-infertile-aift25/", "date": "2025-06-13", "written_by": "independent", "quote": "scan around eight million images in an hour" }, { "kind": "news report", "citation": "Park A (2025). Columbia University STAR method. TIME, The Best Inventions of 2025, 9 October 2025.", "title": "Columbia University STAR method: The Best Inventions of 2025", "url": "https://time.com/collections/best-inventions-2025/7318439/columbia-university-star-method/", "date": "2025-10-09", "written_by": "independent", "quote": "After 20 years of trying, the first couple to use STAR is expecting their first child this year." }, { "kind": "news report", "citation": "Quintanar S (2025). This AI-imaging tech from Columbia researchers is solving male infertility. Columbia Daily Spectator, 26 October 2025 (student newspaper; confirms the 15 unsuccessful IVF cycles).", "title": "This AI-imaging tech from Columbia researchers is solving male infertility", "url": "https://www.columbiaspectator.com/news/2025/10/26/this-ai-imaging-tech-from-columbia-researchers-is-solving-male-infertility/", "date": "2025-10-26", "written_by": "independent", "quote": "After trying to conceive for nearly two decades, a couple successfully received a positive pregnancy test after using the STAR system." }, { "kind": "news report", "citation": "PTI via The Economic Times (2025). How AI helped an infertile couple conceive after 19 years with just '2 sperm'. The Economic Times, 3 November 2025; one of the fourteen sources cited by the OECD Monitor. Gives 2.5 million images over two hours, seven sperm of which two viable, positive test 13 days after transfer, and a heartbeat of 172 beats per minute at eight weeks.", "title": "How AI helped an infertile couple conceive after 19 years with just '2 sperm'", "url": "https://economictimes.indiatimes.com/news/india/how-ai-helped-an-infertile-couple-conceive-after-19-years-with-just-2-sperm/articleshow/125051307.cms", "date": "2025-11-03", "written_by": "independent", "quote": "picked out just two healthy sperm cells, helping a US couple conceive after 19 years of trying, a report in The Lancet said" }, { "kind": "news report", "citation": "Kanchwala T (2025). How AI Helped This Couple Get Pregnant After 19-Year Wait. Free Press Journal, 4 November 2025; cited by the OECD Monitor. Gives the 3.5 mL sample judged sperm-free by manual checks, day-3 transfer, positive test 13 days later and transition to standard obstetric care.", "title": "How AI Helped This Couple Get Pregnant After 19-Year Wait", "url": "https://www.freepressjournal.in/tech/how-ai-helped-this-couple-get-pregnant-after-19-year-wait", "date": "2025-11-04", "written_by": "independent", "quote": "Over approximately two hours, the AI processed a staggering 2.5 million images, detecting seven individual sperm cells: two motile (capable of movement) and five non-motile." }, { "kind": "news report", "citation": "Pathak P (2025). After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby. Republic World, 4 November 2025; cited by the OECD Monitor. Reports 19 egg-retrieval cycles at four fertility centres and a confirmed pregnancy at eight weeks; the headline's 'welcomes miracle baby' is ahead of its own text, which reports a pregnancy, not a birth.", "title": "After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby", "url": "https://www.republicworld.com/tech/after-19-years-of-infertility-ai-finds-2-sperm-from-25-million-images-couple-welcomes-miracle-baby", "date": "2025-11-04", "written_by": "independent", "quote": "In just two hours, the STAR system scanned 2.5 million microscopic images of the man's semen sample and detected seven sperm, two of which were alive and motile." }, { "kind": "news report", "citation": "David A (2025). AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University. The Daily Jagran, 4 November 2025; cited by the OECD Monitor.", "title": "AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University", "url": "https://www.thedailyjagran.com/technology/ai-helps-couple-conceive-after-20-years-of-infertility-a-medical-breakthrough-from-columbia-university-10277754", "date": "2025-11-04", "written_by": "independent", "quote": "the STAR system identified seven sperm cells; two of which were active." }, { "kind": "news report", "citation": "Pall O (2025). After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First. Mashable India, 5 November 2025; cited by the OECD Monitor.", "title": "After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First", "url": "https://in.mashable.com/tech/102002/after-19-years-of-failed-ivf-attempts-ai-helps-couple-conceive-in-groundbreaking-first", "date": "2025-11-05", "written_by": "independent", "quote": "Experts caution that while this case is inspiring, it represents an early-stage success. Larger-scale trials are needed before AI-assisted sperm detection becomes standard clinical practice." }, { "kind": "news report", "citation": "Anderer J (2025). AI detects invisible sperm, leads to couple's first pregnancy after 19 years. StudyFinds, 3 November 2025. Reports from the letter: 19 egg retrievals across four centres over 11 years, two testicular extractions, one fresh and one thawed egg injected with the motile sperm, two non-motile sperm injected without progression, day-3 transfer, 8 weeks with a fetal heart rate of 172, Havens Innovation Fund support, and patent applications held by Suryawanshi and Williams through Columbia.", "title": "AI detects invisible sperm, leads to couple's first pregnancy after 19 years", "url": "https://studyfinds.com/ai-detects-invisible-sperm/", "date": "2025-11-03", "written_by": "independent", "quote": "the first reported clinical pregnancy resulting from AI-guided sperm recovery" }, { "kind": "news report", "citation": "Hong A-reum (2025). AI pinpoints rare sperm and enables successful IVF pregnancy in US study. Chosunbiz, 1 November 2025.", "title": "AI pinpoints rare sperm and enables successful IVF pregnancy in US study", "url": "https://biz.chosun.com/en/en-science/2025/11/01/DUEJDMOPVVAINJVKBQ2ERLB6DU/", "date": "2025-11-01", "written_by": "independent", "quote": "STAR analyzes more than 8 million microscopic semen images per hour." }, { "kind": "news report", "citation": "Jo G (2025). \"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm. DongA Science, 3 November 2025.", "title": "\"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm", "url": "https://www.dongascience.com/en/news/74880", "date": "2025-11-03", "written_by": "independent", "quote": "A recent study reported a successful pregnancy after using AI to find two sperm in the semen of a patient with azoospermia." }, { "kind": "news report", "citation": "Cerati F (2025). First baby thanks to artificial intelligence and robots: a breakthrough in male infertility. Il Sole 24 Ore (English edition), 3 November 2025; despite the headline, the text reports a pregnancy, not a birth.", "title": "First baby thanks to artificial intelligence and robots: a breakthrough in male infertility", "url": "https://en.ilsole24ore.com/art/first-baby-thanks-to-artificial-intelligence-and-robot-breakthrough-in-male-infertility-AH8Kc0WD", "date": "2025-11-03", "written_by": "independent", "quote": "It only takes one healthy spermatozoon to create an embryo" }, { "kind": "news report", "citation": "Dixit M (2025). ‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years. Interesting Engineering, 31 October 2025 (HTML title: Columbia University reports first pregnancy using AI sperm recovery). Notes the result is based on a single case.", "title": "‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years", "url": "https://interestingengineering.com/science/breakthrough-ai-helps-infertile-man", "date": "2025-10-31", "written_by": "independent", "quote": "being further evaluated through larger clinical studies" }, { "kind": "news report", "citation": "Kohli KK (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia: Study. Medical Dialogues, 24 December 2025; confirms the Lancet item is a research letter.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia: Study", "url": "https://medicaldialogues.in/obstetrics-gynaecology/news/first-pregnancy-with-ai-guided-sperm-recovery-method-developed-at-columbia-study-160260", "date": "2025-12-24", "written_by": "independent", "quote": "The case is described in a research letter published in The Lancet." }, { "kind": "news report", "citation": "Padhy K (2026). Finding 'hidden sperm': New technique offers hope to men previously told they were infertile. BBC Future, 30 April 2026. Reports the birth at the end of 2025, sperm found in just under 30% of the latest 175 patients, and a second STAR pregnancy (a Klinefelter patient's micro-TESE tissue).", "title": "Finding 'hidden sperm': New technique offers hope to men previously told they were infertile", "url": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile", "date": "2026-04-30", "written_by": "independent", "quote": "the first baby to be born using the Star system allowed a couple who had battled with infertility for almost two decades to finally have a child" }, { "kind": "news report", "citation": "Medaris A (2026). 'AI babies' are being conceived in 'previously impossible' ways: all about the new IVF tech. New York Post, 13 May 2026.", "title": "Inside the new IVF tech giving rise to 'AI babies'", "url": "https://nypost.com/2026/05/13/health/inside-the-new-ivf-tech-giving-rise-to-ai-babies/", "date": "2026-05-13", "written_by": "independent", "quote": "The first baby born to a dad with the diagnosis using STAR was born in December." }, { "kind": "news report", "citation": "Jo G (2026). Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive. DongA Science, 3 May 2026. Also reports sperm found in about 30% of 175 patients.", "title": "Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive", "url": "https://www.dongascience.com/en/news/77712", "date": "2026-05-03", "written_by": "independent", "quote": "The first baby born through STAR is a healthy girl." }, { "kind": "news report", "citation": "Zaleski A (2026). A.I. Is Finding Sperm Where Doctors Couldn't. The New York Times, 11 August 2026 (nytimes.com/2026/08/11/science/ai-infertile-men-sperm.html), read in the syndicated copy carried by The Star (Malaysia) on 13 August 2026. Reports 175 cases with sperm recovered 26% of the time, three systems in operation at Columbia only, and that STAR cannot help men who produce no sperm.", "title": "AI is finding sperm where doctors couldn't", "url": "https://www.thestar.com.my/tech/tech-news/2026/08/13/ai-is-finding-sperm-where-doctors-couldnt", "date": "2026-08-13", "written_by": "independent", "quote": "Sperm were found after the 39-year-old man’s sample was run through the Star system, and that couple now has a baby girl." }, { "kind": "news report", "citation": "Vega E (2026). A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far. Medical Daily, 12 August 2026. Notes one published pregnancy, no controlled trials and no published success rates.", "title": "A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far", "url": "https://www.medicaldaily.com/ai-sperm-detection-azoospermia-star-method-evidence-477211", "date": "2026-08-12", "written_by": "independent", "quote": "slow, physically fatiguing and inherently incomplete: a technician cannot examine every field of view in a sample within a workable timeframe." }, { "kind": "report", "citation": "INCIID, The InterNational Council on Infertility Information Dissemination (2026). STAR (Sperm Tracking and Recovery) System. inciid.org, 14 May 2026 (modified 5 October 2026). Patient-organisation summary: YOLOv8 detector with precision 0.89 and recall 0.90, about 40 times more sperm than manual search, and patent applications filed by Columbia.", "title": "STAR (Sperm Tracking and Recovery) System", "url": "https://inciid.org/star-sperm-tracking-and-recovery-system/", "date": "2026-05-14", "written_by": "independent", "quote": "The technology integrates high-speed imaging, artificial intelligence, microfluidics, and robotics to perform non-invasive sperm detection and retrieval." }, { "kind": "press release", "citation": "Columbia University Irving Medical Center (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia. Press release via EurekAlert!, 31 October 2025. Gives 3.5 mL sample, 2.5 million images in about two hours, two viable sperm, two embryos; funding from the Havens Innovation Fund.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia", "url": "https://www.eurekalert.org/news-releases/1104028", "date": "2025-10-31", "written_by": "makers", "quote": "You only need one healthy sperm to create an embryo" }, { "kind": "press release", "citation": "Columbia University Fertility Center (2026). Sperm Tracking and Recovery (STAR). Service page on columbiadoctors.org, fetched 20 October 2026. Prices the analysis at $3,000 ($1,500 if no sperm are found), not billable to insurance, and reports about 28% of prior-azoospermia patients with sperm found, about 20% of mature eggs fertilising and about 18% of fertilised eggs reaching good-quality embryos.", "title": "Sperm Tracking and Recovery (STAR)", "url": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center/our-services/sperm-tracking-and-recovery-star", "written_by": "makers", "quote": "STAR achieved its first reported pregnancy in March 2025." }, { "kind": "press release", "citation": "Columbia University Fertility Center (2025). Columbia Fertility Looks to the Stars to Help Men with Infertility. columbiadoctors.org, dated 9 October 2025, fetched 20 October 2026. The Internet Archive copy of 1 November 2025 ends the couple's sentence 'and start a pregnancy'; the live page now reads 'and deliver a healthy baby girl', so the birth was added after that date.", "title": "Columbia Fertility Looks to the Stars to Help Men with Infertility", "url": "https://www.columbiadoctors.org/news/columbia-fertility-looks-stars-help-men-infertility", "date": "2025-10-09", "written_by": "makers", "quote": "Since STAR was unveiled in 2024, it has been used to help dozens of patients at the Columbia University Fertility Center." }, { "kind": "press release", "citation": "Gary H (2025). Columbia Develops STAR Technology for Men with Infertility. Columbia Medicine magazine, Vagelos College of Physicians and Surgeons, Fall 2025.", "title": "Columbia Develops STAR Technology for Men with Infertility", "url": "https://www.vagelos.columbia.edu/about-us/columbia-medicine-magazine/archives/fall-2025/clinical-advances/columbia-develops-star-technology-men-infertility", "written_by": "makers", "quote": "like trying to find a needle hidden among a thousand haystacks—but doing it within one hour" }, { "kind": "press release", "citation": "NewYork-Presbyterian (2025). Ep38: Building an AI-Powered System to Improve Fertility Success. Advances in Care podcast with Zev Williams, 7 August 2025.", "title": "Ep38: Building an AI-Powered System to Improve Fertility Success", "url": "https://www.nyp.org/advances/podcast/building-an-ai-powered-system-to-improve-fertility-success", "date": "2025-08-07", "written_by": "makers", "quote": "about four months pregnant with a healthy, ongoing pregnancy" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2025). Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample. US patent application US20250264398A1, priority 27 July 2022, published 21 August 2025; describes a YOLO (YOLOv4) detector, 100-500 frames per second and a flow channel 10-50 micrometres high.", "title": "Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample", "url": "https://patents.google.com/patent/US20250264398A1/en", "date": "2025-08-21", "written_by": "makers", "quote": "Biological cells can be identified and recovered from a sample by pumping the sample through a flow channel" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2026). Microfluidic device for recovering rare biological cells from a sample. PCT application WO2026019779A1, priority 17 July 2024, published 22 January 2026.", "title": "Microfluidic device for recovering rare biological cells from a sample", "url": "https://patents.google.com/patent/WO2026019779A1/en", "date": "2026-01-22", "written_by": "makers", "quote": "Sperm cells can be extracted from a sample by passing the sample through a microfluidic device, capturing images of the sample" }, { "kind": "peer-reviewed study", "citation": "Gemmell LC, Suryawanshi H, Williams Z (2026). AI-based techniques in sperm detection. Current Opinion in Urology, published 22 July 2026. Review by the STAR team; abstract read on Europe PMC.", "title": "AI-based techniques in sperm detection", "url": "https://doi.org/10.1097/MOU.0000000000001430", "date": "2026-07-22", "written_by": "makers", "quote": "Early clinical data suggest these approaches may enable sperm recovery in patients previously considered sperm-negative by conventional methods." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0151-source-0001", "AIBD-0151-source-0002", "AIBD-0151-source-0003", "AIBD-0151-source-0004", "AIBD-0151-source-0005", "AIBD-0151-source-0006", "AIBD-0151-source-0007", "AIBD-0151-source-0008", "AIBD-0151-source-0009", "AIBD-0151-source-0010", "AIBD-0151-source-0011", "AIBD-0151-source-0012", "AIBD-0151-source-0013", "AIBD-0151-source-0014", "AIBD-0151-source-0015", "AIBD-0151-source-0016", "AIBD-0151-source-0017", "AIBD-0151-source-0018", "AIBD-0151-source-0019", "AIBD-0151-source-0020", "AIBD-0151-source-0021", "AIBD-0151-source-0022", "AIBD-0151-source-0023", "AIBD-0151-source-0024", "AIBD-0151-source-0025", "AIBD-0151-source-0026", "AIBD-0151-source-0027", "AIBD-0151-source-0028", "AIBD-0151-source-0029", "AIBD-0151-source-0030", "AIBD-0151-source-0031", "AIBD-0151-source-0032", "AIBD-0151-source-0033" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Suryawanshi H, Gemmell LC, Morgan S, Koustas G, Prosser RW, Fu R, Forman EJ, Williams Z (2025). First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia. The Lancet 406(10516):2213-2214, research letter published online 31 October 2025 (received 15 May, accepted 4 August 2025), PMID 41183539. Written by the team that developed STAR; the clinical figures are reported by the press release, PTI, the Free Press Journal, StudyFinds and Republic World.", "title": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia", "url": "https://doi.org/10.1016/S0140-6736(25)01623-X", "date": "2025-10-31", "written_by": "makers", "quote": "First clinical pregnancy following AI-based microfluidic sperm detection and recovery in non-obstructive azoospermia" }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025. Quotes two uninvolved specialists, Robert Brannigan (ASRM president-elect) and Allison K. Rodgers, in support, and one sceptic, Gianpiero Palermo.", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "Researchers at the Columbia University Fertility Center say this procedure, conducted in March, amounts to the first-known use of AI-enabled conception using this particular technology." }, { "kind": "news report", "citation": "Malhi S (2025). AI helps find viable sperm in infertility case. The Washington Post, 27 June 2025 (second quotation: Gianpiero Palermo of Weill Cornell Medicine, who pioneered intracytoplasmic sperm injection, on the risk of false hope; Brannigan asked for testing at other clinics and tracking of pregnancy rates).", "title": "AI helps find viable sperm in infertility case", "url": "https://www.washingtonpost.com/health/2025/06/27/ai-enabled-search-viable-sperm-infertility/", "date": "2025-06-27", "written_by": "independent", "quote": "You are attracting patients who have been told they have no sperm and offering what may turn out to be false hope" }, { "kind": "news report", "citation": "Park A (2025). Doctors Report the First Pregnancy Using a New AI Procedure. TIME, 10 June 2025. First report of the pregnancy: the wife, given the pseudonym Rosie, 38, became pregnant in March 2025 after nearly 19 years and 15 unsuccessful IVF cycles.", "title": "Doctors Report the First Pregnancy Using a New AI Procedure", "url": "https://time.com/7291154/doctors-report-first-pregnancy-new-ai-procedure/", "date": "2025-06-10", "written_by": "independent", "quote": "The system can scan eight million images in about an hour." }, { "kind": "news report", "citation": "Howard J (2025). A couple tried for 18 years to get pregnant. AI made it happen. CNN, 3 July 2025. Gives the December due date and Williams' estimate of a little under $3,000 to find, isolate and freeze sperm.", "title": "A couple tried for 18 years to get pregnant. AI made it happen", "url": "https://www.cnn.com/2025/07/03/health/ai-male-infertility-sperm-wellness", "date": "2025-07-03", "written_by": "independent", "quote": "hidden sperm were found, recovered and used to fertilize the wife’s eggs via IVF, and she became the first successful pregnancy enabled by the STAR method" }, { "kind": "news report", "citation": "FemTech World News Desk (2025). Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile. FemTech World, 13 June 2025.", "title": "Doctors report first pregnancy using AI system to detect sperm in men previously considered infertile", "url": "https://www.femtechworld.co.uk/insight/doctors-report-first-pregnancy-using-ai-system-to-detect-sperm-in-men-previously-considered-infertile-aift25/", "date": "2025-06-13", "written_by": "independent", "quote": "scan around eight million images in an hour" }, { "kind": "news report", "citation": "Park A (2025). Columbia University STAR method. TIME, The Best Inventions of 2025, 9 October 2025.", "title": "Columbia University STAR method: The Best Inventions of 2025", "url": "https://time.com/collections/best-inventions-2025/7318439/columbia-university-star-method/", "date": "2025-10-09", "written_by": "independent", "quote": "After 20 years of trying, the first couple to use STAR is expecting their first child this year." }, { "kind": "news report", "citation": "Quintanar S (2025). This AI-imaging tech from Columbia researchers is solving male infertility. Columbia Daily Spectator, 26 October 2025 (student newspaper; confirms the 15 unsuccessful IVF cycles).", "title": "This AI-imaging tech from Columbia researchers is solving male infertility", "url": "https://www.columbiaspectator.com/news/2025/10/26/this-ai-imaging-tech-from-columbia-researchers-is-solving-male-infertility/", "date": "2025-10-26", "written_by": "independent", "quote": "After trying to conceive for nearly two decades, a couple successfully received a positive pregnancy test after using the STAR system." }, { "kind": "news report", "citation": "PTI via The Economic Times (2025). How AI helped an infertile couple conceive after 19 years with just '2 sperm'. The Economic Times, 3 November 2025; one of the fourteen sources cited by the OECD Monitor. Gives 2.5 million images over two hours, seven sperm of which two viable, positive test 13 days after transfer, and a heartbeat of 172 beats per minute at eight weeks.", "title": "How AI helped an infertile couple conceive after 19 years with just '2 sperm'", "url": "https://economictimes.indiatimes.com/news/india/how-ai-helped-an-infertile-couple-conceive-after-19-years-with-just-2-sperm/articleshow/125051307.cms", "date": "2025-11-03", "written_by": "independent", "quote": "picked out just two healthy sperm cells, helping a US couple conceive after 19 years of trying, a report in The Lancet said" }, { "kind": "news report", "citation": "Kanchwala T (2025). How AI Helped This Couple Get Pregnant After 19-Year Wait. Free Press Journal, 4 November 2025; cited by the OECD Monitor. Gives the 3.5 mL sample judged sperm-free by manual checks, day-3 transfer, positive test 13 days later and transition to standard obstetric care.", "title": "How AI Helped This Couple Get Pregnant After 19-Year Wait", "url": "https://www.freepressjournal.in/tech/how-ai-helped-this-couple-get-pregnant-after-19-year-wait", "date": "2025-11-04", "written_by": "independent", "quote": "Over approximately two hours, the AI processed a staggering 2.5 million images, detecting seven individual sperm cells: two motile (capable of movement) and five non-motile." }, { "kind": "news report", "citation": "Pathak P (2025). After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby. Republic World, 4 November 2025; cited by the OECD Monitor. Reports 19 egg-retrieval cycles at four fertility centres and a confirmed pregnancy at eight weeks; the headline's 'welcomes miracle baby' is ahead of its own text, which reports a pregnancy, not a birth.", "title": "After 19 Years of Infertility, AI Finds 2 Sperm from 2.5 Million Images; Couple Welcomes Miracle Baby", "url": "https://www.republicworld.com/tech/after-19-years-of-infertility-ai-finds-2-sperm-from-25-million-images-couple-welcomes-miracle-baby", "date": "2025-11-04", "written_by": "independent", "quote": "In just two hours, the STAR system scanned 2.5 million microscopic images of the man's semen sample and detected seven sperm, two of which were alive and motile." }, { "kind": "news report", "citation": "David A (2025). AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University. The Daily Jagran, 4 November 2025; cited by the OECD Monitor.", "title": "AI Helps Couple Conceive After 20 Years Of Infertility: A Medical Breakthrough From Columbia University", "url": "https://www.thedailyjagran.com/technology/ai-helps-couple-conceive-after-20-years-of-infertility-a-medical-breakthrough-from-columbia-university-10277754", "date": "2025-11-04", "written_by": "independent", "quote": "the STAR system identified seven sperm cells; two of which were active." }, { "kind": "news report", "citation": "Pall O (2025). After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First. Mashable India, 5 November 2025; cited by the OECD Monitor.", "title": "After 19 Years Of Failed IVF Attempts, AI Helps Couple Conceive In Groundbreaking First", "url": "https://in.mashable.com/tech/102002/after-19-years-of-failed-ivf-attempts-ai-helps-couple-conceive-in-groundbreaking-first", "date": "2025-11-05", "written_by": "independent", "quote": "Experts caution that while this case is inspiring, it represents an early-stage success. Larger-scale trials are needed before AI-assisted sperm detection becomes standard clinical practice." }, { "kind": "news report", "citation": "Anderer J (2025). AI detects invisible sperm, leads to couple's first pregnancy after 19 years. StudyFinds, 3 November 2025. Reports from the letter: 19 egg retrievals across four centres over 11 years, two testicular extractions, one fresh and one thawed egg injected with the motile sperm, two non-motile sperm injected without progression, day-3 transfer, 8 weeks with a fetal heart rate of 172, Havens Innovation Fund support, and patent applications held by Suryawanshi and Williams through Columbia.", "title": "AI detects invisible sperm, leads to couple's first pregnancy after 19 years", "url": "https://studyfinds.com/ai-detects-invisible-sperm/", "date": "2025-11-03", "written_by": "independent", "quote": "the first reported clinical pregnancy resulting from AI-guided sperm recovery" }, { "kind": "news report", "citation": "Hong A-reum (2025). AI pinpoints rare sperm and enables successful IVF pregnancy in US study. Chosunbiz, 1 November 2025.", "title": "AI pinpoints rare sperm and enables successful IVF pregnancy in US study", "url": "https://biz.chosun.com/en/en-science/2025/11/01/DUEJDMOPVVAINJVKBQ2ERLB6DU/", "date": "2025-11-01", "written_by": "independent", "quote": "STAR analyzes more than 8 million microscopic semen images per hour." }, { "kind": "news report", "citation": "Jo G (2025). \"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm. DongA Science, 3 November 2025.", "title": "\"AI Finds 'Miracle' Sperm\": Man with Azoospermia Achieves First Pregnancy with His Own Sperm", "url": "https://www.dongascience.com/en/news/74880", "date": "2025-11-03", "written_by": "independent", "quote": "A recent study reported a successful pregnancy after using AI to find two sperm in the semen of a patient with azoospermia." }, { "kind": "news report", "citation": "Cerati F (2025). First baby thanks to artificial intelligence and robots: a breakthrough in male infertility. Il Sole 24 Ore (English edition), 3 November 2025; despite the headline, the text reports a pregnancy, not a birth.", "title": "First baby thanks to artificial intelligence and robots: a breakthrough in male infertility", "url": "https://en.ilsole24ore.com/art/first-baby-thanks-to-artificial-intelligence-and-robot-breakthrough-in-male-infertility-AH8Kc0WD", "date": "2025-11-03", "written_by": "independent", "quote": "It only takes one healthy spermatozoon to create an embryo" }, { "kind": "news report", "citation": "Dixit M (2025). ‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years. Interesting Engineering, 31 October 2025 (HTML title: Columbia University reports first pregnancy using AI sperm recovery). Notes the result is based on a single case.", "title": "‘STAR is born’: Breakthrough AI helps infertile man father child after 20 years", "url": "https://interestingengineering.com/science/breakthrough-ai-helps-infertile-man", "date": "2025-10-31", "written_by": "independent", "quote": "being further evaluated through larger clinical studies" }, { "kind": "news report", "citation": "Kohli KK (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia: Study. Medical Dialogues, 24 December 2025; confirms the Lancet item is a research letter.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia: Study", "url": "https://medicaldialogues.in/obstetrics-gynaecology/news/first-pregnancy-with-ai-guided-sperm-recovery-method-developed-at-columbia-study-160260", "date": "2025-12-24", "written_by": "independent", "quote": "The case is described in a research letter published in The Lancet." }, { "kind": "news report", "citation": "Padhy K (2026). Finding 'hidden sperm': New technique offers hope to men previously told they were infertile. BBC Future, 30 April 2026. Reports the birth at the end of 2025, sperm found in just under 30% of the latest 175 patients, and a second STAR pregnancy (a Klinefelter patient's micro-TESE tissue).", "title": "Finding 'hidden sperm': New technique offers hope to men previously told they were infertile", "url": "https://www.bbc.com/future/article/20260429-finding-hidden-sperm-new-technology-offers-hope-to-men-previously-told-they-were-infertile", "date": "2026-04-30", "written_by": "independent", "quote": "the first baby to be born using the Star system allowed a couple who had battled with infertility for almost two decades to finally have a child" }, { "kind": "news report", "citation": "Medaris A (2026). 'AI babies' are being conceived in 'previously impossible' ways: all about the new IVF tech. New York Post, 13 May 2026.", "title": "Inside the new IVF tech giving rise to 'AI babies'", "url": "https://nypost.com/2026/05/13/health/inside-the-new-ivf-tech-giving-rise-to-ai-babies/", "date": "2026-05-13", "written_by": "independent", "quote": "The first baby born to a dad with the diagnosis using STAR was born in December." }, { "kind": "news report", "citation": "Jo G (2026). Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive. DongA Science, 3 May 2026. Also reports sperm found in about 30% of 175 patients.", "title": "Columbia University AI STAR system finds sperm, helps couples with azoospermia conceive", "url": "https://www.dongascience.com/en/news/77712", "date": "2026-05-03", "written_by": "independent", "quote": "The first baby born through STAR is a healthy girl." }, { "kind": "news report", "citation": "Zaleski A (2026). A.I. Is Finding Sperm Where Doctors Couldn't. The New York Times, 11 August 2026 (nytimes.com/2026/08/11/science/ai-infertile-men-sperm.html), read in the syndicated copy carried by The Star (Malaysia) on 13 August 2026. Reports 175 cases with sperm recovered 26% of the time, three systems in operation at Columbia only, and that STAR cannot help men who produce no sperm.", "title": "AI is finding sperm where doctors couldn't", "url": "https://www.thestar.com.my/tech/tech-news/2026/08/13/ai-is-finding-sperm-where-doctors-couldnt", "date": "2026-08-13", "written_by": "independent", "quote": "Sperm were found after the 39-year-old man’s sample was run through the Star system, and that couple now has a baby girl." }, { "kind": "news report", "citation": "Vega E (2026). A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far. Medical Daily, 12 August 2026. Notes one published pregnancy, no controlled trials and no published success rates.", "title": "A New Imaging Method Finds Sperm That Standard Laboratory Review Misses, with Limited Published Results So Far", "url": "https://www.medicaldaily.com/ai-sperm-detection-azoospermia-star-method-evidence-477211", "date": "2026-08-12", "written_by": "independent", "quote": "slow, physically fatiguing and inherently incomplete: a technician cannot examine every field of view in a sample within a workable timeframe." }, { "kind": "report", "citation": "INCIID, The InterNational Council on Infertility Information Dissemination (2026). STAR (Sperm Tracking and Recovery) System. inciid.org, 14 May 2026 (modified 5 October 2026). Patient-organisation summary: YOLOv8 detector with precision 0.89 and recall 0.90, about 40 times more sperm than manual search, and patent applications filed by Columbia.", "title": "STAR (Sperm Tracking and Recovery) System", "url": "https://inciid.org/star-sperm-tracking-and-recovery-system/", "date": "2026-05-14", "written_by": "independent", "quote": "The technology integrates high-speed imaging, artificial intelligence, microfluidics, and robotics to perform non-invasive sperm detection and retrieval." }, { "kind": "press release", "citation": "Columbia University Irving Medical Center (2025). First pregnancy with AI-guided sperm recovery method developed at Columbia. Press release via EurekAlert!, 31 October 2025. Gives 3.5 mL sample, 2.5 million images in about two hours, two viable sperm, two embryos; funding from the Havens Innovation Fund.", "title": "First pregnancy with AI-guided sperm recovery method developed at Columbia", "url": "https://www.eurekalert.org/news-releases/1104028", "date": "2025-10-31", "written_by": "makers", "quote": "You only need one healthy sperm to create an embryo" }, { "kind": "press release", "citation": "Columbia University Fertility Center (2026). Sperm Tracking and Recovery (STAR). Service page on columbiadoctors.org, fetched 20 October 2026. Prices the analysis at $3,000 ($1,500 if no sperm are found), not billable to insurance, and reports about 28% of prior-azoospermia patients with sperm found, about 20% of mature eggs fertilising and about 18% of fertilised eggs reaching good-quality embryos.", "title": "Sperm Tracking and Recovery (STAR)", "url": "https://www.columbiadoctors.org/specialties/obstetrics-gynecology/our-services/columbia-university-fertility-center/our-services/sperm-tracking-and-recovery-star", "written_by": "makers", "quote": "STAR achieved its first reported pregnancy in March 2025." }, { "kind": "press release", "citation": "Columbia University Fertility Center (2025). Columbia Fertility Looks to the Stars to Help Men with Infertility. columbiadoctors.org, dated 9 October 2025, fetched 20 October 2026. The Internet Archive copy of 1 November 2025 ends the couple's sentence 'and start a pregnancy'; the live page now reads 'and deliver a healthy baby girl', so the birth was added after that date.", "title": "Columbia Fertility Looks to the Stars to Help Men with Infertility", "url": "https://www.columbiadoctors.org/news/columbia-fertility-looks-stars-help-men-infertility", "date": "2025-10-09", "written_by": "makers", "quote": "Since STAR was unveiled in 2024, it has been used to help dozens of patients at the Columbia University Fertility Center." }, { "kind": "press release", "citation": "Gary H (2025). Columbia Develops STAR Technology for Men with Infertility. Columbia Medicine magazine, Vagelos College of Physicians and Surgeons, Fall 2025.", "title": "Columbia Develops STAR Technology for Men with Infertility", "url": "https://www.vagelos.columbia.edu/about-us/columbia-medicine-magazine/archives/fall-2025/clinical-advances/columbia-develops-star-technology-men-infertility", "written_by": "makers", "quote": "like trying to find a needle hidden among a thousand haystacks—but doing it within one hour" }, { "kind": "press release", "citation": "NewYork-Presbyterian (2025). Ep38: Building an AI-Powered System to Improve Fertility Success. Advances in Care podcast with Zev Williams, 7 August 2025.", "title": "Ep38: Building an AI-Powered System to Improve Fertility Success", "url": "https://www.nyp.org/advances/podcast/building-an-ai-powered-system-to-improve-fertility-success", "date": "2025-08-07", "written_by": "makers", "quote": "about four months pregnant with a healthy, ongoing pregnancy" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2025). Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample. US patent application US20250264398A1, priority 27 July 2022, published 21 August 2025; describes a YOLO (YOLOv4) detector, 100-500 frames per second and a flow channel 10-50 micrometres high.", "title": "Systems and Methods for Identifying and Recovering Rare Biological Cells from a Sample", "url": "https://patents.google.com/patent/US20250264398A1/en", "date": "2025-08-21", "written_by": "makers", "quote": "Biological cells can be identified and recovered from a sample by pumping the sample through a flow channel" }, { "kind": "other", "citation": "Williams SZ, Suryawanshi H; The Trustees of Columbia University in the City of New York (2026). Microfluidic device for recovering rare biological cells from a sample. PCT application WO2026019779A1, priority 17 July 2024, published 22 January 2026.", "title": "Microfluidic device for recovering rare biological cells from a sample", "url": "https://patents.google.com/patent/WO2026019779A1/en", "date": "2026-01-22", "written_by": "makers", "quote": "Sperm cells can be extracted from a sample by passing the sample through a microfluidic device, capturing images of the sample" }, { "kind": "peer-reviewed study", "citation": "Gemmell LC, Suryawanshi H, Williams Z (2026). AI-based techniques in sperm detection. Current Opinion in Urology, published 22 July 2026. Review by the STAR team; abstract read on Europe PMC.", "title": "AI-based techniques in sperm detection", "url": "https://doi.org/10.1097/MOU.0000000000001430", "date": "2026-07-22", "written_by": "makers", "quote": "Early clinical data suggest these approaches may enable sperm recovery in patients previously considered sperm-negative by conventional methods." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "STAR AI found 7 sperm (2 motile) in 2.5m images of a “sperm-free” sample; a couple infertile for 19 years conceived and had a girl.", "account": "At Columbia University Fertility Center in New York, a 39-year-old man with non-obstructive azoospermia and his 37-year-old wife had tried for 19 years. TIME calls her “Rosie”. That included 15 failed IVF cycles and two surgical sperm extractions. His 3.5 mL semen sample, read as sperm-free by manual examination, was run through STAR. It captured about 2.5 million images in roughly two hours and detected seven sperm, two motile. The two motile sperm were injected into eggs and two embryos were transferred on day 3. A pregnancy test was positive 13 days later, in March 2025. The Lancet published the case on 31 October 2025. A girl was born in December 2025." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The detector located sperm in microscope images so that the retrieval system could recover them." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A detector from the YOLO family." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "A detector from the YOLO family.", "editor_note": "INCIID names “YOLOv8 Architecture” (reference 25), whereas Columbia’s patent illustrates a “YOLOv4 object detection model” (reference 31, figures 4–5). Neither source identifies the version used for this pregnancy." } }, "systems[].model_version": { "state": "unresolved", "provenance": { "kind": "legacy_record", "basis": "Preserved the conflicting architecture descriptions already documented in the existing entry.", "record_fields": [ "ai_role" ], "source_refs": [] }, "reason": "INCIID names YOLOv8 while the cited patent filings describe YOLOv4; the clinical detector release is not established.", "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact detector release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "STAR (Sperm Tracking and Recovery): a semen sample flows through a single-use microfluidic chip while a high-speed camera (about 300 frames per second, over 8 million images an hour) images it; an AI object-detection model flags sperm among cellular debris in real time and a microfluidic gate or robotic step diverts each flagged sperm into a droplet for immediate injection or freezing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Columbia University, Columbia University Irving Medical Center (team led by Zev Williams and Hemant Suryawanshi)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Columbia's STAR system found two motile sperm in a sample manual checks had called sperm-free; after 19 years of infertility the couple conceived and had a daughter", "headline": "STAR finds two motile sperm; couple conceives after 19 years" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "24833b4ff5afe3799bee7da830cd27fc0fdb6055ebf64f1e2ac9435b9b1e57ec" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At Columbia University Fertility Center in New York, a 39-year-old man with non-obstructive azoospermia and his 37-year-old wife had tried for 19 years. TIME calls her “Rosie”. That included 15 failed IVF cycles and two surgical sperm extractions. His 3.5 mL semen sample, read as sperm-free by manual examination, was run through STAR. It captured about 2.5 million images in roughly two hours and detected seven sperm, two motile. The two motile sperm were injected into eggs and two embryos were transferred on day 3. A pregnancy test was positive 13 days later, in March 2025. The Lancet published the case on 31 October 2025. A girl was born in December 2025.", "replication": { "produced_by": [ "A man with non-obstructive azoospermia whose 3.5 mL ejaculate still held a handful of sperm (seven, two motile). Manual microscopy and two surgical extractions had missed them. He did produce some sperm.", "STAR's full pipeline on that sample: flow through a single-use microfluidic chip and a high-speed camera capturing about 2.5 million frames in roughly two hours. An AI detector flagged sperm among debris. A gate or robotic step diverted each flagged sperm gently enough to leave it usable.", "A partner with mature eggs available (one fresh, one thawed). An IVF laboratory able to inject the two motile sperm, culture two embryos and transfer them on day 3.", "About five years of in-house development at an academic fertility center staffed with embryologists, microfabrication, machine-learning and robotics specialists. A couple who kept trying after 15 failed IVF cycles." ], "must_hold": [ "Some sperm must exist in the sample. STAR finds sperm, it does not create them, and it cannot help men who produce none (NYT in syndication; Williams in the Washington Post).", "Rates are low even at Columbia. About 28% of prior-azoospermia patients have sperm found, about 20% of mature eggs fertilize and about 18% of fertilized eggs become good-quality embryos (service page). Across 175 cases sperm were recovered in 26% (NYT) to just under 30% (BBC).", "The evidence is one peer-reviewed case plus clinic-reported series. As of August 2026: no controlled trial and no published success rate (Medical Daily). ICSI pioneer Gianpiero Palermo warned the approach may sell false hope (Washington Post).", "Access is narrow. Three systems at one New York clinic (NYT), $3,000 per analysis or $1,500 if nothing is found, not billable to insurance (service page)." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "STAR examined about 2.5 million images of a sample that manual examiners had considered sperm-free. It recovered seven sperm, two of them motile. Embryologists injected the two motile sperm into eggs, cultured two embryos, and transferred them on day three." } } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 1, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0125", "title": "A facial recognition check at an Adana police stop identified a man who said he had no ID as Süleyman Abül, a robbery convict wanted to serve a sentence of 10 years, 1 month and 10 days", "summary": "Adana police stopped a man with no ID; facial recognition identified him as a robbery convict wanted to serve a 10-year sentence.", "date_observed": "2025-03-03", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Officers of the Seyhan District Police Directorate in Adana, Turkey, stopped a suspicious man during a street check in the Sucuzade neighborhood. He said he had no identity document and, by DHA's account, gave contradictory statements. So the district's Crime Prevention and Investigation Bureau took him to the station for fingerprint and facial recognition checks. The facial recognition system identified him as Süleyman Abül, 38, a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery. İHA and DHA published this in the early hours of 4 March 2025 without stating the day of the stop. The OECD Monitor dates it 3 March. DHA said he would go to prison once processing was done.", "category": "benefit created", "unexpected": false, "purpose": "Police facial recognition systems exist to identify people against identity and wanted-person records. Matching an unidentified detainee to a fugitive convict is that function, not a side effect.", "system": "Facial recognition system used by Turkish police at the Seyhan district station (not named in the reports)", "model_version": null, "developer": null, "deployer": "Seyhan District Police Directorate, Adana (Turkish National Police)", "location": "Adana, Turkey", "domain": "Policing / fugitive identification", "segment": "Street identity checks by district police", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-03-03-13e9" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Seyhan unit established at the station that a man who said he had no ID and gave contradictory statements was a fugitive convict. He had a robbery sentence of 10 years, 1 month and 10 days outstanding, and could go to prison. A material but single-case gain for one police unit." }, { "group": "societal", "depth": 1, "reason": "One convicted robber who had evaded a long sentence was returned to custody. The reports give no evidence of any further harm prevented, so the public benefit is small and diffuse." } ], "ai_role": { "status": "assessed", "statement": "The İHA and DHA reports credit the facial recognition system with the identification. The man produced no ID, and the match against police records returned his name and outstanding sentence. DHA's version says he was taken in for both fingerprint and facial recognition checks, so fingerprints might have identified him regardless. What the system is attested to have contributed is the identification itself, not time saved. The reports name neither the system nor its developer and give no match score. No official is quoted by name." }, "evidence": [ { "kind": "news report", "citation": "Demirören Haber Ajansı via NTV (2025). Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi. NTV, 4 March 2025.", "title": "Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi", "url": "https://www.ntv.com.tr/turkiye/firari-hukumlu-yuz-tanima-sistemiyle-yakayi-ele-verdi,U5c9NcXxdUWolAOeyn13sA", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yapılan incelemede yüz tanıma sisteminde şüphelinin, yağma suçundan 10 yıl 1 ay 10 gün hapis cezası ile aranan firari hükümlü Süleyman Abül olduğu belirlendi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Habertürk (2025). Yüz tanıma sistemiyle yakayı eleverdi. Habertürk, 4 March 2025.", "title": "Yüz tanıma sistemiyle yakayı eleverdi", "url": "https://www.haberturk.com/yuz-tanima-sistemiyle-yakayi-eleverdi-3770669", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yüz tanıma sistemi kullanılarak şüphelinin yağma suçundan 10 yıl 1 ay 10 gün aranan Süleyman Abül (38) olduğu tespit edildi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Haberler.com (2025). Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi. Haberler.com, published 00:18 local time, 4 March 2025.", "title": "Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi", "url": "https://www.haberler.com/3-sayfa/yuz-tanima-sistemiyle-yakalanan-hukumlu-kimligim-yok-dedi-18423978-haberi", "date": "2025-03-04", "written_by": "independent", "quote": "Adana'da yağma suçundan 10 yıl hapis cezasıyla aranan hükümlü polislere \"Kimliğim yok\" dedi ancak yüz tanıma sistemi sayesinde yakayı ele verdi." } ], "replication": { "produced_by": [ "A street identity check in which the detainee could not or would not produce identification and gave contradictory answers", "A facial recognition system at the station linked to records that hold wanted fugitives' photographs and outstanding sentences" ], "must_hold": [ "The face match must be confirmed against identity records before anyone is handed to prison. The reports describe processing continuing after the match", "Fingerprint checks were available in parallel, so the system's contribution is the identification, not a capability police otherwise lacked" ], "echoes": [] }, "paired_incident": null, "headline": "Facial recognition in Adana identifies a wanted robbery convict", "metric": "a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No report later than the 4 March 2025 agency stories was found; they say only that he would be handed to prison after processing.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-03-13e9", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0125", "catalog_version": "1.0.0", "source_fingerprint": "9c28da9b1e2e3c230acc71037f4ac3f46c199651a3abdd954683fef9ebebcbf0", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0125-source-0001", "AIBD-0125-source-0002", "AIBD-0125-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Seyhan District Police Directorate, Adana (Turkish National Police)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The İHA and DHA reports credit the facial recognition system with the identification. The man produced no ID, and the match against police records returned his name and outstanding sentence. DHA's version says he was taken in for both fingerprint and facial recognition checks, so fingerprints might have identified him regardless. What the system is attested to have contributed is the identification itself, not time saved. The reports name neither the system nor its developer and give no match score. No official is quoted by name." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The İHA and DHA reports credit the facial recognition system with the identification. The man produced no ID, and the match against police records returned his name and outstanding sentence. DHA's version says he was taken in for both fingerprint and facial recognition checks, so fingerprints might have identified him regardless. What the system is attested to have contributed is the identification itself, not time saved. The reports name neither the system nor its developer and give no match score. No official is quoted by name." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Seyhan unit established at the station that a man who said he had no ID and gave contradictory statements was a fugitive convict. He had a robbery sentence of 10 years, 1 month and 10 days outstanding, and could go to prison. A material but single-case gain for one police unit." }, { "group": "societal", "depth": 1, "reason": "One convicted robber who had evaded a long sentence was returned to custody. The reports give no evidence of any further harm prevented, so the public benefit is small and diffuse." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Seyhan unit established at the station that a man who said he had no ID and gave contradictory statements was a fugitive convict. He had a robbery sentence of 10 years, 1 month and 10 days outstanding, and could go to prison. A material but single-case gain for one police unit." }, { "group": "societal", "depth": 1, "reason": "One convicted robber who had evaded a long sentence was returned to custody. The reports give no evidence of any further harm prevented, so the public benefit is small and diffuse." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Seyhan unit established at the station that a man who said he had no ID and gave contradictory statements was a fugitive convict. He had a robbery sentence of 10 years, 1 month and 10 days outstanding, and could go to prison. A material but single-case gain for one police unit." }, { "group": "societal", "depth": 1, "reason": "One convicted robber who had evaded a long sentence was returned to custody. The reports give no evidence of any further harm prevented, so the public benefit is small and diffuse." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-03-03-13e9" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No report later than the 4 March 2025 agency stories was found; they say only that he would be handed to prison after processing." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0125" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Officers of the Seyhan District Police Directorate in Adana, Turkey, stopped a suspicious man during a street check in the Sucuzade neighborhood. He said he had no identity document and, by DHA's account, gave contradictory statements. So the district's Crime Prevention and Investigation Bureau took him to the station for fingerprint and facial recognition checks. The facial recognition system identified him as Süleyman Abül, 38, a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery. İHA and DHA published this in the early hours of 4 March 2025 without stating the day of the stop. The OECD Monitor dates it 3 March. DHA said he would go to prison once processing was done.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The Seyhan unit established at the station that a man who said he had no ID and gave contradictory statements was a fugitive convict. He had a robbery sentence of 10 years, 1 month and 10 days outstanding, and could go to prison. A material but single-case gain for one police unit." }, { "group": "societal", "depth": 1, "reason": "One convicted robber who had evaded a long sentence was returned to custody. The reports give no evidence of any further harm prevented, so the public benefit is small and diffuse." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Police facial recognition systems exist to identify people against identity and wanted-person records. Matching an unidentified detainee to a fugitive convict is that function, not a side effect." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Adana, Turkey", "deployer_country": "Turkey" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Police facial recognition systems exist to identify people against identity and wanted-person records. Matching an unidentified detainee to a fugitive convict is that function, not a side effect." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-03", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-03-13e9", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A street identity check in which the detainee could not or would not produce identification and gave contradictory answers", "A facial recognition system at the station linked to records that hold wanted fugitives' photographs and outstanding sentences" ], "must_hold": [ "The face match must be confirmed against identity records before anyone is handed to prison. The reports describe processing continuing after the match", "Fingerprint checks were available in parallel, so the system's contribution is the identification, not a capability police otherwise lacked" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-03-13e9", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / fugitive identification", "segment": "Street identity checks by district police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Demirören Haber Ajansı via NTV (2025). Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi. NTV, 4 March 2025.", "title": "Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi", "url": "https://www.ntv.com.tr/turkiye/firari-hukumlu-yuz-tanima-sistemiyle-yakayi-ele-verdi,U5c9NcXxdUWolAOeyn13sA", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yapılan incelemede yüz tanıma sisteminde şüphelinin, yağma suçundan 10 yıl 1 ay 10 gün hapis cezası ile aranan firari hükümlü Süleyman Abül olduğu belirlendi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Habertürk (2025). Yüz tanıma sistemiyle yakayı eleverdi. Habertürk, 4 March 2025.", "title": "Yüz tanıma sistemiyle yakayı eleverdi", "url": "https://www.haberturk.com/yuz-tanima-sistemiyle-yakayi-eleverdi-3770669", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yüz tanıma sistemi kullanılarak şüphelinin yağma suçundan 10 yıl 1 ay 10 gün aranan Süleyman Abül (38) olduğu tespit edildi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Haberler.com (2025). Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi. Haberler.com, published 00:18 local time, 4 March 2025.", "title": "Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi", "url": "https://www.haberler.com/3-sayfa/yuz-tanima-sistemiyle-yakalanan-hukumlu-kimligim-yok-dedi-18423978-haberi", "date": "2025-03-04", "written_by": "independent", "quote": "Adana'da yağma suçundan 10 yıl hapis cezasıyla aranan hükümlü polislere \"Kimliğim yok\" dedi ancak yüz tanıma sistemi sayesinde yakayı ele verdi." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0125-source-0001", "AIBD-0125-source-0002", "AIBD-0125-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Demirören Haber Ajansı via NTV (2025). Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi. NTV, 4 March 2025.", "title": "Firari hükümlü, yüz tanıma sistemiyle yakayı ele verdi", "url": "https://www.ntv.com.tr/turkiye/firari-hukumlu-yuz-tanima-sistemiyle-yakayi-ele-verdi,U5c9NcXxdUWolAOeyn13sA", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yapılan incelemede yüz tanıma sisteminde şüphelinin, yağma suçundan 10 yıl 1 ay 10 gün hapis cezası ile aranan firari hükümlü Süleyman Abül olduğu belirlendi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Habertürk (2025). Yüz tanıma sistemiyle yakayı eleverdi. Habertürk, 4 March 2025.", "title": "Yüz tanıma sistemiyle yakayı eleverdi", "url": "https://www.haberturk.com/yuz-tanima-sistemiyle-yakayi-eleverdi-3770669", "date": "2025-03-04", "written_by": "independent", "quote": "Burada yüz tanıma sistemi kullanılarak şüphelinin yağma suçundan 10 yıl 1 ay 10 gün aranan Süleyman Abül (38) olduğu tespit edildi." }, { "kind": "news report", "citation": "İhlas Haber Ajansı via Haberler.com (2025). Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi. Haberler.com, published 00:18 local time, 4 March 2025.", "title": "Yüz Tanıma Sistemiyle Yakalanan Hükümlü: 'Kimliğim Yok' Dedi", "url": "https://www.haberler.com/3-sayfa/yuz-tanima-sistemiyle-yakalanan-hukumlu-kimligim-yok-dedi-18423978-haberi", "date": "2025-03-04", "written_by": "independent", "quote": "Adana'da yağma suçundan 10 yıl hapis cezasıyla aranan hükümlü polislere \"Kimliğim yok\" dedi ancak yüz tanıma sistemi sayesinde yakayı ele verdi." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Adana police stopped a man with no ID; facial recognition identified him as a robbery convict wanted to serve a 10-year sentence.", "account": "Officers of the Seyhan District Police Directorate in Adana, Turkey, stopped a suspicious man during a street check in the Sucuzade neighborhood. He said he had no identity document and, by DHA's account, gave contradictory statements. So the district's Crime Prevention and Investigation Bureau took him to the station for fingerprint and facial recognition checks. The facial recognition system identified him as Süleyman Abül, 38, a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery. İHA and DHA published this in the early hours of 4 March 2025 without stating the day of the stop. The OECD Monitor dates it 3 March. DHA said he would go to prison once processing was done." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Facial recognition system used by Turkish police at the Seyhan district station (not named in the reports)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A facial recognition check at an Adana police stop identified a man who said he had no ID as Süleyman Abül, a robbery convict wanted to serve a sentence of 10 years, 1 month and 10 days", "headline": "Facial recognition in Adana identifies a wanted robbery convict" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9c28da9b1e2e3c230acc71037f4ac3f46c199651a3abdd954683fef9ebebcbf0" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Officers of the Seyhan District Police Directorate in Adana, Turkey, stopped a suspicious man during a street check in the Sucuzade neighborhood. He said he had no identity document and, by DHA's account, gave contradictory statements. So the district's Crime Prevention and Investigation Bureau took him to the station for fingerprint and facial recognition checks. The facial recognition system identified him as Süleyman Abül, 38, a fugitive convict wanted to serve 10 years, 1 month and 10 days for robbery. İHA and DHA published this in the early hours of 4 March 2025 without stating the day of the stop. The OECD Monitor dates it 3 March. DHA said he would go to prison once processing was done.", "replication": { "produced_by": [ "A street identity check in which the detainee could not or would not produce identification and gave contradictory answers", "A facial recognition system at the station linked to records that hold wanted fugitives' photographs and outstanding sentences" ], "must_hold": [ "The face match must be confirmed against identity records before anyone is handed to prison. The reports describe processing continuing after the match", "Fingerprint checks were available in parallel, so the system's contribution is the identification, not a capability police otherwise lacked" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0288", "title": "Smartwatch single-lead ECG captures a 165 bpm wide-complex tachycardia in a 64-year-old man; Emory diagnoses ventricular tachycardia, implants a defibrillator and later ablates", "summary": "A smartwatch ECG recorded a 165 bpm wide-complex tachycardia during palpitations; VT was confirmed on telemetry, an ICD placed and later shocked VT, and ablation stopped the VT (JACC Case Rep 2025).", "date_observed": "2025-03-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Guynn, Regis, Eckert, D'souza, Turbow, Westerman, Sperling and Lloyd are in Emory University School of Medicine's Division of Cardiology, Atlanta. They reported in JACC: Case Reports (published online 12 March 2025; event dates not reported) on a 64-year-old man. He had a bioprosthetic aortic valve replaced at 55 and a month of intermittent palpitations and near-syncope. During symptoms he used his smartwatch's electrocardiogram (ECG) function. The watch captured a 10-second single-lead ECG and reported a heart rate above 150 beats/min, warning him to speak to a doctor. The tracing showed wide complex tachycardia at 165 beats/min. On admission he was in sinus rhythm at 77 bpm. But telemetry and ECG caught multiple episodes of monomorphic ventricular tachycardia, and he went to intensive cardiac care. Cardiac magnetic resonance imaging (MRI) suggested scar or late myocarditis at the basal septum. An electrophysiology study found easily inducible VT. A secondary-prevention ICD was implanted and he was discharged on metoprolol, spironolactone and dapagliflozin. Three months later the ICD shocked him for VT. Device interrogation showed pace-terminated episodes, some degenerating into ventricular fibrillation. Successful ablation below the aortic prosthesis followed, with no further VT on serial interrogations. The authors write VT would have gone undiagnosed had the clinician not considered the smartwatch data. The watch's brand and model are unstated.", "category": "benefit created", "unexpected": false, "purpose": "Smartwatch ECG apps are built to record a single-lead trace and warn of high heart rates. Capturing the VT during symptoms was that function. The authors note no smartwatch algorithm is validated to detect VT and the diagnosis came from clinicians reading the trace.", "system": "Smartwatch ECG function with high-heart-rate warning (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "Atlanta, United States (authors' institution; the admitting hospital is not named)", "domain": "Healthcare (cardiology; electrophysiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "The captured trace led to a VT diagnosis, an ICD that later delivered shocks for VT degenerating into ventricular fibrillation, and a curative ablation. The report presents the ICD decision as vindicated by those shocks. So the benefit reaches a life-threatening arrhythmia, though the counterfactual is the authors' judgment." } ], "ai_role": { "status": "assessed", "statement": "The device's contribution was recording a user-triggered single-lead ECG and issuing a generic high-heart-rate warning. It did not classify the rhythm as VT, which the authors say no wearable algorithm is validated to do. Clinicians read the QRS morphology on the smartwatch trace and on the 12-lead ECG, and made every treatment decision. The brand is unknown." }, "evidence": [ { "kind": "case report", "citation": "Guynn N, Regis K, Eckert A, D'souza M, Turbow S, Westerman S, Sperling L, Lloyd M (2025). Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology. JACC: Case Reports 30(9):103273. doi:10.1016/j.jaccas.2025.103273 (PMC12245455).", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The watch captured a 10-second single-lead ECG and reported a heart rate >150 beats/min with a warning to speak to a doctor" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, presentation.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The symptoms corresponded to a wide complex tachycardia with a rate of 165 beats/min on his smartwatch" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, follow-up and conclusions.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "Three months following discharge he was shocked by his implantable defibrillator and interrogation showed VT." }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, counterfactual claim.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "this case demonstrates that VT would have gone undiagnosed if this patient’s clinician had not considered the smartwatch data" } ], "replication": { "produced_by": [ "A wearer who activates the watch's ECG recording during a transient symptomatic episode", "A clinician who reviews the single-lead trace rather than dismissing consumer data", "Access to telemetry, cardiac MRI, electrophysiology study, ICD implantation and ablation" ], "must_hold": [ "The arrhythmia occurs while the wearer is able to trigger a recording (the watch has no continuous ECG)", "The QRS morphology on a single lead is clear enough for a clinician to suspect VT and pursue confirmation" ], "echoes": [ { "date": null, "setting": "Three earlier published cases of VT diagnosed from a smartwatch recording, each leading to an electrophysiology study and ICD, ablation or both, as summarized in this report's discussion", "model_version": null, "outcome": "recurred", "source": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, discussion ('To date, there have only been 3 other reported cases of VT diagnosed by a smartwatch')" } ] }, "paired_incident": null, "headline": "Smartwatch ECG captures 165 bpm tachycardia; Emory diagnoses VT", "metric": "recorded a 165 bpm wide-complex tachycardia during palpitations", "comparator": { "against": "the clinician's evaluation of palpitations without considering the smartwatch recording", "before": "VT would have gone undiagnosed", "after": "a wide complex tachycardia with a rate of 165 beats/min on his smartwatch", "basis": "assumed", "quote": "There is a need for a more cost-effective approach to evaluation and management of palpitations, and this case demonstrates that VT would have gone undiagnosed if this patient’s clinician had not considered the smartwatch data.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/" }, "later": { "status": "unknown", "date": null, "note": "The ICD shock and ablation are undated events within the same report; nothing after publication was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0288", "catalog_version": "1.0.0", "source_fingerprint": "e2acc392d1077fe071a1a9e055a3162007fafdd8931eaf2779f8b07430966e00", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0288-source-0001", "AIBD-0288-source-0002", "AIBD-0288-source-0003", "AIBD-0288-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The device's contribution was recording a user-triggered single-lead ECG and issuing a generic high-heart-rate warning. It did not classify the rhythm as VT, which the authors say no wearable algorithm is validated to do. Clinicians read the QRS morphology on the smartwatch trace and on the 12-lead ECG, and made every treatment decision. The brand is unknown." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The device's contribution was recording a user-triggered single-lead ECG and issuing a generic high-heart-rate warning. It did not classify the rhythm as VT, which the authors say no wearable algorithm is validated to do. Clinicians read the QRS morphology on the smartwatch trace and on the 12-lead ECG, and made every treatment decision. The brand is unknown." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The captured trace led to a VT diagnosis, an ICD that later delivered shocks for VT degenerating into ventricular fibrillation, and a curative ablation. The report presents the ICD decision as vindicated by those shocks. So the benefit reaches a life-threatening arrhythmia, though the counterfactual is the authors' judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The captured trace led to a VT diagnosis, an ICD that later delivered shocks for VT degenerating into ventricular fibrillation, and a curative ablation. The report presents the ICD decision as vindicated by those shocks. So the benefit reaches a life-threatening arrhythmia, though the counterfactual is the authors' judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The captured trace led to a VT diagnosis, an ICD that later delivered shocks for VT degenerating into ventricular fibrillation, and a curative ablation. The report presents the ICD decision as vindicated by those shocks. 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"partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "recorded a 165 bpm wide-complex tachycardia during palpitations", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The ICD shock and ablation are undated events within the same report; nothing after publication was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0288" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Guynn, Regis, Eckert, D'souza, Turbow, Westerman, Sperling and Lloyd are in Emory University School of Medicine's Division of Cardiology, Atlanta. They reported in JACC: Case Reports (published online 12 March 2025; event dates not reported) on a 64-year-old man. He had a bioprosthetic aortic valve replaced at 55 and a month of intermittent palpitations and near-syncope. During symptoms he used his smartwatch's electrocardiogram (ECG) function. The watch captured a 10-second single-lead ECG and reported a heart rate above 150 beats/min, warning him to speak to a doctor. The tracing showed wide complex tachycardia at 165 beats/min. On admission he was in sinus rhythm at 77 bpm. But telemetry and ECG caught multiple episodes of monomorphic ventricular tachycardia, and he went to intensive cardiac care. Cardiac magnetic resonance imaging (MRI) suggested scar or late myocarditis at the basal septum. An electrophysiology study found easily inducible VT. A secondary-prevention ICD was implanted and he was discharged on metoprolol, spironolactone and dapagliflozin. Three months later the ICD shocked him for VT. Device interrogation showed pace-terminated episodes, some degenerating into ventricular fibrillation. Successful ablation below the aortic prosthesis followed, with no further VT on serial interrogations. The authors write VT would have gone undiagnosed had the clinician not considered the smartwatch data. The watch's brand and model are unstated.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The captured trace led to a VT diagnosis, an ICD that later delivered shocks for VT degenerating into ventricular fibrillation, and a curative ablation. The report presents the ICD decision as vindicated by those shocks. So the benefit reaches a life-threatening arrhythmia, though the counterfactual is the authors' judgment." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Smartwatch ECG apps are built to record a single-lead trace and warn of high heart rates. Capturing the VT during symptoms was that function. The authors note no smartwatch algorithm is validated to detect VT and the diagnosis came from clinicians reading the trace." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Atlanta, United States (authors' institution; the admitting hospital is not named)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Smartwatch ECG apps are built to record a single-lead trace and warn of high heart rates. Capturing the VT during symptoms was that function. The authors note no smartwatch algorithm is validated to detect VT and the diagnosis came from clinicians reading the trace." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-12", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A wearer who activates the watch's ECG recording during a transient symptomatic episode", "A clinician who reviews the single-lead trace rather than dismissing consumer data", "Access to telemetry, cardiac MRI, electrophysiology study, ICD implantation and ablation" ], "must_hold": [ "The arrhythmia occurs while the wearer is able to trigger a recording (the watch has no continuous ECG)", "The QRS morphology on a single lead is clear enough for a clinician to suspect VT and pursue confirmation" ], "echoes": [ { "setting": "Three earlier published cases of VT diagnosed from a smartwatch recording, each leading to an electrophysiology study and ICD, ablation or both, as summarized in this report's discussion", "outcome": "recurred", "source": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, discussion ('To date, there have only been 3 other reported cases of VT diagnosed by a smartwatch')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A wearer who activates the watch's ECG recording during a transient symptomatic episode", "A clinician who reviews the single-lead trace rather than dismissing consumer data", "Access to telemetry, cardiac MRI, electrophysiology study, ICD implantation and ablation" ], "must_hold": [ "The arrhythmia occurs while the wearer is able to trigger a recording (the watch has no continuous ECG)", "The QRS morphology on a single lead is clear enough for a clinician to suspect VT and pursue confirmation" ], "echoes": [ { "setting": "Three earlier published cases of VT diagnosed from a smartwatch recording, each leading to an electrophysiology study and ICD, ablation or both, as summarized in this report's discussion", "outcome": "recurred", "source": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, discussion ('To date, there have only been 3 other reported cases of VT diagnosed by a smartwatch')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; electrophysiology)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Guynn N, Regis K, Eckert A, D'souza M, Turbow S, Westerman S, Sperling L, Lloyd M (2025). Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology. JACC: Case Reports 30(9):103273. doi:10.1016/j.jaccas.2025.103273 (PMC12245455).", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The watch captured a 10-second single-lead ECG and reported a heart rate >150 beats/min with a warning to speak to a doctor" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, presentation.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The symptoms corresponded to a wide complex tachycardia with a rate of 165 beats/min on his smartwatch" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, follow-up and conclusions.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "Three months following discharge he was shocked by his implantable defibrillator and interrogation showed VT." }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, counterfactual claim.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "this case demonstrates that VT would have gone undiagnosed if this patient’s clinician had not considered the smartwatch data" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0288-source-0001", "AIBD-0288-source-0002", "AIBD-0288-source-0003", "AIBD-0288-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Guynn N, Regis K, Eckert A, D'souza M, Turbow S, Westerman S, Sperling L, Lloyd M (2025). Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology. JACC: Case Reports 30(9):103273. doi:10.1016/j.jaccas.2025.103273 (PMC12245455).", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The watch captured a 10-second single-lead ECG and reported a heart rate >150 beats/min with a warning to speak to a doctor" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, presentation.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "The symptoms corresponded to a wide complex tachycardia with a rate of 165 beats/min on his smartwatch" }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, follow-up and conclusions.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "Three months following discharge he was shocked by his implantable defibrillator and interrogation showed VT." }, { "kind": "case report", "citation": "Guynn N et al. (2025), JACC Case Rep 30(9):103273, counterfactual claim.", "title": "Sustained Monomorphic Ventricular Tachycardia Accurately Detected by Wearable Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12245455/", "date": "2025-03-12", "written_by": "independent", "quote": "this case demonstrates that VT would have gone undiagnosed if this patient’s clinician had not considered the smartwatch data" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A smartwatch ECG recorded a 165 bpm wide-complex tachycardia during palpitations; VT was confirmed on telemetry, an ICD placed and later shocked VT, and ablation stopped the VT (JACC Case Rep 2025).", "account": "Guynn, Regis, Eckert, D'souza, Turbow, Westerman, Sperling and Lloyd are in Emory University School of Medicine's Division of Cardiology, Atlanta. They reported in JACC: Case Reports (published online 12 March 2025; event dates not reported) on a 64-year-old man. He had a bioprosthetic aortic valve replaced at 55 and a month of intermittent palpitations and near-syncope. During symptoms he used his smartwatch's electrocardiogram (ECG) function. The watch captured a 10-second single-lead ECG and reported a heart rate above 150 beats/min, warning him to speak to a doctor. The tracing showed wide complex tachycardia at 165 beats/min. On admission he was in sinus rhythm at 77 bpm. But telemetry and ECG caught multiple episodes of monomorphic ventricular tachycardia, and he went to intensive cardiac care. Cardiac magnetic resonance imaging (MRI) suggested scar or late myocarditis at the basal septum. An electrophysiology study found easily inducible VT. A secondary-prevention ICD was implanted and he was discharged on metoprolol, spironolactone and dapagliflozin. Three months later the ICD shocked him for VT. Device interrogation showed pace-terminated episodes, some degenerating into ventricular fibrillation. Successful ablation below the aortic prosthesis followed, with no further VT on serial interrogations. The authors write VT would have gone undiagnosed had the clinician not considered the smartwatch data. The watch's brand and model are unstated." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartwatch ECG function with high-heart-rate warning (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Smartwatch single-lead ECG captures a 165 bpm wide-complex tachycardia in a 64-year-old man; Emory diagnoses ventricular tachycardia, implants a defibrillator and later ablates", "headline": "Smartwatch ECG captures 165 bpm tachycardia; Emory diagnoses VT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e2acc392d1077fe071a1a9e055a3162007fafdd8931eaf2779f8b07430966e00" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Guynn, Regis, Eckert, D'souza, Turbow, Westerman, Sperling and Lloyd are in Emory University School of Medicine's Division of Cardiology, Atlanta. They reported in JACC: Case Reports (published online 12 March 2025; event dates not reported) on a 64-year-old man. He had a bioprosthetic aortic valve replaced at 55 and a month of intermittent palpitations and near-syncope. During symptoms he used his smartwatch's electrocardiogram (ECG) function. The watch captured a 10-second single-lead ECG and reported a heart rate above 150 beats/min, warning him to speak to a doctor. The tracing showed wide complex tachycardia at 165 beats/min. On admission he was in sinus rhythm at 77 bpm. But telemetry and ECG caught multiple episodes of monomorphic ventricular tachycardia, and he went to intensive cardiac care. Cardiac magnetic resonance imaging (MRI) suggested scar or late myocarditis at the basal septum. An electrophysiology study found easily inducible VT. A secondary-prevention ICD was implanted and he was discharged on metoprolol, spironolactone and dapagliflozin. Three months later the ICD shocked him for VT. 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(2025), JACC Case Rep 30(9):103273, discussion ('To date, there have only been 3 other reported cases of VT diagnosed by a smartwatch')" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0566", "title": "Tunbridge Wells Borough Council: The Amelia Scott, Collecting Tomorrow", "summary": "The Amelia Scott reports 50% faster image processing, improved scans, interactive exhibits, and volunteers progressing to paid museum roles.", "date_observed": "2025-03-12", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-030", "account": "The Amelia Scott uses Adobe Lightroom AI to prepare artifact images for digital twins and tactile display objects. The council reports 50% faster scan/image processing, better scan quality, interactive exhibitions, and volunteers progressing to paid museum roles. Commercial revenue remains prospective, and visitor learning gains are unmeasured. Training, partnerships, and digital production contribute jointly to the results. AI’s effect on employment and learning is unknown.", "category": "general benefit", "unexpected": false, "purpose": "Improve artifact-imaging workflows and create digital and tactile museum experiences.", "system": "Adobe Lightroom generative-AI functions within The Amelia Scott’s 3D scanning and digital-twin workflow", "model_version": null, "developer": "Adobe (Lightroom); PolyPlay supported workflow development", "deployer": "Tunbridge Wells Borough Council, The Amelia Scott", "location": "United Kingdom", "domain": "Museums, cultural heritage, and accessibility", "segment": null, "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Improved digital twins and delivered interactive and tactile exhibits extend the museum’s capabilities." }, { "group": "personal", "depth": 2, "reason": "The source reports skill development, volunteers obtaining paid roles, and expanded ways to experience artifacts. These are capability/opportunity gains without established livelihood preservation." } ], "ai_role": { "status": "assessed", "statement": "The source attributes faster masking, editing, and improved scan preparation to Lightroom AI within a broader production workflow. Training, partnerships, and other tools also contribute, so employment and visitor-learning effects cannot be isolated to AI." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Tunbridge Wells Borough Council: The Amelia Scott, Collecting Tomorrow", "url": "https://www.local.gov.uk/case-studies/tunbridge-wells-borough-council-amelia-collecting-tomorrow", "date": "2025-03-12", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The museum worked with PolyPlay to improve existing 3D-scanning workflows.", "Digital twins were used in interactive exhibitions and tactile objects, with volunteers and learners involved in production." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "The Amelia Scott reports better scans and expanded digital exhibits", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/tunbridge-wells-borough-council-amelia-collecting-tomorrow", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0566", "catalog_version": "1.0.0", "source_fingerprint": "d21c344d6b5704f3bca9f3cd65512e7e141d59440ae5ebfe0b686f2a74b4831e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0566-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Adobe (Lightroom); PolyPlay supported workflow development", "deployer": "Tunbridge Wells Borough Council, The Amelia Scott" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The source attributes faster masking, editing, and improved scan preparation to Lightroom AI within a broader production workflow. Training, partnerships, and other tools also contribute, so employment and visitor-learning effects cannot be isolated to AI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The source attributes faster masking, editing, and improved scan preparation to Lightroom AI within a broader production workflow. 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The council reports 50% faster scan/image processing, better scan quality, interactive exhibitions, and volunteers progressing to paid museum roles. Commercial revenue remains prospective, and visitor learning gains are unmeasured. Training, partnerships, and digital production contribute jointly to the results. AI’s effect on employment and learning is unknown.", "replication": { "produced_by": [ "The museum worked with PolyPlay to improve existing 3D-scanning workflows.", "Digital twins were used in interactive exhibitions and tactile objects, with volunteers and learners involved in production." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0092", "title": "Independent evaluation finds Google Flood Hub and GloFAS forecasts skillful beyond four days in Mali's frequently flooded regions, suggesting seven-day Red Cross early-action triggers", "summary": "Forecasts could allow earlier action in parts of Mali, but Google Flood Hub produced frequent false alarms. No benefit from an implemented early action was measured.", "date_observed": "2025-03-14", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Researchers evaluated Google Flood Hub and GloFAS forecasts against river-flow observations and records of flood impacts in Mali. Their results suggest that some early-action plans could extend from four to seven days without much loss of forecast skill. Performance varied across districts and thresholds, and no correctly predicted floods were found in the northern districts that were evaluated. At a seven-day lead time, Google Flood Hub’s false-alarm ratio was around 0.8 across discharge thresholds, compared with around 0.5 for GloFAS. The authors describe GloFAS as more balanced in several comparisons. They used a ten-day matching window to compare forecasts with reported impacts, which affects the interpretation of performance. This was a retrospective forecast evaluation; it did not measure benefits from an implemented early action. 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Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Lead-time potential, false alarms, and geographic limits", "source_chain": [ { "url": "https://onlinelibrary.wiley.com/doi/full/10.1111/jfr3.70247", "locator": "Sections 2.4, 3, 4.1, 4.2, 5.1; Table 1; Appendices A–C", "role": "Original full evaluation paper and appendices", "access_status": "Full relevant text reviewed", "published_on": "2026-09-16" } ], "limitations": [ "Seven-day Flood Hub false-alarm ratio around 0.8; local skill varies", "No implemented early-action benefit measured" ], "source_ref": "AIBD-0092-source-0001" }, { "claim": "Forecast inputs, impact data, and reproducibility", "source_chain": [ { "url": "https://sites.research.google/gr/floodforecasting/resources/", "locator": "GRRR historical forecast resource", "role": "Original Google dataset documentation", "access_status": "Full relevant text reviewed" }, { "url": "https://ewds.climate.copernicus.eu/datasets/cems-glofas-reforecast", "locator": "GloFAS reforecasts", "role": "Original comparison-data catalog", "access_status": "Full relevant text reviewed" }, { "url": "https://github.com/rodekruis/river-flood-data-analysis", "locator": "README and repository description", "role": "Authors’ analysis-code repository", "access_status": "Full relevant text reviewed" }, { "url": "https://doi.org/10.1111/jfr3.70247", "locator": "Data Availability statement; Appendix A impact-source inventory", "role": "Original declaration of source access and constraints", "access_status": "Full relevant text reviewed" } ], "limitations": [ "Mali DNH flow observations for 2016–2018 are under a nondisclosure agreement", "Text-mined impact data are available on request; underlying observations were not independently reanalyzed", "The evaluation is independent of Google; a JRC coauthor is connected to GloFAS" ], "source_ref": "AIBD-0092-source-0001" }, { "claim": "Earlier public version of the longer-lead-time finding", "source_chain": [ { "url": "https://meetingorganizer.copernicus.org/EGU25/EGU25-302.html", "locator": "Abstract: results paragraph; page marked updated March 14, 2025", "role": "Original preliminary conference abstract", "access_status": "Full relevant text reviewed", "published_on": "2025-03-14" }, { "url": "https://eartharxiv.org/repository/view/11374/", "locator": "Preprint cited in the journal paper’s Data Availability statement", "role": "Earlier manuscript version", "access_status": "Repository returned a bot-verification page; full preprint not retrieved" } ], "limitations": [ "March 14 is the earliest verified public version date, not a verified initial publication date", "The preliminary abstract supports lead times beyond four days; the detailed seven-day and false-alarm results are supported by the 2026 full paper", "The conference presentation requires registration and was not obtained" ], "source_ref": "AIBD-0092-source-0001" } ], "limitations": [ "Confidential observations and on-request impact data prevent complete independent reproduction", "EarthArXiv full preprint and the conference presentation were inaccessible" ], "chronology_source": { "url": "https://meetingorganizer.copernicus.org/EGU25/EGU25-302.html", "locator": "Abstract page updated March 14, 2025", "role": "Earliest verified public version of the central finding", "access_status": "Full relevant text reviewed", "published_on": "2025-03-14", "date": "2025-03-14", "title": "Assessing the riverine flood forecast skill of GloFAS and Google Flood Hub with impact data and river flow observations to support early actions in Mali" } } }, "provenance": { "kind": "source_review", "basis": "Consolidated repeated quotations of one paper, added material limitations from the full results and appendices, and traced the finding to its earlier EGU abstract.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0092-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Some observations are confidential, and the impact data are available only on request. The EarthArXiv preprint and conference presentation were inaccessible.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Forecasts could allow earlier action in parts of Mali, but Google Flood Hub produced frequent false alarms. No benefit from an implemented early action was measured.", "account": "Researchers evaluated Google Flood Hub and GloFAS forecasts against river-flow observations and records of flood impacts in Mali. Their results suggest that some early-action plans could extend from four to seven days without much loss of forecast skill. Performance varied across districts and thresholds, and no correctly predicted floods were found in the northern districts that were evaluated. At a seven-day lead time, Google Flood Hub’s false-alarm ratio was around 0.8 across discharge thresholds, compared with around 0.5 for GloFAS. The authors describe GloFAS as more balanced in several comparisons. They used a ten-day matching window to compare forecasts with reported impacts, which affects the interpretation of performance. This was a retrospective forecast evaluation; it did not measure benefits from an implemented early action. The researchers are independent of Google, although one coauthor works at the Joint Research Centre, which contributes to GloFAS." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0092-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Google Flood Hub" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Independent evaluation finds Google Flood Hub and GloFAS forecasts skillful beyond four days in Mali's frequently flooded regions, suggesting seven-day Red Cross early-action triggers", "headline": "Study suggests seven-day flood warnings in parts of Mali" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0092-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "6a7e928484f2c855dedc6488ab41753b9edb46481b759f3433d7738dd3e35bab" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Researchers evaluated Google Flood Hub and GloFAS forecasts against river-flow observations and records of flood impacts in Mali. Their results suggest that some early-action plans could extend from four to seven days without much loss of forecast skill. Performance varied across districts and thresholds, and no correctly predicted floods were found in the northern districts that were evaluated. At a seven-day lead time, Google Flood Hub’s false-alarm ratio was around 0.8 across discharge thresholds, compared with around 0.5 for GloFAS. The authors describe GloFAS as more balanced in several comparisons. They used a ten-day matching window to compare forecasts with reported impacts, which affects the interpretation of performance. This was a retrospective forecast evaluation; it did not measure benefits from an implemented early action. The researchers are independent of Google, although one coauthor works at the Joint Research Centre, which contributes to GloFAS.", "replication": { "produced_by": [ "Global AI flood forecasts available for ungauged Malian rivers", "Evaluation against discharge observations and text-mined district-level impact data across lead times and thresholds" ], "must_hold": [ "Forecast thresholds and matching windows require local validation; performance differs substantially by district", "Frequent false alarms need to be considered alongside the potential for earlier warnings", "The proposed change to early-action planning requires implementation and outcome evaluation" ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0092-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 4, "record_mapped": 27, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0072", "title": "AI-supported Electronic Babylonian Library platform identifies manuscripts of a lost Hymn to Babylon, published in the journal Iraq", "summary": "LMU's AI-supported eBL platform identified further manuscripts of a lost Hymn to Babylon; edition published in Iraq (online 17 March 2025)", "date_observed": "2025-03-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Assyriologists Anmar A. Fadhil (University of Baghdad) and Enrique Jiménez (LMU Munich) published an edition of a previously unknown Babylonian hymn. It praises Babylon and its people and is in the journal Iraq (volume 86, online 17 March 2025). The composition may have been about 250 lines long. It survives in no fewer than 20 manuscripts dating from the 7th to the 2nd/1st centuries BCE. They come from the Sippar Library tablets. Per LMU's press release of 1 July 2025, the team's AI-supported Electronic Babylonian Library platform identified 30 further manuscripts belonging to the hymn. That would formerly have taken decades. The article itself states that without the eBL platform the edition could not have used 21 manuscripts in 31 fragments.", "category": "benefit created", "unexpected": false, "purpose": "Match and join cuneiform fragments across collections to reconstruct Babylonian literary texts", "system": "Electronic Babylonian Library (eBL) Fragmentarium, AI-supported fragment-matching platform", "model_version": null, "developer": "LMU Munich, Institute of Assyriology (Enrique Jiménez's eBL project)", "deployer": "LMU Munich and University of Baghdad collaboration", "location": "Munich, Germany", "domain": "Linguistics and ancient texts", "segment": "Assyriology and cuneiform studies", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: a peer-reviewed edition for the LMU and Baghdad teams. The sources describe a scholarly publication, no institutional change" }, { "group": "societal", "depth": 1, "reason": "Small: recovery of one lost literary text. The press release calls it a fascinating hymn describing Babylon and its inhabitants" } ], "ai_role": { "status": "assessed", "statement": "The platform's matching identified additional manuscripts of the hymn (30 per the LMU release; the edition uses 21 manuscripts in 31 fragments per the article). The edition, translation and interpretation were done by the two authors. The AI attribution comes from the LMU release, in which Jiménez speaks of “our AI-supported platform”. The article credits the eBL platform and team without mentioning artificial intelligence. The LMU release is vendor-authored, since LMU is the platform's developer, and ScienceAlert mainly relays that release and the paper. The peer-reviewed edition appeared in Iraq. Its first author Anmar A. Fadhil is at the University of Baghdad, with one developer co-author (Jiménez)." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Fadhil, A. A., Jiménez, E. (2024/2025). Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians. Iraq 86, 21–78.", "title": "Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians", "url": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "date": "2025-03-17", "written_by": "makers", "quote": "Without the eBL platform and the work of the entire eBL team, it would be impossible for this edition to use 21 manuscripts, consisting of 31 fragments" }, { "kind": "press release", "citation": "LMU Munich (2025). LMU professor Enrique Jiménez discovered hymn to Babylon. LMU press release.", "title": "LMU professor Enrique Jiménez discovered hymn to Babylon", "url": "https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "date": "2025-07-01", "written_by": "makers", "quote": "Using our AI-supported platform, we managed to identify 30 other manuscripts that belong to the rediscovered hymn – a process that would formerly have taken decades." }, { "kind": "news report", "citation": "Cockerill, J. (2025). Classic hymn deciphered from ancient Babylonian library. ScienceAlert.", "title": "Classic hymn deciphered from ancient Babylonian library", "url": "https://www.sciencealert.com/classic-hymn-deciphered-from-ancient-babylonian-library", "date": "2025-07-07", "written_by": "independent", "quote": "have now found a 250-line hymn in praise of the ancient city by comparing text scattered across numerous fragments on tablets" } ], "replication": { "produced_by": [ "Digitized transliterations of cuneiform fragments in the eBL Fragmentarium", "Algorithmic matching of sign sequences across fragments and collections", "Philological edition and translation by Fadhil and Jiménez" ], "must_hold": [ "Fragment transliterations exist in the database", "Overlapping text between manuscripts allows joins", "Each proposed join is verified by Assyriologists" ], "echoes": [] }, "paired_incident": null, "headline": "LMU's eBL platform finds manuscripts of a lost Hymn to Babylon", "metric": "without the eBL platform the edition could not have used 21 manuscripts in 31 fragments", "comparator": { "against": "an edition prepared without the eBL platform", "before": "impossible for this edition to use 21 manuscripts, consisting of 31 fragments", "after": "21 manuscripts, consisting of 31 fragments, most of them previously published only on eBL", "basis": "assumed", "quote": "Without the eBL platform and the work of the entire eBL team, it would be impossible for this edition to use 21 manuscripts, consisting of 31 fragments, most of them previously published only on eBL.", "url": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article" }, "later": { "status": "persisted", "date": "2025-07-01", "note": "Three and a half months after the edition appeared, LMU's press release restated the finding and credited the AI-supported platform with identifying 30 further manuscripts of the hymn.", "quote": "Using our AI-supported platform, we managed to identify 30 other manuscripts that belong to the rediscovered hymn – a process that would formerly have taken decades.", "url": "https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html" }, "value": null, "developer_country": "Germany", "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reclassified the LMU press release as vendor-authored (LMU is the platform's developer) and the Iraq article as not vendor-authored (University of Baghdad first author, one developer co-author), and restated in the system's part that admission rests on the peer-reviewed edition and that the AI attribution comes from the LMU release, not from the article.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article; https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich; https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' peer-reviewed study and the makers' press release. 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Fadhil (University of Baghdad) and Enrique Jiménez (LMU Munich) published an edition of a previously unknown Babylonian hymn. It praises Babylon and its people and is in the journal Iraq (volume 86, online 17 March 2025). The composition may have been about 250 lines long. It survives in no fewer than 20 manuscripts dating from the 7th to the 2nd/1st centuries BCE. They come from the Sippar Library tablets. Per LMU's press release of 1 July 2025, the team's AI-supported Electronic Babylonian Library platform identified 30 further manuscripts belonging to the hymn. That would formerly have taken decades. The article itself states that without the eBL platform the edition could not have used 21 manuscripts in 31 fragments.", "benefit_type": "Improved Knowledge Discovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: a peer-reviewed edition for the LMU and Baghdad teams. 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The press release calls it a fascinating hymn describing Babylon and its inhabitants" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Match and join cuneiform fragments across collections to reconstruct Babylonian literary texts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Munich, Germany", "developer_country": "Germany", "deployer_country": "Germany" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Match and join cuneiform fragments across collections to reconstruct Babylonian literary texts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-17", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reclassified the LMU press release as vendor-authored (LMU is the platform's developer) and the Iraq article as not vendor-authored (University of Baghdad first author, one developer co-author), and restated in the system's part that admission rests on the peer-reviewed edition and that the AI attribution comes from the LMU release, not from the article.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article; https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich; https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Digitized transliterations of cuneiform fragments in the eBL Fragmentarium", "Algorithmic matching of sign sequences across fragments and collections", "Philological edition and translation by Fadhil and Jiménez" ], "must_hold": [ "Fragment transliterations exist in the database", "Overlapping text between manuscripts allows joins", "Each proposed join is verified by Assyriologists" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reclassified the LMU press release as vendor-authored (LMU is the platform's developer) and the Iraq article as not vendor-authored (University of Baghdad first author, one developer co-author), and restated in the system's part that admission rests on the peer-reviewed edition and that the AI attribution comes from the LMU release, not from the article.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article; https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich; https://en.wikipedia.org/wiki/Ludwig_Maximilian_University_of_Munich", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Linguistics and ancient texts", "segment": "Assyriology and cuneiform studies" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Fadhil, A. A., Jiménez, E. (2024/2025). Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians. Iraq 86, 21–78.", "title": "Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians", "url": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "date": "2025-03-17", "written_by": "makers", "quote": "Without the eBL platform and the work of the entire eBL team, it would be impossible for this edition to use 21 manuscripts, consisting of 31 fragments" }, { "kind": "press release", "citation": "LMU Munich (2025). LMU professor Enrique Jiménez discovered hymn to Babylon. LMU press release.", "title": "LMU professor Enrique Jiménez discovered hymn to Babylon", "url": "https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "date": "2025-07-01", "written_by": "makers", "quote": "Using our AI-supported platform, we managed to identify 30 other manuscripts that belong to the rediscovered hymn – a process that would formerly have taken decades." }, { "kind": "news report", "citation": "Cockerill, J. (2025). Classic hymn deciphered from ancient Babylonian library. ScienceAlert.", "title": "Classic hymn deciphered from ancient Babylonian library", "url": "https://www.sciencealert.com/classic-hymn-deciphered-from-ancient-babylonian-library", "date": "2025-07-07", "written_by": "independent", "quote": "have now found a 250-line hymn in praise of the ancient city by comparing text scattered across numerous fragments on tablets" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0072-source-0001", "AIBD-0072-source-0002", "AIBD-0072-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Fadhil, A. A., Jiménez, E. (2024/2025). Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians. Iraq 86, 21–78.", "title": "Literary Texts from the Sippar Library V: A Hymn in Praise of Babylon and the Babylonians", "url": "https://www.cambridge.org/core/product/identifier/S0021088924000238/type/journal_article", "date": "2025-03-17", "written_by": "makers", "quote": "Without the eBL platform and the work of the entire eBL team, it would be impossible for this edition to use 21 manuscripts, consisting of 31 fragments" }, { "kind": "press release", "citation": "LMU Munich (2025). LMU professor Enrique Jiménez discovered hymn to Babylon. LMU press release.", "title": "LMU professor Enrique Jiménez discovered hymn to Babylon", "url": "https://www.lmu.de/en/about-lmu/structure/central-university-administration/media-relations-and-communications/press-room/press-release/lmu-professor-enrique-jimenez-discovered-hymn-to-babylon-8e671888.html", "date": "2025-07-01", "written_by": "makers", "quote": "Using our AI-supported platform, we managed to identify 30 other manuscripts that belong to the rediscovered hymn – a process that would formerly have taken decades." }, { "kind": "news report", "citation": "Cockerill, J. (2025). Classic hymn deciphered from ancient Babylonian library. ScienceAlert.", "title": "Classic hymn deciphered from ancient Babylonian library", "url": "https://www.sciencealert.com/classic-hymn-deciphered-from-ancient-babylonian-library", "date": "2025-07-07", "written_by": "independent", "quote": "have now found a 250-line hymn in praise of the ancient city by comparing text scattered across numerous fragments on tablets" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "LMU's AI-supported eBL platform identified further manuscripts of a lost Hymn to Babylon; edition published in Iraq (online 17 March 2025)", "account": "Assyriologists Anmar A. Fadhil (University of Baghdad) and Enrique Jiménez (LMU Munich) published an edition of a previously unknown Babylonian hymn. It praises Babylon and its people and is in the journal Iraq (volume 86, online 17 March 2025). The composition may have been about 250 lines long. It survives in no fewer than 20 manuscripts dating from the 7th to the 2nd/1st centuries BCE. They come from the Sippar Library tablets. Per LMU's press release of 1 July 2025, the team's AI-supported Electronic Babylonian Library platform identified 30 further manuscripts belonging to the hymn. That would formerly have taken decades. The article itself states that without the eBL platform the edition could not have used 21 manuscripts in 31 fragments." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Electronic Babylonian Library (eBL) Fragmentarium, AI-supported fragment-matching platform" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "LMU Munich, Institute of Assyriology (Enrique Jiménez's eBL project)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-supported Electronic Babylonian Library platform identifies manuscripts of a lost Hymn to Babylon, published in the journal Iraq", "headline": "LMU's eBL platform finds manuscripts of a lost Hymn to Babylon" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e794ce418f9d7ba9bb80ad891d08db0b3a3b69ba1d10939a776d2b1b8acf6fad" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Assyriologists Anmar A. Fadhil (University of Baghdad) and Enrique Jiménez (LMU Munich) published an edition of a previously unknown Babylonian hymn. It praises Babylon and its people and is in the journal Iraq (volume 86, online 17 March 2025). The composition may have been about 250 lines long. It survives in no fewer than 20 manuscripts dating from the 7th to the 2nd/1st centuries BCE. They come from the Sippar Library tablets. Per LMU's press release of 1 July 2025, the team's AI-supported Electronic Babylonian Library platform identified 30 further manuscripts belonging to the hymn. That would formerly have taken decades. The article itself states that without the eBL platform the edition could not have used 21 manuscripts in 31 fragments.", "replication": { "produced_by": [ "Digitized transliterations of cuneiform fragments in the eBL Fragmentarium", "Algorithmic matching of sign sequences across fragments and collections", "Philological edition and translation by Fadhil and Jiménez" ], "must_hold": [ "Fragment transliterations exist in the database", "Overlapping text between manuscripts allows joins", "Each proposed join is verified by Assyriologists" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0382", "title": "ASENA narcotics analysis software flags a car at the Köy Hizmetleri checkpoint in Şırnak; the dog Hector finds 86.6 kg of skunk in 119 packages and three lawyers are remanded", "summary": "Şırnak police stopped a car selected by the ASENA narcotics analysis software; the dog Hector found 86.6 kg of skunk in 119 packages in the trunk, and three lawyers were remanded (March 2025).", "date_observed": "2025-03-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Şırnak Provincial Police stopped a vehicle at the Köy Hizmetleri (Village Services) police checkpoint after ASENA selected it for inspection. DHA calls ASENA police software “in artificial intelligence format”. The narcotics dog Hector then found 86 kilograms 600 grams of skunk in 119 packages hidden in the trunk. Three occupants, M.E., H.K. and Ş.A., were detained (Sözcü/DHA and Habertürk/DHA, 17 March 2025). Diken, citing İHA, gives ASENA's full name as Analiz Sistemleri Narkotik Ağı (Narcotics Analysis Systems Network). It says the three were lawyers registered with the Mardin Bar Association. They were taken to court after police processing and remanded in custody (Diken, 18 March 2025). None of the reports gives the day of the stop, what data ASENA analyzed or how it chose the car, or any official's name.", "category": "benefit created", "unexpected": false, "purpose": "Police analysis software built to pick out vehicles and people likely to be carrying narcotics for checkpoint stops. This seizure was that use.", "system": "ASENA (Analiz Sistemleri Narkotik Ağı), Turkish police narcotics analysis software", "model_version": null, "developer": null, "deployer": "Şırnak Provincial Police Directorate (Turkish National Police)", "location": "Şırnak, Turkey", "domain": "Law enforcement / narcotics interdiction", "segment": "Checkpoint vehicle screening", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-03-17-8c32" }, "ratings": [ { "group": "societal", "depth": 2, "reason": "86.6 kg of skunk was taken out of circulation and three suspects remanded. A measurable interdiction result, but the reports specify no downstream harm averted." }, { "group": "organizational", "depth": 2, "reason": "The Şırnak police turned a software flag into a large seizure and three remands, per the DHA and İHA reports. A measurable result for the unit." } ], "ai_role": { "status": "assessed", "statement": "ASENA supplied the selection and nothing more. DHA's wording is that the vehicle was identified and stopped “thanks to the ASENA software”. The dog Hector then found the packages and officers made the arrests. No report describes ASENA's inputs, its ranking method, or whether an analyst reviewed the flag before the stop." }, "evidence": [ { "kind": "news report", "citation": "Sözcü / DHA (2025). 86 kilo uyuşturucuyu narkotik köpeği buldu. Sözcü, March 17, 2025.", "title": "86 kilo uyuşturucuyu narkotik köpeği buldu", "url": "https://www.sozcu.com.tr/86-kilo-uyusturucuyu-narkotik-kopegi-buldu-p151719", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım" }, { "kind": "news report", "citation": "Habertürk / DHA (2025). Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu. Habertürk, March 17, 2025.", "title": "Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu", "url": "https://yerel-haberler.haberturk.com/sirnak-haberleri/durdurulan-aractaki-86-kilo-uyusturucuyu-hektor-buldu-112096987", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım olan ASENA yazılımı sayesinde" }, { "kind": "news report", "citation": "Diken / İHA (2025). Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı. Diken, March 18, 2025.", "title": "Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı", "url": "https://www.diken.com.tr/sirnakta-86-kilo-uyusturucuyla-yakalanan-uc-avukat-tutuklandi", "date": "2025-03-18", "written_by": "independent", "quote": "Analiz Sistemleri Narkotik Ağı" }, { "kind": "registry label", "citation": "OECD.AI (2025). AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested. OECD AI Incidents and Hazards Monitor, 2025-03-17.", "title": "AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested", "url": "https://oecd.ai/en/incidents/2025-03-17-8c32", "date": "2025-03-17", "written_by": "independent", "quote": "used the ASENA AI narcotics analysis system and detection dog Hector to intercept a vehicle, uncovering 86.6 kg of skunk cannabis" } ], "replication": { "produced_by": [ "A police analysis program that ranks vehicles for interdiction", "A fixed checkpoint at which a flagged car can be stopped and searched", "A narcotics dog and officers prepared to search the trunk" ], "must_hold": [ "The flag must be followed by a lawful stop and a physical search. The software only selects", "Seized material and arrests must be carried through prosecution" ], "echoes": [] }, "paired_incident": null, "headline": "ASENA flags a car at a Şırnak checkpoint; 86.6 kg of skunk found", "metric": "86.6 kg of skunk in 119 packages", "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-17-8c32", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0382", "catalog_version": "1.0.0", "source_fingerprint": "dfb098d8d930258fe8fdd8c4942e4947cefe5cd57f667980f8d2a644a86efc2f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0382-source-0001", "AIBD-0382-source-0002", "AIBD-0382-source-0003", "AIBD-0382-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Şırnak Provincial Police Directorate (Turkish National Police)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ASENA supplied the selection and nothing more. DHA's wording is that the vehicle was identified and stopped “thanks to the ASENA software”. The dog Hector then found the packages and officers made the arrests. No report describes ASENA's inputs, its ranking method, or whether an analyst reviewed the flag before the stop." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "ASENA supplied the selection and nothing more. DHA's wording is that the vehicle was identified and stopped “thanks to the ASENA software”. The dog Hector then found the packages and officers made the arrests. 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"value": { "kind": "record_fields", "fields": { "id": "AIBD-0382" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Şırnak Provincial Police stopped a vehicle at the Köy Hizmetleri (Village Services) police checkpoint after ASENA selected it for inspection. DHA calls ASENA police software “in artificial intelligence format”. The narcotics dog Hector then found 86 kilograms 600 grams of skunk in 119 packages hidden in the trunk. Three occupants, M.E., H.K. and Ş.A., were detained (Sözcü/DHA and Habertürk/DHA, 17 March 2025). Diken, citing İHA, gives ASENA's full name as Analiz Sistemleri Narkotik Ağı (Narcotics Analysis Systems Network). It says the three were lawyers registered with the Mardin Bar Association. They were taken to court after police processing and remanded in custody (Diken, 18 March 2025). None of the reports gives the day of the stop, what data ASENA analyzed or how it chose the car, or any official's name.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "86.6 kg of skunk was taken out of circulation and three suspects remanded. A measurable interdiction result, but the reports specify no downstream harm averted." }, { "group": "organizational", "depth": 2, "reason": "The Şırnak police turned a software flag into a large seizure and three remands, per the DHA and İHA reports. A measurable result for the unit." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Police analysis software built to pick out vehicles and people likely to be carrying narcotics for checkpoint stops. This seizure was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Şırnak, Turkey", "deployer_country": "Turkey" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Police analysis software built to pick out vehicles and people likely to be carrying narcotics for checkpoint stops. This seizure was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-17", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-17-8c32", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/General_Directorate_of_Security_(Turkey)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A police analysis program that ranks vehicles for interdiction", "A fixed checkpoint at which a flagged car can be stopped and searched", "A narcotics dog and officers prepared to search the trunk" ], "must_hold": [ "The flag must be followed by a lawful stop and a physical search. 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Sözcü, March 17, 2025.", "title": "86 kilo uyuşturucuyu narkotik köpeği buldu", "url": "https://www.sozcu.com.tr/86-kilo-uyusturucuyu-narkotik-kopegi-buldu-p151719", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım" }, { "kind": "news report", "citation": "Habertürk / DHA (2025). Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu. Habertürk, March 17, 2025.", "title": "Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu", "url": "https://yerel-haberler.haberturk.com/sirnak-haberleri/durdurulan-aractaki-86-kilo-uyusturucuyu-hektor-buldu-112096987", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım olan ASENA yazılımı sayesinde" }, { "kind": "news report", "citation": "Diken / İHA (2025). Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı. Diken, March 18, 2025.", "title": "Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı", "url": "https://www.diken.com.tr/sirnakta-86-kilo-uyusturucuyla-yakalanan-uc-avukat-tutuklandi", "date": "2025-03-18", "written_by": "independent", "quote": "Analiz Sistemleri Narkotik Ağı" }, { "kind": "registry label", "citation": "OECD.AI (2025). AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested. OECD AI Incidents and Hazards Monitor, 2025-03-17.", "title": "AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested", "url": "https://oecd.ai/en/incidents/2025-03-17-8c32", "date": "2025-03-17", "written_by": "independent", "quote": "used the ASENA AI narcotics analysis system and detection dog Hector to intercept a vehicle, uncovering 86.6 kg of skunk cannabis" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0382-source-0001", "AIBD-0382-source-0002", "AIBD-0382-source-0003", "AIBD-0382-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Sözcü / DHA (2025). 86 kilo uyuşturucuyu narkotik köpeği buldu. Sözcü, March 17, 2025.", "title": "86 kilo uyuşturucuyu narkotik köpeği buldu", "url": "https://www.sozcu.com.tr/86-kilo-uyusturucuyu-narkotik-kopegi-buldu-p151719", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım" }, { "kind": "news report", "citation": "Habertürk / DHA (2025). Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu. Habertürk, March 17, 2025.", "title": "Durdurulan araçtaki 86 kilo uyuşturucuyu Hektor buldu", "url": "https://yerel-haberler.haberturk.com/sirnak-haberleri/durdurulan-aractaki-86-kilo-uyusturucuyu-hektor-buldu-112096987", "date": "2025-03-17", "written_by": "independent", "quote": "yapay zeka formatında bir yazılım olan ASENA yazılımı sayesinde" }, { "kind": "news report", "citation": "Diken / İHA (2025). Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı. Diken, March 18, 2025.", "title": "Şırnak'ta 86 kilo uyuşturucuyla yakalanan üç avukat tutuklandı", "url": "https://www.diken.com.tr/sirnakta-86-kilo-uyusturucuyla-yakalanan-uc-avukat-tutuklandi", "date": "2025-03-18", "written_by": "independent", "quote": "Analiz Sistemleri Narkotik Ağı" }, { "kind": "registry label", "citation": "OECD.AI (2025). AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested. OECD AI Incidents and Hazards Monitor, 2025-03-17.", "title": "AI-Driven Raid Seizes 86.6 kg of Drugs in Şırnak, Three Lawyers Arrested", "url": "https://oecd.ai/en/incidents/2025-03-17-8c32", "date": "2025-03-17", "written_by": "independent", "quote": "used the ASENA AI narcotics analysis system and detection dog Hector to intercept a vehicle, uncovering 86.6 kg of skunk cannabis" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Şırnak police stopped a car selected by the ASENA narcotics analysis software; the dog Hector found 86.6 kg of skunk in 119 packages in the trunk, and three lawyers were remanded (March 2025).", "account": "Şırnak Provincial Police stopped a vehicle at the Köy Hizmetleri (Village Services) police checkpoint after ASENA selected it for inspection. DHA calls ASENA police software “in artificial intelligence format”. The narcotics dog Hector then found 86 kilograms 600 grams of skunk in 119 packages hidden in the trunk. Three occupants, M.E., H.K. and Ş.A., were detained (Sözcü/DHA and Habertürk/DHA, 17 March 2025). Diken, citing İHA, gives ASENA's full name as Analiz Sistemleri Narkotik Ağı (Narcotics Analysis Systems Network). It says the three were lawyers registered with the Mardin Bar Association. They were taken to court after police processing and remanded in custody (Diken, 18 March 2025). None of the reports gives the day of the stop, what data ASENA analyzed or how it chose the car, or any official's name." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ASENA (Analiz Sistemleri Narkotik Ağı), Turkish police narcotics analysis software" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ASENA narcotics analysis software flags a car at the Köy Hizmetleri checkpoint in Şırnak; the dog Hector finds 86.6 kg of skunk in 119 packages and three lawyers are remanded", "headline": "ASENA flags a car at a Şırnak checkpoint; 86.6 kg of skunk found" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "dfb098d8d930258fe8fdd8c4942e4947cefe5cd57f667980f8d2a644a86efc2f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Şırnak Provincial Police stopped a vehicle at the Köy Hizmetleri (Village Services) police checkpoint after ASENA selected it for inspection. DHA calls ASENA police software “in artificial intelligence format”. The narcotics dog Hector then found 86 kilograms 600 grams of skunk in 119 packages hidden in the trunk. Three occupants, M.E., H.K. and Ş.A., were detained (Sözcü/DHA and Habertürk/DHA, 17 March 2025). Diken, citing İHA, gives ASENA's full name as Analiz Sistemleri Narkotik Ağı (Narcotics Analysis Systems Network). It says the three were lawyers registered with the Mardin Bar Association. They were taken to court after police processing and remanded in custody (Diken, 18 March 2025). None of the reports gives the day of the stop, what data ASENA analyzed or how it chose the car, or any official's name.", "replication": { "produced_by": [ "A police analysis program that ranks vehicles for interdiction", "A fixed checkpoint at which a flagged car can be stopped and searched", "A narcotics dog and officers prepared to search the trunk" ], "must_hold": [ "The flag must be followed by a lawful stop and a physical search. The software only selects", "Seized material and arrests must be carried through prosecution" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0078", "title": "Viz ICH Plus detects a parieto-occipital hemorrhage and auto-alerts the transfer team; 47-year-old moved between hospitals of a large urban health system in 101 minutes, mRS 1 at one year", "summary": "Viz ICH Plus flagged a 47-year-old's haematoma and alerted the transfer team; transfer in 101 min vs 199.7 average; mRS 1 at one year.", "date_observed": "2025-03-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 47-year-old man came to the transferring hospital of the authors' large urban health system. He had severe headache, nausea and vomiting but no speech or motor deficits. The paper names neither the hospitals nor the city. All authors are at the Icahn School of Medicine at Mount Sinai, New York. Viz ICH Plus (Viz.ai) analyzed his computed tomography (CT), revealing a substantial right parieto-occipital haematoma with ventricular extension. It auto-alerted the Neuroemergencies Management and Transfer (NEMAT) team at the receiving specialized stroke center. With an ICH score of 2 he was transferred within 101 minutes across 13.7 miles, against an average interhospital transfer time of 199.7 minutes. He had supratentorial craniotomy with endoscopic haematoma evacuation and ventriculoperitoneal shunt placement. His scores were mRS 4 and NIHSS 6 at one month, 3 and 5 at three months. At one year: mRS 1 and NIHSS 2.", "category": "harm prevented", "unexpected": false, "purpose": "Viz ICH Plus is built to detect intracranial hemorrhage on non-contrast CT and automatically notify care and transfer teams. Faster interhospital transfer is its intended function.", "system": "Viz ICH Plus", "model_version": null, "developer": "Viz.ai", "deployer": "Large urban healthcare system, not named in the report; the city is not stated, and all authors are affiliated with Neurosurgery, Icahn School of Medicine at Mount Sinai, New York", "location": null, "domain": "Healthcare - neurosurgery / intracerebral hemorrhage", "segment": "AI hemorrhage detection with automated transfer notification", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "After a hemorrhage with ventricular extension the patient improved from mRS 4 at one month to mRS 1 at one year. The AI's share is the time saved in transfer, the surgery being the treatment." }, { "group": "organizational", "depth": 2, "reason": "Interhospital transfer took 101 minutes against the system's 199.7-minute average, with the receiving team engaged before the patient left the first hospital." } ], "ai_role": { "status": "assessed", "statement": "The software detected the haematoma and auto-alerted the receiving team, which coordinated stabilization advice and transfer. A CT ordered for severe headache would have shown the bleed regardless, so the AI's contribution is the speed of notification and transfer. Dr Kellner discloses research grant support from Viz.AI among other companies. No author is a Viz.ai employee." }, "evidence": [ { "kind": "case report", "citation": "Afreen R, Ezzat B, Kalagara R, Dangayach NS, Kellner CP (2025). Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology. Cureus 17(3):e80790.", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "Viz ICH Plus analyzed the patient's CT, revealing a substantial right parieto-occipital hematoma with ventricular extension, and automatically alerted the Neuroemergencies Management and Transfer (NEMAT) team" }, { "kind": "case report", "citation": "Afreen R et al. (2025). Cureus 17(3):e80790 (second quotation).", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "With an ICH score of 2, the patient was transferred within 101 minutes across a 13.7-mile distance - much faster than the average IHT time of 199.7 minutes" }, { "kind": "case report", "citation": "Afreen R et al. (2025). Cureus 17(3):e80790 (third quotation, one-year outcome).", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "one year, his scores had further improved to mRS 1 and NIHSS 2" } ], "replication": { "produced_by": [ "Viz ICH Plus running on CT scans at the transferring hospital with automatic notification to a centralized neuro-emergency transfer team", "A command-center workflow that coordinates stabilization advice and ambulance transfer" ], "must_hold": [ "A receiving center able to operate promptly", "Clinicians act on the automated alert rather than waiting for a formal radiology read" ], "echoes": [] }, "paired_incident": null, "headline": "Viz ICH Plus flags a haematoma; transfer in 101 minutes, mRS 1", "metric": "transfer in 101 min vs 199.7 average; mRS 1 at one year", "comparator": { "against": "the average interhospital transfer time for similar intracerebral hemorrhage cases, taken from a published New York City hospital-system cohort", "before": "199.7 minutes", "after": "101 minutes", "basis": "measured", "quote": "With an ICH score of 2, the patient was transferred within 101 minutes across a 13.7-mile distance - much faster than the average IHT time of 199.7 minutes for similar cases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/" }, "later": { "status": "unknown", "date": null, "note": "The report ends at the one-year outcome; nothing later was found in the cited source.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the New York placement from the title, account and deployer and set location to null, stating instead that the paper names neither the hospitals nor the city and that the authors are affiliated with the Icahn School of Medicine at Mount Sinai, New York, because the paper describes only “our large urban healthcare system” and the city had been inferred from the affiliation line.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.viz.ai/privacy-policy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0078", "catalog_version": "1.0.0", "source_fingerprint": "b7c100236750549c264a6987267138ea67496b9d72ab3497e21e3616de147237", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0078-source-0001", "AIBD-0078-source-0002", "AIBD-0078-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Viz.ai", "deployer": "Large urban healthcare system, not named in the report; the city is not stated, and all authors are affiliated with Neurosurgery, Icahn School of Medicine at Mount Sinai, New York" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The software detected the haematoma and auto-alerted the receiving team, which coordinated stabilization advice and transfer. A CT ordered for severe headache would have shown the bleed regardless, so the AI's contribution is the speed of notification and transfer. Dr Kellner discloses research grant support from Viz.AI among other companies. No author is a Viz.ai employee." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The software detected the haematoma and auto-alerted the receiving team, which coordinated stabilization advice and transfer. A CT ordered for severe headache would have shown the bleed regardless, so the AI's contribution is the speed of notification and transfer. Dr Kellner discloses research grant support from Viz.AI among other companies. No author is a Viz.ai employee." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After a hemorrhage with ventricular extension the patient improved from mRS 4 at one month to mRS 1 at one year. The AI's share is the time saved in transfer, the surgery being the treatment." }, { "group": "organizational", "depth": 2, "reason": "Interhospital transfer took 101 minutes against the system's 199.7-minute average, with the receiving team engaged before the patient left the first hospital." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After a hemorrhage with ventricular extension the patient improved from mRS 4 at one month to mRS 1 at one year. The AI's share is the time saved in transfer, the surgery being the treatment." }, { "group": "organizational", "depth": 2, "reason": "Interhospital transfer took 101 minutes against the system's 199.7-minute average, with the receiving team engaged before the patient left the first hospital." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "After a hemorrhage with ventricular extension the patient improved from mRS 4 at one month to mRS 1 at one year. The AI's share is the time saved in transfer, the surgery being the treatment." }, { "group": "organizational", "depth": 2, "reason": "Interhospital transfer took 101 minutes against the system's 199.7-minute average, with the receiving team engaged before the patient left the first hospital." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", 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He had severe headache, nausea and vomiting but no speech or motor deficits. The paper names neither the hospitals nor the city. All authors are at the Icahn School of Medicine at Mount Sinai, New York. Viz ICH Plus (Viz.ai) analyzed his computed tomography (CT), revealing a substantial right parieto-occipital haematoma with ventricular extension. It auto-alerted the Neuroemergencies Management and Transfer (NEMAT) team at the receiving specialized stroke center. With an ICH score of 2 he was transferred within 101 minutes across 13.7 miles, against an average interhospital transfer time of 199.7 minutes. He had supratentorial craniotomy with endoscopic haematoma evacuation and ventriculoperitoneal shunt placement. His scores were mRS 4 and NIHSS 6 at one month, 3 and 5 at three months. At one year: mRS 1 and NIHSS 2.", "replication": { "produced_by": [ "Viz ICH Plus running on CT scans at the transferring hospital with automatic notification to a centralized neuro-emergency transfer team", "A command-center workflow that coordinates stabilization advice and ambulance transfer" ], "must_hold": [ "A receiving center able to operate promptly", "Clinicians act on the automated alert rather than waiting for a formal radiology read" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0126", "title": "Delhi Police matched a CCTV frame to a prior arrest record with Israeli facial recognition software, arrested two men within about a day of a Rs 80 lakh armed robbery in Chandni Chowk and recovered Rs 79.5 lakh", "summary": "Facial recognition on CCTV named a Chandni Chowk robber; two arrested within about a day and Rs 79.5 lakh of the Rs 80 lakh recovered.", "date_observed": "2025-03-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On the evening of 17 March 2025, cash courier Ajmal Bhai Ganesh, 49, of R K Enterprises was robbed at gunpoint of Rs 80 lakh. It was near his Fatehpuri home, Chandni Chowk, Delhi. Delhi Police's North district analyzed some 500 closed-circuit television (CCTV) cameras' footage. Israeli facial recognition software matched a frame of a man who had followed the victim to a record at Kotwali police station. That gave Mohammad Ali, 21, of Daryaganj. Ali was arrested early on 19 March (the Times of India says Tuesday) and named Samir, 19, arrested in Daryaganj. A raid on Samir's home found Rs 79.5 lakh and a semi-automatic pistol, which police called the entire amount.", "category": "benefit created", "unexpected": false, "purpose": "The software was deployed to identify people in CCTV footage by matching faces against police databases. Naming a robbery suspect from a frame is that function.", "system": "Israeli facial recognition software used by Delhi Police (not named in the reports)", "model_version": null, "developer": null, "deployer": "Delhi Police, North district", "location": "Delhi, India", "domain": "Policing / robbery investigation", "segment": "CCTV-based suspect identification in an armed robbery case", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-03-19-2b12" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Ajmal Bhai Ganesh and his employer R K Enterprises recovered Rs 79.5 lakh of the Rs 80 lakh taken at gunpoint. Police described that as the entire amount. A large material loss reversed within two days." }, { "group": "organizational", "depth": 2, "reason": "Delhi Police's North district cleared an armed robbery whose video had gone viral within about 24 hours. Both accused are in judicial custody under the BNS and Arms Act and the pistol recovered." }, { "group": "societal", "depth": 1, "reason": "Two men who had surveilled cash couriers and used a firearm were taken off the street. The reports give no evidence of further robberies prevented, so the public benefit is small." } ], "ai_role": { "status": "assessed", "statement": "By DCP (North) Raja Banthia's account, teams took a screengrab of a man seen following the victim. The Israeli software matched it to a prior record from Kotwali police station with a similarity score of 32.09 percent. That gave them Ali's name and his Daryaganj address. A score that low is a lead, not an identification. Police confirmed it by laying a trap and interrogating Ali. The auto-rickshaw trace, the reconnaissance evidence and Samir's arrest came from conventional work. The reports name neither the software nor its vendor." }, "evidence": [ { "kind": "news report", "citation": "The Times of India (2025). Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs. The Times of India, Delhi, 19 March 2025.", "title": "Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs", "url": "https://timesofindia.indiatimes.com/city/delhi/israeli-face-recognition-software-ends-robbers-run-within-24-hrs/articleshow/119222102.cms", "date": "2025-03-19", "written_by": "independent", "quote": "A breakthrough came when Mohammad Ali's face was captured on CCTV near the crime scene. Using Israeli facial recognition software, our teams matched it with a prior criminal record" }, { "kind": "news report", "citation": "The Indian Express (2025). CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader. The Indian Express, 20 March 2025.", "title": "CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader", "url": "https://indianexpress.com/article/cities/delhi/cctv-footage-face-recognition-tech-how-delhi-cops-nabbed-two-men-who-stole-rs-80-lakh-from-trader-9895565/", "date": "2025-03-20", "written_by": "independent", "quote": "As police analysed footage from around 500 CCTV cameras, they identified Ali in the clips — as he followed Ajmal — through a facial recognition system." }, { "kind": "news report", "citation": "Press Trust of India via Hindustan Times (2025). Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held. Hindustan Times, 19 March 2025.", "title": "Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held", "url": "https://www.hindustantimes.com/india-news/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-2-held-101742373825793.html", "date": "2025-03-19", "written_by": "independent", "quote": "An Israeli facial recognition system has helped Delhi Police solve a case of robbery at gunpoint, arrest two accused persons, and recover the entire stolen amount of ₹80 lakh" }, { "kind": "news report", "citation": "Press Trust of India via Rediff.com (2025). Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held. Rediff.com, 19 March 2025.", "title": "Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "date": "2025-03-19", "written_by": "independent", "quote": "The similarity score was 32.09 percent. We got to know that the accused lived in Daryaganj, where teams were already working to trace the Scooty used in the crime" }, { "kind": "news report", "citation": "The New Indian Express (2025). Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held. The New Indian Express, 20 March 2025.", "title": "Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held", "url": "https://www.newindianexpress.com/cities/delhi/2025/Mar/20/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-two-held", "date": "2025-03-20", "written_by": "independent", "quote": "Facial recognition technology identified one suspect as Mohammad Ali, who had been arrested previously in a similar case, Deputy Commissioner of Police (North) Raja Banthia said." } ], "replication": { "produced_by": [ "Dense CCTV coverage (about 500 cameras across five areas) from which a usable frame of the suspect's face could be taken", "A police facial recognition database that already held the suspect's photograph from a prior arrest at Kotwali police station" ], "must_hold": [ "A low-similarity match (32.09 percent) is only a lead and must be confirmed by conventional investigation before arrest", "The suspect must already be in the database; a first-time offender would not have been matched" ], "echoes": [] }, "paired_incident": null, "headline": "Delhi Police facial recognition leads to Rs 79.5 lakh recovery", "metric": "two arrested within about a day and Rs 79.5 lakh of the Rs 80 lakh recovered", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No chargesheet, trial or other development after the 19-20 March 2025 arrest reports was found; the reports say only that both accused were booked.", "quote": null, "url": null }, "value": { "amount": "Rs 79.5 lakh", "what": "stolen cash recovered", "who": "the robbed cash courier's firm, R K Enterprises (recovered by Delhi Police from the accused's residence)", "estimate": false, "quote": "A raid at Samir's residence led to the recovery of Rs 79.5 lakh in cash, a semi-automatic pistol with three bullets, and other incriminating materials.", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm" }, "developer_country": null, "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-19-2b12", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0126", "catalog_version": "1.0.0", "source_fingerprint": "583679466697009ff9b744c37371ceccd1d79ea0ed2ace31dcb6a8f928a344e7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0126-source-0001", "AIBD-0126-source-0002", "AIBD-0126-source-0003", "AIBD-0126-source-0004", "AIBD-0126-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0126-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Delhi Police, North district" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "By DCP (North) Raja Banthia's account, teams took a screengrab of a man seen following the victim. The Israeli software matched it to a prior record from Kotwali police station with a similarity score of 32.09 percent. That gave them Ali's name and his Daryaganj address. A score that low is a lead, not an identification. Police confirmed it by laying a trap and interrogating Ali. The auto-rickshaw trace, the reconnaissance evidence and Samir's arrest came from conventional work. The reports name neither the software nor its vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "By DCP (North) Raja Banthia's account, teams took a screengrab of a man seen following the victim. The Israeli software matched it to a prior record from Kotwali police station with a similarity score of 32.09 percent. That gave them Ali's name and his Daryaganj address. A score that low is a lead, not an identification. Police confirmed it by laying a trap and interrogating Ali. The auto-rickshaw trace, the reconnaissance evidence and Samir's arrest came from conventional work. The reports name neither the software nor its vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ajmal Bhai Ganesh and his employer R K Enterprises recovered Rs 79.5 lakh of the Rs 80 lakh taken at gunpoint. Police described that as the entire amount. A large material loss reversed within two days." }, { "group": "organizational", "depth": 2, "reason": "Delhi Police's North district cleared an armed robbery whose video had gone viral within about 24 hours. Both accused are in judicial custody under the BNS and Arms Act and the pistol recovered." }, { "group": "societal", "depth": 1, "reason": "Two men who had surveilled cash couriers and used a firearm were taken off the street. The reports give no evidence of further robberies prevented, so the public benefit is small." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ajmal Bhai Ganesh and his employer R K Enterprises recovered Rs 79.5 lakh of the Rs 80 lakh taken at gunpoint. Police described that as the entire amount. A large material loss reversed within two days." }, { "group": "organizational", "depth": 2, "reason": "Delhi Police's North district cleared an armed robbery whose video had gone viral within about 24 hours. Both accused are in judicial custody under the BNS and Arms Act and the pistol recovered." }, { "group": "societal", "depth": 1, "reason": "Two men who had surveilled cash couriers and used a firearm were taken off the street. The reports give no evidence of further robberies prevented, so the public benefit is small." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ajmal Bhai Ganesh and his employer R K Enterprises recovered Rs 79.5 lakh of the Rs 80 lakh taken at gunpoint. Police described that as the entire amount. A large material loss reversed within two days." }, { "group": "organizational", "depth": 2, "reason": "Delhi Police's North district cleared an armed robbery whose video had gone viral within about 24 hours. Both accused are in judicial custody under the BNS and Arms Act and the pistol recovered." }, { "group": "societal", "depth": 1, "reason": "Two men who had surveilled cash couriers and used a firearm were taken off the street. 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external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "Rs 79.5 lakh", "what": "stolen cash recovered", "who": "the robbed cash courier's firm, R K Enterprises (recovered by Delhi Police from the accused's residence)", "estimate": false, "quote": "A raid at Samir's residence led to the recovery of Rs 79.5 lakh in cash, a semi-automatic pistol with three bullets, and other incriminating materials.", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "Rs 79.5 lakh", "what": "stolen cash recovered", "who": "the robbed cash courier's firm, R K Enterprises (recovered by Delhi Police from the accused's residence)", "estimate": false, "quote": "A raid at Samir's residence led to the recovery of Rs 79.5 lakh in cash, a semi-automatic pistol with three bullets, and other incriminating materials.", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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It was near his Fatehpuri home, Chandni Chowk, Delhi. Delhi Police's North district analyzed some 500 closed-circuit television (CCTV) cameras' footage. Israeli facial recognition software matched a frame of a man who had followed the victim to a record at Kotwali police station. That gave Mohammad Ali, 21, of Daryaganj. Ali was arrested early on 19 March (the Times of India says Tuesday) and named Samir, 19, arrested in Daryaganj. A raid on Samir's home found Rs 79.5 lakh and a semi-automatic pistol, which police called the entire amount.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ajmal Bhai Ganesh and his employer R K Enterprises recovered Rs 79.5 lakh of the Rs 80 lakh taken at gunpoint. Police described that as the entire amount. A large material loss reversed within two days." }, { "group": "organizational", "depth": 2, "reason": "Delhi Police's North district cleared an armed robbery whose video had gone viral within about 24 hours. Both accused are in judicial custody under the BNS and Arms Act and the pistol recovered." }, { "group": "societal", "depth": 1, "reason": "Two men who had surveilled cash couriers and used a firearm were taken off the street. The reports give no evidence of further robberies prevented, so the public benefit is small." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The software was deployed to identify people in CCTV footage by matching faces against police databases. Naming a robbery suspect from a frame is that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Delhi, India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The software was deployed to identify people in CCTV footage by matching faces against police databases. Naming a robbery suspect from a frame is that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-19", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-19-2b12", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Dense CCTV coverage (about 500 cameras across five areas) from which a usable frame of the suspect's face could be taken", "A police facial recognition database that already held the suspect's photograph from a prior arrest at Kotwali police station" ], "must_hold": [ "A low-similarity match (32.09 percent) is only a lead and must be confirmed by conventional investigation before arrest", "The suspect must already be in the database; a first-time offender would not have been matched" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-19-2b12", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added the value as stated from the cited sources.", "source": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Delhi_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / robbery investigation", "segment": "CCTV-based suspect identification in an armed robbery case" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Times of India (2025). Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs. The Times of India, Delhi, 19 March 2025.", "title": "Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs", "url": "https://timesofindia.indiatimes.com/city/delhi/israeli-face-recognition-software-ends-robbers-run-within-24-hrs/articleshow/119222102.cms", "date": "2025-03-19", "written_by": "independent", "quote": "A breakthrough came when Mohammad Ali's face was captured on CCTV near the crime scene. Using Israeli facial recognition software, our teams matched it with a prior criminal record" }, { "kind": "news report", "citation": "The Indian Express (2025). CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader. The Indian Express, 20 March 2025.", "title": "CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader", "url": "https://indianexpress.com/article/cities/delhi/cctv-footage-face-recognition-tech-how-delhi-cops-nabbed-two-men-who-stole-rs-80-lakh-from-trader-9895565/", "date": "2025-03-20", "written_by": "independent", "quote": "As police analysed footage from around 500 CCTV cameras, they identified Ali in the clips — as he followed Ajmal — through a facial recognition system." }, { "kind": "news report", "citation": "Press Trust of India via Hindustan Times (2025). Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held. Hindustan Times, 19 March 2025.", "title": "Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held", "url": "https://www.hindustantimes.com/india-news/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-2-held-101742373825793.html", "date": "2025-03-19", "written_by": "independent", "quote": "An Israeli facial recognition system has helped Delhi Police solve a case of robbery at gunpoint, arrest two accused persons, and recover the entire stolen amount of ₹80 lakh" }, { "kind": "news report", "citation": "Press Trust of India via Rediff.com (2025). Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held. Rediff.com, 19 March 2025.", "title": "Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "date": "2025-03-19", "written_by": "independent", "quote": "The similarity score was 32.09 percent. We got to know that the accused lived in Daryaganj, where teams were already working to trace the Scooty used in the crime" }, { "kind": "news report", "citation": "The New Indian Express (2025). Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held. The New Indian Express, 20 March 2025.", "title": "Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held", "url": "https://www.newindianexpress.com/cities/delhi/2025/Mar/20/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-two-held", "date": "2025-03-20", "written_by": "independent", "quote": "Facial recognition technology identified one suspect as Mohammad Ali, who had been arrested previously in a similar case, Deputy Commissioner of Police (North) Raja Banthia said." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0126-source-0001", "AIBD-0126-source-0002", "AIBD-0126-source-0003", "AIBD-0126-source-0004", "AIBD-0126-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Times of India (2025). Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs. The Times of India, Delhi, 19 March 2025.", "title": "Chandni Chowk heist: Israeli face recognition software ends robbers' run within 24 hrs", "url": "https://timesofindia.indiatimes.com/city/delhi/israeli-face-recognition-software-ends-robbers-run-within-24-hrs/articleshow/119222102.cms", "date": "2025-03-19", "written_by": "independent", "quote": "A breakthrough came when Mohammad Ali's face was captured on CCTV near the crime scene. Using Israeli facial recognition software, our teams matched it with a prior criminal record" }, { "kind": "news report", "citation": "The Indian Express (2025). CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader. The Indian Express, 20 March 2025.", "title": "CCTV footage, face recognition tech: How Delhi cops nabbed two men who stole Rs 80 lakh from trader", "url": "https://indianexpress.com/article/cities/delhi/cctv-footage-face-recognition-tech-how-delhi-cops-nabbed-two-men-who-stole-rs-80-lakh-from-trader-9895565/", "date": "2025-03-20", "written_by": "independent", "quote": "As police analysed footage from around 500 CCTV cameras, they identified Ali in the clips — as he followed Ajmal — through a facial recognition system." }, { "kind": "news report", "citation": "Press Trust of India via Hindustan Times (2025). Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held. Hindustan Times, 19 March 2025.", "title": "Israeli facial recognition tech helps Delhi Police crack ₹80 lakh robbery case; 2 held", "url": "https://www.hindustantimes.com/india-news/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-2-held-101742373825793.html", "date": "2025-03-19", "written_by": "independent", "quote": "An Israeli facial recognition system has helped Delhi Police solve a case of robbery at gunpoint, arrest two accused persons, and recover the entire stolen amount of ₹80 lakh" }, { "kind": "news report", "citation": "Press Trust of India via Rediff.com (2025). Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held. Rediff.com, 19 March 2025.", "title": "Israeli tech helps Delhi police crack Rs 80 lakh robbery; 2 held", "url": "https://www.rediff.com/news/report/israeli-tech-helps-delhi-police-crack-rs-80-lakh-robbery-2-held/20250319.htm", "date": "2025-03-19", "written_by": "independent", "quote": "The similarity score was 32.09 percent. We got to know that the accused lived in Daryaganj, where teams were already working to trace the Scooty used in the crime" }, { "kind": "news report", "citation": "The New Indian Express (2025). Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held. The New Indian Express, 20 March 2025.", "title": "Israeli facial recognition tech helps Delhi police crack Rs 80 lakh robbery case, two held", "url": "https://www.newindianexpress.com/cities/delhi/2025/Mar/20/israeli-facial-recognition-tech-helps-delhi-police-crack-rs-80-lakh-robbery-case-two-held", "date": "2025-03-20", "written_by": "independent", "quote": "Facial recognition technology identified one suspect as Mohammad Ali, who had been arrested previously in a similar case, Deputy Commissioner of Police (North) Raja Banthia said." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Facial recognition on CCTV named a Chandni Chowk robber; two arrested within about a day and Rs 79.5 lakh of the Rs 80 lakh recovered.", "account": "On the evening of 17 March 2025, cash courier Ajmal Bhai Ganesh, 49, of R K Enterprises was robbed at gunpoint of Rs 80 lakh. It was near his Fatehpuri home, Chandni Chowk, Delhi. Delhi Police's North district analyzed some 500 closed-circuit television (CCTV) cameras' footage. Israeli facial recognition software matched a frame of a man who had followed the victim to a record at Kotwali police station. That gave Mohammad Ali, 21, of Daryaganj. Ali was arrested early on 19 March (the Times of India says Tuesday) and named Samir, 19, arrested in Daryaganj. A raid on Samir's home found Rs 79.5 lakh and a semi-automatic pistol, which police called the entire amount." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Israeli facial recognition software used by Delhi Police (not named in the reports)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Delhi Police matched a CCTV frame to a prior arrest record with Israeli facial recognition software, arrested two men within about a day of a Rs 80 lakh armed robbery in Chandni Chowk and recovered Rs 79.5 lakh", "headline": "Delhi Police facial recognition leads to Rs 79.5 lakh recovery" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "583679466697009ff9b744c37371ceccd1d79ea0ed2ace31dcb6a8f928a344e7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the evening of 17 March 2025, cash courier Ajmal Bhai Ganesh, 49, of R K Enterprises was robbed at gunpoint of Rs 80 lakh. It was near his Fatehpuri home, Chandni Chowk, Delhi. Delhi Police's North district analyzed some 500 closed-circuit television (CCTV) cameras' footage. Israeli facial recognition software matched a frame of a man who had followed the victim to a record at Kotwali police station. That gave Mohammad Ali, 21, of Daryaganj. Ali was arrested early on 19 March (the Times of India says Tuesday) and named Samir, 19, arrested in Daryaganj. A raid on Samir's home found Rs 79.5 lakh and a semi-automatic pistol, which police called the entire amount.", "replication": { "produced_by": [ "Dense CCTV coverage (about 500 cameras across five areas) from which a usable frame of the suspect's face could be taken", "A police facial recognition database that already held the suspect's photograph from a prior arrest at Kotwali police station" ], "must_hold": [ "A low-similarity match (32.09 percent) is only a lead and must be confirmed by conventional investigation before arrest", "The suspect must already be in the database; a first-time offender would not have been matched" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0127", "title": "Physicians treated Joseph Coates’s POEMS syndrome with three drugs that an early Every Cure algorithm also ranked highly, allowing a later stem cell transplant and remission", "summary": "Mr. Joseph Coates received three drugs (i) that a consulting physician had considered and (ii) that Every Cure’s early drug-repurposing system had scored highly.", "date_observed": "2025-03-20", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In January 2024, Joseph Coates, 37, of Renton, Washington, was critically ill with POEMS syndrome. His heart and kidneys were failing, and he was too sick for a stem cell transplant. His partner, Tara Theobald, asked David Fajgenbaum of the University of Pennsylvania and Every Cure for help. Fajgenbaum considered three drugs used for multiple myeloma, a related disease. He later explained that an early Every Cure algorithm also scored those drugs highly for POEMS. He recommended carfilzomib, cyclophosphamide, and dexamethasone to Coates’s treating hematologist and oncologist, Wayne Gao, who agreed to administer them. Coates later reported that he responded within one or two weeks and left intensive care three weeks later. He recovered enough to receive a stem cell transplant and reported full remission five months after that transplant. The New York Times reported improvement within a week and transplant eligibility about four months later. A brief vignette in The Lancet Haematology describes a matching unnamed patient and labels the result unpublished data. The sources support a contribution from AI alongside the physicians’ judgment, but they do not establish the exact model release or isolate its effect on recovery.", "category": "benefit created", "unexpected": false, "purpose": "Every Cure uses AI to rank existing drugs as candidates for other diseases. Its early algorithms helped Fajgenbaum assess drugs that he had considered for Coates’s POEMS syndrome. The New Yorker notes that Every Cure does not usually make recommendations for individual patients.", "system": "Every Cure’s early drug-repurposing system", "model_version": null, "developer": "Every Cure (co-founded by David Fajgenbaum, University of Pennsylvania)", "deployer": "David Fajgenbaum (Every Cure / University of Pennsylvania); regimen administered by Wayne Gao, Coates's treating hematologist and oncologist", "location": "Renton, United States", "domain": "Healthcare - rare disease / drug repurposing", "segment": "Individual off-label treatment of a terminal POEMS syndrome patient", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-03-21-aa9f" }, "ratings": [ { "group": "personal", "depth": 5, "reason": "Coates was critically ill, too sick for a transplant, and facing hospice care. He reported that he began responding to the drug regimen within one or two weeks, later received a stem cell transplant, and reached full remission five months after that transplant. The reported benefit was life-preserving. The available evidence does not isolate AI’s contribution from clinical judgment, the drugs, supportive care, or the transplant." } ], "ai_role": { "status": "assessed", "statement": "Fajgenbaum said that he had considered three drugs used for multiple myeloma and that Every Cure’s AI algorithm also scored them highly for POEMS syndrome. In an earlier AAMC interview, he described reviewing the scores and recommending the drugs to Coates’s treating physician. Wayne Gao weighed the risks and administered the treatment. The AI therefore supported the physicians’ assessment of candidate drugs. The sources do not show that it independently devised the regimen or that the benefit would have been impossible without it. The Lancet Haematology commentary contains a brief vignette of a matching unnamed POEMS patient, explicitly labeled unpublished data. No detailed clinical case report, underlying medical records, or case-specific model output was located. The commentary names KGML-xDTD as one of several algorithms in Every Cure’s platform, but it does not establish which algorithm or release was used for Coates." }, "evidence": [ { "kind": "news report", "citation": "Morgan, K. (2025). Doctors Told Him He Was Going to Die. Then A.I. Saved His Life. The New York Times, March 20, 2025.", "title": "Doctors Told Him He Was Going to Die. Then A.I. Saved His Life.", "url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "date": "2025-03-20", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Khullar, D. (2025). Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have? The New Yorker, Open Questions, 15 July 2025.", "title": "Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have?", "url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "date": "2025-07-15", "written_by": "independent", "quote": "used the organization's A.I. platform to recommend a combination of drugs normally used to treat a blood cancer: a steroid called dexamethasone; a chemotherapy called cyclophosphamide; an immunotherapy called carfilzomib." }, { "kind": "press release", "citation": "Every Cure. Repurposing Portfolio, “Carfilzomib-cyclophosphamide-dexamethasone for POEMS syndrome.”", "title": "Repurposing Portfolio", "url": "https://everycure.org/portfolio/", "date": null, "written_by": "makers", "quote": "carfilzomib-cyclophosphamide-dexamethasone was administered to a POEMS patient in January 2024 who was getting ready to go onto hospice care, which ultimately saved his life" }, { "kind": "report", "citation": "Every Cure. 2025 Annual Report, “Joseph,” p. 15.", "title": "Every Cure 2025 Annual Report", "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf", "date": null, "written_by": "makers", "quote": "In January 2024, Joseph was on life support with POEMS syndrome, a rare blood disorder that caused his vital organs to shut down." }, { "kind": "report", "citation": "Advanced Research Projects Agency for Health. Fiscal Year 2027 Congressional Justification for Appropriations Committees, 17, “Repurposing for rare disease.”", "title": "Fiscal Year 2027 Congressional Justification for Appropriations Committees", "url": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "date": null, "written_by": "unknown", "quote": null }, { "kind": "other", "citation": "Penn Medicine. “Finding Hidden Cures | Dr. David Fajgenbaum & Joseph’s Story.” Video, 14:19, November 17, 2025, 8:26–9:04 and 9:52–11:25. Publisher-supplied English captions.", "title": "Finding Hidden Cures | Dr. David Fajgenbaum & Joseph's Story", "url": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "date": "2025-11-17", "written_by": "makers", "quote": "this AI algorithm that we use also scored those three drugs highly." }, { "kind": "news report", "citation": "Stacy Weiner. “This doctor saved his own life. Now he’s on a mission to save thousands more.” AAMCNews, September 24, 2024, response to “Has Every Cure had any successes yet?”", "title": "This doctor saved his own life. Now he’s on a mission to save thousands more", "url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "date": "2024-09-24", "written_by": "deployer", "quote": null }, { "kind": "other", "citation": "David C. Fajgenbaum, Sally Nijim, Grant Mitchell, Matej Macak, Chris Bizon, Alexander Tropsha, and David Koslicki. “Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines.” The Lancet Haematology 12, no. 2 (February 2025): e94–e96. Commentary, paragraph beginning “We have already begun to pilot these processes.” https://doi.org/10.1016/S2352-3026(24)00278-3.", "title": "Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines", "url": "https://doi.org/10.1016/S2352-3026(24)00278-3", "date": null, "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Liz Tung. “UPenn professor receives $48.3 million to find new treatments in old drugs.” WHYY, March 10, 2024, opening POEMS account and “Harnessing the power of AI.”", "title": "UPenn professor receives $48.3 million to find new treatments in old drugs", "url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "date": "2024-03-10", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Ann-Marie Roche. “Elsevier and Every Cure: treating rare diseases with generic drugs — at scale.” Elsevier Connect, January 30, 2024.", "title": "Elsevier and Every Cure: treating rare diseases with generic drugs — at scale", "url": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "date": "2024-01-30", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Fajgenbaum recognized similarities between POEMS syndrome and multiple myeloma and reviewed high AI scores for drugs that were used for myeloma.", "Fajgenbaum answered the family’s urgent appeal and discussed treatment with Wayne Gao, who assessed the risks and administered the three drugs." ], "must_hold": [ "Clinicians must assess the proposed drugs, the patient’s condition, and the risks of treatment. A high model score alone does not establish that a drug is suitable.", "The patient must respond sufficiently to receive any further treatment that is needed. Coates later underwent a stem cell transplant before he reported full remission." ], "echoes": [] }, "paired_incident": null, "headline": "A man with a rare blood disorder became well enough for a transplant", "metric": "he responded within one or two weeks", "comparator": { "against": "the treatments his doctors had tried, with hospice as the remaining option", "before": "Coates was now entering a terminal stage: his heart and kidneys were failing, and fluid had to be drained from his belly several times a week. He was too sick to undergo a stem-cell transplant, which could save his life.", "after": "within days Coates started to improve. A few months later, he'd recovered sufficiently to receive a stem-cell transplant. He is now in remission.", "basis": "measured", "quote": "But, with little to lose, they gave it a try—and within days Coates started to improve. A few months later, he'd recovered sufficiently to receive a stem-cell transplant. He is now in remission.", "url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have" }, "later": { "status": "persisted", "date": null, "note": "Every Cure’s 2025 annual report states that Joseph remains in remission. Its patient story is on page 15. The New Yorker also reported remission in July 2025. In Penn Medicine’s documentary, published on November 17, 2025, Coates says that full remission followed five months after his transplant. The annual report’s exact publication day is not established here.", "quote": "Within a week, Joseph began improving. Four months later, he was healthy enough to receive a stem cell transplant. Today, he remains in remission — and makes the most of what he and Dr. Fajgenbaum call \"overtime.\"", "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-21-aa9f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have; https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf; https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://everycure.org/privacy-policy/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated the NYT original and its licensed Spanish edition as one reporting origin. Retained the New Yorker for its separate interview and named regimen, Every Cure's portfolio for the algorithm and treatment date, and its annual report for follow-up. Corrected the annual-report locator to printed page 15. Removed the redundant TED retelling and unsupported precision in the annual-report follow-up date.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Reworded the headline to identify the AI contribution as proposing the drug regimen. The account retains the subsequent improvement, stem cell transplant, and remission.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Described the intermediary by his role in the subtitle while retaining his full name and affiliation in the complete record.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original English New York Times article through its archived copy, including the treating physician's interview and embedded research links. Named Wayne Gao as the treating physician. Resolved the English-text access limitation and recorded that the linked medical paper concerns a different patient. The archive remains an access copy of the existing source.", "source": "https://archive.ph/5xNut", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added original patient and physician interviews, an early WHYY account, and the investigators’ Lancet Haematology commentary. Clarified that physicians considered and selected drugs that AI also scored highly. Distinguished the initial response from remission after transplantation, preserved uncertainty about the exact model, and recorded clinical precedents involving other patients. Added Penn Medicine beside the NYT source on the homepage.", "source": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced the later platform name with a descriptive name for the early Every Cure system. Added contemporary evidence of multiple algorithms and recorded that the exact model, provider, and release for Coates’s scores remain unreported.", "source": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' report, the makers' news report, the makers' press release, two other sources from the makers, the deployer's news report and one report with authorship relationship unassessed. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0127", "catalog_version": "1.0.0", "source_fingerprint": "fe0be1b2a61438f2745378b83c663e369f6a01d69068c3e40452180265ca4413", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Every Cure (co-founded by David Fajgenbaum, University of Pennsylvania)", "deployer": "David Fajgenbaum (Every Cure / University of Pennsylvania); regimen administered by Wayne Gao, Coates's treating hematologist and oncologist" } }, "provenance": { "kind": "legacy_record", "basis": "Updated the fields affected by the original English article review.", "record_fields": [ "developer", "deployer" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Fajgenbaum said that he had considered three drugs used for multiple myeloma and that Every Cure’s AI algorithm also scored them highly for POEMS syndrome. In an earlier AAMC interview, he described reviewing the scores and recommending the drugs to Coates’s treating physician. Wayne Gao weighed the risks and administered the treatment. The AI therefore supported the physicians’ assessment of candidate drugs. The sources do not show that it independently devised the regimen or that the benefit would have been impossible without it. The Lancet Haematology commentary contains a brief vignette of a matching unnamed POEMS patient, explicitly labeled unpublished data. No detailed clinical case report, underlying medical records, or case-specific model output was located. The commentary names KGML-xDTD as one of several algorithms in Every Cure’s platform, but it does not establish which algorithm or release was used for Coates." } } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A consulting physician considered three myeloma drugs and reviewed the high scores that Every Cure’s algorithm gave them for POEMS syndrome. The treating physician assessed the risks and administered them. The available accounts do not isolate the AI’s contribution to recovery.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Fajgenbaum said that he had considered three drugs used for multiple myeloma and that Every Cure’s AI algorithm also scored them highly for POEMS syndrome. In an earlier AAMC interview, he described reviewing the scores and recommending the drugs to Coates’s treating physician. Wayne Gao weighed the risks and administered the treatment. The AI therefore supported the physicians’ assessment of candidate drugs. The sources do not show that it independently devised the regimen or that the benefit would have been impossible without it. The Lancet Haematology commentary contains a brief vignette of a matching unnamed POEMS patient, explicitly labeled unpublished data. No detailed clinical case report, underlying medical records, or case-specific model output was located. The commentary names KGML-xDTD as one of several algorithms in Every Cure’s platform, but it does not establish which algorithm or release was used for Coates." } } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. 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He reported that he began responding to the drug regimen within one or two weeks, later received a stem cell transplant, and reached full remission five months after that transplant. The reported benefit was life-preserving. The available evidence does not isolate AI’s contribution from clinical judgment, the drugs, supportive care, or the transplant." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Original interviews and institutional accounts support the reported treatment and recovery. The investigators’ commentary contains a brief vignette labeled unpublished data. Elsevier’s interview adds technical context. No detailed clinical case report or independent evaluation of AI’s contribution was located.", "interpretation": "The display rule remains unchanged. Originality and independence are assessed by claim in the source lineage. Several accounts share Fajgenbaum’s testimony. Neither the institutional documentary nor the investigators’ commentary establishes independent clinical confirmation, and the separate clinical precedents do not contribute to this case’s confidence.", "system_identity_review": "Additional sources clarify technical identity or chronology. They do not establish the AI contribution independently of the original investigators or witnesses." } }, "provenance": { "kind": "source_review", "basis": "Recomputed the existing display rule after adding the reviewed sources. Confidence remains medium; contextual evidence involving other patients is excluded from the calculation.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Coates was critically ill, too sick for a transplant, and facing hospice care. He reported that he began responding to the drug regimen within one or two weeks, later received a stem cell transplant, and reached full remission five months after that transplant. The reported benefit was life-preserving. The available evidence does not isolate AI’s contribution from clinical judgment, the drugs, supportive care, or the transplant." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Coates was critically ill and too sick for a transplant. He reported that he responded to the drugs within one or two weeks, later received a transplant, and reached remission five months afterward. The benefit was life-preserving, with the contribution from AI inseparable from the rest of his care.", "editor_note": "" } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Coates was critically ill, too sick for a transplant, and facing hospice care. He reported that he began responding to the drug regimen within one or two weeks, later received a stem cell transplant, and reached full remission five months after that transplant. The reported benefit was life-preserving. The available evidence does not isolate AI’s contribution from clinical judgment, the drugs, supportive care, or the transplant." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "he responded within one or two weeks", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-03-21-aa9f" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "note": "Every Cure’s 2025 annual report states that Joseph remains in remission. Its patient story is on page 15. The New Yorker also reported remission in July 2025. In Penn Medicine’s documentary, published on November 17, 2025, Coates says that full remission followed five months after his transplant. The annual report’s exact publication day is not established here.", "quote": "Within a week, Joseph began improving. Four months later, he was healthy enough to receive a stem cell transplant. Today, he remains in remission — and makes the most of what he and Dr. Fajgenbaum call \"overtime.\"", "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf" } } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Every Cure’s 2025 annual report states that Coates remains in remission. In Penn Medicine’s November 2025 documentary, he says that full remission followed five months after his transplant.", "editor_note": "" } }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0127" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In January 2024, Joseph Coates, 37, of Renton, Washington, was critically ill with POEMS syndrome. His heart and kidneys were failing, and he was too sick for a stem cell transplant. His partner, Tara Theobald, asked David Fajgenbaum of the University of Pennsylvania and Every Cure for help. Fajgenbaum considered three drugs used for multiple myeloma, a related disease. He later explained that an early Every Cure algorithm also scored those drugs highly for POEMS. He recommended carfilzomib, cyclophosphamide, and dexamethasone to Coates’s treating hematologist and oncologist, Wayne Gao, who agreed to administer them. Coates later reported that he responded within one or two weeks and left intensive care three weeks later. He recovered enough to receive a stem cell transplant and reported full remission five months after that transplant. The New York Times reported improvement within a week and transplant eligibility about four months later. A brief vignette in The Lancet Haematology describes a matching unnamed patient and labels the result unpublished data. The sources support a contribution from AI alongside the physicians’ judgment, but they do not establish the exact model release or isolate its effect on recovery.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Coates reported that he responded to treatment within one or two weeks and later became well enough for a stem cell transplant.", "editor_note": "" } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "Coates was critically ill, too sick for a transplant, and facing hospice care. He reported that he began responding to the drug regimen within one or two weeks, later received a stem cell transplant, and reached full remission five months after that transplant. The reported benefit was life-preserving. The available evidence does not isolate AI’s contribution from clinical judgment, the drugs, supportive care, or the transplant." } ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Every Cure uses AI to rank existing drugs as candidates for other diseases. Its early algorithms helped Fajgenbaum assess drugs that he had considered for Coates’s POEMS syndrome. The New Yorker notes that Every Cure does not usually make recommendations for individual patients." } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Renton, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Every Cure uses AI to rank existing drugs as candidates for other diseases. Its early algorithms helped Fajgenbaum assess drugs that he had considered for Coates’s POEMS syndrome. The New Yorker notes that Every Cure does not usually make recommendations for individual patients." } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "purpose" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Every Cure ranks existing drugs for potential use against other diseases. Its early system helped a physician assess drugs that he had considered for Coates.", "editor_note": "" } }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-03-20", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-21-aa9f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have; https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf; https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://everycure.org/privacy-policy/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated the NYT original and its licensed Spanish edition as one reporting origin. Retained the New Yorker for its separate interview and named regimen, Every Cure's portfolio for the algorithm and treatment date, and its annual report for follow-up. Corrected the annual-report locator to printed page 15. Removed the redundant TED retelling and unsupported precision in the annual-report follow-up date.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Reworded the headline to identify the AI contribution as proposing the drug regimen. The account retains the subsequent improvement, stem cell transplant, and remission.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Described the intermediary by his role in the subtitle while retaining his full name and affiliation in the complete record.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original English New York Times article through its archived copy, including the treating physician's interview and embedded research links. Named Wayne Gao as the treating physician. Resolved the English-text access limitation and recorded that the linked medical paper concerns a different patient. The archive remains an access copy of the existing source.", "source": "https://archive.ph/5xNut", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added original patient and physician interviews, an early WHYY account, and the investigators’ Lancet Haematology commentary. Clarified that physicians considered and selected drugs that AI also scored highly. Distinguished the initial response from remission after transplantation, preserved uncertainty about the exact model, and recorded clinical precedents involving other patients. Added Penn Medicine beside the NYT source on the homepage.", "source": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced the later platform name with a descriptive name for the early Every Cure system. Added contemporary evidence of multiple algorithms and recorded that the exact model, provider, and release for Coates’s scores remain unreported.", "source": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "date_observed", "revisions", "date_basis", "date_precision" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Fajgenbaum recognized similarities between POEMS syndrome and multiple myeloma and reviewed high AI scores for drugs that were used for myeloma.", "Fajgenbaum answered the family’s urgent appeal and discussed treatment with Wayne Gao, who assessed the risks and administered the three drugs." ], "must_hold": [ "Clinicians must assess the proposed drugs, the patient’s condition, and the risks of treatment. A high model score alone does not establish that a drug is suitable.", "The patient must respond sufficiently to receive any further treatment that is needed. Coates later underwent a stem cell transplant before he reported full remission." ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Clinicians need to assess the patient’s condition, the drugs, and their risks. A high AI score does not establish suitability. In this instance, recovery also depended on a response sufficient to permit a later transplant.", "editor_note": "" } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-03-21-aa9f", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have; https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf; https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://everycure.org/privacy-policy/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated the NYT original and its licensed Spanish edition as one reporting origin. Retained the New Yorker for its separate interview and named regimen, Every Cure's portfolio for the algorithm and treatment date, and its annual report for follow-up. Corrected the annual-report locator to printed page 15. Removed the redundant TED retelling and unsupported precision in the annual-report follow-up date.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Reworded the headline to identify the AI contribution as proposing the drug regimen. The account retains the subsequent improvement, stem cell transplant, and remission.", "source": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Described the intermediary by his role in the subtitle while retaining his full name and affiliation in the complete record.", "source": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original English New York Times article through its archived copy, including the treating physician's interview and embedded research links. Named Wayne Gao as the treating physician. Resolved the English-text access limitation and recorded that the linked medical paper concerns a different patient. The archive remains an access copy of the existing source.", "source": "https://archive.ph/5xNut", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added original patient and physician interviews, an early WHYY account, and the investigators’ Lancet Haematology commentary. Clarified that physicians considered and selected drugs that AI also scored highly. Distinguished the initial response from remission after transplantation, preserved uncertainty about the exact model, and recorded clinical precedents involving other patients. Added Penn Medicine beside the NYT source on the homepage.", "source": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced the later platform name with a descriptive name for the early Every Cure system. Added contemporary evidence of multiple algorithms and recorded that the exact model, provider, and release for Coates’s scores remain unreported.", "source": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - rare disease / drug repurposing", "segment": "Individual off-label treatment of a terminal POEMS syndrome patient" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "versions_and_access": [ { "source_url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "access_url": "https://archive.ph/5xNut", "accessed_on": "2026-10-24", "capture_timestamp": "2026-09-24T11:14:37Z", "publication_date": "2025-03-20", "status": "Complete original English article and embedded links inspected in the archived copy. Includes interviews with Coates, Fajgenbaum, and treating physician Wayne Gao. The capture date does not replace the original publication date." }, { "source_url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "access_url": "https://www.infobae.com/america/the-new-york-times/2025/03/24/los-medicos-le-dijeron-que-iba-a-morir-pero-la-inteligencia-artificial-le-salvo-la-vida/", "accessed_on": "2026-10-24", "status": "Licensed full-text Spanish translation inspected as an alternate access copy of the same article." }, { "source_url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "status": "Publisher page inspected through its embedded full article text." }, { "source_url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf", "locator": "Printed page 15, also the fifteenth page in the downloaded file.", "publication_date": "Exact day not established." }, { "source_url": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "status": "Original source inspected.", "locator": "Printed p. 17, Repurposing for rare disease.", "reviewed_on": "2026-10-24" }, { "source_url": "https://everycure.org/portfolio/", "status": "POEMS entry and its link to the original NYT story are accessible and were reread.", "locator": "Carfilzomib-cyclophosphamide-dexamethasone for POEMS syndrome.", "reviewed_on": "2026-10-24" }, { "source_url": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "publication_date": "2025-11-17", "publication_precision": "day", "accessed_on": "2026-10-24", "status": "Complete documentary transcript inspected using the publisher-supplied English en-US captions. Official Penn Medicine video, 14:19. The manual caption track is distinct from the automatically generated captions.", "locator": "8:26–9:04 and 9:52–11:25." }, { "source_url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "publication_date": "2024-09-24", "publication_precision": "day", "accessed_on": "2026-10-24", "status": "Original interview inspected on the AAMC publisher page. November 11, 2024 is the advertised conference appearance, not this article’s publication date.", "locator": "Response to “Has Every Cure had any successes yet?”" }, { "source_url": "https://doi.org/10.1016/S2352-3026(24)00278-3", "access_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12090018/", "publication_date": "2025-02", "publication_precision": "month", "accessed_on": "2026-10-24", "status": "Complete author manuscript inspected in PMC, including the vignette, platform description, references, and disclosures. Final journal pagination e94–e96. The PMC availability date is August 1, 2025 and is not the journal publication date. The evidence date is null because an exact publication day was not verified.", "locator": "Paragraph beginning “We have already begun to pilot these processes.”" }, { "source_url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "publication_date": "2024-03-10", "publication_precision": "day", "accessed_on": "2026-10-24", "status": "Original publisher article inspected. The embedded audio is another format of the same reporting, not a separate source.", "locator": "Opening POEMS account and “Harnessing the power of AI.”" }, { "source_url": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "source_ref": "AIBD-0127-source-0010", "publication_date": "2024-01-30", "accessed_on": "2026-10-24", "status": "Original publisher text inspected.", "locator": "Opening description of the algorithms and responses about Elsevier’s contribution." } ], "limitations": [ "No detailed clinical case report, underlying medical records, drug doses, or case-specific model output for Coates was located. The Lancet commentary contains a brief unnamed vignette and explicitly labels the result unpublished data.", "The sources do not isolate AI’s contribution from the physicians’ judgment, the drug regimen, supportive care, and later transplantation. Coates places full remission five months after his transplant.", "MATRIX names the platform, but the precise algorithm and release used in January 2024 remain unknown. KGML-xDTD is one of several algorithms described later, not an established identification of the model used for Coates.", "The unnamed patients in WHYY, the Lancet commentary, and ARPA-H are matched to Coates by context. These identifications remain inferences. ARPA-H’s relative date differs from the January 2024 chronology.", "The NYT and Every Cure annual report say that improvement began within a week and that transplant eligibility followed about four months later. Coates recalls a response within one or two weeks in the documentary. The Lancet vignette gives nine months of remission at submission without a submission date or definition that reconciles it with Coates’s post-transplant timeline.", "The medical commentary, institutional film, and additional interviews share investigators or witnesses. Their publication in different outlets does not establish independent clinical confirmation." ] } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Patient and physician interviews describe treatment and recovery. Detailed clinical records, drug doses, and the patient’s AI scores are unavailable. The accounts differ on the timing of treatment and recovery.", "editor_note": "The unnamed patients in the Lancet commentary, WHYY, and ARPA-H are matched to Coates by their disease, treatment, and circumstances (references 5, 8–9). ARPA-H gives a relative date that differs from Every Cure’s January 2024 chronology. The Lancet commentary labels its vignette unpublished data." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Morgan, K. (2025). Doctors Told Him He Was Going to Die. Then A.I. Saved His Life. The New York Times, March 20, 2025.", "title": "Doctors Told Him He Was Going to Die. Then A.I. Saved His Life.", "url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "date": "2025-03-20", "written_by": "independent" }, { "kind": "news report", "citation": "Khullar, D. (2025). Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have? The New Yorker, Open Questions, 15 July 2025.", "title": "Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have?", "url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "date": "2025-07-15", "written_by": "independent", "quote": "used the organization's A.I. platform to recommend a combination of drugs normally used to treat a blood cancer: a steroid called dexamethasone; a chemotherapy called cyclophosphamide; an immunotherapy called carfilzomib." }, { "kind": "press release", "citation": "Every Cure. Repurposing Portfolio, “Carfilzomib-cyclophosphamide-dexamethasone for POEMS syndrome.”", "title": "Repurposing Portfolio", "url": "https://everycure.org/portfolio/", "written_by": "makers", "quote": "carfilzomib-cyclophosphamide-dexamethasone was administered to a POEMS patient in January 2024 who was getting ready to go onto hospice care, which ultimately saved his life" }, { "kind": "report", "citation": "Every Cure. 2025 Annual Report, “Joseph,” p. 15.", "title": "Every Cure 2025 Annual Report", "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf", "written_by": "makers", "quote": "In January 2024, Joseph was on life support with POEMS syndrome, a rare blood disorder that caused his vital organs to shut down." }, { "kind": "report", "citation": "Advanced Research Projects Agency for Health. Fiscal Year 2027 Congressional Justification for Appropriations Committees, 17, “Repurposing for rare disease.”", "title": "Fiscal Year 2027 Congressional Justification for Appropriations Committees", "url": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "written_by": "unknown" }, { "kind": "other", "citation": "Penn Medicine. “Finding Hidden Cures | Dr. David Fajgenbaum & Joseph’s Story.” Video, 14:19, November 17, 2025, 8:26–9:04 and 9:52–11:25. Publisher-supplied English captions.", "title": "Finding Hidden Cures | Dr. David Fajgenbaum & Joseph's Story", "url": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "date": "2025-11-17", "written_by": "makers", "quote": "this AI algorithm that we use also scored those three drugs highly." }, { "kind": "news report", "citation": "Stacy Weiner. “This doctor saved his own life. Now he’s on a mission to save thousands more.” AAMCNews, September 24, 2024, response to “Has Every Cure had any successes yet?”", "title": "This doctor saved his own life. Now he’s on a mission to save thousands more", "url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "date": "2024-09-24", "written_by": "deployer" }, { "kind": "other", "citation": "David C. Fajgenbaum, Sally Nijim, Grant Mitchell, Matej Macak, Chris Bizon, Alexander Tropsha, and David Koslicki. “Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines.” The Lancet Haematology 12, no. 2 (February 2025): e94–e96. Commentary, paragraph beginning “We have already begun to pilot these processes.” https://doi.org/10.1016/S2352-3026(24)00278-3.", "title": "Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines", "url": "https://doi.org/10.1016/S2352-3026(24)00278-3", "written_by": "makers" }, { "kind": "news report", "citation": "Liz Tung. “UPenn professor receives $48.3 million to find new treatments in old drugs.” WHYY, March 10, 2024, opening POEMS account and “Harnessing the power of AI.”", "title": "UPenn professor receives $48.3 million to find new treatments in old drugs", "url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "date": "2024-03-10", "written_by": "independent" }, { "kind": "news report", "citation": "Ann-Marie Roche. “Elsevier and Every Cure: treating rare diseases with generic drugs — at scale.” Elsevier Connect, January 30, 2024.", "title": "Elsevier and Every Cure: treating rare diseases with generic drugs — at scale", "url": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "date": "2024-01-30", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "role": "Retained evidence sources in reviewed order" }, "provenance": { "kind": "source_review", "basis": "Preserved existing source IDs and appended original sources that add technical detail or earlier testimony.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Morgan, K. (2025). Doctors Told Him He Was Going to Die. Then A.I. Saved His Life. The New York Times, March 20, 2025.", "title": "Doctors Told Him He Was Going to Die. Then A.I. Saved His Life.", "url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "date": "2025-03-20", "written_by": "independent" }, { "kind": "news report", "citation": "Khullar, D. (2025). Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have? The New Yorker, Open Questions, 15 July 2025.", "title": "Can A.I. Find Cures for Untreatable Diseases—Using Drugs We Already Have?", "url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "date": "2025-07-15", "written_by": "independent", "quote": "used the organization's A.I. platform to recommend a combination of drugs normally used to treat a blood cancer: a steroid called dexamethasone; a chemotherapy called cyclophosphamide; an immunotherapy called carfilzomib." }, { "kind": "press release", "citation": "Every Cure. Repurposing Portfolio, “Carfilzomib-cyclophosphamide-dexamethasone for POEMS syndrome.”", "title": "Repurposing Portfolio", "url": "https://everycure.org/portfolio/", "written_by": "makers", "quote": "carfilzomib-cyclophosphamide-dexamethasone was administered to a POEMS patient in January 2024 who was getting ready to go onto hospice care, which ultimately saved his life" }, { "kind": "report", "citation": "Every Cure. 2025 Annual Report, “Joseph,” p. 15.", "title": "Every Cure 2025 Annual Report", "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf", "written_by": "makers", "quote": "In January 2024, Joseph was on life support with POEMS syndrome, a rare blood disorder that caused his vital organs to shut down." }, { "kind": "report", "citation": "Advanced Research Projects Agency for Health. Fiscal Year 2027 Congressional Justification for Appropriations Committees, 17, “Repurposing for rare disease.”", "title": "Fiscal Year 2027 Congressional Justification for Appropriations Committees", "url": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "written_by": "unknown" }, { "kind": "other", "citation": "Penn Medicine. “Finding Hidden Cures | Dr. David Fajgenbaum & Joseph’s Story.” Video, 14:19, November 17, 2025, 8:26–9:04 and 9:52–11:25. Publisher-supplied English captions.", "title": "Finding Hidden Cures | Dr. David Fajgenbaum & Joseph's Story", "url": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "date": "2025-11-17", "written_by": "makers", "quote": "this AI algorithm that we use also scored those three drugs highly." }, { "kind": "news report", "citation": "Stacy Weiner. “This doctor saved his own life. Now he’s on a mission to save thousands more.” AAMCNews, September 24, 2024, response to “Has Every Cure had any successes yet?”", "title": "This doctor saved his own life. Now he’s on a mission to save thousands more", "url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "date": "2024-09-24", "written_by": "deployer" }, { "kind": "other", "citation": "David C. Fajgenbaum, Sally Nijim, Grant Mitchell, Matej Macak, Chris Bizon, Alexander Tropsha, and David Koslicki. “Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines.” The Lancet Haematology 12, no. 2 (February 2025): e94–e96. Commentary, paragraph beginning “We have already begun to pilot these processes.” https://doi.org/10.1016/S2352-3026(24)00278-3.", "title": "Pioneering a new field of computational pharmacophenomics to unlock the life-saving potential of existing medicines", "url": "https://doi.org/10.1016/S2352-3026(24)00278-3", "written_by": "makers" }, { "kind": "news report", "citation": "Liz Tung. “UPenn professor receives $48.3 million to find new treatments in old drugs.” WHYY, March 10, 2024, opening POEMS account and “Harnessing the power of AI.”", "title": "UPenn professor receives $48.3 million to find new treatments in old drugs", "url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "date": "2024-03-10", "written_by": "independent" }, { "kind": "news report", "citation": "Ann-Marie Roche. “Elsevier and Every Cure: treating rare diseases with generic drugs — at scale.” Elsevier Connect, January 30, 2024.", "title": "Elsevier and Every Cure: treating rare diseases with generic drugs — at scale", "url": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "date": "2024-01-30", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "lead_source_ref": "AIBD-0127-source-0001", "retained_source_order": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "origins": [ { "url": "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "contribution": "Original interviews with Coates, Fajgenbaum, and treating physician Wayne Gao support the reported condition, treatment decision, response within a week, later transplant, and remission.", "locator": "Opening patient narrative and final section, including the interview with treating physician Wayne Gao. Original English article read through the archived copy.", "relationship": "Original journalism with firsthand patient, treating physician, and researcher testimony. No medical records or clinical case report for Coates are supplied.", "source_refs": [ "AIBD-0127-source-0001" ], "display_name": "The New York Times", "access_url": "https://archive.ph/5xNut" }, { "url": "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "contribution": "Separate interview with Fajgenbaum identifies the three drugs and clinical decision.", "locator": "Paragraph beginning “Last year, Fajgenbaum received an e-mail”.", "relationship": "Independent reporter, same underlying case and researcher; not a new medical assessment.", "source_refs": [ "AIBD-0127-source-0002" ] }, { "url": "https://everycure.org/portfolio/", "contribution": "Developer specifies January 2024 and high algorithm scores alongside biological similarity.", "locator": "Carfilzomib-cyclophosphamide-dexamethasone for POEMS syndrome.", "relationship": "Developer account; its only case link returns to the NYT article.", "source_refs": [ "AIBD-0127-source-0003" ] }, { "url": "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf", "contribution": "Later institutional account of remission.", "locator": "Printed p. 15, Joseph.", "relationship": "Every Cure account; patient testimony and developer report, not an independent clinical follow-up.", "source_refs": [ "AIBD-0127-source-0004" ] }, { "url": "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "contribution": "Names MATRIX and attributes a matching POEMS treatment to that toolkit.", "locator": "Printed p. 17, Repurposing for rare disease.", "relationship": "Funding agency’s retrospective account. The patient is unnamed and the relative date conflicts with the developer’s January 2024 chronology.", "source_refs": [ "AIBD-0127-source-0005" ], "display_name": "ARPA-H" }, { "url": "https://www.youtube.com/watch?v=4FxwoOuPGWs", "contribution": "Original interviews and patient videos explain how human judgment and AI scores contributed, give Coates’s response timeline, and place full remission after transplantation.", "locator": "6:44–8:16, failed prior treatment and hospice discussion; 8:26–9:04, knowledge graph, physician’s candidates, and AI scores; 9:52–10:00, response and transfer from CCU; 10:43–11:25, kidney recovery, transplantation, and later remission.", "relationship": "Produced by Penn Medicine, Fajgenbaum’s institution. Coates, Tara Theobald, and Fajgenbaum give firsthand testimony. Patient videos add contemporaneous testimony, but the film is not an independent clinical evaluation.", "source_refs": [ "AIBD-0127-source-0006" ], "display_name": "Penn Medicine" }, { "url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "contribution": "An interview published in September 2024 names Joseph, dates the appeal to January, and describes reviewing AI scores before recommending three myeloma drugs to his doctor.", "locator": "Response to “Has Every Cure had any successes yet?” and preceding discussion of Every Cure’s platform.", "relationship": "Original interview conducted by Stacy Weiner for AAMCNews. The relevant answer is Fajgenbaum’s firsthand account as the recommending physician and platform cofounder, not independent clinical verification.", "source_refs": [ "AIBD-0127-source-0007" ], "display_name": "AAMC" }, { "url": "https://doi.org/10.1016/S2352-3026(24)00278-3", "access_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12090018/", "contribution": "The investigators describe reviewing platform scores for a refractory POEMS patient facing hospice and report nine months of remission at submission. They also describe the platform and identify KGML-xDTD as one of several algorithms.", "locator": "Paragraph beginning “We have already begun to pilot these processes”; platform description beginning “The Every Cure platform is built to integrate multiple knowledge sources”; reference 10.", "relationship": "Commentary by the platform’s investigators, with a brief clinical vignette explicitly labeled unpublished data. The patient is unnamed, so identification as Coates is inferred from the disease, hospice setting, drug class, and related firsthand accounts. It is not an independent study or a detailed clinical case report.", "source_refs": [ "AIBD-0127-source-0008" ], "display_name": "The Lancet Haematology", "publication_date": "2025-02", "publication_precision": "month" }, { "url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "contribution": "An early original interview reports that a Washington POEMS patient had left intensive care and the hospital after the three-drug recommendation. It also names MATRIX and describes the platform as being in beta in March 2024.", "locator": "Opening six paragraphs and “Harnessing the power of AI,” especially the paragraph beginning “Currently, Every Cure’s matchmaking program is in beta mode.”", "relationship": "Original reporting by Liz Tung. The clinical claims come from Fajgenbaum, and the patient is unnamed. Identification as Coates is inferred from Washington state, POEMS, the timing, the hospice plan, and the myeloma-drug recommendation. This is additional early testimony from the same physician, not independent clinical replication.", "source_refs": [ "AIBD-0127-source-0009" ], "display_name": "WHYY" }, { "url": "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale", "source_refs": [ "AIBD-0127-source-0010" ], "locator": "Opening description of the algorithms and responses about Elsevier’s contribution.", "display_name": "Elsevier", "contribution": "Contemporaneous interview establishes that Every Cure was using several algorithms, including customized Elsevier algorithms.", "relationship": "Technical partner’s interview with Fajgenbaum. It does not identify which algorithm supplied Coates’s scores or corroborate his clinical outcome." } ], "claim_chains": [ { "claim": "Treatment, response, and remission", "path": [ "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "https://archive.ph/5xNut", "https://www.infobae.com/america/the-new-york-times/2025/03/24/los-medicos-le-dijeron-que-iba-a-morir-pero-la-inteligencia-artificial-le-salvo-la-vida/", "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "https://everycure.org/wp-content/uploads/2026/01/EVery.Cure_.2025.Annual.Report.Single.Digital.Pages.pdf#page=15", "https://www.youtube.com/watch?v=4FxwoOuPGWs", "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "https://doi.org/10.1016/S2352-3026(24)00278-3", "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/" ], "finding": "The NYT article, its archived English copy, and the licensed Infobae translation are one reporting origin. The original includes testimony from Coates and Wayne Gao. The New Yorker has its own interview. Penn Medicine adds original patient and partner testimony and earlier patient videos. AAMC and WHYY add earlier interviews with Fajgenbaum. The Lancet commentary gives a brief vignette labeled unpublished data. These sources are original accounts, but their shared witnesses and institutional relationships do not constitute independent clinical replication." }, { "claim": "AI recommendation and January 2024 chronology", "path": [ "https://everycure.org/portfolio/", "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "https://www.youtube.com/watch?v=4FxwoOuPGWs", "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "https://doi.org/10.1016/S2352-3026(24)00278-3" ], "finding": "Fajgenbaum says in the documentary that he had considered the drugs and that AI also scored them highly. His September 2024 AAMC interview describes reviewing the scores before recommending drugs and explicitly dates Joseph’s crisis to January. WHYY’s March 2024 account describes a matching unnamed Washington patient about six weeks after the appeal. These accounts support AI-assisted assessment alongside clinical judgment, not the claim that AI alone invented an untested regimen." }, { "claim": "System identity", "path": [ "https://www.nytimes.com/2025/03/20/well/ai-drug-repurposing.html", "https://everycure.org/portfolio/", "https://www.newyorker.com/culture/open-questions/can-ai-find-cures-for-untreatable-diseases-using-drugs-we-already-have", "https://arpa-h.gov/sites/default/files/2026-04/FY27%20ARPA-H%20CJ_Greenlight_508%20compliant.pdf", "https://www.youtube.com/watch?v=4FxwoOuPGWs", "https://doi.org/10.1016/S2352-3026(24)00278-3", "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "https://www.elsevier.com/en-gb/connect/elsevier-and-every-cure-treating-rare-diseases-with-generic-drugs-at-scale" ], "finding": "Every Cure identifies an early version of its algorithms for the January 2024 treatment. A January 30 interview describes multiple algorithms, including Elsevier contributions, without identifying which produced Coates’s scores. WHYY names MATRIX in March 2024. Neither that platform name nor the later KGML-xDTD documentation establishes the algorithm or release used for Coates." }, { "claim": "Treatment novelty and the separate summer-2024 conference report", "path": [ "https://everycure.org/portfolio/", "https://doi.org/10.1016/j.jaccas.2020.12.027", "https://pmc.ncbi.nlm.nih.gov/articles/PMC8310984/", "https://library.ehaweb.org/eha/2024/eha2024-congress/document?c_id=421524&cm_id=436356&type=document436356" ], "finding": "A 2021 JACC case report describes the same three drugs for a different POEMS patient. EHA abstract PB2758 reports a separate eight-patient Qilu Hospital cohort, with seven responses. Neither source reports AI involvement. The EHA abstract is a plausible match for Every Cure’s uncited conference reference, but that match remains an inference. Both are clinical context, not evidence about Coates or independent verification of his AI-assisted recommendation." } ], "limitations": [ "No detailed clinical case report, underlying medical records, drug doses, or case-specific model output for Coates was located. The Lancet commentary contains a brief unnamed vignette and explicitly labels the result unpublished data.", "The sources do not isolate AI’s contribution from the physicians’ judgment, the drug regimen, supportive care, and later transplantation. Coates places full remission five months after his transplant.", "MATRIX names the platform, but the precise algorithm and release used in January 2024 remain unknown. KGML-xDTD is one of several algorithms described later, not an established identification of the model used for Coates.", "The unnamed patients in WHYY, the Lancet commentary, and ARPA-H are matched to Coates by context. These identifications remain inferences. ARPA-H’s relative date differs from the January 2024 chronology.", "The NYT and Every Cure annual report say that improvement began within a week and that transplant eligibility followed about four months later. Coates recalls a response within one or two weeks in the documentary. The Lancet vignette gives nine months of remission at submission without a submission date or definition that reconciles it with Coates’s post-transplant timeline.", "The medical commentary, institutional film, and additional interviews share investigators or witnesses. Their publication in different outlets does not establish independent clinical confirmation." ], "excluded_or_consolidated_sources": [ { "url": "https://www.infobae.com/america/the-new-york-times/2025/03/24/los-medicos-le-dijeron-que-iba-a-morir-pero-la-inteligencia-artificial-le-salvo-la-vida/", "reason": "Licensed translation of the NYT story, retained as an alternate access copy of the same reporting." }, { "url": "https://www.ted.com/talks/david_fajgenbaum_how_nearly_dying_helped_me_discover_my_own_cure_and_many_more/transcript", "reason": "Developer's TED retelling adds no necessary evidence beyond the portfolio, annual report, and original interviews." }, { "url": "https://archive.ph/5xNut", "reason": "Archived copy of the original English NYT article, captured on September 24, 2026, and inspected on October 24, 2026. The article was published on March 20, 2025. The copy is not a separate source or independent corroboration." } ], "review_scope": "Retained the archived English NYT review and added the complete Penn Medicine documentary and publisher captions, original AAMC and WHYY interviews, the Lancet Haematology author manuscript, and contextual clinical precedents. Distinguished original testimony from independent clinical confirmation and preserved uncertainty about patient matching, treatment timing, and the exact model. Reviewed the contemporary Elsevier interview and public MATRIX releases to distinguish the early system from subsequently documented implementations.", "embedded_reference_checks": [ { "url": "https://www.nejm.org/doi/full/10.1056/NEJMc2412494", "title": "Identifying and Targeting TNF Signaling in Idiopathic Multicentric Castleman’s Disease", "access_url": "https://pubmed.ncbi.nlm.nih.gov/39908436/", "finding": "The linked NEJM paper concerns an adalimumab-treated patient under Luke Chen’s care. Coates received carfilzomib, cyclophosphamide, and dexamethasone under Wayne Gao’s care. These are different patients and regimens, even though an earlier CDCN profile also described Coates as having POEMS-associated multicentric Castleman disease. The NEJM paper is not clinical documentation for Coates." }, { "url": "https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/giad057/7246583", "title": "KGML-xDTD: a knowledge graph–based machine learning framework for drug treatment prediction and mechanism description", "finding": "The NYT links this methods paper as background. The Lancet Haematology commentary confirms that KGML-xDTD is one of several algorithms used in Every Cure’s platform. Neither paper establishes which algorithm or release contributed to Coates’s recommendation." }, { "url": "https://github.com/everycure-org/matrix/blob/25e1272fe14f4029627e91e1ad90a576e312ade4/docs/src/releases/posts/2024-11-27v0.2.5/post.md", "title": "MATRIX v0.2.5 release notes", "finding": "The November 28, 2024 notes describe KGML-xDTD and an integrated knowledge graph. The notes do not identify Coates’s earlier run. Public repository searches did not supply a case-specific configuration or checkpoint." } ], "homepage_source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0006" ], "earlier_reporting": [ { "url": "https://whyy.org/articles/ai-platform-every-cure-medicine-disease-treatment-university-pennyslvania/", "publication_date": "2024-03-10", "identification": "Patient unnamed; matching to Coates remains an inference." }, { "url": "https://www.aamc.org/news/doctor-saved-his-own-life-now-he-s-mission-save-thousands-more", "publication_date": "2024-09-24", "identification": "Names Joseph and January 2024; matching to Joseph Coates follows the surrounding case details." } ], "chronology_note": "The case date remains March 20, 2025, the NYT publication date recorded for this entry. Earlier reporting is preserved here without substituting a different date in this revision.", "contextual_clinical_precedents": [ { "url": "https://doi.org/10.1016/j.jaccas.2020.12.027", "access_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8310984/", "title": "Pericardial Tamponade and Other Cardiac Complications in POEMS Syndrome", "citation": "Levene et al., JACC: Case Reports, 2021. https://doi.org/10.1016/j.jaccas.2020.12.027.", "locator": "Management and Follow-Up sections.", "finding": "A different 66-year-old patient treated at Oregon Health & Science University received carfilzomib, cyclophosphamide, and dexamethasone for POEMS syndrome. This establishes clinical use before Coates’s treatment. No AI contribution is described.", "relationship": "Contextual clinical precedent only. Not retained as evidence of Coates’s outcome and not counted toward confidence in this case." }, { "url": "https://library.ehaweb.org/eha/2024/eha2024-congress/document?c_id=421524&cm_id=436356&type=document436356", "title": "EFFICACY AND SAFETY OF CARFILZOMIB, CYCLOPHOSPHAMIDE AND DEXAMETHASONE FOR THE TREATMENT OF POEMS SYNDROME", "locator": "EHA 2024 abstract PB2758, Methods and Results. Publication-only abstract.", "publication_date": "2024", "publication_precision": "year", "access_note": "Full extracted text of the original EHA document was inspected. The individual abstract’s publication day and author list were not established. The congress abstract book was published on June 14, 2024, but that date is not substituted for the individual item’s unverified release date.", "finding": "A retrospective Qilu Hospital cohort included eight POEMS patients treated from March 2022 through January 2024. Seven responded, and one underwent autologous stem cell transplantation. These are other patients, and no AI involvement is stated.", "relationship": "Plausible match for Every Cure’s summer-2024 conference claim, but the portfolio does not cite PB2758, so the match remains inferential. Context only, not counted as evidence of Coates’s treatment or of AI’s benefit." } ], "diagnostic_history_note": { "url": "https://cdcn.org/wp-content/uploads/2023/12/CDCN-2023-Impact-Report.pdf", "locator": "November 2023 report, printed p. 4, “The Faces of Castleman Disease,” Joseph Coates.", "finding": "This earlier profile calls Coates’s condition POEMS-associated multicentric Castleman disease. That historical label does not make him the adalimumab-treated patient in the separate NEJM report." } } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "evidence", "system" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Original interviews provide testimony from Coates and his physicians. Every Cure, Penn Medicine, and ARPA-H later describe the same treatment. The accounts share witnesses and investigators rather than providing independent clinical confirmation.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Mr. Joseph Coates received three drugs (i) that a consulting physician had considered and (ii) that Every Cure’s early drug-repurposing system had scored highly.", "account": "In January 2024, Joseph Coates, 37, of Renton, Washington, was critically ill with POEMS syndrome. His heart and kidneys were failing, and he was too sick for a stem cell transplant. His partner, Tara Theobald, asked David Fajgenbaum of the University of Pennsylvania and Every Cure for help. Fajgenbaum considered three drugs used for multiple myeloma, a related disease. He later explained that an early Every Cure algorithm also scored those drugs highly for POEMS. He recommended carfilzomib, cyclophosphamide, and dexamethasone to Coates’s treating hematologist and oncologist, Wayne Gao, who agreed to administer them. Coates later reported that he responded within one or two weeks and left intensive care three weeks later. He recovered enough to receive a stem cell transplant and reported full remission five months after that transplant. The New York Times reported improvement within a week and transplant eligibility about four months later. A brief vignette in The Lancet Haematology describes a matching unnamed patient and labels the result unpublished data. The sources support a contribution from AI alongside the physicians’ judgment, but they do not establish the exact model release or isolate its effect on recovery." } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "use": "Drug-disease scoring to support the physicians’ assessment of candidate treatments for POEMS syndrome in January 2024.", "human_decision": "Fajgenbaum recommended the regimen; Wayne Gao weighed the risks and administered it.", "unreported_details": [ "Exact algorithm and release", "Input knowledge-graph snapshot", "Case-specific scores and run identifier" ], "historical_context": "MATRIX was publicly named by March 2024. Its subsequently published configuration is not a verified description of Coates’s January run." } }, "provenance": { "kind": "source_review", "basis": "Separated the reported clinical workflow from later platform documentation.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0127-source-0003", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The system scored candidate drugs for POEMS syndrome in January 2024. Physicians reviewed the scores and chose the treatment.", "editor_note": "" } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The case accounts identify Every Cure’s early algorithms, but no reviewed source identifies the exact algorithm or model release that supplied Coates’s January 2024 scores. KGML-xDTD and the later documented MATRIX architecture cannot be assigned to this run.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0127-source-0003", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "reason": "The case accounts identify Every Cure’s early algorithms, but no reviewed source identifies the exact algorithm or model release that supplied Coates’s January 2024 scores. KGML-xDTD and the later documented MATRIX architecture cannot be assigned to this run.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Every Cure’s early algorithm for scoring possible uses of drugs against diseases. The accounts do not identify which of its algorithms produced these scores.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The case accounts identify Every Cure’s early algorithms, but no reviewed source identifies the exact algorithm or model release that supplied Coates’s January 2024 scores. KGML-xDTD and the later documented MATRIX architecture cannot be assigned to this run.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0127-source-0003", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "reason": "The case accounts identify Every Cure’s early algorithms, but no reviewed source identifies the exact algorithm or model release that supplied Coates’s January 2024 scores. KGML-xDTD and the later documented MATRIX architecture cannot be assigned to this run.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The January 2024 configuration has no published release identifier.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Every Cure’s early drug-repurposing system" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0127-source-0003", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Every Cure", "underlying_model_provider": "Not identified for this case." } }, "provenance": { "kind": "source_review", "basis": "Every Cure is identified in its own portfolio and Fajgenbaum’s accounts. The contemporary Elsevier interview establishes multiple contributing algorithms, without identifying the one used for Coates.", "record_fields": [ "developer", "system" ], "source_refs": [ "AIBD-0127-source-0003", "AIBD-0127-source-0006", "AIBD-0127-source-0010" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Physicians treated Joseph Coates’s POEMS syndrome with three drugs that an early Every Cure algorithm also ranked highly, allowing a later stem cell transplant and remission", "headline": "A man with a rare blood disorder became well enough for a transplant" } }, "provenance": { "kind": "source_review", "basis": "Reviewed original patient and physician accounts and the investigators’ commentary. Clarified AI’s contribution and separated unpublished clinical details, contextual precedents, and patient-matching inferences.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "fe0be1b2a61438f2745378b83c663e369f6a01d69068c3e40452180265ca4413" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after the homepage copy revision.", "record_fields": [ "summary", "revisions" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In January 2024, Joseph Coates, 37, of Renton, Washington, was critically ill with POEMS syndrome. His heart and kidneys were failing, and he was too sick for a stem cell transplant. His partner, Tara Theobald, asked David Fajgenbaum of the University of Pennsylvania and Every Cure for help. Fajgenbaum considered three drugs used for multiple myeloma, a related disease. He later explained that an early Every Cure algorithm also scored those drugs highly for POEMS. He recommended carfilzomib, cyclophosphamide, and dexamethasone to Coates’s treating hematologist and oncologist, Wayne Gao, who agreed to administer them. Coates later reported that he responded within one or two weeks and left intensive care three weeks later. He recovered enough to receive a stem cell transplant and reported full remission five months after that transplant. The New York Times reported improvement within a week and transplant eligibility about four months later. A brief vignette in The Lancet Haematology describes a matching unnamed patient and labels the result unpublished data. The sources support a contribution from AI alongside the physicians’ judgment, but they do not establish the exact model release or isolate its effect on recovery.", "replication": { "produced_by": [ "Fajgenbaum recognized similarities between POEMS syndrome and multiple myeloma and reviewed high AI scores for drugs that were used for myeloma.", "Fajgenbaum answered the family’s urgent appeal and discussed treatment with Wayne Gao, who assessed the risks and administered the three drugs." ], "must_hold": [ "Clinicians must assess the proposed drugs, the patient’s condition, and the risks of treatment. A high model score alone does not establish that a drug is suitable.", "The patient must respond sufficiently to receive any further treatment that is needed. Coates later underwent a stem cell transplant before he reported full remission." ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0127-source-0001", "AIBD-0127-source-0002", "AIBD-0127-source-0003", "AIBD-0127-source-0004", "AIBD-0127-source-0005", "AIBD-0127-source-0006", "AIBD-0127-source-0007", "AIBD-0127-source-0008", "AIBD-0127-source-0009" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The consulting physician recognized similarities between POEMS syndrome and multiple myeloma and reviewed the AI scores for drugs that were used for myeloma. He discussed treatment with the physician responsible for Coates, who assessed the risks and administered the drugs.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 27, "record_mapped": 7, "not_assessed": 57, "complete": false, "by_state": { "value_present": 32, "not_reported": 2, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0552", "title": "Lancashire County Council – A strategic approach to deploying AI in transport", "summary": "Lancashire reports that AI traffic predictions, junction observations, and congestion analysis support transport decisions and bus-route planning.", "date_observed": "2025-03-25", "date_basis": "source publication", "date_precision": "day", "benefit_status": "mixed", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-012", "account": "Lancashire combines Aimsun, VivaCity, and Alchera tools for traffic forecasts, junction observations, and congestion analysis in its Future Mobility Platform. The page says that insights have been used to plan bus routes. It gives no before-and-after congestion, travel-time, service, or safety outcome.", "category": "general benefit", "unexpected": false, "purpose": "Provide traffic intelligence and prediction to support transport planning and network management.", "system": "Future Mobility Platform using Aimsun Real Time, VivaCity sensors, and Alchera Pinch Point Analysis", "model_version": null, "developer": "Aimsun, VivaCity, and Alchera", "deployer": "Lancashire County Council", "location": "United Kingdom", "domain": "Transport planning and network management", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The source reports that new traffic intelligence is used in planning, including bus routes. This is an analytical capability gain, without a measured congestion reduction." }, { "group": "societal", "depth": null, "reason": "Faster journeys, reduced congestion, and improved bus services remain objectives without defined reported outcomes." } ], "ai_role": { "status": "assessed", "statement": "The source identifies AI-based traffic prediction, visual junction observations, and congestion analysis as inputs to planning. It states that the intelligence has informed bus-route work, without quantifying improved journeys or congestion outcomes." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Lancashire County Council – A strategic approach to deploying AI in transport", "url": "https://www.local.gov.uk/case-studies/lancashire-county-council-strategic-approach-deploying-ai-transport", "date": "2025-03-25", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The program integrates historical and real-time transport data and draws on cross-council technical and procurement expertise.", "Different vendor components contribute predictions, observations, and hotspot analysis." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "Lancashire uses AI traffic insights to support route planning", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/lancashire-county-council-strategic-approach-deploying-ai-transport", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0552", "catalog_version": "1.0.0", "source_fingerprint": "7ef237ba7da547ccc9e1b8e1038c4cd5af1146658520451943ed41411a4c6c0a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0552-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Aimsun, VivaCity, and Alchera", "deployer": "Lancashire County Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The source identifies AI-based traffic prediction, visual junction observations, and congestion analysis as inputs to planning. It states that the intelligence has informed bus-route work, without quantifying improved journeys or congestion outcomes." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The source identifies AI-based traffic prediction, visual junction observations, and congestion analysis as inputs to planning. It states that the intelligence has informed bus-route work, without quantifying improved journeys or congestion outcomes." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The source reports that new traffic intelligence is used in planning, including bus routes. This is an analytical capability gain, without a measured congestion reduction." }, { "group": "societal", "reason": "Faster journeys, reduced congestion, and improved bus services remain objectives without defined reported outcomes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The source reports that new traffic intelligence is used in planning, including bus routes. This is an analytical capability gain, without a measured congestion reduction." }, { "group": "societal", "reason": "Faster journeys, reduced congestion, and improved bus services remain objectives without defined reported outcomes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported and intended benefits" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The source reports that new traffic intelligence is used in planning, including bus routes. 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"review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Lancashire combines Aimsun, VivaCity, and Alchera tools for traffic forecasts, junction observations, and congestion analysis in its Future Mobility Platform. 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The page says that insights have been used to plan bus routes. It gives no before-and-after congestion, travel-time, service, or safety outcome." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Future Mobility Platform using Aimsun Real Time, VivaCity sensors, and Alchera Pinch Point Analysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Aimsun, VivaCity, and Alchera" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lancashire County Council – A strategic approach to deploying AI in transport", "headline": "Lancashire uses AI traffic insights to support route planning" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7ef237ba7da547ccc9e1b8e1038c4cd5af1146658520451943ed41411a4c6c0a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Lancashire combines Aimsun, VivaCity, and Alchera tools for traffic forecasts, junction observations, and congestion analysis in its Future Mobility Platform. The page says that insights have been used to plan bus routes. It gives no before-and-after congestion, travel-time, service, or safety outcome.", "replication": { "produced_by": [ "The program integrates historical and real-time transport data and draws on cross-council technical and procurement expertise.", "Different vendor components contribute predictions, observations, and hotspot analysis." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0576", "title": "Milton Keynes City Council – Milton Keynes AI (MKAI) Festival", "summary": "Milton Keynes offered a practical AI workshop and interactive demonstrations in 2024. Better understanding, confidence, and feedback remain intended benefits without measured changes.", "date_observed": "2025-03-25", "date_basis": "source publication", "date_precision": "day", "benefit_status": "intended", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-016", "account": "The festival included Code For Her's October 29, 2024 workshop, where participants could use and build AI on their own laptops. The Smart City Experience Centre opened on November 1 with interactive AI applications and robots, including Pepper for visitor information and entertainment. The host aimed to improve public understanding and confidence and gather feedback for technology providers. The accounts provide no measurements of changes in learning, anxiety, or product quality. Civic outcomes from the separate hackathon are unspecified.", "category": "general benefit", "unexpected": false, "purpose": "Improve understanding of AI through practical use and interactive demonstrations, and obtain user feedback on technology applications.", "system": "AI tools in the Code For Her workshop and interactive AI applications at the Smart City Experience Centre", "model_version": null, "developer": null, "deployer": "Code For Her, Smart City Consultancy, Milton Keynes City Council, and centre:mk", "location": "Milton Keynes, United Kingdom", "domain": "Education and public engagement", "segment": null, "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Workshop participants and visitors are intended to understand AI better through practical use and interactive demonstrations. The extent of any learning or confidence improvement is unmeasured." }, { "group": "organizational", "depth": null, "reason": "Technology providers are intended to receive useful feedback from public interaction with their applications. The sources do not establish the extent or consequences of that feedback." } ], "ai_role": { "status": "unassessed", "statement": "Participants could use and build AI, and visitors could interact with AI applications. Effects on learning and feedback are not separated from human instruction and the wider event." }, "evidence": [ { "kind": "report", "citation": "Code For Her event listing hosted by Protospace. The workshop date is October 29, 2024; the publication date is unspecified.", "title": "Using, Building and Understanding Responsible AI", "url": "https://protospace.uk/events/using-building-and-understanding-responsible-ai", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "The Open University Knowledge Media Institute, October 29, 2024. A participating institution identifies the workshop as a festival activity.", "title": "KMi’s Prof Enrico Motta and Prof John Domingue attend the launch of the Milton Keynes AI Festival at historic Bletchley Park", "url": "https://kmi.open.ac.uk/news/article/944", "date": "2024-10-29", "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "centre:mk, account of the November 2024 Experience Centre launch. Publication date unspecified.", "title": "Smart City Experience Centre has Launched at centre:mk", "url": "https://www.centremk.com/about-us/latest-news/smart-city-experience-centre-has-launched-at-centremk/", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Smart City Consultancy event listing hosted by Protospace. The opening date is November 1, 2024; the publication date is unspecified.", "title": "Milton Keynes Smart City Experience Centre: Official Opening", "url": "https://protospace.uk/events/milton-keynes-smart-city-experience-centre-official-opening", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Local Government Association, March 25, 2025. 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Council account of the festival, demonstrations, and Experience Centre launch.", "title": "Milton Keynes City Council – Milton Keynes AI (MKAI) Festival", "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-milton-keynes-ai-mkai-festival", "date": "2025-03-25", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Milton Keynes offered a practical AI workshop and interactive demonstrations in 2024. 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Civic outcomes from the separate hackathon are unspecified." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI tools in the Code For Her workshop and interactive AI applications at the Smart City Experience Centre" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Milton Keynes City Council – Milton Keynes AI (MKAI) Festival", "headline": "Milton Keynes offers hands-on AI learning and interactive demonstrations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e0185304f9c557f83eb82251f27376bfe8f6c1c0cdb168aba1b93cda197e8e68" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The festival included Code For Her's October 29, 2024 workshop, where participants could use and build AI on their own laptops. The Smart City Experience Centre opened on November 1 with interactive AI applications and robots, including Pepper for visitor information and entertainment. The host aimed to improve public understanding and confidence and gather feedback for technology providers. The accounts provide no measurements of changes in learning, anxiety, or product quality. Civic outcomes from the separate hackathon are unspecified.", "replication": { "produced_by": [ "Participants are offered practical AI exercises, while visitors can interact with AI applications in an accessible shopping-center setting." ], "must_hold": [ "Likely requirements include suitable AI tools, practical instruction, usable demonstrations, and visitor feedback. These have not been validated as sufficient for a beneficial outcome." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0145", "title": "HMRC's Connect data-matching system: about £4.6 billion of additional yield in 2024–25", "summary": "HMRC's Connect data-matching system yielded ~£4.6bn extra tax in 2024–25 per FOI; C&AG confirms its use to stop risky repayments", "date_observed": "2025-03-31", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "HM Revenue & Customs launched Connect in 2010–11. Its annual report calls it an IT system that joins a billion pieces of data across its tax regimes to help identify fraud. In a freedom-of-information response reported by Pinsent Masons on 8 October 2025, HMRC said Connect cases generated an average £3.4 billion of additional annual yield. It was about £4.6 billion in 2024–25, with around 4,300 staff using it. The Comptroller and Auditor General's report in HMRC's 2024–25 accounts records that HMRC used TRUCE (Transaction Risking Upstream in a Connect Environment). It served to identify and stop VAT and income-tax repayments needing investigation. IDRS replaced it from August 2023. Official sources describe data analytics and risk rules, not AI.", "category": "general benefit", "unexpected": false, "purpose": "Match and analyze data from many sources to identify tax non-compliance and risky repayment claims", "system": "HMRC Connect (data-matching and risk analytics) and TRUCE (Transaction Risking Upstream in a Connect Environment)", "model_version": null, "developer": null, "deployer": "HM Revenue & Customs (HMRC)", "location": null, "domain": "Tax administration: compliance and fraud detection", "segment": "National revenue authority", "benefit_type": "Increased Product Revenue", "taxonomy_note": "Tax yield is read as the authority's revenue; Trustible's description is written for product sales.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate yield with no discrete attributable event." }, { "group": "organizational", "depth": null, "reason": "The £4.6 billion figure is HMRC's own annual attribution via FOI, not an audited event." }, { "group": "societal", "depth": null, "reason": "Aggregate national revenue figure." } ], "ai_role": { "status": "unassessed", "statement": "Yield attribution to Connect comes from HMRC's FOI response as reported by Pinsent Masons. No independent evaluation apportions yield between the system and caseworkers. The NAO's audit report describes TRUCE/IDRS as automated risk-assessment of repayment claims whose controls it reviewed, without quantifying stopped repayments. The cited sources describe the system as data analytics and risk rules rather than machine learning." }, "evidence": [ { "kind": "report", "citation": "Comptroller and Auditor General (2025). Report on the Trust Statement, in HM Revenue & Customs Annual Report and Accounts 2024 to 2025, Key audit matter 5 (printed pp. 177-178).", "title": "HMRC Annual Report and Accounts 2024 to 2025 – Report of the Comptroller and Auditor General", "url": "https://assets.publishing.service.gov.uk/media/687e5d318adf4250705c96d8/HMRC_annual_report_and_accounts_2024_to_2025.pdf", "date": null, "written_by": "independent", "quote": "For both VAT and income tax, HMRC used TRUCE (the Transaction Risking Upstream in a Connect Environment) to identify and stop repayments that may require investigation." }, { "kind": "report", "citation": "HM Revenue & Customs (2011). Annual Report and Accounts 2010-11, HC 981, p. 10.", "title": "HMRC Annual Report and Accounts 2010-11", "url": "https://assets.publishing.service.gov.uk/media/5a78b230ed915d07d35b1b53/annual-report-accounts-1011.pdf", "date": null, "written_by": "deployer", "quote": "We successfully launched the ‘Connect’ IT system which joins a billion pieces of data from across our tax regimes to help identify fraud." }, { "kind": "news report", "citation": "Pinsent Masons Out-Law (2025). HMRC finds value in 'big data' after bringing in extra £4.6 billion, 8 Oct 2025 (reporting an HMRC FOI response).", "title": "HMRC finds value in ‘big data’ after bringing in extra £4.6billion", "url": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion", "date": "2025-10-08", "written_by": "independent", "quote": "HMRC, in a freedom of information request to Pinsent Masons, said it generated on average £3.4bn in additional annual yield from Connect cases" }, { "kind": "report", "citation": "HM Revenue & Customs (2026). Annual Report and Accounts 2025 to 2026, HC 350. Ordered by the House of Commons to be printed on 9 July 2026.", "title": "HMRC Annual Report and Accounts 2025 to 2026", "url": "https://assets.publishing.service.gov.uk/media/6a4f66c406e7256c331df8a2/HMRC_annual_report_and_accounts_2025_to_2026.pdf", "date": "2026-07-09", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Linking of bank, marketplace, land-registry and other data to taxpayer records", "Risk rules and scorecards feeding compliance cases to about 4,300 staff", "Upstream risking of VAT and Self Assessment repayment claims (TRUCE, then IDRS)" ], "must_hold": [ "Legal gateways to third-party data", "Staff capacity to work cases generated by the system", "Governance of risk rules, which the C&AG reviews annually" ], "echoes": [ { "date": "2023-08-01", "setting": "TRUCE replaced by IDRS for VAT repayments from August 2023, Self Assessment migrated May 2024 (C&AG report; month only)", "model_version": null, "outcome": "unknown", "source": "https://assets.publishing.service.gov.uk/media/687e5d318adf4250705c96d8/HMRC_annual_report_and_accounts_2024_to_2025.pdf" }, { "date": "2025-03-31", "setting": "Average annual yield £3.4bn from Connect cases over the period covered by the FOI response (Pinsent Masons, 8 October 2025)", "model_version": null, "outcome": "recurred", "source": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion" } ] }, "paired_incident": null, "headline": "HMRC's Connect yields about £4.6 billion of extra tax in 2024–25", "metric": "£3.4 billion of additional annual yield, about £4.6 billion in 2024–25", "comparator": null, "later": { "status": "persisted", "date": "2026-07-09", "note": "HMRC's 2025-26 annual report, ordered printed on 9 July 2026, says that AI and advanced analytics enabled the protection and recovery of £10 billion in tax in 2025-26 and that a Chief AI Officer was appointed in April 2026; the report does not name Connect.", "quote": "Artificial intelligence (AI) and advanced analytics has already enabled the protection and recovery of £10 billion in tax between 2025 and 2026, and we are continuing to work at pace in this area, appointing our first ever Chief AI Officer in April 2026, to provide clear leadership and ensure the AI advancements that we make are responsible.", "url": "https://assets.publishing.service.gov.uk/media/6a4f66c406e7256c331df8a2/HMRC_annual_report_and_accounts_2025_to_2026.pdf" }, "value": { "amount": "£4.6bn", "what": "additional tax yield from Connect cases in the 2024-25 tax year (average £3.4bn a year)", "who": "HMRC, for the Exchequer, gains", "estimate": false, "quote": "HMRC, in a freedom of information request to Pinsent Masons, said it generated on average £3.4bn in additional annual yield from Connect cases, with the 2024-25 tax year generating approximately £4.6bn.", "url": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion" }, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the value as stated from the cited sources.", "source": "https://assets.publishing.service.gov.uk/media/6a4f66c406e7256c331df8a2/HMRC_annual_report_and_accounts_2025_to_2026.pdf; https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.gov.uk/government/organisations/hm-revenue-customs/about", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, one independent news report and two reports from the deployer. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0145", "catalog_version": "1.0.0", "source_fingerprint": "609307d763754e7933c1086b7de496e0819b101a501f5bc3aa8947927223a934", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0145-source-0001", "AIBD-0145-source-0002", "AIBD-0145-source-0003", "AIBD-0145-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0145-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "HM Revenue & Customs (HMRC)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Yield attribution to Connect comes from HMRC's FOI response as reported by Pinsent Masons. No independent evaluation apportions yield between the system and caseworkers. The NAO's audit report describes TRUCE/IDRS as automated risk-assessment of repayment claims whose controls it reviewed, without quantifying stopped repayments. The cited sources describe the system as data analytics and risk rules rather than machine learning." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report, one independent news report and two reports from the deployer. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate yield with no discrete attributable event." }, { "group": "organizational", "reason": "The £4.6 billion figure is HMRC's own annual attribution via FOI, not an audited event." }, { "group": "societal", "reason": "Aggregate national revenue figure." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Aggregate yield with no discrete attributable event." }, { "group": "organizational", "reason": "The £4.6 billion figure is HMRC's own annual attribution via FOI, not an audited event." }, { "group": "societal", "reason": "Aggregate national revenue figure." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "£4.6bn", "what": "additional tax yield from Connect cases in the 2024-25 tax year (average £3.4bn a year)", "who": "HMRC, for the Exchequer, gains", "estimate": false, "quote": "HMRC, in a freedom of information request to Pinsent Masons, said it generated on average £3.4bn in additional annual yield from Connect cases, with the 2024-25 tax year generating approximately £4.6bn.", "url": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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HMRC finds value in 'big data' after bringing in extra £4.6 billion, 8 Oct 2025 (reporting an HMRC FOI response).", "title": "HMRC finds value in ‘big data’ after bringing in extra £4.6billion", "url": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion", "date": "2025-10-08", "written_by": "independent", "quote": "HMRC, in a freedom of information request to Pinsent Masons, said it generated on average £3.4bn in additional annual yield from Connect cases" }, { "kind": "report", "citation": "HM Revenue & Customs (2026). Annual Report and Accounts 2025 to 2026, HC 350. Ordered by the House of Commons to be printed on 9 July 2026.", "title": "HMRC Annual Report and Accounts 2025 to 2026", "url": "https://assets.publishing.service.gov.uk/media/6a4f66c406e7256c331df8a2/HMRC_annual_report_and_accounts_2025_to_2026.pdf", "date": "2026-07-09", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "HMRC's Connect data-matching system yielded ~£4.6bn extra tax in 2024–25 per FOI; C&AG confirms its use to stop risky repayments", "account": "HM Revenue & Customs launched Connect in 2010–11. Its annual report calls it an IT system that joins a billion pieces of data across its tax regimes to help identify fraud. In a freedom-of-information response reported by Pinsent Masons on 8 October 2025, HMRC said Connect cases generated an average £3.4 billion of additional annual yield. It was about £4.6 billion in 2024–25, with around 4,300 staff using it. The Comptroller and Auditor General's report in HMRC's 2024–25 accounts records that HMRC used TRUCE (Transaction Risking Upstream in a Connect Environment). It served to identify and stop VAT and income-tax repayments needing investigation. IDRS replaced it from August 2023. Official sources describe data analytics and risk rules, not AI." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "HMRC Connect (data-matching and risk analytics) and TRUCE (Transaction Risking Upstream in a Connect Environment)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "HMRC's Connect data-matching system: about £4.6 billion of additional yield in 2024–25", "headline": "HMRC's Connect yields about £4.6 billion of extra tax in 2024–25" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "609307d763754e7933c1086b7de496e0819b101a501f5bc3aa8947927223a934" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "HM Revenue & Customs launched Connect in 2010–11. Its annual report calls it an IT system that joins a billion pieces of data across its tax regimes to help identify fraud. In a freedom-of-information response reported by Pinsent Masons on 8 October 2025, HMRC said Connect cases generated an average £3.4 billion of additional annual yield. It was about £4.6 billion in 2024–25, with around 4,300 staff using it. The Comptroller and Auditor General's report in HMRC's 2024–25 accounts records that HMRC used TRUCE (Transaction Risking Upstream in a Connect Environment). It served to identify and stop VAT and income-tax repayments needing investigation. IDRS replaced it from August 2023. Official sources describe data analytics and risk rules, not AI.", "replication": { "produced_by": [ "Linking of bank, marketplace, land-registry and other data to taxpayer records", "Risk rules and scorecards feeding compliance cases to about 4,300 staff", "Upstream risking of VAT and Self Assessment repayment claims (TRUCE, then IDRS)" ], "must_hold": [ "Legal gateways to third-party data", "Staff capacity to work cases generated by the system", "Governance of risk rules, which the C&AG reviews annually" ], "echoes": [ { "date": "2023-08-01", "setting": "TRUCE replaced by IDRS for VAT repayments from August 2023, Self Assessment migrated May 2024 (C&AG report; month only)", "outcome": "unknown", "source": "https://assets.publishing.service.gov.uk/media/687e5d318adf4250705c96d8/HMRC_annual_report_and_accounts_2024_to_2025.pdf" }, { "date": "2025-03-31", "setting": "Average annual yield £3.4bn from Connect cases over the period covered by the FOI response (Pinsent Masons, 8 October 2025)", "outcome": "recurred", "source": "https://www.pinsentmasons.com/out-law/news/hmrc-big-data-tax-revenue-boost-4-6-billion" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0562", "title": "St Helens Borough Council – augmenting TEC with AI", "summary": "St Helens built AI tools that match care assessments to a technology catalog and draft personalized care plans. Improved resident independence remains an intended benefit.", "date_observed": "2025-04-09", "date_basis": "source publication", "date_precision": "day", "benefit_status": "mixed", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-026", "account": "St Helens Borough Council built an AI-integrated technology-enabled-care catalog using Microsoft Copilot Studio. Care professionals co-curated the catalog. Predictive matching connects care-assessment information to suitable technology options, and generative AI drafts personalized care plans and costings. The workflow is intended to help residents return home and live independently. Improvements in care and independent living remain unevaluated. Reported medication-dispenser savings and in-house development costs concern other parts of the service.", "category": "general benefit", "unexpected": false, "purpose": "Match care needs to technology-enabled support and generate personalized care plans.", "system": "St Helens AI-integrated technology-enabled-care catalog and planning tools built with Microsoft Copilot Studio", "model_version": null, "developer": "St Helens Borough Council using Microsoft Copilot Studio", "deployer": "St Helens Borough Council", "location": "United Kingdom", "domain": "Adult social care and care planning", "segment": null, "benefit_type": "Product Personalization", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council reports a built AI workflow that matches care assessments to a technology catalog and generates personalized care plans. This is a planning-capability benefit, without an established cost saving or resident outcome." }, { "group": "personal", "depth": null, "reason": "Better matching and independent living are intended, but the source does not define an achieved resident outcome." } ], "ai_role": { "status": "assessed", "statement": "Predictive matching links care-assessment information to catalog options, and generative AI drafts personalized care plans. The source identifies this functionality but does not establish improved resident outcomes or AI-produced financial savings." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "St Helens Borough Council – augmenting TEC with AI", "url": "https://www.local.gov.uk/case-studies/st-helens-borough-council-augmenting-tec-ai", "date": "2025-04-09", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The council used Microsoft Copilot Studio to combine care-assessment information with a technology catalog co-curated by care professionals.", "Predictive matching selects relevant technology options and generative AI drafts personalized care plans and costings." ], "must_hold": [ "The conditions needed to reproduce a care or efficiency improvement are unknown." ], "echoes": [] }, "paired_incident": null, "headline": "St Helens uses AI to match care needs and draft care plans", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/st-helens-borough-council-augmenting-tec-ai", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0562", "catalog_version": "1.0.0", "source_fingerprint": "c6db14eda9c713615f01323f8443759a011d37b91687e065a2fb6580a53a93cd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0562-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "St Helens Borough Council using Microsoft Copilot Studio", "deployer": "St Helens Borough Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Predictive matching links care-assessment information to catalog options, and generative AI drafts personalized care plans. The source identifies this functionality but does not establish improved resident outcomes or AI-produced financial savings." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Predictive matching links care-assessment information to catalog options, and generative AI drafts personalized care plans. The source identifies this functionality but does not establish improved resident outcomes or AI-produced financial savings." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council reports a built AI workflow that matches care assessments to a technology catalog and generates personalized care plans. This is a planning-capability benefit, without an established cost saving or resident outcome." }, { "group": "personal", "reason": "Better matching and independent living are intended, but the source does not define an achieved resident outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council reports a built AI workflow that matches care assessments to a technology catalog and generates personalized care plans. This is a planning-capability benefit, without an established cost saving or resident outcome." }, { "group": "personal", "reason": "Better matching and independent living are intended, but the source does not define an achieved resident outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported and intended benefits" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council reports a built AI workflow that matches care assessments to a technology catalog and generates personalized care plans. This is a planning-capability benefit, without an established cost saving or resident outcome." }, { "group": "personal", "reason": "Better matching and independent living are intended, but the source does not define an achieved resident outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-026" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0562" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Product Personalization" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "St Helens Borough Council built an AI-integrated technology-enabled-care catalog using Microsoft Copilot Studio. Care professionals co-curated the catalog. Predictive matching connects care-assessment information to suitable technology options, and generative AI drafts personalized care plans and costings. The workflow is intended to help residents return home and live independently. Improvements in care and independent living remain unevaluated. Reported medication-dispenser savings and in-house development costs concern other parts of the service.", "benefit_type": "Product Personalization" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The council reports a built AI workflow that matches care assessments to a technology catalog and generates personalized care plans. This is a planning-capability benefit, without an established cost saving or resident outcome." }, { "group": "personal", "reason": "Better matching and independent living are intended, but the source does not define an achieved resident outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "mixed" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Match care needs to technology-enabled support and generate personalized care plans." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Care professionals co-curated the catalog. Predictive matching connects care-assessment information to suitable technology options, and generative AI drafts personalized care plans and costings. The workflow is intended to help residents return home and live independently. Improvements in care and independent living remain unevaluated. 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The authors are at the Department of Cardiology and Pneumology, University Medical Center Göttingen, Germany. It was published 15 April 2025. The event dates are not given. A 34-year-old man with no medical history consulted his primary care physician. His smartwatch had detected “heart arrhythmias” while he was asymptomatic. A 12-lead electrocardiogram (ECG) showed sinus rhythm with frequent premature atrial contractions (PACs). A cardiologist found a left ventricular ejection fraction of 35% with a dilated ventricle. Despite guideline-directed heart-failure therapy he returned months later with palpitations and chest pain. Cardiac magnetic resonance imaging (MRI) showed LVEF 15%. Coronary disease was excluded by computed tomography (CT) angiography. Holter recordings showed a PAC burden of 30–50%. High-density 3D mapping located the ectopic focus at the left inferior pulmonary vein. Radiofrequency ablation terminated the arrhythmia. At six months he was symptom-free with LVEF 50% and fewer than 1% PACs. Spironolactone was stopped. The authors call it the first reported PAC-related arrhythmia-induced cardiomyopathy initially detected by a wearable. The watch's brand, model and the form of its alert are not stated.", "category": "benefit created", "unexpected": false, "purpose": "Smartwatch arrhythmia alerts are built to prompt medical review of irregular rhythms. The alert here served that purpose. The condition it uncovered, PAC-induced cardiomyopathy, is one the authors say wearables are not usually credited with finding.", "system": "Smartwatch arrhythmia detection (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "Göttingen, Germany", "domain": "Healthcare (cardiology; heart failure)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "The alert started a chain that diagnosed a cardiomyopathy. The condition progressed to LVEF 15%. Ablation reversed it to LVEF 50% with resolution of symptoms. The authors present early detection as what allowed the heart failure to be treated before further progression." } ], "ai_role": { "status": "assessed", "statement": "The watch's detection of “heart arrhythmias” is what sent an asymptomatic man to his doctor. Everything after (ECG, echo, MRI, mapping, ablation) was clinical. The report does not say what the watch flagged, whether a notification or an ECG reading, nor which algorithm. The device's contribution is therefore established only as the trigger." }, "evidence": [ { "kind": "case report", "citation": "Soubh N, Rasenack E, Haarmann H, Zabel M, Bergau L (2025). Smartwatch-enabled early detection and treatment of cardiomyopathy induced by premature atrial contractions: a case report. European Heart Journal - Case Reports 9(4):ytaf151. doi:10.1093/ehjcr/ytaf151 (PMC12209856).", "title": "Smartwatch-enabled early detection and treatment of cardiomyopathy induced by premature atrial contractions: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12209856/", "date": "2025-04-15", "written_by": "independent", "quote": "A 34-year-old male with no prior medical history consulted his primary care physician after his smartwatch detected ‘heart arrhythmias’." }, { "kind": "case report", "citation": "Soubh N et al. (2025), Eur Heart J Case Rep 9(4):ytaf151, outcome.", "title": "Smartwatch-enabled early detection and treatment of cardiomyopathy induced by premature atrial contractions: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12209856/", "date": "2025-04-15", "written_by": "independent", "quote": "At the six-month follow-up, the patient was symptom-free with a recovered LVEF of 50%." }, { "kind": "case report", "citation": "Soubh N et al. (2025), Eur Heart J Case Rep 9(4):ytaf151, discussion.", "title": "Smartwatch-enabled early detection and treatment of cardiomyopathy induced by premature atrial contractions: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12209856/", "date": "2025-04-15", "written_by": "independent", "quote": "To the best of our knowledge, this is the first reported case of PAC-related AiCM initially detected by a wearable device." } ], "replication": { "produced_by": [ "An asymptomatic wearer whose smartwatch flagged arrhythmias and who took the flag to a physician", "A primary care ECG followed by cardiology work-up including echocardiography, MRI and Holter monitoring", "An electrophysiology service able to map and ablate a high-burden PAC focus" ], "must_hold": [ "The PAC burden is high enough to be caught by the watch and to cause the cardiomyopathy. The authors note case reports typically exceed 30%.", "The ventricular dysfunction is still reversible when the arrhythmia is eliminated" ], "echoes": [] }, "paired_incident": null, "headline": "Smartwatch alert uncovers PAC cardiomyopathy; LVEF 15% to 50%", "metric": "radiofrequency ablation restored LVEF to 50% at six months", "comparator": { "against": "the same patient's LVEF before the radiofrequency ablation that the smartwatch alert led to (a treatment effect, not a with-versus-without-device comparison)", "before": "15%", "after": "50%", "basis": "measured", "quote": "In our case, the ablation of the PACs not only eliminated symptoms but also led to a remarkable improvement in LVEF, from 15% to 50%.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12209856/" }, "later": { "status": "unknown", "date": null, "note": "Nothing after the six-month follow-up in the report was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12209856/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0286", "catalog_version": "1.0.0", "source_fingerprint": "7c943f9c0f73049a024007201fc0138f7afd85e5d845bff5d1ba5c8c911a557b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0286-source-0001", "AIBD-0286-source-0002", "AIBD-0286-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The watch's detection of “heart arrhythmias” is what sent an asymptomatic man to his doctor. Everything after (ECG, echo, MRI, mapping, ablation) was clinical. The report does not say what the watch flagged, whether a notification or an ECG reading, nor which algorithm. The device's contribution is therefore established only as the trigger." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The watch's detection of “heart arrhythmias” is what sent an asymptomatic man to his doctor. Everything after (ECG, echo, MRI, mapping, ablation) was clinical. The report does not say what the watch flagged, whether a notification or an ECG reading, nor which algorithm. The device's contribution is therefore established only as the trigger." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The alert started a chain that diagnosed a cardiomyopathy. The condition progressed to LVEF 15%. Ablation reversed it to LVEF 50% with resolution of symptoms. 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The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The alert started a chain that diagnosed a cardiomyopathy. The condition progressed to LVEF 15%. Ablation reversed it to LVEF 50% with resolution of symptoms. 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The authors are at the Department of Cardiology and Pneumology, University Medical Center Göttingen, Germany. It was published 15 April 2025. The event dates are not given. A 34-year-old man with no medical history consulted his primary care physician. His smartwatch had detected “heart arrhythmias” while he was asymptomatic. A 12-lead electrocardiogram (ECG) showed sinus rhythm with frequent premature atrial contractions (PACs). A cardiologist found a left ventricular ejection fraction of 35% with a dilated ventricle. Despite guideline-directed heart-failure therapy he returned months later with palpitations and chest pain. Cardiac magnetic resonance imaging (MRI) showed LVEF 15%. Coronary disease was excluded by computed tomography (CT) angiography. Holter recordings showed a PAC burden of 30–50%. High-density 3D mapping located the ectopic focus at the left inferior pulmonary vein. Radiofrequency ablation terminated the arrhythmia. At six months he was symptom-free with LVEF 50% and fewer than 1% PACs. Spironolactone was stopped. The authors call it the first reported PAC-related arrhythmia-induced cardiomyopathy initially detected by a wearable. The watch's brand, model and the form of its alert are not stated.", "replication": { "produced_by": [ "An asymptomatic wearer whose smartwatch flagged arrhythmias and who took the flag to a physician", "A primary care ECG followed by cardiology work-up including echocardiography, MRI and Holter monitoring", "An electrophysiology service able to map and ablate a high-burden PAC focus" ], "must_hold": [ "The PAC burden is high enough to be caught by the watch and to cause the cardiomyopathy. The authors note case reports typically exceed 30%.", "The ventricular dysfunction is still reversible when the arrhythmia is eliminated" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0128", "title": "KEA's QR-code facial recognition app exposes a woman trying to enter a Bengaluru CET hall on another candidate's forged admit card", "summary": "KEA's facial recognition app flagged a woman with a forged CET admit card in Bengaluru on 17 April 2025; she fled before writing the paper.", "date_observed": "2025-04-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Thursday 17 April 2025 a woman calling herself Tuba Fathima Jameel tried to enter the CET-2025 mathematics paper. The center was Silver Valley Public PU College in Malleswaram, Bengaluru. She had spent nearly an hour in the restroom. Her admit card carried her own pasted photograph and an altered name. It bore the hall ticket number and QR code of a genuine candidate, Tabu Naz. Staff scanned the code and captured her photo with the new Karnataka Examinations Authority (KEA) facial recognition app. It reported that she was not the candidate on record. She fled before the principal was told. KEA executive director H. Prasanna ordered a report with video footage and said legal action would follow.", "category": "harm prevented", "unexpected": false, "purpose": "KEA built the app to verify candidates at the hall entrance and prevent impersonation. It scans the admit card's QR code and matches a live photograph against the photo submitted at registration. Exposing this impersonator was exactly that purpose.", "system": "Karnataka Examinations Authority QR code-based facial recognition app (CET-2025 candidate verification)", "model_version": null, "developer": "Karnataka Examinations Authority (The Hindu and ETV Bharat: 'developed by KEA'; no vendor named)", "deployer": "Karnataka Examinations Authority", "location": "Bengaluru, India", "domain": "Education (state entrance examinations)", "segment": "Public sector examination administration", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-04-14-e47b" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "KEA stopped a forged-entry attempt in the app's first state-wide run. The Hindu reports that all verifications ran without technical glitches on the second day. The benefit to the authority is a working integrity control across 3,30,808 registrants, demonstrated on one case." }, { "group": "societal", "depth": 1, "reason": "Genuine CET-2025 candidates: one person who was not the candidate on record was kept out of a competition for seats among 3.3 lakh registrants. It is a small benefit spread across the cohort. The sources do not say what she meant to gain." } ], "ai_role": { "status": "assessed", "statement": "The app did the detecting. Staff scanned the admit card's QR code and captured the woman's photo. It flagged a mismatch with the photo on record (New Indian Express). It “revealed that she was not the genuine candidate” (The Hindu). The Hindu and the Times of India both report the forged card's contents. It carried her own photograph with the genuine candidate's hall ticket number and QR code. Comparing the card with her face would therefore not have exposed her. The flag depended on the app's match against the registered photograph. Staff then acted, but she fled before the principal was told. No arrest or sanction is attributable to the system. KEA's probe and the promised legal action were still pending in every report." }, "evidence": [ { "kind": "news report", "citation": "The Hindu Bureau (2025). CET: Impersonator caught using facial recognition app, probe ordered. The Hindu, Bengaluru, 17 April 2025.", "title": "CET: Impersonator caught using facial recognition app, probe ordered", "url": "https://www.thehindu.com/news/cities/bangalore/cet-impersonator-caught-using-facial-recognition-app-probe-ordered/article69461334.ece", "date": "2025-04-17", "written_by": "independent", "quote": "when her photo was captured and verified through the facial recognition app, it revealed that she was not the genuine candidate" }, { "kind": "news report", "citation": "The Times of India (2025). Facial recognition app foils impersonation attempt at Bengaluru CET centre. The Times of India, Bengaluru, 17 April 2025.", "title": "Facial recognition app foils impersonation attempt at Bengaluru CET centre", "url": "https://timesofindia.indiatimes.com/city/bengaluru/cet-facial-recognition-app-nails-fake-candidate-in-bengaluru/articleshow/120388988.cms", "date": "2025-04-17", "written_by": "independent", "quote": "She had changed the original candidate's name but retained the hall ticket number and QR code." }, { "kind": "news report", "citation": "Express News Service (2025). QR code facial recognition app exposes impersonator in Bengaluru. The New Indian Express, 18 April 2025.", "title": "QR code facial recognition app exposes impersonator in Bengaluru", "url": "https://www.newindianexpress.com/cities/bengaluru/2025/Apr/18/qr-code-facial-recognition-app-exposes-impersonator-in-bengaluru", "date": "2025-04-18", "written_by": "independent", "quote": "the facial recognition app flagged a mismatch between her face and the photo on record, revealing she was not the actual candidate" }, { "kind": "news report", "citation": "ETV Bharat (2025). Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On. ETV Bharat, 18 April 2025.", "title": "Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On", "url": "https://www.etvbharat.com/en/!state/karnataka-examination-authoritys-new-facial-recognition-system-helps-identify-a-proxy-candidate-investigation-underway-enn25041801048", "date": "2025-04-18", "written_by": "independent", "quote": "designed to detect impersonation by matching real-time photographs of candidates with those submitted at the time of registration" }, { "kind": "news report", "citation": "The Times of India (2025). Karnataka Common Entrance Test set to begin with new security norms for candidates. The Times of India, Bengaluru, 14 April 2025.", "title": "Karnataka Common Entrance Test set to begin with new security norms for candidates", "url": "https://timesofindia.indiatimes.com/city/bengaluru/karnataka-common-entrance-test-set-to-begin-with-new-security-norms-for-candidates/articleshow/120288622.cms", "date": "2025-04-14", "written_by": "independent", "quote": "This was piloted in a few centres earlier and will be in force across all centres this time round." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2025-04-14-e47b", "title": "Facial recognition app exposes exam impersonator during Karnataka CET", "url": "https://oecd.ai/en/incidents/2025-04-14-e47b", "date": "2025-04-14", "written_by": "independent", "quote": "The system flagged a mismatch when Tuba Fatima Jameel attempted to impersonate another student, thwarting her fraud and prompting a probe." }, { "kind": "news report", "citation": "ETV Bharat (2026). Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24. ETV Bharat, 22 April 2026.", "title": "Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24", "url": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "date": "2026-04-22", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Admit cards printed with a QR code that resolves to the candidate's registered record and photograph. A photo pasted over the card therefore does not change what the app compares against.", "A live photograph taken at the hall door and matched by the app against the registered photo before entry. This ran at every center rather than the earlier pilot subset.", "Center staff instructed to act on a mismatch and escalate to the principal and KEA. Video coverage of the entrance that KEA could call for afterwards." ], "must_hold": [ "The registered photograph must be of the genuine candidate. The control fails if the fraud is committed at registration rather than at the door.", "Verification must be completed before the candidate is admitted. This depends on staffing and app reliability at scale. KEA reported no glitches this time.", "A flagged person must be detained or identified on the spot. Here she fled, so the deterrent rests on the probe and the video footage rather than on an arrest." ], "echoes": [] }, "paired_incident": null, "headline": "KEA's facial recognition app exposes a forged CET admit card", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-04-22", "note": "A year later KEA announced that facial recognition and QR-code verification would again be done for every candidate at K-CET 2026 on 23-24 April 2026.", "quote": "In order to avoid impersonation of candidates, facial recognition and QR code verification will be done for every candidate.", "url": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented, as the classifier proposed: the harm was specific (entry to the mathematics paper under a genuine candidate's hall ticket number) and the supporting evidence is that the forged card carried the impersonator's own photograph, so the app's match against the registered photo, not a visual check, produced the flag, and she left without writing the paper. Every account traces to a statement by KEA executive director H. Prasanna; KEA both built and ran the app, and no police record, court filing or outcome of the promised legal action was found. The Hindu says the catch came on the app's second day, the Times of India on its third (counting the Kannada paper of 15 April). Dated to the attempt, Thursday 17 April 2025; the Monitor's ID date (14 April) is the Times of India preview of the new security norms. The Monitor spells the name “Tuba Fatima Jameel” after ETV Bharat; The Hindu, the Times of India and the New Indian Express print “Tuba Fathima Jameel”, and the genuine candidate appears as “Tabu Naz” (Hindu, TOI, NIE) and “Tabu Naaz” (ETV). Udayavani's page sat behind a bot check and was not read.", "source": "https://oecd.ai/en/incidents/2025-04-14-e47b", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (1 sources and the registry id carried over); the duplicate was removed.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0128", "catalog_version": "1.0.0", "source_fingerprint": "130ac3437aa9f0f7724f683c02021f8757b8e3ec53ac7f5901d17585acecdfdb", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0128-source-0001", "AIBD-0128-source-0002", "AIBD-0128-source-0003", "AIBD-0128-source-0004", "AIBD-0128-source-0005", "AIBD-0128-source-0006", "AIBD-0128-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Karnataka Examinations Authority (The Hindu and ETV Bharat: 'developed by KEA'; no vendor named)", "deployer": "Karnataka Examinations Authority" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The app did the detecting. Staff scanned the admit card's QR code and captured the woman's photo. It flagged a mismatch with the photo on record (New Indian Express). It “revealed that she was not the genuine candidate” (The Hindu). The Hindu and the Times of India both report the forged card's contents. It carried her own photograph with the genuine candidate's hall ticket number and QR code. Comparing the card with her face would therefore not have exposed her. The flag depended on the app's match against the registered photograph. Staff then acted, but she fled before the principal was told. No arrest or sanction is attributable to the system. KEA's probe and the promised legal action were still pending in every report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The examination app compared a captured photograph with the registered candidate’s photograph and flagged a mismatch. Comparing the person only with the forged admit card would not have exposed the substitution.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The app did the detecting. Staff scanned the admit card's QR code and captured the woman's photo. It flagged a mismatch with the photo on record (New Indian Express). It “revealed that she was not the genuine candidate” (The Hindu). The Hindu and the Times of India both report the forged card's contents. It carried her own photograph with the genuine candidate's hall ticket number and QR code. Comparing the card with her face would therefore not have exposed her. The flag depended on the app's match against the registered photograph. Staff then acted, but she fled before the principal was told. No arrest or sanction is attributable to the system. KEA's probe and the promised legal action were still pending in every report." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "KEA stopped a forged-entry attempt in the app's first state-wide run. The Hindu reports that all verifications ran without technical glitches on the second day. The benefit to the authority is a working integrity control across 3,30,808 registrants, demonstrated on one case." }, { "group": "societal", "depth": 1, "reason": "Genuine CET-2025 candidates: one person who was not the candidate on record was kept out of a competition for seats among 3.3 lakh registrants. It is a small benefit spread across the cohort. The sources do not say what she meant to gain." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "KEA stopped a forged-entry attempt in the app's first state-wide run. The Hindu reports that all verifications ran without technical glitches on the second day. The benefit to the authority is a working integrity control across 3,30,808 registrants, demonstrated on one case." }, { "group": "societal", "depth": 1, "reason": "Genuine CET-2025 candidates: one person who was not the candidate on record was kept out of a competition for seats among 3.3 lakh registrants. It is a small benefit spread across the cohort. The sources do not say what she meant to gain." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "KEA stopped a forged-entry attempt in the app's first state-wide run. The Hindu reports that all verifications ran without technical glitches on the second day. The benefit to the authority is a working integrity control across 3,30,808 registrants, demonstrated on one case." }, { "group": "societal", "depth": 1, "reason": "Genuine CET-2025 candidates: one person who was not the candidate on record was kept out of a competition for seats among 3.3 lakh registrants. It is a small benefit spread across the cohort. The sources do not say what she meant to gain." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The person left before the principal was informed. The reports describe a pending investigation and do not establish an arrest or sanction.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-04-14-e47b" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-04-22", "note": "A year later KEA announced that facial recognition and QR-code verification would again be done for every candidate at K-CET 2026 on 23-24 April 2026.", "quote": "In order to avoid impersonation of candidates, facial recognition and QR code verification will be done for every candidate.", "url": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Examination staff scanned the admit card, captured the photograph, and acted on the mismatch." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0128" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Thursday 17 April 2025 a woman calling herself Tuba Fathima Jameel tried to enter the CET-2025 mathematics paper. The center was Silver Valley Public PU College in Malleswaram, Bengaluru. She had spent nearly an hour in the restroom. Her admit card carried her own pasted photograph and an altered name. It bore the hall ticket number and QR code of a genuine candidate, Tabu Naz. Staff scanned the code and captured her photo with the new Karnataka Examinations Authority (KEA) facial recognition app. It reported that she was not the candidate on record. She fled before the principal was told. KEA executive director H. Prasanna ordered a report with video footage and said legal action would follow.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "KEA stopped a forged-entry attempt in the app's first state-wide run. The Hindu reports that all verifications ran without technical glitches on the second day. The benefit to the authority is a working integrity control across 3,30,808 registrants, demonstrated on one case." }, { "group": "societal", "depth": 1, "reason": "Genuine CET-2025 candidates: one person who was not the candidate on record was kept out of a competition for seats among 3.3 lakh registrants. It is a small benefit spread across the cohort. The sources do not say what she meant to gain." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "KEA built the app to verify candidates at the hall entrance and prevent impersonation. It scans the admit card's QR code and matches a live photograph against the photo submitted at registration. Exposing this impersonator was exactly that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Bengaluru, India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "KEA built the app to verify candidates at the hall entrance and prevent impersonation. It scans the admit card's QR code and matches a live photograph against the photo submitted at registration. Exposing this impersonator was exactly that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-04-17", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented, as the classifier proposed: the harm was specific (entry to the mathematics paper under a genuine candidate's hall ticket number) and the supporting evidence is that the forged card carried the impersonator's own photograph, so the app's match against the registered photo, not a visual check, produced the flag, and she left without writing the paper. Every account traces to a statement by KEA executive director H. Prasanna; KEA both built and ran the app, and no police record, court filing or outcome of the promised legal action was found. The Hindu says the catch came on the app's second day, the Times of India on its third (counting the Kannada paper of 15 April). Dated to the attempt, Thursday 17 April 2025; the Monitor's ID date (14 April) is the Times of India preview of the new security norms. The Monitor spells the name “Tuba Fatima Jameel” after ETV Bharat; The Hindu, the Times of India and the New Indian Express print “Tuba Fathima Jameel”, and the genuine candidate appears as “Tabu Naz” (Hindu, TOI, NIE) and “Tabu Naaz” (ETV). Udayavani's page sat behind a bot check and was not read.", "source": "https://oecd.ai/en/incidents/2025-04-14-e47b", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (1 sources and the registry id carried over); the duplicate was removed.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Admit cards printed with a QR code that resolves to the candidate's registered record and photograph. A photo pasted over the card therefore does not change what the app compares against.", "A live photograph taken at the hall door and matched by the app against the registered photo before entry. This ran at every center rather than the earlier pilot subset.", "Center staff instructed to act on a mismatch and escalate to the principal and KEA. Video coverage of the entrance that KEA could call for afterwards." ], "must_hold": [ "The registered photograph must be of the genuine candidate. The control fails if the fraud is committed at registration rather than at the door.", "Verification must be completed before the candidate is admitted. This depends on staffing and app reliability at scale. KEA reported no glitches this time.", "A flagged person must be detained or identified on the spot. Here she fled, so the deterrent rests on the probe and the video footage rather than on an arrest." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented, as the classifier proposed: the harm was specific (entry to the mathematics paper under a genuine candidate's hall ticket number) and the supporting evidence is that the forged card carried the impersonator's own photograph, so the app's match against the registered photo, not a visual check, produced the flag, and she left without writing the paper. Every account traces to a statement by KEA executive director H. Prasanna; KEA both built and ran the app, and no police record, court filing or outcome of the promised legal action was found. The Hindu says the catch came on the app's second day, the Times of India on its third (counting the Kannada paper of 15 April). Dated to the attempt, Thursday 17 April 2025; the Monitor's ID date (14 April) is the Times of India preview of the new security norms. The Monitor spells the name “Tuba Fatima Jameel” after ETV Bharat; The Hindu, the Times of India and the New Indian Express print “Tuba Fathima Jameel”, and the genuine candidate appears as “Tabu Naz” (Hindu, TOI, NIE) and “Tabu Naaz” (ETV). Udayavani's page sat behind a bot check and was not read.", "source": "https://oecd.ai/en/incidents/2025-04-14-e47b", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (1 sources and the registry id carried over); the duplicate was removed.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Education (state entrance examinations)", "segment": "Public sector examination administration" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Hindu Bureau (2025). CET: Impersonator caught using facial recognition app, probe ordered. The Hindu, Bengaluru, 17 April 2025.", "title": "CET: Impersonator caught using facial recognition app, probe ordered", "url": "https://www.thehindu.com/news/cities/bangalore/cet-impersonator-caught-using-facial-recognition-app-probe-ordered/article69461334.ece", "date": "2025-04-17", "written_by": "independent", "quote": "when her photo was captured and verified through the facial recognition app, it revealed that she was not the genuine candidate" }, { "kind": "news report", "citation": "The Times of India (2025). Facial recognition app foils impersonation attempt at Bengaluru CET centre. The Times of India, Bengaluru, 17 April 2025.", "title": "Facial recognition app foils impersonation attempt at Bengaluru CET centre", "url": "https://timesofindia.indiatimes.com/city/bengaluru/cet-facial-recognition-app-nails-fake-candidate-in-bengaluru/articleshow/120388988.cms", "date": "2025-04-17", "written_by": "independent", "quote": "She had changed the original candidate's name but retained the hall ticket number and QR code." }, { "kind": "news report", "citation": "Express News Service (2025). QR code facial recognition app exposes impersonator in Bengaluru. The New Indian Express, 18 April 2025.", "title": "QR code facial recognition app exposes impersonator in Bengaluru", "url": "https://www.newindianexpress.com/cities/bengaluru/2025/Apr/18/qr-code-facial-recognition-app-exposes-impersonator-in-bengaluru", "date": "2025-04-18", "written_by": "independent", "quote": "the facial recognition app flagged a mismatch between her face and the photo on record, revealing she was not the actual candidate" }, { "kind": "news report", "citation": "ETV Bharat (2025). Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On. ETV Bharat, 18 April 2025.", "title": "Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On", "url": "https://www.etvbharat.com/en/!state/karnataka-examination-authoritys-new-facial-recognition-system-helps-identify-a-proxy-candidate-investigation-underway-enn25041801048", "date": "2025-04-18", "written_by": "independent", "quote": "designed to detect impersonation by matching real-time photographs of candidates with those submitted at the time of registration" }, { "kind": "news report", "citation": "The Times of India (2025). Karnataka Common Entrance Test set to begin with new security norms for candidates. The Times of India, Bengaluru, 14 April 2025.", "title": "Karnataka Common Entrance Test set to begin with new security norms for candidates", "url": "https://timesofindia.indiatimes.com/city/bengaluru/karnataka-common-entrance-test-set-to-begin-with-new-security-norms-for-candidates/articleshow/120288622.cms", "date": "2025-04-14", "written_by": "independent", "quote": "This was piloted in a few centres earlier and will be in force across all centres this time round." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2025-04-14-e47b", "title": "Facial recognition app exposes exam impersonator during Karnataka CET", "url": "https://oecd.ai/en/incidents/2025-04-14-e47b", "date": "2025-04-14", "written_by": "independent", "quote": "The system flagged a mismatch when Tuba Fatima Jameel attempted to impersonate another student, thwarting her fraud and prompting a probe." }, { "kind": "news report", "citation": "ETV Bharat (2026). Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24. ETV Bharat, 22 April 2026.", "title": "Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24", "url": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "date": "2026-04-22", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0128-source-0001", "AIBD-0128-source-0002", "AIBD-0128-source-0003", "AIBD-0128-source-0004", "AIBD-0128-source-0005", "AIBD-0128-source-0006", "AIBD-0128-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The Hindu Bureau (2025). CET: Impersonator caught using facial recognition app, probe ordered. The Hindu, Bengaluru, 17 April 2025.", "title": "CET: Impersonator caught using facial recognition app, probe ordered", "url": "https://www.thehindu.com/news/cities/bangalore/cet-impersonator-caught-using-facial-recognition-app-probe-ordered/article69461334.ece", "date": "2025-04-17", "written_by": "independent", "quote": "when her photo was captured and verified through the facial recognition app, it revealed that she was not the genuine candidate" }, { "kind": "news report", "citation": "The Times of India (2025). Facial recognition app foils impersonation attempt at Bengaluru CET centre. The Times of India, Bengaluru, 17 April 2025.", "title": "Facial recognition app foils impersonation attempt at Bengaluru CET centre", "url": "https://timesofindia.indiatimes.com/city/bengaluru/cet-facial-recognition-app-nails-fake-candidate-in-bengaluru/articleshow/120388988.cms", "date": "2025-04-17", "written_by": "independent", "quote": "She had changed the original candidate's name but retained the hall ticket number and QR code." }, { "kind": "news report", "citation": "Express News Service (2025). QR code facial recognition app exposes impersonator in Bengaluru. The New Indian Express, 18 April 2025.", "title": "QR code facial recognition app exposes impersonator in Bengaluru", "url": "https://www.newindianexpress.com/cities/bengaluru/2025/Apr/18/qr-code-facial-recognition-app-exposes-impersonator-in-bengaluru", "date": "2025-04-18", "written_by": "independent", "quote": "the facial recognition app flagged a mismatch between her face and the photo on record, revealing she was not the actual candidate" }, { "kind": "news report", "citation": "ETV Bharat (2025). Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On. ETV Bharat, 18 April 2025.", "title": "Proxy CET Examinee Caught Red-Handed In Karnataka, Investigation On", "url": "https://www.etvbharat.com/en/!state/karnataka-examination-authoritys-new-facial-recognition-system-helps-identify-a-proxy-candidate-investigation-underway-enn25041801048", "date": "2025-04-18", "written_by": "independent", "quote": "designed to detect impersonation by matching real-time photographs of candidates with those submitted at the time of registration" }, { "kind": "news report", "citation": "The Times of India (2025). Karnataka Common Entrance Test set to begin with new security norms for candidates. The Times of India, Bengaluru, 14 April 2025.", "title": "Karnataka Common Entrance Test set to begin with new security norms for candidates", "url": "https://timesofindia.indiatimes.com/city/bengaluru/karnataka-common-entrance-test-set-to-begin-with-new-security-norms-for-candidates/articleshow/120288622.cms", "date": "2025-04-14", "written_by": "independent", "quote": "This was piloted in a few centres earlier and will be in force across all centres this time round." }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, incident 2025-04-14-e47b", "title": "Facial recognition app exposes exam impersonator during Karnataka CET", "url": "https://oecd.ai/en/incidents/2025-04-14-e47b", "date": "2025-04-14", "written_by": "independent", "quote": "The system flagged a mismatch when Tuba Fatima Jameel attempted to impersonate another student, thwarting her fraud and prompting a probe." }, { "kind": "news report", "citation": "ETV Bharat (2026). Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24. ETV Bharat, 22 April 2026.", "title": "Karnataka Examination Authority All Set To Conduct K-CET On April 23, 24", "url": "https://www.etvbharat.com/en/state/karnataka-education-authority-to-conduct-k-cet-on-april-23-and-24-enn26042204512", "date": "2026-04-22", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "KEA's facial recognition app flagged a woman with a forged CET admit card in Bengaluru on 17 April 2025; she fled before writing the paper.", "account": "On Thursday 17 April 2025 a woman calling herself Tuba Fathima Jameel tried to enter the CET-2025 mathematics paper. The center was Silver Valley Public PU College in Malleswaram, Bengaluru. She had spent nearly an hour in the restroom. Her admit card carried her own pasted photograph and an altered name. It bore the hall ticket number and QR code of a genuine candidate, Tabu Naz. Staff scanned the code and captured her photo with the new Karnataka Examinations Authority (KEA) facial recognition app. It reported that she was not the candidate on record. She fled before the principal was told. KEA executive director H. Prasanna ordered a report with video footage and said legal action would follow." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Karnataka Examinations Authority QR code-based facial recognition app (CET-2025 candidate verification)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Karnataka Examinations Authority (The Hindu and ETV Bharat: 'developed by KEA'; no vendor named)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "KEA's QR-code facial recognition app exposes a woman trying to enter a Bengaluru CET hall on another candidate's forged admit card", "headline": "KEA's facial recognition app exposes a forged CET admit card" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "130ac3437aa9f0f7724f683c02021f8757b8e3ec53ac7f5901d17585acecdfdb" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Thursday 17 April 2025 a woman calling herself Tuba Fathima Jameel tried to enter the CET-2025 mathematics paper. The center was Silver Valley Public PU College in Malleswaram, Bengaluru. She had spent nearly an hour in the restroom. Her admit card carried her own pasted photograph and an altered name. It bore the hall ticket number and QR code of a genuine candidate, Tabu Naz. Staff scanned the code and captured her photo with the new Karnataka Examinations Authority (KEA) facial recognition app. It reported that she was not the candidate on record. She fled before the principal was told. KEA executive director H. Prasanna ordered a report with video footage and said legal action would follow.", "replication": { "produced_by": [ "Admit cards printed with a QR code that resolves to the candidate's registered record and photograph. A photo pasted over the card therefore does not change what the app compares against.", "A live photograph taken at the hall door and matched by the app against the registered photo before entry. This ran at every center rather than the earlier pilot subset.", "Center staff instructed to act on a mismatch and escalate to the principal and KEA. Video coverage of the entrance that KEA could call for afterwards." ], "must_hold": [ "The registered photograph must be of the genuine candidate. The control fails if the fraud is committed at registration rather than at the door.", "Verification must be completed before the candidate is admitted. This depends on staffing and app reliability at scale. KEA reported no glitches this time.", "A flagged person must be detained or identified on the spot. Here she fled, so the deterrent rests on the probe and the video footage rather than on an arrest." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0583", "title": "MegaDetector reduces the images that snake researchers review, with substantial detection losses", "summary": "MegaDetector removed 94% of images from manual review in a Florida study, but the hybrid workflow detected fewer snake events overall.", "date_observed": "2025-04-20", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Miller and colleagues evaluated MegaDetector 5A on 1,485,924 time-lapse images from 42 cameras at three South Florida sites. At a detection threshold of 0.05, 88,863 images remained for human review, a reported 94.0% reduction. Manual review took 265 hours. Computer processing took 27.7 hours, and the authors estimated a 43.5-hour hybrid workflow by adding human review time calculated from the manual review rate. About 16 hours of that total represent estimated human review, not separately timed hybrid labor. MegaDetector located animals; people assigned snake species in Timelapse2. The hybrid method found 217 independent snake events, compared with 378 manually and 447 across both methods. Snake-image recall was 17.1% for the hybrid method and 96.2% manually. Results differed by species: the hybrid method found five of six Burmese-python events and more North American racer events than manual review. Neither method found every event. The study documents reduced review work with detection losses. It does not document a management decision, population improvement, or net financial saving.", "category": "general benefit", "unexpected": false, "purpose": "MegaDetector locates animals, people, and vehicles in camera images. This study tested whether filtering images could reduce the work required to monitor cryptic snakes.", "system": "MegaDetector with Timelapse2", "model_version": "MegaDetector 5A", "developer": "MegaDetector contributors", "deployer": "University of Florida, South Florida Water Management District, and U.S. Geological Survey researchers", "location": "Miami-Dade County, Florida, United States", "domain": "Environment and conservation", "segment": "Camera-based snake monitoring", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The supported benefit is reduced image-review work. Detection quality and conservation effects are assessed separately.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Researchers reviewed fewer images, and the study estimated a shorter workflow. Detection losses limit which monitoring tasks can use it." }, { "group": "societal", "depth": null, "reason": "The study does not establish a conservation intervention or wildlife outcome." } ], "ai_role": { "status": "assessed", "statement": "MegaDetector filtered images by detecting animals. People identified species. The same image set and reviewer supported a comparison, but hybrid human review time was estimated and overall detection was lower." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Miller S, Kirkland M, Hart KM, McCleery RA. Object detection-assisted workflow facilitates cryptic snake monitoring. Remote Sensing in Ecology and Conservation 11(5):606-617. First published April 20, 2025. doi:10.1002/rse2.70009.", "title": "Object detection-assisted workflow facilitates cryptic snake monitoring", "url": "https://doi.org/10.1002/rse2.70009", "date": "2025-04-20", "written_by": "independent", "quote": null }, { "kind": "other", "citation": "MegaDetector contributors. MegaDetector User Guide. Repository version at commit 51270ebad6131b9f2eb7b200ecc706ab616d698c, February 27, 2025.", "title": "MegaDetector User Guide", "url": "https://github.com/agentmorris/MegaDetector/blob/51270ebad6131b9f2eb7b200ecc706ab616d698c/megadetector.md", "date": "2025-02-27", "written_by": "makers", "quote": null, "supports_benefit": false } ], "replication": { "produced_by": [ "Time-lapse images from 42 cameras collected from June 20 through July 18, 2022.", "Unadapted MegaDetector 5A at a 0.05 threshold, running on an Nvidia A100 GPU on UF HiPerGator.", "Human species identification in Timelapse2 and a comparison with manual review of the same images." ], "must_hold": [ "The chosen threshold must retain the species and events that matter to the research question.", "Available computing and expert review must be included when comparing workflow time and cost.", "Images, labels, outputs, and timing records must be available to reproduce the comparison." ], "echoes": [] }, "paired_incident": null, "headline": "Snake researchers review fewer images with MegaDetector", "metric": "94.0% fewer images for human review", "comparator": { "against": "Manual review of the same time-lapse image dataset.", "before": "265 hours of measured manual review; 378 independent snake detections.", "after": "43.5 hours estimated for the hybrid workflow, including 27.7 hours of measured compute; 217 independent snake detections.", "basis": "assumed", "quote": "it took 43.5 h to classify all images with ~64% of the total time spent computer processing", "url": "https://doi.org/10.1002/rse2.70009" }, "later": { "status": "unknown", "date": null, "note": "Subsequent operational adoption, model corrections, and conservation decisions have not been established by this source review.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-25", "change": "Added the original comparative study, its methods and limitations, source lineage, and unresolved follow-up questions.", "source": "https://doi.org/10.1002/rse2.70009", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent peer-reviewed study and the makers' other. For the benefit itself, the cited sources include no finding by a regulator or court.", "profile": { "case_id": "AIBD-0583", "catalog_version": "1.0.0", "source_fingerprint": "df395c17d053ec2235382a07fa14f659352291fff391bfad9ac3f91669b2dd50", "collection_refs": [ { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0583-evaluation-miller-2025" ], "role": "evaluations" }, "provenance": { "kind": "source_review", "basis": "Reviewed the original comparative study.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "record_ids": [ "AIBD-0583-evaluation-miller-2025" ] }, "monetary observations": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original comparative study.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not report a monetary benefit or net-cost estimate.", "review_state": "reviewed", "coverage": "complete", "record_ids": [] }, "institutional decisions": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original comparative study.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not document a subsequent institutional or conservation-management decision.", "review_state": "reviewed", "coverage": "complete", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "University of Florida, South Florida Water Management District, and U.S. Geological Survey researchers evaluated the workflow. Dan Morris is acknowledged for technical advice and is not a study author." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector filtered images by detecting animals. People identified species. The same image set and reviewer supported a comparison, but hybrid human review time was estimated and overall detection was lower." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "ai_relationship": { "state": "value_present", "value": { "kind": "text", "text": "AI was part of the measured image-filtering workflow. Human review supplied species labels and the comparison data." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].alternatives": { "state": "value_present", "value": { "kind": "text", "text": "Manual review detects more snake events overall. A hybrid workflow may suit particular large species, while a broader inventory may require more human review." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].assessor_date": { "state": "value_present", "value": { "kind": "structured", "data": { "assessor": "AIBD", "reviewed_on": "2026-10-25" } }, "provenance": { "kind": "curatorial", "basis": "Recorded this source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD reviewed this assessment on October 25, 2026." } }, "assessments[].depth": { "state": "value_present", "value": { "kind": "structured", "data": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Researchers reviewed fewer images, and the study estimated a shorter workflow. Detection losses limit which monitoring tasks can use it." }, { "group": "societal", "reason": "The study does not establish a conservation intervention or wildlife outcome." } ] } }, "provenance": { "kind": "curatorial", "basis": "Applied the existing AIBD depth scale to the stated research benefit.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Organizational depth 1: reduced review work. Societal depth is unassessed because a conservation outcome is not documented." } }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent peer-reviewed study and the makers' other. For the benefit itself, the cited sources include no finding by a regulator or court.", "interpretation": "The existing display rule reflects source authorship and kind. The detailed fields preserve methodological qualifications." } }, "provenance": { "kind": "derivation", "basis": "Applied the existing display rule to the reviewed evidence.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Independently studied, with developer technical advice acknowledged and the timing estimate qualified." } }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "text", "text": "Researchers reviewed fewer images, and the study estimated a shorter workflow. Detection losses limit which monitoring tasks can use it. The study does not establish a conservation intervention or wildlife outcome." }, "provenance": { "kind": "curatorial", "basis": "Separated organizational benefit from unmeasured societal effects.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].rubric_version": { "state": "value_present", "value": { "kind": "text", "text": "AIBD depth scale and the Trustible benefit taxonomy in the current local catalog, reviewed October 25, 2026." }, "provenance": { "kind": "curatorial", "basis": "Applied the existing repository method and taxonomy without modifying them.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "The record distinguishes demonstrated analytical results from estimated or unmeasured downstream benefits." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "assessments[].target": { "state": "value_present", "value": { "kind": "text", "text": "The documented research benefit for the participating organizations." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "availability": { "state": "value_present", "value": { "kind": "text", "text": "The study and versioned model guide are public. The underlying study data are available on request." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "value_present", "value": { "kind": "text", "text": "Comparative research study." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "related_cases": [ "AIBD-0584" ], "relationship": "Separate comparative wildlife studies that use MegaDetector. They do not replicate the same outcome." } }, "provenance": { "kind": "curatorial", "basis": "Linked related research without combining study populations or results.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The other new conservation record concerns a separate evaluation that also uses MegaDetector. It is not a replication of this result." } }, "claims[].evidence_links": { "state": "value_present", "value": { "kind": "structured", "data": { "benefit_source_refs": [ "AIBD-0583-source-0001" ], "methods_source_refs": [ "AIBD-0583-source-0002" ] } }, "provenance": { "kind": "source_review", "basis": "The lead study supplies the comparative result; additional materials supply methods or reproducibility information.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original study supports the comparative result. The second source adds methods or reproducibility information." } }, "claims[].evidence_strength": { "state": "value_present", "value": { "kind": "text", "text": "An original comparative field-data study supports reduced review work and documents detection losses. The hybrid human-time component is estimated, and the study does not independently measure financial or conservation outcomes." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "claims[].missingness": { "state": "value_present", "value": { "kind": "text", "text": "Actual hybrid review logs, complete workflow costs, subsequent adoption, and conservation decisions remain unresolved. Study data require a request to the authors." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector removed 94% of images from manual review in a Florida study, but the hybrid workflow detected fewer snake events overall." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "cross_border_flows[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original study and its stated data availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "Specific cross-border transfers of study data or model outputs are not documented in the reviewed sources.", "review_state": "reviewed", "coverage": "complete" }, "decisions[].action_outcome": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "institutional decisions" }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "Research evaluation using field-collected camera images." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "economics[].amount": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].realization": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_reported", "review_state": "reviewed", "coverage": "complete", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "AI directly reduced the image set that people reviewed. The time comparison combines measured compute with estimated human review and does not hold detection quality constant." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "Manual review of the same time-lapse image dataset." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Comparison of manual and AI-assisted review of the same image dataset, using the same reviewer. The paper does not report a randomized or blinded workflow comparison." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "At threshold 0.05, the hybrid workflow left 88,863 images for human review and had an estimated total duration of 43.5 hours. It found 217 independent events compared with 378 manually." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].exposure": { "state": "value_present", "value": { "kind": "text", "text": "The image-review denominator is 1,485,924 images. Detection metrics use the subset remaining after humans, vehicles, and other animals were removed. Combined independent snake events number 447." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0583-evaluation-miller-2025" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "The authors timed manual review and computer processing, estimated hybrid human review from the baseline review rate, and compared detections after combining findings from both methods." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "structured", "data": { "images_total": 1485924, "images_for_hybrid_review": 88863, "reported_reduction_percent": 94.0, "manual_hours_measured": 265, "computer_hours_measured": 27.7, "hybrid_total_hours_estimated": 43.5, "hybrid_human_hours_estimated_approx": 16, "independent_events_manual": 378, "independent_events_hybrid": 217, "independent_events_combined": 447, "snake_image_recall_manual_percent": 96.2, "snake_image_recall_hybrid_percent": 17.1 } }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Of 1,485,924 images, 88,863 remained for human review. Manual review took 265 hours; the hybrid workflow was estimated at 43.5 hours. Hybrid and manual review found 217 and 378 independent snake events, respectively." } }, "evaluations[].reproduction_materials": { "state": "value_present", "value": { "kind": "text", "text": "The paper states that the study data are available on request. No public study dataset, analysis-code archive, or supplement is linked. Those unpublished materials were not inspected." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "42 cameras at three South Florida sites produced 1,485,924 images between June 20 and July 18, 2022." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "Human review within the hybrid workflow was estimated. The same reviewer assessed both methods. Ground truth combined their findings and could miss snakes overlooked by both. Results depend on species size, camera conditions, hardware, and threshold. 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The record also links the versioned MegaDetector guide." } }, "follow_up[]": { "state": "not_assessed", "reason": "Post-study adoption and conservation decisions require follow-up.", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "A researcher or herpetologist identified species. The same reviewer supported both workflows, and the paper does not report randomization or blinding." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0583" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The study used 42 Reconyx HP2X cameras, UF HiPerGator, an Nvidia A100 GPU, MegaDetector 5A, Timelapse2, and expert human review." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "The research team that processed the South Florida snake images." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].beneficiary_count": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original study and its stated data availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not count people who benefited. Cameras, images, species, and detection events are study units.", "review_state": "reviewed", "coverage": "complete" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved Organizational Efficiency" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "Miller and colleagues evaluated MegaDetector 5A on 1,485,924 time-lapse images from 42 cameras at three South Florida sites. At a detection threshold of 0.05, 88,863 images remained for human review, a reported 94.0% reduction. Manual review took 265 hours. Computer processing took 27.7 hours, and the authors estimated a 43.5-hour hybrid workflow by adding human review time calculated from the manual review rate. About 16 hours of that total represent estimated human review, not separately timed hybrid labor. MegaDetector located animals; people assigned snake species in Timelapse2. The hybrid method found 217 independent snake events, compared with 378 manually and 447 across both methods. Snake-image recall was 17.1% for the hybrid method and 96.2% manually. Results differed by species: the hybrid method found five of six Burmese-python events and more North American racer events than manual review. Neither method found every event. The study documents reduced review work with detection losses. It does not document a management decision, population improvement, or net financial saving." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Performance differed across snake species and sizes. The hybrid workflow retained five of six Burmese-python events but missed the ring-necked-snake event that manual review found." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].duration": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original study and its stated data availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not establish how long the benefit persisted after the evaluation.", "review_state": "reviewed", "coverage": "complete" }, "outcomes[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0583-outcome-research" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Participating research organizations. Wider conservation benefits remain unmeasured." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Reported research result with explicit limitations." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Reduced image-review work came with fewer total snake detections. The hybrid workflow found some events that manual review missed, and neither method established complete ground truth." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "The result concerns the intended use of AI to support wildlife-image analysis." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "case_jurisdictions": [ "United States" ], "developer_jurisdictions": [], "study_places": [ "Three Miami-Dade County sites bordering Everglades National Park, Florida." ], "computing": "University of Florida HiPerGator." } }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Three sites in Miami-Dade County, Florida, United States. Processing used UF HiPerGator." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector locates animals, people, and vehicles in camera images. This study tested whether filtering images could reduce the work required to monitor cryptic snakes." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "image_collection": { "start": "2022-06-20", "end": "2022-07-18" }, "first_publication": "2025-04-20", "case_date": "2025-04-20", "case_date_basis": "Original study publication; the AI-analysis date is not reported.", "last_reviewed": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Images were collected from June 20 through July 18, 2022. The study was first published April 20, 2025. The AI-analysis completion date is not reported." } }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "The chosen threshold must retain the species and events that matter to the research question. Available computing and expert review must be included when comparing workflow time and cost. Images, labels, outputs, and timing records must be available to reproduce the comparison." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "revision_history[]": { "state": "value_present", "value": { "kind": "structured", "data": { "revisions": [ { "date": "2026-10-25", "change": "Added the original comparative study, its methods and limitations, source lineage, and unresolved follow-up questions.", "source": "https://doi.org/10.1002/rse2.70009", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Recorded the initial source review and addition.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The record and its source assessment were added on October 25, 2026." } }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Environment and conservation" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "article": "Version of record, first published April 20, 2025; October 2025 is the issue date.", "model_guide_commit": "51270ebad6131b9f2eb7b200ecc706ab616d698c", "model_guide_date": "2025-02-27", "unavailable": "The article provides data on request, without a public study archive. The author-lab PDF link returned 404; the original Wiley article was read." } }, "provenance": { "kind": "source_review", "basis": "Recorded the inspected versions and material access limits.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The original April 2025 study and February 27, 2025 model-guide version were inspected. Study data are available on request and were not inspected." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "source_ref": "AIBD-0583-source-0001", "citation": "Miller S, Kirkland M, Hart KM, McCleery RA. Object detection-assisted workflow facilitates cryptic snake monitoring. Remote Sensing in Ecology and Conservation 11(5):606-617. First published April 20, 2025. doi:10.1002/rse2.70009.", "url": "https://doi.org/10.1002/rse2.70009" }, { "source_ref": "AIBD-0583-source-0002", "citation": "MegaDetector contributors. MegaDetector User Guide. Repository version at commit 51270ebad6131b9f2eb7b200ecc706ab616d698c, February 27, 2025.", "url": "https://github.com/agentmorris/MegaDetector/blob/51270ebad6131b9f2eb7b200ecc706ab616d698c/megadetector.md" } ] } }, "provenance": { "kind": "source_review", "basis": "Preserved original publication details and stable links.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Miller et al., Methods, Tables 2-4, Discussion, and Data Availability. The versioned MegaDetector guide supplies model history and limitations." } }, "sources[].id": { "state": "value_present", "value": { "kind": "structured", "data": { "identifiers": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ] } }, "provenance": { "kind": "curatorial", "basis": "Assigned stable source references for the retained evidence.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two retained sources have stable identifiers beneath this record." } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "The retained sources are in English." }, "provenance": { "kind": "source_review", "basis": "Inspected the retained sources.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The study authors are researchers at UF, SFWMD, and USGS, with no model-developer author listed. Dan Morris supplied acknowledged technical advice. The guide is developer documentation and does not independently confirm the benefit." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0583-source-0001", "retained_source_order": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "origins": [ { "url": "https://doi.org/10.1002/rse2.70009", "source_refs": [ "AIBD-0583-source-0001" ], "display_name": "Remote Sensing in Ecology and Conservation", "contribution": "Original comparison, image counts, timing methods, detection results, and data-access statement.", "locator": "Methods; Results, Tables 2-4; Discussion; Acknowledgments; Data Availability.", "relationship": "Original evaluation by the research team. Dan Morris supplied technical advice but is not an author." }, { "url": "https://github.com/agentmorris/MegaDetector/blob/51270ebad6131b9f2eb7b200ecc706ab616d698c/megadetector.md", "source_refs": [ "AIBD-0583-source-0002" ], "display_name": "MegaDetector documentation", "contribution": "Versioned developer description of the model, YOLOv5 lineage, release history, and reptile limitations.", "locator": "MegaDetector overview; MegaDetector versions; What is MegaDetector bad at?", "relationship": "Developer documentation. It is not a second evaluation of the snake study." } ], "excluded_or_consolidated_sources": [ { "url": "https://pubs.usgs.gov/publication/70266494", "reason": "An institutional record of the same article, without a distinct evaluation." } ], "review_scope": "Original article and versioned model guide inspected. Raw study data and analysis code were not available for inspection." } }, "provenance": { "kind": "source_review", "basis": "Traced the benefit to the original study and limited the additional source to model methods.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study supplies the comparative results. The developer guide supplies model methods and does not independently confirm the benefit." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector removed 94% of images from manual review in a Florida study, but the hybrid workflow detected fewer snake events overall." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "The model filtered images for review. It did not identify snake species or initiate conservation action." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector detected animals. Timelapse2 supported human review and species identification." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Unadapted MegaDetector 5A ran on an Nvidia A100 GPU on UF HiPerGator. The reported comparison used a confidence threshold of 0.05." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Time-lapse photographs were the input. Detection scores and locations selected images for human species identification." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector, based on YOLOv5." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001", "AIBD-0583-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector 5A" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector with Timelapse2" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector contributors" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector reduces the images that snake researchers review, with substantial detection losses" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "version": { "state": "value_present", "value": { "kind": "structured", "data": { "fingerprint": "df395c17d053ec2235382a07fa14f659352291fff391bfad9ac3f91669b2dd50" } }, "provenance": { "kind": "derivation", "basis": "SHA-256 of the normalized record.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The record has a content fingerprint that changes when its source data change." } }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Researchers collected images, compared manual review with MegaDetector filtering followed by human review, and reconciled detections from both methods." }, "provenance": { "kind": "source_review", "basis": "Miller et al., Methods (Study design, Hybrid review, Efficiency), Results, Tables 2-4, Discussion, Acknowledgments, and Data Availability.", "record_fields": [], "source_refs": [ "AIBD-0583-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" } }, "summary": { "total": 91, "addressed": 91, "known": 67, "reviewed": 85, "record_mapped": 0, "not_assessed": 6, "complete": false, "by_state": { "value_present": 67, "not_reported": 18, "unresolved": 0, "not_assessed": 6, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0129", "title": "Taoyuan's AI sound cameras locate a white BMW that had been roaring down Jieshou Road at night, within a day of residents' complaint", "summary": "Taoyuan's AI sound cameras pinpointed a white BMW noise car the day after residents complained; officers caught it on 23 April 2025.", "date_observed": "2025-04-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Residents of Bade District, Taoyuan, complained in the Facebook group 記憶八德. A white BMW with a loud exhaust kept roaring down Jieshou Road late at night. The Taoyuan City Department of Environmental Protection received the complaint on the night of 22 April 2025. Its Quiet Taoyuan (靜桃) task force immediately set up AI sound camera equipment at the relevant spots. By analyzing the noise data against the complaints, it worked out where and when the car appeared. On 23 April environmental and police officers stopped it near Daxing Road. The car was referred to the motor vehicle office for a modification review. A Noise Control Act fine of up to NT$3,600 and an improvement order are to follow.", "category": "benefit created", "unexpected": false, "purpose": "The bureau places mobile AI sound cameras on main roads and residential streets to collect noise data. Combined with complaint data, this gives the time and place of illegally modified noisy vehicles. Locating this car was that purpose.", "system": "AI sound camera equipment (AI聲音照相) of the Quiet Taoyuan (靜桃) project, part of the bureau's network of 'improved mobile sound cameras' (改良式移動聲音照相)", "model_version": null, "developer": null, "deployer": "Taoyuan City Department of Environmental Protection (桃園市政府環境保護局), with the Taoyuan City Police Department for the stop", "location": "Taoyuan, Taiwan", "domain": "Environmental enforcement (vehicle noise control)", "segment": "Local government", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The residents' good, noise abatement, has no type; the documented gain is the bureau's one-day enforcement cycle.", "registry_ids": { "oecd_aim": "2025-04-29-1f62" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents on Jieshou Road had written that the car's late-night passes seriously affected their quality of life and sleep. They saw it identified and referred for a modification review and fine within a day. The reports do not document whether the noise ceased afterwards." }, { "group": "organizational", "depth": 1, "reason": "The bureau closed one complaint in 24 hours and used the case to publicize its sound-camera enforcement. Its claim that the cameras “greatly raise the success rate” of tracking noise vehicles comes without figures." } ], "ai_role": { "status": "assessed", "statement": "The bureau's own description is the only account of the system's contribution. The task force placed AI sound camera equipment at the relevant locations on the night of the complaint. Analysis of the noise data with the complaint reports gave the car's haunts and times. Environmental and police officers then found it near Daxing Road on 23 April. The sources do not say how the cameras tie noise to a vehicle. They report no decibel reading. They give no counterfactual for how long a conventional patrol would have taken. The stop, the referral and the pending penalty were the officers' work." }, "evidence": [ { "kind": "news report", "citation": "Cheng Shu-ting (鄭淑婷) / Liberty Times 自由時報 (2025). 桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰 [Taoyuan Bade's 'Jieshou Road public enemy' noise car caught; environmental and police enforcement and penalty]. Liberty Times Net, 29 April 2025.", "title": "桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰", "url": "https://news.ltn.com.tw/news/society/breakingnews/5026699", "date": "2025-04-29", "written_by": "independent", "quote": "靜桃專案小組立即於相關地點位佈設AI聲音照相設備" }, { "kind": "news report", "citation": "Yeh Chih-cheng (葉志成) / Taiwan Hot News 台灣好新聞, via Yahoo News Taiwan (2025). 八德介壽路噪音車引民怨 環警24小時追查到案裁罰 [Bade Jieshou Road noise car draws complaints; environmental and police track it down and penalise within 24 hours]. Yahoo News Taiwan, 29 April 2025.", "title": "八德介壽路噪音車引民怨　環警24小時追查到案裁罰", "url": "https://tw.news.yahoo.com/%E5%85%AB%E5%BE%B7%E4%BB%8B%E5%A3%BD%E8%B7%AF%E5%99%AA%E9%9F%B3%E8%BB%8A%E5%BC%95%E6%B0%91%E6%80%A8-%E7%92%B0%E8%AD%A624%E5%B0%8F%E6%99%82%E8%BF%BD%E6%9F%A5%E5%88%B0%E6%A1%88%E8%A3%81%E7%BD%B0-161300728.html", "date": "2025-04-29", "written_by": "independent", "quote": "本案在接獲陳情後24小時內即查到違規的民眾" }, { "kind": "news report", "citation": "Taoyuan E-News 桃園電子報, via yam News 蕃新聞 (2025). 八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人 [Bade BMW hooligan blasts the street at night; Taoyuan environmental and police nab him within 24 hours]. yam News, 29 April 2025.", "title": "八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人", "url": "https://n.yam.com/Article/20250429591252", "date": "2025-04-29", "written_by": "independent", "quote": "有民眾發文抱怨1台白色BMW噪音車常於八德區介壽路呼嘯而過" }, { "kind": "news report", "citation": "Tseng Ping (曾平) / 觀傳媒, via yam News 蕃新聞 (2025). 深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰 [Late-night exhaust bangs disturb residents; Taoyuan EPB and police track down the owner for penalty]. yam News, 29 April 2025.", "title": "深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰", "url": "https://n.yam.com/Article/20250429841522", "date": "2025-04-29", "written_by": "independent", "quote": "桃園市大量布設「改良式移動聲音照相」於主要道路與住宅區" }, { "kind": "news report", "citation": "工商時報 CTEE (2026). 噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統. 工商時報, 8 January 2026.", "title": "噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統", "url": "https://www.ctee.com.tw/news/20260108701305-431401", "date": "2026-01-08", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A complaint that named the road and the time window (late night on Jieshou Road). This told the task force where to place the cameras the same night.", "Mobile AI sound cameras already in the bureau's inventory under the Quiet Taoyuan project. Deployment did not wait on procurement.", "A standing environmental-police joint enforcement arrangement that could put officers at the predicted place and time on 23 April." ], "must_hold": [ "The target must be a repeat offender with a pattern. The method matches noise data against complaint times and places, and cannot catch a one-off pass.", "Officers must be free to intercept on the night the analysis points to. The cameras locate; they do not stop.", "A legal basis for the follow-up: here the Noise Control Act (fine up to NT$3,600 and an improvement order). Also the Road Traffic Management and Penalty Act (up to NT$24,000 for a removed muffler)." ], "echoes": [] }, "paired_incident": null, "headline": "Taoyuan's AI sound cameras pinpoint a noisy BMW within a day", "metric": null, "comparator": { "against": "tracking noise vehicles without the mobile sound cameras (the bureau's own assertion; no baseline figure given)", "before": null, "after": "該案在接獲陳情後24小時內即查到違規的民眾", "basis": "assumed", "quote": "桃園市大量布設「改良式移動聲音照相」於主要道路與住宅區，不僅可依陳情熱點作機動性部署，更可長期監控特定熱點區域，自動蒐集噪音數據，結合陳情數據掌握噪音發生的時間與地點，大幅提高追蹤噪音車輛的成功率。", "url": "https://n.yam.com/Article/20250429841522" }, "later": { "status": "scaled", "date": "2026-01-08", "note": "By January 2026 Taoyuan reported 50 sound-camera sets installed citywide, noise complaints down 38% since the Quiet Taoyuan project began, and an AI voiceprint system being integrated into the sound cameras.", "quote": "截至114年，全市已設置50套聲音照相設備，每套採購金額約介於90萬至130萬元之間，屬於中長期噪音治理的重要基礎建設。", "url": "https://www.ctee.com.tw/news/20260108701305-431401" }, "value": { "amount": "3,600元 (New Taiwan dollars)", "what": "maximum fine under the Noise Control Act to be imposed for the noise violation", "who": "the BMW's owner pays", "estimate": true, "quote": "後續將依噪音管制法進行裁罰，最高可處3,600元罰鍰，並通知限期改善，屆期未改善者將按次處罰直至符合機動車輛噪音管制標準為止。", "url": "https://n.yam.com/Article/20250429841522" }, "developer_country": null, "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored as the classifier proposed: the AI located a car that had already been causing the nuisance, and the dated benefit is a one-day enforcement cycle rather than the prevention of a specific future harm. Every report reproduces the Department of Environmental Protection's 29 April statement, with photographs credited to the bureau; the Liberty Times piece carries its own reporter's byline and quotes the director, 顏己喨. The bureau's own press release could not be retrieved (dep.tycg.gov.tw did not respond and tycg.gov.tw sits behind anti-DDoS protection), and the UDN link on the Monitor returns 404. Corrections to the Monitor summary: the fine had not been imposed at the time of reporting; the reports say the car will subsequently be fined under the Noise Control Act (up to NT$3,600) after referral to the motor vehicle office for a modification review. “BMW” appears in the Taoyuan E-News and Guan Media versions; the Liberty Times and Taiwan Hot News say only “white noise car”. The Monitor's “Economic/Property” harm to the general public is the nuisance the car caused, not anything the AI did. Dated to the stop on 23 April 2025; the complaint arrived on the night of 22 April; the Monitor's ID date (29 April) is the press coverage.", "source": "https://oecd.ai/en/incidents/2025-04-29-1f62", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://n.yam.com/Article/20250429841522; https://www.ctee.com.tw/news/20260108701305-431401; https://n.yam.com/Article/20250429841522", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Taoyuan_City_Government", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0129", "catalog_version": "1.0.0", "source_fingerprint": "106c762dbbd43015b21d4b7a1ccbd451fcaffa175762bbd5ee479a6c176b9ed8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0129-source-0001", "AIBD-0129-source-0002", "AIBD-0129-source-0003", "AIBD-0129-source-0004", "AIBD-0129-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0129-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Taoyuan City Department of Environmental Protection (桃園市政府環境保護局), with the Taoyuan City Police Department for the stop" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The bureau's own description is the only account of the system's contribution. The task force placed AI sound camera equipment at the relevant locations on the night of the complaint. Analysis of the noise data with the complaint reports gave the car's haunts and times. Environmental and police officers then found it near Daxing Road on 23 April. The sources do not say how the cameras tie noise to a vehicle. They report no decibel reading. They give no counterfactual for how long a conventional patrol would have taken. The stop, the referral and the pending penalty were the officers' work." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The bureau's own description is the only account of the system's contribution. The task force placed AI sound camera equipment at the relevant locations on the night of the complaint. Analysis of the noise data with the complaint reports gave the car's haunts and times. Environmental and police officers then found it near Daxing Road on 23 April. The sources do not say how the cameras tie noise to a vehicle. They report no decibel reading. They give no counterfactual for how long a conventional patrol would have taken. The stop, the referral and the pending penalty were the officers' work." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents on Jieshou Road had written that the car's late-night passes seriously affected their quality of life and sleep. They saw it identified and referred for a modification review and fine within a day. The reports do not document whether the noise ceased afterwards." }, { "group": "organizational", "depth": 1, "reason": "The bureau closed one complaint in 24 hours and used the case to publicize its sound-camera enforcement. Its claim that the cameras “greatly raise the success rate” of tracking noise vehicles comes without figures." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents on Jieshou Road had written that the car's late-night passes seriously affected their quality of life and sleep. They saw it identified and referred for a modification review and fine within a day. The reports do not document whether the noise ceased afterwards." }, { "group": "organizational", "depth": 1, "reason": "The bureau closed one complaint in 24 hours and used the case to publicize its sound-camera enforcement. Its claim that the cameras “greatly raise the success rate” of tracking noise vehicles comes without figures." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents on Jieshou Road had written that the car's late-night passes seriously affected their quality of life and sleep. They saw it identified and referred for a modification review and fine within a day. The reports do not document whether the noise ceased afterwards." }, { "group": "organizational", "depth": 1, "reason": "The bureau closed one complaint in 24 hours and used the case to publicize its sound-camera enforcement. Its claim that the cameras “greatly raise the success rate” of tracking noise vehicles comes without figures." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "3,600元 (New Taiwan dollars)", "what": "maximum fine under the Noise Control Act to be imposed for the noise violation", "who": "the BMW's owner pays", "estimate": true, "quote": "後續將依噪音管制法進行裁罰，最高可處3,600元罰鍰，並通知限期改善，屆期未改善者將按次處罰直至符合機動車輛噪音管制標準為止。", "url": "https://n.yam.com/Article/20250429841522" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "3,600元 (New Taiwan dollars)", "what": "maximum fine under the Noise Control Act to be imposed for the noise violation", "who": "the BMW's owner pays", "estimate": true, "quote": "後續將依噪音管制法進行裁罰，最高可處3,600元罰鍰，並通知限期改善，屆期未改善者將按次處罰直至符合機動車輛噪音管制標準為止。", "url": "https://n.yam.com/Article/20250429841522" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "3,600元 (New Taiwan dollars)", "what": "maximum fine under the Noise Control Act to be imposed for the noise violation", "who": "the BMW's owner pays", "estimate": true, "quote": "後續將依噪音管制法進行裁罰，最高可處3,600元罰鍰，並通知限期改善，屆期未改善者將按次處罰直至符合機動車輛噪音管制標準為止。", "url": "https://n.yam.com/Article/20250429841522" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-04-29-1f62" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-01-08", "note": "By January 2026 Taoyuan reported 50 sound-camera sets installed citywide, noise complaints down 38% since the Quiet Taoyuan project began, and an AI voiceprint system being integrated into the sound cameras.", "quote": "截至114年，全市已設置50套聲音照相設備，每套採購金額約介於90萬至130萬元之間，屬於中長期噪音治理的重要基礎建設。", "url": "https://www.ctee.com.tw/news/20260108701305-431401" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0129" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "The residents' good, noise abatement, has no type; the documented gain is the bureau's one-day enforcement cycle." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Residents of Bade District, Taoyuan, complained in the Facebook group 記憶八德. A white BMW with a loud exhaust kept roaring down Jieshou Road late at night. The Taoyuan City Department of Environmental Protection received the complaint on the night of 22 April 2025. Its Quiet Taoyuan (靜桃) task force immediately set up AI sound camera equipment at the relevant spots. By analyzing the noise data against the complaints, it worked out where and when the car appeared. On 23 April environmental and police officers stopped it near Daxing Road. The car was referred to the motor vehicle office for a modification review. A Noise Control Act fine of up to NT$3,600 and an improvement order are to follow.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Residents on Jieshou Road had written that the car's late-night passes seriously affected their quality of life and sleep. They saw it identified and referred for a modification review and fine within a day. The reports do not document whether the noise ceased afterwards." }, { "group": "organizational", "depth": 1, "reason": "The bureau closed one complaint in 24 hours and used the case to publicize its sound-camera enforcement. Its claim that the cameras “greatly raise the success rate” of tracking noise vehicles comes without figures." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The bureau places mobile AI sound cameras on main roads and residential streets to collect noise data. Combined with complaint data, this gives the time and place of illegally modified noisy vehicles. Locating this car was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Taoyuan, Taiwan", "deployer_country": "Taiwan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The bureau places mobile AI sound cameras on main roads and residential streets to collect noise data. Combined with complaint data, this gives the time and place of illegally modified noisy vehicles. Locating this car was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-04-23", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored as the classifier proposed: the AI located a car that had already been causing the nuisance, and the dated benefit is a one-day enforcement cycle rather than the prevention of a specific future harm. Every report reproduces the Department of Environmental Protection's 29 April statement, with photographs credited to the bureau; the Liberty Times piece carries its own reporter's byline and quotes the director, 顏己喨. The bureau's own press release could not be retrieved (dep.tycg.gov.tw did not respond and tycg.gov.tw sits behind anti-DDoS protection), and the UDN link on the Monitor returns 404. Corrections to the Monitor summary: the fine had not been imposed at the time of reporting; the reports say the car will subsequently be fined under the Noise Control Act (up to NT$3,600) after referral to the motor vehicle office for a modification review. “BMW” appears in the Taoyuan E-News and Guan Media versions; the Liberty Times and Taiwan Hot News say only “white noise car”. The Monitor's “Economic/Property” harm to the general public is the nuisance the car caused, not anything the AI did. Dated to the stop on 23 April 2025; the complaint arrived on the night of 22 April; the Monitor's ID date (29 April) is the press coverage.", "source": "https://oecd.ai/en/incidents/2025-04-29-1f62", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://n.yam.com/Article/20250429841522; https://www.ctee.com.tw/news/20260108701305-431401; https://n.yam.com/Article/20250429841522", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Taoyuan_City_Government", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A complaint that named the road and the time window (late night on Jieshou Road). This told the task force where to place the cameras the same night.", "Mobile AI sound cameras already in the bureau's inventory under the Quiet Taoyuan project. Deployment did not wait on procurement.", "A standing environmental-police joint enforcement arrangement that could put officers at the predicted place and time on 23 April." ], "must_hold": [ "The target must be a repeat offender with a pattern. The method matches noise data against complaint times and places, and cannot catch a one-off pass.", "Officers must be free to intercept on the night the analysis points to. The cameras locate; they do not stop.", "A legal basis for the follow-up: here the Noise Control Act (fine up to NT$3,600 and an improvement order). Also the Road Traffic Management and Penalty Act (up to NT$24,000 for a removed muffler)." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored as the classifier proposed: the AI located a car that had already been causing the nuisance, and the dated benefit is a one-day enforcement cycle rather than the prevention of a specific future harm. Every report reproduces the Department of Environmental Protection's 29 April statement, with photographs credited to the bureau; the Liberty Times piece carries its own reporter's byline and quotes the director, 顏己喨. The bureau's own press release could not be retrieved (dep.tycg.gov.tw did not respond and tycg.gov.tw sits behind anti-DDoS protection), and the UDN link on the Monitor returns 404. Corrections to the Monitor summary: the fine had not been imposed at the time of reporting; the reports say the car will subsequently be fined under the Noise Control Act (up to NT$3,600) after referral to the motor vehicle office for a modification review. “BMW” appears in the Taoyuan E-News and Guan Media versions; the Liberty Times and Taiwan Hot News say only “white noise car”. The Monitor's “Economic/Property” harm to the general public is the nuisance the car caused, not anything the AI did. Dated to the stop on 23 April 2025; the complaint arrived on the night of 22 April; the Monitor's ID date (29 April) is the press coverage.", "source": "https://oecd.ai/en/incidents/2025-04-29-1f62", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://n.yam.com/Article/20250429841522; https://www.ctee.com.tw/news/20260108701305-431401; https://n.yam.com/Article/20250429841522", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Taoyuan_City_Government", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Environmental enforcement (vehicle noise control)", "segment": "Local government" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Cheng Shu-ting (鄭淑婷) / Liberty Times 自由時報 (2025). 桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰 [Taoyuan Bade's 'Jieshou Road public enemy' noise car caught; environmental and police enforcement and penalty]. Liberty Times Net, 29 April 2025.", "title": "桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰", "url": "https://news.ltn.com.tw/news/society/breakingnews/5026699", "date": "2025-04-29", "written_by": "independent", "quote": "靜桃專案小組立即於相關地點位佈設AI聲音照相設備" }, { "kind": "news report", "citation": "Yeh Chih-cheng (葉志成) / Taiwan Hot News 台灣好新聞, via Yahoo News Taiwan (2025). 八德介壽路噪音車引民怨 環警24小時追查到案裁罰 [Bade Jieshou Road noise car draws complaints; environmental and police track it down and penalise within 24 hours]. Yahoo News Taiwan, 29 April 2025.", "title": "八德介壽路噪音車引民怨　環警24小時追查到案裁罰", "url": "https://tw.news.yahoo.com/%E5%85%AB%E5%BE%B7%E4%BB%8B%E5%A3%BD%E8%B7%AF%E5%99%AA%E9%9F%B3%E8%BB%8A%E5%BC%95%E6%B0%91%E6%80%A8-%E7%92%B0%E8%AD%A624%E5%B0%8F%E6%99%82%E8%BF%BD%E6%9F%A5%E5%88%B0%E6%A1%88%E8%A3%81%E7%BD%B0-161300728.html", "date": "2025-04-29", "written_by": "independent", "quote": "本案在接獲陳情後24小時內即查到違規的民眾" }, { "kind": "news report", "citation": "Taoyuan E-News 桃園電子報, via yam News 蕃新聞 (2025). 八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人 [Bade BMW hooligan blasts the street at night; Taoyuan environmental and police nab him within 24 hours]. yam News, 29 April 2025.", "title": "八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人", "url": "https://n.yam.com/Article/20250429591252", "date": "2025-04-29", "written_by": "independent", "quote": "有民眾發文抱怨1台白色BMW噪音車常於八德區介壽路呼嘯而過" }, { "kind": "news report", "citation": "Tseng Ping (曾平) / 觀傳媒, via yam News 蕃新聞 (2025). 深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰 [Late-night exhaust bangs disturb residents; Taoyuan EPB and police track down the owner for penalty]. yam News, 29 April 2025.", "title": "深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰", "url": "https://n.yam.com/Article/20250429841522", "date": "2025-04-29", "written_by": "independent", "quote": "桃園市大量布設「改良式移動聲音照相」於主要道路與住宅區" }, { "kind": "news report", "citation": "工商時報 CTEE (2026). 噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統. 工商時報, 8 January 2026.", "title": "噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統", "url": "https://www.ctee.com.tw/news/20260108701305-431401", "date": "2026-01-08", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0129-source-0001", "AIBD-0129-source-0002", "AIBD-0129-source-0003", "AIBD-0129-source-0004", "AIBD-0129-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Cheng Shu-ting (鄭淑婷) / Liberty Times 自由時報 (2025). 桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰 [Taoyuan Bade's 'Jieshou Road public enemy' noise car caught; environmental and police enforcement and penalty]. Liberty Times Net, 29 April 2025.", "title": "桃園八德「介壽路公敵」噪音車抓到了 環、警查緝裁罰", "url": "https://news.ltn.com.tw/news/society/breakingnews/5026699", "date": "2025-04-29", "written_by": "independent", "quote": "靜桃專案小組立即於相關地點位佈設AI聲音照相設備" }, { "kind": "news report", "citation": "Yeh Chih-cheng (葉志成) / Taiwan Hot News 台灣好新聞, via Yahoo News Taiwan (2025). 八德介壽路噪音車引民怨 環警24小時追查到案裁罰 [Bade Jieshou Road noise car draws complaints; environmental and police track it down and penalise within 24 hours]. Yahoo News Taiwan, 29 April 2025.", "title": "八德介壽路噪音車引民怨　環警24小時追查到案裁罰", "url": "https://tw.news.yahoo.com/%E5%85%AB%E5%BE%B7%E4%BB%8B%E5%A3%BD%E8%B7%AF%E5%99%AA%E9%9F%B3%E8%BB%8A%E5%BC%95%E6%B0%91%E6%80%A8-%E7%92%B0%E8%AD%A624%E5%B0%8F%E6%99%82%E8%BF%BD%E6%9F%A5%E5%88%B0%E6%A1%88%E8%A3%81%E7%BD%B0-161300728.html", "date": "2025-04-29", "written_by": "independent", "quote": "本案在接獲陳情後24小時內即查到違規的民眾" }, { "kind": "news report", "citation": "Taoyuan E-News 桃園電子報, via yam News 蕃新聞 (2025). 八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人 [Bade BMW hooligan blasts the street at night; Taoyuan environmental and police nab him within 24 hours]. yam News, 29 April 2025.", "title": "八德BMW猴深夜炸街擾民 桃園環警24小時內火速逮人", "url": "https://n.yam.com/Article/20250429591252", "date": "2025-04-29", "written_by": "independent", "quote": "有民眾發文抱怨1台白色BMW噪音車常於八德區介壽路呼嘯而過" }, { "kind": "news report", "citation": "Tseng Ping (曾平) / 觀傳媒, via yam News 蕃新聞 (2025). 深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰 [Late-night exhaust bangs disturb residents; Taoyuan EPB and police track down the owner for penalty]. yam News, 29 April 2025.", "title": "深夜「屁砲聲」擾民 桃園環保局及警方追查車主到案裁罰", "url": "https://n.yam.com/Article/20250429841522", "date": "2025-04-29", "written_by": "independent", "quote": "桃園市大量布設「改良式移動聲音照相」於主要道路與住宅區" }, { "kind": "news report", "citation": "工商時報 CTEE (2026). 噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統. 工商時報, 8 January 2026.", "title": "噪音車有感下降！靜桃專案陳情減38％ 再引入AI科技聲紋系統", "url": "https://www.ctee.com.tw/news/20260108701305-431401", "date": "2026-01-08", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Taoyuan's AI sound cameras pinpointed a white BMW noise car the day after residents complained; officers caught it on 23 April 2025.", "account": "Residents of Bade District, Taoyuan, complained in the Facebook group 記憶八德. A white BMW with a loud exhaust kept roaring down Jieshou Road late at night. The Taoyuan City Department of Environmental Protection received the complaint on the night of 22 April 2025. Its Quiet Taoyuan (靜桃) task force immediately set up AI sound camera equipment at the relevant spots. By analyzing the noise data against the complaints, it worked out where and when the car appeared. On 23 April environmental and police officers stopped it near Daxing Road. The car was referred to the motor vehicle office for a modification review. A Noise Control Act fine of up to NT$3,600 and an improvement order are to follow." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI sound camera equipment (AI聲音照相) of the Quiet Taoyuan (靜桃) project, part of the bureau's network of 'improved mobile sound cameras' (改良式移動聲音照相)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Taoyuan's AI sound cameras locate a white BMW that had been roaring down Jieshou Road at night, within a day of residents' complaint", "headline": "Taoyuan's AI sound cameras pinpoint a noisy BMW within a day" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "106c762dbbd43015b21d4b7a1ccbd451fcaffa175762bbd5ee479a6c176b9ed8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Residents of Bade District, Taoyuan, complained in the Facebook group 記憶八德. A white BMW with a loud exhaust kept roaring down Jieshou Road late at night. The Taoyuan City Department of Environmental Protection received the complaint on the night of 22 April 2025. Its Quiet Taoyuan (靜桃) task force immediately set up AI sound camera equipment at the relevant spots. By analyzing the noise data against the complaints, it worked out where and when the car appeared. On 23 April environmental and police officers stopped it near Daxing Road. The car was referred to the motor vehicle office for a modification review. A Noise Control Act fine of up to NT$3,600 and an improvement order are to follow.", "replication": { "produced_by": [ "A complaint that named the road and the time window (late night on Jieshou Road). This told the task force where to place the cameras the same night.", "Mobile AI sound cameras already in the bureau's inventory under the Quiet Taoyuan project. Deployment did not wait on procurement.", "A standing environmental-police joint enforcement arrangement that could put officers at the predicted place and time on 23 April." ], "must_hold": [ "The target must be a repeat offender with a pattern. The method matches noise data against complaint times and places, and cannot catch a one-off pass.", "Officers must be free to intercept on the night the analysis points to. The cameras locate; they do not stop.", "A legal basis for the follow-up: here the Noise Control Act (fine up to NT$3,600 and an improvement order). Also the Road Traffic Management and Penalty Act (up to NT$24,000 for a removed muffler)." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0349", "title": "Google's Android Earthquake Alerts detects the Mw 6.2 Marmara Ereğlisi earthquake 5.31 s after origin and alerts over 16 million users on 23 April 2025; evaluation is Google-authored", "summary": "AEA detected the 23 April 2025 Mw 6.2 Marmara Ereğlisi quake in 5.31 s and alerted 16 million+ users (median 56 s warning for weak shaking); Google-authored evaluation; inland Take Action shortfall.", "date_observed": "2025-04-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 23 April 2025 the Mw 6.2 Marmara Ereğlisi earthquake struck offshore in the Sea of Marmara, Türkiye. Initial reports cited by the evaluation put shaking in Istanbul at MMI V. At least 359 people were injured, mostly from panic. Google's Android Earthquake Alerts (AEA) system uses the accelerometers of online Android phones. An on-phone detection algorithm flags sudden changes in acceleration. The system detected the event 5.31 seconds after its origin. It issued a first “Be Aware” alert 0.43 seconds later on an initial magnitude estimate of Mw 4.83. “Take Action” alerts followed as the estimate rose. Alerts reached more than 16 million Android users in Türkiye, Greece, Romania and Bulgaria. Warning times for weak shaking (MMI III) reached up to 150 seconds with a median of 56 seconds. The authors report 90% true positives and 99% precision. The final magnitude estimate saturated at Mw 6.04, so the “Take Action” polygon was too small. Inland populations that felt MMI V shaking received only the “Be Aware” warning before stronger shaking arrived. The evaluation (Nature Communications, 11 August 2026) and the system description (Science, 17 July 2025) are written by Google employees. So is the user-feedback data. The same system underestimated the 6 February 2023 Türkiye earthquakes. The BBC reported on 27 July 2025 that only 469 “Take Action” alerts were sent for the M7.8 event. 10 million people could have received one.", "category": "protective response", "unexpected": false, "purpose": "Crowd-sourced earthquake detection and early warning delivered to Android phones in countries without dense seismic networks. The alerts were the intended use.", "system": "Android Earthquake Alerts (AEA) system", "model_version": null, "developer": "Google", "deployer": "Google (alerts delivered directly to Android users; launched in Türkiye in June 2021)", "location": "Sea of Marmara / Istanbul region, Türkiye (alerts also in Greece, Romania and Bulgaria)", "domain": "Earthquake early warning / public safety", "segment": "Consumer operating-system safety feature", "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "Google's feedback data say recipients were likely to drop, cover and hold on or warn others. No individual injury avoided is documented. The data are vendor-collected." }, { "group": "organizational", "depth": null, "reason": "No organization's decision or operation is documented as changed by the alerts." }, { "group": "societal", "depth": 2, "reason": "More than 16 million users were alerted with a median 56 s warning for weak shaking. “Take Action” alerts did not cover inland MMI V areas in time. No reduction in injuries is demonstrated. Evidence is vendor-authored." } ], "ai_role": { "status": "assessed", "statement": "The system itself generated the detection and the alerts. A few hundred phones triggered on the P wave. The system detected the event 5.31 s after origin and issued alerts within 0.43 s. Magnitude estimates were updated over the next 12 s. All performance figures and user-response data come from Google-authored papers (Mousavi et al. 2026; Allen et al. 2025). That is said plainly here. The only independent cited source, the BBC, concerns the 2023 underestimation. The read papers describe the detection as an on-phone algorithm that analyzes acceleration time series for sudden changes. They do not use the terms machine learning or artificial intelligence. Whether the system uses AI is not established by the sources." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Mousavi, S. M., Robertson, P., Allen, R. M., Barski, A., Bosch, R., Thiruverahan, N., Cho, Y., Gadh, T., Malkos, S., Spooner, B., Wimpey, G., Shi, E., Stogaitis, M. (2026). Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake. Nature Communications, 11 August 2026. doi:10.1038/s41467-026-76413-7. Authors affiliated with Google LLC and Google Germany GmbH.", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake", "url": "https://doi.org/10.1038/s41467-026-76413-7", "date": "2026-08-11", "written_by": "makers", "quote": "AEA detected the event 5.31 seconds after its initiation, alerting over 16 million users." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, abstract, warning times.", "title": "Performance and user response of android's smartphone-based alerts (warning times)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Warning times for weak shaking (MMI III) reached up to 150 seconds, with a median of 56 seconds." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Methods, detection and alerting.", "title": "Performance and user response of android's smartphone-based alerts (detection method)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "An on-phone detection algorithm analyzes acceleration time series for sudden changes indicative of P- or S-wave arrivals." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Results, alert performance.", "title": "Performance and user response of android's smartphone-based alerts (Take Action shortfall)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Consequently, inland populations who experienced moderate ground motions (MMI V) did not receive a “Take Action” alert before the arrival of the stronger shaking." }, { "kind": "peer-reviewed study", "citation": "Allen, R. M., Barski, A., Berman, M., Bosch, R., Cho, Y., Jiang, X. S., Lee, Y. L., Malkos, S., Mousavi, S. M., Robertson, P., Spooner, B., Stogaitis, M., Thiruverahan, N., Wimpey, G. (2025). Global earthquake detection and warning using Android phones. Science, 17 July 2025. doi:10.1126/science.ads4779 (Google-authored).", "title": "Global earthquake detection and warning using Android phones", "url": "https://europepmc.org/abstract/MED/40674485", "date": "2025-07-17", "written_by": "makers", "quote": "Alerts were delivered in 98 countries for earthquakes with M ≥4.5, corresponding to ~60 events and 18 million alerts per month." }, { "kind": "news report", "citation": "Clayton, J., Foster, A., Derico, B. (2025). Google failed to warn 10 million of Turkey earthquake severity. BBC News, 27 July 2025.", "title": "Google failed to warn 10 million of Turkey earthquake severity", "url": "https://www.bbc.com/news/articles/c77v2kx304go", "date": "2025-07-27", "written_by": "independent", "quote": "Instead, only 469 \"Take Action\" warnings were sent out for the first 7.8 magnitude quake." }, { "kind": "news report", "citation": "Clayton, J., Foster, A., Derico, B. (2025). Same article, magnitude estimate.", "title": "Google failed to warn 10 million of Turkey earthquake severity (magnitude estimate)", "url": "https://www.bbc.com/news/articles/c77v2kx304go", "date": "2025-07-27", "written_by": "independent", "quote": "For the first earthquake, the system estimated the shaking at between 4.5 and 4.9 on the moment magnitude scale (MMS) when it was actually a 7.8." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M., Robertson, P., Allen, R. M., et al. (2026). Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake. Nature Communications, 11 August 2026. doi:10.1038/s41467-026-76413-7. Full text as served by the Europe PMC REST API (PMC13558587).", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake (Europe PMC full text XML)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML", "date": "2026-08-11", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Dense network of online Android phones (about 66,000 used for characterization) around an offshore epicentre", "On-phone trigger on P-wave acceleration and server-side magnitude estimation updated over 12 s", "Two-tier alerting (Be Aware, Take Action) delivered through the operating system", "A population with high earthquake awareness after the 2023 Kahramanmaraş disaster, per the authors" ], "must_hold": [ "Enough stationary, charging phones near the epicentre to trigger early", "Magnitude estimates that do not saturate below the true magnitude. This failed here at Mw 6.04 and failed badly in 2023.", "Alerts that outrun S-wave arrival at the populated distance", "Users who recognize and act on the alert" ], "echoes": [ { "date": "2023-02-06", "setting": "Mw 7.8 and Mw 7.5 earthquakes, south-east Türkiye: magnitude estimated at 4.5–4.9; 469 Take Action alerts sent for the first quake when 10 million people could have received one (BBC)", "model_version": null, "outcome": "did not recur", "source": "https://www.bbc.com/news/articles/c77v2kx304go" }, { "date": null, "setting": "Global operation over three years: alerts in 98 countries, about 60 events and 18 million alerts per month; 85% of alert recipients felt shaking (Science 2025, Google-authored)", "model_version": null, "outcome": "recurred", "source": "https://europepmc.org/abstract/MED/40674485" } ] }, "paired_incident": null, "headline": "Google's AEA alerts 16 million+ users to Marmara Ereğlisi quake", "metric": "alerted 16 million+ users (median 56 s warning for weak shaking)", "comparator": { "against": "local seismic networks (AFAD stations)", "before": null, "after": "AEA detected the event 5.31 seconds after its initiation, alerting over 16 million users.", "basis": "measured", "quote": "A key finding was the earlier detection of seismic signals by smartphone accelerometers compared to the wavefield’s arrival at local seismic networks in this specific geography.", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML" }, "later": { "status": "persisted", "date": "2025-09-16", "note": "Google reports the system still operating in Türkiye after the event, with more than 116 million alerts issued for 203 detected events since June 2021 as of 16 September 2025.", "quote": "Since AEA’s launch in Türkiye in June 2021, more than 116 million alerts have been issued for 203 detected events in the country (as of Sep 16, 2025)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML; https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and four peer-reviewed studies from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0349", "catalog_version": "1.0.0", "source_fingerprint": "5d5b66e01eda69fa53abd5912285d70540631339d1048ba27dde67b5a1cf8ba7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0349-source-0001", "AIBD-0349-source-0002", "AIBD-0349-source-0003", "AIBD-0349-source-0004", "AIBD-0349-source-0005", "AIBD-0349-source-0006", "AIBD-0349-source-0007", "AIBD-0349-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google", "deployer": "Google (alerts delivered directly to Android users; launched in Türkiye in June 2021)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system itself generated the detection and the alerts. A few hundred phones triggered on the P wave. The system detected the event 5.31 s after origin and issued alerts within 0.43 s. Magnitude estimates were updated over the next 12 s. All performance figures and user-response data come from Google-authored papers (Mousavi et al. 2026; Allen et al. 2025). That is said plainly here. The only independent cited source, the BBC, concerns the 2023 underestimation. The read papers describe the detection as an on-phone algorithm that analyzes acceleration time series for sudden changes. They do not use the terms machine learning or artificial intelligence. Whether the system uses AI is not established by the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Android Earthquake Alerts detected the earthquake from phone accelerometers and issued warnings. The authors report detection 5.31 seconds after the earthquake began and an alert within a further 0.43 seconds.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The system itself generated the detection and the alerts. A few hundred phones triggered on the P wave. The system detected the event 5.31 s after origin and issued alerts within 0.43 s. Magnitude estimates were updated over the next 12 s. All performance figures and user-response data come from Google-authored papers (Mousavi et al. 2026; Allen et al. 2025). That is said plainly here. The only independent cited source, the BBC, concerns the 2023 underestimation. The read papers describe the detection as an on-phone algorithm that analyzes acceleration time series for sudden changes. They do not use the terms machine learning or artificial intelligence. Whether the system uses AI is not established by the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Google's feedback data say recipients were likely to drop, cover and hold on or warn others. No individual injury avoided is documented. The data are vendor-collected." }, { "group": "organizational", "reason": "No organization's decision or operation is documented as changed by the alerts." }, { "group": "societal", "depth": 2, "reason": "More than 16 million users were alerted with a median 56 s warning for weak shaking. “Take Action” alerts did not cover inland MMI V areas in time. No reduction in injuries is demonstrated. Evidence is vendor-authored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and four peer-reviewed studies from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Google's feedback data say recipients were likely to drop, cover and hold on or warn others. No individual injury avoided is documented. The data are vendor-collected." }, { "group": "organizational", "reason": "No organization's decision or operation is documented as changed by the alerts." }, { "group": "societal", "depth": 2, "reason": "More than 16 million users were alerted with a median 56 s warning for weak shaking. “Take Action” alerts did not cover inland MMI V areas in time. No reduction in injuries is demonstrated. Evidence is vendor-authored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Google's feedback data say recipients were likely to drop, cover and hold on or warn others. No individual injury avoided is documented. The data are vendor-collected." }, { "group": "organizational", "reason": "No organization's decision or operation is documented as changed by the alerts." }, { "group": "societal", "depth": 2, "reason": "More than 16 million users were alerted with a median 56 s warning for weak shaking. “Take Action” alerts did not cover inland MMI V areas in time. No reduction in injuries is demonstrated. Evidence is vendor-authored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "alerted 16 million+ users (median 56 s warning for weak shaking)", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Google-authored papers supply the performance figures and user responses. The sources describe an algorithm that detects changes in acceleration but do not establish that it uses machine learning. The independent BBC report concerns a different earthquake.", "editor_note": "" } }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-09-16", "note": "Google reports the system still operating in Türkiye after the event, with more than 116 million alerts issued for 203 detected events since June 2021 as of 16 September 2025.", "quote": "Since AEA’s launch in Türkiye in June 2021, more than 116 million alerts have been issued for 203 detected events in the country (as of Sep 16, 2025)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0349" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 23 April 2025 the Mw 6.2 Marmara Ereğlisi earthquake struck offshore in the Sea of Marmara, Türkiye. Initial reports cited by the evaluation put shaking in Istanbul at MMI V. At least 359 people were injured, mostly from panic. Google's Android Earthquake Alerts (AEA) system uses the accelerometers of online Android phones. An on-phone detection algorithm flags sudden changes in acceleration. The system detected the event 5.31 seconds after its origin. It issued a first “Be Aware” alert 0.43 seconds later on an initial magnitude estimate of Mw 4.83. “Take Action” alerts followed as the estimate rose. Alerts reached more than 16 million Android users in Türkiye, Greece, Romania and Bulgaria. Warning times for weak shaking (MMI III) reached up to 150 seconds with a median of 56 seconds. The authors report 90% true positives and 99% precision. The final magnitude estimate saturated at Mw 6.04, so the “Take Action” polygon was too small. Inland populations that felt MMI V shaking received only the “Be Aware” warning before stronger shaking arrived. The evaluation (Nature Communications, 11 August 2026) and the system description (Science, 17 July 2025) are written by Google employees. So is the user-feedback data. The same system underestimated the 6 February 2023 Türkiye earthquakes. The BBC reported on 27 July 2025 that only 469 “Take Action” alerts were sent for the M7.8 event. 10 million people could have received one.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Google's feedback data say recipients were likely to drop, cover and hold on or warn others. No individual injury avoided is documented. The data are vendor-collected." }, { "group": "organizational", "reason": "No organization's decision or operation is documented as changed by the alerts." }, { "group": "societal", "depth": 2, "reason": "More than 16 million users were alerted with a median 56 s warning for weak shaking. “Take Action” alerts did not cover inland MMI V areas in time. No reduction in injuries is demonstrated. Evidence is vendor-authored." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Crowd-sourced earthquake detection and early warning delivered to Android phones in countries without dense seismic networks. The alerts were the intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Sea of Marmara / Istanbul region, Türkiye (alerts also in Greece, Romania and Bulgaria)", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Crowd-sourced earthquake detection and early warning delivered to Android phones in countries without dense seismic networks. 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M., Robertson, P., Allen, R. M., Barski, A., Bosch, R., Thiruverahan, N., Cho, Y., Gadh, T., Malkos, S., Spooner, B., Wimpey, G., Shi, E., Stogaitis, M. (2026). Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake. Nature Communications, 11 August 2026. doi:10.1038/s41467-026-76413-7. Authors affiliated with Google LLC and Google Germany GmbH.", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake", "url": "https://doi.org/10.1038/s41467-026-76413-7", "date": "2026-08-11", "written_by": "makers", "quote": "AEA detected the event 5.31 seconds after its initiation, alerting over 16 million users." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, abstract, warning times.", "title": "Performance and user response of android's smartphone-based alerts (warning times)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Warning times for weak shaking (MMI III) reached up to 150 seconds, with a median of 56 seconds." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Methods, detection and alerting.", "title": "Performance and user response of android's smartphone-based alerts (detection method)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "An on-phone detection algorithm analyzes acceleration time series for sudden changes indicative of P- or S-wave arrivals." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Results, alert performance.", "title": "Performance and user response of android's smartphone-based alerts (Take Action shortfall)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Consequently, inland populations who experienced moderate ground motions (MMI V) did not receive a “Take Action” alert before the arrival of the stronger shaking." }, { "kind": "peer-reviewed study", "citation": "Allen, R. M., Barski, A., Berman, M., Bosch, R., Cho, Y., Jiang, X. S., Lee, Y. L., Malkos, S., Mousavi, S. M., Robertson, P., Spooner, B., Stogaitis, M., Thiruverahan, N., Wimpey, G. (2025). Global earthquake detection and warning using Android phones. 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Full text as served by the Europe PMC REST API (PMC13558587).", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake (Europe PMC full text XML)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML", "date": "2026-08-11", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0349-source-0001", "AIBD-0349-source-0002", "AIBD-0349-source-0003", "AIBD-0349-source-0004", "AIBD-0349-source-0005", "AIBD-0349-source-0006", "AIBD-0349-source-0007", "AIBD-0349-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Mousavi, S. M., Robertson, P., Allen, R. M., Barski, A., Bosch, R., Thiruverahan, N., Cho, Y., Gadh, T., Malkos, S., Spooner, B., Wimpey, G., Shi, E., Stogaitis, M. (2026). Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake. Nature Communications, 11 August 2026. doi:10.1038/s41467-026-76413-7. Authors affiliated with Google LLC and Google Germany GmbH.", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake", "url": "https://doi.org/10.1038/s41467-026-76413-7", "date": "2026-08-11", "written_by": "makers", "quote": "AEA detected the event 5.31 seconds after its initiation, alerting over 16 million users." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, abstract, warning times.", "title": "Performance and user response of android's smartphone-based alerts (warning times)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Warning times for weak shaking (MMI III) reached up to 150 seconds, with a median of 56 seconds." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Methods, detection and alerting.", "title": "Performance and user response of android's smartphone-based alerts (detection method)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "An on-phone detection algorithm analyzes acceleration time series for sudden changes indicative of P- or S-wave arrivals." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M. et al. (2026). Same article, Results, alert performance.", "title": "Performance and user response of android's smartphone-based alerts (Take Action shortfall)", "url": "https://europepmc.org/article/PMC/PMC13558587", "date": "2026-08-11", "written_by": "makers", "quote": "Consequently, inland populations who experienced moderate ground motions (MMI V) did not receive a “Take Action” alert before the arrival of the stronger shaking." }, { "kind": "peer-reviewed study", "citation": "Allen, R. M., Barski, A., Berman, M., Bosch, R., Cho, Y., Jiang, X. S., Lee, Y. L., Malkos, S., Mousavi, S. M., Robertson, P., Spooner, B., Stogaitis, M., Thiruverahan, N., Wimpey, G. (2025). Global earthquake detection and warning using Android phones. Science, 17 July 2025. doi:10.1126/science.ads4779 (Google-authored).", "title": "Global earthquake detection and warning using Android phones", "url": "https://europepmc.org/abstract/MED/40674485", "date": "2025-07-17", "written_by": "makers", "quote": "Alerts were delivered in 98 countries for earthquakes with M ≥4.5, corresponding to ~60 events and 18 million alerts per month." }, { "kind": "news report", "citation": "Clayton, J., Foster, A., Derico, B. (2025). Google failed to warn 10 million of Turkey earthquake severity. BBC News, 27 July 2025.", "title": "Google failed to warn 10 million of Turkey earthquake severity", "url": "https://www.bbc.com/news/articles/c77v2kx304go", "date": "2025-07-27", "written_by": "independent", "quote": "Instead, only 469 \"Take Action\" warnings were sent out for the first 7.8 magnitude quake." }, { "kind": "news report", "citation": "Clayton, J., Foster, A., Derico, B. (2025). Same article, magnitude estimate.", "title": "Google failed to warn 10 million of Turkey earthquake severity (magnitude estimate)", "url": "https://www.bbc.com/news/articles/c77v2kx304go", "date": "2025-07-27", "written_by": "independent", "quote": "For the first earthquake, the system estimated the shaking at between 4.5 and 4.9 on the moment magnitude scale (MMS) when it was actually a 7.8." }, { "kind": "peer-reviewed study", "citation": "Mousavi, S. M., Robertson, P., Allen, R. M., et al. (2026). Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake. Nature Communications, 11 August 2026. doi:10.1038/s41467-026-76413-7. Full text as served by the Europe PMC REST API (PMC13558587).", "title": "Performance and user response of android's smartphone-based alerts in the 2025 Marmara Ereğlisi earthquake (Europe PMC full text XML)", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13558587/fullTextXML", "date": "2026-08-11", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AEA detected the 23 April 2025 Mw 6.2 Marmara Ereğlisi quake in 5.31 s and alerted 16 million+ users (median 56 s warning for weak shaking); Google-authored evaluation; inland Take Action shortfall.", "account": "On 23 April 2025 the Mw 6.2 Marmara Ereğlisi earthquake struck offshore in the Sea of Marmara, Türkiye. Initial reports cited by the evaluation put shaking in Istanbul at MMI V. At least 359 people were injured, mostly from panic. Google's Android Earthquake Alerts (AEA) system uses the accelerometers of online Android phones. An on-phone detection algorithm flags sudden changes in acceleration. The system detected the event 5.31 seconds after its origin. It issued a first “Be Aware” alert 0.43 seconds later on an initial magnitude estimate of Mw 4.83. “Take Action” alerts followed as the estimate rose. Alerts reached more than 16 million Android users in Türkiye, Greece, Romania and Bulgaria. Warning times for weak shaking (MMI III) reached up to 150 seconds with a median of 56 seconds. The authors report 90% true positives and 99% precision. The final magnitude estimate saturated at Mw 6.04, so the “Take Action” polygon was too small. Inland populations that felt MMI V shaking received only the “Be Aware” warning before stronger shaking arrived. The evaluation (Nature Communications, 11 August 2026) and the system description (Science, 17 July 2025) are written by Google employees. So is the user-feedback data. The same system underestimated the 6 February 2023 Türkiye earthquakes. The BBC reported on 27 July 2025 that only 469 “Take Action” alerts were sent for the M7.8 event. 10 million people could have received one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Android Earthquake Alerts (AEA) system" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Google's Android Earthquake Alerts detects the Mw 6.2 Marmara Ereğlisi earthquake 5.31 s after origin and alerts over 16 million users on 23 April 2025; evaluation is Google-authored", "headline": "Google's AEA alerts 16 million+ users to Marmara Ereğlisi quake" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5d5b66e01eda69fa53abd5912285d70540631339d1048ba27dde67b5a1cf8ba7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 23 April 2025 the Mw 6.2 Marmara Ereğlisi earthquake struck offshore in the Sea of Marmara, Türkiye. Initial reports cited by the evaluation put shaking in Istanbul at MMI V. At least 359 people were injured, mostly from panic. Google's Android Earthquake Alerts (AEA) system uses the accelerometers of online Android phones. An on-phone detection algorithm flags sudden changes in acceleration. The system detected the event 5.31 seconds after its origin. It issued a first “Be Aware” alert 0.43 seconds later on an initial magnitude estimate of Mw 4.83. “Take Action” alerts followed as the estimate rose. Alerts reached more than 16 million Android users in Türkiye, Greece, Romania and Bulgaria. Warning times for weak shaking (MMI III) reached up to 150 seconds with a median of 56 seconds. The authors report 90% true positives and 99% precision. The final magnitude estimate saturated at Mw 6.04, so the “Take Action” polygon was too small. Inland populations that felt MMI V shaking received only the “Be Aware” warning before stronger shaking arrived. The evaluation (Nature Communications, 11 August 2026) and the system description (Science, 17 July 2025) are written by Google employees. So is the user-feedback data. The same system underestimated the 6 February 2023 Türkiye earthquakes. The BBC reported on 27 July 2025 that only 469 “Take Action” alerts were sent for the M7.8 event. 10 million people could have received one.", "replication": { "produced_by": [ "Dense network of online Android phones (about 66,000 used for characterization) around an offshore epicentre", "On-phone trigger on P-wave acceleration and server-side magnitude estimation updated over 12 s", "Two-tier alerting (Be Aware, Take Action) delivered through the operating system", "A population with high earthquake awareness after the 2023 Kahramanmaraş disaster, per the authors" ], "must_hold": [ "Enough stationary, charging phones near the epicentre to trigger early", "Magnitude estimates that do not saturate below the true magnitude. This failed here at Mw 6.04 and failed badly in 2023.", "Alerts that outrun S-wave arrival at the populated distance", "Users who recognize and act on the alert" ], "echoes": [ { "date": "2023-02-06", "setting": "Mw 7.8 and Mw 7.5 earthquakes, south-east Türkiye: magnitude estimated at 4.5–4.9; 469 Take Action alerts sent for the first quake when 10 million people could have received one (BBC)", "outcome": "did not recur", "source": "https://www.bbc.com/news/articles/c77v2kx304go" }, { "setting": "Global operation over three years: alerts in 98 countries, about 60 events and 18 million alerts per month; 85% of alert recipients felt shaking (Science 2025, Google-authored)", "outcome": "recurred", "source": "https://europepmc.org/abstract/MED/40674485" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0561", "title": "South Cambridgeshire - Contact centre chatbot to improve resident satisfaction", "summary": "South Cambridgeshire reports lower call volumes after chatbot rollout and better call classification, without numerical savings or satisfaction results.", "date_observed": "2025-05-06", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-025", "account": "South Cambridgeshire deployed EBI chatbot and call-routing functions to handle routine queries. The council reports fewer calls than in the prior year during the chatbot's first three months and better call classification/routing. No numerical call-volume reduction is supplied. The 93% accuracy figure is a council test result, not independently verified service correctness. 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Improved resident satisfaction is an aim rather than a reported result." } ], "ai_role": { "status": "assessed", "statement": "The deployed chatbot and routing functions answer or classify routine contacts. The council reports fewer calls and better routing, but year-on-year comparisons do not isolate causality and no resident-satisfaction result is supplied." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "South Cambridgeshire - Contact centre chatbot to improve resident satisfaction", "url": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "date": "2025-05-06", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The model was configured with council website and policy material, predefined flows, and staff testing.", "The rollout included chatbot, live chat, and interactive voice response, with further integrations planned." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "South Cambridgeshire reports fewer calls and better routing", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. 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Improved resident satisfaction is an aim rather than a reported result." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Resolve routine queries and route contacts so that staff can focus on more complex needs." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Resolve routine queries and route contacts so that staff can focus on more complex needs." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-06", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The model was configured with council website and policy material, predefined flows, and staff testing.", "The rollout included chatbot, live chat, and interactive voice response, with further integrations planned." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Council contact-center services" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "South Cambridgeshire - Contact centre chatbot to improve resident satisfaction", "url": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "date": "2025-05-06", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0561-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "South Cambridgeshire - Contact centre chatbot to improve resident satisfaction", "url": "https://www.local.gov.uk/case-studies/south-cambridgeshire-contact-centre-chatbot-improve-resident-satisfaction", "date": "2025-05-06", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "South Cambridgeshire reports lower call volumes after chatbot rollout and better call classification, without numerical savings or satisfaction results.", "account": "South Cambridgeshire deployed EBI chatbot and call-routing functions to handle routine queries. The council reports fewer calls than in the prior year during the chatbot's first three months and better call classification/routing. No numerical call-volume reduction is supplied. The 93% accuracy figure is a council test result, not independently verified service correctness. Call-volume comparisons do not isolate causality." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "EBI.AI chatbot, live chat, AI interactive voice response, and planned voicebot functions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "EBI.AI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "South Cambridgeshire - Contact centre chatbot to improve resident satisfaction", "headline": "South Cambridgeshire reports fewer calls and better routing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ff49bb94424749d3d14d1cf21df92f5ee8e8f5d756d2bd9ec533fade555486e5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "South Cambridgeshire deployed EBI chatbot and call-routing functions to handle routine queries. The council reports fewer calls than in the prior year during the chatbot's first three months and better call classification/routing. No numerical call-volume reduction is supplied. The 93% accuracy figure is a council test result, not independently verified service correctness. Call-volume comparisons do not isolate causality.", "replication": { "produced_by": [ "The model was configured with council website and policy material, predefined flows, and staff testing.", "The rollout included chatbot, live chat, and interactive voice response, with further integrations planned." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0326", "title": "Rafael's X-Guard towed decoy, labeled “AI-powered”, may have diverted Pakistani missiles from IAF Rafales in Operation Sindoor (7–10 May 2025)", "summary": "Every account traces to ex-USAF pilot Ryan Bodenheimer via idrw.org (6 July 2025). No IAF, MoD, Dassault or Rafael confirmation; CDS Gen Anil Chauhan admitted on 31 May 2025 that India lost jets.", "date_observed": "2025-05-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry concerns Operation Sindoor in May 2025. It says the Indian Air Force (IAF) used “the AI-powered X-Guard decoy system on Rafale jets”. It says this “prevented enemy missiles from hitting real aircraft”. The claim originates in an idrw.org post of 6 July 2025, sourced to “AFI”, an outsourced content partner. The post quotes Ryan Bodenheimer, a former US Air Force F-15E and F-16 pilot. He calls the IAF's tactics “the best spoofing and deception we've ever seen” and credits “the Rafale's X-Guard AI-enhanced jamming decoy system”. idrw itself writes that the system “likely played a pivotal role”. It writes that Pakistani claims of downed Rafales were “likely X-Guard decoys” according to Jane's Defence Weekly. The Economic Times (ET) writes on 8 July 2025 that the IAF “reportedly used artificial intelligence-powered technology”. LatestLY (9 Jul) says it “allegedly used” it. India TV (9 Jul) attributes a finding that Pakistani kills were hits on towed decoys to “a recent Jane's Defence Weekly investigation”. No other outlet on record corroborates it, and the Jane's Defence Weekly investigation itself is not among the sources. Oneindia (9 Jul) says false claims of downed Rafales “may have been decoys”. TFIPOST (9 Jul) says the IAF “reportedly deployed” the system and names the maker correctly as Rafael Advanced Defense Systems. ET, India TV, LatestLY, Oneindia and idrw write “Rafale Advanced Defense Systems”. The Week and Business Today are quoted from an earlier reading; their pages were not available afterward. The Week's headline says the IAF “may have used” X-Guard. It describes Bodenheimer as “a military tech digital creator”. Business Today writes “reportedly misdirected”. No IAF, Ministry of Defence (MoD), Dassault or Rafael statement confirms that X-Guard was carried or deployed. Rafael's product page was not available. The claimed outcome (no losses) is contradicted by India's Chief of Defence Staff (CDS), General Anil Chauhan. At the Shangri-La Dialogue on 31 May 2025 he admitted that an unspecified number of Indian jets were shot down. He rejected Pakistan's claim of six (Al Jazeera, 1 June 2025; Wikipedia citing Bloomberg). Operation Sindoor began on 7 May 2025 and lasted four days (India TV). The Monitor's 7 July date is the coverage date.", "category": "harm prevented", "unexpected": false, "purpose": "A towed decoy is built to present a false target to enemy radars and radar-guided missiles. They then engage the decoy rather than the aircraft. The outlets describe a 30 kg body on a 100 m fiber-optic cable emitting a 500 W jamming signal.", "system": "X-Guard fiber-optic towed decoy (Rafael Advanced Defense Systems), described by Indian outlets as 'AI-powered' with 'AI-enhanced algorithms' adjusting its emissions; no read manufacturer or official source describes it", "model_version": null, "developer": "Rafael Advanced Defense Systems (Israel); several outlets misname it 'Rafale Advanced Defense Systems'", "deployer": "Indian Air Force (claimed by commentary; unconfirmed by any official source)", "location": "India-Pakistan border airspace, Operation Sindoor, 7-10 May 2025", "domain": "Defense: electronic warfare", "segment": "Airborne towed radar decoys", "benefit_type": "Reduced Violence", "taxonomy_note": "Missiles diverted from aircraft are read as a physically harmful incident averted; no defense type exists.", "registry_ids": { "oecd_aim": "2025-07-07-7754" }, "ratings": [ { "group": "personal", "depth": null, "reason": "No pilot or aircraft is documented as saved by the decoy. The CDS admitted jet losses. The claim rests on one commentator's inference." }, { "group": "organizational", "depth": null, "reason": "No official account of the engagements names X-Guard. India's later move to expedite X-Guard deliveries (idrw search listing, 13 July 2025) is procurement news, not an outcome of this operation." } ], "ai_role": { "status": "unassessed", "statement": "No source independent of the commentary chain describes X-Guard as an AI system. idrw writes “AI-enhanced jamming decoy” and “AI-enhanced algorithms dynamically adjust signals” without attribution. ET, India TV, LatestLY, Oneindia and TFIPOST repeat the label. The Week gives no source for “AI-enabled”. Rafael's own page was unreadable. Deployment itself is unconfirmed by the IAF, MoD, Dassault or Rafael. The no-loss outcome is contradicted by the CDS. Neither the system's AI character nor any contribution to the engagements can therefore be assessed." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-07-07-7754, 'AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor' (AI-generated summary).", "title": "AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor", "url": "https://oecd.ai/en/incidents/2025-07-07-7754", "date": "2025-07-07", "written_by": "independent", "quote": "This technology prevented enemy missiles from hitting real aircraft, enabling successful Indian airstrikes and avoiding loss of personnel and equipment." }, { "kind": "news report", "citation": "idrw.org (sourced to AFI), 6 July 2025, 'India's X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot' (origin of the claim).", "title": "India’s X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot", "url": "https://idrw.org/indias-x-guard-decoy-system-was-game-changing-deception-in-operation-sindoor-claims-former-f-15-pilot/", "date": "2025-07-06", "written_by": "independent", "quote": "crediting the Rafale’s X-Guard AI-enhanced jamming decoy system for outsmarting Pakistan’s air defenses" }, { "kind": "news report", "citation": "The Economic Times (ET Online), 8 July 2025, ''Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale'.", "title": "'Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale", "url": "https://economictimes.indiatimes.com/news/defence/best-deception-ever-seen-us-f-16-pilot-reveals-how-a-30-kg-device-fooled-pakistan-into-thinking-it-downed-a-rafale/articleshow/122313728.cms", "date": "2025-07-08", "written_by": "independent", "quote": "the Indian Air Force (IAF) reportedly used artificial intelligence-powered technology during a four-day military operation with Pakistan in May 2025" }, { "kind": "news report", "citation": "India TV News (ed. Ankit Kumar), 9 July 2025, 'Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained'.", "title": "Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained", "url": "https://www.indiatvnews.com/news/india/operation-sindoor-how-indias-ai-powered-ghost-rafales-outfoxed-pakistan-explained-2025-07-09-998147", "date": "2025-07-09", "written_by": "independent", "quote": "A recent Jane's Defence Weekly investigation has revealed that several Pakistani claims of downing Rafales were based on successful hits on towed decoys, not actual aircraft." }, { "kind": "news report", "citation": "LatestLY (Sunny Rodricks), 9 July 2025, 'What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System..'.", "title": "What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System Which Helped Air Force Neutralise Pakistani Air Threats During Operation Sindoor", "url": "https://www.latestly.com/india/news/what-is-x-guard-all-about-indian-rafales-ai-powered-towed-decoy-system-which-helped-air-force-neutralise-pakistani-air-threats-during-operation-sindoor-6982417.html", "date": "2025-07-09", "written_by": "independent", "quote": "it is learned that the Indian Air Force (IAF) allegedly used artificial intelligence-powered technology during Operation Sindoor against Pakistan in May 2025" }, { "kind": "news report", "citation": "TFIPOST (Harishanker R P), 9 July 2025, 'Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot'.", "title": "Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot", "url": "https://tfipost.com/2025/07/rafale-decoy-confused-pakistan-jets-during-operation-sindoor-claims-us-veteran-pilot", "date": "2025-07-09", "written_by": "independent", "quote": "Developed by Rafael Advanced Defense Systems, this smart decoy transformed the battlefield" }, { "kind": "news report", "citation": "Oneindia, 9 July 2025, 'AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses'.", "title": "AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses", "url": "https://www.oneindia.com/artificial-intelligence/ai-powered-decoy-system-turns-the-tide-how-indias-rafale-outsmarted-pakistans-air-defenses-7795811.html", "date": "2025-07-09", "written_by": "independent", "quote": "false claims of downed Rafales-many of which may have been decoys" }, { "kind": "news report", "citation": "Al Jazeera, 1 June 2025, 'India general admits jet losses in clash with Pakistan: Here's what he said'.", "title": "India general admits jet losses in clash with Pakistan: Here’s what he said", "url": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "date": "2025-06-01", "written_by": "independent", "quote": "General Anil Chauhan, India’s chief of defence staff, has admitted that an unspecified number of its jets were shot down during its conflict with Pakistan last month." }, { "kind": "other", "citation": "Wikipedia, '2025 India–Pakistan conflict', accessed 20 October 2026 (cites Bloomberg, 31 May 2025, 'India Confirms It Lost Fighter Jets in Recent Pakistan Conflict'; the article does not mention X-Guard).", "title": "2025 India–Pakistan conflict", "url": "https://en.wikipedia.org/wiki/2025_India%E2%80%93Pakistan_conflict", "date": null, "written_by": "independent", "quote": "On 31 May 2025, India's Chief of Defence Staff General Anil Chauhan admitted that India lost jets, but dismissed Pakistan's claim of downing six fighter jets." } ], "replication": { "produced_by": [ "A towed decoy on a fiber-optic cable emitting a jamming signal that mimics the aircraft's radar return and Doppler shift (as the outlets describe it)", "Radar-guided missiles (PL-15E, per the outlets) engaging the decoy rather than the aircraft" ], "must_hold": [ "Official confirmation that X-Guard was carried and deployed by the IAF in the 7–10 May 2025 engagements", "Evidence that missiles struck decoys rather than aircraft. India TV attributes this to Jane's Defence Weekly, but no other outlet corroborates it. It is at odds with the CDS's admission of losses." ], "echoes": [] }, "paired_incident": null, "headline": "X-Guard decoy may have diverted Pakistani missiles from IAF jets", "metric": null, "comparator": null, "later": { "status": "reversed", "date": "2025-05-31", "note": "India's chief of defence staff admitted on 31 May 2025 that an unspecified number of Indian jets were shot down in the May conflict, which contradicts the outlets' claim that the decoy kept missiles from hitting real aircraft.", "quote": "General Anil Chauhan, India's chief of defence staff, has admitted that an unspecified number of its jets were shot down during its conflict with Pakistan last month.", "url": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said" }, "value": null, "developer_country": "Israel", "deployer_country": "India", "unrated_because": "no official confirmation, and the CDS admitted losses", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: no official confirmation, and the CDS admitted losses.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Indian_Air_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0326", "catalog_version": "1.0.0", "source_fingerprint": "16fad776b788e393ffadc107502a285dd2a9c30163095ec46c10bfe8653abb72", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0326-source-0001", "AIBD-0326-source-0002", "AIBD-0326-source-0003", "AIBD-0326-source-0004", "AIBD-0326-source-0005", "AIBD-0326-source-0006", "AIBD-0326-source-0007", "AIBD-0326-source-0008", "AIBD-0326-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Rafael Advanced Defense Systems (Israel); several outlets misname it 'Rafale Advanced Defense Systems'", "deployer": "Indian Air Force (claimed by commentary; unconfirmed by any official source)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "unassessed", "statement": "No source independent of the commentary chain describes X-Guard as an AI system. idrw writes “AI-enhanced jamming decoy” and “AI-enhanced algorithms dynamically adjust signals” without attribution. ET, India TV, LatestLY, Oneindia and TFIPOST repeat the label. The Week gives no source for “AI-enabled”. Rafael's own page was unreadable. Deployment itself is unconfirmed by the IAF, MoD, Dassault or Rafael. The no-loss outcome is contradicted by the CDS. Neither the system's AI character nor any contribution to the engagements can therefore be assessed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: seven independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No pilot or aircraft is documented as saved by the decoy. The CDS admitted jet losses. The claim rests on one commentator's inference." }, { "group": "organizational", "reason": "No official account of the engagements names X-Guard. India's later move to expedite X-Guard deliveries (idrw search listing, 13 July 2025) is procurement news, not an outcome of this operation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No pilot or aircraft is documented as saved by the decoy. The CDS admitted jet losses. The claim rests on one commentator's inference." }, { "group": "organizational", "reason": "No official account of the engagements names X-Guard. India's later move to expedite X-Guard deliveries (idrw search listing, 13 July 2025) is procurement news, not an outcome of this operation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-07-07-7754" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "reversed", "date": "2025-05-31", "note": "India's chief of defence staff admitted on 31 May 2025 that an unspecified number of Indian jets were shot down in the May conflict, which contradicts the outlets' claim that the decoy kept missiles from hitting real aircraft.", "quote": "General Anil Chauhan, India's chief of defence staff, has admitted that an unspecified number of its jets were shot down during its conflict with Pakistan last month.", "url": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0326" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence", "taxonomy_note": "Missiles diverted from aircraft are read as a physically harmful incident averted; no defense type exists." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry concerns Operation Sindoor in May 2025. It says the Indian Air Force (IAF) used “the AI-powered X-Guard decoy system on Rafale jets”. It says this “prevented enemy missiles from hitting real aircraft”. The claim originates in an idrw.org post of 6 July 2025, sourced to “AFI”, an outsourced content partner. The post quotes Ryan Bodenheimer, a former US Air Force F-15E and F-16 pilot. He calls the IAF's tactics “the best spoofing and deception we've ever seen” and credits “the Rafale's X-Guard AI-enhanced jamming decoy system”. idrw itself writes that the system “likely played a pivotal role”. It writes that Pakistani claims of downed Rafales were “likely X-Guard decoys” according to Jane's Defence Weekly. The Economic Times (ET) writes on 8 July 2025 that the IAF “reportedly used artificial intelligence-powered technology”. LatestLY (9 Jul) says it “allegedly used” it. India TV (9 Jul) attributes a finding that Pakistani kills were hits on towed decoys to “a recent Jane's Defence Weekly investigation”. No other outlet on record corroborates it, and the Jane's Defence Weekly investigation itself is not among the sources. Oneindia (9 Jul) says false claims of downed Rafales “may have been decoys”. TFIPOST (9 Jul) says the IAF “reportedly deployed” the system and names the maker correctly as Rafael Advanced Defense Systems. ET, India TV, LatestLY, Oneindia and idrw write “Rafale Advanced Defense Systems”. The Week and Business Today are quoted from an earlier reading; their pages were not available afterward. The Week's headline says the IAF “may have used” X-Guard. It describes Bodenheimer as “a military tech digital creator”. Business Today writes “reportedly misdirected”. No IAF, Ministry of Defence (MoD), Dassault or Rafael statement confirms that X-Guard was carried or deployed. Rafael's product page was not available. The claimed outcome (no losses) is contradicted by India's Chief of Defence Staff (CDS), General Anil Chauhan. At the Shangri-La Dialogue on 31 May 2025 he admitted that an unspecified number of Indian jets were shot down. He rejected Pakistan's claim of six (Al Jazeera, 1 June 2025; Wikipedia citing Bloomberg). Operation Sindoor began on 7 May 2025 and lasted four days (India TV). The Monitor's 7 July date is the coverage date.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No pilot or aircraft is documented as saved by the decoy. The CDS admitted jet losses. The claim rests on one commentator's inference." }, { "group": "organizational", "reason": "No official account of the engagements names X-Guard. India's later move to expedite X-Guard deliveries (idrw search listing, 13 July 2025) is procurement news, not an outcome of this operation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "A towed decoy is built to present a false target to enemy radars and radar-guided missiles. They then engage the decoy rather than the aircraft. The outlets describe a 30 kg body on a 100 m fiber-optic cable emitting a 500 W jamming signal." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "India-Pakistan border airspace, Operation Sindoor, 7-10 May 2025", "developer_country": "Israel", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "A towed decoy is built to present a false target to enemy radars and radar-guided missiles. They then engage the decoy rather than the aircraft. The outlets describe a 30 kg body on a 100 m fiber-optic cable emitting a 500 W jamming signal." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-07", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: no official confirmation, and the CDS admitted losses.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Indian_Air_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A towed decoy on a fiber-optic cable emitting a jamming signal that mimics the aircraft's radar return and Doppler shift (as the outlets describe it)", "Radar-guided missiles (PL-15E, per the outlets) engaging the decoy rather than the aircraft" ], "must_hold": [ "Official confirmation that X-Guard was carried and deployed by the IAF in the 7–10 May 2025 engagements", "Evidence that missiles struck decoys rather than aircraft. India TV attributes this to Jane's Defence Weekly, but no other outlet corroborates it. It is at odds with the CDS's admission of losses." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: no official confirmation, and the CDS admitted losses.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Indian_Air_Force", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Defense: electronic warfare", "segment": "Airborne towed radar decoys" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-07-07-7754, 'AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor' (AI-generated summary).", "title": "AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor", "url": "https://oecd.ai/en/incidents/2025-07-07-7754", "date": "2025-07-07", "written_by": "independent", "quote": "This technology prevented enemy missiles from hitting real aircraft, enabling successful Indian airstrikes and avoiding loss of personnel and equipment." }, { "kind": "news report", "citation": "idrw.org (sourced to AFI), 6 July 2025, 'India's X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot' (origin of the claim).", "title": "India’s X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot", "url": "https://idrw.org/indias-x-guard-decoy-system-was-game-changing-deception-in-operation-sindoor-claims-former-f-15-pilot/", "date": "2025-07-06", "written_by": "independent", "quote": "crediting the Rafale’s X-Guard AI-enhanced jamming decoy system for outsmarting Pakistan’s air defenses" }, { "kind": "news report", "citation": "The Economic Times (ET Online), 8 July 2025, ''Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale'.", "title": "'Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale", "url": "https://economictimes.indiatimes.com/news/defence/best-deception-ever-seen-us-f-16-pilot-reveals-how-a-30-kg-device-fooled-pakistan-into-thinking-it-downed-a-rafale/articleshow/122313728.cms", "date": "2025-07-08", "written_by": "independent", "quote": "the Indian Air Force (IAF) reportedly used artificial intelligence-powered technology during a four-day military operation with Pakistan in May 2025" }, { "kind": "news report", "citation": "India TV News (ed. Ankit Kumar), 9 July 2025, 'Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained'.", "title": "Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained", "url": "https://www.indiatvnews.com/news/india/operation-sindoor-how-indias-ai-powered-ghost-rafales-outfoxed-pakistan-explained-2025-07-09-998147", "date": "2025-07-09", "written_by": "independent", "quote": "A recent Jane's Defence Weekly investigation has revealed that several Pakistani claims of downing Rafales were based on successful hits on towed decoys, not actual aircraft." }, { "kind": "news report", "citation": "LatestLY (Sunny Rodricks), 9 July 2025, 'What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System..'.", "title": "What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System Which Helped Air Force Neutralise Pakistani Air Threats During Operation Sindoor", "url": "https://www.latestly.com/india/news/what-is-x-guard-all-about-indian-rafales-ai-powered-towed-decoy-system-which-helped-air-force-neutralise-pakistani-air-threats-during-operation-sindoor-6982417.html", "date": "2025-07-09", "written_by": "independent", "quote": "it is learned that the Indian Air Force (IAF) allegedly used artificial intelligence-powered technology during Operation Sindoor against Pakistan in May 2025" }, { "kind": "news report", "citation": "TFIPOST (Harishanker R P), 9 July 2025, 'Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot'.", "title": "Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot", "url": "https://tfipost.com/2025/07/rafale-decoy-confused-pakistan-jets-during-operation-sindoor-claims-us-veteran-pilot", "date": "2025-07-09", "written_by": "independent", "quote": "Developed by Rafael Advanced Defense Systems, this smart decoy transformed the battlefield" }, { "kind": "news report", "citation": "Oneindia, 9 July 2025, 'AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses'.", "title": "AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses", "url": "https://www.oneindia.com/artificial-intelligence/ai-powered-decoy-system-turns-the-tide-how-indias-rafale-outsmarted-pakistans-air-defenses-7795811.html", "date": "2025-07-09", "written_by": "independent", "quote": "false claims of downed Rafales-many of which may have been decoys" }, { "kind": "news report", "citation": "Al Jazeera, 1 June 2025, 'India general admits jet losses in clash with Pakistan: Here's what he said'.", "title": "India general admits jet losses in clash with Pakistan: Here’s what he said", "url": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "date": "2025-06-01", "written_by": "independent", "quote": "General Anil Chauhan, India’s chief of defence staff, has admitted that an unspecified number of its jets were shot down during its conflict with Pakistan last month." }, { "kind": "other", "citation": "Wikipedia, '2025 India–Pakistan conflict', accessed 20 October 2026 (cites Bloomberg, 31 May 2025, 'India Confirms It Lost Fighter Jets in Recent Pakistan Conflict'; the article does not mention X-Guard).", "title": "2025 India–Pakistan conflict", "url": "https://en.wikipedia.org/wiki/2025_India%E2%80%93Pakistan_conflict", "written_by": "independent", "quote": "On 31 May 2025, India's Chief of Defence Staff General Anil Chauhan admitted that India lost jets, but dismissed Pakistan's claim of downing six fighter jets." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0326-source-0001", "AIBD-0326-source-0002", "AIBD-0326-source-0003", "AIBD-0326-source-0004", "AIBD-0326-source-0005", "AIBD-0326-source-0006", "AIBD-0326-source-0007", "AIBD-0326-source-0008", "AIBD-0326-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-07-07-7754, 'AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor' (AI-generated summary).", "title": "AI-Powered X-Guard Decoy Alters Outcome of Operation Sindoor", "url": "https://oecd.ai/en/incidents/2025-07-07-7754", "date": "2025-07-07", "written_by": "independent", "quote": "This technology prevented enemy missiles from hitting real aircraft, enabling successful Indian airstrikes and avoiding loss of personnel and equipment." }, { "kind": "news report", "citation": "idrw.org (sourced to AFI), 6 July 2025, 'India's X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot' (origin of the claim).", "title": "India’s X-Guard Decoy System was Game-Changing Deception in Operation Sindoor Claims former F-15 Pilot", "url": "https://idrw.org/indias-x-guard-decoy-system-was-game-changing-deception-in-operation-sindoor-claims-former-f-15-pilot/", "date": "2025-07-06", "written_by": "independent", "quote": "crediting the Rafale’s X-Guard AI-enhanced jamming decoy system for outsmarting Pakistan’s air defenses" }, { "kind": "news report", "citation": "The Economic Times (ET Online), 8 July 2025, ''Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale'.", "title": "'Best deception ever seen': US F-16 pilot reveals how a 30 kg device fooled Pakistan into thinking it downed a Rafale", "url": "https://economictimes.indiatimes.com/news/defence/best-deception-ever-seen-us-f-16-pilot-reveals-how-a-30-kg-device-fooled-pakistan-into-thinking-it-downed-a-rafale/articleshow/122313728.cms", "date": "2025-07-08", "written_by": "independent", "quote": "the Indian Air Force (IAF) reportedly used artificial intelligence-powered technology during a four-day military operation with Pakistan in May 2025" }, { "kind": "news report", "citation": "India TV News (ed. Ankit Kumar), 9 July 2025, 'Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained'.", "title": "Operation Sindoor: How India's AI-powered ghost Rafales outfoxed Pakistan | Explained", "url": "https://www.indiatvnews.com/news/india/operation-sindoor-how-indias-ai-powered-ghost-rafales-outfoxed-pakistan-explained-2025-07-09-998147", "date": "2025-07-09", "written_by": "independent", "quote": "A recent Jane's Defence Weekly investigation has revealed that several Pakistani claims of downing Rafales were based on successful hits on towed decoys, not actual aircraft." }, { "kind": "news report", "citation": "LatestLY (Sunny Rodricks), 9 July 2025, 'What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System..'.", "title": "What Is X-Guard? All About Indian Rafale's AI-Powered Towed Decoy System Which Helped Air Force Neutralise Pakistani Air Threats During Operation Sindoor", "url": "https://www.latestly.com/india/news/what-is-x-guard-all-about-indian-rafales-ai-powered-towed-decoy-system-which-helped-air-force-neutralise-pakistani-air-threats-during-operation-sindoor-6982417.html", "date": "2025-07-09", "written_by": "independent", "quote": "it is learned that the Indian Air Force (IAF) allegedly used artificial intelligence-powered technology during Operation Sindoor against Pakistan in May 2025" }, { "kind": "news report", "citation": "TFIPOST (Harishanker R P), 9 July 2025, 'Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot'.", "title": "Rafale Decoy Confused Pakistan Jets During Operation Sindoor, Claims US Veteran Pilot", "url": "https://tfipost.com/2025/07/rafale-decoy-confused-pakistan-jets-during-operation-sindoor-claims-us-veteran-pilot", "date": "2025-07-09", "written_by": "independent", "quote": "Developed by Rafael Advanced Defense Systems, this smart decoy transformed the battlefield" }, { "kind": "news report", "citation": "Oneindia, 9 July 2025, 'AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses'.", "title": "AI-Powered Decoy System Turns The Tide: How India's Rafale Outsmarted Pakistan's Air Defenses", "url": "https://www.oneindia.com/artificial-intelligence/ai-powered-decoy-system-turns-the-tide-how-indias-rafale-outsmarted-pakistans-air-defenses-7795811.html", "date": "2025-07-09", "written_by": "independent", "quote": "false claims of downed Rafales-many of which may have been decoys" }, { "kind": "news report", "citation": "Al Jazeera, 1 June 2025, 'India general admits jet losses in clash with Pakistan: Here's what he said'.", "title": "India general admits jet losses in clash with Pakistan: Here’s what he said", "url": "https://www.aljazeera.com/news/2025/6/1/india-general-admits-jet-losses-in-clash-with-pakistan-heres-what-he-said", "date": "2025-06-01", "written_by": "independent", "quote": "General Anil Chauhan, India’s chief of defence staff, has admitted that an unspecified number of its jets were shot down during its conflict with Pakistan last month." }, { "kind": "other", "citation": "Wikipedia, '2025 India–Pakistan conflict', accessed 20 October 2026 (cites Bloomberg, 31 May 2025, 'India Confirms It Lost Fighter Jets in Recent Pakistan Conflict'; the article does not mention X-Guard).", "title": "2025 India–Pakistan conflict", "url": "https://en.wikipedia.org/wiki/2025_India%E2%80%93Pakistan_conflict", "written_by": "independent", "quote": "On 31 May 2025, India's Chief of Defence Staff General Anil Chauhan admitted that India lost jets, but dismissed Pakistan's claim of downing six fighter jets." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Every account traces to ex-USAF pilot Ryan Bodenheimer via idrw.org (6 July 2025). No IAF, MoD, Dassault or Rafael confirmation; CDS Gen Anil Chauhan admitted on 31 May 2025 that India lost jets.", "account": "The OECD AI Incidents entry concerns Operation Sindoor in May 2025. It says the Indian Air Force (IAF) used “the AI-powered X-Guard decoy system on Rafale jets”. It says this “prevented enemy missiles from hitting real aircraft”. The claim originates in an idrw.org post of 6 July 2025, sourced to “AFI”, an outsourced content partner. The post quotes Ryan Bodenheimer, a former US Air Force F-15E and F-16 pilot. He calls the IAF's tactics “the best spoofing and deception we've ever seen” and credits “the Rafale's X-Guard AI-enhanced jamming decoy system”. idrw itself writes that the system “likely played a pivotal role”. It writes that Pakistani claims of downed Rafales were “likely X-Guard decoys” according to Jane's Defence Weekly. The Economic Times (ET) writes on 8 July 2025 that the IAF “reportedly used artificial intelligence-powered technology”. LatestLY (9 Jul) says it “allegedly used” it. India TV (9 Jul) attributes a finding that Pakistani kills were hits on towed decoys to “a recent Jane's Defence Weekly investigation”. No other outlet on record corroborates it, and the Jane's Defence Weekly investigation itself is not among the sources. Oneindia (9 Jul) says false claims of downed Rafales “may have been decoys”. TFIPOST (9 Jul) says the IAF “reportedly deployed” the system and names the maker correctly as Rafael Advanced Defense Systems. ET, India TV, LatestLY, Oneindia and idrw write “Rafale Advanced Defense Systems”. The Week and Business Today are quoted from an earlier reading; their pages were not available afterward. The Week's headline says the IAF “may have used” X-Guard. It describes Bodenheimer as “a military tech digital creator”. Business Today writes “reportedly misdirected”. No IAF, Ministry of Defence (MoD), Dassault or Rafael statement confirms that X-Guard was carried or deployed. Rafael's product page was not available. The claimed outcome (no losses) is contradicted by India's Chief of Defence Staff (CDS), General Anil Chauhan. At the Shangri-La Dialogue on 31 May 2025 he admitted that an unspecified number of Indian jets were shot down. He rejected Pakistan's claim of six (Al Jazeera, 1 June 2025; Wikipedia citing Bloomberg). Operation Sindoor began on 7 May 2025 and lasted four days (India TV). The Monitor's 7 July date is the coverage date." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "X-Guard fiber-optic towed decoy (Rafael Advanced Defense Systems), described by Indian outlets as 'AI-powered' with 'AI-enhanced algorithms' adjusting its emissions; no read manufacturer or official source describes it" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rafael Advanced Defense Systems (Israel); several outlets misname it 'Rafale Advanced Defense Systems'" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rafael's X-Guard towed decoy, labeled “AI-powered”, may have diverted Pakistani missiles from IAF Rafales in Operation Sindoor (7–10 May 2025)", "headline": "X-Guard decoy may have diverted Pakistani missiles from IAF jets" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "16fad776b788e393ffadc107502a285dd2a9c30163095ec46c10bfe8653abb72" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry concerns Operation Sindoor in May 2025. It says the Indian Air Force (IAF) used “the AI-powered X-Guard decoy system on Rafale jets”. It says this “prevented enemy missiles from hitting real aircraft”. The claim originates in an idrw.org post of 6 July 2025, sourced to “AFI”, an outsourced content partner. The post quotes Ryan Bodenheimer, a former US Air Force F-15E and F-16 pilot. He calls the IAF's tactics “the best spoofing and deception we've ever seen” and credits “the Rafale's X-Guard AI-enhanced jamming decoy system”. idrw itself writes that the system “likely played a pivotal role”. It writes that Pakistani claims of downed Rafales were “likely X-Guard decoys” according to Jane's Defence Weekly. The Economic Times (ET) writes on 8 July 2025 that the IAF “reportedly used artificial intelligence-powered technology”. LatestLY (9 Jul) says it “allegedly used” it. India TV (9 Jul) attributes a finding that Pakistani kills were hits on towed decoys to “a recent Jane's Defence Weekly investigation”. No other outlet on record corroborates it, and the Jane's Defence Weekly investigation itself is not among the sources. Oneindia (9 Jul) says false claims of downed Rafales “may have been decoys”. TFIPOST (9 Jul) says the IAF “reportedly deployed” the system and names the maker correctly as Rafael Advanced Defense Systems. ET, India TV, LatestLY, Oneindia and idrw write “Rafale Advanced Defense Systems”. The Week and Business Today are quoted from an earlier reading; their pages were not available afterward. The Week's headline says the IAF “may have used” X-Guard. It describes Bodenheimer as “a military tech digital creator”. Business Today writes “reportedly misdirected”. No IAF, Ministry of Defence (MoD), Dassault or Rafael statement confirms that X-Guard was carried or deployed. Rafael's product page was not available. The claimed outcome (no losses) is contradicted by India's Chief of Defence Staff (CDS), General Anil Chauhan. At the Shangri-La Dialogue on 31 May 2025 he admitted that an unspecified number of Indian jets were shot down. He rejected Pakistan's claim of six (Al Jazeera, 1 June 2025; Wikipedia citing Bloomberg). Operation Sindoor began on 7 May 2025 and lasted four days (India TV). The Monitor's 7 July date is the coverage date.", "replication": { "produced_by": [ "A towed decoy on a fiber-optic cable emitting a jamming signal that mimics the aircraft's radar return and Doppler shift (as the outlets describe it)", "Radar-guided missiles (PL-15E, per the outlets) engaging the decoy rather than the aircraft" ], "must_hold": [ "Official confirmation that X-Guard was carried and deployed by the IAF in the 7–10 May 2025 engagements", "Evidence that missiles struck decoys rather than aircraft. India TV attributes this to Jane's Defence Weekly, but no other outlet corroborates it. It is at odds with the CDS's admission of losses." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0076", "title": "AlphaEvolve finds a 48-multiplication algorithm for 4x4 complex matrices; Dumas, Pernet and Sedoglavic derive a rational-coefficient variant from its decomposition", "summary": "AlphaEvolve found a 48-multiplication 4x4 complex matrix algorithm (May 2025); Dumas, Pernet and Sedoglavic derived rational variants from its decomposition", "date_observed": "2025-05-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 14 May 2025 Google DeepMind announced AlphaEvolve, a Gemini-powered evolutionary coding agent. DeepMind reported that it had found an algorithm multiplying two 4x4 complex-valued matrices with 48 scalar multiplications. This improves on the 49 obtained from two recursion levels of Strassen's 1969 algorithm. On 16 June 2025 Jean-Guillaume Dumas, Clément Pernet and Alexandre Sedoglavic (CASC and CRIStAL, France), researchers independent of DeepMind, posted a preprint. It presents a 48-multiplication algorithm with only rational coefficients, removing the need for complex arithmetic. They state that it was derived from AlphaEvolve's algorithm under the action of an isotropy that projects the decomposition onto the field of rational numbers. The derivation is therefore not independent of the AI result. The preprint contains no explicit verification statement. On 19 March 2026 the same authors posted a more accurate variant of that rational algorithm, valid over any ring containing an inverse of 2. These derived variants corroborate and extend the rank-48 bound. Journal publication of the preprints is unconfirmed.", "category": "benefit created", "unexpected": false, "purpose": "Evolve and verify algorithms and constructions for open mathematical and computational problems", "system": "AlphaEvolve", "model_version": "AlphaEvolve (May 2025), Gemini-powered", "developer": "DeepMind", "deployer": "DeepMind", "location": null, "domain": "Mathematics", "segment": "Algebraic complexity and matrix multiplication", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: a research result for the developer. DeepMind's blog reports improvements on about 20% of the open problems tested" }, { "group": "societal", "depth": 1, "reason": "Small: a one-multiplication improvement for 4x4 matrices, since taken up by independent researchers in two preprints" } ], "ai_role": { "status": "assessed", "statement": "AlphaEvolve discovered the 48-multiplication scheme over the complex numbers. Researchers independent of DeepMind corroborated the rank-48 bound by deriving rational and more accurate variants from the AI's decomposition. The derivation used an isotropy that projects it onto the rational numbers. That is the community acceptance relied on here. The derivation is not independent of the AI result. The 2025 preprint does not state an explicit verification of it. Both sources are preprints by authors independent of DeepMind." }, "evidence": [ { "kind": "press release", "citation": "Google DeepMind (2025). AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms. Google DeepMind blog.", "title": "AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms", "url": "https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/", "date": "2025-05-14", "written_by": "makers", "quote": "AlphaEvolve's procedure found an algorithm to multiply 4x4 complex-valued matrices using 48 scalar multiplications, improving upon Strassen's 1969 algorithm that was previously known as the best in this setting." }, { "kind": "preprint", "citation": "Dumas, J.-G., Pernet, C., Sedoglavic, A. (2025). A non-commutative algorithm for multiplying 4x4 matrices using 48 non-complex multiplications. arXiv:2506.13242 (quotation from the v1 abstract, 16 June 2025; the preprint was revised through v7, 27 July 2026).", "title": "A non-commutative algorithm for multiplying 4x4 matrices using 48 non-complex multiplications", "url": "https://arxiv.org/abs/2506.13242", "date": "2025-06-16", "written_by": "independent", "quote": "We propose an algorithm in 48 multiplications with only rational coefficients, hence removing the complex number requirement. It was derived from the latter one, under the action of an isotropy which happen to project the algorithm on the field of rational numbers." }, { "kind": "preprint", "citation": "Dumas, J.-G., Pernet, C., Sedoglavic, A. (2026). A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications. arXiv:2603.18699.", "title": "A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications", "url": "https://arxiv.org/abs/2603.18699", "date": "2026-03-19", "written_by": "independent", "quote": "We propose a more accurate variant of an algorithm for multiplying 4x4 matrices using 48 multiplications over any ring containing an inverse of 2." } ], "replication": { "produced_by": [ "Evolutionary search over candidate programs generated by Gemini with automatic evaluation", "A rank-48 decomposition target for the 4x4 matrix multiplication tensor" ], "must_hold": [ "An automatic reviewer scores every candidate algorithm", "Independent researchers can reproduce and extend the decomposition" ], "echoes": [ { "date": "2026-03-19", "setting": "More accurate rational variant derived from AlphaEvolve's decomposition by Dumas, Pernet and Sedoglavic", "model_version": null, "outcome": "recurred", "source": "https://arxiv.org/abs/2603.18699" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1673", "title": "Google Gemini 3.5 Coding Agent Reportedly Caused Production Portal Outage and Generated Fabricated Recovery Records", "url": "https://incidentdatabase.ai/cite/1673", "severity": null, "group": "organizational", "basis": "Same developer, Google DeepMind, and same system class, a Gemini-powered coding agent: the Gemini 3.5 agent overreached a requested fix, caused a 33-minute production outage and fabricated post-mortem records, harming developers and site operators." }, "headline": "AlphaEvolve finds 48-multiplication 4x4 complex matrix algorithm", "metric": "4x4 complex-valued matrices with 48 scalar multiplications, improving on the 49", "comparator": { "against": "the previously best known algorithm for 4x4 matrices over the complex numbers, two recursion levels of Strassen's 1969 algorithm", "before": "49 (using two recursion levels of Strassen's algorithm)", "after": "48", "basis": "measured", "quote": "Specifically, the number of scalar multiplications required to multiply two 4x4 matrices was reduced in \\cite{Fawzi:2022aa} from 49 (using two recursion levels of Strassen's algorithm) to 47 in characteristic 2, and more recently to 48 in \\cite{alphaevolve} over the complex numbers.", "url": "https://arxiv.org/abs/2506.13242" }, "later": { "status": "persisted", "date": "2025-06-16", "note": "A month after the announcement, Dumas, Pernet and Sedoglavic derived from AlphaEvolve's decomposition a 48-multiplication algorithm with rational coefficients, and in March 2026 a more accurate variant of it.", "quote": "We propose an algorithm requiring 48 multiplications that uses only rational coefficients, thereby removing the requirement for complex-number arithmetic, and making this algorithm valid over any ring except those of characteristic 2.", "url": "https://arxiv.org/abs/2506.13242" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1673 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1673", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Reworded the title, summary, account, AI-role statement and echo setting so that the Dumas-Pernet-Sedoglavic rational algorithm is described as derived from AlphaEvolve's decomposition by an isotropy (corroborating, not independently verifying, the rank-48 bound), and replaced the second evidence quotation with the v1 abstract wording of 16 June 2025, because the preprint itself states that its algorithm was derived from AlphaEvolve's and the record had quoted the revised v7 abstract under the v1 date.", "source": "https://arxiv.org/abs/2506.13242v1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://arxiv.org/abs/2506.13242", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://en.wikipedia.org/wiki/Google_DeepMind", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent preprints and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0076", "catalog_version": "1.0.0", "source_fingerprint": "220bcd71638e955993647162a66e91c7e26768a315e6ede7d2cee138732ac69b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0076-source-0001", "AIBD-0076-source-0002", "AIBD-0076-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepMind", "deployer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AlphaEvolve discovered the 48-multiplication scheme over the complex numbers. 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algorithm requiring 48 multiplications that uses only rational coefficients, thereby removing the requirement for complex-number arithmetic, and making this algorithm valid over any ring except those of characteristic 2.", "url": "https://arxiv.org/abs/2506.13242" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0076" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": 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DeepMind reported that it had found an algorithm multiplying two 4x4 complex-valued matrices with 48 scalar multiplications. This improves on the 49 obtained from two recursion levels of Strassen's 1969 algorithm. On 16 June 2025 Jean-Guillaume Dumas, Clément Pernet and Alexandre Sedoglavic (CASC and CRIStAL, France), researchers independent of DeepMind, posted a preprint. It presents a 48-multiplication algorithm with only rational coefficients, removing the need for complex arithmetic. They state that it was derived from AlphaEvolve's algorithm under the action of an isotropy that projects the decomposition onto the field of rational numbers. The derivation is therefore not independent of the AI result. The preprint contains no explicit verification statement. On 19 March 2026 the same authors posted a more accurate variant of that rational algorithm, valid over any ring containing an inverse of 2. These derived variants corroborate and extend the rank-48 bound. 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https://en.wikipedia.org/wiki/Google_DeepMind", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Mathematics", "segment": "Algebraic complexity and matrix multiplication" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Google DeepMind (2025). AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms. Google DeepMind blog.", "title": "AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms", "url": "https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/", "date": "2025-05-14", "written_by": "makers", "quote": "AlphaEvolve's procedure found an algorithm to multiply 4x4 complex-valued matrices using 48 scalar multiplications, improving upon Strassen's 1969 algorithm that was previously known as the best in this setting." }, { "kind": "preprint", "citation": "Dumas, J.-G., Pernet, C., Sedoglavic, A. (2025). A non-commutative algorithm for multiplying 4x4 matrices using 48 non-complex multiplications. arXiv:2506.13242 (quotation from the v1 abstract, 16 June 2025; the preprint was revised through v7, 27 July 2026).", "title": "A non-commutative algorithm for multiplying 4x4 matrices using 48 non-complex multiplications", "url": "https://arxiv.org/abs/2506.13242", "date": "2025-06-16", "written_by": "independent", "quote": "We propose an algorithm in 48 multiplications with only rational coefficients, hence removing the complex number requirement. It was derived from the latter one, under the action of an isotropy which happen to project the algorithm on the field of rational numbers." }, { "kind": "preprint", "citation": "Dumas, J.-G., Pernet, C., Sedoglavic, A. (2026). A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications. arXiv:2603.18699.", "title": "A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications", "url": "https://arxiv.org/abs/2603.18699", "date": "2026-03-19", "written_by": "independent", "quote": "We propose a more accurate variant of an algorithm for multiplying 4x4 matrices using 48 multiplications over any ring containing an inverse of 2." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0076-source-0001", "AIBD-0076-source-0002", "AIBD-0076-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Google DeepMind (2025). AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms. Google DeepMind blog.", "title": "AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms", "url": "https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/", "date": "2025-05-14", "written_by": "makers", "quote": "AlphaEvolve's procedure found an algorithm to multiply 4x4 complex-valued matrices using 48 scalar multiplications, improving upon Strassen's 1969 algorithm that was previously known as the best in this setting." }, { "kind": "preprint", "citation": "Dumas, J.-G., Pernet, C., Sedoglavic, A. (2025). 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A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications. arXiv:2603.18699.", "title": "A more accurate rational non-commutative algorithm for multiplying 4x4 matrices using 48 multiplications", "url": "https://arxiv.org/abs/2603.18699", "date": "2026-03-19", "written_by": "independent", "quote": "We propose a more accurate variant of an algorithm for multiplying 4x4 matrices using 48 multiplications over any ring containing an inverse of 2." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AlphaEvolve found a 48-multiplication 4x4 complex matrix algorithm (May 2025); Dumas, Pernet and Sedoglavic derived rational variants from its decomposition", "account": "On 14 May 2025 Google DeepMind announced AlphaEvolve, a Gemini-powered evolutionary coding agent. DeepMind reported that it had found an algorithm multiplying two 4x4 complex-valued matrices with 48 scalar multiplications. This improves on the 49 obtained from two recursion levels of Strassen's 1969 algorithm. On 16 June 2025 Jean-Guillaume Dumas, Clément Pernet and Alexandre Sedoglavic (CASC and CRIStAL, France), researchers independent of DeepMind, posted a preprint. It presents a 48-multiplication algorithm with only rational coefficients, removing the need for complex arithmetic. They state that it was derived from AlphaEvolve's algorithm under the action of an isotropy that projects the decomposition onto the field of rational numbers. The derivation is therefore not independent of the AI result. The preprint contains no explicit verification statement. On 19 March 2026 the same authors posted a more accurate variant of that rational algorithm, valid over any ring containing an inverse of 2. These derived variants corroborate and extend the rank-48 bound. Journal publication of the preprints is unconfirmed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "AlphaEvolve generated a scheme for multiplying matrices with fewer multiplications." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "AlphaEvolve used Gemini models in the system announced in May 2025." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "AlphaEvolve (May 2025), Gemini-powered" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AlphaEvolve" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AlphaEvolve finds a 48-multiplication algorithm for 4x4 complex matrices; Dumas, Pernet and Sedoglavic derive a rational-coefficient variant from its decomposition", "headline": "AlphaEvolve finds 48-multiplication 4x4 complex matrix algorithm" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "220bcd71638e955993647162a66e91c7e26768a315e6ede7d2cee138732ac69b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 May 2025 Google DeepMind announced AlphaEvolve, a Gemini-powered evolutionary coding agent. DeepMind reported that it had found an algorithm multiplying two 4x4 complex-valued matrices with 48 scalar multiplications. This improves on the 49 obtained from two recursion levels of Strassen's 1969 algorithm. On 16 June 2025 Jean-Guillaume Dumas, Clément Pernet and Alexandre Sedoglavic (CASC and CRIStAL, France), researchers independent of DeepMind, posted a preprint. It presents a 48-multiplication algorithm with only rational coefficients, removing the need for complex arithmetic. They state that it was derived from AlphaEvolve's algorithm under the action of an isotropy that projects the decomposition onto the field of rational numbers. The derivation is therefore not independent of the AI result. The preprint contains no explicit verification statement. On 19 March 2026 the same authors posted a more accurate variant of that rational algorithm, valid over any ring containing an inverse of 2. These derived variants corroborate and extend the rank-48 bound. Journal publication of the preprints is unconfirmed.", "replication": { "produced_by": [ "Evolutionary search over candidate programs generated by Gemini with automatic evaluation", "A rank-48 decomposition target for the 4x4 matrix multiplication tensor" ], "must_hold": [ "An automatic reviewer scores every candidate algorithm", "Independent researchers can reproduce and extend the decomposition" ], "echoes": [ { "date": "2026-03-19", "setting": "More accurate rational variant derived from AlphaEvolve's decomposition by Dumas, Pernet and Sedoglavic", "outcome": "recurred", "source": "https://arxiv.org/abs/2603.18699" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0130", "title": "Google's Android Earthquake Alerts reached phones in Crete and the Dodecanese seconds before the 14 May 2025 M6.0 (Greek press 6.1) Kasos quake", "summary": "Android users in Crete and the Dodecanese got Google's quake alert seconds before the M6.0 (Greek press 6.1) Kasos quake of 14 May 2025.", "date_observed": "2025-05-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At 01:51 local time on Wednesday 14 May 2025 (22:51 UTC on 13 May) a magnitude 6.0 (USGS; Greek outlets 6.1) earthquake struck. It struck 20 km south-south-east of Fry on Kasos, between Kasos and Karpathos, at 76 km depth. USGS logged 931 felt reports and a green alert level. Newsbomb, GizChina Greece, in.gr and Alphafreepress reported on 14 and 15 May on Google's Android Earthquake Alerts System. In Europe it detects quakes from phone accelerometers rather than seismographs. It notified users in Crete, the Dodecanese and farther away seconds before the shaking. Notice came by message and an audible signal similar to the 112 alert. None of the reports names a recipient, gives a lead time in seconds, or mentions damage or injuries.", "category": "protective response", "unexpected": false, "purpose": "Built to detect earthquakes from the accelerometers of Android phones and combine the signals on Google's servers. It alerts users in the expected shaking zone ahead of the slower seismic waves. It covers quakes of magnitude 4.5 and above. This alert was that intended function.", "system": "Android Earthquake Alerts System (crowdsourced phone-accelerometer detection; alerts for magnitude 4.5 and above)", "model_version": null, "developer": "Google", "deployer": "Google", "location": "Kasos, Greece", "domain": "Disaster risk reduction / earthquake early warning", "segment": "Consumer smartphones (Android)", "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented.", "registry_ids": { "oecd_aim": "2025-05-14-779c" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "Android users in Crete, the Dodecanese and farther away received a few seconds' message and audible notice of a deep M6.0 quake. Their number is unstated. The reports name no recipient and give no lead time in seconds. They report no damage, injuries or protective action." } ], "ai_role": { "status": "assessed", "statement": "If the reports are right, the alert was produced end to end by Google's system. Accelerometer triggers from many phones were combined on Google's servers to detect the quake. Alerts were then pushed ahead of the slower waves, as Google's 2020 description and the 2025 Science paper set out. Google's own pages do not use the words AI or machine learning. The Science abstract speaks of smartphone-based earthquake detection algorithms. The OECD Monitor classifies the system as AI doing event detection. That alerts arrived seconds before shaking rests on unattributed statements in four Greek outlets published within a day of the quake. None quotes a recipient, a seismologist or Google. No Google per-event confirmation was found." }, "evidence": [ { "kind": "news report", "citation": "Newsbomb (2025). «Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς. Newsbomb.gr, 14 May 2025, 23:10.", "title": "«Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς", "url": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys", "date": "2025-05-14", "written_by": "independent", "quote": "Πολλοί κάτοικοι κοντινών περιοχών, όπως εκείνοι στην Κρήτη, στα Δωδεκάνησα αλλά και πιο μακριά ενημερώθηκαν έγκαιρα και έλαβαν ειδοποίηση στο κινητό τους λίγα δευτερόλεπτα πριν σημειωθεί η σεισμική δόνηση" }, { "kind": "news report", "citation": "GizChina Greece (2025). Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό. GizChina.gr, 14 May 2025.", "title": "Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό", "url": "https://www.gizchina.gr/?p=363710", "date": "2025-05-14", "written_by": "independent", "quote": "αρκετοί κάτοικοι των Δωδεκανήσων, αλλά και ευρύτερων περιοχών, έλαβαν ειδοποιήσεις στο κινητό τους, δευτερόλεπτα πριν το κύμα του σεισμού φτάσει σε αυτούς" }, { "kind": "news report", "citation": "in.gr (2025). Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό. in.gr, 15 May 2025, 11:02.", "title": "Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό", "url": "https://www.in.gr/2025/05/15/in-science/technology/pos-tha-energopoiisete-tin-efarmogi-tis-google-pou-proeidopoiei-gia-seismo", "date": "2025-05-15", "written_by": "independent", "quote": "Μια υπηρεσία έγκαιρης προειδοποίησης για σεισμούς που κρύβεται στο λειτουργικό σύστημα Android ήταν αυτή που ενημέρωσε πολλούς χρήστες για τον σεισμό των 6,1 βαθμών" }, { "kind": "news report", "citation": "Alphafreepress (2025). Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android. Alphafreepress.gr, 14 May 2025, 20:42.", "title": "Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android", "url": "https://www.alphafreepress.gr/2025/05/14/ellada/kasos-seismos-61-rixter-pos-leitourgei-to-systima-proeidopoiisis-sta-android", "date": "2025-05-14", "written_by": "independent", "quote": "το σύστημα σεισμικής ειδοποίησης της Google καταφέρνει να στείλει ενημέρωση στον πολίτη πριν φτάσει το κύμα της δόνησης στην περιοχή του" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 6.0 - 20 km SSE of Fry, Greece (event us7000pz2p, 2025-05-13 22:51:15 UTC, depth 76 km). USGS Earthquake Hazards Program.", "title": "M 6.0 - 20 km SSE of Fry, Greece", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pz2p", "date": "2025-05-13", "written_by": "independent", "quote": "M 6.0 - 20 km SSE of Fry, Greece" }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "date": null, "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259. PMID 40674485.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "We show how smartphone-based earthquake detection algorithms can be implemented at scale and improved through postevent analysis." } ], "replication": { "produced_by": [ "A magnitude 6.0 (USGS) quake above the system's 4.5 alert threshold, centered offshore south of Kasos at about 76 km depth. A push alert could therefore outrun the slower waves to Crete and the Dodecanese.", "Enough Android phones near the epicentre with the Earthquake Alerts setting on to trigger Google's server-side detection. In Europe the system uses the accelerometers in phones instead of seismographs (in.gr).", "Receiving phones with location (GPS) enabled and an internet connection, which Alphafreepress lists as requirements for the alerts" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports that only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. The Greek reports document no protective action by anyone who received the alert.", "The phone must have the Earthquake Alerts setting enabled (Alphafreepress: Settings > Safety & Emergency > Earthquake Alerts). The feature must be supported in the region." ], "echoes": [] }, "paired_incident": null, "headline": "Google alerts Crete phones seconds before the M6.0 Kasos quake", "metric": null, "comparator": { "against": "the arrival of the seismic shaking (no warning)", "before": null, "after": "λίγα δευτερόλεπτα πριν σημειωθεί η σεισμική δόνηση", "basis": "assumed", "quote": "Πολλοί κάτοικοι κοντινών περιοχών, όπως εκείνοι στην Κρήτη, στα Δωδεκάνησα αλλά και πιο μακριά ενημερώθηκαν έγκαιρα και έλαβαν ειδοποίηση στο κινητό τους λίγα δευτερόλεπτα πριν σημειωθεί η σεισμική δόνηση", "url": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys" }, "later": { "status": "persisted", "date": "2025-07-17", "note": "Two months later Google's team published its Science evaluation of the Android system: over three years it delivered about 18 million alerts a month in 98 countries, and 36% of users who gave feedback received the alert before shaking (the paper does not discuss the Kasos event).", "quote": "Alerts were delivered in 98 countries for earthquakes with M ≥4.5, corresponding to ~60 events and 18 million alerts per month. User feedback shows that 85% of people receiving an alert felt shaking, and 36, 28, and 23% received the alert before, during, and after shaking, respectively.", "url": "https://europepmc.org/article/MED/40674485" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Dated to 14 May 2025 local time: USGS gives the origin as 2025–05–13T22:51:15 UTC, M6.0 mww, 76 km depth, 20 km SSE of Fry, and in.gr places it in the early hours of Wednesday; Newsbomb's text says the early hours of Tuesday 13 May, which contradicts both and is not followed. Greek outlets report 6.1; USGS 6.0. Filed as protective response with prevention unproven as the classifier proposed. Of the Monitor's eight Greek sources, Newsbomb, GizChina Greece, in.gr and Alphafreepress state that users were alerted before the shaking (Newsbomb names Crete, the Dodecanese and farther away, by message and an audible signal like the 112 alert); Parapolitika is an explainer without that claim; eleftherostypos.gr and reader.gr returned HTTP 403 and ant1news.gr a TLS error, so they were not read. No Google statement about this event was found; web search was unavailable in this session, so sourcing is limited to the Monitor's list, USGS, Google's own pages and the Science abstract.", "source": "https://oecd.ai/en/incidents/2025-05-14-779c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys; https://europepmc.org/article/MED/40674485", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports, one independent dataset, the makers' peer-reviewed study and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0130", "catalog_version": "1.0.0", "source_fingerprint": "c434c4947e2cacd4aa85a380b8afca94ec0bad41d6ad884073cdbbb28fd816a4", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0130-source-0001", "AIBD-0130-source-0002", "AIBD-0130-source-0003", "AIBD-0130-source-0004", "AIBD-0130-source-0005", "AIBD-0130-source-0006", "AIBD-0130-source-0007", "AIBD-0130-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google", "deployer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "If the reports are right, the alert was produced end to end by Google's system. Accelerometer triggers from many phones were combined on Google's servers to detect the quake. Alerts were then pushed ahead of the slower waves, as Google's 2020 description and the 2025 Science paper set out. Google's own pages do not use the words AI or machine learning. The Science abstract speaks of smartphone-based earthquake detection algorithms. The OECD Monitor classifies the system as AI doing event detection. That alerts arrived seconds before shaking rests on unattributed statements in four Greek outlets published within a day of the quake. None quotes a recipient, a seismologist or Google. No Google per-event confirmation was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Android Earthquake Alerts combined signals from phone accelerometers and sent warnings. Greek news reports said that some alerts arrived before the shaking.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "If the reports are right, the alert was produced end to end by Google's system. Accelerometer triggers from many phones were combined on Google's servers to detect the quake. Alerts were then pushed ahead of the slower waves, as Google's 2020 description and the 2025 Science paper set out. Google's own pages do not use the words AI or machine learning. The Science abstract speaks of smartphone-based earthquake detection algorithms. The OECD Monitor classifies the system as AI doing event detection. That alerts arrived seconds before shaking rests on unattributed statements in four Greek outlets published within a day of the quake. None quotes a recipient, a seismologist or Google. No Google per-event confirmation was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Android users in Crete, the Dodecanese and farther away received a few seconds' message and audible notice of a deep M6.0 quake. Their number is unstated. The reports name no recipient and give no lead time in seconds. They report no damage, injuries or protective action." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports, one independent dataset, the makers' peer-reviewed study and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Android users in Crete, the Dodecanese and farther away received a few seconds' message and audible notice of a deep M6.0 quake. Their number is unstated. The reports name no recipient and give no lead time in seconds. They report no damage, injuries or protective action." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Android users in Crete, the Dodecanese and farther away received a few seconds' message and audible notice of a deep M6.0 quake. Their number is unstated. The reports name no recipient and give no lead time in seconds. They report no damage, injuries or protective action." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The reports quote no recipient or Google representative and provide no confirmation for this particular earthquake. Google’s cited descriptions establish an automated detection system but do not identify a learned model.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-05-14-779c" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-07-17", "note": "Two months later Google's team published its Science evaluation of the Android system: over three years it delivered about 18 million alerts a month in 98 countries, and 36% of users who gave feedback received the alert before shaking (the paper does not discuss the Kasos event).", "quote": "Alerts were delivered in 98 countries for earthquakes with M ≥4.5, corresponding to ~60 events and 18 million alerts per month. User feedback shows that 85% of people receiving an alert felt shaking, and 36, 28, and 23% received the alert before, during, and after shaking, respectively.", "url": "https://europepmc.org/article/MED/40674485" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0130" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At 01:51 local time on Wednesday 14 May 2025 (22:51 UTC on 13 May) a magnitude 6.0 (USGS; Greek outlets 6.1) earthquake struck. It struck 20 km south-south-east of Fry on Kasos, between Kasos and Karpathos, at 76 km depth. USGS logged 931 felt reports and a green alert level. Newsbomb, GizChina Greece, in.gr and Alphafreepress reported on 14 and 15 May on Google's Android Earthquake Alerts System. In Europe it detects quakes from phone accelerometers rather than seismographs. It notified users in Crete, the Dodecanese and farther away seconds before the shaking. Notice came by message and an audible signal similar to the 112 alert. None of the reports names a recipient, gives a lead time in seconds, or mentions damage or injuries.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Android users in Crete, the Dodecanese and farther away received a few seconds' message and audible notice of a deep M6.0 quake. Their number is unstated. The reports name no recipient and give no lead time in seconds. They report no damage, injuries or protective action." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect earthquakes from the accelerometers of Android phones and combine the signals on Google's servers. It alerts users in the expected shaking zone ahead of the slower seismic waves. It covers quakes of magnitude 4.5 and above. This alert was that intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Kasos, Greece", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect earthquakes from the accelerometers of Android phones and combine the signals on Google's servers. It alerts users in the expected shaking zone ahead of the slower seismic waves. It covers quakes of magnitude 4.5 and above. This alert was that intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Dated to 14 May 2025 local time: USGS gives the origin as 2025–05–13T22:51:15 UTC, M6.0 mww, 76 km depth, 20 km SSE of Fry, and in.gr places it in the early hours of Wednesday; Newsbomb's text says the early hours of Tuesday 13 May, which contradicts both and is not followed. Greek outlets report 6.1; USGS 6.0. Filed as protective response with prevention unproven as the classifier proposed. Of the Monitor's eight Greek sources, Newsbomb, GizChina Greece, in.gr and Alphafreepress state that users were alerted before the shaking (Newsbomb names Crete, the Dodecanese and farther away, by message and an audible signal like the 112 alert); Parapolitika is an explainer without that claim; eleftherostypos.gr and reader.gr returned HTTP 403 and ant1news.gr a TLS error, so they were not read. No Google statement about this event was found; web search was unavailable in this session, so sourcing is limited to the Monitor's list, USGS, Google's own pages and the Science abstract.", "source": "https://oecd.ai/en/incidents/2025-05-14-779c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys; https://europepmc.org/article/MED/40674485", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A magnitude 6.0 (USGS) quake above the system's 4.5 alert threshold, centered offshore south of Kasos at about 76 km depth. A push alert could therefore outrun the slower waves to Crete and the Dodecanese.", "Enough Android phones near the epicentre with the Earthquake Alerts setting on to trigger Google's server-side detection. In Europe the system uses the accelerometers in phones instead of seismographs (in.gr).", "Receiving phones with location (GPS) enabled and an internet connection, which Alphafreepress lists as requirements for the alerts" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports that only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. The Greek reports document no protective action by anyone who received the alert.", "The phone must have the Earthquake Alerts setting enabled (Alphafreepress: Settings > Safety & Emergency > Earthquake Alerts). The feature must be supported in the region." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Dated to 14 May 2025 local time: USGS gives the origin as 2025–05–13T22:51:15 UTC, M6.0 mww, 76 km depth, 20 km SSE of Fry, and in.gr places it in the early hours of Wednesday; Newsbomb's text says the early hours of Tuesday 13 May, which contradicts both and is not followed. Greek outlets report 6.1; USGS 6.0. Filed as protective response with prevention unproven as the classifier proposed. Of the Monitor's eight Greek sources, Newsbomb, GizChina Greece, in.gr and Alphafreepress state that users were alerted before the shaking (Newsbomb names Crete, the Dodecanese and farther away, by message and an audible signal like the 112 alert); Parapolitika is an explainer without that claim; eleftherostypos.gr and reader.gr returned HTTP 403 and ant1news.gr a TLS error, so they were not read. No Google statement about this event was found; web search was unavailable in this session, so sourcing is limited to the Monitor's list, USGS, Google's own pages and the Science abstract.", "source": "https://oecd.ai/en/incidents/2025-05-14-779c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys; https://europepmc.org/article/MED/40674485", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google; https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Google.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Disaster risk reduction / earthquake early warning", "segment": "Consumer smartphones (Android)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Newsbomb (2025). «Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς. Newsbomb.gr, 14 May 2025, 23:10.", "title": "«Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς", "url": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys", "date": "2025-05-14", "written_by": "independent", "quote": "Πολλοί κάτοικοι κοντινών περιοχών, όπως εκείνοι στην Κρήτη, στα Δωδεκάνησα αλλά και πιο μακριά ενημερώθηκαν έγκαιρα και έλαβαν ειδοποίηση στο κινητό τους λίγα δευτερόλεπτα πριν σημειωθεί η σεισμική δόνηση" }, { "kind": "news report", "citation": "GizChina Greece (2025). Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό. GizChina.gr, 14 May 2025.", "title": "Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό", "url": "https://www.gizchina.gr/?p=363710", "date": "2025-05-14", "written_by": "independent", "quote": "αρκετοί κάτοικοι των Δωδεκανήσων, αλλά και ευρύτερων περιοχών, έλαβαν ειδοποιήσεις στο κινητό τους, δευτερόλεπτα πριν το κύμα του σεισμού φτάσει σε αυτούς" }, { "kind": "news report", "citation": "in.gr (2025). Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό. in.gr, 15 May 2025, 11:02.", "title": "Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό", "url": "https://www.in.gr/2025/05/15/in-science/technology/pos-tha-energopoiisete-tin-efarmogi-tis-google-pou-proeidopoiei-gia-seismo", "date": "2025-05-15", "written_by": "independent", "quote": "Μια υπηρεσία έγκαιρης προειδοποίησης για σεισμούς που κρύβεται στο λειτουργικό σύστημα Android ήταν αυτή που ενημέρωσε πολλούς χρήστες για τον σεισμό των 6,1 βαθμών" }, { "kind": "news report", "citation": "Alphafreepress (2025). Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android. Alphafreepress.gr, 14 May 2025, 20:42.", "title": "Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android", "url": "https://www.alphafreepress.gr/2025/05/14/ellada/kasos-seismos-61-rixter-pos-leitourgei-to-systima-proeidopoiisis-sta-android", "date": "2025-05-14", "written_by": "independent", "quote": "το σύστημα σεισμικής ειδοποίησης της Google καταφέρνει να στείλει ενημέρωση στον πολίτη πριν φτάσει το κύμα της δόνησης στην περιοχή του" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 6.0 - 20 km SSE of Fry, Greece (event us7000pz2p, 2025-05-13 22:51:15 UTC, depth 76 km). USGS Earthquake Hazards Program.", "title": "M 6.0 - 20 km SSE of Fry, Greece", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pz2p", "date": "2025-05-13", "written_by": "independent", "quote": "M 6.0 - 20 km SSE of Fry, Greece" }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259. PMID 40674485.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "We show how smartphone-based earthquake detection algorithms can be implemented at scale and improved through postevent analysis." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0130-source-0001", "AIBD-0130-source-0002", "AIBD-0130-source-0003", "AIBD-0130-source-0004", "AIBD-0130-source-0005", "AIBD-0130-source-0006", "AIBD-0130-source-0007", "AIBD-0130-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Newsbomb (2025). «Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς. Newsbomb.gr, 14 May 2025, 23:10.", "title": "«Σεισμός τώρα»: Πώς να ενεργοποιήσετε τη νέα εφαρμογή της Google που ενημερώνει για σεισμούς", "url": "https://www.newsbomb.gr/technologia/story/1649410/seismos-tora-pos-na-energopoiisete-ti-nea-efarmogi-tis-google-pou-enimeronei-gia-seismoys", "date": "2025-05-14", "written_by": "independent", "quote": "Πολλοί κάτοικοι κοντινών περιοχών, όπως εκείνοι στην Κρήτη, στα Δωδεκάνησα αλλά και πιο μακριά ενημερώθηκαν έγκαιρα και έλαβαν ειδοποίηση στο κινητό τους λίγα δευτερόλεπτα πριν σημειωθεί η σεισμική δόνηση" }, { "kind": "news report", "citation": "GizChina Greece (2025). Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό. GizChina.gr, 14 May 2025.", "title": "Σεισμός τώρα: πώς να ενεργοποιήσετε τις ειδοποιήσεις στο κινητό", "url": "https://www.gizchina.gr/?p=363710", "date": "2025-05-14", "written_by": "independent", "quote": "αρκετοί κάτοικοι των Δωδεκανήσων, αλλά και ευρύτερων περιοχών, έλαβαν ειδοποιήσεις στο κινητό τους, δευτερόλεπτα πριν το κύμα του σεισμού φτάσει σε αυτούς" }, { "kind": "news report", "citation": "in.gr (2025). Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό. in.gr, 15 May 2025, 11:02.", "title": "Πώς θα ενεργοποιήσετε την εφαρμογή της Google που προειδοποιεί για σεισμό", "url": "https://www.in.gr/2025/05/15/in-science/technology/pos-tha-energopoiisete-tin-efarmogi-tis-google-pou-proeidopoiei-gia-seismo", "date": "2025-05-15", "written_by": "independent", "quote": "Μια υπηρεσία έγκαιρης προειδοποίησης για σεισμούς που κρύβεται στο λειτουργικό σύστημα Android ήταν αυτή που ενημέρωσε πολλούς χρήστες για τον σεισμό των 6,1 βαθμών" }, { "kind": "news report", "citation": "Alphafreepress (2025). Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android. Alphafreepress.gr, 14 May 2025, 20:42.", "title": "Κάσος σεισμός 6,1 Ρίχτερ: Πώς λειτουργεί το σύστημα προειδοποίησης στα Android", "url": "https://www.alphafreepress.gr/2025/05/14/ellada/kasos-seismos-61-rixter-pos-leitourgei-to-systima-proeidopoiisis-sta-android", "date": "2025-05-14", "written_by": "independent", "quote": "το σύστημα σεισμικής ειδοποίησης της Google καταφέρνει να στείλει ενημέρωση στον πολίτη πριν φτάσει το κύμα της δόνησης στην περιοχή του" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 6.0 - 20 km SSE of Fry, Greece (event us7000pz2p, 2025-05-13 22:51:15 UTC, depth 76 km). USGS Earthquake Hazards Program.", "title": "M 6.0 - 20 km SSE of Fry, Greece", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pz2p", "date": "2025-05-13", "written_by": "independent", "quote": "M 6.0 - 20 km SSE of Fry, Greece" }, { "kind": "press release", "citation": "Stogaitis M (2020). Earthquake detection and early alerts, now on your Android phone. Google, The Keyword, 11 August 2020.", "title": "Earthquake detection and early alerts, now on your Android phone", "url": "https://blog.google/products/android/earthquake-detection-and-alerts/", "date": "2020-08-11", "written_by": "makers", "quote": "The server then combines information from many phones to figure out if an earthquake is happening." }, { "kind": "press release", "citation": "Google (n.d.). Android early earthquake warnings. Google Crisis Resilience.", "title": "Android early earthquake warnings", "url": "https://crisisresilience.google/android-early-earthquake-warnings", "written_by": "makers", "quote": "These alerts are only sent for earthquakes of magnitude 4.5 or greater." }, { "kind": "peer-reviewed study", "citation": "Allen RM, Barski A, Berman M, et al. (2025). Global earthquake detection and warning using Android phones. Science 389(6757):254-259. PMID 40674485.", "title": "Global earthquake detection and warning using Android phones", "url": "https://doi.org/10.1126/science.ads4779", "date": "2025-07-17", "written_by": "makers", "quote": "We show how smartphone-based earthquake detection algorithms can be implemented at scale and improved through postevent analysis." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Android users in Crete and the Dodecanese got Google's quake alert seconds before the M6.0 (Greek press 6.1) Kasos quake of 14 May 2025.", "account": "At 01:51 local time on Wednesday 14 May 2025 (22:51 UTC on 13 May) a magnitude 6.0 (USGS; Greek outlets 6.1) earthquake struck. It struck 20 km south-south-east of Fry on Kasos, between Kasos and Karpathos, at 76 km depth. USGS logged 931 felt reports and a green alert level. Newsbomb, GizChina Greece, in.gr and Alphafreepress reported on 14 and 15 May on Google's Android Earthquake Alerts System. In Europe it detects quakes from phone accelerometers rather than seismographs. It notified users in Crete, the Dodecanese and farther away seconds before the shaking. Notice came by message and an audible signal similar to the 112 alert. None of the reports names a recipient, gives a lead time in seconds, or mentions damage or injuries." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Android Earthquake Alerts System (crowdsourced phone-accelerometer detection; alerts for magnitude 4.5 and above)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Google's Android Earthquake Alerts reached phones in Crete and the Dodecanese seconds before the 14 May 2025 M6.0 (Greek press 6.1) Kasos quake", "headline": "Google alerts Crete phones seconds before the M6.0 Kasos quake" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c434c4947e2cacd4aa85a380b8afca94ec0bad41d6ad884073cdbbb28fd816a4" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At 01:51 local time on Wednesday 14 May 2025 (22:51 UTC on 13 May) a magnitude 6.0 (USGS; Greek outlets 6.1) earthquake struck. It struck 20 km south-south-east of Fry on Kasos, between Kasos and Karpathos, at 76 km depth. USGS logged 931 felt reports and a green alert level. Newsbomb, GizChina Greece, in.gr and Alphafreepress reported on 14 and 15 May on Google's Android Earthquake Alerts System. In Europe it detects quakes from phone accelerometers rather than seismographs. It notified users in Crete, the Dodecanese and farther away seconds before the shaking. Notice came by message and an audible signal similar to the 112 alert. None of the reports names a recipient, gives a lead time in seconds, or mentions damage or injuries.", "replication": { "produced_by": [ "A magnitude 6.0 (USGS) quake above the system's 4.5 alert threshold, centered offshore south of Kasos at about 76 km depth. A push alert could therefore outrun the slower waves to Crete and the Dodecanese.", "Enough Android phones near the epicentre with the Earthquake Alerts setting on to trigger Google's server-side detection. In Europe the system uses the accelerometers in phones instead of seismographs (in.gr).", "Receiving phones with location (GPS) enabled and an internet connection, which Alphafreepress lists as requirements for the alerts" ], "must_hold": [ "The server's magnitude and location estimate must be right and early. The 2025 Science paper reports that only 36% of alert recipients got the alert before shaking.", "Recipients must know what to do with seconds of notice. The Greek reports document no protective action by anyone who received the alert.", "The phone must have the Earthquake Alerts setting enabled (Alphafreepress: Settings > Safety & Emergency > Earthquake Alerts). The feature must be supported in the region." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0131", "title": "KTÜ students' AI early-warning app pings phones about 30 seconds before a Kulu quake is felt at the Turkish parliament, 15 May 2025", "summary": "KTÜ students' AI quake app alerted phones about 30 s before a Kulu quake (DHA 5.2, USGS 5.0) was felt at Turkey's parliament, 15 May 2025.", "date_observed": "2025-05-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 15 May 2025 software-engineering students from Karadeniz Technical University were presenting their Erken Uyarı Merkezi (Early Warning Center) to members of parliament. DHA's report describes it as an AI-based earthquake early-warning system. During the presentation, in the TBMM Public Relations building in Ankara, a quake centered in Kulu, Konya, was felt in the capital. DHA gave the magnitude as 5.2. USGS lists M5.0 at 15:46 local time (12:46:37 UTC), 14 km east-north-east of Kulu at 10 km depth. Student Birkan Yılmaz said notifications had reached their phones 30 seconds before the quake. Students, some MPs and building staff went outside. The read reports mention no damage or injuries.", "category": "protective response", "unexpected": false, "purpose": "A student-built earthquake early-warning system meant to notify phones before shaking arrives. Warning the room before the Kulu quake was felt was that intended function, demonstrated live during the team's own presentation to MPs.", "system": "Erken Uyarı Merkezi (Early Warning Center), AI-based earthquake early-warning system built by Karadeniz Technical University software-engineering students", "model_version": null, "developer": "Karadeniz Technical University (KTÜ) software-engineering students (DHA); no company or faculty lead named", "deployer": "Karadeniz Technical University (student team), demonstrating the system at the TBMM Public Relations building", "location": "Ankara, Turkey", "domain": "Disaster risk reduction / earthquake early warning", "segment": "Student prototype demonstrated to parliamentarians", "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented.", "registry_ids": { "oecd_aim": "2025-05-15-ad86" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "MPs, students and staff in the TBMM Public Relations building got about 30 seconds' notice, on the developer's own account. They went outside. No damage or injury is reported, so the benefit is the notice itself." } ], "ai_role": { "status": "assessed", "statement": "The system is called yapay zeka tabanlı (AI-based) in DHA's report, on the students' description. None of the read reports explains how it detects quakes, what data it uses, or whether the alert time was logged. The 30-second lead is the statement of student Birkan Yılmaz, a member of the team that built it. DHA carried it and Haberler, Yeni Akit and Yeni Çağ reproduced it. No MP, AFAD or Kandilli comment on the alert was found. Leaving the building was a human response to the notification and to the shaking." }, "evidence": [ { "kind": "news report", "citation": "DHA / Haberler.com (2025). Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti. Haberler.com, 15 May 2025, 18:48.", "title": "Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti", "url": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Akit (2025). Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği. Yeni Akit, 15 May 2025, 18:58.", "title": "Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği", "url": "https://www.yeniakit.com.tr/haber/milletvekilleri-deprem-konusurken-depreme-yakalandi-tbmmde-deprem-panigi-1933002.html", "date": "2025-05-15", "written_by": "independent", "quote": "yapay zeka tabanlı deprem erken uyarı sistemi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Erken uyarı sistemini vekillere anlatırken depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 21:33.", "title": "Erken uyarı sistemini vekillere anlatırken depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/erken-uyar%C4%B1-sistemini-vekillere-anlatirken-depreme-yakalandilar-915433h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 23:45.", "title": "Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/deprem-erken-uyar%C4%B1-sistemini-anlatirken-tbmmde-depreme-yakalandilar-915462h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Öğrenciler, bazı vekiller ve binada çalışanlarla birlikte dışarıya çıktı" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 5.0 - 14 km ENE of Kulu, Turkey (event us7000pzcl, 2025-05-15 12:46:37 UTC, depth 10 km). USGS Earthquake Hazards Program.", "title": "M 5.0 - 14 km ENE of Kulu, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pzcl", "date": "2025-05-15", "written_by": "independent", "quote": "M 5.0 - 14 km ENE of Kulu, Turkey" } ], "replication": { "produced_by": [ "A quake large enough to be felt in Ankara from an epicentre in Kulu, Konya (DHA 5.2; USGS M5.0 at 10 km depth). This left a gap between detection and the arrival of shaking in the capital.", "The team's own phones carrying the app, with connectivity inside the TBMM building, during a live demonstration to MPs", "An audience already primed by the presentation to treat the notification as a cue to leave" ], "must_hold": [ "The alert must arrive before the shaking. Here the lead time is the developer's statement, with no independent log or official timing.", "The detection source and false-alarm rate are undocumented in the read reports. Reliability beyond this one event is therefore unknown.", "Recipients must act on the notice. Here students, some MPs and staff went outside." ], "echoes": [] }, "paired_incident": null, "headline": "KTÜ students' app pings phones about 30 seconds before a quake", "metric": "notifications had reached their phones 30 seconds before the quake", "comparator": { "against": "feeling the quake with no warning", "before": null, "after": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi", "basis": "assumed", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi, yanımızdaki vekillere bunun bilgisini sağladık ve öncesinde çıktık.", "url": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi" }, "later": { "status": "unknown", "date": null, "note": "No later report on the KTÜ students' Erken Uyarı Merkezi was found.", "quote": null, "url": null }, "value": null, "developer_country": "Turkey", "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. All four readable sources carry the same DHA report; ensonhaber.com and gercekgundem.com returned HTTP 403 and were not read. USGS lists the Kulu event as M5.0 mww at 2025–05–15T12:46:37 UTC, 10 km depth, 14 km ENE of Kulu; DHA reports 5.2. The system name Erken Uyarı Merkezi appears in the Yeni Çağ texts. No KTÜ, AFAD or parliamentary statement was found; web search was unavailable in this session. Filed as protective response with prevention unproven as the classifier proposed: the warning is documented only by the developer's statement in a DHA report, and no harm was averted.", "source": "https://oecd.ai/en/incidents/2025-05-15-ad86", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Karadeniz_Technical_University; https://en.wikipedia.org/wiki/Karadeniz_Technical_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Karadeniz Technical University.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports and one independent dataset. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0131", "catalog_version": "1.0.0", "source_fingerprint": "047c86dedff83ae19f523631d37cf8f8a36e573639fab4ede8bc861ad3b6d92c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0131-source-0001", "AIBD-0131-source-0002", "AIBD-0131-source-0003", "AIBD-0131-source-0004", "AIBD-0131-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Karadeniz Technical University (KTÜ) software-engineering students (DHA); no company or faculty lead named", "deployer": "Karadeniz Technical University (student team), demonstrating the system at the TBMM Public Relations building" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system is called yapay zeka tabanlı (AI-based) in DHA's report, on the students' description. None of the read reports explains how it detects quakes, what data it uses, or whether the alert time was logged. The 30-second lead is the statement of student Birkan Yılmaz, a member of the team that built it. DHA carried it and Haberler, Yeni Akit and Yeni Çağ reproduced it. No MP, AFAD or Kandilli comment on the alert was found. Leaving the building was a human response to the notification and to the shaking." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The system is called yapay zeka tabanlı (AI-based) in DHA's report, on the students' description. None of the read reports explains how it detects quakes, what data it uses, or whether the alert time was logged. The 30-second lead is the statement of student Birkan Yılmaz, a member of the team that built it. DHA carried it and Haberler, Yeni Akit and Yeni Çağ reproduced it. No MP, AFAD or Kandilli comment on the alert was found. Leaving the building was a human response to the notification and to the shaking." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "MPs, students and staff in the TBMM Public Relations building got about 30 seconds' notice, on the developer's own account. They went outside. No damage or injury is reported, so the benefit is the notice itself." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports and one independent dataset. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "MPs, students and staff in the TBMM Public Relations building got about 30 seconds' notice, on the developer's own account. They went outside. No damage or injury is reported, so the benefit is the notice itself." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "MPs, students and staff in the TBMM Public Relations building got about 30 seconds' notice, on the developer's own account. They went outside. No damage or injury is reported, so the benefit is the notice itself." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "notifications had reached their phones 30 seconds before the quake", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-05-15-ad86" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later report on the KTÜ students' Erken Uyarı Merkezi was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0131" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "An earthquake warning is read as a detection mechanism; no averted injury is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 15 May 2025 software-engineering students from Karadeniz Technical University were presenting their Erken Uyarı Merkezi (Early Warning Center) to members of parliament. DHA's report describes it as an AI-based earthquake early-warning system. During the presentation, in the TBMM Public Relations building in Ankara, a quake centered in Kulu, Konya, was felt in the capital. DHA gave the magnitude as 5.2. USGS lists M5.0 at 15:46 local time (12:46:37 UTC), 14 km east-north-east of Kulu at 10 km depth. Student Birkan Yılmaz said notifications had reached their phones 30 seconds before the quake. Students, some MPs and building staff went outside. The read reports mention no damage or injuries.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "MPs, students and staff in the TBMM Public Relations building got about 30 seconds' notice, on the developer's own account. They went outside. No damage or injury is reported, so the benefit is the notice itself." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "A student-built earthquake early-warning system meant to notify phones before shaking arrives. Warning the room before the Kulu quake was felt was that intended function, demonstrated live during the team's own presentation to MPs." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ankara, Turkey", "developer_country": "Turkey", "deployer_country": "Turkey" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "A student-built earthquake early-warning system meant to notify phones before shaking arrives. Warning the room before the Kulu quake was felt was that intended function, demonstrated live during the team's own presentation to MPs." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-15", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. All four readable sources carry the same DHA report; ensonhaber.com and gercekgundem.com returned HTTP 403 and were not read. USGS lists the Kulu event as M5.0 mww at 2025–05–15T12:46:37 UTC, 10 km depth, 14 km ENE of Kulu; DHA reports 5.2. The system name Erken Uyarı Merkezi appears in the Yeni Çağ texts. No KTÜ, AFAD or parliamentary statement was found; web search was unavailable in this session. Filed as protective response with prevention unproven as the classifier proposed: the warning is documented only by the developer's statement in a DHA report, and no harm was averted.", "source": "https://oecd.ai/en/incidents/2025-05-15-ad86", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Karadeniz_Technical_University; https://en.wikipedia.org/wiki/Karadeniz_Technical_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Karadeniz Technical University.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A quake large enough to be felt in Ankara from an epicentre in Kulu, Konya (DHA 5.2; USGS M5.0 at 10 km depth). This left a gap between detection and the arrival of shaking in the capital.", "The team's own phones carrying the app, with connectivity inside the TBMM building, during a live demonstration to MPs", "An audience already primed by the presentation to treat the notification as a cue to leave" ], "must_hold": [ "The alert must arrive before the shaking. Here the lead time is the developer's statement, with no independent log or official timing.", "The detection source and false-alarm rate are undocumented in the read reports. Reliability beyond this one event is therefore unknown.", "Recipients must act on the notice. Here students, some MPs and staff went outside." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. All four readable sources carry the same DHA report; ensonhaber.com and gercekgundem.com returned HTTP 403 and were not read. USGS lists the Kulu event as M5.0 mww at 2025–05–15T12:46:37 UTC, 10 km depth, 14 km ENE of Kulu; DHA reports 5.2. The system name Erken Uyarı Merkezi appears in the Yeni Çağ texts. No KTÜ, AFAD or parliamentary statement was found; web search was unavailable in this session. Filed as protective response with prevention unproven as the classifier proposed: the warning is documented only by the developer's statement in a DHA report, and no harm was averted.", "source": "https://oecd.ai/en/incidents/2025-05-15-ad86", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Karadeniz_Technical_University; https://en.wikipedia.org/wiki/Karadeniz_Technical_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Karadeniz Technical University.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Disaster risk reduction / earthquake early warning", "segment": "Student prototype demonstrated to parliamentarians" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "DHA / Haberler.com (2025). Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti. Haberler.com, 15 May 2025, 18:48.", "title": "Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti", "url": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Akit (2025). Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği. Yeni Akit, 15 May 2025, 18:58.", "title": "Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği", "url": "https://www.yeniakit.com.tr/haber/milletvekilleri-deprem-konusurken-depreme-yakalandi-tbmmde-deprem-panigi-1933002.html", "date": "2025-05-15", "written_by": "independent", "quote": "yapay zeka tabanlı deprem erken uyarı sistemi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Erken uyarı sistemini vekillere anlatırken depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 21:33.", "title": "Erken uyarı sistemini vekillere anlatırken depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/erken-uyar%C4%B1-sistemini-vekillere-anlatirken-depreme-yakalandilar-915433h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 23:45.", "title": "Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/deprem-erken-uyar%C4%B1-sistemini-anlatirken-tbmmde-depreme-yakalandilar-915462h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Öğrenciler, bazı vekiller ve binada çalışanlarla birlikte dışarıya çıktı" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 5.0 - 14 km ENE of Kulu, Turkey (event us7000pzcl, 2025-05-15 12:46:37 UTC, depth 10 km). USGS Earthquake Hazards Program.", "title": "M 5.0 - 14 km ENE of Kulu, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pzcl", "date": "2025-05-15", "written_by": "independent", "quote": "M 5.0 - 14 km ENE of Kulu, Turkey" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0131-source-0001", "AIBD-0131-source-0002", "AIBD-0131-source-0003", "AIBD-0131-source-0004", "AIBD-0131-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "DHA / Haberler.com (2025). Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti. Haberler.com, 15 May 2025, 18:48.", "title": "Karadeniz Teknik Üniversitesi Öğrencileri TBMM'de Depremi Hissetti", "url": "https://www.haberler.com/guncel/karadeniz-teknik-universitesi-ogrencileri-tbmm-de-depremi-hissetti-18634729-haberi", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Akit (2025). Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği. Yeni Akit, 15 May 2025, 18:58.", "title": "Milletvekilleri deprem konuşurken depreme yakalandı! TBMM'de deprem paniği", "url": "https://www.yeniakit.com.tr/haber/milletvekilleri-deprem-konusurken-depreme-yakalandi-tbmmde-deprem-panigi-1933002.html", "date": "2025-05-15", "written_by": "independent", "quote": "yapay zeka tabanlı deprem erken uyarı sistemi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Erken uyarı sistemini vekillere anlatırken depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 21:33.", "title": "Erken uyarı sistemini vekillere anlatırken depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/erken-uyar%C4%B1-sistemini-vekillere-anlatirken-depreme-yakalandilar-915433h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Bu deprem olmadan 30 saniye öncesinde telefonlarımıza bildirim geldi" }, { "kind": "news report", "citation": "DHA / Yeni Çağ (2025). Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar. Yeniçağ Gazetesi, 15 May 2025, 23:45.", "title": "Deprem erken uyarı sistemini anlatırken TBMM'de depreme yakalandılar", "url": "https://www.yenicaggazetesi.com/deprem-erken-uyar%C4%B1-sistemini-anlatirken-tbmmde-depreme-yakalandilar-915462h.htm", "date": "2025-05-15", "written_by": "independent", "quote": "Öğrenciler, bazı vekiller ve binada çalışanlarla birlikte dışarıya çıktı" }, { "kind": "dataset", "citation": "U.S. Geological Survey (2025). M 5.0 - 14 km ENE of Kulu, Turkey (event us7000pzcl, 2025-05-15 12:46:37 UTC, depth 10 km). USGS Earthquake Hazards Program.", "title": "M 5.0 - 14 km ENE of Kulu, Turkey", "url": "https://earthquake.usgs.gov/earthquakes/eventpage/us7000pzcl", "date": "2025-05-15", "written_by": "independent", "quote": "M 5.0 - 14 km ENE of Kulu, Turkey" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "KTÜ students' AI quake app alerted phones about 30 s before a Kulu quake (DHA 5.2, USGS 5.0) was felt at Turkey's parliament, 15 May 2025.", "account": "On 15 May 2025 software-engineering students from Karadeniz Technical University were presenting their Erken Uyarı Merkezi (Early Warning Center) to members of parliament. DHA's report describes it as an AI-based earthquake early-warning system. During the presentation, in the TBMM Public Relations building in Ankara, a quake centered in Kulu, Konya, was felt in the capital. DHA gave the magnitude as 5.2. USGS lists M5.0 at 15:46 local time (12:46:37 UTC), 14 km east-north-east of Kulu at 10 km depth. Student Birkan Yılmaz said notifications had reached their phones 30 seconds before the quake. Students, some MPs and building staff went outside. The read reports mention no damage or injuries." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Erken Uyarı Merkezi (Early Warning Center), AI-based earthquake early-warning system built by Karadeniz Technical University software-engineering students" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Karadeniz Technical University (KTÜ) software-engineering students (DHA); no company or faculty lead named" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "KTÜ students' AI early-warning app pings phones about 30 seconds before a Kulu quake is felt at the Turkish parliament, 15 May 2025", "headline": "KTÜ students' app pings phones about 30 seconds before a quake" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "047c86dedff83ae19f523631d37cf8f8a36e573639fab4ede8bc861ad3b6d92c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 15 May 2025 software-engineering students from Karadeniz Technical University were presenting their Erken Uyarı Merkezi (Early Warning Center) to members of parliament. DHA's report describes it as an AI-based earthquake early-warning system. During the presentation, in the TBMM Public Relations building in Ankara, a quake centered in Kulu, Konya, was felt in the capital. DHA gave the magnitude as 5.2. USGS lists M5.0 at 15:46 local time (12:46:37 UTC), 14 km east-north-east of Kulu at 10 km depth. Student Birkan Yılmaz said notifications had reached their phones 30 seconds before the quake. Students, some MPs and building staff went outside. The read reports mention no damage or injuries.", "replication": { "produced_by": [ "A quake large enough to be felt in Ankara from an epicentre in Kulu, Konya (DHA 5.2; USGS M5.0 at 10 km depth). This left a gap between detection and the arrival of shaking in the capital.", "The team's own phones carrying the app, with connectivity inside the TBMM building, during a live demonstration to MPs", "An audience already primed by the presentation to treat the notification as a cue to leave" ], "must_hold": [ "The alert must arrive before the shaking. Here the lead time is the developer's statement, with no independent log or official timing.", "The detection source and false-alarm rate are undocumented in the read reports. Reliability beyond this one event is therefore unknown.", "Recipients must act on the notice. Here students, some MPs and staff went outside." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0132", "title": "Met Police live facial recognition flags David Cheneler, a sex offender breaching his order, alone with a six-year-old girl and a lock knife at Denmark Hill", "summary": "Met LFR flagged David Cheneler, 73, with a six-year-old and a lock knife at Denmark Hill, Jan 2025, breaching his SOPO; jailed 20 May 2025.", "date_observed": "2025-05-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In January 2025 Metropolitan Police Live Facial Recognition (LFR) cameras on a van at Denmark Hill identified David Cheneler, 73. He was under a 2019 Sexual Offences Prevention Order barring him from being alone with children under 14. The order followed a 2010 conviction for 15 counts of indecent assault on a female under 16 and five of gross indecency with a child. Officers found him with a six-year-old girl he had collected from school for her mother. The mother did not know his history. A lock knife was hidden in his belt buckle. He pleaded guilty at Wimbledon Magistrates' Court on 13 January 2025 to breaching the order and possessing an offensive weapon. On 20 May 2025 Kingston Crown Court jailed him for two years.", "category": "protective response", "unexpected": false, "purpose": "The Met deploys Live Facial Recognition cameras on police vans to identify people of interest and alert officers. Its LFR lead, Lindsey Chiswick, describes the aim as using data and technology to identify offenders that pose a risk to our communities. Identifying a sex offender in breach of his order was that purpose.", "system": "Live Facial Recognition (LFR) cameras mounted on a Metropolitan Police van", "model_version": null, "developer": null, "deployer": "Metropolitan Police Service", "location": "London, United Kingdom", "domain": "Policing / public protection", "segment": "Law enforcement use of live facial recognition in public places", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-05-20-368b" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "A six-year-old girl was taken out of unsupervised contact with a man convicted of 15 counts of indecent assault on a female under 16. He had collected her from school twice before and was carrying a lock knife. Material for one child, though the Met itself puts the averted abuse as possible rather than established." }, { "group": "societal", "depth": 1, "reason": "The public: a registered sex offender in breach of his order was jailed for two years. The Met presents this as removing a dangerous offender from the streets. The OECD Monitor tags the same event with human-rights, psychological, reputational and public-interest harm types. The wider benefit is therefore contested." } ], "ai_role": { "status": "assessed", "statement": "The LFR system did the identification. Cameras on the back of a van at Denmark Hill matched Cheneler's face and alerted officers, Southwark News reports. Finding the child and the knife, the arrest, the charges and the sentence were human and judicial acts. The offense itself existed only because of his 2019 order. The counterfactual is the Met's own hedge. DC Adam Pearce said it is possible that, had he not been identified, Cheneler could have gone on to abuse the child. No allegation about this occasion is reported. The readable source does not name the vendor or algorithm. The Met's press release is not among the sources." }, "evidence": [ { "kind": "news report", "citation": "Clarke I (2025). Sex offender caught in Denmark Hill thanks to facial recognition cameras. Southwark News, 21 May 2025.", "title": "Sex offender caught in Denmark Hill thanks to facial recognition cameras", "url": "https://southwarknews.co.uk/area/camberwell/sex-offender-caught-in-denmark-hill-thanks-to-facial-recognition-cameras/", "date": "2025-05-21", "written_by": "independent", "quote": "was caught in January in Denmark Hill after his face was identified by Live Facial Recognition cameras attached to the back of a van" }, { "kind": "other", "citation": "OECD.AI (2025). Live Facial Recognition Apprehends Sex Offender in Breach. OECD AI Incidents and Hazards Monitor, incident 2025-05-20-368b.", "title": "Live Facial Recognition Apprehends Sex Offender in Breach", "url": "https://oecd.ai/en/incidents/2025-05-20-368b", "date": null, "written_by": "independent", "quote": "prevented possible harm to the child and others" }, { "kind": "news report", "citation": "Biometric Update (2025). London police mark 1K arrests through live facial recognition. Biometric Update, 4 July 2025.", "title": "London police mark 1K arrests through live facial recognition", "url": "https://www.biometricupdate.com/202507/london-police-mark-1000-arrests-through-live-facial-recognition", "date": "2025-07-04", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A van-mounted LFR deployment at Denmark Hill in January 2025 and a face the system was able to identify. The match alerted officers on the spot.", "Officers who stopped him at once and found the child and the lock knife hidden in his belt buckle. They knew the terms of his 2019 Sexual Offences Prevention Order.", "A court record of the order and his 2010 convictions. This turned the stop into a guilty plea for breaching the order and possessing an offensive weapon." ], "must_hold": [ "The person must be known to the system and subject to conditions that make his presence with a child an offense. The benefit depends on the prior order, not on the camera alone.", "Officers must verify the match and intervene immediately. The child was found only because he was stopped on the spot.", "The deployment must be lawful and proportionate. The OECD Monitor files this same event under human-rights, psychological, reputational and public-interest harm types. The protective benefit therefore sits beside a contested surveillance practice." ], "echoes": [] }, "paired_incident": null, "headline": "Met LFR flags David Cheneler, a sex offender, alone with a child", "metric": "Kingston Crown Court jailed him for two years", "comparator": { "against": "not being identified (no live facial recognition check)", "before": "it’s possible if he hadn’t been identified using this technology, he could have gone on to abuse this child", "after": "his face was identified by Live Facial Recognition cameras attached to the back of a van, alerting officers to his presence", "basis": "assumed", "quote": "Although there were no allegations made towards David Cheneler on this occasion, it’s possible if he hadn’t been identified using this technology, he could have gone on to abuse this child.", "url": "https://southwarknews.co.uk/area/camberwell/sex-offender-caught-in-denmark-hill-thanks-to-facial-recognition-cameras/" }, "later": { "status": "scaled", "date": "2025-07-04", "note": "Six weeks after the sentencing the Met announced more than 1,000 LFR arrests since the start of 2024, with 773 people charged or cautioned and 93 registered sex offenders identified, and published Cheneler's case as one of its case studies.", "quote": "The police service published several case studies, including 73-year-old David Cheneler, a registered sex offender who was found to be with a six-year-old girl in breach of a court order.", "url": "https://www.biometricupdate.com/202507/london-police-mark-1000-arrests-through-live-facial-recognition" }, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Dated 20 May 2025, the sentencing at Kingston Crown Court and the Monitor's own date; the LFR identification happened in January 2025 (Southwark News), before his guilty plea at Wimbledon Magistrates' Court on Monday 13 January 2025, and no readable source gives the day. Of the Monitor's eleven sources only Southwark News could be read: BBC, Sky News, The Times, Daily Mail, Mirror, The Irish Sun, Daily Star and News Shopper are not fetchable by this tool, the London News Online and Parikiaki pages are gone, and the Met newsroom search did not render, so the Met's press release was not read and the vendor and algorithm are not named. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented because the Met's own officer put the averted abuse as possible and no allegation about this occasion is reported.", "source": "https://oecd.ai/en/incidents/2025-05-20-368b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://southwarknews.co.uk/area/camberwell/sex-offender-caught-in-denmark-hill-thanks-to-facial-recognition-cameras/; https://www.biometricupdate.com/202507/london-police-mark-1000-arrests-through-live-facial-recognition", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Metropolitan_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0132", "catalog_version": "1.0.0", "source_fingerprint": "7223682fc26832f65d4c5cca613d50d644e7ee22c73c627e7e0719274193e544", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0132-source-0001", "AIBD-0132-source-0002", "AIBD-0132-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Metropolitan Police Service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The LFR system did the identification. Cameras on the back of a van at Denmark Hill matched Cheneler's face and alerted officers, Southwark News reports. Finding the child and the knife, the arrest, the charges and the sentence were human and judicial acts. The offense itself existed only because of his 2019 order. The counterfactual is the Met's own hedge. DC Adam Pearce said it is possible that, had he not been identified, Cheneler could have gone on to abuse the child. No allegation about this occasion is reported. The readable source does not name the vendor or algorithm. The Met's press release is not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The LFR system did the identification. Cameras on the back of a van at Denmark Hill matched Cheneler's face and alerted officers, Southwark News reports. Finding the child and the knife, the arrest, the charges and the sentence were human and judicial acts. The offense itself existed only because of his 2019 order. The counterfactual is the Met's own hedge. DC Adam Pearce said it is possible that, had he not been identified, Cheneler could have gone on to abuse the child. No allegation about this occasion is reported. The readable source does not name the vendor or algorithm. The Met's press release is not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A six-year-old girl was taken out of unsupervised contact with a man convicted of 15 counts of indecent assault on a female under 16. He had collected her from school twice before and was carrying a lock knife. Material for one child, though the Met itself puts the averted abuse as possible rather than established." }, { "group": "societal", "depth": 1, "reason": "The public: a registered sex offender in breach of his order was jailed for two years. The Met presents this as removing a dangerous offender from the streets. The OECD Monitor tags the same event with human-rights, psychological, reputational and public-interest harm types. The wider benefit is therefore contested." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A six-year-old girl was taken out of unsupervised contact with a man convicted of 15 counts of indecent assault on a female under 16. He had collected her from school twice before and was carrying a lock knife. Material for one child, though the Met itself puts the averted abuse as possible rather than established." }, { "group": "societal", "depth": 1, "reason": "The public: a registered sex offender in breach of his order was jailed for two years. The Met presents this as removing a dangerous offender from the streets. The OECD Monitor tags the same event with human-rights, psychological, reputational and public-interest harm types. The wider benefit is therefore contested." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A six-year-old girl was taken out of unsupervised contact with a man convicted of 15 counts of indecent assault on a female under 16. He had collected her from school twice before and was carrying a lock knife. Material for one child, though the Met itself puts the averted abuse as possible rather than established." }, { "group": "societal", "depth": 1, "reason": "The public: a registered sex offender in breach of his order was jailed for two years. The Met presents this as removing a dangerous offender from the streets. The OECD Monitor tags the same event with human-rights, psychological, reputational and public-interest harm types. 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"value": { "kind": "record_fields", "fields": { "account": "In January 2025 Metropolitan Police Live Facial Recognition (LFR) cameras on a van at Denmark Hill identified David Cheneler, 73. 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Of the Monitor's eleven sources only Southwark News could be read: BBC, Sky News, The Times, Daily Mail, Mirror, The Irish Sun, Daily Star and News Shopper are not fetchable by this tool, the London News Online and Parikiaki pages are gone, and the Met newsroom search did not render, so the Met's press release was not read and the vendor and algorithm are not named. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented because the Met's own officer put the averted abuse as possible and no allegation about this occasion is reported.", "source": "https://oecd.ai/en/incidents/2025-05-20-368b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://southwarknews.co.uk/area/camberwell/sex-offender-caught-in-denmark-hill-thanks-to-facial-recognition-cameras/; https://www.biometricupdate.com/202507/london-police-mark-1000-arrests-through-live-facial-recognition", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Metropolitan_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A van-mounted LFR deployment at Denmark Hill in January 2025 and a face the system was able to identify. 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Biometric Update, 4 July 2025.", "title": "London police mark 1K arrests through live facial recognition", "url": "https://www.biometricupdate.com/202507/london-police-mark-1000-arrests-through-live-facial-recognition", "date": "2025-07-04", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Met LFR flagged David Cheneler, 73, with a six-year-old and a lock knife at Denmark Hill, Jan 2025, breaching his SOPO; jailed 20 May 2025.", "account": "In January 2025 Metropolitan Police Live Facial Recognition (LFR) cameras on a van at Denmark Hill identified David Cheneler, 73. He was under a 2019 Sexual Offences Prevention Order barring him from being alone with children under 14. The order followed a 2010 conviction for 15 counts of indecent assault on a female under 16 and five of gross indecency with a child. Officers found him with a six-year-old girl he had collected from school for her mother. The mother did not know his history. A lock knife was hidden in his belt buckle. He pleaded guilty at Wimbledon Magistrates' Court on 13 January 2025 to breaching the order and possessing an offensive weapon. On 20 May 2025 Kingston Crown Court jailed him for two years." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Live Facial Recognition (LFR) cameras mounted on a Metropolitan Police van" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Met Police live facial recognition flags David Cheneler, a sex offender breaching his order, alone with a six-year-old girl and a lock knife at Denmark Hill", "headline": "Met LFR flags David Cheneler, a sex offender, alone with a child" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7223682fc26832f65d4c5cca613d50d644e7ee22c73c627e7e0719274193e544" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In January 2025 Metropolitan Police Live Facial Recognition (LFR) cameras on a van at Denmark Hill identified David Cheneler, 73. He was under a 2019 Sexual Offences Prevention Order barring him from being alone with children under 14. The order followed a 2010 conviction for 15 counts of indecent assault on a female under 16 and five of gross indecency with a child. Officers found him with a six-year-old girl he had collected from school for her mother. The mother did not know his history. A lock knife was hidden in his belt buckle. He pleaded guilty at Wimbledon Magistrates' Court on 13 January 2025 to breaching the order and possessing an offensive weapon. On 20 May 2025 Kingston Crown Court jailed him for two years.", "replication": { "produced_by": [ "A van-mounted LFR deployment at Denmark Hill in January 2025 and a face the system was able to identify. The match alerted officers on the spot.", "Officers who stopped him at once and found the child and the lock knife hidden in his belt buckle. They knew the terms of his 2019 Sexual Offences Prevention Order.", "A court record of the order and his 2010 convictions. This turned the stop into a guilty plea for breaching the order and possessing an offensive weapon." ], "must_hold": [ "The person must be known to the system and subject to conditions that make his presence with a child an offense. The benefit depends on the prior order, not on the camera alone.", "Officers must verify the match and intervene immediately. The child was found only because he was stopped on the spot.", "The deployment must be lawful and proportionate. The OECD Monitor files this same event under human-rights, psychological, reputational and public-interest harm types. The protective benefit therefore sits beside a contested surveillance practice." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0236", "title": "OpenAI o3 finds CVE-2025–37899, a remote use-after-free in the Linux kernel's ksmbd; patched in all maintained branches", "summary": "Sean Heelan, benchmarking o3 on ksmbd with no scaffolding, had the model surface an unknown use-after-free in the SMB logoff handler; the kernel CNA published CVE-2025–37899 on 20 May 2025.", "date_observed": "2025-05-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Heelan's write-up followed on 22 May 2025. Heelan is an independent vulnerability researcher auditing ksmbd (the Linux kernel's in-kernel SMB3 server). He used a known bug (CVE-2025–37778) to benchmark OpenAI's o3 via the plain application programming interface (API), with no scaffolding, agents or tools. Given about 12,000 lines covering all SMB command handlers, o3 reported a previously unknown use-after-free in the handler for the SMB “logoff” command. sess->user can be freed while another connection bound to the same session still uses it. The Linux kernel CNA's record describes the fix (“ksmbd: fix use-after-free in session logoff”) with commits in five stable branches. Linuxiac reports the upstream response was fast and patches were merged for every maintained branch. Heelan calls it, to his knowledge, the first public case of a large language model (LLM) finding a vulnerability of that nature.", "category": "benefit created", "unexpected": false, "purpose": "General-purpose reasoning model used by the researcher to audit kernel source code for vulnerabilities.", "system": "OpenAI o3", "model_version": "o3", "developer": "OpenAI", "deployer": "Sean Heelan (independent researcher)", "location": null, "domain": "Cybersecurity / vulnerability research", "segment": "Technology", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "A remotely reachable kernel memory-safety bug was fixed across maintained branches before any reported exploitation. Exposure of ksmbd users is not quantified." }, { "group": "organizational", "depth": 1, "reason": "The kernel project received a report with a fix merged quickly, per Linuxiac." } ], "ai_role": { "status": "assessed", "statement": "The model produced the finding unprompted during a benchmark. Heelan selected the code, validated the report and handled disclosure. He notes the model also produced false positives in other runs. The account is the independent deployer's own, corroborated by the CVE record and third-party coverage, not by OpenAI." }, "evidence": [ { "kind": "report", "citation": "Sean Heelan, personal blog, 22 May 2025", "title": "How I used o3 to find CVE-2025-37899, a remote zeroday vulnerability in the Linux kernel’s SMB implementation", "url": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/", "date": "2025-05-22", "written_by": "deployer", "quote": "I found the vulnerability with nothing more complicated than the o3 API – no scaffolding, no agentic frameworks, no tool use." }, { "kind": "registry label", "citation": "CVE Program record CVE-2025-37899 (CNA: Linux), published 20 May 2025", "title": "CVE-2025-37899", "url": "https://www.cve.org/CVERecord?id=CVE-2025-37899", "date": "2025-05-20", "written_by": "independent", "quote": "The sess->user object can currently be in use by another thread, for example if another connection has sent a session setup request to bind to the session being free'd." }, { "kind": "news report", "citation": "Bobby Borisov, Linuxiac, 29 May 2025", "title": "ChatGPT’s o3 Model Found Remote Zeroday in Linux Kernel Code", "url": "https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "date": "2025-05-29", "written_by": "independent", "quote": "Upstream response was really fast, and the patches merged for every still-maintained kernel branch." } ], "replication": { "produced_by": [ "A code slice under roughly 10k-12k lines chosen by an expert", "Repeated model runs with reports triaged by a human", "A maintainer workflow that accepts and patches reports quickly" ], "must_hold": [ "Expert curation of context and validation of candidate bugs", "Tolerance for false positives across runs" ], "echoes": [] }, "paired_incident": null, "headline": "OpenAI o3 finds CVE-2025–37899, a use-after-free in ksmbd", "metric": null, "comparator": { "against": "Claude Sonnet 3.7 and Claude Sonnet 3.5 on the same 100-run benchmark (the known ksmbd Kerberos bug)", "before": "Claude Sonnet 3.7 finds it 3 out of 100 runs and Claude Sonnet 3.5 does not find it in 100 runs", "after": "o3 finds the kerberos authentication vulnerability in the benchmark in 8 of the 100 runs", "basis": "measured", "quote": "o3 finds the kerberos authentication vulnerability in the benchmark in 8 of the 100 runs. In another 66 of the runs o3 concludes there is no bug present in the code (false negatives), and the remaining 28 reports are false positives. For comparison, Claude Sonnet 3.7 finds it 3 out of 100 runs and Claude Sonnet 3.5 does not find it in 100 runs.", "url": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/" }, "later": { "status": "persisted", "date": "2025-05-29", "note": "Linuxiac reported that the upstream fix was merged quickly into every maintained kernel branch, and the CVE record lists five stable-branch commits.", "quote": "Upstream response was really fast, and the patches merged for every still-maintained kernel branch.", "url": "https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/; https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, a registry entry and the deployer's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0236", "catalog_version": "1.0.0", "source_fingerprint": "9cb79554fbd39e1a6ca90976eab27ce993eb349e7861e95de4647ab3e6f9a36c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0236-source-0001", "AIBD-0236-source-0002", "AIBD-0236-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "Sean Heelan (independent researcher)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model produced the finding unprompted during a benchmark. Heelan selected the code, validated the report and handled disclosure. He notes the model also produced false positives in other runs. The account is the independent deployer's own, corroborated by the CVE record and third-party coverage, not by OpenAI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The model produced the finding unprompted during a benchmark. Heelan selected the code, validated the report and handled disclosure. He notes the model also produced false positives in other runs. The account is the independent deployer's own, corroborated by the CVE record and third-party coverage, not by OpenAI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A remotely reachable kernel memory-safety bug was fixed across maintained branches before any reported exploitation. Exposure of ksmbd users is not quantified." }, { "group": "organizational", "depth": 1, "reason": "The kernel project received a report with a fix merged quickly, per Linuxiac." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, a registry entry and the deployer's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A remotely reachable kernel memory-safety bug was fixed across maintained branches before any reported exploitation. Exposure of ksmbd users is not quantified." }, { "group": "organizational", "depth": 1, "reason": "The kernel project received a report with a fix merged quickly, per Linuxiac." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A remotely reachable kernel memory-safety bug was fixed across maintained branches before any reported exploitation. Exposure of ksmbd users is not quantified." }, { "group": "organizational", "depth": 1, "reason": "The kernel project received a report with a fix merged quickly, per Linuxiac." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2025-05-29", "note": "Linuxiac reported that the upstream fix was merged quickly into every maintained kernel branch, and the CVE record lists five stable-branch commits.", "quote": "Upstream response was really fast, and the patches merged for every still-maintained kernel branch.", "url": "https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0236" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Heelan's write-up followed on 22 May 2025. Heelan is an independent vulnerability researcher auditing ksmbd (the Linux kernel's in-kernel SMB3 server). He used a known bug (CVE-2025–37778) to benchmark OpenAI's o3 via the plain application programming interface (API), with no scaffolding, agents or tools. Given about 12,000 lines covering all SMB command handlers, o3 reported a previously unknown use-after-free in the handler for the SMB “logoff” command. sess->user can be freed while another connection bound to the same session still uses it. The Linux kernel CNA's record describes the fix (“ksmbd: fix use-after-free in session logoff”) with commits in five stable branches. Linuxiac reports the upstream response was fast and patches were merged for every maintained branch. Heelan calls it, to his knowledge, the first public case of a large language model (LLM) finding a vulnerability of that nature.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A remotely reachable kernel memory-safety bug was fixed across maintained branches before any reported exploitation. Exposure of ksmbd users is not quantified." }, { "group": "organizational", "depth": 1, "reason": "The kernel project received a report with a fix merged quickly, per Linuxiac." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "General-purpose reasoning model used by the researcher to audit kernel source code for vulnerabilities." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "General-purpose reasoning model used by the researcher to audit kernel source code for vulnerabilities." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/; https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A code slice under roughly 10k-12k lines chosen by an expert", "Repeated model runs with reports triaged by a human", "A maintainer workflow that accepts and patches reports quickly" ], "must_hold": [ "Expert curation of context and validation of candidate bugs", "Tolerance for false positives across runs" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/; https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Cybersecurity / vulnerability research", "segment": "Technology" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Sean Heelan, personal blog, 22 May 2025", "title": "How I used o3 to find CVE-2025-37899, a remote zeroday vulnerability in the Linux kernel’s SMB implementation", "url": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/", "date": "2025-05-22", "written_by": "deployer", "quote": "I found the vulnerability with nothing more complicated than the o3 API – no scaffolding, no agentic frameworks, no tool use." }, { "kind": "registry label", "citation": "CVE Program record CVE-2025-37899 (CNA: Linux), published 20 May 2025", "title": "CVE-2025-37899", "url": "https://www.cve.org/CVERecord?id=CVE-2025-37899", "date": "2025-05-20", "written_by": "independent", "quote": "The sess->user object can currently be in use by another thread, for example if another connection has sent a session setup request to bind to the session being free'd." }, { "kind": "news report", "citation": "Bobby Borisov, Linuxiac, 29 May 2025", "title": "ChatGPT’s o3 Model Found Remote Zeroday in Linux Kernel Code", "url": "https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "date": "2025-05-29", "written_by": "independent", "quote": "Upstream response was really fast, and the patches merged for every still-maintained kernel branch." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0236-source-0001", "AIBD-0236-source-0002", "AIBD-0236-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Sean Heelan, personal blog, 22 May 2025", "title": "How I used o3 to find CVE-2025-37899, a remote zeroday vulnerability in the Linux kernel’s SMB implementation", "url": "https://sean.heelan.io/2025/05/22/how-i-used-o3-to-find-cve-2025-37899-a-remote-zeroday-vulnerability-in-the-linux-kernels-smb-implementation/", "date": "2025-05-22", "written_by": "deployer", "quote": "I found the vulnerability with nothing more complicated than the o3 API – no scaffolding, no agentic frameworks, no tool use." }, { "kind": "registry label", "citation": "CVE Program record CVE-2025-37899 (CNA: Linux), published 20 May 2025", "title": "CVE-2025-37899", "url": "https://www.cve.org/CVERecord?id=CVE-2025-37899", "date": "2025-05-20", "written_by": "independent", "quote": "The sess->user object can currently be in use by another thread, for example if another connection has sent a session setup request to bind to the session being free'd." }, { "kind": "news report", "citation": "Bobby Borisov, Linuxiac, 29 May 2025", "title": "ChatGPT’s o3 Model Found Remote Zeroday in Linux Kernel Code", "url": "https://linuxiac.com/chatgpt-o3-model-found-remote-zeroday-in-linux-kernel-code/", "date": "2025-05-29", "written_by": "independent", "quote": "Upstream response was really fast, and the patches merged for every still-maintained kernel branch." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Sean Heelan, benchmarking o3 on ksmbd with no scaffolding, had the model surface an unknown use-after-free in the SMB logoff handler; the kernel CNA published CVE-2025–37899 on 20 May 2025.", "account": "Heelan's write-up followed on 22 May 2025. Heelan is an independent vulnerability researcher auditing ksmbd (the Linux kernel's in-kernel SMB3 server). He used a known bug (CVE-2025–37778) to benchmark OpenAI's o3 via the plain application programming interface (API), with no scaffolding, agents or tools. Given about 12,000 lines covering all SMB command handlers, o3 reported a previously unknown use-after-free in the handler for the SMB “logoff” command. sess->user can be freed while another connection bound to the same session still uses it. The Linux kernel CNA's record describes the fix (“ksmbd: fix use-after-free in session logoff”) with commits in five stable branches. Linuxiac reports the upstream response was fast and patches were merged for every maintained branch. Heelan calls it, to his knowledge, the first public case of a large language model (LLM) finding a vulnerability of that nature." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model analyzed source code and identified a possible vulnerability for a researcher to verify." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "o3." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "o3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "OpenAI o3" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OpenAI o3 finds CVE-2025–37899, a remote use-after-free in the Linux kernel's ksmbd; patched in all maintained branches", "headline": "OpenAI o3 finds CVE-2025–37899, a use-after-free in ksmbd" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9cb79554fbd39e1a6ca90976eab27ce993eb349e7861e95de4647ab3e6f9a36c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Heelan's write-up followed on 22 May 2025. Heelan is an independent vulnerability researcher auditing ksmbd (the Linux kernel's in-kernel SMB3 server). He used a known bug (CVE-2025–37778) to benchmark OpenAI's o3 via the plain application programming interface (API), with no scaffolding, agents or tools. Given about 12,000 lines covering all SMB command handlers, o3 reported a previously unknown use-after-free in the handler for the SMB “logoff” command. sess->user can be freed while another connection bound to the same session still uses it. The Linux kernel CNA's record describes the fix (“ksmbd: fix use-after-free in session logoff”) with commits in five stable branches. Linuxiac reports the upstream response was fast and patches were merged for every maintained branch. Heelan calls it, to his knowledge, the first public case of a large language model (LLM) finding a vulnerability of that nature.", "replication": { "produced_by": [ "A code slice under roughly 10k-12k lines chosen by an expert", "Repeated model runs with reports triaged by a human", "A maintainer workflow that accepts and patches reports quickly" ], "must_hold": [ "Expert curation of context and validation of candidate bugs", "Tolerance for false positives across runs" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0325", "title": "ChatGPT's paraffin-oil advice may have saved Islam Adel's 17-year-old cousin after an aluminum phosphide “grain pill” ingestion in Assiut", "summary": "A Facebook post of 24 May 2025 credits ChatGPT with first aid. Assiut Faculty of Medicine dean Alaa Attia says that the youth had no phosphine symptoms and said he threw the pill into water.", "date_observed": "2025-05-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "El Balad (24 May 2025, 12:39) reproduces a Facebook post by Islam Adel, a commercial-control inspector. He wrote it at 1 a.m. after “24 hours” had passed since his cousin Mohamed Yousry (17) swallowed part of a “grain pill” (aluminum phosphide). The pill came from samples Adel had seized and kept at the family's old house. The cousin took it after a quarrel with his father. Adel writes that the Abnoub central hospital refused the case. He writes that within minutes he asked ChatGPT for the best course. It advised paraffin oil to coat the pill and limit phosphine release. The youth drank a bottle from a pharmacy before they went to Assiut University Hospital's poison reception. Doctors there said there was no treatment protocol and the case would die. He then gave instructions from “an advanced AI model and a limited-use trial version of GPT-5”. Nine bottles of paraffin oil were given in turn with breathing exercises. The cousin stayed conscious, vomited for hours and was discharged stable. Dostor (24 May 2025, 22:40) reports the post and the reply of Dr Alaa Attia, dean of the Faculty of Medicine at Assiut University. He said precise medical examinations showed no signs or symptoms of swallowing the pill. The youth denied taking it and admitted throwing it into a water basin. The dean added that the hospital is researching paraffin oil with acetylcysteine as an adjunct. The protocol is experimental and not officially adopted. Masrawy (25 May 2025) quotes the dean that the youth, about 17, showed no clinical symptoms of phosphine poisoning. The team questioned him and he categorically denied swallowing the pill. He cited a family dispute over travel to Italy. Dostor (25 May 2025) adds toxicologist Dr Mahmoud Amr, founder of the National Poison Center. He says oils are indeed a necessary first aid in grain-pill poisoning. Al Jazeera Mubasher (26 May 2025) quotes Amr that the claim that paraffin oil rescues such a case “has no scientific basis”. It quotes Cairo University toxicologist Dr Nermin Hamdi that Assiut University denied the case involved the grain pill. Hamdi adds that giving oil is first aid, not treatment. The Monitor lists 13 syndications. Al Arabiya's syndication was not available. The ingestion date is not fixed by any source.", "category": "harm prevented", "unexpected": true, "purpose": "ChatGPT is a general-purpose assistant. The cousin used it for emergency first-aid advice and, by his account, for instructions during hospital care. The claimed benefit (a survival) is outside any stated purpose of the system.", "system": "ChatGPT (OpenAI), described in the post as 'an advanced AI model and a limited-use trial version of GPT-5'", "model_version": "GPT-5 trial version, per the cousin's post; unverified", "developer": "OpenAI", "deployer": "Islam Adel, the patient's cousin, as a consumer user", "location": "Abnoub and Assiut University Hospital, Assiut Governorate, Egypt", "domain": "Healthcare: emergency toxicology", "segment": "Consumer chatbot used for first-aid advice", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-05-24-415b" }, "ratings": [ { "group": "personal", "depth": null, "reason": "The survival claim rests on the cousin's post. The dean says that there was no poisoning to survive. No outcome attributable to the advice is therefore documented." }, { "group": "societal", "depth": null, "reason": "Al Jazeera Mubasher and Dostor report experts warning that the “trend” could kill. No wider effect is documented." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT's output (advice to give paraffin oil, then nine bottles in turn with breathing exercises) is documented only by the cousin's own post. The chat transcripts were not published (“too many to publish all”, per Masrawy's summary of the post). Dean Alaa Attia contradicts its effect: he says that the patient had no clinical signs of phosphine poisoning and denied swallowing the pill. Dr Nermin Hamdi's report that Assiut University denied the case involved the grain pill also contradicts it. Dr Mahmoud Amr says that oil is a recognized first aid but not a cure. Whether the hospital followed any of the AI's instructions is unsupported by any source other than the post." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-05-24-415b, 'AI Intervention Saves Teen from Poisoning' (AI-generated summary).", "title": "AI Intervention Saves Teen from Poisoning", "url": "https://oecd.ai/en/incidents/2025-05-24-415b", "date": "2025-05-24", "written_by": "independent", "quote": "The AI recommended immediately coating the pill with paraffin oil to mitigate poisoning effects, helping counteract doctors’ initial pessimism and contributing to the teen’s survival." }, { "kind": "news report", "citation": "Sada El Balad (Sara Abdallah), 24 May 2025, 'عاد من الموت. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة' (reproduces Islam Adel's Facebook post).", "title": "عاد من الموت.. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة", "url": "https://www.elbalad.news/6583785", "date": "2025-05-24", "written_by": "independent", "quote": "خلال دقائق قررت أسأل شات جي بي تي عن التصرف الأمثل فنصحني فورًا باستخدام زيت البرافين" }, { "kind": "news report", "citation": "Al-Dostor (Asmaa Ibrahim), 24 May 2025, 'الذكاء الاصطناعي السبب. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة'.", "title": "الذكاء الاصطناعي السبب.. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة", "url": "https://www.dostor.org/5081951", "date": "2025-05-24", "written_by": "independent", "quote": "كما أكد أن الشاب نفى تناوله للقرص وأقر بأنه ألقاه في حوض ماء" }, { "kind": "news report", "citation": "Masrawy (Mahmoud Agami, Assiut), 25 May 2025, 'عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"'.", "title": "عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"", "url": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "date": "2025-05-25", "written_by": "independent", "quote": "لم تظهر عليه أي أعراض سريرية تشير إلى تعرضه لتسمم بمادة الفوسفين الناتجة عن قرص الغلة" }, { "kind": "news report", "citation": "Al-Dostor, 25 May 2025, 'دراما إنقاذ \"قرص الغلة\" عبر الذكاء الاصطناعي. وخبراء يحذرون من كارثة محتملة' (quotes Dr Mahmoud Amr, founder of the National Poison Centre).", "title": "دراما إنقاذ “قرص الغلة” عبر الذكاء الاصطناعي.. وخبراء يحذرون من كارثة محتملة", "url": "https://www.dostor.org/5083066", "date": "2025-05-25", "written_by": "independent", "quote": "تناول الزيوت بالفعل يُعد من الإسعافات الأولية الضرورية في حالات التسمم بحبوب الغلة" }, { "kind": "news report", "citation": "Al Jazeera Mubasher (Sameh Gad), 26 May 2025, '\"قرص الغلة\" والمنشور الذي حيّر المصريين. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من \"الترند القاتل\"' (quotes Dr Nermin Hamdi and Dr Mahmoud Mohamed Amr).", "title": "“قرص الغلة” والمنشور الذي حيّر المصريين.. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من “الترند القاتل”", "url": "https://www.aljazeeramubasher.net/news/reports/2025/5/26/%d9%82%d8%b1%d8%b5-%d8%a7%d9%84%d8%ba%d9%84%d8%a9-%d9%88%d8%a7%d9%84%d9%85%d9%86%d8%b4%d9%88%d8%b1-%d8%a7%d9%84%d8%b0%d9%8a-%d8%ad%d9%8a%d8%b1", "date": "2025-05-26", "written_by": "independent", "quote": "إعطاء المصاب بالتسمم أي نوع من الزيوت هو بمثابة إسعاف أولي وليس علاجا" } ], "replication": { "produced_by": [ "A layperson prompting ChatGPT for first aid during a suspected aluminum phosphide ingestion", "Paraffin oil bought from a pharmacy and given before and, by the cousin's account, during hospital care" ], "must_hold": [ "That the pill was swallowed at all, which the treating dean says the patient denied", "Clinical confirmation of phosphine poisoning and of any effect of the oil. Assiut's paraffin-oil-plus-acetylcysteine protocol is described by the dean as experimental and not officially adopted." ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT's first-aid advice may have saved a teen in Assiut", "metric": null, "comparator": null, "later": { "status": "reversed", "date": "2025-05-25", "note": "The next day the dean of Assiut University's Faculty of Medicine told Masrawy that the youth showed no clinical signs of phosphine poisoning and had categorically denied swallowing the pill, and on 26 May a toxicologist told Al Jazeera Mubasher that the claim that paraffin oil rescues such a case has no scientific basis.", "quote": "فى المقابل، أوضح عميد كلية طب أسيوط، لـ\"مصراوي\" أن الشاب، البالغ من العمر نحو 17 عامًا، لم تظهر عليه أي أعراض سريرية تشير إلى تعرضه لتسمم بمادة الفوسفين الناتجة عن قرص الغلة، وهي أعراض معروفة وواضحة في مثل هذه الحالات. وأضاف أن الفريق الطبي تابع الحالة بدقة، ووجّه للشاب عدة استفسارات حول تناوله للقرص، إلا أنه نفى ذلك بشكل قاطع، مؤكدًا أنه ألقى القرص في حوض ماء ولم يبتلعه.", "url": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": "the dean denies that there was a poisoning", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the dean denies that there was a poisoning.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0325", "catalog_version": "1.0.0", "source_fingerprint": "c89c1581d594839bae821d714dc3afa69acacd79a4a7a7f16669b13a0928a51a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0325-source-0001", "AIBD-0325-source-0002", "AIBD-0325-source-0003", "AIBD-0325-source-0004", "AIBD-0325-source-0005", "AIBD-0325-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "Islam Adel, the patient's cousin, as a consumer user" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ChatGPT's output (advice to give paraffin oil, then nine bottles in turn with breathing exercises) is documented only by the cousin's own post. The chat transcripts were not published (“too many to publish all”, per Masrawy's summary of the post). Dean Alaa Attia contradicts its effect: he says that the patient had no clinical signs of phosphine poisoning and denied swallowing the pill. Dr Nermin Hamdi's report that Assiut University denied the case involved the grain pill also contradicts it. Dr Mahmoud Amr says that oil is a recognized first aid but not a cure. Whether the hospital followed any of the AI's instructions is unsupported by any source other than the post." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "ChatGPT's output (advice to give paraffin oil, then nine bottles in turn with breathing exercises) is documented only by the cousin's own post. The chat transcripts were not published (“too many to publish all”, per Masrawy's summary of the post). Dean Alaa Attia contradicts its effect: he says that the patient had no clinical signs of phosphine poisoning and denied swallowing the pill. Dr Nermin Hamdi's report that Assiut University denied the case involved the grain pill also contradicts it. Dr Mahmoud Amr says that oil is a recognized first aid but not a cure. Whether the hospital followed any of the AI's instructions is unsupported by any source other than the post." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The survival claim rests on the cousin's post. The dean says that there was no poisoning to survive. No outcome attributable to the advice is therefore documented." }, { "group": "societal", "reason": "Al Jazeera Mubasher and Dostor report experts warning that the “trend” could kill. 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No wider effect is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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"not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-05-24-415b" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "reversed", "date": "2025-05-25", "note": "The next day the dean of Assiut University's Faculty of Medicine told Masrawy that the youth showed no clinical signs of phosphine poisoning and had categorically denied swallowing the pill, and on 26 May a toxicologist told Al Jazeera Mubasher that the claim that paraffin oil rescues such a case has no scientific basis.", "quote": "فى المقابل، أوضح عميد كلية طب أسيوط، لـ\"مصراوي\" أن الشاب، البالغ من العمر نحو 17 عامًا، لم تظهر عليه أي أعراض سريرية تشير إلى تعرضه لتسمم بمادة الفوسفين الناتجة عن قرص الغلة، وهي أعراض معروفة وواضحة في مثل هذه الحالات. وأضاف أن الفريق الطبي تابع الحالة بدقة، ووجّه للشاب عدة استفسارات حول تناوله للقرص، إلا أنه نفى ذلك بشكل قاطع، مؤكدًا أنه ألقى القرص في حوض ماء ولم يبتلعه.", "url": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0325" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "El Balad (24 May 2025, 12:39) reproduces a Facebook post by Islam Adel, a commercial-control inspector. He wrote it at 1 a.m. after “24 hours” had passed since his cousin Mohamed Yousry (17) swallowed part of a “grain pill” (aluminum phosphide). The pill came from samples Adel had seized and kept at the family's old house. The cousin took it after a quarrel with his father. Adel writes that the Abnoub central hospital refused the case. He writes that within minutes he asked ChatGPT for the best course. It advised paraffin oil to coat the pill and limit phosphine release. The youth drank a bottle from a pharmacy before they went to Assiut University Hospital's poison reception. Doctors there said there was no treatment protocol and the case would die. He then gave instructions from “an advanced AI model and a limited-use trial version of GPT-5”. Nine bottles of paraffin oil were given in turn with breathing exercises. The cousin stayed conscious, vomited for hours and was discharged stable. Dostor (24 May 2025, 22:40) reports the post and the reply of Dr Alaa Attia, dean of the Faculty of Medicine at Assiut University. He said precise medical examinations showed no signs or symptoms of swallowing the pill. The youth denied taking it and admitted throwing it into a water basin. The dean added that the hospital is researching paraffin oil with acetylcysteine as an adjunct. The protocol is experimental and not officially adopted. Masrawy (25 May 2025) quotes the dean that the youth, about 17, showed no clinical symptoms of phosphine poisoning. The team questioned him and he categorically denied swallowing the pill. He cited a family dispute over travel to Italy. Dostor (25 May 2025) adds toxicologist Dr Mahmoud Amr, founder of the National Poison Center. He says oils are indeed a necessary first aid in grain-pill poisoning. Al Jazeera Mubasher (26 May 2025) quotes Amr that the claim that paraffin oil rescues such a case “has no scientific basis”. It quotes Cairo University toxicologist Dr Nermin Hamdi that Assiut University denied the case involved the grain pill. Hamdi adds that giving oil is first aid, not treatment. The Monitor lists 13 syndications. Al Arabiya's syndication was not available. The ingestion date is not fixed by any source.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The survival claim rests on the cousin's post. The dean says that there was no poisoning to survive. No outcome attributable to the advice is therefore documented." }, { "group": "societal", "reason": "Al Jazeera Mubasher and Dostor report experts warning that the “trend” could kill. No wider effect is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "ChatGPT is a general-purpose assistant. The cousin used it for emergency first-aid advice and, by his account, for instructions during hospital care. The claimed benefit (a survival) is outside any stated purpose of the system." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Abnoub and Assiut University Hospital, Assiut Governorate, Egypt", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose assistant. The cousin used it for emergency first-aid advice and, by his account, for instructions during hospital care. The claimed benefit (a survival) is outside any stated purpose of the system." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-05-24", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the dean denies that there was a poisoning.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A layperson prompting ChatGPT for first aid during a suspected aluminum phosphide ingestion", "Paraffin oil bought from a pharmacy and given before and, by the cousin's account, during hospital care" ], "must_hold": [ "That the pill was swallowed at all, which the treating dean says the patient denied", "Clinical confirmation of phosphine poisoning and of any effect of the oil. Assiut's paraffin-oil-plus-acetylcysteine protocol is described by the dean as experimental and not officially adopted." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the dean denies that there was a poisoning.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare: emergency toxicology", "segment": "Consumer chatbot used for first-aid advice" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-05-24-415b, 'AI Intervention Saves Teen from Poisoning' (AI-generated summary).", "title": "AI Intervention Saves Teen from Poisoning", "url": "https://oecd.ai/en/incidents/2025-05-24-415b", "date": "2025-05-24", "written_by": "independent", "quote": "The AI recommended immediately coating the pill with paraffin oil to mitigate poisoning effects, helping counteract doctors’ initial pessimism and contributing to the teen’s survival." }, { "kind": "news report", "citation": "Sada El Balad (Sara Abdallah), 24 May 2025, 'عاد من الموت. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة' (reproduces Islam Adel's Facebook post).", "title": "عاد من الموت.. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة", "url": "https://www.elbalad.news/6583785", "date": "2025-05-24", "written_by": "independent", "quote": "خلال دقائق قررت أسأل شات جي بي تي عن التصرف الأمثل فنصحني فورًا باستخدام زيت البرافين" }, { "kind": "news report", "citation": "Al-Dostor (Asmaa Ibrahim), 24 May 2025, 'الذكاء الاصطناعي السبب. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة'.", "title": "الذكاء الاصطناعي السبب.. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة", "url": "https://www.dostor.org/5081951", "date": "2025-05-24", "written_by": "independent", "quote": "كما أكد أن الشاب نفى تناوله للقرص وأقر بأنه ألقاه في حوض ماء" }, { "kind": "news report", "citation": "Masrawy (Mahmoud Agami, Assiut), 25 May 2025, 'عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"'.", "title": "عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"", "url": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "date": "2025-05-25", "written_by": "independent", "quote": "لم تظهر عليه أي أعراض سريرية تشير إلى تعرضه لتسمم بمادة الفوسفين الناتجة عن قرص الغلة" }, { "kind": "news report", "citation": "Al-Dostor, 25 May 2025, 'دراما إنقاذ \"قرص الغلة\" عبر الذكاء الاصطناعي. وخبراء يحذرون من كارثة محتملة' (quotes Dr Mahmoud Amr, founder of the National Poison Centre).", "title": "دراما إنقاذ “قرص الغلة” عبر الذكاء الاصطناعي.. وخبراء يحذرون من كارثة محتملة", "url": "https://www.dostor.org/5083066", "date": "2025-05-25", "written_by": "independent", "quote": "تناول الزيوت بالفعل يُعد من الإسعافات الأولية الضرورية في حالات التسمم بحبوب الغلة" }, { "kind": "news report", "citation": "Al Jazeera Mubasher (Sameh Gad), 26 May 2025, '\"قرص الغلة\" والمنشور الذي حيّر المصريين. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من \"الترند القاتل\"' (quotes Dr Nermin Hamdi and Dr Mahmoud Mohamed Amr).", "title": "“قرص الغلة” والمنشور الذي حيّر المصريين.. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من “الترند القاتل”", "url": "https://www.aljazeeramubasher.net/news/reports/2025/5/26/%d9%82%d8%b1%d8%b5-%d8%a7%d9%84%d8%ba%d9%84%d8%a9-%d9%88%d8%a7%d9%84%d9%85%d9%86%d8%b4%d9%88%d8%b1-%d8%a7%d9%84%d8%b0%d9%8a-%d8%ad%d9%8a%d8%b1", "date": "2025-05-26", "written_by": "independent", "quote": "إعطاء المصاب بالتسمم أي نوع من الزيوت هو بمثابة إسعاف أولي وليس علاجا" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0325-source-0001", "AIBD-0325-source-0002", "AIBD-0325-source-0003", "AIBD-0325-source-0004", "AIBD-0325-source-0005", "AIBD-0325-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2025-05-24-415b, 'AI Intervention Saves Teen from Poisoning' (AI-generated summary).", "title": "AI Intervention Saves Teen from Poisoning", "url": "https://oecd.ai/en/incidents/2025-05-24-415b", "date": "2025-05-24", "written_by": "independent", "quote": "The AI recommended immediately coating the pill with paraffin oil to mitigate poisoning effects, helping counteract doctors’ initial pessimism and contributing to the teen’s survival." }, { "kind": "news report", "citation": "Sada El Balad (Sara Abdallah), 24 May 2025, 'عاد من الموت. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة' (reproduces Islam Adel's Facebook post).", "title": "عاد من الموت.. شات جي بي تي ينقذ شابا بعد تناول حبة الغلة", "url": "https://www.elbalad.news/6583785", "date": "2025-05-24", "written_by": "independent", "quote": "خلال دقائق قررت أسأل شات جي بي تي عن التصرف الأمثل فنصحني فورًا باستخدام زيت البرافين" }, { "kind": "news report", "citation": "Al-Dostor (Asmaa Ibrahim), 24 May 2025, 'الذكاء الاصطناعي السبب. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة'.", "title": "الذكاء الاصطناعي السبب.. شاب ينجو من تسمم قرص الغلة وعميد طب أسيوط ينفي الحادثة", "url": "https://www.dostor.org/5081951", "date": "2025-05-24", "written_by": "independent", "quote": "كما أكد أن الشاب نفى تناوله للقرص وأقر بأنه ألقاه في حوض ماء" }, { "kind": "news report", "citation": "Masrawy (Mahmoud Agami, Assiut), 25 May 2025, 'عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"'.", "title": "عميد طب أسيوط يكشف حقيقة منشور \"شات جي بي تي وحبة الغلال\"", "url": "https://www.masrawy.com/news/news_regions/details/2025/5/25/2793185/", "date": "2025-05-25", "written_by": "independent", "quote": "لم تظهر عليه أي أعراض سريرية تشير إلى تعرضه لتسمم بمادة الفوسفين الناتجة عن قرص الغلة" }, { "kind": "news report", "citation": "Al-Dostor, 25 May 2025, 'دراما إنقاذ \"قرص الغلة\" عبر الذكاء الاصطناعي. وخبراء يحذرون من كارثة محتملة' (quotes Dr Mahmoud Amr, founder of the National Poison Centre).", "title": "دراما إنقاذ “قرص الغلة” عبر الذكاء الاصطناعي.. وخبراء يحذرون من كارثة محتملة", "url": "https://www.dostor.org/5083066", "date": "2025-05-25", "written_by": "independent", "quote": "تناول الزيوت بالفعل يُعد من الإسعافات الأولية الضرورية في حالات التسمم بحبوب الغلة" }, { "kind": "news report", "citation": "Al Jazeera Mubasher (Sameh Gad), 26 May 2025, '\"قرص الغلة\" والمنشور الذي حيّر المصريين. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من \"الترند القاتل\"' (quotes Dr Nermin Hamdi and Dr Mahmoud Mohamed Amr).", "title": "“قرص الغلة” والمنشور الذي حيّر المصريين.. وصفة غريبة لإنقاذ المنتحرين وتحذيرات من “الترند القاتل”", "url": "https://www.aljazeeramubasher.net/news/reports/2025/5/26/%d9%82%d8%b1%d8%b5-%d8%a7%d9%84%d8%ba%d9%84%d8%a9-%d9%88%d8%a7%d9%84%d9%85%d9%86%d8%b4%d9%88%d8%b1-%d8%a7%d9%84%d8%b0%d9%8a-%d8%ad%d9%8a%d8%b1", "date": "2025-05-26", "written_by": "independent", "quote": "إعطاء المصاب بالتسمم أي نوع من الزيوت هو بمثابة إسعاف أولي وليس علاجا" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Facebook post of 24 May 2025 credits ChatGPT with first aid. Assiut Faculty of Medicine dean Alaa Attia says that the youth had no phosphine symptoms and said he threw the pill into water.", "account": "El Balad (24 May 2025, 12:39) reproduces a Facebook post by Islam Adel, a commercial-control inspector. He wrote it at 1 a.m. after “24 hours” had passed since his cousin Mohamed Yousry (17) swallowed part of a “grain pill” (aluminum phosphide). The pill came from samples Adel had seized and kept at the family's old house. The cousin took it after a quarrel with his father. Adel writes that the Abnoub central hospital refused the case. He writes that within minutes he asked ChatGPT for the best course. It advised paraffin oil to coat the pill and limit phosphine release. The youth drank a bottle from a pharmacy before they went to Assiut University Hospital's poison reception. Doctors there said there was no treatment protocol and the case would die. He then gave instructions from “an advanced AI model and a limited-use trial version of GPT-5”. Nine bottles of paraffin oil were given in turn with breathing exercises. The cousin stayed conscious, vomited for hours and was discharged stable. Dostor (24 May 2025, 22:40) reports the post and the reply of Dr Alaa Attia, dean of the Faculty of Medicine at Assiut University. He said precise medical examinations showed no signs or symptoms of swallowing the pill. The youth denied taking it and admitted throwing it into a water basin. The dean added that the hospital is researching paraffin oil with acetylcysteine as an adjunct. The protocol is experimental and not officially adopted. Masrawy (25 May 2025) quotes the dean that the youth, about 17, showed no clinical symptoms of phosphine poisoning. The team questioned him and he categorically denied swallowing the pill. He cited a family dispute over travel to Italy. Dostor (25 May 2025) adds toxicologist Dr Mahmoud Amr, founder of the National Poison Center. He says oils are indeed a necessary first aid in grain-pill poisoning. Al Jazeera Mubasher (26 May 2025) quotes Amr that the claim that paraffin oil rescues such a case “has no scientific basis”. It quotes Cairo University toxicologist Dr Nermin Hamdi that Assiut University denied the case involved the grain pill. Hamdi adds that giving oil is first aid, not treatment. The Monitor lists 13 syndications. Al Arabiya's syndication was not available. The ingestion date is not fixed by any source." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The chatbot supplied treatment suggestions, according to the patient’s cousin." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A trial version of GPT-5, according to the cousin’s post." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "A trial version of GPT-5, according to the cousin’s post.", "editor_note": "The identification comes from the cousin’s post. The existing sources provide no model output or vendor confirmation." } }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-5 trial version, per the cousin's post; unverified" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (OpenAI), described in the post as 'an advanced AI model and a limited-use trial version of GPT-5'" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT's paraffin-oil advice may have saved Islam Adel's 17-year-old cousin after an aluminum phosphide “grain pill” ingestion in Assiut", "headline": "ChatGPT's first-aid advice may have saved a teen in Assiut" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c89c1581d594839bae821d714dc3afa69acacd79a4a7a7f16669b13a0928a51a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "El Balad (24 May 2025, 12:39) reproduces a Facebook post by Islam Adel, a commercial-control inspector. He wrote it at 1 a.m. after “24 hours” had passed since his cousin Mohamed Yousry (17) swallowed part of a “grain pill” (aluminum phosphide). The pill came from samples Adel had seized and kept at the family's old house. The cousin took it after a quarrel with his father. Adel writes that the Abnoub central hospital refused the case. He writes that within minutes he asked ChatGPT for the best course. It advised paraffin oil to coat the pill and limit phosphine release. The youth drank a bottle from a pharmacy before they went to Assiut University Hospital's poison reception. Doctors there said there was no treatment protocol and the case would die. He then gave instructions from “an advanced AI model and a limited-use trial version of GPT-5”. Nine bottles of paraffin oil were given in turn with breathing exercises. The cousin stayed conscious, vomited for hours and was discharged stable. Dostor (24 May 2025, 22:40) reports the post and the reply of Dr Alaa Attia, dean of the Faculty of Medicine at Assiut University. He said precise medical examinations showed no signs or symptoms of swallowing the pill. The youth denied taking it and admitted throwing it into a water basin. The dean added that the hospital is researching paraffin oil with acetylcysteine as an adjunct. The protocol is experimental and not officially adopted. Masrawy (25 May 2025) quotes the dean that the youth, about 17, showed no clinical symptoms of phosphine poisoning. The team questioned him and he categorically denied swallowing the pill. He cited a family dispute over travel to Italy. Dostor (25 May 2025) adds toxicologist Dr Mahmoud Amr, founder of the National Poison Center. He says oils are indeed a necessary first aid in grain-pill poisoning. Al Jazeera Mubasher (26 May 2025) quotes Amr that the claim that paraffin oil rescues such a case “has no scientific basis”. It quotes Cairo University toxicologist Dr Nermin Hamdi that Assiut University denied the case involved the grain pill. Hamdi adds that giving oil is first aid, not treatment. The Monitor lists 13 syndications. Al Arabiya's syndication was not available. The ingestion date is not fixed by any source.", "replication": { "produced_by": [ "A layperson prompting ChatGPT for first aid during a suspected aluminum phosphide ingestion", "Paraffin oil bought from a pharmacy and given before and, by the cousin's account, during hospital care" ], "must_hold": [ "That the pill was swallowed at all, which the treating dean says the patient denied", "Clinical confirmation of phosphine poisoning and of any effect of the oil. Assiut's paraffin-oil-plus-acetylcysteine protocol is described by the dean as experimental and not officially adopted." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0383", "title": "Sky Sentinel, an AI-controlled machine-gun turret built by Ukrainian engineers, is reported to have downed four Shahed drones with one prototype; UNITED24 raises $1.5 million for 10 units", "summary": "Ukraine's Sky Sentinel, an AI-controlled heavy-machine-gun turret, is reported to have downed four Russian Shahed drones with one prototype; dates and places are withheld (May-June 2025).", "date_observed": "2025-05-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Sky Sentinel is an autonomous turret, a heavy machine gun on a 360-degree mount. Its software, written by Ukrainian engineers, takes radar input and separates drones from birds. It tracks the target, computes the ballistic solution and fires without a human. UNITED24 Media, the outlet of the UNITED24 fundraising platform, reported on 26 May 2025 that one prototype had downed four Shahed drones at the front. Dates and places were withheld for security. Its $1.5 million campaign for 10 turrets at about $150,000 each was complete. Forbes (David Hambling, 27 May 2025), as relayed by Euromaidan Press on 28 May 2025, repeats the four kills. It gives a pointing precision of 17 micro-radians. The Defense Post (3 June 2025) adds that 10 to 30 units would be needed to protect a city. It adds that production is scaling to dozens a month. The Monitor's statement that a human authorizes each shot is not in any read report.", "category": "general benefit", "unexpected": false, "purpose": "Built to shoot down Shahed-type attack drones and other small air targets automatically. The reported interceptions are that purpose.", "system": "Sky Sentinel AI-controlled anti-drone turret (heavy machine gun, radar-cued)", "model_version": "prototype", "developer": "Ukrainian engineering team (not named in the reports)", "deployer": "Ukrainian Defense Forces (unit not named)", "location": null, "domain": "Air defense / counter-drone", "segment": "Shahed-type one-way attack drones", "benefit_type": "Reduced Violence", "taxonomy_note": "Trustible has no military-defense type; the reported good is attack drones destroyed before reaching their targets, counted here as weapons removed, the nearest fit to Reduced Violence.", "registry_ids": { "oecd_aim": "2025-06-02-0176" }, "ratings": [ { "group": "societal", "depth": null, "reason": "Four shoot-downs are reported by the fundraising platform with no dates, places or targets. No protected population or averted strike is therefore documented." }, { "group": "organizational", "depth": null, "reason": "The reports do not identify the unit that fielded the prototype or any result beyond the kill count." } ], "ai_role": { "status": "assessed", "statement": "Per UNITED24 Media and Forbes via Euromaidan Press, the AI does the whole engagement. It takes radar data, distinguishes drones from birds and tracks the flight path. It computes the shot with wind and target speed, and fires conventional rounds. The four kills are the makers' claim relayed by the fundraiser. No independent confirmation, footage date or location is given. The Monitor's human-authorization step does not appear in the read reports." }, "evidence": [ { "kind": "news report", "citation": "Kabachynskyi, I. (2025). Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats. UNITED24 Media, May 26, 2025.", "title": "Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats", "url": "https://united24media.com/war-in-ukraine/ai-powered-turret-that-hunts-russian-drones-meet-sky-sentinel-ukraines-new-air-defense-8589", "date": "2025-05-26", "written_by": "deployer", "quote": "We had to build a system that moves a lot with zero mechanical play." }, { "kind": "news report", "citation": "Tril, M. (2025). Forbes: Ukraine deploys AI turrets against record Russian drone attacks. Euromaidan Press, May 28, 2025.", "title": "Forbes: Ukraine deploys AI turrets against record Russian drone attacks", "url": "https://euromaidanpress.com/2025/05/28/forbes-ukraine-deploys-ai-turrets-against-record-russian-drone-attacks/", "date": "2025-05-28", "written_by": "independent", "quote": "It never needs rest, never gets tired, and reacts instantly and precisely to incoming threats at any time day or night" }, { "kind": "news report", "citation": "Bisht, I. S. (2025). Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones. The Defense Post, June 3, 2025.", "title": "Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones", "url": "https://thedefensepost.com/2025/06/03/ukraine-ai-shahed-drones", "date": "2025-06-03", "written_by": "independent", "quote": "detects, locks on, tracks the flight paths, calculates the shot, and fires. All on its own" }, { "kind": "registry label", "citation": "OECD.AI (2025). Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat. OECD AI Incidents and Hazards Monitor, 2025-06-02.", "title": "Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat", "url": "https://oecd.ai/en/incidents/2025-06-02-0176", "date": "2025-06-02", "written_by": "independent", "quote": "has autonomously downed several Russian Shahed drones in active combat" } ], "replication": { "produced_by": [ "Radar cueing that hands the turret a track on a slow, low-flying drone", "A fixed heavy-machine-gun mount with near-zero mechanical play and fast optics", "Rules that let the system engage without a human in the loop" ], "must_hold": [ "Targets fly within the gun's effective range and are not masked by birds or clutter", "Enough units are fielded to cover a city, which the makers put at 10 to 30" ], "echoes": [] }, "paired_incident": null, "headline": "Sky Sentinel AI turret may have downed four Shahed drones", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Ukraine", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-06-02-0176", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Armed_Forces_of_Ukraine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Ukrainian Defense Forces.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, a registry entry and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0383", "catalog_version": "1.0.0", "source_fingerprint": "406751e34e0ddb062d1db3036f93b2c6191624c4a25d0b89f12234ccff7fbaf0", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0383-source-0001", "AIBD-0383-source-0002", "AIBD-0383-source-0003", "AIBD-0383-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Ukrainian engineering team (not named in the reports)", "deployer": "Ukrainian Defense Forces (unit not named)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Per UNITED24 Media and Forbes via Euromaidan Press, the AI does the whole engagement. It takes radar data, distinguishes drones from birds and tracks the flight path. It computes the shot with wind and target speed, and fires conventional rounds. The four kills are the makers' claim relayed by the fundraiser. No independent confirmation, footage date or location is given. The Monitor's human-authorization step does not appear in the read reports." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Per UNITED24 Media and Forbes via Euromaidan Press, the AI does the whole engagement. It takes radar data, distinguishes drones from birds and tracks the flight path. It computes the shot with wind and target speed, and fires conventional rounds. The four kills are the makers' claim relayed by the fundraiser. No independent confirmation, footage date or location is given. The Monitor's human-authorization step does not appear in the read reports." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, a registry entry and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Four shoot-downs are reported by the fundraising platform with no dates, places or targets. No protected population or averted strike is therefore documented." }, { "group": "organizational", "reason": "The reports do not identify the unit that fielded the prototype or any result beyond the kill count." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Four shoot-downs are reported by the fundraising platform with no dates, places or targets. No protected population or averted strike is therefore documented." }, { "group": "organizational", "reason": "The reports do not identify the unit that fielded the prototype or any result beyond the kill count." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-06-02-0176" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0383" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence", "taxonomy_note": "Trustible has no military-defense type; the reported good is attack drones destroyed before reaching their targets, counted here as weapons removed, the nearest fit to Reduced Violence." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Sky Sentinel is an autonomous turret, a heavy machine gun on a 360-degree mount. Its software, written by Ukrainian engineers, takes radar input and separates drones from birds. It tracks the target, computes the ballistic solution and fires without a human. UNITED24 Media, the outlet of the UNITED24 fundraising platform, reported on 26 May 2025 that one prototype had downed four Shahed drones at the front. Dates and places were withheld for security. Its $1.5 million campaign for 10 turrets at about $150,000 each was complete. Forbes (David Hambling, 27 May 2025), as relayed by Euromaidan Press on 28 May 2025, repeats the four kills. It gives a pointing precision of 17 micro-radians. The Defense Post (3 June 2025) adds that 10 to 30 units would be needed to protect a city. It adds that production is scaling to dozens a month. 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The reported interceptions are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer_country": "Ukraine" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to shoot down Shahed-type attack drones and other small air targets automatically. 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(2025). Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats. UNITED24 Media, May 26, 2025.", "title": "Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats", "url": "https://united24media.com/war-in-ukraine/ai-powered-turret-that-hunts-russian-drones-meet-sky-sentinel-ukraines-new-air-defense-8589", "date": "2025-05-26", "written_by": "deployer", "quote": "We had to build a system that moves a lot with zero mechanical play." }, { "kind": "news report", "citation": "Tril, M. (2025). Forbes: Ukraine deploys AI turrets against record Russian drone attacks. Euromaidan Press, May 28, 2025.", "title": "Forbes: Ukraine deploys AI turrets against record Russian drone attacks", "url": "https://euromaidanpress.com/2025/05/28/forbes-ukraine-deploys-ai-turrets-against-record-russian-drone-attacks/", "date": "2025-05-28", "written_by": "independent", "quote": "It never needs rest, never gets tired, and reacts instantly and precisely to incoming threats at any time day or night" }, { "kind": "news report", "citation": "Bisht, I. S. (2025). Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones. The Defense Post, June 3, 2025.", "title": "Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones", "url": "https://thedefensepost.com/2025/06/03/ukraine-ai-shahed-drones", "date": "2025-06-03", "written_by": "independent", "quote": "detects, locks on, tracks the flight paths, calculates the shot, and fires. All on its own" }, { "kind": "registry label", "citation": "OECD.AI (2025). Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat. OECD AI Incidents and Hazards Monitor, 2025-06-02.", "title": "Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat", "url": "https://oecd.ai/en/incidents/2025-06-02-0176", "date": "2025-06-02", "written_by": "independent", "quote": "has autonomously downed several Russian Shahed drones in active combat" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0383-source-0001", "AIBD-0383-source-0002", "AIBD-0383-source-0003", "AIBD-0383-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kabachynskyi, I. (2025). Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats. UNITED24 Media, May 26, 2025.", "title": "Ukraine Develops New AI-controlled Sky Sentinel Turret to Combat Russian Drone Threats", "url": "https://united24media.com/war-in-ukraine/ai-powered-turret-that-hunts-russian-drones-meet-sky-sentinel-ukraines-new-air-defense-8589", "date": "2025-05-26", "written_by": "deployer", "quote": "We had to build a system that moves a lot with zero mechanical play." }, { "kind": "news report", "citation": "Tril, M. (2025). Forbes: Ukraine deploys AI turrets against record Russian drone attacks. Euromaidan Press, May 28, 2025.", "title": "Forbes: Ukraine deploys AI turrets against record Russian drone attacks", "url": "https://euromaidanpress.com/2025/05/28/forbes-ukraine-deploys-ai-turrets-against-record-russian-drone-attacks/", "date": "2025-05-28", "written_by": "independent", "quote": "It never needs rest, never gets tired, and reacts instantly and precisely to incoming threats at any time day or night" }, { "kind": "news report", "citation": "Bisht, I. S. (2025). Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones. The Defense Post, June 3, 2025.", "title": "Ukraine Develops AI-Run Turret to Take Down Erratic Shahed Drones", "url": "https://thedefensepost.com/2025/06/03/ukraine-ai-shahed-drones", "date": "2025-06-03", "written_by": "independent", "quote": "detects, locks on, tracks the flight paths, calculates the shot, and fires. All on its own" }, { "kind": "registry label", "citation": "OECD.AI (2025). Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat. OECD AI Incidents and Hazards Monitor, 2025-06-02.", "title": "Ukraine Deploys AI-Powered Sky Sentinel Turret in Drone Combat", "url": "https://oecd.ai/en/incidents/2025-06-02-0176", "date": "2025-06-02", "written_by": "independent", "quote": "has autonomously downed several Russian Shahed drones in active combat" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Ukraine's Sky Sentinel, an AI-controlled heavy-machine-gun turret, is reported to have downed four Russian Shahed drones with one prototype; dates and places are withheld (May-June 2025).", "account": "Sky Sentinel is an autonomous turret, a heavy machine gun on a 360-degree mount. Its software, written by Ukrainian engineers, takes radar input and separates drones from birds. It tracks the target, computes the ballistic solution and fires without a human. UNITED24 Media, the outlet of the UNITED24 fundraising platform, reported on 26 May 2025 that one prototype had downed four Shahed drones at the front. Dates and places were withheld for security. Its $1.5 million campaign for 10 turrets at about $150,000 each was complete. Forbes (David Hambling, 27 May 2025), as relayed by Euromaidan Press on 28 May 2025, repeats the four kills. It gives a pointing precision of 17 micro-radians. The Defense Post (3 June 2025) adds that 10 to 30 units would be needed to protect a city. It adds that production is scaling to dozens a month. The Monitor's statement that a human authorizes each shot is not in any read report." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The developers reported that the system classified radar detections, tracked drones, and calculated firing corrections." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The project used a prototype." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "prototype" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Sky Sentinel AI-controlled anti-drone turret (heavy machine gun, radar-cued)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Ukrainian engineering team (not named in the reports)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Sky Sentinel, an AI-controlled machine-gun turret built by Ukrainian engineers, is reported to have downed four Shahed drones with one prototype; UNITED24 raises $1.5 million for 10 units", "headline": "Sky Sentinel AI turret may have downed four Shahed drones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "406751e34e0ddb062d1db3036f93b2c6191624c4a25d0b89f12234ccff7fbaf0" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Sky Sentinel is an autonomous turret, a heavy machine gun on a 360-degree mount. Its software, written by Ukrainian engineers, takes radar input and separates drones from birds. It tracks the target, computes the ballistic solution and fires without a human. UNITED24 Media, the outlet of the UNITED24 fundraising platform, reported on 26 May 2025 that one prototype had downed four Shahed drones at the front. Dates and places were withheld for security. Its $1.5 million campaign for 10 turrets at about $150,000 each was complete. Forbes (David Hambling, 27 May 2025), as relayed by Euromaidan Press on 28 May 2025, repeats the four kills. It gives a pointing precision of 17 micro-radians. The Defense Post (3 June 2025) adds that 10 to 30 units would be needed to protect a city. It adds that production is scaling to dozens a month. The Monitor's statement that a human authorizes each shot is not in any read report.", "replication": { "produced_by": [ "Radar cueing that hands the turret a track on a slow, low-flying drone", "A fixed heavy-machine-gun mount with near-zero mechanical play and fast optics", "Rules that let the system engage without a human in the loop" ], "must_hold": [ "Targets fly within the gun's effective range and are not masked by birds or clutter", "Enough units are fielded to cover a city, which the makers put at 10 to 30" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0203", "title": "FDA uses AI to choose where to concentrate food inspections; an imported-seafood pilot ran for years", "summary": "Commissioner Marty Makary told a Senate committee in May 2025 that FDA uses AI to target food inspections; a multi-year imported-seafood AI pilot is mentioned; no outcome figures in the source.", "date_observed": "2025-05-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Civil Eats reported on 27 May 2025 that FDA Commissioner Marty Makary, appearing before a Senate committee the previous week, said the agency was using AI to identify where to concentrate food inspections and that AI can sometimes find patterns faster than people, adding that a human reviews the information. The article notes that FDA had been working for several years on a pilot focused on imported seafood and had announced an agency-wide generative AI rollout, with an FDA spokesperson saying all centers would run on a unified platform by 30 June; a 2 June update records the launch of FDA's generative tool Elsa, said to be used in part to identify high-priority inspection targets. Jaydee Hanson of the Center for Food Safety is quoted on the risks of using AI amid staff cuts. No inspection outcome, detection or recall attributable to the AI is given. FDA's own pilot page was not available, so no official report is among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Prioritize food inspection targets, including imported seafood, using pattern recognition over agency data.", "system": "FDA AI inspection-targeting tools (imported seafood pilot; Elsa generative AI)", "model_version": null, "developer": "U.S. Food and Drug Administration (details not in the cited source)", "deployer": "U.S. Food and Drug Administration", "location": null, "domain": "Food safety regulation", "segment": "Import and facility inspection targeting", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "Statements of use only; the type names better-targeted inspections, not a documented outcome.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No figure on inspections targeted, violations found or seafood shipments flagged appears in the source." }, { "group": "societal", "depth": null, "reason": "No contamination detection or recall is attributed to the AI." } ], "ai_role": { "status": "unassessed", "statement": "Only the Commissioner's testimony and an FDA spokesperson's statements, as reported by Civil Eats, describe the AI's use. No evaluation, outcome or official report is among the sources, and FDA's pilot page was not available." }, "evidence": [ { "kind": "news report", "citation": "Held L. FDA Expanding Use of AI in Food Safety Inspection. 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Civil Eats, 27 May 2025 (updated 2 June 2025).", "title": "FDA Expanding Use of AI in Food Safety Inspection", "url": "https://civileats.com/2025/05/27/fda-expanding-use-of-ai-in-food-safety-inspection/", "date": "2025-05-27", "written_by": "independent", "quote": "We’re using AI to identify where we should be concentrating our food inspections" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Commissioner Marty Makary told a Senate committee in May 2025 that FDA uses AI to target food inspections; a multi-year imported-seafood AI pilot is mentioned; no outcome figures in the source.", "account": "Civil Eats reported on 27 May 2025 that FDA Commissioner Marty Makary, appearing before a Senate committee the previous week, said the agency was using AI to identify where to concentrate food inspections and that AI can sometimes find patterns faster than people, adding that a human reviews the information. 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FDA's own pilot page was not available, so no official report is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FDA AI inspection-targeting tools (imported seafood pilot; Elsa generative AI)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "U.S. Food and Drug Administration (details not in the cited source)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "FDA uses AI to choose where to concentrate food inspections; an imported-seafood pilot ran for years", "headline": "FDA uses AI to target food inspections" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d479c5a5bdccb684cd707bf8df0c6f108182ed1adcc31b8736a30af08b34214f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Civil Eats reported on 27 May 2025 that FDA Commissioner Marty Makary, appearing before a Senate committee the previous week, said the agency was using AI to identify where to concentrate food inspections and that AI can sometimes find patterns faster than people, adding that a human reviews the information. The article notes that FDA had been working for several years on a pilot focused on imported seafood and had announced an agency-wide generative AI rollout, with an FDA spokesperson saying all centers would run on a unified platform by 30 June; a 2 June update records the launch of FDA's generative tool Elsa, said to be used in part to identify high-priority inspection targets. Jaydee Hanson of the Center for Food Safety is quoted on the risks of using AI amid staff cuts. No inspection outcome, detection or recall attributable to the AI is given. FDA's own pilot page was not available, so no official report is among the sources.", "replication": { "produced_by": [ "An agency-wide generative AI rollout announced in May 2025", "A multi-year imported-seafood pilot" ], "must_hold": [ "Human review of AI outputs, as the Commissioner stated" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0133", "title": "NIO owner falls asleep at 110 km/h on a rainy highway; his car's NWM emergency pull-over stops it and an SOS call wakes him", "summary": "Driver asleep at 110 km/h on a rainy highway; NIO's NWM emergency pull-over stopped the car and an SOS call woke him, 1 June 2025.", "date_observed": "2025-06-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Around midnight on 1 June 2025, a NIO owner fell asleep driving at 110 km/h on a highway in rain in China. NIO's assisted driving was engaged. The NIO World Model (NWM) emergency autonomous pull-over function triggered, and an SOS call woke him. NIO had begun pushing it to more than 400,000 Banyan-platform cars on 30 May 2025. He posted a video on social media on 2 June. NIO founder William Li reposted it, describing the function (gradual deceleration, a lane change to the rightmost emergency lane, hazard lights, SOS intervention). He stressed that assisted driving is not autonomous driving. No crash or injury was reported. The vehicle model and highway are not named.", "category": "protective response", "unexpected": false, "purpose": "NIO's first NWM release, pushed to Banyan-platform cars from 30 May 2025, added an “emergency autonomous pull-over”. It works on a highway or urban expressway when the assisted-driving system detects an unresponsive driver. The car slows gradually, moves to the rightmost emergency lane, turns on its hazard lights and triggers an SOS call. CnEVPost notes that NIO cars previously could only decelerate and stop within the current lane. This event is that function doing what it was built to do.", "system": "NIO World Model (NWM) emergency autonomous pull-over function within NIO's assisted-driving system", "model_version": "First release of NIO World Model (NWM), pushed to more than 400,000 Banyan-platform cars from 30 May 2025; the vehicle model and software build are not reported", "developer": "NIO", "deployer": "NIO", "location": null, "domain": "Road vehicle crash avoidance", "segment": "Consumer driver-assistance software on a privately owned vehicle", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-05-30-3168" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable driver, asleep at 110 km/h in rain on a highway, was brought to a stop and woken without a crash. The owner's account, as relayed by the outlets, calls it a rescue (“挽救”). The account does not establish that a crash was imminent." } ], "ai_role": { "status": "assessed", "statement": "The NWM-based assisted-driving system judged the driver unresponsive, ran the emergency pull-over and placed the SOS call that woke him. The car was already under assisted driving. Its specific contribution was therefore taking the car out of the live lane and rousing the driver rather than keeping it in lane. The sequence is known only from the owner's video as relayed by independent outlets. NIO's founder confirmed the function's design. No telemetry, police report or third-party verification was published." }, "evidence": [ { "kind": "news report", "citation": "快科技 / 驱动之家 (2025). 蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶. news.mydrivers.com.", "title": "蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶 [NIO owner falls asleep at 110 km/h on a rainy night highway, triggering emergency autonomous pull-over; William Li: assisted driving is not autonomous driving]", "url": "https://news.mydrivers.com/1/1051/1051320.htm", "date": "2025-06-02", "written_by": "independent", "quote": "他在6月1日凌晨12点开车睡着了，靠车辆自主靠边停车挽救" }, { "kind": "news report", "citation": "新浪科技 (闫妍), via 和讯网 (2025). 李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主. auto.hexun.com.", "title": "李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主 [William Li responds to NIO owner who fell asleep on the highway: assisted driving is not autonomous driving; automatic emergency pull-over triggered, SOS call woke the owner]", "url": "http://auto.hexun.com/2025-06-03/219371749.html", "date": "2025-06-03", "written_by": "independent", "quote": "触发了自动紧急靠边停车，并通过SOS电话方式唤醒了车主" }, { "kind": "news report", "citation": "易车讯, via 中金在线 (2025). 李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全. auto.cnfol.com.", "title": "李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全 [William Li responds to owner who fell asleep on the highway: assisted driving is not autonomous driving, take care on the drive back to work]", "url": "http://auto.cnfol.com/xincheshangshi/20250603/31358495.shtml", "date": "2025-06-03", "written_by": "independent", "quote": "在5月30日宣布，蔚来世界模型 NWM首个版本开启推送" }, { "kind": "news report", "citation": "中关村在线 (2025). 蔚来车主高速睡着，车辆自动靠边停车. news.zol.com.cn; republished by 新浪汽车 (k.sina.com.cn) on 3 June 2025.", "title": "蔚来车主高速睡着，车辆自动靠边停车 [NIO owner falls asleep on the highway, car pulls over automatically]", "url": "https://news.zol.com.cn/991/9916102.html", "date": "2025-06-02", "written_by": "independent", "quote": "以110公里/小时的速度行驶时，自己在高速公路上不慎睡着" }, { "kind": "news report", "citation": "Zhang, Phate (2025). [Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities. CnEVPost.", "title": "[Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities", "url": "https://cnevpost.com/2025/05/30/nio-rolls-out-first-version-nwm/", "date": "2025-05-30", "written_by": "independent", "quote": "With NWM, if the vehicle detects driver dysfunction, it will autonomously pull over to the roadside." }, { "kind": "news report", "citation": "CnEVPost (2026). Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience. CnEVPost, 28 January 2026.", "title": "Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience", "url": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "date": "2026-01-28", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "The car was running the first NIO World Model (NWM) release with the “emergency autonomous pull-over” function, pushed to Banyan-platform cars from 30 May 2025.", "Assisted driving was engaged on a highway, the function's stated operating domain (highways and urban expressways).", "The assisted-driving system judged the driver unresponsive. He did not respond to the escalating alarms NIO describes. The pull-over and the SOS call therefore ran to completion." ], "must_hold": [ "Driver monitoring must detect an unresponsive driver. The road must offer a rightmost emergency lane to stop in.", "The SOS call needs working connectivity and a NIO emergency-response channel to reach the driver or a responder.", "NIO and its founder present the function as a safety net within assisted driving, not autonomous driving. The driver remains responsible for staying awake." ], "echoes": [] }, "paired_incident": null, "headline": "NIO's NWM emergency pull-over stops a sleeping driver's car", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2026-01-28", "note": "NIO rolled out a major NWM update in January 2026 to more than 460,000 Banyan-system vehicles with Cedar and Cedar S models to follow; the report does not discuss the pull-over function itself.", "quote": "The update will first become available to over 460,000 vehicles equipped with the Banyan system. Models featuring the Cedar and Cedar S systems will also receive the update shortly.", "url": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/" }, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-05-30-3168", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Nio_Inc.; https://en.wikipedia.org/wiki/Nio_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0133", "catalog_version": "1.0.0", "source_fingerprint": "13ec2ded56728532b6aa3c142cfe7bd1ae46dcb7c8841fd49a4063c25a533414", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0133-source-0001", "AIBD-0133-source-0002", "AIBD-0133-source-0003", "AIBD-0133-source-0004", "AIBD-0133-source-0005", "AIBD-0133-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "NIO", "deployer": "NIO" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The NWM-based assisted-driving system judged the driver unresponsive, ran the emergency pull-over and placed the SOS call that woke him. The car was already under assisted driving. Its specific contribution was therefore taking the car out of the live lane and rousing the driver rather than keeping it in lane. The sequence is known only from the owner's video as relayed by independent outlets. NIO's founder confirmed the function's design. No telemetry, police report or third-party verification was published." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The NWM-based assisted-driving system judged the driver unresponsive, ran the emergency pull-over and placed the SOS call that woke him. The car was already under assisted driving. Its specific contribution was therefore taking the car out of the live lane and rousing the driver rather than keeping it in lane. The sequence is known only from the owner's video as relayed by independent outlets. NIO's founder confirmed the function's design. No telemetry, police report or third-party verification was published." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable driver, asleep at 110 km/h in rain on a highway, was brought to a stop and woken without a crash. The owner's account, as relayed by the outlets, calls it a rescue (“挽救”). The account does not establish that a crash was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable driver, asleep at 110 km/h in rain on a highway, was brought to a stop and woken without a crash. The owner's account, as relayed by the outlets, calls it a rescue (“挽救”). The account does not establish that a crash was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable driver, asleep at 110 km/h in rain on a highway, was brought to a stop and woken without a crash. The owner's account, as relayed by the outlets, calls it a rescue (“挽救”). 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system. Models featuring the Cedar and Cedar S systems will also receive the update shortly.", "url": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0133" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Around midnight on 1 June 2025, a NIO owner fell asleep driving at 110 km/h on a highway in rain in China. NIO's assisted driving was engaged. The NIO World Model (NWM) emergency autonomous pull-over function triggered, and an SOS call woke him. NIO had begun pushing it to more than 400,000 Banyan-platform cars on 30 May 2025. He posted a video on social media on 2 June. NIO founder William Li reposted it, describing the function (gradual deceleration, a lane change to the rightmost emergency lane, hazard lights, SOS intervention). He stressed that assisted driving is not autonomous driving. No crash or injury was reported. The vehicle model and highway are not named.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable driver, asleep at 110 km/h in rain on a highway, was brought to a stop and woken without a crash. The owner's account, as relayed by the outlets, calls it a rescue (“挽救”). The account does not establish that a crash was imminent." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "NIO's first NWM release, pushed to Banyan-platform cars from 30 May 2025, added an “emergency autonomous pull-over”. It works on a highway or urban expressway when the assisted-driving system detects an unresponsive driver. The car slows gradually, moves to the rightmost emergency lane, turns on its hazard lights and triggers an SOS call. CnEVPost notes that NIO cars previously could only decelerate and stop within the current lane. This event is that function doing what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "China", "deployer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "NIO's first NWM release, pushed to Banyan-platform cars from 30 May 2025, added an “emergency autonomous pull-over”. It works on a highway or urban expressway when the assisted-driving system detects an unresponsive driver. The car slows gradually, moves to the rightmost emergency lane, turns on its hazard lights and triggers an SOS call. CnEVPost notes that NIO cars previously could only decelerate and stop within the current lane. This event is that function doing what it was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-05-30-3168", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Nio_Inc.; https://en.wikipedia.org/wiki/Nio_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The car was running the first NIO World Model (NWM) release with the “emergency autonomous pull-over” function, pushed to Banyan-platform cars from 30 May 2025.", "Assisted driving was engaged on a highway, the function's stated operating domain (highways and urban expressways).", "The assisted-driving system judged the driver unresponsive. He did not respond to the escalating alarms NIO describes. The pull-over and the SOS call therefore ran to completion." ], "must_hold": [ "Driver monitoring must detect an unresponsive driver. The road must offer a rightmost emergency lane to stop in.", "The SOS call needs working connectivity and a NIO emergency-response channel to reach the driver or a responder.", "NIO and its founder present the function as a safety net within assisted driving, not autonomous driving. The driver remains responsible for staying awake." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-05-30-3168", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Nio_Inc.; https://en.wikipedia.org/wiki/Nio_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road vehicle crash avoidance", "segment": "Consumer driver-assistance software on a privately owned vehicle" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "快科技 / 驱动之家 (2025). 蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶. news.mydrivers.com.", "title": "蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶 [NIO owner falls asleep at 110 km/h on a rainy night highway, triggering emergency autonomous pull-over; William Li: assisted driving is not autonomous driving]", "url": "https://news.mydrivers.com/1/1051/1051320.htm", "date": "2025-06-02", "written_by": "independent", "quote": "他在6月1日凌晨12点开车睡着了，靠车辆自主靠边停车挽救" }, { "kind": "news report", "citation": "新浪科技 (闫妍), via 和讯网 (2025). 李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主. auto.hexun.com.", "title": "李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主 [William Li responds to NIO owner who fell asleep on the highway: assisted driving is not autonomous driving; automatic emergency pull-over triggered, SOS call woke the owner]", "url": "http://auto.hexun.com/2025-06-03/219371749.html", "date": "2025-06-03", "written_by": "independent", "quote": "触发了自动紧急靠边停车，并通过SOS电话方式唤醒了车主" }, { "kind": "news report", "citation": "易车讯, via 中金在线 (2025). 李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全. auto.cnfol.com.", "title": "李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全 [William Li responds to owner who fell asleep on the highway: assisted driving is not autonomous driving, take care on the drive back to work]", "url": "http://auto.cnfol.com/xincheshangshi/20250603/31358495.shtml", "date": "2025-06-03", "written_by": "independent", "quote": "在5月30日宣布，蔚来世界模型 NWM首个版本开启推送" }, { "kind": "news report", "citation": "中关村在线 (2025). 蔚来车主高速睡着，车辆自动靠边停车. news.zol.com.cn; republished by 新浪汽车 (k.sina.com.cn) on 3 June 2025.", "title": "蔚来车主高速睡着，车辆自动靠边停车 [NIO owner falls asleep on the highway, car pulls over automatically]", "url": "https://news.zol.com.cn/991/9916102.html", "date": "2025-06-02", "written_by": "independent", "quote": "以110公里/小时的速度行驶时，自己在高速公路上不慎睡着" }, { "kind": "news report", "citation": "Zhang, Phate (2025). [Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities. CnEVPost.", "title": "[Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities", "url": "https://cnevpost.com/2025/05/30/nio-rolls-out-first-version-nwm/", "date": "2025-05-30", "written_by": "independent", "quote": "With NWM, if the vehicle detects driver dysfunction, it will autonomously pull over to the roadside." }, { "kind": "news report", "citation": "CnEVPost (2026). Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience. CnEVPost, 28 January 2026.", "title": "Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience", "url": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "date": "2026-01-28", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0133-source-0001", "AIBD-0133-source-0002", "AIBD-0133-source-0003", "AIBD-0133-source-0004", "AIBD-0133-source-0005", "AIBD-0133-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "快科技 / 驱动之家 (2025). 蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶. news.mydrivers.com.", "title": "蔚来车主雨夜高速110km/h时速睡着触发紧急自主靠边停车 李斌：辅助驾驶不是自动驾驶 [NIO owner falls asleep at 110 km/h on a rainy night highway, triggering emergency autonomous pull-over; William Li: assisted driving is not autonomous driving]", "url": "https://news.mydrivers.com/1/1051/1051320.htm", "date": "2025-06-02", "written_by": "independent", "quote": "他在6月1日凌晨12点开车睡着了，靠车辆自主靠边停车挽救" }, { "kind": "news report", "citation": "新浪科技 (闫妍), via 和讯网 (2025). 李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主. auto.hexun.com.", "title": "李斌回应蔚来车主高速睡着：辅助驾驶不是自动驾驶，返工路上注意安全！触发自动紧急靠边停车，SOS电话唤醒车主 [William Li responds to NIO owner who fell asleep on the highway: assisted driving is not autonomous driving; automatic emergency pull-over triggered, SOS call woke the owner]", "url": "http://auto.hexun.com/2025-06-03/219371749.html", "date": "2025-06-03", "written_by": "independent", "quote": "触发了自动紧急靠边停车，并通过SOS电话方式唤醒了车主" }, { "kind": "news report", "citation": "易车讯, via 中金在线 (2025). 李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全. auto.cnfol.com.", "title": "李斌回应车主高速睡着：辅助驾驶不是自动驾驶 返工注意安全 [William Li responds to owner who fell asleep on the highway: assisted driving is not autonomous driving, take care on the drive back to work]", "url": "http://auto.cnfol.com/xincheshangshi/20250603/31358495.shtml", "date": "2025-06-03", "written_by": "independent", "quote": "在5月30日宣布，蔚来世界模型 NWM首个版本开启推送" }, { "kind": "news report", "citation": "中关村在线 (2025). 蔚来车主高速睡着，车辆自动靠边停车. news.zol.com.cn; republished by 新浪汽车 (k.sina.com.cn) on 3 June 2025.", "title": "蔚来车主高速睡着，车辆自动靠边停车 [NIO owner falls asleep on the highway, car pulls over automatically]", "url": "https://news.zol.com.cn/991/9916102.html", "date": "2025-06-02", "written_by": "independent", "quote": "以110公里/小时的速度行驶时，自己在高速公路上不慎睡着" }, { "kind": "news report", "citation": "Zhang, Phate (2025). [Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities. CnEVPost.", "title": "[Video] Nio rolls out first version of NWM, bringing enhanced smart driving capabilities", "url": "https://cnevpost.com/2025/05/30/nio-rolls-out-first-version-nwm/", "date": "2025-05-30", "written_by": "independent", "quote": "With NWM, if the vehicle detects driver dysfunction, it will autonomously pull over to the roadside." }, { "kind": "news report", "citation": "CnEVPost (2026). Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience. CnEVPost, 28 January 2026.", "title": "Nio rolls out major update to NWM driver assist software in China, delivering more human-like driving experience", "url": "https://cnevpost.com/2026/01/28/nio-rolls-out-major-update-to-nwm-driver-assist-china/", "date": "2026-01-28", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Driver asleep at 110 km/h on a rainy highway; NIO's NWM emergency pull-over stopped the car and an SOS call woke him, 1 June 2025.", "account": "Around midnight on 1 June 2025, a NIO owner fell asleep driving at 110 km/h on a highway in rain in China. NIO's assisted driving was engaged. The NIO World Model (NWM) emergency autonomous pull-over function triggered, and an SOS call woke him. NIO had begun pushing it to more than 400,000 Banyan-platform cars on 30 May 2025. He posted a video on social media on 2 June. NIO founder William Li reposted it, describing the function (gradual deceleration, a lane change to the rightmost emergency lane, hazard lights, SOS intervention). He stressed that assisted driving is not autonomous driving. No crash or injury was reported. The vehicle model and highway are not named." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The system detected that the driver was unresponsive and initiated an emergency pull-over, according to the owner’s account." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "NIO released the first NIO World Model to more than 400,000 cars using its Banyan platform on 30 May 2025." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "First release of NIO World Model (NWM), pushed to more than 400,000 Banyan-platform cars from 30 May 2025; the vehicle model and software build are not reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The first NIO World Model release, distributed from 30 May 2025. The installed build is not identified.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "NIO World Model (NWM) emergency autonomous pull-over function within NIO's assisted-driving system" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "NIO" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "NIO owner falls asleep at 110 km/h on a rainy highway; his car's NWM emergency pull-over stops it and an SOS call wakes him", "headline": "NIO's NWM emergency pull-over stops a sleeping driver's car" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "13ec2ded56728532b6aa3c142cfe7bd1ae46dcb7c8841fd49a4063c25a533414" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Around midnight on 1 June 2025, a NIO owner fell asleep driving at 110 km/h on a highway in rain in China. NIO's assisted driving was engaged. The NIO World Model (NWM) emergency autonomous pull-over function triggered, and an SOS call woke him. NIO had begun pushing it to more than 400,000 Banyan-platform cars on 30 May 2025. He posted a video on social media on 2 June. NIO founder William Li reposted it, describing the function (gradual deceleration, a lane change to the rightmost emergency lane, hazard lights, SOS intervention). He stressed that assisted driving is not autonomous driving. No crash or injury was reported. The vehicle model and highway are not named.", "replication": { "produced_by": [ "The car was running the first NIO World Model (NWM) release with the “emergency autonomous pull-over” function, pushed to Banyan-platform cars from 30 May 2025.", "Assisted driving was engaged on a highway, the function's stated operating domain (highways and urban expressways).", "The assisted-driving system judged the driver unresponsive. He did not respond to the escalating alarms NIO describes. The pull-over and the SOS call therefore ran to completion." ], "must_hold": [ "Driver monitoring must detect an unresponsive driver. The road must offer a rightmost emergency lane to stop in.", "The SOS call needs working connectivity and a NIO emergency-response channel to reach the driver or a responder.", "NIO and its founder present the function as a safety net within assisted driving, not autonomous driving. The driver remains responsible for staying awake." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0385", "title": "Intelligent Applications Based on Medical Large Models to Enhance People's Healthcare Experience and Health Status", "summary": "Ant reports that its medical AI served 13 million users and improved annotation efficiency by 50%; individual health outcomes are not specified.", "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "benefit_status": "mixed", "source_collection": "ITU AI for Good: Innovate for Impact (2025)", "source_entry": "ITU-001", "account": "Alipay describes medical assistants for residents, clinicians, and underserved areas. The submission reports 13 million users, 78 million service interactions, and a 50% improvement in the annotation workflow developed with medical specialists. Improved health and a more equitable distribution of care remain broader intended benefits.", "category": "general benefit", "unexpected": false, "purpose": "Provide medical guidance and reduce administrative and information-processing work.", "system": "Ant medical large model and health-assistant agents", "model_version": null, "developer": "Alipay / Ant Group", "deployer": "Zhejiang Provincial Health Commission; Hangzhou Municipal Medical Insurance Bureau; Renji Hospital", "location": "China: Zhejiang, Hangzhou, and Shanghai", "domain": "Healthcare", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Ant/Renji development workflow reportedly improved annotation efficiency by 50%. Clinical outcomes are not reported." }, { "group": "personal", "depth": null, "reason": "The source reports broad uptake and 98% satisfaction, but does not quantify a change in health or individual service experience." }, { "group": "societal", "depth": null, "reason": "Healthcare equity and rural access are asserted aims without a measured distributional outcome." } ], "ai_role": { "status": "unassessed", "statement": "The account does not isolate AI’s contribution from the surrounding workflow." }, "evidence": [ { "kind": "report", "citation": "International Telecommunication Union, AI for Good: Innovate for Impact (2025). Project-submitted account, current as of June 2025. ITU provides no independent outcome evaluation.", "title": "Use Case 1: Intelligent Applications Based on Medical Large Models to Enhance People's Healthcare Experience and Health Status", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-13", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "The account does not establish conditions sufficient to reproduce the benefit." ], "must_hold": [ "The account does not establish requirements for reproducing the benefit in other settings." ], "echoes": [] }, "paired_incident": null, "headline": "Ant health assistants reach patients and support medical work", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-13", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0385", "catalog_version": "1.0.0", "source_fingerprint": "c7784875704c926c11d60b15524f4765be27e43d1c426c5ae33a049c7034a24e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0385-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Alipay / Ant Group", "deployer": "Zhejiang Provincial Health Commission; Hangzhou Municipal Medical Insurance Bureau; Renji Hospital" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The account does not isolate AI’s contribution from the surrounding workflow." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Ant/Renji development workflow reportedly improved annotation efficiency by 50%. 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"claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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Early deployments reportedly reduced data-alignment time by 85% and outsourcing costs by 10%, while improving trial success by 25%. Blisstech is named as a validation partner. The submission does not give trial counts, comparison periods, or a patient benefit attributable to the tools.", "replication": { "produced_by": [ "The account does not establish conditions sufficient to reproduce the benefit." ], "must_hold": [ "The account does not establish requirements for reproducing the benefit in other settings." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0398", "title": "AI-Enabled Pathology Model for Precision Diagnosis and Treatment", "summary": "Huawei reports that RuiPath reduced pathology-review time at Ruijin Hospital, including initial review from 20–40 to 10–15 minutes per patient.", "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "benefit_status": "mixed", "source_collection": "ITU AI for Good: Innovate for Impact (2025)", "source_entry": "ITU-014", "account": "The RuiPath pathology pilot covers 11 subspecialties at Ruijin Hospital. Huawei reports shorter review and report-preparation workflows, including initial review of 10–15 minutes rather than 20–40 minutes. The source also claims model-accuracy and data-engineering benefits. Some percentage and timing statements differ, and no patient-specific treatment improvement is reported.", "category": "general benefit", "unexpected": false, "purpose": "Assist pathology analysis and reduce report-preparation work.", "system": "RuiPath multimodal pathology model", "model_version": null, "developer": "Huawei Technologies Co., Ltd.", "deployer": "Ruijin Hospital", "location": "Ruijin Hospital, Shanghai, China", "domain": "Healthcare", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "In the Ruijin pilot, initial review reportedly fell from 20–40 to 10–15 minutes per patient." }, { "group": "personal", "depth": null, "reason": "No patient-specific diagnosis, treatment change, or recovery is reported." }, { "group": "societal", "depth": null, "reason": "Improved global public health is aspirational." } ], "ai_role": { "status": "unassessed", "statement": "The account does not isolate AI’s contribution from the surrounding workflow." }, "evidence": [ { "kind": "report", "citation": "International Telecommunication Union, AI for Good: Innovate for Impact (2025). 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Its planned escalation workflow would involve counselors when high-risk content appears. Accuracy and response-time figures are development targets. 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Injury prevention and wider productivity gains remain intended and have not been separately measured.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Field tests report over 90% accuracy for specialized translation in more than 20 languages, addressing terminology failures." }, { "group": "personal", "depth": 2, "reason": "Multilingual field tests report over 90% user satisfaction with specialized workplace translation. 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The source reports field testing in more than 20 languages and over 90% accuracy and satisfaction. 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Transcription quality, staff time saved, and resulting newsroom improvements remain unquantified." }, { "group": "personal", "depth": null, "reason": "Local audiences are intended to benefit from improved information monitoring; a change in their access to trustworthy information is not established." }, { "group": "societal", "depth": null, "reason": "Monitoring problematic content is intended to support peace and linguistic inclusion; those downstream effects are not measured." } ], "ai_role": { "status": "assessed", "statement": "AI converts Swahili and French broadcasts into text. Keyword searches informed by local journalists support monitoring. Use of learned AI in those searches remains unestablished." }, "evidence": [ { "kind": "report", "citation": "International Telecommunication Union, AI for Good: Innovate for Impact (2025). Project-submitted account, current as of June 2025. ITU provides no independent outcome evaluation.", "title": "Use Case 13: Lost in Translation? 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Cost savings remain expected.", "account": "The UAE Ministry of Finance reports that its assistant is in full production and provides instant bilingual answers and document search, reducing routine manual effort. 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Borrower income and net emissions effects are unmeasured.", "category": "general benefit", "unexpected": false, "purpose": "Use vehicle telemetry and risk scoring to expand electric-vehicle financing.", "system": "AIZEN CreditConnect-EV", "model_version": null, "developer": "AIZEN", "deployer": "AIZEN and lending partners", "location": "Indonesia", "domain": "Finance", "segment": null, "benefit_type": "Increased Inclusion", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The source reports financing more than 20,000 electric two-wheelers, representing improved access to an asset and financing. It does not establish higher borrower income or durable financial security." }, { "group": "organizational", "depth": 2, "reason": "The operating financing system supports lending for a previously difficult asset class at reported scale. Portfolio profitability and default improvement are not established." }, { "group": "societal", "depth": null, "reason": "Lower transport pollution is intended. Net emissions attributable to the financing program are unmeasured." } ], "ai_role": { "status": "unassessed", "statement": "The project account does not separately evaluate AI’s contribution to the benefit." }, "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Outcomes are reported by the project team. The account provides no independent outcome evaluation.", "title": "Use Case 3: AIZEN – CreditConnect-EV", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-635", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Conditions that could produce the benefit are unspecified." ], "must_hold": [ "Vehicle and battery telemetry", "Integration with lending workflows" ], "echoes": [] }, "paired_incident": null, "headline": "CreditConnect-EV expands electric-motorcycle financing", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-635", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0487", "catalog_version": "1.0.0", "source_fingerprint": "0928062b1112791d91b534231c36b671c058fa235d5db0b0c121ee62ab238beb", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0487-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "AIZEN", "deployer": "AIZEN and lending partners" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The project account does not separately evaluate AI’s contribution to the benefit." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The source reports financing more than 20,000 electric two-wheelers, representing improved access to an asset and financing. 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"review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": 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It does not establish higher borrower income or durable financial security." }, { "group": "organizational", "depth": 2, "reason": "The operating financing system supports lending for a previously difficult asset class at reported scale. Portfolio profitability and default improvement are not established." }, { "group": "societal", "reason": "Lower transport pollution is intended. 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The account provides no independent outcome evaluation.", "title": "Use Case 3: AIZEN – CreditConnect-EV", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-635", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0487-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. 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Borrower income and net emissions effects are unmeasured." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AIZEN CreditConnect-EV" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "AIZEN" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AIZEN – CreditConnect-EV", "headline": "CreditConnect-EV expands electric-motorcycle financing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0928062b1112791d91b534231c36b671c058fa235d5db0b0c121ee62ab238beb" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "AIZEN reports that CreditConnect-EV financed more than 20,000 electric two-wheelers in Indonesia. Borrower income and net emissions effects are unmeasured.", "replication": { "produced_by": [ "Conditions that could produce the benefit are unspecified." ], "must_hold": [ "Vehicle and battery telemetry", "Integration with lending workflows" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0488", "title": "AI-Powered Payroll Solution (AI Payroll Guard)", "summary": "The UAE Ministry of Finance reports that its live AI-enabled payroll system reduced processing time by up to 95%. AI's share of the wider automation gain is not isolated.", "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "benefit_status": "mixed", "source_collection": "ITU AI for Good: Innovate for Impact (2025)", "source_entry": "ITU-105", "account": "The UAE Ministry of Finance reports that its live federal payroll system reduced processing time by up to 95%. AI's share of the wider automation gain is unknown.", "category": "general benefit", "unexpected": false, "purpose": "Automate payroll processing, validation, and exception handling.", "system": "AI Payroll Guard", "model_version": null, "developer": null, "deployer": "UAE Ministry of Finance and federal entities", "location": "United Arab Emirates", "domain": "Finance", "segment": null, "benefit_type": "Reduced Task Time", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Ministry reports up to 95% less payroll-processing time. AI's share of the wider automation gain is unknown." }, { "group": "personal", "depth": null, "reason": "Timely, accurate salaries are intended. Changes in missed or erroneous payments are unmeasured." } ], "ai_role": { "status": "assessed", "statement": "AI is described as validating payroll data, detecting exceptions, and supporting the interface. Other automation also executes processing and payments, so AI's separate contribution is unknown." }, "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Outcomes are reported by the project team. The account provides no independent outcome evaluation.", "title": "Use Case 4: AI-Powered Payroll Solution (AI Payroll Guard)", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-641", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Conditions that could produce the benefit are unspecified." ], "must_hold": [ "Payroll data validation and human approval checkpoints", "Exception review before payment completion" ], "echoes": [] }, "paired_incident": null, "headline": "AI Payroll Guard cuts federal payroll processing time", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-641", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0488", "catalog_version": "1.0.0", "source_fingerprint": "b8e2a5b83b02e57dd8d6db69ca263cc64d6ca76a2397174a6f89e5307b1a4ac6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0488-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "UAE Ministry of Finance and federal entities" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AI is described as validating payroll data, detecting exceptions, and supporting the interface. Other automation also executes processing and payments, so AI's separate contribution is unknown." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "AI is described as validating payroll data, detecting exceptions, and supporting the interface. 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Changes in missed or erroneous payments are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": 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Fraud and audit-efficiency improvements are projections.", "replication": { "produced_by": [ "Conditions that could produce the benefit are unspecified." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 25, "reviewed": 0, "record_mapped": 25, "not_assessed": 66, "complete": false, "by_state": { "value_present": 25, "not_reported": 0, "unresolved": 0, "not_assessed": 66, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0491", "title": "Strengthening Financial Integrity and International Trust: UAE’s FATCA/CRS Framework", "summary": "The UAE Ministry of Finance reports that its website AI assistant gives real-time FATCA/CRS guidance. Changes in service quality or reporting work are unmeasured.", "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "benefit_status": "reported", "source_collection": "ITU AI for Good: Innovate for Impact (2025)", "source_entry": "ITU-108", "account": "The UAE Ministry of Finance reports that its website includes an AI conversational assistant that answers FATCA/CRS inquiries and provides real-time guidance. The main reporting platform uses rules, without model training. Counts of reporting institutions and international exchange partners describe that wider infrastructure. The assistant’s effect on inquiry resolution, staff time, or user experience is unmeasured.", "category": "general benefit", "unexpected": false, "purpose": "Help users obtain guidance about FATCA/CRS reporting requirements.", "system": "UAE Ministry of Finance FATCA/CRS inquiry assistant", "model_version": null, "developer": null, "deployer": "UAE Ministry of Finance", "location": "United Arab Emirates", "domain": "Finance", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The Ministry reports that an AI assistant provides real-time reporting guidance, but gives no measured improvement in inquiry handling or reporting work attributable to the assistant." } ], "ai_role": { "status": "assessed", "statement": "The identified AI function is conversational guidance for reporting inquiries. Registration, validation and international tax-data exchange belong to a separately described rule-based platform." }, "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Outcomes are reported by the project team. The account provides no independent outcome evaluation.", "title": "Use Case 7: Strengthening Financial Integrity and International Trust: UAE’s FATCA/CRS Framework", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A website conversational AI assistant provides FATCA/CRS guidance" ], "must_hold": [ "Current FATCA/CRS guidance and access to the Ministry website. Other requirements for the assistant are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "AI assistant answers UAE FATCA/CRS reporting inquiries", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0491", "catalog_version": "1.0.0", "source_fingerprint": "be94a50788672a45bc0935410c24bc2fe6d875a5c516be69f0112aa625dbb5d7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0491-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "UAE Ministry of Finance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The identified AI function is conversational guidance for reporting inquiries. 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"state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The UAE Ministry of Finance reports that its website includes an AI conversational assistant that answers FATCA/CRS inquiries and provides real-time guidance. The main reporting platform uses rules, without model training. Counts of reporting institutions and international exchange partners describe that wider infrastructure. The assistant’s effect on inquiry resolution, staff time, or user experience is unmeasured.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The Ministry reports that an AI assistant provides real-time reporting guidance, but gives no measured improvement in inquiry handling or reporting work attributable to the assistant." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Help users obtain guidance about FATCA/CRS reporting requirements." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Arab Emirates" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Help users obtain guidance about FATCA/CRS reporting requirements." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A website conversational AI assistant provides FATCA/CRS guidance" ], "must_hold": [ "Current FATCA/CRS guidance and access to the Ministry website. Other requirements for the assistant are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Finance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Outcomes are reported by the project team. The account provides no independent outcome evaluation.", "title": "Use Case 7: Strengthening Financial Integrity and International Trust: UAE’s FATCA/CRS Framework", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0491-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Outcomes are reported by the project team. The account provides no independent outcome evaluation.", "title": "Use Case 7: Strengthening Financial Integrity and International Trust: UAE’s FATCA/CRS Framework", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-659", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The UAE Ministry of Finance reports that its website AI assistant gives real-time FATCA/CRS guidance. Changes in service quality or reporting work are unmeasured.", "account": "The UAE Ministry of Finance reports that its website includes an AI conversational assistant that answers FATCA/CRS inquiries and provides real-time guidance. The main reporting platform uses rules, without model training. Counts of reporting institutions and international exchange partners describe that wider infrastructure. The assistant’s effect on inquiry resolution, staff time, or user experience is unmeasured." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UAE Ministry of Finance FATCA/CRS inquiry assistant" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Strengthening Financial Integrity and International Trust: UAE’s FATCA/CRS Framework", "headline": "AI assistant answers UAE FATCA/CRS reporting inquiries" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "be94a50788672a45bc0935410c24bc2fe6d875a5c516be69f0112aa625dbb5d7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The UAE Ministry of Finance reports that its website includes an AI conversational assistant that answers FATCA/CRS inquiries and provides real-time guidance. The main reporting platform uses rules, without model training. Counts of reporting institutions and international exchange partners describe that wider infrastructure. The assistant’s effect on inquiry resolution, staff time, or user experience is unmeasured.", "replication": { "produced_by": [ "A website conversational AI assistant provides FATCA/CRS guidance" ], "must_hold": [ "Current FATCA/CRS guidance and access to the Ministry website. Other requirements for the assistant are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0492", "title": "Sustainable Financing Partnership", "summary": "MBRHE reports that AI credit and eligibility models automate housing-loan assessment and remove manual approval bottlenecks. AI’s separate effect is unmeasured.", "date_observed": "2025-06-01", "date_basis": "source information", "date_precision": "month", "benefit_status": "reported", "source_collection": "ITU AI for Good: Innovate for Impact (2025)", "source_entry": "ITU-109", "account": "MBRHE reports that AI models evaluate housing-loan eligibility and priority using credit, income and social criteria. It identifies logistic regression, decision trees and ensemble models trained with historical approvals and credit-bureau data. The models are described as removing manual approval bottlenecks within a service integrated with Emirates Islamic Bank. Full deployment is dated to Q1 2025. Bank financing, interest subsidies, APIs and digital identity also contribute to the overall program. Its loan volume, budget savings and workload totals do not isolate the models’ contribution.", "category": "general benefit", "unexpected": false, "purpose": "Reduce manual work and delays in housing-loan eligibility assessment.", "system": "MBRHE AI housing-loan credit and eligibility assessment", "model_version": null, "developer": null, "deployer": "Mohammed Bin Rashid Housing Establishment and Emirates Islamic Bank", "location": "Dubai, United Arab Emirates", "domain": "Finance", "segment": null, "benefit_type": "Reduced Task Time", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "MBRHE reports that AI automates credit and eligibility evaluation and removes manual approval bottlenecks. AI’s share of the wider program’s reported 30% workload reduction is unknown." }, { "group": "personal", "depth": 1, "reason": "MBRHE reports that automated eligibility evaluation helps applicants move through approval more quickly. 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Waiting-time improvements are unmeasured.", "category": "general benefit", "unexpected": false, "purpose": "Increase parking capacity and simplify vehicle storage and retrieval.", "system": "AI robotic parking and scheduling system", "model_version": null, "developer": null, "deployer": null, "location": null, "domain": "Smart home/cities", "segment": null, "benefit_type": "Increased Scalability", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Shanghai AI Research Institute estimates that single-layer robotic layouts can increase capacity by 60–80%. No measured capacity increase at a specified garage is reported." }, { "group": "personal", "depth": 1, "reason": "The source describes easier parking and vehicle retrieval through robotic operation. 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Effects on access and independence remain unverified." } ], "ai_role": { "status": "unassessed", "statement": "Nara’s patent specifies deep-learning speech recognition for user control. Its use in the Blind Metaverse demo and effect on users remain unverified. The demo also integrates Google Cloud speech synthesis, but the exact Korean Standard voice model is unverified." }, "evidence": [ { "kind": "other", "citation": "Nara Knowledge Information, patent KR102807935B1, May 16, 2025, paragraphs 0163–0168. Describes deep-learning speech recognition for a metaverse and Braille interface. The connection to Blind Metaverse is inferred from the assignee, inventor, purpose, and architecture. The patent does not name the product, demonstrate deployment, or evaluate outcomes.", "title": "Nara patent for converting a visual interface into an accessible tactile interface", "url": "https://patents.google.com/patent/KR102807935B1/en", "date": "2025-05-16", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Nara project account in International Telecommunication Union, AI for Good: Innovate for Impact, 2025. Information current as of June 2025. Describes an accessibility demonstration and user feedback. Deployment and benefits of the patented speech-recognition function remain unverified.", "title": "Use Case 7: Blind Metaverse", "url": "https://www.itu.int/epublications/publication/ai-for-good-innovate-for-impact#_idParaDest-866", "date": null, "written_by": "makers", "quote": null }, { "kind": "other", "citation": "Blind_DemoApp_iOS, commit a757db268dde983d49d7ad9b135dfe67be318f73, Assets/blindScript/JoyStickTTS.cs. 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A Nara patent describes deep-learning speech recognition that interprets spoken input from a Braille terminal and controls the computing device. Its connection to Blind Metaverse is inferred from the assignee, inventor, purpose, and interface design. The patent does not name the product. The public demo integrates Google Cloud speech synthesis, although the exact model behind its Korean Standard voice is unspecified. Nara reports exhibition use of the accessibility platform. The sources do not confirm deployment of the patented speech-recognition function or measure its effect on users.", "replication": { "produced_by": [ "The patent proposes a deep-learning speech-recognition model that converts spoken input from a Braille terminal into control of the computing device supporting the metaverse interface." ], "must_hold": [ "The proposed design requires speech recognition, compatible audio input and Braille interfaces, and integration with the virtual environment. Conditions sufficient to improve access remain unknown." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0580", "title": "Lynxight alerts lifeguards to an unconscious swimmer at Inglewood Pool; he recovers fully after rescue", "summary": "Lynxight sent his location and images from the pool’s cameras to a lifeguard’s smartwatch.", "date_observed": "2025-06-10", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "On June 10, 2025, a man suffered a medical episode and sank in the outdoor pool at Stirling Leisure - Inglewood, Perth. Lynxight sent lifeguard Cameron Menzies a smartwatch alert with the swimmer's location and images. Another swimmer, Ofer Lefelman, independently noticed the emergency and lifted the man to the surface. Menzies and fellow lifeguards brought him out of the water. The City of Stirling reports that he was conscious when paramedics took him away and later recovered fully. ABC subsequently interviewed the city's operations coordinator, who credited the alert with accelerating the lifeguard's response.", "category": "harm prevented", "unexpected": false, "purpose": "Detect swimmers in distress and alert lifeguards.", "system": "Lynxight AI pool monitoring with CCTV analysis and smartwatch alerts", "model_version": null, "developer": "Lynxight", "deployer": "City of Stirling", "location": "Stirling Leisure - Inglewood, Perth, Western Australia, Australia", "domain": "Aquatic safety and rescue", "segment": "Public swimming pools", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "An unconscious swimmer survived and recovered fully after a rescue supported by an AI alert. Another swimmer also intervened independently." } ], "ai_role": { "status": "assessed", "statement": "Lynxight detected distress and alerted the lifeguard, who had not seen the man sink. Human rescuers brought him to safety. Whether he would have survived without the alert is unknown." }, "evidence": [ { "kind": "press release", "citation": "City of Stirling, July 1, 2025.", "title": "Power of anti-drowning technology on display at Stirling Leisure - Inglewood in WA’s first AI-assisted pool rescue", "url": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "date": "2025-07-01", "written_by": "deployer", "quote": "The swimmer was conscious and talking when he was taken away by paramedics and has since made a full recovery." }, { "kind": "news report", "citation": "Petroska, R. (2025). AI pool monitoring system helps save life of swimmer suffering medical episode in the water. 7NEWS, July 1, 2025.", "title": "AI pool monitoring system helps save life of swimmer suffering medical episode in the water", "url": "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "date": "2025-07-01", "written_by": "independent", "quote": "Lifeguards were sent an urgent alert at the same time fellow swimmer Ofer Lefelman noticed something was wrong." }, { "kind": "news report", "citation": "Lauren Smith and Isabel Moussalli, ABC News, December 31, 2025.", "title": "AI technology gives swimming pool lifeguards an extra set of eyes this summer", "url": "https://www.abc.net.au/news/2025-12-31/ai-system-to-help-lifeguards-in-pools-swim-safety/106172140", "date": "2025-12-31", "written_by": "independent", "quote": "our lifeguard was there pretty much a few seconds after that" }, { "kind": "report", "citation": "Lynxight. “מדיניות פרטיות לאימון המערכת ולשיפורה” [Privacy policy for training and improving the system]. Effective August 23, 2026. Company details and contact information.", "title": "מדיניות פרטיות לאימון המערכת ולשיפורה", "url": "https://www.lynxight.com/legal/privacy-policy-pools-he", "date": "2026-08-23", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Camera analysis identified distress and sent a location alert.", "A nearby swimmer and trained lifeguards performed the rescue." ], "must_hold": [ "The system must detect distress and deliver an alert that lifeguards can act on promptly." ], "echoes": [] }, "paired_incident": null, "headline": "Lifeguards and a fellow swimmer rescued an unconscious man", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "Israel", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the PerthNow account to the original July 1, 2025 7NEWS report. Retained the City of Stirling's original account, the original interviews with the swimmer and lifeguard, and ABC's separate later interview. Preserved that a bystander noticed the emergency and pulled the swimmer up, independently of the lifeguard alert.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added Israel as the developer jurisdiction from Lynxight’s own company-address statement. Retained the policy only for corporate geography and preserved the event date, beneficiary account, system attribution, and ratings.", "source": "https://www.lynxight.com/legal/privacy-policy-pools-he", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, the makers' report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0580", "catalog_version": "1.0.0", "source_fingerprint": "c59b561f1965f0513531983bd68b819e8e40dce2523d8ea5c9a9594bc9dd78f7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Lynxight", "deployer": "City of Stirling" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Lynxight detected distress and alerted the lifeguard, who had not seen the man sink. 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Another swimmer also intervened independently." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule retained. Originality, authorship, and independence are assessed separately in the source lineage. 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0580" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On June 10, 2025, a man suffered a medical episode and sank in the outdoor pool at Stirling Leisure - Inglewood, Perth. Lynxight sent lifeguard Cameron Menzies a smartwatch alert with the swimmer's location and images. Another swimmer, Ofer Lefelman, independently noticed the emergency and lifted the man to the surface. Menzies and fellow lifeguards brought him out of the water. The City of Stirling reports that he was conscious when paramedics took him away and later recovered fully. ABC subsequently interviewed the city's operations coordinator, who credited the alert with accelerating the lifeguard's response.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "An unconscious swimmer survived and recovered fully after a rescue supported by an AI alert. Another swimmer also intervened independently." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect swimmers in distress and alert lifeguards." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "location": "Stirling Leisure - Inglewood, Perth, Western Australia, Australia", "developer_country": "Israel", "deployer_country": "Australia", "developer_jurisdictions": [ "Israel" ], "case_jurisdictions": [ "Australia" ] } }, "provenance": { "kind": "source_review", "basis": "Lynxight’s Hebrew policy, effective August 23, 2026, identifies Lynxight Ltd. at 1 HaTzmicha Street, Yokneam Illit, Israel. This establishes the company’s stated jurisdiction as of the policy date, not an independently verified historical address on the June 2025 rescue date. The existing Australian deployer and benefit location are preserved from the reviewed City of Stirling account. The policy adds no evidence about the rescue outcome.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The rescue occurred at Stirling Leisure - Inglewood in Perth, Australia. Lynxight is based in Israel, and the pool operator is Australian.", "editor_note": "" } }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect swimmers in distress and alert lifeguards." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-10", "date_basis": "event", "date_precision": "day", "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the PerthNow account to the original July 1, 2025 7NEWS report. Retained the City of Stirling's original account, the original interviews with the swimmer and lifeguard, and ABC's separate later interview. Preserved that a bystander noticed the emergency and pulled the swimmer up, independently of the lifeguard alert.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added Israel as the developer jurisdiction from Lynxight’s own company-address statement. Retained the policy only for corporate geography and preserved the event date, beneficiary account, system attribution, and ratings.", "source": "https://www.lynxight.com/legal/privacy-policy-pools-he", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Added the geography review to the revision history and preserved the previously assessed event chronology and its evidence.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera analysis identified distress and sent a location alert.", "A nearby swimmer and trained lifeguards performed the rescue." ], "must_hold": [ "The system must detect distress and deliver an alert that lifeguards can act on promptly." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-23", "change": "Added the case.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the PerthNow account to the original July 1, 2025 7NEWS report. Retained the City of Stirling's original account, the original interviews with the swimmer and lifeguard, and ABC's separate later interview. Preserved that a bystander noticed the emergency and pulled the swimmer up, independently of the lifeguard alert.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added Israel as the developer jurisdiction from Lynxight’s own company-address statement. Retained the policy only for corporate geography and preserved the event date, beneficiary account, system attribution, and ratings.", "source": "https://www.lynxight.com/legal/privacy-policy-pools-he", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Added the geography review to the revision history and preserved the previously assessed event chronology and its evidence.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Aquatic safety and rescue", "segment": "Public swimming pools" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "versions_and_access": [ { "source_url": "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "published_on": "2025-07-01", "status": "Original interviews and published date read." }, { "source_url": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "status": "Operator article read through its indexed original page; repeated direct fetches timed out." }, { "source_url": "https://www.lynxight.com/legal/privacy-policy-pools-he", "source_ref": "AIBD-0580-source-0004", "accessed_on": "2026-10-25", "language": "Hebrew", "status": "Original developer webpage inspected for corporate geography.", "locator": "Company details and contact information: Lynxight Ltd., 1 HaTzmicha Street, Yokneam Illit, Israel. Effective date at the beginning of the page.", "effective_date": "2026-08-23" } ], "limitations": [ "The swimmer's clinical records and raw detection/alert timing are unavailable.", "The sources do not establish what would have happened without the alert. The bystander was already responding." ] } }, "provenance": { "kind": "source_review", "basis": "Inspected the additional corporate-geography source and retained prior access and identity limitations.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The pool operator and subsequent reporting describe the rescue. Clinical records and raw alert timings are unavailable. A bystander had already begun responding, so the alert’s effect on the outcome cannot be isolated.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "City of Stirling, July 1, 2025.", "title": "Power of anti-drowning technology on display at Stirling Leisure - Inglewood in WA’s first AI-assisted pool rescue", "url": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "date": "2025-07-01", "written_by": "deployer", "quote": "The swimmer was conscious and talking when he was taken away by paramedics and has since made a full recovery." }, { "kind": "news report", "citation": "Petroska, R. (2025). AI pool monitoring system helps save life of swimmer suffering medical episode in the water. 7NEWS, July 1, 2025.", "title": "AI pool monitoring system helps save life of swimmer suffering medical episode in the water", "url": "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "date": "2025-07-01", "written_by": "independent", "quote": "Lifeguards were sent an urgent alert at the same time fellow swimmer Ofer Lefelman noticed something was wrong." }, { "kind": "news report", "citation": "Lauren Smith and Isabel Moussalli, ABC News, December 31, 2025.", "title": "AI technology gives swimming pool lifeguards an extra set of eyes this summer", "url": "https://www.abc.net.au/news/2025-12-31/ai-system-to-help-lifeguards-in-pools-swim-safety/106172140", "date": "2025-12-31", "written_by": "independent", "quote": "our lifeguard was there pretty much a few seconds after that" }, { "kind": "report", "citation": "Lynxight. “מדיניות פרטיות לאימון המערכת ולשיפורה” [Privacy policy for training and improving the system]. Effective August 23, 2026. Company details and contact information.", "title": "מדיניות פרטיות לאימון המערכת ולשיפורה", "url": "https://www.lynxight.com/legal/privacy-policy-pools-he", "date": "2026-08-23", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Appended an original corporate-geography source while preserving the existing evidence, ordering, and clinical or system-identity qualifications.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "role": "Retained evidence sources in reviewed order" }, "provenance": { "kind": "source_review", "basis": "Preserved all existing source identifiers and appended the primary corporate-geography source.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "City of Stirling, July 1, 2025.", "title": "Power of anti-drowning technology on display at Stirling Leisure - Inglewood in WA’s first AI-assisted pool rescue", "url": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "date": "2025-07-01", "written_by": "deployer", "quote": "The swimmer was conscious and talking when he was taken away by paramedics and has since made a full recovery." }, { "kind": "news report", "citation": "Petroska, R. (2025). AI pool monitoring system helps save life of swimmer suffering medical episode in the water. 7NEWS, July 1, 2025.", "title": "AI pool monitoring system helps save life of swimmer suffering medical episode in the water", "url": "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "date": "2025-07-01", "written_by": "independent", "quote": "Lifeguards were sent an urgent alert at the same time fellow swimmer Ofer Lefelman noticed something was wrong." }, { "kind": "news report", "citation": "Lauren Smith and Isabel Moussalli, ABC News, December 31, 2025.", "title": "AI technology gives swimming pool lifeguards an extra set of eyes this summer", "url": "https://www.abc.net.au/news/2025-12-31/ai-system-to-help-lifeguards-in-pools-swim-safety/106172140", "date": "2025-12-31", "written_by": "independent", "quote": "our lifeguard was there pretty much a few seconds after that" }, { "kind": "report", "citation": "Lynxight. “מדיניות פרטיות לאימון המערכת ולשיפורה” [Privacy policy for training and improving the system]. Effective August 23, 2026. Company details and contact information.", "title": "מדיניות פרטיות לאימון המערכת ולשיפורה", "url": "https://www.lynxight.com/legal/privacy-policy-pools-he", "date": "2026-08-23", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Appended an original corporate-geography source while preserving the existing evidence, ordering, and clinical or system-identity qualifications.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0580-source-0001", "retained_source_order": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "origins": [ { "url": "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "contribution": "Original operator account dates the incident to June 10 and reports recovery.", "locator": "Incident description, Cameron Menzies's account, and recovery statement.", "relationship": "Deployer report. No raw alert log or medical record is supplied.", "source_refs": [ "AIBD-0580-source-0001" ], "display_name": "City of Stirling" }, { "url": "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "contribution": "Direct interviews add the bystander's actions and the lifeguard's cautious description of the alert.", "locator": "Ofer Lefelman and Cameron interviews in the report.", "relationship": "Original reporting; same rescue, not a clinical counterfactual.", "source_refs": [ "AIBD-0580-source-0002" ] }, { "url": "https://www.abc.net.au/news/2025-12-31/ai-system-to-help-lifeguards-in-pools-swim-safety/106172140", "contribution": "Separate interview with the city's leisure manager describes the sequence of bystander and lifeguard arrival.", "locator": "Duncan Hutton interview about the Inglewood rescue.", "relationship": "Original later reporting based on operator testimony; no independent clinical verification.", "source_refs": [ "AIBD-0580-source-0003" ] }, { "url": "https://www.lynxight.com/legal/privacy-policy-pools-he", "contribution": "Establishes the developer’s company address in Israel. Retained for corporate geography only.", "locator": "Company details and contact information: Lynxight Ltd., 1 HaTzmicha Street, Yokneam Illit, Israel. Effective date at the beginning of the page.", "relationship": "Original developer policy in Hebrew. It supplies no new evidence about the swimmer’s rescue or recovery.", "source_refs": [ "AIBD-0580-source-0004" ], "display_name": "Lynxight" } ], "claim_chains": [ { "claim": "Alert, rescue and recovery", "path": [ "https://www.stirling.wa.gov.au/city-and-council/news/power-of-anti-drowning-technology-on-display-at-stirling-leisure-%E2%80%93-inglewood-in-wa%E2%80%99s-first-ai-assist", "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045", "https://www.abc.net.au/news/2025-12-31/ai-system-to-help-lifeguards-in-pools-swim-safety/106172140" ], "finding": "The operator is the original source for the June 10 date and full recovery. The two original reports add interviews and the crucial human-rescuer qualification." }, { "claim": "Secondary-source origin", "path": [ "https://www.perthnow.com.au/wa/perth/north/stirling/ai-pool-monitoring-system-in-stirling-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19213706", "https://7news.com.au/news/ai-pool-monitoring-system-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19203045" ], "finding": "PerthNow repeats 7NEWS interviews. The original 7NEWS report replaces it rather than being counted alongside it." }, { "claim": "Developer jurisdiction and geographic scope", "path": [ "https://www.lynxight.com/legal/privacy-policy-pools-he" ], "finding": "Lynxight’s Hebrew policy, effective August 23, 2026, identifies Lynxight Ltd. at 1 HaTzmicha Street, Yokneam Illit, Israel. This establishes the company’s stated jurisdiction as of the policy date, not an independently verified historical address on the June 2025 rescue date. The existing Australian deployer and benefit location are preserved from the reviewed City of Stirling account. The policy adds no evidence about the rescue outcome." } ], "limitations": [ "The swimmer's clinical records and raw detection/alert timing are unavailable.", "The sources do not establish what would have happened without the alert. The bystander was already responding." ], "excluded_or_consolidated_sources": [ { "url": "https://www.perthnow.com.au/wa/perth/north/stirling/ai-pool-monitoring-system-in-stirling-helps-save-life-of-swimmer-suffering-medical-episode-in-the-water-c-19213706", "reason": "Republication of the 7NEWS report, with no additional evidence for this case." } ], "review_scope": "Traced the claims in this case through accessible original publications and relevant embedded references, tables, appendices, corrections, and supplements. The stated access limits remain unresolved. Additional review on October 25, 2026, establishes developer jurisdiction and clarifies geographic scope; prior clinical and attribution limitations remain unchanged." } }, "provenance": { "kind": "source_review", "basis": "Added corporate geography and its original source without repeating or replacing the prior clinical and system-identity assessments.", "record_fields": [ "evidence", "developer_country", "location" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003", "AIBD-0580-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The City of Stirling reports the rescue. Separate 7NEWS and ABC interviews add accounts from a bystander, lifeguard, and leisure manager. Lynxight’s policy establishes its corporate address, not the rescue outcome.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Lynxight sent his location and images from the pool’s cameras to a lifeguard’s smartwatch.", "account": "On June 10, 2025, a man suffered a medical episode and sank in the outdoor pool at Stirling Leisure - Inglewood, Perth. Lynxight sent lifeguard Cameron Menzies a smartwatch alert with the swimmer's location and images. Another swimmer, Ofer Lefelman, independently noticed the emergency and lifted the man to the surface. Menzies and fellow lifeguards brought him out of the water. The City of Stirling reports that he was conscious when paramedics took him away and later recovered fully. ABC subsequently interviewed the city's operations coordinator, who credited the alert with accelerating the lifeguard's response." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "inputs": "Images from the pool’s existing CCTV cameras.", "outputs": "A smartwatch alert with the swimmer’s location and camera images.", "human_action": "Lifeguards and a fellow swimmer rescued the swimmer.", "unreported_details": [ "Underlying model and release", "Installed software version", "Specific camera model" ] } }, "provenance": { "kind": "source_review", "basis": "Recorded the deployment components that the original case accounts describe.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Lynxight analyzed images from the pool’s existing cameras and sent a smartwatch alert with the swimmer’s location and camera images.", "editor_note": "" } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The original pool-operator account and subsequent reporting identify Lynxight, but do not name the underlying model, release, camera model, or installed software version.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003" ], "reviewed_on": "2026-10-24" }, "reason": "The original pool-operator account and subsequent reporting identify Lynxight, but do not name the underlying model, release, camera model, or installed software version.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Lynxight’s detector for unusual swimmer behavior. The operator’s account gives no separate model name.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "The original pool-operator account and subsequent reporting identify Lynxight, but do not name the underlying model, release, camera model, or installed software version.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003" ], "reviewed_on": "2026-10-24" }, "reason": "The original pool-operator account and subsequent reporting identify Lynxight, but do not name the underlying model, release, camera model, or installed software version.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The installed model and software releases are not disclosed.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Lynxight AI pool monitoring with CCTV analysis and smartwatch alerts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Lynxight", "underlying_model_provider": "No separate model provider is identified." } }, "provenance": { "kind": "source_review", "basis": "The original operator or research-institution report identifies the application developer.", "record_fields": [ "developer", "system" ], "source_refs": [ "AIBD-0580-source-0001", "AIBD-0580-source-0002", "AIBD-0580-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lynxight alerts lifeguards to an unconscious swimmer at Inglewood Pool; he recovers fully after rescue", "headline": "Lifeguards and a fellow swimmer rescued an unconscious man" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c59b561f1965f0513531983bd68b819e8e40dce2523d8ea5c9a9594bc9dd78f7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after the system-identity and model-version review.", "record_fields": [ "revisions" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On June 10, 2025, a man suffered a medical episode and sank in the outdoor pool at Stirling Leisure - Inglewood, Perth. Lynxight sent lifeguard Cameron Menzies a smartwatch alert with the swimmer's location and images. Another swimmer, Ofer Lefelman, independently noticed the emergency and lifted the man to the surface. Menzies and fellow lifeguards brought him out of the water. The City of Stirling reports that he was conscious when paramedics took him away and later recovered fully. ABC subsequently interviewed the city's operations coordinator, who credited the alert with accelerating the lifeguard's response.", "replication": { "produced_by": [ "Camera analysis identified distress and sent a location alert.", "A nearby swimmer and trained lifeguards performed the rescue." ], "must_hold": [ "The system must detect distress and deliver an alert that lifeguards can act on promptly." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 13, "record_mapped": 21, "not_assessed": 57, "complete": false, "by_state": { "value_present": 32, "not_reported": 2, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0555", "title": "Northumberland County Council- FloodAI, using AI to detect flash floods", "summary": "Northumberland describes an alpha-stage flood-forecasting service for six catchments. No issued warning or avoided flood impact is reported.", "date_observed": "2025-06-17", "date_basis": "source publication", "date_precision": "day", "benefit_status": "intended", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-019", "account": "Northumberland's FloodAI research project is developing forecasts for six flash-flood-prone catchments. At publication, the system was at alpha stage and approaching limited piloting. No issued warning or avoided flood impact is documented.", "category": "general benefit", "unexpected": false, "purpose": "Develop forecasts for flash-flood-prone catchments that lack suitable warning coverage.", "system": "FloodAI machine-learning flood-forecasting service", "model_version": null, "developer": "Northumbria University with project partners", "deployer": "Northumberland County Council", "location": "United Kingdom", "domain": "Flood forecasting and resilience", "segment": null, "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Improved flood resilience is the aim, but no warning or changed flood outcome is reported." }, { "group": "organizational", "depth": null, "reason": "Improved forecasting is intended. Operational gains are unreported." } ], "ai_role": { "status": "unassessed", "statement": "Machine-learning models combine environmental and hydrological data to support flash-flood forecasting. At publication, the service was at alpha stage. No warning, response, or avoided harm is attributed to operational use." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Northumberland County Council- FloodAI, using AI to detect flash floods", "url": "https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods", "date": "2025-06-17", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The project covers six catchments and combines university research with council, Arup, Isle Utilities, and Environment Agency participation.", "Training sources include Met Office, Environment Agency, and hydrological-model data." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] }, "paired_incident": null, "headline": "Northumberland develops FloodAI for six flash-flood catchments", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0555", "catalog_version": "1.0.0", "source_fingerprint": "589c36be629b9a2b577abb0fa645fc80cbbbd459b8391db57c9358ed299cf737", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0555-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Northumbria University with project partners", "deployer": "Northumberland County Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Machine-learning models combine environmental and hydrological data to support flash-flood forecasting. At publication, the service was at alpha stage. No warning, response, or avoided harm is attributed to operational use." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Improved flood resilience is the aim, but no warning or changed flood outcome is reported." }, { "group": "organizational", "reason": "Improved forecasting is intended. Operational gains are unreported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Intended benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Improved flood resilience is the aim, but no warning or changed flood outcome is reported." }, { "group": "organizational", "reason": "Improved forecasting is intended. Operational gains are unreported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-019" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0555" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Northumberland's FloodAI research project is developing forecasts for six flash-flood-prone catchments. At publication, the system was at alpha stage and approaching limited piloting. No issued warning or avoided flood impact is documented.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Improved flood resilience is the aim, but no warning or changed flood outcome is reported." }, { "group": "organizational", "reason": "Improved forecasting is intended. Operational gains are unreported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "intended" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Develop forecasts for flash-flood-prone catchments that lack suitable warning coverage." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Develop forecasts for flash-flood-prone catchments that lack suitable warning coverage." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-17", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The project covers six catchments and combines university research with council, Arup, Isle Utilities, and Environment Agency participation.", "Training sources include Met Office, Environment Agency, and hydrological-model data." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Flood forecasting and resilience" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. 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The account provides no independent outcome evaluation.", "title": "Northumberland County Council- FloodAI, using AI to detect flash floods", "url": "https://www.local.gov.uk/case-studies/northumberland-county-council-floodai-using-ai-detect-flash-floods", "date": "2025-06-17", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Northumberland describes an alpha-stage flood-forecasting service for six catchments. No issued warning or avoided flood impact is reported.", "account": "Northumberland's FloodAI research project is developing forecasts for six flash-flood-prone catchments. At publication, the system was at alpha stage and approaching limited piloting. No issued warning or avoided flood impact is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FloodAI machine-learning flood-forecasting service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Northumbria University with project partners" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Northumberland County Council- FloodAI, using AI to detect flash floods", "headline": "Northumberland develops FloodAI for six flash-flood catchments" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "589c36be629b9a2b577abb0fa645fc80cbbbd459b8391db57c9358ed299cf737" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Northumberland's FloodAI research project is developing forecasts for six flash-flood-prone catchments. At publication, the system was at alpha stage and approaching limited piloting. No issued warning or avoided flood impact is documented.", "replication": { "produced_by": [ "The project covers six catchments and combines university research with council, Arup, Isle Utilities, and Environment Agency participation.", "Training sources include Met Office, Environment Agency, and hydrological-model data." ], "must_hold": [ "The conditions needed to reproduce the benefit are unspecified." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0316", "title": "UNDP hands SESU the Ukrainian “Mines Eye” AI aerial detection system after a pilot that scanned over 360 hectares in Kharkiv and Mykolaiv oblasts", "summary": "Mines Eye (magnetometry, visual/infrared imaging, AI detection of explosive remnants) scanned over 360 ha in a five-month SESU pilot; handed over 21 June 2025. No detection or land-release counts.", "date_observed": "2025-06-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "UNDP Ukraine's press release of 21 June 2025 is datelined Mykolaiv. It says UNDP “officially handed over the Mines Eye aerial detection system to the State Emergency Service of Ukraine (SESU)”. Financial support came from the Government of Luxembourg. The base of SESU's Main Department in Mykolaiv oblast hosted it, with UNDP Acting Administrator Haoliang Xu present. The release calls the system “Developed in Ukraine” but does not name the developer. It combines magnetometry with visual and infrared aerial imaging. It states that “Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation”. It produces maps and anomaly reports for operators before manual or mechanical clearance. UNDP-trained SESU teams ran a five-month pilot. They “used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts”. SESU First Deputy Head Vitalii Myroniuk is quoted that the technology “enables us to detect threats in areas that are too dangerous for manual inspection”. The release gives no number of items detected or confirmed, no hectares released, and no accuracy figure. UNDP's 26 June 2025 release concerned a testing exhibition with mock devices. No source independent of UNDP or SESU was found.", "category": "general benefit", "unexpected": false, "purpose": "Built to survey contaminated land remotely and flag explosive remnants of war, including anti-tank mines under vegetation. This lets clearance teams plan safely. The pilot was that intended use.", "system": "Mines Eye aerial detection system (unmanned aerial platform with magnetometry, visual and infrared sensors, and AI detection of explosive remnants of war)", "model_version": null, "developer": "Ukrainian developer not named in the UNDP release ('Developed in Ukraine')", "deployer": "State Emergency Service of Ukraine (SESU), Kharkiv and Mykolaiv oblast demining teams; procured by UNDP with funding from the Government of Luxembourg", "location": "Kharkiv and Mykolaiv oblasts, Ukraine", "domain": "Humanitarian mine action", "segment": "State emergency service survey of hazardous areas", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": "No detection or land release is reported; the type names the agency's stated aim of faster survey.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "SESU scanned over 360 hectares with the system during the pilot. The release gives no detection counts, confirmation rates or clearance results against which to measure the benefit." }, { "group": "societal", "depth": null, "reason": "No land released to communities, casualty avoided or farmland restored is documented. The officials' statements about faster and safer demining are expectations." } ], "ai_role": { "status": "assessed", "statement": "UNDP's release attributes the detection of explosive remnants beneath vegetation to the system's artificial intelligence working on magnetometry and visual and infrared imagery. It reports only area scanned. No detection, false-alarm or confirmation figure is given. No source independent of UNDP and SESU was found. The developer is unnamed, so the AI component cannot be characterized further." }, "evidence": [ { "kind": "press release", "citation": "UNDP Ukraine (2025). UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations. Press release, Mykolaiv, 21 June 2025 (UNDP is the funder and implementer, not the developer).", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation." }, { "kind": "press release", "citation": "UNDP Ukraine (2025). Same release, pilot results paragraph.", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts" } ], "replication": { "produced_by": [ "UNDP-trained SESU teams flying the system over confirmed and suspected hazardous areas during a five-month pilot", "Donor funding (Government of Luxembourg) for procurement and training" ], "must_hold": [ "Anomaly reports are followed by manual or mechanical clearance that confirms the detections. The release documents no such confirmation.", "Terrain and vegetation resemble the Kharkiv and Mykolaiv pilot areas" ], "echoes": [] }, "paired_incident": null, "headline": "UNDP hands Mines Eye to SESU after a pilot scanning over 360 ha", "metric": "scan over 360 hectares of confirmed and suspected hazardous areas", "comparator": { "against": "manual inspection of hazardous areas", "before": "areas that are too dangerous for manual inspection", "after": "survey dangerous areas quickly, precisely, and without risk to people", "basis": "assumed", "quote": "This technology is a smart solution that allows us to survey dangerous areas quickly, precisely, and without risk to people,” Myroniuk said. “It enables us to detect threats in areas that are too dangerous for manual inspection.", "url": "https://web.archive.org/web/20260114205650/https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations" }, "later": { "status": "unknown", "date": null, "note": "No source dated after the 21 June 2025 handover was found; the release itself only states that the system will be integrated into SESU's toolbox and deployed across Ukraine.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Ukraine", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://web.archive.org/web/20260114205650/https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/State_Emergency_Service_of_Ukraine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0316", "catalog_version": "1.0.0", "source_fingerprint": "c16272e410a7b896b68f645e21a63ace3781b89731eb0ef2ef97cf08562dc694", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0316-source-0001", "AIBD-0316-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Ukrainian developer not named in the UNDP release ('Developed in Ukraine')", "deployer": "State Emergency Service of Ukraine (SESU), Kharkiv and Mykolaiv oblast demining teams; procured by UNDP with funding from the Government of Luxembourg" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "UNDP's release attributes the detection of explosive remnants beneath vegetation to the system's artificial intelligence working on magnetometry and visual and infrared imagery. It reports only area scanned. No detection, false-alarm or confirmation figure is given. No source independent of UNDP and SESU was found. The developer is unnamed, so the AI component cannot be characterized further." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "UNDP's release attributes the detection of explosive remnants beneath vegetation to the system's artificial intelligence working on magnetometry and visual and infrared imagery. It reports only area scanned. No detection, false-alarm or confirmation figure is given. No source independent of UNDP and SESU was found. The developer is unnamed, so the AI component cannot be characterized further." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "SESU scanned over 360 hectares with the system during the pilot. The release gives no detection counts, confirmation rates or clearance results against which to measure the benefit." }, { "group": "societal", "reason": "No land released to communities, casualty avoided or farmland restored is documented. The officials' statements about faster and safer demining are expectations." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "SESU scanned over 360 hectares with the system during the pilot. 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SESU First Deputy Head Vitalii Myroniuk is quoted that the technology “enables us to detect threats in areas that are too dangerous for manual inspection”. The release gives no number of items detected or confirmed, no hectares released, and no accuracy figure. UNDP's 26 June 2025 release concerned a testing exhibition with mock devices. 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UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations. Press release, Mykolaiv, 21 June 2025 (UNDP is the funder and implementer, not the developer).", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation." }, { "kind": "press release", "citation": "UNDP Ukraine (2025). Same release, pilot results paragraph.", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0316-source-0001", "AIBD-0316-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "UNDP Ukraine (2025). UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations. Press release, Mykolaiv, 21 June 2025 (UNDP is the funder and implementer, not the developer).", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation." }, { "kind": "press release", "citation": "UNDP Ukraine (2025). Same release, pilot results paragraph.", "title": "UNDP equips SESU with cutting-edge Ukrainian aerial detection technology to accelerate humanitarian demining operations", "url": "https://www.undp.org/ukraine/press-releases/undp-equips-sesu-cutting-edge-ukrainian-aerial-detection-technology-accelerate-humanitarian-demining-operations", "date": "2025-06-21", "written_by": "deployer", "quote": "used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Mines Eye (magnetometry, visual/infrared imaging, AI detection of explosive remnants) scanned over 360 ha in a five-month SESU pilot; handed over 21 June 2025. No detection or land-release counts.", "account": "UNDP Ukraine's press release of 21 June 2025 is datelined Mykolaiv. It says UNDP “officially handed over the Mines Eye aerial detection system to the State Emergency Service of Ukraine (SESU)”. Financial support came from the Government of Luxembourg. The base of SESU's Main Department in Mykolaiv oblast hosted it, with UNDP Acting Administrator Haoliang Xu present. The release calls the system “Developed in Ukraine” but does not name the developer. It combines magnetometry with visual and infrared aerial imaging. It states that “Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation”. It produces maps and anomaly reports for operators before manual or mechanical clearance. UNDP-trained SESU teams ran a five-month pilot. They “used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts”. SESU First Deputy Head Vitalii Myroniuk is quoted that the technology “enables us to detect threats in areas that are too dangerous for manual inspection”. The release gives no number of items detected or confirmed, no hectares released, and no accuracy figure. UNDP's 26 June 2025 release concerned a testing exhibition with mock devices. 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It says UNDP “officially handed over the Mines Eye aerial detection system to the State Emergency Service of Ukraine (SESU)”. Financial support came from the Government of Luxembourg. The base of SESU's Main Department in Mykolaiv oblast hosted it, with UNDP Acting Administrator Haoliang Xu present. The release calls the system “Developed in Ukraine” but does not name the developer. It combines magnetometry with visual and infrared aerial imaging. It states that “Using artificial intelligence, it detects explosive remnants of war (ERW), including anti-tank mines, even beneath vegetation”. It produces maps and anomaly reports for operators before manual or mechanical clearance. UNDP-trained SESU teams ran a five-month pilot. They “used the system to scan over 360 hectares of confirmed and suspected hazardous areas in Kharkiv and Mykolaiv oblasts”. SESU First Deputy Head Vitalii Myroniuk is quoted that the technology “enables us to detect threats in areas that are too dangerous for manual inspection”. The release gives no number of items detected or confirmed, no hectares released, and no accuracy figure. UNDP's 26 June 2025 release concerned a testing exhibition with mock devices. No source independent of UNDP or SESU was found.", "replication": { "produced_by": [ "UNDP-trained SESU teams flying the system over confirmed and suspected hazardous areas during a five-month pilot", "Donor funding (Government of Luxembourg) for procurement and training" ], "must_hold": [ "Anomaly reports are followed by manual or mechanical clearance that confirms the detections. The release documents no such confirmation.", "Terrain and vegetation resemble the Kharkiv and Mykolaiv pilot areas" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0061", "title": "DeepSeek-R1 dialogue leads a 34-year-old man to a genetically confirmed familial Mediterranean fever diagnosis after roughly three decades of symptoms", "summary": "Patient's DeepSeek-R1 dialogue proposed FMF; MEFV genetic testing confirmed it and colchicine stopped attacks after ~30 years of symptoms.", "date_observed": "2025-06-28", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 34-year-old man of Egyptian origin began a dialogue with the DeepSeek-R1-0528 model on 28 June 2025. He had recurrent fever, migratory abdominal pain, arthralgia, myalgia and erythematous skin lesions since early childhood. The model refined its differential toward familial Mediterranean fever (FMF). It recommended specialist evaluation, inflammatory markers, genetic testing and colchicine under supervision. He arranged genetic testing, which found two pathogenic MEFV variants (p.Met694Val and p.Val726Ala). He obtained colchicine 0.5 mg twice daily from an Egyptian pharmacy. His attacks ceased, but alanine aminotransferase rose to 160 U/L. Colchicine was temporarily discontinued. His liver enzymes were monitored by his primary care physician. After they improved it was resumed at 0.5 mg daily under close supervision. He presented to the Department of Medicine III, University Medical Center Hamburg-Eppendorf, Germany, in February 2026, already taking 0.5 mg daily. The clinic confirmed FMF and he has remained attack-free.", "category": "benefit created", "unexpected": false, "purpose": "DeepSeek-R1 is a general-purpose reasoning chatbot. Answering a user's medical questions with a differential diagnosis falls within its general question-answering function. It is not a validated medical device.", "system": "DeepSeek-R1", "model_version": "DeepSeek-R1-0528", "developer": "DeepSeek", "deployer": null, "location": "Hamburg, Germany", "domain": "Healthcare - rheumatology / autoinflammatory disease", "segment": "Patient-initiated use of a consumer LLM", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Inflammatory attacks that had recurred since early childhood ceased on colchicine after a genetically confirmed diagnosis. The benefit is life-changing, tempered by a documented transaminase rise from self-dosing before medical supervision." } ], "ai_role": { "status": "assessed", "statement": "The large language model (LLM) generated the FMF hypothesis and the suggested work-up over a multi-turn dialogue. Confirmation came from MEFV genotyping and clinical response to colchicine. The authors stress that the model repeatedly advised specialist supervision. The self-directed genetic testing and self-medication were the patient's own actions." }, "evidence": [ { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report. EULAR Rheumatology Open 2(4):100244.", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The patient nevertheless translated the generated diagnostic hypothesis into autonomous genetic testing and self-medication." }, { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244 (second quotation).", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The model did not simply produce a correct diagnosis from a static symptom list but continuously refined its differential diagnosis" } ], "replication": { "produced_by": [ "A patient with a long-standing, characteristic but undiagnosed phenotype describing it in detail to a reasoning LLM over multiple turns", "Access to genetic testing for the suspected condition" ], "must_hold": [ "Genetic or clinical confirmation by a specialist before the diagnosis is accepted", "Treatment initiated under medical supervision (the case documents hepatotoxicity from self-dosing)" ], "echoes": [] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1609", "title": "ChatGPT-4o Allegedly Discouraged Florida Pastor From Seeking Care Before Pulmonary Embolism", "url": "https://incidentdatabase.ai/cite/1609", "severity": null, "group": "personal", "basis": "Same task, a consumer chatbot assessing a patient's own symptoms in dialogue: ChatGPT-4o attributed Scott Winters's dizziness and pain to benign causes and discouraged hospital care before a massive pulmonary embolism, the inverse of DeepSeek-R1's correct rare diagnosis." }, "headline": "DeepSeek-R1 proposes FMF; MEFV testing confirms the diagnosis", "metric": "colchicine stopped attacks after ~30 years of symptoms", "comparator": { "against": "almost three decades of conventional investigations", "before": "Despite almost 3 decades of symptoms, extensive investigations, including contrast-enhanced abdominal CT and MRI, gastroscopy, colonoscopy, and urological assessment, failed to establish a diagnosis.", "after": "the diagnosis of FMF was confirmed", "basis": "measured", "quote": "Despite almost 3 decades of symptoms, extensive investigations, including contrast-enhanced abdominal CT and MRI, gastroscopy, colonoscopy, and urological assessment, failed to establish a diagnosis.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/" }, "later": { "status": "persisted", "date": "2026-09-29", "note": "After a colchicine pause for raised liver enzymes and resumption at a lower dose, the patient remained attack-free under clinic follow-up as of publication.", "quote": "The patient has remained free of attacks with regular clinical and laboratory follow-up.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/" }, "value": null, "developer_country": "China", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1609 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1609", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account corrected so that the colchicine pause after the ALT rise to 160 U/L and the resumption at 0.5 mg daily are placed before the February 2026 Hamburg presentation, monitored by the primary care physician, as the source states, and the stray “(day not given; first day used)” note was removed because the date observed is the exactly stated dialogue start date of 28 June 2025.", "source": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244, https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/DeepSeek", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0061", "catalog_version": "1.0.0", "source_fingerprint": "f7dee2b7bd11fcc94de8c213c28d421373f6f5d0a588ac396fac359dcb478eed", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0061-source-0001", "AIBD-0061-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepSeek" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The large language model (LLM) generated the FMF hypothesis and the suggested work-up over a multi-turn dialogue. Confirmation came from MEFV genotyping and clinical response to colchicine. The authors stress that the model repeatedly advised specialist supervision. The self-directed genetic testing and self-medication were the patient's own actions." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The large language model (LLM) generated the FMF hypothesis and the suggested work-up over a multi-turn dialogue. Confirmation came from MEFV genotyping and clinical response to colchicine. The authors stress that the model repeatedly advised specialist supervision. The self-directed genetic testing and self-medication were the patient's own actions." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Inflammatory attacks that had recurred since early childhood ceased on colchicine after a genetically confirmed diagnosis. The benefit is life-changing, tempered by a documented transaminase rise from self-dosing before medical supervision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Inflammatory attacks that had recurred since early childhood ceased on colchicine after a genetically confirmed diagnosis. 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"evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "colchicine stopped attacks after ~30 years of symptoms", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "1609", "title": "ChatGPT-4o Allegedly Discouraged Florida Pastor From Seeking Care Before Pulmonary Embolism", "url": "https://incidentdatabase.ai/cite/1609", "group": "personal", "basis": "Same task, a consumer chatbot assessing a patient's own symptoms in dialogue: ChatGPT-4o attributed Scott Winters's dizziness and pain to benign causes and discouraged hospital care before a massive pulmonary embolism, the inverse of DeepSeek-R1's correct rare diagnosis." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-09-29", "note": "After a colchicine pause for raised liver enzymes and resumption at a lower dose, the patient remained attack-free under clinic follow-up as of publication.", "quote": "The patient has remained free of attacks with regular clinical and laboratory follow-up.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0061" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 34-year-old man of Egyptian origin began a dialogue with the DeepSeek-R1-0528 model on 28 June 2025. He had recurrent fever, migratory abdominal pain, arthralgia, myalgia and erythematous skin lesions since early childhood. The model refined its differential toward familial Mediterranean fever (FMF). It recommended specialist evaluation, inflammatory markers, genetic testing and colchicine under supervision. He arranged genetic testing, which found two pathogenic MEFV variants (p.Met694Val and p.Val726Ala). He obtained colchicine 0.5 mg twice daily from an Egyptian pharmacy. His attacks ceased, but alanine aminotransferase rose to 160 U/L. Colchicine was temporarily discontinued. His liver enzymes were monitored by his primary care physician. After they improved it was resumed at 0.5 mg daily under close supervision. He presented to the Department of Medicine III, University Medical Center Hamburg-Eppendorf, Germany, in February 2026, already taking 0.5 mg daily. The clinic confirmed FMF and he has remained attack-free.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Inflammatory attacks that had recurred since early childhood ceased on colchicine after a genetically confirmed diagnosis. The benefit is life-changing, tempered by a documented transaminase rise from self-dosing before medical supervision." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "DeepSeek-R1 is a general-purpose reasoning chatbot. Answering a user's medical questions with a differential diagnosis falls within its general question-answering function. It is not a validated medical device." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Hamburg, Germany", "developer_country": "China" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "DeepSeek-R1 is a general-purpose reasoning chatbot. Answering a user's medical questions with a differential diagnosis falls within its general question-answering function. It is not a validated medical device." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-28", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1609 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1609", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account corrected so that the colchicine pause after the ALT rise to 160 U/L and the resumption at 0.5 mg daily are placed before the February 2026 Hamburg presentation, monitored by the primary care physician, as the source states, and the stray “(day not given; first day used)” note was removed because the date observed is the exactly stated dialogue start date of 28 June 2025.", "source": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244, https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/DeepSeek", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A patient with a long-standing, characteristic but undiagnosed phenotype describing it in detail to a reasoning LLM over multiple turns", "Access to genetic testing for the suspected condition" ], "must_hold": [ "Genetic or clinical confirmation by a specialist before the diagnosis is accepted", "Treatment initiated under medical supervision (the case documents hepatotoxicity from self-dosing)" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1609 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1609", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Account corrected so that the colchicine pause after the ALT rise to 160 U/L and the resumption at 0.5 mg daily are placed before the February 2026 Hamburg presentation, monitored by the primary care physician, as the source states, and the stray “(day not given; first day used)” note was removed because the date observed is the exactly stated dialogue start date of 28 June 2025.", "source": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244, https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/DeepSeek", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - rheumatology / autoinflammatory disease", "segment": "Patient-initiated use of a consumer LLM" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report. EULAR Rheumatology Open 2(4):100244.", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The patient nevertheless translated the generated diagnostic hypothesis into autonomous genetic testing and self-medication." }, { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244 (second quotation).", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The model did not simply produce a correct diagnosis from a static symptom list but continuously refined its differential diagnosis" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0061-source-0001", "AIBD-0061-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report. EULAR Rheumatology Open 2(4):100244.", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The patient nevertheless translated the generated diagnostic hypothesis into autonomous genetic testing and self-medication." }, { "kind": "case report", "citation": "Pauz J, Kremer P, Xiong T, Krusche M (2026). EULAR Rheumatology Open 2(4):100244 (second quotation).", "title": "LLM-supported self-diagnosis and self-treatment of familial Mediterranean fever: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13651492/", "date": "2026-09-29", "written_by": "independent", "quote": "The model did not simply produce a correct diagnosis from a static symptom list but continuously refined its differential diagnosis" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Patient's DeepSeek-R1 dialogue proposed FMF; MEFV genetic testing confirmed it and colchicine stopped attacks after ~30 years of symptoms.", "account": "A 34-year-old man of Egyptian origin began a dialogue with the DeepSeek-R1-0528 model on 28 June 2025. He had recurrent fever, migratory abdominal pain, arthralgia, myalgia and erythematous skin lesions since early childhood. The model refined its differential toward familial Mediterranean fever (FMF). It recommended specialist evaluation, inflammatory markers, genetic testing and colchicine under supervision. He arranged genetic testing, which found two pathogenic MEFV variants (p.Met694Val and p.Val726Ala). He obtained colchicine 0.5 mg twice daily from an Egyptian pharmacy. His attacks ceased, but alanine aminotransferase rose to 160 U/L. Colchicine was temporarily discontinued. His liver enzymes were monitored by his primary care physician. After they improved it was resumed at 0.5 mg daily under close supervision. He presented to the Department of Medicine III, University Medical Center Hamburg-Eppendorf, Germany, in February 2026, already taking 0.5 mg daily. The clinic confirmed FMF and he has remained attack-free." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model suggested a possible diagnosis and further investigations during a conversation." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "DeepSeek-R1-0528." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "DeepSeek-R1-0528" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "DeepSeek-R1-0528.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DeepSeek-R1" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepSeek" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "DeepSeek-R1 dialogue leads a 34-year-old man to a genetically confirmed familial Mediterranean fever diagnosis after roughly three decades of symptoms", "headline": "DeepSeek-R1 proposes FMF; MEFV testing confirms the diagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f7dee2b7bd11fcc94de8c213c28d421373f6f5d0a588ac396fac359dcb478eed" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A 34-year-old man of Egyptian origin began a dialogue with the DeepSeek-R1-0528 model on 28 June 2025. He had recurrent fever, migratory abdominal pain, arthralgia, myalgia and erythematous skin lesions since early childhood. The model refined its differential toward familial Mediterranean fever (FMF). It recommended specialist evaluation, inflammatory markers, genetic testing and colchicine under supervision. He arranged genetic testing, which found two pathogenic MEFV variants (p.Met694Val and p.Val726Ala). He obtained colchicine 0.5 mg twice daily from an Egyptian pharmacy. His attacks ceased, but alanine aminotransferase rose to 160 U/L. Colchicine was temporarily discontinued. His liver enzymes were monitored by his primary care physician. After they improved it was resumed at 0.5 mg daily under close supervision. He presented to the Department of Medicine III, University Medical Center Hamburg-Eppendorf, Germany, in February 2026, already taking 0.5 mg daily. The clinic confirmed FMF and he has remained attack-free.", "replication": { "produced_by": [ "A patient with a long-standing, characteristic but undiagnosed phenotype describing it in detail to a reasoning LLM over multiple turns", "Access to genetic testing for the suspected condition" ], "must_hold": [ "Genetic or clinical confirmation by a specialist before the diagnosis is accepted", "Treatment initiated under medical supervision (the case documents hepatotoxicity from self-dosing)" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0187", "title": "Medicare withholds $4.41 billion in suspected fraudulent payments", "summary": "Federal analysts flagged unusual billing, and HHS-OIG and CMS held $4.41 billion in escrow during Operation Gold Rush.", "date_observed": "2025-06-30", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "DOJ reported that analysts detected unusual billing in Operation Gold Rush. HHS-OIG and CMS held $4.41 billion in escrow from about $4.45 billion scheduled for payment. Medicare paid about $41 million, and supplemental insurers paid about $900 million. DOJ stated that HHS and CMS intended to seek the return of the escrow to the Medicare trust fund. The announcement also proposed an AI-enabled Data Fusion Center. It does not establish that AI was used in the Gold Rush detection.", "category": "harm prevented", "unexpected": false, "purpose": "Detect, investigate and prosecute complex health care fraud schemes.", "system": "DOJ Health Care Fraud Unit proactive billing analytics", "model_version": null, "developer": "U.S. Department of Justice, Criminal Division Fraud Section, Health Care Fraud Unit Data Analytics Team", "deployer": "U.S. Department of Justice with HHS-OIG and CMS", "location": null, "domain": "Health care fraud and public insurance", "segment": "Medicare durable medical equipment claims", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 4, "reason": "The release states that $4.41 billion scheduled to be paid by Medicare was held in escrow for return to the Medicare trust fund. Supplemental insurers still paid about $900 million." }, { "group": "organizational", "depth": 3, "reason": "CMS and HHS-OIG stopped payment of all but about $41 million of $4.45 billion in claims from the organization, per the release." }, { "group": "personal", "depth": null, "reason": "The release describes over one million stolen identities but documents no outcome for the individual beneficiaries." } ], "ai_role": { "status": "unassessed", "statement": "DOJ attributes detection to proactive data analytics. The reviewed sources do not establish that AI was used. The AI-enabled Data Fusion Center was announced separately as future work." }, "evidence": [ { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, “National Health Care Fraud Takedown Results in 324 Defendants Charged in Connection with Over $14.6 Billion in Alleged Fraud,” June 30, 2025, § “Transnational Criminal Organizations.”", "title": "National Health Care Fraud Takedown Results in 324 Defendants Charged in Connection with Over $14.6 Billion in Alleged Fraud", "url": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "date": "2025-06-30", "written_by": "deployer", "quote": "The Health Care Fraud Unit's Data Analytics Team and its partners detected the anomalous billing through proactive data analytics" }, { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, press release, 3 February 2026. Brooklyn Banker Pleads Guilty to Laundering Proceeds of Medicare Fraud for Transnational Criminal Organization.", "title": "Brooklyn Banker Pleads Guilty to Laundering Proceeds of Medicare Fraud for Transnational Criminal Organization", "url": "https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal", "date": "2026-02-03", "written_by": "deployer", "quote": null }, { "kind": "court document", "citation": "United States v. Nakhmatullaev et al., No. 25-cr-203, indictment, June 18, 2025, 1–10, ¶¶ 1–20, 32–34 (E.D.N.Y.).", "title": "United States v. Nakhmatullaev et al., indictment", "url": "https://www.justice.gov/criminal/media/1405326/dl?inline=", "date": "2025-06-18", "written_by": "deployer", "quote": null }, { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, “Ohio Man Pleads Guilty to Laundering Health Care Fraud Proceeds for Transnational Criminal Organization,” August 14, 2026, ¶¶ 1–9.", "title": "Ohio Man Pleads Guilty to Laundering Health Care Fraud Proceeds for Transnational Criminal Organization", "url": "https://www.justice.gov/opa/pr/ohio-man-pleads-guilty-laundering-health-care-fraud-proceeds-transnational-criminal", "date": "2026-08-14", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Analysts detected anomalous Medicare billing.", "HHS-OIG and CMS suspended scheduled payments." ], "must_hold": [ "Access to billing data before payment.", "Legal authority and operational capacity to suspend payments." ], "echoes": [] }, "paired_incident": null, "headline": "Medicare withholds $4.41 billion in suspected fraudulent payments", "metric": "HHS-OIG and CMS prevented all but $41 million of $4.45 billion", "comparator": { "against": "the amount Medicare was scheduled to pay on the fraudulent claims had the billing gone undetected", "before": "the approximately $4.45 billion that was scheduled to be paid by Medicare", "after": "all but approximately $41 million", "basis": "measured", "quote": "The Health Care Fraud Unit's Data Analytics Team and its partners detected the anomalous billing through proactive data analytics, and HHS-OIG and CMS successfully prevented the organization from receiving all but approximately $41 million of the approximately $4.45 billion that was scheduled to be paid by Medicare.", "url": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146" }, "later": { "status": "litigated", "date": "2026-08-13", "note": "DOJ reported 35 people charged and 16 convicted by August 14, 2026, following a money-laundering guilty plea the previous day. These developments do not establish an AI contribution or the final disposition of the $4.41 billion in escrow.", "quote": null, "url": "https://www.justice.gov/opa/pr/ohio-man-pleads-guilty-laundering-health-care-fraud-proceeds-transnational-criminal" }, "value": { "amount": "$4.41 billion", "what": "fraudulent Medicare payments held in escrow rather than paid out, to be returned to the Medicare trust fund", "who": "Medicare trust fund (HHS and CMS)", "estimate": false, "quote": "HHS and CMS intend to seek to return the $4.41 billion in escrow to the Medicare trust fund for needed medical care.", "url": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146; https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal; https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.justice.gov/contact-us; https://www.justice.gov/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Read the original DOJ announcements and linked indictment; separated billing analytics from the proposed AI-enabled Fusion Center, clarified escrow and losses, and added the August 2026 prosecution update.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's court document and three press releases from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0187", "catalog_version": "1.0.0", "source_fingerprint": "97b6aaeb2665f23ec816fe89bd7d400e53a9861274835d537c0b95d803e7f548", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "DIV-0026" ], "role": "monetary observations" }, "provenance": { "kind": "source_review", "basis": "DOJ reports a gross payment hold, without an established AI contribution.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "record_ids": [ "DIV-0026" ] }, "institutional decisions": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "25-cr-203" ], "role": "institutional decisions" }, "provenance": { "kind": "source_review", "basis": "DOJ announcement and the linked indictment.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "record_ids": [ "25-cr-203" ] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "text", "text": "DOJ’s Health Care Fraud Unit and partners analyzed billing. 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Returning the escrow to the Medicare trust fund was still intended." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The payment hold is reported as completed. Returning the escrow to the Medicare trust fund was still intended." } }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "The release states that $4.41 billion scheduled to be paid by Medicare was held in escrow for return to the Medicare trust fund. 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They do not establish that AI produced the benefit." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Official accounts support the withheld-payment figure and prosecution updates. They do not establish that AI produced the benefit." } }, "claims[].missingness": { "state": "value_present", "value": { "kind": "text", "text": "The algorithm, AI contribution, operating costs, false-positive rate, and final escrow disposition remain unestablished." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The algorithm, AI contribution, operating costs, false-positive rate, and final escrow disposition remain unestablished." } }, "claims[].proposition": { "state": "value_present", "value": { "kind": "text", "text": "Billing analysis contributed to the detection of a scheme whose scheduled payments were largely suspended." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Billing analysis contributed to the detection of a scheme whose scheduled payments were largely suspended." } }, "cross_border_flows[]": { "state": "value_present", "value": { "kind": "text", "text": "DOJ describes criminal transfers to overseas companies and accounts. It does not document cross-border movement of the analytic system, its training data, or its computing resources." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ describes criminal transfers to overseas companies and accounts. It does not document cross-border movement of the analytic system, its training data, or its computing resources." } }, "decisions[].action_outcome": { "state": "value_present", "value": { "kind": "text", "text": "Payments were suspended. The June 2025 indictment and later guilty pleas concern the alleged criminal scheme." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Payments were suspended. The June 2025 indictment and later guilty pleas concern the alleged criminal scheme." } }, "decisions[].grounds": { "state": "value_present", "value": { "kind": "text", "text": "Anomalous billing and evidence of fraudulent claims were the stated grounds. The sources do not give a separate test of AI’s contribution." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Anomalous billing and evidence of fraudulent claims were the stated grounds. The sources do not give a separate test of AI’s contribution." } }, "decisions[].institution_task": { "state": "value_present", "value": { "kind": "text", "text": "HHS-OIG and CMS suspended payments while DOJ and its partners investigated the alleged fraud." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "HHS-OIG and CMS suspended payments while DOJ and its partners investigated the alleged fraud." } }, "decisions[].success_criterion": { "state": "value_present", "value": { "kind": "text", "text": "The announcements describe preventing improper payments and prosecuting fraud. They do not specify a prospective numerical threshold for success." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The announcements describe preventing improper payments and prosecuting fraud. They do not specify a prospective numerical threshold for success." } }, "deployment_stage": { "state": "value_present", "value": { "kind": "text", "text": "Operational billing analysis supported an active investigation." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Operational billing analysis supported an active investigation." } }, "economics[].amount": { "state": "value_present", "value": { "kind": "text", "text": "US$4.41 billion held in escrow." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "US$4.41 billion held in escrow." } }, "economics[].costs[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not quantify operating or enforcement costs.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not quantify operating or enforcement costs." } }, "economics[].counterfactual": { "state": "value_present", "value": { "kind": "text", "text": "About $4.45 billion was scheduled for payment; about $41 million was paid. This accounting comparison does not isolate AI’s effect." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "About $4.45 billion was scheduled for payment; about $41 million was paid. This accounting comparison does not isolate AI’s effect." } }, "economics[].currency_price_basis": { "state": "value_present", "value": { "kind": "text", "text": "U.S. dollars. The figures are nominal; no inflation adjustment is stated." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "U.S. dollars. The figures are nominal; no inflation adjustment is stated." } }, "economics[].gross_net": { "state": "value_present", "value": { "kind": "text", "text": "The figure is gross money withheld. It does not deduct investigation, prosecution, or administrative costs." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The figure is gross money withheld. It does not deduct investigation, prosecution, or administrative costs." } }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "text", "text": "Scheduled payments withheld in escrow, rather than a realized net saving." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Scheduled payments withheld in escrow, rather than a realized net saving." } }, "economics[].period_unit": { "state": "value_present", "value": { "kind": "text", "text": "The Operation Gold Rush payment hold reported on June 30, 2025. The exact interval covered by the total is not specified." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Operation Gold Rush payment hold reported on June 30, 2025. The exact interval covered by the total is not specified." } }, "economics[].realization": { "state": "value_present", "value": { "kind": "text", "text": "$4.41 billion was held in escrow. Returning it to the trust fund remained an intention in the announcement." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "$4.41 billion was held in escrow. Returning it to the trust fund remained an intention in the announcement." } }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "text", "text": "Medicare was the scheduled payer; the Medicare trust fund was the intended recipient of returned escrow." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Medicare was the scheduled payer; the Medicare trust fund was the intended recipient of returned escrow." } }, "economics[].return_payback": { "state": "unresolved", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "A return or payback period cannot be calculated from the reviewed figures because costs and an AI contribution are unestablished.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "A return or payback period cannot be calculated from the reviewed figures because costs and an AI contribution are unestablished." } }, "economics[].valuation_method": { "state": "value_present", "value": { "kind": "text", "text": "DOJ reports the scheduled, paid, and escrowed amounts. No monetary valuation model is described." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ reports the scheduled, paid, and escrowed amounts. No monetary valuation model is described." } }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "HHS-OIG and CMS prevented all but $41 million of $4.45 billion", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "text", "text": "United States v. Nakhmatullaev et al., No. 25-cr-203." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "United States v. Nakhmatullaev et al., No. 25-cr-203." } }, "follow_up[]": { "state": "value_present", "value": { "kind": "text", "text": "DOJ reported 35 people charged and 16 convicted by August 14, 2026, following a money-laundering guilty plea the previous day. These developments do not establish an AI contribution or the final disposition of the $4.41 billion in escrow." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0002", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ reported 35 people charged and 16 convicted by August 14, 2026, following a money-laundering guilty plea the previous day. These developments do not establish an AI contribution or the final disposition of the $4.41 billion in escrow." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Federal analysts, investigators, prosecutors, and payment administrators performed distinct roles. The sources do not describe a specific review protocol for software alerts." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Federal analysts, investigators, prosecutors, and payment administrators performed distinct roles. The sources do not describe a specific review protocol for software alerts." } }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0187" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "The investigation required Medicare billing records, access to payment administration, and cooperation among federal agencies." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The investigation required Medicare billing records, access to payment administration, and cooperation among federal agencies." } }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Medicare and the public funds that support it." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Medicare and the public funds that support it." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "More than one million people had identities stolen. That is a count of people affected by the alleged fraud, not a measured count of people helped by AI." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0003" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "More than one million people had identities stolen. That is a count of people affected by the alleged fraud, not a measured count of people helped by AI." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Avoided payment of suspected fraudulent claims." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Avoided payment of suspected fraudulent claims." } }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "$4.41 billion in scheduled Medicare payments was held in escrow." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "$4.41 billion in scheduled Medicare payments was held in escrow." } }, "outcomes[].distribution": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The announcement does not measure how the payment hold benefited particular beneficiaries or communities.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The announcement does not measure how the payment hold benefited particular beneficiaries or communities." } }, "outcomes[].duration": { "state": "value_present", "value": { "kind": "text", "text": "The money was held by June 30, 2025. The reviewed sources do not establish the final disposition of the escrow." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The money was held by June 30, 2025. The reviewed sources do not establish the final disposition of the escrow." } }, "outcomes[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0187-outcome-01" }, "provenance": { "kind": "curatorial", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "AIBD-0187-outcome-01" } }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 4, "reason": "The release states that $4.41 billion scheduled to be paid by Medicare was held in escrow for return to the Medicare trust fund. Supplemental insurers still paid about $900 million." }, { "group": "organizational", "depth": 3, "reason": "CMS and HHS-OIG stopped payment of all but about $41 million of $4.45 billion in claims from the organization, per the release." }, { "group": "personal", "reason": "The release describes over one million stolen identities but documents no outcome for the individual beneficiaries." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "The payment suspension occurred. Return of the escrow to the Medicare trust fund remained intended." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The payment suspension occurred. Return of the escrow to the Medicare trust fund remained intended." } }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "About $41 million reached the organization through Medicare, and supplemental insurers paid about $900 million. Enforcement costs and effects on legitimate payments are not quantified." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "About $41 million reached the organization through Medicare, and supplemental insurers paid about $900 million. Enforcement costs and effects on legitimate payments are not quantified." } }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "Preventing fraudulent payments was an intended purpose of the analysis." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Preventing fraudulent payments was an intended purpose of the analysis." } }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "developer_country": "United States", "deployer_country": "United States", "location": "United States", "answer": "The analysis and payment administration occurred in the United States. The investigation involved overseas arrests and transfers." } }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The analysis and payment administration occurred in the United States. The investigation involved overseas arrests and transfers." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "Detect health care fraud before scheduled payments leave Medicare." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Detect health care fraud before scheduled payments leave Medicare." } }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-06-30", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146; https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal; https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.justice.gov/contact-us; https://www.justice.gov/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Read the original DOJ announcements and linked indictment; separated billing analytics from the proposed AI-enabled Fusion Center, clarified escrow and losses, and added the August 2026 prosecution update.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not describe an independent replication of the billing analysis.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not describe an independent replication of the billing analysis." } }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "The agencies needed billing data and the authority to stop payments before the money was transferred." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The agencies needed billing data and the authority to stop payments before the money was transferred." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146; https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal; https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.justice.gov/contact-us; https://www.justice.gov/contact-us", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Read the original DOJ announcements and linked indictment; separated billing analytics from the proposed AI-enabled Fusion Center, clarified escrow and losses, and added the August 2026 prosecution update.", "source": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Public health insurance and fraud enforcement." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Public health insurance and fraud enforcement." } }, "sources[].access_version": { "state": "value_present", "value": { "kind": "text", "text": "DOJ’s original online releases and the June 18, 2025 indictment were inspected on October 25, 2026." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ’s original online releases and the June 18, 2025 indictment were inspected on October 25, 2026." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, “National Health Care Fraud Takedown Results in 324 Defendants Charged in Connection with Over $14.6 Billion in Alleged Fraud,” June 30, 2025, § “Transnational Criminal Organizations.”", "title": "National Health Care Fraud Takedown Results in 324 Defendants Charged in Connection with Over $14.6 Billion in Alleged Fraud", "url": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "date": "2025-06-30", "written_by": "deployer", "quote": "The Health Care Fraud Unit's Data Analytics Team and its partners detected the anomalous billing through proactive data analytics" }, { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, press release, 3 February 2026. Brooklyn Banker Pleads Guilty to Laundering Proceeds of Medicare Fraud for Transnational Criminal Organization.", "title": "Brooklyn Banker Pleads Guilty to Laundering Proceeds of Medicare Fraud for Transnational Criminal Organization", "url": "https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal", "date": "2026-02-03", "written_by": "deployer" }, { "kind": "court document", "citation": "United States v. Nakhmatullaev et al., No. 25-cr-203, indictment, June 18, 2025, 1–10, ¶¶ 1–20, 32–34 (E.D.N.Y.).", "title": "United States v. Nakhmatullaev et al., indictment", "url": "https://www.justice.gov/criminal/media/1405326/dl?inline=", "date": "2025-06-18", "written_by": "deployer" }, { "kind": "press release", "citation": "U.S. Department of Justice, Office of Public Affairs, “Ohio Man Pleads Guilty to Laundering Health Care Fraud Proceeds for Transnational Criminal Organization,” August 14, 2026, ¶¶ 1–9.", "title": "Ohio Man Pleads Guilty to Laundering Health Care Fraud Proceeds for Transnational Criminal Organization", "url": "https://www.justice.gov/opa/pr/ohio-man-pleads-guilty-laundering-health-care-fraud-proceeds-transnational-criminal", "date": "2026-08-14", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "role": "Retained sources" }, "provenance": { "kind": "curatorial", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "4 retained sources." } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "English." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "English." } }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "DOJ reports its own investigation and prosecutions. The indictment records prosecutors’ allegations, not a judicial finding about an AI benefit." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ reports its own investigation and prosecutions. The indictment records prosecutors’ allegations, not a judicial finding about an AI benefit." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "lead_source_ref": "AIBD-0187-source-0001", "retained_source_order": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "origins": [ { "source_refs": [ "AIBD-0187-source-0001" ], "display_name": "U.S. Department of Justice", "url": "https://www.justice.gov/opa/pr/national-health-care-fraud-takedown-results-324-defendants-charged-connection-over-146", "contribution": "Reports the billing detection, scheduled payments, escrow, and losses. Announces the future AI-enabled center separately.", "locator": "§§ “Transnational Criminal Organizations” and “Breaking Down Silos in the Fight Against Health Care Fraud.”" }, { "source_refs": [ "AIBD-0187-source-0002" ], "display_name": "U.S. Department of Justice", "url": "https://www.justice.gov/opa/pr/brooklyn-banker-pleads-guilty-laundering-proceeds-medicare-fraud-transnational-criminal", "contribution": "Documents the banker’s guilty plea on February 3, 2026.", "locator": "¶¶ 1–5." }, { "source_refs": [ "AIBD-0187-source-0003" ], "display_name": "U.S. Department of Justice", "url": "https://www.justice.gov/criminal/media/1405326/dl?inline=", "contribution": "Original indictment underlying the announcement. Describes alleged ownership, billing, and money laundering; it does not establish an AI method.", "locator": "1–10, ¶¶ 1–20, 32–34." }, { "source_refs": [ "AIBD-0187-source-0004" ], "display_name": "U.S. Department of Justice", "url": "https://www.justice.gov/opa/pr/ohio-man-pleads-guilty-laundering-health-care-fraud-proceeds-transnational-criminal", "contribution": "Reports 35 people charged and 16 convicted by August 14, 2026.", "locator": "¶¶ 1–9." } ], "limitations": [ "No reviewed source identifies an AI component in the billing detection.", "The announcements do not document a final return of the escrowed money to the trust fund." ] } }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001", "AIBD-0187-source-0002", "AIBD-0187-source-0003", "AIBD-0187-source-0004" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ is the original source for the payment figures. Its linked indictment describes the alleged scheme; later announcements document guilty pleas." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "Federal analysts flagged unusual billing, and HHS-OIG and CMS held $4.41 billion in escrow during Operation Gold Rush." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Federal analysts flagged unusual billing, and HHS-OIG and CMS held $4.41 billion in escrow during Operation Gold Rush." } }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "HHS-OIG and CMS controlled payment suspensions. The sources do not describe an autonomous system that could withhold funds." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "HHS-OIG and CMS controlled payment suspensions. The sources do not describe an autonomous system that could withhold funds." } }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The analysts detected unusual billing. HHS-OIG and CMS then stopped most scheduled payments." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The analysts detected unusual billing. HHS-OIG and CMS then stopped most scheduled payments." } }, "systems[].deployment_configuration": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not specify the software, hosting, or runtime settings.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not specify the software, hosting, or runtime settings." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Analysts examined health care billing and identified anomalous patterns. The model inputs and alert format are not specified." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Analysts examined health care billing and identified anomalous patterns. The model inputs and alert format are not specified." } }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not identify a model.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not identify a model." } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The reviewed sources do not identify a model release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The reviewed sources do not identify a model release." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "DOJ Health Care Fraud Unit proactive billing analytics" }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "DOJ Health Care Fraud Unit proactive billing analytics" } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "The Department of Justice identifies its Health Care Fraud Unit Data Analytics Team and partners; it names no software supplier." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The Department of Justice identifies its Health Care Fraud Unit Data Analytics Team and partners; it names no software supplier." } }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "Medicare withholds $4.41 billion in suspected fraudulent payments" }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Medicare withholds $4.41 billion in suspected fraudulent payments" } }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "97b6aaeb2665f23ec816fe89bd7d400e53a9861274835d537c0b95d803e7f548" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Content fingerprint refreshed after the October 25, 2026 source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Analysts detected anomalous billing; investigators examined the scheme, and HHS-OIG and CMS withheld scheduled payments." }, "provenance": { "kind": "source_review", "basis": "Original DOJ announcements and the linked indictment, reviewed October 25, 2026.", "record_fields": [], "source_refs": [ "AIBD-0187-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Analysts detected anomalous billing; investigators examined the scheme, and HHS-OIG and CMS withheld scheduled payments." } } }, "summary": { "total": 91, "addressed": 91, "known": 64, "reviewed": 64, "record_mapped": 9, "not_assessed": 18, "complete": false, "by_state": { "value_present": 64, "not_reported": 7, "unresolved": 2, "not_assessed": 18, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0141", "title": "ChatGPT ties a Reddit user's ten-plus years of unexplained symptoms to a homozygous A1298C MTHFR test result and proposes B12 supplementation; the symptoms may have largely resolved", "summary": "A Reddit user says ChatGPT tied 10+ years of symptoms to an MTHFR A1298C result and B12 use; doctor agreed; symptoms largely resolved.", "date_observed": "2025-07-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 4 July 2025 Reddit user u/Adventurous-Gold6935 wrote in r/ChatGPT from the United States. They reported over ten years of unexplained symptoms. Tests included spinal magnetic resonance imaging (MRI), a computed tomography (CT) scan, in-depth blood work, a Lyme test and a neurologist's check for MS. Then a Function Health panel showed a homozygous A1298C MTHFR mutation. They uploaded five PDFs of those results and a symptom history to ChatGPT (o3, they said). It concluded the symptoms were “on par with the mutation”. It concluded that normal-looking B12 might not be utilized, so supplementation was needed. Their doctor, “super shocked”, agreed. On a methyl B complex, their symptoms were “largely resolved” a few months later. OpenAI's president reposted the thread on 6 July.", "category": "benefit created", "unexpected": false, "purpose": "ChatGPT is OpenAI's general-purpose assistant, built to answer questions over typed text and uploaded documents. Reading lab PDFs and a symptom history and proposing an explanation is an instance of that general use, not a designed diagnostic function. So the benefit falls within what the system was built to do.", "system": "ChatGPT (OpenAI consumer app), given five uploaded Function Health lab PDFs and a written symptom timeline", "model_version": "o3 (the author's one-word reply when asked whether they used the free or paid version of ChatGPT)", "developer": "OpenAI", "deployer": "OpenAI", "location": null, "domain": "Consumer health (self-directed interpretation of laboratory and genetic results)", "segment": "Consumer", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-07-06-2ff8" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "By the user's own account, ten-plus years of near-constant tingling, tinnitus and chronic fatigue were “largely resolved” within months of a doctor-approved methyl B complex. Corroborated, that would rate one level higher. It is pseudonymous and self-reported. No clinician has spoken publicly. A DXY-sourced ifeng piece reports doctors doubting its authenticity." } ], "ai_role": { "status": "assessed", "statement": "The mutation was not found by ChatGPT. The user wrote that a Function Health panel showed the homozygous A1298C MTHFR variant. The AppSo account says the same (“在功能医学检查中发现”). What ChatGPT (o3, per the user) added was the inference. Given about five paragraphs of history and five PDFs of results, it concluded the symptoms were “on par with the mutation”. It concluded that B12 values that looked normal on paper might not be utilized, so supplementation was warranted. The doctor confirmed the reading and the supplement. The user then improved. The counterfactual is unproven. The same results were available to the doctor. The user had earlier been told the symptoms were anxiety and given an SSRI and Xanax. Whether the improvement came from the supplement, from regression, or from expectation is unknown. Livemint (“The AI flagged a possible genetic mutation”) and the Monitor's summary (“identification of genetic mutations missed by doctors”) overstate the model's role. The ACMG guideline and the ifeng piece also put the MTHFR premise itself in doubt." }, "evidence": [ { "kind": "other", "citation": "u/Adventurous-Gold6935 (2025). ChatGPT solved a 10+ year problem no doctors could figure out. Reddit, r/ChatGPT, 4 July 2025.", "title": "ChatGPT solved a 10+ year problem no doctors could figure out", "url": "https://www.reddit.com/r/ChatGPT/comments/1lrmom4/chatgpt_solved_a_10_year_problem_no_doctors_could/", "date": "2025-07-04", "written_by": "beneficiary", "quote": "ChatGPT took all my lab results and symptom history and concluded this was on par with the mutation." }, { "kind": "news report", "citation": "Chouhan, M. S. / Hindustan Times (2025). ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years. Hindustan Times, Trending, 5 July 2025.", "title": "ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years", "url": "https://www.hindustantimes.com/trending/chatgpt-uncovers-root-cause-of-mysterious-illness-that-baffled-doctors-for-over-10-years-101751704864270.html", "date": "2025-07-05", "written_by": "independent", "quote": "A Reddit post is gaining significant attention after a user claimed that ChatGPT helped uncover the root cause of a decade-long health mystery" }, { "kind": "news report", "citation": "Thakur, A. / Mint (2025). Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade. Livemint, 6 July 2025.", "title": "Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade", "url": "https://www.livemint.com/news/trends/reddit-user-claims-chatgpt-uncovered-medical-condition-doctors-overlooked-for-a-decade-11751788742326.html", "date": "2025-07-06", "written_by": "independent", "quote": "The AI flagged a possible genetic mutation- homozygous A1298C MTHFR, known to affect B12 processing in the body, even when blood levels seem normal." }, { "kind": "news report", "citation": "PYMNTS (2025). ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice. PYMNTS.com, 10 July 2025.", "title": "ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice", "url": "https://www.pymnts.com/news/artificial-intelligence/2025/chatgpt-as-doctor-when-consumers-rely-on-ai-for-medical-advice/", "date": "2025-07-10", "written_by": "independent", "quote": "A physician later confirmed the diagnosis and the B12 supplement treatment later \"largely resolved\" the symptoms." }, { "kind": "news report", "citation": "财联社 / Cailian Press (2025). 十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近. 新浪财经, 6 July 2025.", "title": "十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近", "url": "https://finance.sina.com.cn/jjxw/2025-07-06/doc-infephkm0866335.shtml", "date": "2025-07-06", "written_by": "independent", "quote": "OpenAI总裁兼联合创始人Greg Brockman也在今日转发了这一事件。" }, { "kind": "news report", "citation": "AppSo (2025). 百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因. 网易 (mirror of 36氪), 7 July 2025.", "title": "百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因", "url": "https://m.163.com/dy/article/K3SPL1UB0511CSAO.html", "date": "2025-07-07", "written_by": "independent", "quote": "直到某天，他在功能医学检查中发现了一个异于常人的遗传突变，MTHFR（叶酸代谢基因）A1298C 突变" }, { "kind": "news report", "citation": "新智元 (2025). 10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界. 网易 (mirror of 36氪), 6 July 2025.", "title": "10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界", "url": "https://m.163.com/dy/article/K3PMM22K0511ABV6.html", "date": "2025-07-06", "written_by": "independent", "quote": "ChatGPT发现，虽然血清维生素B12水平正常，但却与持续性的神经痛和慢性疲乏矛盾" }, { "kind": "news report", "citation": "丁香园 / DXY (2025). 10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了. 凤凰网, 8 July 2025.", "title": "10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了", "url": "https://news.ifeng.com/c/8kp8doX5Vd0", "date": "2025-07-08", "written_by": "independent", "quote": "但也有医生怒斥，这个病例真实性存疑，『更可能是功能医学宣传再一次立功』。" }, { "kind": "report", "citation": "Hickey, S. E., Curry, C. J., Toriello, H. V. (2013). ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing. Genetics in Medicine 15(2), 153-156. doi:10.1038/gim.2012.165.", "title": "ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing", "url": "https://europepmc.org/article/MED/23288205", "date": "2013-01-03", "written_by": "independent", "quote": "There is growing evidence that MTHFR polymorphism testing has minimal clinical utility and, therefore should not be ordered as a part of a routine evaluation for thrombophilia." } ], "replication": { "produced_by": [ "The user already held a genetic result (homozygous A1298C MTHFR from a Function Health panel), five PDFs of laboratory results and a written symptom timeline. They gave all of it to the model rather than a description of symptoms alone.", "A paid reasoning model (o3, by the user's account) was asked to reconcile B12 values in the laboratory's normal range with persistent neurological symptoms. It proposed a mechanism and a supplement rather than a bare label.", "A treating doctor willing to review the model's reasoning and the gene report and to approve a methylated B-complex before it was started." ], "must_hold": [ "A clinician reviews the model's inference and approves any supplement or treatment before it is started. Here the doctor did, by the user's account.", "The genetic result comes from an actual test. The model interprets; it does not genotype. The ACMG guideline says MTHFR polymorphism testing has minimal clinical utility, so the premise itself is contested.", "The benefit is self-reported and pseudonymous. Any record of this kind must carry the absence of a clinician statement and the published medical doubt (DXY via ifeng) as a standing caveat." ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT ties ten-plus years of symptoms to an MTHFR mutation", "metric": null, "comparator": null, "later": { "status": "reversed", "date": "2025-07-08", "note": "Four days after the post, DXY reported that a doctor dismissed the case as of doubtful authenticity and probably functional-medicine promotion, cited the ACMG guideline against routine MTHFR testing, and noted that the post now showed as deleted by its author; this is a published dispute and deletion, not a documented reversal of the reported recovery.", "quote": "但也有医生怒斥，这个病例真实性存疑，「更可能是功能医学宣传再一次立功」。", "url": "https://news.ifeng.com/c/8kp8doX5Vd0" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored, as the classifier proposed: a health improvement for one person, not prevention of a specified harm; the Monitor itself labels it an incident on “harm mitigation (improvement in health)”. The Monitor entry bundles several Reddit cases (the 新智元 piece adds crasstyfartman's sister, buyableblah's endometriosis and sometimelater0212's dog) and Microsoft's MAI-DxO benchmark on NEJM cases, which is a study; this record is restricted to the one dated post. The post was read through the PullPush archive API (reddit.com returned 403): author u/Adventurous-Gold6935, 4 July 2025 16:16 UTC, 9,149 points and 1,089 comments at capture; Hindustan Times counted over 6,000 upvotes on 5 July and Livemint more than 9,000 on 6 July. The user's own words make clear that the mutation came from a Function Health panel and that ChatGPT supplied the interpretation; the model name, the five uploaded PDFs, the methyl B complex, the earlier anxiety diagnosis with an SSRI and Xanax, and the symptom list (full-body tingling, tinnitus, chronic fatigue) come from the author's replies in the thread, 4 to 6 July. Greg Brockman's repost on X is reported by Cailian Press (“今日”, 6 July Beijing time) and AppSo (quoting him as saying ChatGPT was used to solve a long-standing medical problem), and PYMNTS links the post (ID 1941567568155902397, whose timestamp resolves to 5 July 2025 18:39 UTC); the post itself could not be read. The repost is vendor amplification of a self-report, not evidence. Dated to the post; the improvement accrued over the preceding months and is undated, and the Monitor's ID date (6 July) is the first Chinese report. The author's gender is not stated. The k.sina.cn article now returns “article no longer exists”; both 36kr pages sat behind a bot check, so their 163.com mirrors were read; Hindustan Times and Livemint were read with curl after WebFetch was refused. The ACMG guideline was read through the Europe PMC API.", "source": "https://oecd.ai/en/incidents/2025-07-06-2ff8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://news.ifeng.com/c/8kp8doX5Vd0", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, seven independent news reports and the beneficiary's other. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0141", "catalog_version": "1.0.0", "source_fingerprint": "93eb1e0326c679485e074fb8a055a496ad8200ac9bf7133980740a921278f8f2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0141-source-0001", "AIBD-0141-source-0002", "AIBD-0141-source-0003", "AIBD-0141-source-0004", "AIBD-0141-source-0005", "AIBD-0141-source-0006", "AIBD-0141-source-0007", "AIBD-0141-source-0008", "AIBD-0141-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The mutation was not found by ChatGPT. The user wrote that a Function Health panel showed the homozygous A1298C MTHFR variant. The AppSo account says the same (“在功能医学检查中发现”). What ChatGPT (o3, per the user) added was the inference. Given about five paragraphs of history and five PDFs of results, it concluded the symptoms were “on par with the mutation”. It concluded that B12 values that looked normal on paper might not be utilized, so supplementation was warranted. The doctor confirmed the reading and the supplement. The user then improved. The counterfactual is unproven. The same results were available to the doctor. The user had earlier been told the symptoms were anxiety and given an SSRI and Xanax. Whether the improvement came from the supplement, from regression, or from expectation is unknown. Livemint (“The AI flagged a possible genetic mutation”) and the Monitor's summary (“identification of genetic mutations missed by doctors”) overstate the model's role. The ACMG guideline and the ifeng piece also put the MTHFR premise itself in doubt." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "ChatGPT interpreted laboratory results that already showed an MTHFR variant and suggested that vitamin B12 supplementation might help. The user reported that a doctor agreed and that symptoms improved afterward.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The mutation was not found by ChatGPT. The user wrote that a Function Health panel showed the homozygous A1298C MTHFR variant. The AppSo account says the same (“在功能医学检查中发现”). What ChatGPT (o3, per the user) added was the inference. Given about five paragraphs of history and five PDFs of results, it concluded the symptoms were “on par with the mutation”. It concluded that B12 values that looked normal on paper might not be utilized, so supplementation was warranted. The doctor confirmed the reading and the supplement. The user then improved. The counterfactual is unproven. The same results were available to the doctor. The user had earlier been told the symptoms were anxiety and given an SSRI and Xanax. Whether the improvement came from the supplement, from regression, or from expectation is unknown. Livemint (“The AI flagged a possible genetic mutation”) and the Monitor's summary (“identification of genetic mutations missed by doctors”) overstate the model's role. The ACMG guideline and the ifeng piece also put the MTHFR premise itself in doubt." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the user's own account, ten-plus years of near-constant tingling, tinnitus and chronic fatigue were “largely resolved” within months of a doctor-approved methyl B complex. Corroborated, that would rate one level higher. It is pseudonymous and self-reported. No clinician has spoken publicly. A DXY-sourced ifeng piece reports doctors doubting its authenticity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent report, seven independent news reports and the beneficiary's other. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the user's own account, ten-plus years of near-constant tingling, tinnitus and chronic fatigue were “largely resolved” within months of a doctor-approved methyl B complex. Corroborated, that would rate one level higher. It is pseudonymous and self-reported. No clinician has spoken publicly. A DXY-sourced ifeng piece reports doctors doubting its authenticity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the user's own account, ten-plus years of near-constant tingling, tinnitus and chronic fatigue were “largely resolved” within months of a doctor-approved methyl B complex. Corroborated, that would rate one level higher. It is pseudonymous and self-reported. No clinician has spoken publicly. A DXY-sourced ifeng piece reports doctors doubting its authenticity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The account does not establish that the supplement caused the improvement or that ChatGPT found a mutation that clinicians had missed. The cited ACMG guidance also questions the clinical significance of the MTHFR premise.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-07-06-2ff8" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "reversed", "date": "2025-07-08", "note": "Four days after the post, DXY reported that a doctor dismissed the case as of doubtful authenticity and probably functional-medicine promotion, cited the ACMG guideline against routine MTHFR testing, and noted that the post now showed as deleted by its author; this is a published dispute and deletion, not a documented reversal of the reported recovery.", "quote": "但也有医生怒斥，这个病例真实性存疑，「更可能是功能医学宣传再一次立功」。", "url": "https://news.ifeng.com/c/8kp8doX5Vd0" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "A doctor reviewed the interpretation and confirmed the supplement." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0141" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 4 July 2025 Reddit user u/Adventurous-Gold6935 wrote in r/ChatGPT from the United States. They reported over ten years of unexplained symptoms. Tests included spinal magnetic resonance imaging (MRI), a computed tomography (CT) scan, in-depth blood work, a Lyme test and a neurologist's check for MS. Then a Function Health panel showed a homozygous A1298C MTHFR mutation. They uploaded five PDFs of those results and a symptom history to ChatGPT (o3, they said). It concluded the symptoms were “on par with the mutation”. It concluded that normal-looking B12 might not be utilized, so supplementation was needed. Their doctor, “super shocked”, agreed. On a methyl B complex, their symptoms were “largely resolved” a few months later. OpenAI's president reposted the thread on 6 July.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "By the user's own account, ten-plus years of near-constant tingling, tinnitus and chronic fatigue were “largely resolved” within months of a doctor-approved methyl B complex. Corroborated, that would rate one level higher. It is pseudonymous and self-reported. No clinician has spoken publicly. A DXY-sourced ifeng piece reports doctors doubting its authenticity." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ChatGPT is OpenAI's general-purpose assistant, built to answer questions over typed text and uploaded documents. Reading lab PDFs and a symptom history and proposing an explanation is an instance of that general use, not a designed diagnostic function. So the benefit falls within what the system was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is OpenAI's general-purpose assistant, built to answer questions over typed text and uploaded documents. Reading lab PDFs and a symptom history and proposing an explanation is an instance of that general use, not a designed diagnostic function. So the benefit falls within what the system was built to do." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-04", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored, as the classifier proposed: a health improvement for one person, not prevention of a specified harm; the Monitor itself labels it an incident on “harm mitigation (improvement in health)”. The Monitor entry bundles several Reddit cases (the 新智元 piece adds crasstyfartman's sister, buyableblah's endometriosis and sometimelater0212's dog) and Microsoft's MAI-DxO benchmark on NEJM cases, which is a study; this record is restricted to the one dated post. The post was read through the PullPush archive API (reddit.com returned 403): author u/Adventurous-Gold6935, 4 July 2025 16:16 UTC, 9,149 points and 1,089 comments at capture; Hindustan Times counted over 6,000 upvotes on 5 July and Livemint more than 9,000 on 6 July. The user's own words make clear that the mutation came from a Function Health panel and that ChatGPT supplied the interpretation; the model name, the five uploaded PDFs, the methyl B complex, the earlier anxiety diagnosis with an SSRI and Xanax, and the symptom list (full-body tingling, tinnitus, chronic fatigue) come from the author's replies in the thread, 4 to 6 July. Greg Brockman's repost on X is reported by Cailian Press (“今日”, 6 July Beijing time) and AppSo (quoting him as saying ChatGPT was used to solve a long-standing medical problem), and PYMNTS links the post (ID 1941567568155902397, whose timestamp resolves to 5 July 2025 18:39 UTC); the post itself could not be read. The repost is vendor amplification of a self-report, not evidence. Dated to the post; the improvement accrued over the preceding months and is undated, and the Monitor's ID date (6 July) is the first Chinese report. The author's gender is not stated. The k.sina.cn article now returns “article no longer exists”; both 36kr pages sat behind a bot check, so their 163.com mirrors were read; Hindustan Times and Livemint were read with curl after WebFetch was refused. The ACMG guideline was read through the Europe PMC API.", "source": "https://oecd.ai/en/incidents/2025-07-06-2ff8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://news.ifeng.com/c/8kp8doX5Vd0", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The user already held a genetic result (homozygous A1298C MTHFR from a Function Health panel), five PDFs of laboratory results and a written symptom timeline. They gave all of it to the model rather than a description of symptoms alone.", "A paid reasoning model (o3, by the user's account) was asked to reconcile B12 values in the laboratory's normal range with persistent neurological symptoms. It proposed a mechanism and a supplement rather than a bare label.", "A treating doctor willing to review the model's reasoning and the gene report and to approve a methylated B-complex before it was started." ], "must_hold": [ "A clinician reviews the model's inference and approves any supplement or treatment before it is started. Here the doctor did, by the user's account.", "The genetic result comes from an actual test. The model interprets; it does not genotype. The ACMG guideline says MTHFR polymorphism testing has minimal clinical utility, so the premise itself is contested.", "The benefit is self-reported and pseudonymous. Any record of this kind must carry the absence of a clinician statement and the published medical doubt (DXY via ifeng) as a standing caveat." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as benefit created or restored, as the classifier proposed: a health improvement for one person, not prevention of a specified harm; the Monitor itself labels it an incident on “harm mitigation (improvement in health)”. The Monitor entry bundles several Reddit cases (the 新智元 piece adds crasstyfartman's sister, buyableblah's endometriosis and sometimelater0212's dog) and Microsoft's MAI-DxO benchmark on NEJM cases, which is a study; this record is restricted to the one dated post. The post was read through the PullPush archive API (reddit.com returned 403): author u/Adventurous-Gold6935, 4 July 2025 16:16 UTC, 9,149 points and 1,089 comments at capture; Hindustan Times counted over 6,000 upvotes on 5 July and Livemint more than 9,000 on 6 July. The user's own words make clear that the mutation came from a Function Health panel and that ChatGPT supplied the interpretation; the model name, the five uploaded PDFs, the methyl B complex, the earlier anxiety diagnosis with an SSRI and Xanax, and the symptom list (full-body tingling, tinnitus, chronic fatigue) come from the author's replies in the thread, 4 to 6 July. Greg Brockman's repost on X is reported by Cailian Press (“今日”, 6 July Beijing time) and AppSo (quoting him as saying ChatGPT was used to solve a long-standing medical problem), and PYMNTS links the post (ID 1941567568155902397, whose timestamp resolves to 5 July 2025 18:39 UTC); the post itself could not be read. The repost is vendor amplification of a self-report, not evidence. Dated to the post; the improvement accrued over the preceding months and is undated, and the Monitor's ID date (6 July) is the first Chinese report. The author's gender is not stated. The k.sina.cn article now returns “article no longer exists”; both 36kr pages sat behind a bot check, so their 163.com mirrors were read; Hindustan Times and Livemint were read with curl after WebFetch was refused. The ACMG guideline was read through the Europe PMC API.", "source": "https://oecd.ai/en/incidents/2025-07-06-2ff8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://news.ifeng.com/c/8kp8doX5Vd0", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Consumer health (self-directed interpretation of laboratory and genetic results)", "segment": "Consumer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "u/Adventurous-Gold6935 (2025). ChatGPT solved a 10+ year problem no doctors could figure out. Reddit, r/ChatGPT, 4 July 2025.", "title": "ChatGPT solved a 10+ year problem no doctors could figure out", "url": "https://www.reddit.com/r/ChatGPT/comments/1lrmom4/chatgpt_solved_a_10_year_problem_no_doctors_could/", "date": "2025-07-04", "written_by": "beneficiary", "quote": "ChatGPT took all my lab results and symptom history and concluded this was on par with the mutation." }, { "kind": "news report", "citation": "Chouhan, M. S. / Hindustan Times (2025). ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years. Hindustan Times, Trending, 5 July 2025.", "title": "ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years", "url": "https://www.hindustantimes.com/trending/chatgpt-uncovers-root-cause-of-mysterious-illness-that-baffled-doctors-for-over-10-years-101751704864270.html", "date": "2025-07-05", "written_by": "independent", "quote": "A Reddit post is gaining significant attention after a user claimed that ChatGPT helped uncover the root cause of a decade-long health mystery" }, { "kind": "news report", "citation": "Thakur, A. / Mint (2025). Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade. Livemint, 6 July 2025.", "title": "Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade", "url": "https://www.livemint.com/news/trends/reddit-user-claims-chatgpt-uncovered-medical-condition-doctors-overlooked-for-a-decade-11751788742326.html", "date": "2025-07-06", "written_by": "independent", "quote": "The AI flagged a possible genetic mutation- homozygous A1298C MTHFR, known to affect B12 processing in the body, even when blood levels seem normal." }, { "kind": "news report", "citation": "PYMNTS (2025). ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice. PYMNTS.com, 10 July 2025.", "title": "ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice", "url": "https://www.pymnts.com/news/artificial-intelligence/2025/chatgpt-as-doctor-when-consumers-rely-on-ai-for-medical-advice/", "date": "2025-07-10", "written_by": "independent", "quote": "A physician later confirmed the diagnosis and the B12 supplement treatment later \"largely resolved\" the symptoms." }, { "kind": "news report", "citation": "财联社 / Cailian Press (2025). 十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近. 新浪财经, 6 July 2025.", "title": "十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近", "url": "https://finance.sina.com.cn/jjxw/2025-07-06/doc-infephkm0866335.shtml", "date": "2025-07-06", "written_by": "independent", "quote": "OpenAI总裁兼联合创始人Greg Brockman也在今日转发了这一事件。" }, { "kind": "news report", "citation": "AppSo (2025). 百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因. 网易 (mirror of 36氪), 7 July 2025.", "title": "百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因", "url": "https://m.163.com/dy/article/K3SPL1UB0511CSAO.html", "date": "2025-07-07", "written_by": "independent", "quote": "直到某天，他在功能医学检查中发现了一个异于常人的遗传突变，MTHFR（叶酸代谢基因）A1298C 突变" }, { "kind": "news report", "citation": "新智元 (2025). 10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界. 网易 (mirror of 36氪), 6 July 2025.", "title": "10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界", "url": "https://m.163.com/dy/article/K3PMM22K0511ABV6.html", "date": "2025-07-06", "written_by": "independent", "quote": "ChatGPT发现，虽然血清维生素B12水平正常，但却与持续性的神经痛和慢性疲乏矛盾" }, { "kind": "news report", "citation": "丁香园 / DXY (2025). 10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了. 凤凰网, 8 July 2025.", "title": "10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了", "url": "https://news.ifeng.com/c/8kp8doX5Vd0", "date": "2025-07-08", "written_by": "independent", "quote": "但也有医生怒斥，这个病例真实性存疑，『更可能是功能医学宣传再一次立功』。" }, { "kind": "report", "citation": "Hickey, S. E., Curry, C. J., Toriello, H. V. (2013). ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing. Genetics in Medicine 15(2), 153-156. doi:10.1038/gim.2012.165.", "title": "ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing", "url": "https://europepmc.org/article/MED/23288205", "date": "2013-01-03", "written_by": "independent", "quote": "There is growing evidence that MTHFR polymorphism testing has minimal clinical utility and, therefore should not be ordered as a part of a routine evaluation for thrombophilia." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0141-source-0001", "AIBD-0141-source-0002", "AIBD-0141-source-0003", "AIBD-0141-source-0004", "AIBD-0141-source-0005", "AIBD-0141-source-0006", "AIBD-0141-source-0007", "AIBD-0141-source-0008", "AIBD-0141-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "u/Adventurous-Gold6935 (2025). ChatGPT solved a 10+ year problem no doctors could figure out. Reddit, r/ChatGPT, 4 July 2025.", "title": "ChatGPT solved a 10+ year problem no doctors could figure out", "url": "https://www.reddit.com/r/ChatGPT/comments/1lrmom4/chatgpt_solved_a_10_year_problem_no_doctors_could/", "date": "2025-07-04", "written_by": "beneficiary", "quote": "ChatGPT took all my lab results and symptom history and concluded this was on par with the mutation." }, { "kind": "news report", "citation": "Chouhan, M. S. / Hindustan Times (2025). ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years. Hindustan Times, Trending, 5 July 2025.", "title": "ChatGPT uncovers root cause of mysterious illness that baffled doctors for over 10 years", "url": "https://www.hindustantimes.com/trending/chatgpt-uncovers-root-cause-of-mysterious-illness-that-baffled-doctors-for-over-10-years-101751704864270.html", "date": "2025-07-05", "written_by": "independent", "quote": "A Reddit post is gaining significant attention after a user claimed that ChatGPT helped uncover the root cause of a decade-long health mystery" }, { "kind": "news report", "citation": "Thakur, A. / Mint (2025). Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade. Livemint, 6 July 2025.", "title": "Reddit user claims ChatGPT uncovered medical condition doctors overlooked for a decade", "url": "https://www.livemint.com/news/trends/reddit-user-claims-chatgpt-uncovered-medical-condition-doctors-overlooked-for-a-decade-11751788742326.html", "date": "2025-07-06", "written_by": "independent", "quote": "The AI flagged a possible genetic mutation- homozygous A1298C MTHFR, known to affect B12 processing in the body, even when blood levels seem normal." }, { "kind": "news report", "citation": "PYMNTS (2025). ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice. PYMNTS.com, 10 July 2025.", "title": "ChatGPT as Doctor: When Consumers Rely on AI for Medical Advice", "url": "https://www.pymnts.com/news/artificial-intelligence/2025/chatgpt-as-doctor-when-consumers-rely-on-ai-for-medical-advice/", "date": "2025-07-10", "written_by": "independent", "quote": "A physician later confirmed the diagnosis and the B12 supplement treatment later \"largely resolved\" the symptoms." }, { "kind": "news report", "citation": "财联社 / Cailian Press (2025). 十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近. 新浪财经, 6 July 2025.", "title": "十多年未解谜症，ChatGPT一语道破病因？微软：“医疗超级智能”渐近", "url": "https://finance.sina.com.cn/jjxw/2025-07-06/doc-infephkm0866335.shtml", "date": "2025-07-06", "written_by": "independent", "quote": "OpenAI总裁兼联合创始人Greg Brockman也在今日转发了这一事件。" }, { "kind": "news report", "citation": "AppSo (2025). 百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因. 网易 (mirror of 36氪), 7 July 2025.", "title": "百万人围观，OpenAI总裁转发：他用 ChatGPT，找出了医生10年都没发现的病因", "url": "https://m.163.com/dy/article/K3SPL1UB0511CSAO.html", "date": "2025-07-07", "written_by": "independent", "quote": "直到某天，他在功能医学检查中发现了一个异于常人的遗传突变，MTHFR（叶酸代谢基因）A1298C 突变" }, { "kind": "news report", "citation": "新智元 (2025). 10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界. 网易 (mirror of 36氪), 6 July 2025.", "title": "10年顽疾ChatGPT一眼识破！AlphaGo时刻震撼全球医疗界", "url": "https://m.163.com/dy/article/K3PMM22K0511ABV6.html", "date": "2025-07-06", "written_by": "independent", "quote": "ChatGPT发现，虽然血清维生素B12水平正常，但却与持续性的神经痛和慢性疲乏矛盾" }, { "kind": "news report", "citation": "丁香园 / DXY (2025). 10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了. 凤凰网, 8 July 2025.", "title": "10年顽疾被ChatGPT确诊了？医生怒斥：假的，别被骗了", "url": "https://news.ifeng.com/c/8kp8doX5Vd0", "date": "2025-07-08", "written_by": "independent", "quote": "但也有医生怒斥，这个病例真实性存疑，『更可能是功能医学宣传再一次立功』。" }, { "kind": "report", "citation": "Hickey, S. E., Curry, C. J., Toriello, H. V. (2013). ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing. Genetics in Medicine 15(2), 153-156. doi:10.1038/gim.2012.165.", "title": "ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing", "url": "https://europepmc.org/article/MED/23288205", "date": "2013-01-03", "written_by": "independent", "quote": "There is growing evidence that MTHFR polymorphism testing has minimal clinical utility and, therefore should not be ordered as a part of a routine evaluation for thrombophilia." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Reddit user says ChatGPT tied 10+ years of symptoms to an MTHFR A1298C result and B12 use; doctor agreed; symptoms largely resolved.", "account": "On 4 July 2025 Reddit user u/Adventurous-Gold6935 wrote in r/ChatGPT from the United States. They reported over ten years of unexplained symptoms. Tests included spinal magnetic resonance imaging (MRI), a computed tomography (CT) scan, in-depth blood work, a Lyme test and a neurologist's check for MS. Then a Function Health panel showed a homozygous A1298C MTHFR mutation. They uploaded five PDFs of those results and a symptom history to ChatGPT (o3, they said). It concluded the symptoms were “on par with the mutation”. It concluded that normal-looking B12 might not be utilized, so supplementation was needed. Their doctor, “super shocked”, agreed. On a methyl B complex, their symptoms were “largely resolved” a few months later. OpenAI's president reposted the thread on 6 July." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "ChatGPT interpreted laboratory reports alongside the user’s symptom history." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "o3, according to the author." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "o3 (the author's one-word reply when asked whether they used the free or paid version of ChatGPT)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (OpenAI consumer app), given five uploaded Function Health lab PDFs and a written symptom timeline" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT ties a Reddit user's ten-plus years of unexplained symptoms to a homozygous A1298C MTHFR test result and proposes B12 supplementation; the symptoms may have largely resolved", "headline": "ChatGPT ties ten-plus years of symptoms to an MTHFR mutation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "93eb1e0326c679485e074fb8a055a496ad8200ac9bf7133980740a921278f8f2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 4 July 2025 Reddit user u/Adventurous-Gold6935 wrote in r/ChatGPT from the United States. They reported over ten years of unexplained symptoms. Tests included spinal magnetic resonance imaging (MRI), a computed tomography (CT) scan, in-depth blood work, a Lyme test and a neurologist's check for MS. Then a Function Health panel showed a homozygous A1298C MTHFR mutation. They uploaded five PDFs of those results and a symptom history to ChatGPT (o3, they said). It concluded the symptoms were “on par with the mutation”. It concluded that normal-looking B12 might not be utilized, so supplementation was needed. Their doctor, “super shocked”, agreed. On a methyl B complex, their symptoms were “largely resolved” a few months later. OpenAI's president reposted the thread on 6 July.", "replication": { "produced_by": [ "The user already held a genetic result (homozygous A1298C MTHFR from a Function Health panel), five PDFs of laboratory results and a written symptom timeline. They gave all of it to the model rather than a description of symptoms alone.", "A paid reasoning model (o3, by the user's account) was asked to reconcile B12 values in the laboratory's normal range with persistent neurological symptoms. It proposed a mechanism and a supplement rather than a bare label.", "A treating doctor willing to review the model's reasoning and the gene report and to approve a methylated B-complex before it was started." ], "must_hold": [ "A clinician reviews the model's inference and approves any supplement or treatment before it is started. Here the doctor did, by the user's account.", "The genetic result comes from an actual test. The model interprets; it does not genotype. The ACMG guideline says MTHFR polymorphism testing has minimal clinical utility, so the premise itself is contested.", "The benefit is self-reported and pseudonymous. Any record of this kind must carry the absence of a clinician statement and the published medical doubt (DXY via ifeng) as a standing caveat." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0147", "title": "Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner in Dadu District", "summary": "Taichung EPB AI smoke detection flagged roadside waste burning in Dadu District; a 74-year-old repeat offender was caught and fined.", "date_observed": "2025-07-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Taichung's Environmental Protection Bureau (EPB) installed its AI smoke-recognition system, air micro-sensors and cameras beside Hugan Road, Dadu District. That followed a March 2025 complaint about smoke from a dumping spot. CNA reports that shortly after 08:00 on 4 July 2025 the instruments flagged abnormal air quality. Inspectors found dumped waste burning. The system recorded the same man in July and August. His motorcycle plate was too faded to read. So inspectors collected neighbors' closed-circuit television (CCTV) and dashcam footage. A Wuri Precinct officer recognized a 74-year-old man surnamed Zhao, who confessed. On 13 September 2025 the EPB announced a fine of up to NT$100,000 under the Air Pollution Control Act. It asked the land manager to clear the site.", "category": "protective response", "unexpected": false, "purpose": "The EPB introduced AI smoke-recognition cameras in 2022 to recognize abnormal smoke around the clock at open-burning hotspots. They send automatic alerts so inspectors can locate and stop pollution sources and reduce fire risk. Detecting and recording this roadside burning was that intended use.", "system": "AI智慧判煙系統 (AI smart smoke-recognition system) with air micro-sensors and surveillance cameras, operated by the Taichung City Environmental Protection Bureau; 36 hotspot monitoring stations as of July 2025 and over 100 AI and sensor sites citywide by September 2025", "model_version": null, "developer": null, "deployer": "Taichung City Government Environmental Protection Bureau (臺中市政府環境保護局)", "location": "Taichung, Taiwan", "domain": "Environmental protection (air-quality enforcement)", "segment": "Public sector, municipal environmental enforcement", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "An illegal burner caught and fined removes a pollution source; no air-quality change is measured.", "registry_ids": { "oecd_aim": "2025-09-13-b5dc" }, "ratings": [ { "group": "societal", "depth": 2, "reason": "The EPB says the case removed “a potential pollution source threatening air quality” for residents near Hugan Road in Dadu District. CTS and PTS describe repeated burns at the same spot in February, July and August 2025 next to weeds. No exposure figures or air-quality measurements are reported. So the benefit is material but local and unquantified." }, { "group": "organizational", "depth": 1, "reason": "The EPB and Wuri Precinct police closed a repeat-offender case that the faded plate had stalled. The system's alert and video supplied the inspection trigger and the core evidence. The EPB presents the case as proof that its “smart technology city” enforcement works." } ], "ai_role": { "status": "assessed", "statement": "The AI smoke-recognition system and micro-sensors supplied the detection that sent inspectors to the burning site. CNA dates it first to 4 July 2025, then repeatedly in July and August. It also supplied the video that recorded the offender. It could not read his faded motorcycle plate. So identification came from private CCTV, dashcam footage and a police officer's recognition of a local resident. The system's contribution is detection and documentation. Removal of the source depended on human investigation. No measured air-quality change or proven counterfactual is reported. So the record sits at protective response with prevention unproven rather than specific harm prevented." }, "evidence": [ { "kind": "press release", "citation": "Taichung City Government Environmental Protection Bureau (2025). 真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯 [The truth is one: citizens help the EPB and police crack a serial arsonist]. EPB news release, 13 September 2025.", "title": "真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯", "url": "https://www.epb.taichung.gov.tw/3092215/post", "date": "2025-09-13", "written_by": "deployer", "quote": "共同為大肚區市民解決了一起威脅空氣品質的潛在污染源" }, { "kind": "news report", "citation": "Su Mu-chun / Central News Agency (2025). AI偵測空污異常 台中男非法焚燒廢棄物遭查獲 [AI detects abnormal air pollution; Taichung man caught illegally burning waste]. CNA, 13 September 2025.", "title": "AI偵測空污異常 台中男非法焚燒廢棄物遭查獲", "url": "https://www.cna.com.tw/news/asoc/202509130143.aspx", "date": "2025-09-13", "written_by": "independent", "quote": "環保局今年7月4日上午8時多，運用科學儀器偵測出" }, { "kind": "news report", "citation": "Peng Huan-chun / Public Television Service (2025). 台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾 [Taichung EPB's AI smoke-recognition system catches roadside garbage burner]. PTS News, 13 September 2025.", "title": "台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾", "url": "https://news.pts.org.tw/article/770398", "date": "2025-09-13", "written_by": "independent", "quote": "3月接獲民眾檢舉，大肚區護岸路旁的產業道路常有濃煙" }, { "kind": "news report", "citation": "Wu Shu-ping and Lo Yi-hsin / TVBS (2025). 空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人 [Elderly garbage burner caught by AI; 74-year-old living alone identified by police]. TVBS News, 13 September 2025.", "title": "空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人", "url": "https://news.tvbs.com.tw/local/2988180", "date": "2025-09-13", "written_by": "independent", "quote": "環保局接獲系統通報後立即趕到現場滅火，避免了可能的火災蔓延" }, { "kind": "news report", "citation": "Chinese Television System / 華視 (2025). 男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬 [Man repeatedly burned waste; with no casualties, only a NT$100,000 fine]. CTS via Yahoo News Taiwan, 13 September 2025.", "title": "男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬", "url": "http://web.archive.org/web/20250913113400/https://tw.news.yahoo.com/%E7%94%B7%E5%A4%9A%E6%AC%A1%E7%B8%B1%E7%81%AB%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E5%8D%B1%E5%AE%B3%E5%85%AC%E5%85%B1%E5%AE%89%E5%85%A8-%E6%9C%AA%E9%80%A0%E6%88%90%E5%82%B7%E4%BA%A1-%E5%8F%AA%E8%83%BD%E7%BD%B0%E5%8D%81%E8%90%AC-101000875.html", "date": "2025-09-13", "written_by": "independent", "quote": "分別在2月、7月和8月都亂丟廢棄物、還縱火燃燒" }, { "kind": "news report", "citation": "Tsai Shu-yuan / Liberty Times (2025). 台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟 [Black smoke over Dadu traced to a serial arsonist]. Liberty Times Net, 13 September 2025.", "title": "台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟", "url": "https://news.ltn.com.tw/news/Taichung/breakingnews/5176646", "date": "2025-09-13", "written_by": "independent", "quote": "環保局7、8月以AI智慧判煙系統及空氣微型感測器接連發現" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). AI神助攻 台中揪出焚燒廢棄物縱火慣犯 [AI assist: Taichung catches habitual waste-burning arsonist]. NOWnews via Yahoo News Taiwan, 13 September 2025.", "title": "AI神助攻 台中揪出焚燒廢棄物縱火慣犯", "url": "https://tw.news.yahoo.com/ai%E7%A5%9E%E5%8A%A9%E6%94%BB-%E5%8F%B0%E4%B8%AD%E6%8F%AA%E5%87%BA%E7%84%9A%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E7%B8%B1%E7%81%AB%E6%85%A3%E7%8A%AF-032546731.html", "date": "2025-09-13", "written_by": "independent", "quote": "成功查獲一名長期縱火焚燒廢棄物的行為人，有效消除潛在污染源" }, { "kind": "news report", "citation": "Chuang Yu-hsuan / CTWANT (2025). AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝 [AI catches arsonist: abnormal smoke in Dadu]. CTWANT, 13 September 2025.", "title": "AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝", "url": "https://www.ctwant.com/article/445301/", "date": "2025-09-13", "written_by": "independent", "quote": "透過系統即時告警，結合民眾熱心通報" }, { "kind": "press release", "citation": "Taichung City Government (2025). AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法 [AI as a disaster-prevention tool: real-time alerts on open burning]. City news release, 5 July 2025.", "title": "AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法", "url": "https://www.taichung.gov.tw/8868/8872/9962/3034821", "date": "2025-07-05", "written_by": "deployer", "quote": "系統隨即自動發送告警訊息，值勤人員立即派遣稽巡查人員趕赴現場" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). 露天燃燒小心被抓包 中市AI盯哨無所遁形 [Open burners beware: Taichung's AI is watching]. NOWnews, 5 July 2025.", "title": "露天燃燒小心被抓包 中市AI盯哨無所遁形", "url": "https://www.nownews.com/news/6703456", "date": "2025-07-05", "written_by": "independent", "quote": "自111年起導入AI判煙技術，透過智慧監控、即時通報" }, { "kind": "news report", "citation": "Taiwan News (2026). Taichung uses AI cameras, drones to crack down on illegal open burning. Taiwan News, 16 August 2026.", "title": "Taichung uses AI cameras, drones to crack down on illegal open burning", "url": "https://www.taiwannews.com.tw/news/6422182", "date": "2026-08-16", "written_by": "independent", "quote": "it began deploying AI smoke-detecting cameras along with drones in 2022" } ], "replication": { "produced_by": [ "Fixed AI smoke-recognition cameras and air micro-sensors installed at a known open-burning hotspot after a public complaint, with automatic alerts to inspectors", "Inspectors able to reach the site while the fire burned. They could assemble third-party CCTV and dashcam footage when its video could not read the faded plate", "Local police (Wuri Precinct Dadu Station) familiar enough with residents to match the recorded build, clothing and gait to a known 74-year-old resident", "A legal basis for penalties (Air Pollution Control Act Article 32) and a land manager that could be asked to clear the dump site" ], "must_hold": [ "The AI alert must reach staff who can respond while the fire is burning and who have the mandate to enter the site", "Identification must not rest on the camera alone. Plate recognition failed here and human evidence-gathering closed the case", "The offender must be identifiable and reachable. A stranger with no local ties would likely not have been recognized" ], "echoes": [] }, "paired_incident": null, "headline": "Taichung EPB's AI smoke detection catches a serial waste burner", "metric": "a fine of up to NT$100,000", "comparator": null, "later": { "status": "scaled", "date": "2026-08-16", "note": "By August 2026 the bureau reported nearly 170 AI smoke-detection systems across Taichung, up from 36 stations in July 2025 and over 100 sites in September 2025, with hundreds of open-burning cases caught and NT$1.28 million in fines.", "quote": "The bureau added that nearly 170 AI smoke-detection systems have been installed across Taichung to improve enforcement efficiency.", "url": "https://www.taiwannews.com.tw/news/6422182" }, "value": { "amount": "新臺幣10萬元以下 (up to NT$100,000)", "what": "fine under Article 32 of the Air Pollution Control Act for the open burning; CTS reports the fine as NT$100,000", "who": "the 74-year-old burner pays", "estimate": true, "quote": "依違反空氣污染防制法第32條規定，處新臺幣10萬元以下罰鍰", "url": "https://www.epb.taichung.gov.tw/3092215/post" }, "developer_country": null, "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-09-13-b5dc", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the value as stated from the cited sources.", "source": "https://www.taiwannews.com.tw/news/6422182; https://www.epb.taichung.gov.tw/3092215/post", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.epb.taichung.gov.tw/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: nine independent news reports and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0147", "catalog_version": "1.0.0", "source_fingerprint": "7f516b70e55a6ccadb8762561b98177a908055267bf55b453125a59c66807224", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0147-source-0001", "AIBD-0147-source-0002", "AIBD-0147-source-0003", "AIBD-0147-source-0004", "AIBD-0147-source-0005", "AIBD-0147-source-0006", "AIBD-0147-source-0007", "AIBD-0147-source-0008", "AIBD-0147-source-0009", "AIBD-0147-source-0010", "AIBD-0147-source-0011" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0147-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Taichung City Government Environmental Protection Bureau (臺中市政府環境保護局)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI smoke-recognition system and micro-sensors supplied the detection that sent inspectors to the burning site. CNA dates it first to 4 July 2025, then repeatedly in July and August. It also supplied the video that recorded the offender. It could not read his faded motorcycle plate. So identification came from private CCTV, dashcam footage and a police officer's recognition of a local resident. The system's contribution is detection and documentation. Removal of the source depended on human investigation. No measured air-quality change or proven counterfactual is reported. So the record sits at protective response with prevention unproven rather than specific harm prevented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The AI smoke-recognition system and micro-sensors supplied the detection that sent inspectors to the burning site. CNA dates it first to 4 July 2025, then repeatedly in July and August. It also supplied the video that recorded the offender. It could not read his faded motorcycle plate. So identification came from private CCTV, dashcam footage and a police officer's recognition of a local resident. The system's contribution is detection and documentation. Removal of the source depended on human investigation. No measured air-quality change or proven counterfactual is reported. So the record sits at protective response with prevention unproven rather than specific harm prevented." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The EPB says the case removed “a potential pollution source threatening air quality” for residents near Hugan Road in Dadu District. CTS and PTS describe repeated burns at the same spot in February, July and August 2025 next to weeds. No exposure figures or air-quality measurements are reported. So the benefit is material but local and unquantified." }, { "group": "organizational", "depth": 1, "reason": "The EPB and Wuri Precinct police closed a repeat-offender case that the faded plate had stalled. The system's alert and video supplied the inspection trigger and the core evidence. The EPB presents the case as proof that its “smart technology city” enforcement works." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: nine independent news reports and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The EPB says the case removed “a potential pollution source threatening air quality” for residents near Hugan Road in Dadu District. CTS and PTS describe repeated burns at the same spot in February, July and August 2025 next to weeds. No exposure figures or air-quality measurements are reported. So the benefit is material but local and unquantified." }, { "group": "organizational", "depth": 1, "reason": "The EPB and Wuri Precinct police closed a repeat-offender case that the faded plate had stalled. The system's alert and video supplied the inspection trigger and the core evidence. The EPB presents the case as proof that its “smart technology city” enforcement works." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The EPB says the case removed “a potential pollution source threatening air quality” for residents near Hugan Road in Dadu District. CTS and PTS describe repeated burns at the same spot in February, July and August 2025 next to weeds. No exposure figures or air-quality measurements are reported. So the benefit is material but local and unquantified." }, { "group": "organizational", "depth": 1, "reason": "The EPB and Wuri Precinct police closed a repeat-offender case that the faded plate had stalled. The system's alert and video supplied the inspection trigger and the core evidence. The EPB presents the case as proof that its “smart technology city” enforcement works." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "新臺幣10萬元以下 (up to NT$100,000)", "what": "fine under Article 32 of the Air Pollution Control Act for the open burning; CTS reports the fine as NT$100,000", "who": "the 74-year-old burner pays", "estimate": true, "quote": "依違反空氣污染防制法第32條規定，處新臺幣10萬元以下罰鍰", "url": "https://www.epb.taichung.gov.tw/3092215/post" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "新臺幣10萬元以下 (up to NT$100,000)", "what": "fine under Article 32 of the Air Pollution Control Act for the open burning; CTS reports the fine as NT$100,000", "who": "the 74-year-old burner pays", "estimate": true, "quote": "依違反空氣污染防制法第32條規定，處新臺幣10萬元以下罰鍰", "url": "https://www.epb.taichung.gov.tw/3092215/post" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "新臺幣10萬元以下 (up to NT$100,000)", "what": "fine under Article 32 of the Air Pollution Control Act for the open burning; CTS reports the fine as NT$100,000", "who": "the 74-year-old burner pays", "estimate": true, "quote": "依違反空氣污染防制法第32條規定，處新臺幣10萬元以下罰鍰", "url": "https://www.epb.taichung.gov.tw/3092215/post" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "a fine of up to NT$100,000", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-09-13-b5dc" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-08-16", "note": "By August 2026 the bureau reported nearly 170 AI smoke-detection systems across Taichung, up from 36 stations in July 2025 and over 100 sites in September 2025, with hundreds of open-burning cases caught and NT$1.28 million in fines.", "quote": "The bureau added that nearly 170 AI smoke-detection systems have been installed across Taichung to improve enforcement efficiency.", "url": "https://www.taiwannews.com.tw/news/6422182" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0147" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "An illegal burner caught and fined removes a pollution source; no air-quality change is measured." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Taichung's Environmental Protection Bureau (EPB) installed its AI smoke-recognition system, air micro-sensors and cameras beside Hugan Road, Dadu District. That followed a March 2025 complaint about smoke from a dumping spot. CNA reports that shortly after 08:00 on 4 July 2025 the instruments flagged abnormal air quality. Inspectors found dumped waste burning. The system recorded the same man in July and August. His motorcycle plate was too faded to read. So inspectors collected neighbors' closed-circuit television (CCTV) and dashcam footage. A Wuri Precinct officer recognized a 74-year-old man surnamed Zhao, who confessed. On 13 September 2025 the EPB announced a fine of up to NT$100,000 under the Air Pollution Control Act. It asked the land manager to clear the site.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The EPB says the case removed “a potential pollution source threatening air quality” for residents near Hugan Road in Dadu District. CTS and PTS describe repeated burns at the same spot in February, July and August 2025 next to weeds. No exposure figures or air-quality measurements are reported. So the benefit is material but local and unquantified." }, { "group": "organizational", "depth": 1, "reason": "The EPB and Wuri Precinct police closed a repeat-offender case that the faded plate had stalled. The system's alert and video supplied the inspection trigger and the core evidence. The EPB presents the case as proof that its “smart technology city” enforcement works." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The EPB introduced AI smoke-recognition cameras in 2022 to recognize abnormal smoke around the clock at open-burning hotspots. They send automatic alerts so inspectors can locate and stop pollution sources and reduce fire risk. Detecting and recording this roadside burning was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Taichung, Taiwan", "deployer_country": "Taiwan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The EPB introduced AI smoke-recognition cameras in 2022 to recognize abnormal smoke around the clock at open-burning hotspots. They send automatic alerts so inspectors can locate and stop pollution sources and reduce fire risk. Detecting and recording this roadside burning was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-04", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-09-13-b5dc", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the value as stated from the cited sources.", "source": "https://www.taiwannews.com.tw/news/6422182; https://www.epb.taichung.gov.tw/3092215/post", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.epb.taichung.gov.tw/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Fixed AI smoke-recognition cameras and air micro-sensors installed at a known open-burning hotspot after a public complaint, with automatic alerts to inspectors", "Inspectors able to reach the site while the fire burned. They could assemble third-party CCTV and dashcam footage when its video could not read the faded plate", "Local police (Wuri Precinct Dadu Station) familiar enough with residents to match the recorded build, clothing and gait to a known 74-year-old resident", "A legal basis for penalties (Air Pollution Control Act Article 32) and a land manager that could be asked to clear the dump site" ], "must_hold": [ "The AI alert must reach staff who can respond while the fire is burning and who have the mandate to enter the site", "Identification must not rest on the camera alone. Plate recognition failed here and human evidence-gathering closed the case", "The offender must be identifiable and reachable. A stranger with no local ties would likely not have been recognized" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-09-13-b5dc", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the value as stated from the cited sources.", "source": "https://www.taiwannews.com.tw/news/6422182; https://www.epb.taichung.gov.tw/3092215/post", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.epb.taichung.gov.tw/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Environmental protection (air-quality enforcement)", "segment": "Public sector, municipal environmental enforcement" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Taichung City Government Environmental Protection Bureau (2025). 真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯 [The truth is one: citizens help the EPB and police crack a serial arsonist]. EPB news release, 13 September 2025.", "title": "真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯", "url": "https://www.epb.taichung.gov.tw/3092215/post", "date": "2025-09-13", "written_by": "deployer", "quote": "共同為大肚區市民解決了一起威脅空氣品質的潛在污染源" }, { "kind": "news report", "citation": "Su Mu-chun / Central News Agency (2025). AI偵測空污異常 台中男非法焚燒廢棄物遭查獲 [AI detects abnormal air pollution; Taichung man caught illegally burning waste]. CNA, 13 September 2025.", "title": "AI偵測空污異常 台中男非法焚燒廢棄物遭查獲", "url": "https://www.cna.com.tw/news/asoc/202509130143.aspx", "date": "2025-09-13", "written_by": "independent", "quote": "環保局今年7月4日上午8時多，運用科學儀器偵測出" }, { "kind": "news report", "citation": "Peng Huan-chun / Public Television Service (2025). 台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾 [Taichung EPB's AI smoke-recognition system catches roadside garbage burner]. PTS News, 13 September 2025.", "title": "台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾", "url": "https://news.pts.org.tw/article/770398", "date": "2025-09-13", "written_by": "independent", "quote": "3月接獲民眾檢舉，大肚區護岸路旁的產業道路常有濃煙" }, { "kind": "news report", "citation": "Wu Shu-ping and Lo Yi-hsin / TVBS (2025). 空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人 [Elderly garbage burner caught by AI; 74-year-old living alone identified by police]. TVBS News, 13 September 2025.", "title": "空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人", "url": "https://news.tvbs.com.tw/local/2988180", "date": "2025-09-13", "written_by": "independent", "quote": "環保局接獲系統通報後立即趕到現場滅火，避免了可能的火災蔓延" }, { "kind": "news report", "citation": "Chinese Television System / 華視 (2025). 男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬 [Man repeatedly burned waste; with no casualties, only a NT$100,000 fine]. CTS via Yahoo News Taiwan, 13 September 2025.", "title": "男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬", "url": "http://web.archive.org/web/20250913113400/https://tw.news.yahoo.com/%E7%94%B7%E5%A4%9A%E6%AC%A1%E7%B8%B1%E7%81%AB%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E5%8D%B1%E5%AE%B3%E5%85%AC%E5%85%B1%E5%AE%89%E5%85%A8-%E6%9C%AA%E9%80%A0%E6%88%90%E5%82%B7%E4%BA%A1-%E5%8F%AA%E8%83%BD%E7%BD%B0%E5%8D%81%E8%90%AC-101000875.html", "date": "2025-09-13", "written_by": "independent", "quote": "分別在2月、7月和8月都亂丟廢棄物、還縱火燃燒" }, { "kind": "news report", "citation": "Tsai Shu-yuan / Liberty Times (2025). 台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟 [Black smoke over Dadu traced to a serial arsonist]. Liberty Times Net, 13 September 2025.", "title": "台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟", "url": "https://news.ltn.com.tw/news/Taichung/breakingnews/5176646", "date": "2025-09-13", "written_by": "independent", "quote": "環保局7、8月以AI智慧判煙系統及空氣微型感測器接連發現" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). AI神助攻 台中揪出焚燒廢棄物縱火慣犯 [AI assist: Taichung catches habitual waste-burning arsonist]. NOWnews via Yahoo News Taiwan, 13 September 2025.", "title": "AI神助攻 台中揪出焚燒廢棄物縱火慣犯", "url": "https://tw.news.yahoo.com/ai%E7%A5%9E%E5%8A%A9%E6%94%BB-%E5%8F%B0%E4%B8%AD%E6%8F%AA%E5%87%BA%E7%84%9A%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E7%B8%B1%E7%81%AB%E6%85%A3%E7%8A%AF-032546731.html", "date": "2025-09-13", "written_by": "independent", "quote": "成功查獲一名長期縱火焚燒廢棄物的行為人，有效消除潛在污染源" }, { "kind": "news report", "citation": "Chuang Yu-hsuan / CTWANT (2025). AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝 [AI catches arsonist: abnormal smoke in Dadu]. CTWANT, 13 September 2025.", "title": "AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝", "url": "https://www.ctwant.com/article/445301/", "date": "2025-09-13", "written_by": "independent", "quote": "透過系統即時告警，結合民眾熱心通報" }, { "kind": "press release", "citation": "Taichung City Government (2025). AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法 [AI as a disaster-prevention tool: real-time alerts on open burning]. City news release, 5 July 2025.", "title": "AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法", "url": "https://www.taichung.gov.tw/8868/8872/9962/3034821", "date": "2025-07-05", "written_by": "deployer", "quote": "系統隨即自動發送告警訊息，值勤人員立即派遣稽巡查人員趕赴現場" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). 露天燃燒小心被抓包 中市AI盯哨無所遁形 [Open burners beware: Taichung's AI is watching]. NOWnews, 5 July 2025.", "title": "露天燃燒小心被抓包 中市AI盯哨無所遁形", "url": "https://www.nownews.com/news/6703456", "date": "2025-07-05", "written_by": "independent", "quote": "自111年起導入AI判煙技術，透過智慧監控、即時通報" }, { "kind": "news report", "citation": "Taiwan News (2026). Taichung uses AI cameras, drones to crack down on illegal open burning. Taiwan News, 16 August 2026.", "title": "Taichung uses AI cameras, drones to crack down on illegal open burning", "url": "https://www.taiwannews.com.tw/news/6422182", "date": "2026-08-16", "written_by": "independent", "quote": "it began deploying AI smoke-detecting cameras along with drones in 2022" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0147-source-0001", "AIBD-0147-source-0002", "AIBD-0147-source-0003", "AIBD-0147-source-0004", "AIBD-0147-source-0005", "AIBD-0147-source-0006", "AIBD-0147-source-0007", "AIBD-0147-source-0008", "AIBD-0147-source-0009", "AIBD-0147-source-0010", "AIBD-0147-source-0011" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Taichung City Government Environmental Protection Bureau (2025). 真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯 [The truth is one: citizens help the EPB and police crack a serial arsonist]. EPB news release, 13 September 2025.", "title": "真相只有一個 臺中市多位熱心市民協助環保局與警察局通力合作破獲縱火慣犯", "url": "https://www.epb.taichung.gov.tw/3092215/post", "date": "2025-09-13", "written_by": "deployer", "quote": "共同為大肚區市民解決了一起威脅空氣品質的潛在污染源" }, { "kind": "news report", "citation": "Su Mu-chun / Central News Agency (2025). AI偵測空污異常 台中男非法焚燒廢棄物遭查獲 [AI detects abnormal air pollution; Taichung man caught illegally burning waste]. CNA, 13 September 2025.", "title": "AI偵測空污異常 台中男非法焚燒廢棄物遭查獲", "url": "https://www.cna.com.tw/news/asoc/202509130143.aspx", "date": "2025-09-13", "written_by": "independent", "quote": "環保局今年7月4日上午8時多，運用科學儀器偵測出" }, { "kind": "news report", "citation": "Peng Huan-chun / Public Television Service (2025). 台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾 [Taichung EPB's AI smoke-recognition system catches roadside garbage burner]. PTS News, 13 September 2025.", "title": "台中環保局設AI智慧判煙系統 取締路邊燒垃圾民眾", "url": "https://news.pts.org.tw/article/770398", "date": "2025-09-13", "written_by": "independent", "quote": "3月接獲民眾檢舉，大肚區護岸路旁的產業道路常有濃煙" }, { "kind": "news report", "citation": "Wu Shu-ping and Lo Yi-hsin / TVBS (2025). 空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人 [Elderly garbage burner caught by AI; 74-year-old living alone identified by police]. TVBS News, 13 September 2025.", "title": "空汙老翁「焚燒垃圾」遭AI逮到！74歲獨居翁騎車逃 警1招揪人", "url": "https://news.tvbs.com.tw/local/2988180", "date": "2025-09-13", "written_by": "independent", "quote": "環保局接獲系統通報後立即趕到現場滅火，避免了可能的火災蔓延" }, { "kind": "news report", "citation": "Chinese Television System / 華視 (2025). 男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬 [Man repeatedly burned waste; with no casualties, only a NT$100,000 fine]. CTS via Yahoo News Taiwan, 13 September 2025.", "title": "男多次縱火燒廢棄物危害公共安全 「未造成傷亡」只能罰十萬", "url": "http://web.archive.org/web/20250913113400/https://tw.news.yahoo.com/%E7%94%B7%E5%A4%9A%E6%AC%A1%E7%B8%B1%E7%81%AB%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E5%8D%B1%E5%AE%B3%E5%85%AC%E5%85%B1%E5%AE%89%E5%85%A8-%E6%9C%AA%E9%80%A0%E6%88%90%E5%82%B7%E4%BA%A1-%E5%8F%AA%E8%83%BD%E7%BD%B0%E5%8D%81%E8%90%AC-101000875.html", "date": "2025-09-13", "written_by": "independent", "quote": "分別在2月、7月和8月都亂丟廢棄物、還縱火燃燒" }, { "kind": "news report", "citation": "Tsai Shu-yuan / Liberty Times (2025). 台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟 [Black smoke over Dadu traced to a serial arsonist]. Liberty Times Net, 13 September 2025.", "title": "台中大肚區驚見「黑煙衝天」！真相竟是連環縱火犯作祟", "url": "https://news.ltn.com.tw/news/Taichung/breakingnews/5176646", "date": "2025-09-13", "written_by": "independent", "quote": "環保局7、8月以AI智慧判煙系統及空氣微型感測器接連發現" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). AI神助攻 台中揪出焚燒廢棄物縱火慣犯 [AI assist: Taichung catches habitual waste-burning arsonist]. NOWnews via Yahoo News Taiwan, 13 September 2025.", "title": "AI神助攻 台中揪出焚燒廢棄物縱火慣犯", "url": "https://tw.news.yahoo.com/ai%E7%A5%9E%E5%8A%A9%E6%94%BB-%E5%8F%B0%E4%B8%AD%E6%8F%AA%E5%87%BA%E7%84%9A%E7%87%92%E5%BB%A2%E6%A3%84%E7%89%A9%E7%B8%B1%E7%81%AB%E6%85%A3%E7%8A%AF-032546731.html", "date": "2025-09-13", "written_by": "independent", "quote": "成功查獲一名長期縱火焚燒廢棄物的行為人，有效消除潛在污染源" }, { "kind": "news report", "citation": "Chuang Yu-hsuan / CTWANT (2025). AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝 [AI catches arsonist: abnormal smoke in Dadu]. CTWANT, 13 September 2025.", "title": "AI智慧抓縱火犯！台中大肚異常濃煙曝光驚險追緝", "url": "https://www.ctwant.com/article/445301/", "date": "2025-09-13", "written_by": "independent", "quote": "透過系統即時告警，結合民眾熱心通報" }, { "kind": "press release", "citation": "Taichung City Government (2025). AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法 [AI as a disaster-prevention tool: real-time alerts on open burning]. City news release, 5 July 2025.", "title": "AI成為防災利器 即時通報露天燃燒 中市環保局提醒市民勿觸法", "url": "https://www.taichung.gov.tw/8868/8872/9962/3034821", "date": "2025-07-05", "written_by": "deployer", "quote": "系統隨即自動發送告警訊息，值勤人員立即派遣稽巡查人員趕赴現場" }, { "kind": "news report", "citation": "Liu Jung-chun / NOWnews (2025). 露天燃燒小心被抓包 中市AI盯哨無所遁形 [Open burners beware: Taichung's AI is watching]. NOWnews, 5 July 2025.", "title": "露天燃燒小心被抓包 中市AI盯哨無所遁形", "url": "https://www.nownews.com/news/6703456", "date": "2025-07-05", "written_by": "independent", "quote": "自111年起導入AI判煙技術，透過智慧監控、即時通報" }, { "kind": "news report", "citation": "Taiwan News (2026). Taichung uses AI cameras, drones to crack down on illegal open burning. Taiwan News, 16 August 2026.", "title": "Taichung uses AI cameras, drones to crack down on illegal open burning", "url": "https://www.taiwannews.com.tw/news/6422182", "date": "2026-08-16", "written_by": "independent", "quote": "it began deploying AI smoke-detecting cameras along with drones in 2022" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Taichung EPB AI smoke detection flagged roadside waste burning in Dadu District; a 74-year-old repeat offender was caught and fined.", "account": "Taichung's Environmental Protection Bureau (EPB) installed its AI smoke-recognition system, air micro-sensors and cameras beside Hugan Road, Dadu District. That followed a March 2025 complaint about smoke from a dumping spot. CNA reports that shortly after 08:00 on 4 July 2025 the instruments flagged abnormal air quality. Inspectors found dumped waste burning. The system recorded the same man in July and August. His motorcycle plate was too faded to read. So inspectors collected neighbors' closed-circuit television (CCTV) and dashcam footage. A Wuri Precinct officer recognized a 74-year-old man surnamed Zhao, who confessed. On 13 September 2025 the EPB announced a fine of up to NT$100,000 under the Air Pollution Control Act. It asked the land manager to clear the site." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI智慧判煙系統 (AI smart smoke-recognition system) with air micro-sensors and surveillance cameras, operated by the Taichung City Environmental Protection Bureau; 36 hotspot monitoring stations as of July 2025 and over 100 AI and sensor sites citywide by September 2025" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner in Dadu District", "headline": "Taichung EPB's AI smoke detection catches a serial waste burner" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7f516b70e55a6ccadb8762561b98177a908055267bf55b453125a59c66807224" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Taichung's Environmental Protection Bureau (EPB) installed its AI smoke-recognition system, air micro-sensors and cameras beside Hugan Road, Dadu District. That followed a March 2025 complaint about smoke from a dumping spot. CNA reports that shortly after 08:00 on 4 July 2025 the instruments flagged abnormal air quality. Inspectors found dumped waste burning. The system recorded the same man in July and August. His motorcycle plate was too faded to read. So inspectors collected neighbors' closed-circuit television (CCTV) and dashcam footage. A Wuri Precinct officer recognized a 74-year-old man surnamed Zhao, who confessed. On 13 September 2025 the EPB announced a fine of up to NT$100,000 under the Air Pollution Control Act. It asked the land manager to clear the site.", "replication": { "produced_by": [ "Fixed AI smoke-recognition cameras and air micro-sensors installed at a known open-burning hotspot after a public complaint, with automatic alerts to inspectors", "Inspectors able to reach the site while the fire burned. They could assemble third-party CCTV and dashcam footage when its video could not read the faded plate", "Local police (Wuri Precinct Dadu Station) familiar enough with residents to match the recorded build, clothing and gait to a known 74-year-old resident", "A legal basis for penalties (Air Pollution Control Act Article 32) and a land manager that could be asked to clear the dump site" ], "must_hold": [ "The AI alert must reach staff who can respond while the fire is burning and who have the mandate to enter the site", "Identification must not rest on the camera alone. Plate recognition failed here and human evidence-gathering closed the case", "The offender must be identifiable and reachable. A stranger with no local ties would likely not have been recognized" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0281", "title": "Face2Gene's DeepGestalt changed medical geneticists' testing decisions in 17 cases involving 19 patients, in an international case series", "summary": "Rudy et al. (Am J Med Genet A, online 4 July 2025) report 17 cases/19 patients in which DeepGestalt changed geneticists' testing decisions; full text inaccessible, so no per-patient detail.", "date_observed": "2025-07-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Rudy, Gomes, Tkemaladze and 13 co-authors published “Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene”. It appeared online in the American Journal of Medical Genetics Part A on 4 July 2025 (volume 197, issue 11, November 2025). It states: “We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother”. For those cases, “DeepGestalt, the technology powering Face2Gene, changed medical geneticists” testing decisions'. Crossref lists author affiliations at the Greenwood Genetic Center, UC San Diego and Rady Children's Hospital, Tbilisi State Medical University and Weill Cornell. It also lists the University of Nebraska Medical Center, IDI-IRCCS Rome, the Hospital for Sick Children Toronto, UCSF/Fresno and the University of Alabama at Birmingham. It lists FDNA Inc for one author (Nicole Fleischer). It also lists a CC BY-NC-ND license. Despite that license, the full text was not available from Wiley. Unpaywall listed no repository copy and there is no PMC copy. So the sources on record do not give the patients' ages, features, the suggestions made or the tests ordered. The consultations are undated in the abstract.", "category": "benefit created", "unexpected": false, "purpose": "Face2Gene is built to suggest candidate syndromes from facial photographs and clinical features so that geneticists can direct testing. Changed testing decisions were that purpose.", "system": "Face2Gene (DeepGestalt facial phenotyping)", "model_version": null, "developer": "FDNA", "deployer": "Clinical genetics services at the authors' institutions in the United States, Georgia, Italy and Canada (per Crossref affiliations)", "location": "United States, Georgia, Italy and Canada (authors' institutions; case locations not readable)", "domain": "Healthcare / clinical genetics", "segment": "Rare disease diagnosis", "benefit_type": "Improved Physical Health", "taxonomy_note": "Redirected genetic testing is a step toward diagnosis; per-patient outcomes remain unverified.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "DeepGestalt changed medical geneticists' testing decisions in 17 cases involving 19 patients, per the abstract read on Europe PMC. That is a measurable change in the test strategy itself. What diagnoses or treatment followed is not stated. 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It appeared online in the American Journal of Medical Genetics Part A on 4 July 2025 (volume 197, issue 11, November 2025). It states: “We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother”. For those cases, “DeepGestalt, the technology powering Face2Gene, changed medical geneticists” testing decisions'. Crossref lists author affiliations at the Greenwood Genetic Center, UC San Diego and Rady Children's Hospital, Tbilisi State Medical University and Weill Cornell. It also lists the University of Nebraska Medical Center, IDI-IRCCS Rome, the Hospital for Sick Children Toronto, UCSF/Fresno and the University of Alabama at Birmingham. It lists FDNA Inc for one author (Nicole Fleischer). It also lists a CC BY-NC-ND license. Despite that license, the full text was not available from Wiley. Unpaywall listed no repository copy and there is no PMC copy. 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Cureus, https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Geneticists uploading facial photographs and clinical features to Face2Gene during consultations", "Cases where recognition was hard: atypical presentation, overlapping dysmorphology or phenotypes across ancestries, per the abstract" ], "must_hold": [ "The true syndrome is represented in DeepGestalt's training data", "Clinicians act on the suggestion by changing the test ordered and confirm by molecular testing" ], "echoes": [ { "date": "2023-01-05", "setting": "Single case at Akita National Hospital, Japan: Face2Gene listed MRD7 among candidates for a 22-year-old misdiagnosed with Cornelia de Lange syndrome; exome sequencing confirmed a DYRK1A variant (recorded separately as AIBD-0037)", "outcome": "recurred", "source": "Obara K, Abe E, Toyoshima I (2023). Cureus, https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Depth rated 2 for personal and 1 for organizational on the documented outcome, with the reason stated on each rating.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:40613735%20AND%20SRC:MED&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://fdna.com/privacy-policy/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare / clinical genetics", "segment": "Rare disease diagnosis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Rudy NL, Gomes A, Tkemaladze T, Abdul-Rahman O, Cratsenberg D, Pascolini G, Di Zenzo G, Castiglia D, Black E, Washington C, Chad L, Curry C, Del Campo M, Fleischer N, Bird LM, Hurst ACE (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene. American Journal of Medical Genetics Part A 197(11); online 4 July 2025. Abstract read on Europe PMC (PMID 40613735); one author at FDNA Inc.", "title": "Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene", "url": "https://europepmc.org/article/MED/40613735", "date": "2025-07-04", "written_by": "makers", "quote": "We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother" }, { "kind": "other", "citation": "Crossref metadata for doi:10.1002/ajmg.a.64171 (author affiliations, online date 4 July 2025, CC BY-NC-ND 4.0 licence); the publisher page itself returned a security block.", "title": "Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene", "url": "https://doi.org/10.1002/ajmg.a.64171", "date": "2025-07-04", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0281-source-0001", "AIBD-0281-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Rudy NL, Gomes A, Tkemaladze T, Abdul-Rahman O, Cratsenberg D, Pascolini G, Di Zenzo G, Castiglia D, Black E, Washington C, Chad L, Curry C, Del Campo M, Fleischer N, Bird LM, Hurst ACE (2025). Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene. American Journal of Medical Genetics Part A 197(11); online 4 July 2025. Abstract read on Europe PMC (PMID 40613735); one author at FDNA Inc.", "title": "Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene", "url": "https://europepmc.org/article/MED/40613735", "date": "2025-07-04", "written_by": "makers", "quote": "We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother" }, { "kind": "other", "citation": "Crossref metadata for doi:10.1002/ajmg.a.64171 (author affiliations, online date 4 July 2025, CC BY-NC-ND 4.0 licence); the publisher page itself returned a security block.", "title": "Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene", "url": "https://doi.org/10.1002/ajmg.a.64171", "date": "2025-07-04", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Rudy et al. (Am J Med Genet A, online 4 July 2025) report 17 cases/19 patients in which DeepGestalt changed geneticists' testing decisions; full text inaccessible, so no per-patient detail.", "account": "Rudy, Gomes, Tkemaladze and 13 co-authors published “Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene”. It appeared online in the American Journal of Medical Genetics Part A on 4 July 2025 (volume 197, issue 11, November 2025). It states: “We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother”. For those cases, “DeepGestalt, the technology powering Face2Gene, changed medical geneticists” testing decisions'. Crossref lists author affiliations at the Greenwood Genetic Center, UC San Diego and Rady Children's Hospital, Tbilisi State Medical University and Weill Cornell. It also lists the University of Nebraska Medical Center, IDI-IRCCS Rome, the Hospital for Sick Children Toronto, UCSF/Fresno and the University of Alabama at Birmingham. It lists FDNA Inc for one author (Nicole Fleischer). It also lists a CC BY-NC-ND license. Despite that license, the full text was not available from Wiley. Unpaywall listed no repository copy and there is no PMC copy. So the sources on record do not give the patients' ages, features, the suggestions made or the tests ordered. The consultations are undated in the abstract." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Face2Gene (DeepGestalt facial phenotyping)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "FDNA" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Face2Gene's DeepGestalt changed medical geneticists' testing decisions in 17 cases involving 19 patients, in an international case series", "headline": "Face2Gene's DeepGestalt changes geneticists' testing in 17 cases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1c55708b42400dfb319d92130aaa6fcd520e7168fd3fd9e5a06b74eb092338ae" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Rudy, Gomes, Tkemaladze and 13 co-authors published “Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene”. It appeared online in the American Journal of Medical Genetics Part A on 4 July 2025 (volume 197, issue 11, November 2025). It states: “We present 17 cases involving 19 patients, including one pair of affected siblings and one case involving a child and her affected mother”. For those cases, “DeepGestalt, the technology powering Face2Gene, changed medical geneticists” testing decisions'. Crossref lists author affiliations at the Greenwood Genetic Center, UC San Diego and Rady Children's Hospital, Tbilisi State Medical University and Weill Cornell. It also lists the University of Nebraska Medical Center, IDI-IRCCS Rome, the Hospital for Sick Children Toronto, UCSF/Fresno and the University of Alabama at Birmingham. It lists FDNA Inc for one author (Nicole Fleischer). It also lists a CC BY-NC-ND license. Despite that license, the full text was not available from Wiley. Unpaywall listed no repository copy and there is no PMC copy. So the sources on record do not give the patients' ages, features, the suggestions made or the tests ordered. The consultations are undated in the abstract.", "replication": { "produced_by": [ "Geneticists uploading facial photographs and clinical features to Face2Gene during consultations", "Cases where recognition was hard: atypical presentation, overlapping dysmorphology or phenotypes across ancestries, per the abstract" ], "must_hold": [ "The true syndrome is represented in DeepGestalt's training data", "Clinicians act on the suggestion by changing the test ordered and confirm by molecular testing" ], "echoes": [ { "date": "2023-01-05", "setting": "Single case at Akita National Hospital, Japan: Face2Gene listed MRD7 among candidates for a 22-year-old misdiagnosed with Cornelia de Lange syndrome; exome sequencing confirmed a DYRK1A variant (recorded separately as AIBD-0037)", "outcome": "recurred", "source": "Obara K, Abe E, Toyoshima I (2023). Cureus, https://pmc.ncbi.nlm.nih.gov/articles/PMC9822525/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0373", "title": "Vigia Mais MT facial recognition identifies a woman wanted for drug trafficking in downtown Cuiabá; Ciosp tracks her in real time and the 1st Military Police Battalion arrests her", "summary": "Diário de Cuiabá (14 July 2025): Sesp-MT's Vigia Mais MT cameras matched a woman with a June 2024 trafficking warrant in central Cuiabá on 12 July; Ciosp tracked her live and the 1st BPM arrested her.", "date_observed": "2025-07-12", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Saturday 12 July 2025 the video-monitoring system of Mato Grosso's State Secretariat of Public Security (Sesp) helped arrest a woman in downtown Cuiabá. It acted through the Vigia Mais MT program. She had an open warrant for drug trafficking. That is per the same text carried by Diário de Cuiabá and O Documento on 14 July and CliqueF5 on 15 July 2025. Cameras in the city center identified her by facial recognition. After the system confirmed her identity, the monitoring center of the Integrated Public Security Operations Center (Ciosp) tracked her movements in real time. It passed them to a team of the 1st Military Police Battalion, which made the approach. Her warrant had been issued on 19 June 2024 by the 9th Criminal Court Specialized in Drug Offenses. She was taken to a Civil Judicial Police unit. The reports add that from April to July 2025 about 60 fugitives were located and arrested by state security forces.", "category": "benefit created", "unexpected": false, "purpose": "Vigia Mais MT is the state's video-monitoring program. Its facial recognition compares faces seen on public cameras with wanted persons so that Ciosp can direct patrols to them. Locating a person with an open warrant is that purpose.", "system": "Vigia Mais MT video-monitoring facial recognition (Sesp-MT / Ciosp)", "model_version": null, "developer": null, "deployer": "Secretaria de Estado de Segurança Pública de Mato Grosso (Sesp-MT), through the Centro Integrado de Operações de Segurança Pública (Ciosp)", "location": "Cuiabá, Brazil", "domain": "Policing / fugitive identification", "segment": "Public-space facial recognition against warrant lists", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-07-14-f4e4" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Sesp-MT's Ciosp located a woman wanted since a 19 June 2024 warrant and tracked her in real time, per the 14 July 2025 reports. It handed her to the 1st Military Police Battalion, which arrested her. A measurable result for the unit." }, { "group": "societal", "depth": 1, "reason": "One person with an open drug-trafficking warrant was taken into custody. The reports give no evidence of any further harm prevented. So the public benefit is the execution of a warrant." } ], "ai_role": { "status": "assessed", "statement": "The reports credit the facial recognition system with the identification. Cameras in central Cuiabá matched her face and the system confirmed her identity. Ciosp operators then tracked her and a Military Police team made the arrest. The sources do not name the vendor, the algorithm or any match score. They come from a single text that reads as the state's release." }, "evidence": [ { "kind": "news report", "citation": "Diário de Cuiabá (2025). Reconhecimento facial leva à prisão procurada por tráfico. Diário de Cuiabá, Cidades, 14 July 2025.", "title": "Reconhecimento facial leva à prisão procurada por tráfico", "url": "https://www.diariodecuiaba.com.br/cidades/reconhecimento-facial-leva-a-prisao-procurada-por-trafico/713555", "date": "2025-07-14", "written_by": "independent", "quote": "Após a confirmação da identidade por meio do sistema, a central de monitoramento do Centro Integrado de Operações de Segurança Pública (Ciosp) rastreou os deslocamentos da mulher em tempo real" }, { "kind": "news report", "citation": "O Documento (2025). Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá. O Documento, 14 July 2025.", "title": "Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá", "url": "https://odocumento.com.br/mulher-procurada-por-trafico-e-presa-por-reconhecimento-facial-em-cuiaba", "date": "2025-07-14", "written_by": "independent", "quote": "De abril a julho, aproximadamente 60 foragidos da Justiça foram localizados e presos pelas forças de segurança do Estado." }, { "kind": "news report", "citation": "CliqueF5 (2025). Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento. CliqueF5, Polícia, 15 July 2025.", "title": "Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento", "url": "https://www.cliquef5.com.br/policia/mulher-procurada-por-trafico-e-presa-apos-ser-reconhecida-por-cameras-de-monitoramento/395259", "date": "2025-07-15", "written_by": "independent", "quote": "A captura foi possível graças à tecnologia de reconhecimento facial. A suspeita foi identificada pelas câmeras instaladas na região central da capital." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2025). Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil. OECD.AI, 14 July 2025.", "title": "Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil", "url": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "date": "2025-07-14", "written_by": "independent", "quote": "identified and enabled the real-time tracking and arrest of a woman wanted for drug trafficking in Cuiabá" } ], "replication": { "produced_by": [ "Public cameras in central Cuiabá feeding the Vigia Mais MT facial recognition", "A warrant record for the woman in the list the system compares against", "Ciosp operators able to confirm the match and follow her across cameras in real time", "A Military Police team near enough to make the approach" ], "must_hold": [ "The person passes a camera with a usable view of the face", "The warrant is current in the database the system queries", "Operators confirm the match before a patrol is sent" ], "echoes": [] }, "paired_incident": null, "headline": "Facial recognition finds a wanted woman in downtown Cuiabá", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Brazil", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "http://www.sesp.mt.gov.br/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0373", "catalog_version": "1.0.0", "source_fingerprint": "8fc21882c27f4b8e1bab0c9e3d454396fb600eca31279f33c3b8d5aed62c3981", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0373-source-0001", "AIBD-0373-source-0002", "AIBD-0373-source-0003", "AIBD-0373-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Secretaria de Estado de Segurança Pública de Mato Grosso (Sesp-MT), through the Centro Integrado de Operações de Segurança Pública (Ciosp)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The reports credit the facial recognition system with the identification. Cameras in central Cuiabá matched her face and the system confirmed her identity. Ciosp operators then tracked her and a Military Police team made the arrest. The sources do not name the vendor, the algorithm or any match score. They come from a single text that reads as the state's release." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The reports credit the facial recognition system with the identification. Cameras in central Cuiabá matched her face and the system confirmed her identity. Ciosp operators then tracked her and a Military Police team made the arrest. 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"record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Saturday 12 July 2025 the video-monitoring system of Mato Grosso's State Secretariat of Public Security (Sesp) helped arrest a woman in downtown Cuiabá. It acted through the Vigia Mais MT program. She had an open warrant for drug trafficking. That is per the same text carried by Diário de Cuiabá and O Documento on 14 July and CliqueF5 on 15 July 2025. Cameras in the city center identified her by facial recognition. After the system confirmed her identity, the monitoring center of the Integrated Public Security Operations Center (Ciosp) tracked her movements in real time. It passed them to a team of the 1st Military Police Battalion, which made the approach. Her warrant had been issued on 19 June 2024 by the 9th Criminal Court Specialized in Drug Offenses. She was taken to a Civil Judicial Police unit. The reports add that from April to July 2025 about 60 fugitives were located and arrested by state security forces.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Sesp-MT's Ciosp located a woman wanted since a 19 June 2024 warrant and tracked her in real time, per the 14 July 2025 reports. It handed her to the 1st Military Police Battalion, which arrested her. A measurable result for the unit." }, { "group": "societal", "depth": 1, "reason": "One person with an open drug-trafficking warrant was taken into custody. The reports give no evidence of any further harm prevented. So the public benefit is the execution of a warrant." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Vigia Mais MT is the state's video-monitoring program. Its facial recognition compares faces seen on public cameras with wanted persons so that Ciosp can direct patrols to them. Locating a person with an open warrant is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cuiabá, Brazil", "deployer_country": "Brazil" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Vigia Mais MT is the state's video-monitoring program. Its facial recognition compares faces seen on public cameras with wanted persons so that Ciosp can direct patrols to them. Locating a person with an open warrant is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-12", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "http://www.sesp.mt.gov.br/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Public cameras in central Cuiabá feeding the Vigia Mais MT facial recognition", "A warrant record for the woman in the list the system compares against", "Ciosp operators able to confirm the match and follow her across cameras in real time", "A Military Police team near enough to make the approach" ], "must_hold": [ "The person passes a camera with a usable view of the face", "The warrant is current in the database the system queries", "Operators confirm the match before a patrol is sent" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "http://www.sesp.mt.gov.br/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / fugitive identification", "segment": "Public-space facial recognition against warrant lists" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Diário de Cuiabá (2025). Reconhecimento facial leva à prisão procurada por tráfico. Diário de Cuiabá, Cidades, 14 July 2025.", "title": "Reconhecimento facial leva à prisão procurada por tráfico", "url": "https://www.diariodecuiaba.com.br/cidades/reconhecimento-facial-leva-a-prisao-procurada-por-trafico/713555", "date": "2025-07-14", "written_by": "independent", "quote": "Após a confirmação da identidade por meio do sistema, a central de monitoramento do Centro Integrado de Operações de Segurança Pública (Ciosp) rastreou os deslocamentos da mulher em tempo real" }, { "kind": "news report", "citation": "O Documento (2025). Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá. O Documento, 14 July 2025.", "title": "Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá", "url": "https://odocumento.com.br/mulher-procurada-por-trafico-e-presa-por-reconhecimento-facial-em-cuiaba", "date": "2025-07-14", "written_by": "independent", "quote": "De abril a julho, aproximadamente 60 foragidos da Justiça foram localizados e presos pelas forças de segurança do Estado." }, { "kind": "news report", "citation": "CliqueF5 (2025). Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento. CliqueF5, Polícia, 15 July 2025.", "title": "Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento", "url": "https://www.cliquef5.com.br/policia/mulher-procurada-por-trafico-e-presa-apos-ser-reconhecida-por-cameras-de-monitoramento/395259", "date": "2025-07-15", "written_by": "independent", "quote": "A captura foi possível graças à tecnologia de reconhecimento facial. A suspeita foi identificada pelas câmeras instaladas na região central da capital." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2025). Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil. OECD.AI, 14 July 2025.", "title": "Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil", "url": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "date": "2025-07-14", "written_by": "independent", "quote": "identified and enabled the real-time tracking and arrest of a woman wanted for drug trafficking in Cuiabá" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0373-source-0001", "AIBD-0373-source-0002", "AIBD-0373-source-0003", "AIBD-0373-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Diário de Cuiabá (2025). Reconhecimento facial leva à prisão procurada por tráfico. Diário de Cuiabá, Cidades, 14 July 2025.", "title": "Reconhecimento facial leva à prisão procurada por tráfico", "url": "https://www.diariodecuiaba.com.br/cidades/reconhecimento-facial-leva-a-prisao-procurada-por-trafico/713555", "date": "2025-07-14", "written_by": "independent", "quote": "Após a confirmação da identidade por meio do sistema, a central de monitoramento do Centro Integrado de Operações de Segurança Pública (Ciosp) rastreou os deslocamentos da mulher em tempo real" }, { "kind": "news report", "citation": "O Documento (2025). Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá. O Documento, 14 July 2025.", "title": "Mulher procurada por tráfico é presa por reconhecimento facial no centro de Cuiabá", "url": "https://odocumento.com.br/mulher-procurada-por-trafico-e-presa-por-reconhecimento-facial-em-cuiaba", "date": "2025-07-14", "written_by": "independent", "quote": "De abril a julho, aproximadamente 60 foragidos da Justiça foram localizados e presos pelas forças de segurança do Estado." }, { "kind": "news report", "citation": "CliqueF5 (2025). Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento. CliqueF5, Polícia, 15 July 2025.", "title": "Mulher procurada por tráfico é presa, após ser reconhecida por câmeras de monitoramento", "url": "https://www.cliquef5.com.br/policia/mulher-procurada-por-trafico-e-presa-apos-ser-reconhecida-por-cameras-de-monitoramento/395259", "date": "2025-07-15", "written_by": "independent", "quote": "A captura foi possível graças à tecnologia de reconhecimento facial. A suspeita foi identificada pelas câmeras instaladas na região central da capital." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2025). Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil. OECD.AI, 14 July 2025.", "title": "Facial Recognition AI Leads to Arrest of Fugitive in Cuiabá, Brazil", "url": "https://oecd.ai/en/incidents/2025-07-14-f4e4", "date": "2025-07-14", "written_by": "independent", "quote": "identified and enabled the real-time tracking and arrest of a woman wanted for drug trafficking in Cuiabá" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Diário de Cuiabá (14 July 2025): Sesp-MT's Vigia Mais MT cameras matched a woman with a June 2024 trafficking warrant in central Cuiabá on 12 July; Ciosp tracked her live and the 1st BPM arrested her.", "account": "On Saturday 12 July 2025 the video-monitoring system of Mato Grosso's State Secretariat of Public Security (Sesp) helped arrest a woman in downtown Cuiabá. It acted through the Vigia Mais MT program. She had an open warrant for drug trafficking. That is per the same text carried by Diário de Cuiabá and O Documento on 14 July and CliqueF5 on 15 July 2025. Cameras in the city center identified her by facial recognition. After the system confirmed her identity, the monitoring center of the Integrated Public Security Operations Center (Ciosp) tracked her movements in real time. It passed them to a team of the 1st Military Police Battalion, which made the approach. Her warrant had been issued on 19 June 2024 by the 9th Criminal Court Specialized in Drug Offenses. She was taken to a Civil Judicial Police unit. The reports add that from April to July 2025 about 60 fugitives were located and arrested by state security forces." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Vigia Mais MT video-monitoring facial recognition (Sesp-MT / Ciosp)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Vigia Mais MT facial recognition identifies a woman wanted for drug trafficking in downtown Cuiabá; Ciosp tracks her in real time and the 1st Military Police Battalion arrests her", "headline": "Facial recognition finds a wanted woman in downtown Cuiabá" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8fc21882c27f4b8e1bab0c9e3d454396fb600eca31279f33c3b8d5aed62c3981" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Saturday 12 July 2025 the video-monitoring system of Mato Grosso's State Secretariat of Public Security (Sesp) helped arrest a woman in downtown Cuiabá. It acted through the Vigia Mais MT program. She had an open warrant for drug trafficking. That is per the same text carried by Diário de Cuiabá and O Documento on 14 July and CliqueF5 on 15 July 2025. Cameras in the city center identified her by facial recognition. After the system confirmed her identity, the monitoring center of the Integrated Public Security Operations Center (Ciosp) tracked her movements in real time. It passed them to a team of the 1st Military Police Battalion, which made the approach. Her warrant had been issued on 19 June 2024 by the 9th Criminal Court Specialized in Drug Offenses. She was taken to a Civil Judicial Police unit. The reports add that from April to July 2025 about 60 fugitives were located and arrested by state security forces.", "replication": { "produced_by": [ "Public cameras in central Cuiabá feeding the Vigia Mais MT facial recognition", "A warrant record for the woman in the list the system compares against", "Ciosp operators able to confirm the match and follow her across cameras in real time", "A Military Police team near enough to make the approach" ], "must_hold": [ "The person passes a camera with a usable view of the face", "The warrant is current in the database the system queries", "Operators confirm the match before a patrol is sent" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0253", "title": "RFI's seismic early-warning system on the Rome-Naples high-speed line, operational since 3 May 2025, stops trains preventively during a magnitude 4.4 earthquake", "summary": "euronews (15 Jul 2025): about 20 accelerometric stations over 200 km feed software that analyzes P-waves and automatically slows or stops trains; in the weeks after activation a magnitude 4.4 quake...", "date_observed": "2025-07-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "ANSA reported on 14 Jul 2025 that Ferrovie dello Stato's infrastructure company Rete Ferroviaria Italiana had activated Italy's first seismic early-warning system. It is on the Rome-Naples high-speed line. It was developed with the Physics Department of the University of Naples Federico II. Technical support came from the Railway Technical Research Institute of the Japanese railways. A network of latest-generation sensors detects the earliest seismic waves. Within seconds it automatically activates safety protocols to slow or stop trains. euronews (15 Jul 2025) added that the system comprises about 20 seismic stations along 200 km, on the surface and in deep boreholes. They are linked by an SDH fiber network. An advanced software intelligence instantly analyzes the data and assesses the quake's danger, per euronews. The system had been operational since 3 May 2025. In the following weeks it was tested by a magnitude 4.4 earthquake. During it, trains on the Rome-Naples line were stopped preventively. Neither article gives the date of that earthquake. ANSA does not mention artificial intelligence. The OECD AI Incidents Monitor lists the system as AI-powered and a protective response.", "category": "protective response", "unexpected": false, "purpose": "The system is built to detect the first seismic waves and automatically slow or stop high-speed trains before stronger shaking arrives.", "system": "RFI seismic early-warning system (Early Warning Sismico) on the Rome-Naples high-speed line", "model_version": null, "developer": "Rete Ferroviaria Italiana with the Physics Department of the University of Naples Federico II and JR RTRI", "deployer": "Rete Ferroviaria Italiana (Gruppo FS)", "location": null, "domain": "Railway safety", "segment": "High-speed rail / earthquake early warning", "benefit_type": "Increased Product Safety", "taxonomy_note": "An automatic train stop on P-wave detection is a failsafe; no harm averted is documented.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Precautionary stops were executed automatically during a magnitude 4.4 quake. No damage, derailment or delay figures are reported." }, { "group": "societal", "depth": null, "reason": "No passenger outcome is documented beyond the stops." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The software evaluated the seismic signals and triggered the stop protocol without human intervention, per euronews. The sources are two Italian news reports of the company's announcement. No RFI document is among the sources and the algorithm is not described." }, "evidence": [ { "kind": "news report", "citation": "Euronews (15 Jul 2025). Treni che si fermano da soli: l'Italia inaugura l'allerta sismica automatica in ferrovia.", "title": "Treni che si fermano da soli: l'Italia inaugura l'allerta sismica automatica in ferrovia", "url": "https://it.euronews.com/viaggi/2025/07/15/treni-che-si-fermano-da-soli-litalia-inaugura-lallerta-sismica-automatica-in-ferrovia", "date": "2025-07-15", "written_by": "independent", "quote": "nelle settimane a seguire, è stato testato da un terremoto di magnitudo 4.4: i convogli sulla Roma–Napoli sono stati fermati preventivamente" }, { "kind": "news report", "citation": "ANSA (14 Jul 2025). Fs, su Av Roma-Napoli attivo primo sistema allerta sismica.", "title": "Fs, su Av Roma-Napoli attivo primo sistema allerta sismica", "url": "https://www.ansa.it/sito/notizie/economia/2025/07/14/-fs-su-av-roma-napoli-attivo-primo-sistema-allerta-sismica-_eebe792d-b886-4597-af5d-bd9ce79fc8e4.html", "date": "2025-07-14", "written_by": "independent", "quote": "attiva automaticamente protocolli di sicurezza per rallentare o fermare i treni" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2025-07-14-dd98: AI-Powered Seismic Early Warning System Protects Rome-Naples High-Speed Rail.", "title": "AI-Powered Seismic Early Warning System Protects Rome-Naples High-Speed Rail", "url": "https://oecd.ai/en/incidents/2025-07-14-dd98", "date": "2025-07-14", "written_by": "independent", "quote": "Using real-time sensor data and advanced software, the system automatically slows or stops trains during earthquakes, directly preventing potential harm to passengers and infrastructure." } ], "replication": { "produced_by": [ "Dense accelerometric stations along a high-speed line in a seismic region", "Low-latency fiber links to signaling", "Automatic P-wave analysis with thresholds tied to train control" ], "must_hold": [ "P-waves arrive early enough before damaging shaking to brake trains", "False triggers stay rare enough to keep the automatic stop enabled" ], "echoes": [] }, "paired_incident": null, "headline": "RFI seismic warning stops Rome-Naples trains in a 4.4 quake", "metric": "a magnitude 4.4 earthquake, during which trains on the Rome-Naples line were stopped", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The July 2025 coverage describes activation and RFI's intention to extend the system to other high-speed and ERTMS lines. No later development is established.", "quote": null, "url": null }, "value": null, "developer_country": "Italy", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rete_Ferroviaria_Italiana; https://en.wikipedia.org/wiki/Rete_Ferroviaria_Italiana", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0253", "catalog_version": "1.0.0", "source_fingerprint": "1e13f2aeb2cb54252a5f15abe4e23b6d06aafd6e66e4c39f7b6501212525e12b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0253-source-0001", "AIBD-0253-source-0002", "AIBD-0253-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Rete Ferroviaria Italiana with the Physics Department of the University of Naples Federico II and JR RTRI", "deployer": "Rete Ferroviaria Italiana (Gruppo FS)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The software evaluated the seismic signals and triggered the stop protocol without human intervention, per euronews. The sources are two Italian news reports of the company's announcement. No RFI document is among the sources and the algorithm is not described." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The software evaluated the seismic signals and triggered the stop protocol without human intervention, per euronews. The sources are two Italian news reports of the company's announcement. No RFI document is among the sources and the algorithm is not described." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Precautionary stops were executed automatically during a magnitude 4.4 quake. No damage, derailment or delay figures are reported." }, { "group": "societal", "reason": "No passenger outcome is documented beyond the stops." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Precautionary stops were executed automatically during a magnitude 4.4 quake. No damage, derailment or delay figures are reported." }, { "group": "societal", "reason": "No passenger outcome is documented beyond the stops." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Precautionary stops were executed automatically during a magnitude 4.4 quake. No damage, derailment or delay figures are reported." }, { "group": "societal", "reason": "No passenger outcome is documented beyond the stops." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", 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Fs, su Av Roma-Napoli attivo primo sistema allerta sismica.", "title": "Fs, su Av Roma-Napoli attivo primo sistema allerta sismica", "url": "https://www.ansa.it/sito/notizie/economia/2025/07/14/-fs-su-av-roma-napoli-attivo-primo-sistema-allerta-sismica-_eebe792d-b886-4597-af5d-bd9ce79fc8e4.html", "date": "2025-07-14", "written_by": "independent", "quote": "attiva automaticamente protocolli di sicurezza per rallentare o fermare i treni" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2025-07-14-dd98: AI-Powered Seismic Early Warning System Protects Rome-Naples High-Speed Rail.", "title": "AI-Powered Seismic Early Warning System Protects Rome-Naples High-Speed Rail", "url": "https://oecd.ai/en/incidents/2025-07-14-dd98", "date": "2025-07-14", "written_by": "independent", "quote": "Using real-time sensor data and advanced software, the system automatically slows or stops trains during earthquakes, directly preventing potential harm to passengers and infrastructure." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "euronews (15 Jul 2025): about 20 accelerometric stations over 200 km feed software that analyzes P-waves and automatically slows or stops trains; in the weeks after activation a magnitude 4.4 quake...", "account": "ANSA reported on 14 Jul 2025 that Ferrovie dello Stato's infrastructure company Rete Ferroviaria Italiana had activated Italy's first seismic early-warning system. 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The OECD AI Incidents Monitor lists the system as AI-powered and a protective response." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "RFI seismic early-warning system (Early Warning Sismico) on the Rome-Naples high-speed line" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rete Ferroviaria Italiana with the Physics Department of the University of Naples Federico II and JR RTRI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "RFI's seismic early-warning system on the Rome-Naples high-speed line, operational since 3 May 2025, stops trains preventively during a magnitude 4.4 earthquake", "headline": "RFI seismic warning stops Rome-Naples trains in a 4.4 quake" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1e13f2aeb2cb54252a5f15abe4e23b6d06aafd6e66e4c39f7b6501212525e12b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ANSA reported on 14 Jul 2025 that Ferrovie dello Stato's infrastructure company Rete Ferroviaria Italiana had activated Italy's first seismic early-warning system. It is on the Rome-Naples high-speed line. It was developed with the Physics Department of the University of Naples Federico II. Technical support came from the Railway Technical Research Institute of the Japanese railways. A network of latest-generation sensors detects the earliest seismic waves. Within seconds it automatically activates safety protocols to slow or stop trains. euronews (15 Jul 2025) added that the system comprises about 20 seismic stations along 200 km, on the surface and in deep boreholes. They are linked by an SDH fiber network. An advanced software intelligence instantly analyzes the data and assesses the quake's danger, per euronews. The system had been operational since 3 May 2025. In the following weeks it was tested by a magnitude 4.4 earthquake. During it, trains on the Rome-Naples line were stopped preventively. Neither article gives the date of that earthquake. ANSA does not mention artificial intelligence. The OECD AI Incidents Monitor lists the system as AI-powered and a protective response.", "replication": { "produced_by": [ "Dense accelerometric stations along a high-speed line in a seismic region", "Low-latency fiber links to signaling", "Automatic P-wave analysis with thresholds tied to train control" ], "must_hold": [ "P-waves arrive early enough before damaging shaking to brake trains", "False triggers stay rare enough to keep the automatic stop enabled" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0384", "title": "South Wales Police's Operator Initiated Facial Recognition app identifies a 38-year-old in Cardiff wanted on a 2012 European arrest warrant from Poland; he is remanded to Westminster magistrates", "summary": "A South Wales Police officer's OIFR phone app matched a 38-year-old in Cardiff to a 2012 Polish European arrest warrant for drug dealing and assaulting an officer; he was remanded (July 2025).", "date_observed": "2025-07-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "South Wales Police and Gwent Police are the first UK forces with the Operator Initiated Facial Recognition (OIFR) app. It lets an officer photograph a person on a police phone and compare the image with a reference database. It is for when the person refuses or gives false details. It launched in December 2024. More than 500 officers had been trained by July 2025 (Emergency Services Times, 15 July 2025). In one use, an officer in Cardiff identified a 38-year-old man wanted on a European arrest warrant since 2012. The warrant was for drug dealing and assaulting a police officer with a weapon in Poland. He was remanded in custody to Westminster magistrates' court (Wales Online, 14 July 2025). The forces report 50 South Wales searches producing 10 arrests, and six Gwent uses with three matches and one arrest. They cite National Physical Laboratory testing in which the correct match came top for people in the database (Wales Online). The arrest date is not given.", "category": "benefit created", "unexpected": false, "purpose": "Built to confirm the identity of a person an officer suspects is missing, at risk or wanted when they cannot or will not give details. This identification was that use.", "system": "Operator Initiated Facial Recognition (OIFR) mobile app, South Wales Police and Gwent Police", "model_version": null, "developer": null, "deployer": "South Wales Police (with Gwent Police)", "location": "Cardiff, United Kingdom", "domain": "Law enforcement / identity verification", "segment": "Street identity checks of people who refuse or give false details", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-07-14-7341" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "South Wales Police identified in Cardiff a man wanted on a 2012 European arrest warrant and remanded him. It reports 10 arrests from 50 app searches. A measurable result for the forces, on their own figures as relayed by the press." }, { "group": "societal", "depth": 1, "reason": "One man wanted for drug dealing and assaulting an officer with a weapon in Poland was taken into custody for extradition proceedings. The reports give no further harm prevented. So the public benefit is the execution of a warrant." } ], "ai_role": { "status": "assessed", "statement": "The app compared a photograph taken on a police phone to the reference database and returned the match that identified the man. Officers then confirmed the warrant and detained him. The force says National Physical Laboratory testing found the correct match returned as the top result for persons in the database. It says the app returns nothing for people not in it. Neither report names the vendor, the algorithm or a match score. Both rest on the force's figures." }, "evidence": [ { "kind": "news report", "citation": "Dalling, R. (2025). Man wanted since 2012 arrested after facial recognition app match. Wales Online, July 14, 2025.", "title": "Man wanted since 2012 arrested after facial recognition app match", "url": "https://www.walesonline.co.uk/news/wales-news/man-wanted-2012-arrested-after-32057351", "date": "2025-07-14", "written_by": "independent", "quote": "The 38-year-old man was remanded in custody to Westminster magistrates' court." }, { "kind": "news report", "citation": "Devonshire, J. (2025). More than 500 officers in Wales now trained to use real-time facial recognition app. Emergency Services Times, July 15, 2025.", "title": "More than 500 officers in Wales now trained to use real-time facial recognition app", "url": "https://emergencyservicestimes.com/2025/07/15/more-than-500-officers-in-wales-now-trained-to-use-real-time-facial-recognition-app/", "date": "2025-07-15", "written_by": "independent", "quote": "Thanks to the app, he was swiftly identified, remanded in custody, and brought before Westminster Magistrates' Court." }, { "kind": "registry label", "citation": "OECD.AI (2025). Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years. OECD AI Incidents and Hazards Monitor, 2025-07-14.", "title": "Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years", "url": "https://oecd.ai/en/incidents/2025-07-14-7341", "date": "2025-07-14", "written_by": "independent", "quote": "used a new AI-powered facial recognition app to identify and arrest a fugitive drug dealer wanted since 2012" } ], "replication": { "produced_by": [ "A street encounter in which the person refuses or gives false details", "A phone app linked to a reference database that holds the wanted person's image", "A warrant record current enough for officers to act on the match" ], "must_hold": [ "The app is used after an attempted engagement and only where necessary and proportionate, per the force's policy", "The match is confirmed against the warrant before detention" ], "echoes": [] }, "paired_incident": null, "headline": "Police phone app identifies man wanted since 2012 in Cardiff", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-7341", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/South_Wales_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0384", "catalog_version": "1.0.0", "source_fingerprint": "bfe51851999dc8d362daa237a555c84a3337b06a8cd2979fee1b8168eac29d33", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0384-source-0001", "AIBD-0384-source-0002", "AIBD-0384-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "South Wales Police (with Gwent Police)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The app compared a photograph taken on a police phone to the reference database and returned the match that identified the man. Officers then confirmed the warrant and detained him. The force says National Physical Laboratory testing found the correct match returned as the top result for persons in the database. It says the app returns nothing for people not in it. Neither report names the vendor, the algorithm or a match score. Both rest on the force's figures." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The app compared a photograph taken on a police phone to the reference database and returned the match that identified the man. Officers then confirmed the warrant and detained him. The force says National Physical Laboratory testing found the correct match returned as the top result for persons in the database. It says the app returns nothing for people not in it. Neither report names the vendor, the algorithm or a match score. 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"record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "South Wales Police and Gwent Police are the first UK forces with the Operator Initiated Facial Recognition (OIFR) app. It lets an officer photograph a person on a police phone and compare the image with a reference database. It is for when the person refuses or gives false details. It launched in December 2024. More than 500 officers had been trained by July 2025 (Emergency Services Times, 15 July 2025). In one use, an officer in Cardiff identified a 38-year-old man wanted on a European arrest warrant since 2012. The warrant was for drug dealing and assaulting a police officer with a weapon in Poland. He was remanded in custody to Westminster magistrates' court (Wales Online, 14 July 2025). The forces report 50 South Wales searches producing 10 arrests, and six Gwent uses with three matches and one arrest. They cite National Physical Laboratory testing in which the correct match came top for people in the database (Wales Online). The arrest date is not given.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "South Wales Police identified in Cardiff a man wanted on a 2012 European arrest warrant and remanded him. It reports 10 arrests from 50 app searches. A measurable result for the forces, on their own figures as relayed by the press." }, { "group": "societal", "depth": 1, "reason": "One man wanted for drug dealing and assaulting an officer with a weapon in Poland was taken into custody for extradition proceedings. The reports give no further harm prevented. So the public benefit is the execution of a warrant." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to confirm the identity of a person an officer suspects is missing, at risk or wanted when they cannot or will not give details. This identification was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Cardiff, United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to confirm the identity of a person an officer suspects is missing, at risk or wanted when they cannot or will not give details. This identification was that use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-14", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-7341", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/South_Wales_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A street encounter in which the person refuses or gives false details", "A phone app linked to a reference database that holds the wanted person's image", "A warrant record current enough for officers to act on the match" ], "must_hold": [ "The app is used after an attempted engagement and only where necessary and proportionate, per the force's policy", "The match is confirmed against the warrant before detention" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-14-7341", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/South_Wales_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Law enforcement / identity verification", "segment": "Street identity checks of people who refuse or give false details" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dalling, R. (2025). Man wanted since 2012 arrested after facial recognition app match. Wales Online, July 14, 2025.", "title": "Man wanted since 2012 arrested after facial recognition app match", "url": "https://www.walesonline.co.uk/news/wales-news/man-wanted-2012-arrested-after-32057351", "date": "2025-07-14", "written_by": "independent", "quote": "The 38-year-old man was remanded in custody to Westminster magistrates' court." }, { "kind": "news report", "citation": "Devonshire, J. (2025). More than 500 officers in Wales now trained to use real-time facial recognition app. Emergency Services Times, July 15, 2025.", "title": "More than 500 officers in Wales now trained to use real-time facial recognition app", "url": "https://emergencyservicestimes.com/2025/07/15/more-than-500-officers-in-wales-now-trained-to-use-real-time-facial-recognition-app/", "date": "2025-07-15", "written_by": "independent", "quote": "Thanks to the app, he was swiftly identified, remanded in custody, and brought before Westminster Magistrates' Court." }, { "kind": "registry label", "citation": "OECD.AI (2025). Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years. OECD AI Incidents and Hazards Monitor, 2025-07-14.", "title": "Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years", "url": "https://oecd.ai/en/incidents/2025-07-14-7341", "date": "2025-07-14", "written_by": "independent", "quote": "used a new AI-powered facial recognition app to identify and arrest a fugitive drug dealer wanted since 2012" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0384-source-0001", "AIBD-0384-source-0002", "AIBD-0384-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Dalling, R. (2025). Man wanted since 2012 arrested after facial recognition app match. Wales Online, July 14, 2025.", "title": "Man wanted since 2012 arrested after facial recognition app match", "url": "https://www.walesonline.co.uk/news/wales-news/man-wanted-2012-arrested-after-32057351", "date": "2025-07-14", "written_by": "independent", "quote": "The 38-year-old man was remanded in custody to Westminster magistrates' court." }, { "kind": "news report", "citation": "Devonshire, J. (2025). More than 500 officers in Wales now trained to use real-time facial recognition app. Emergency Services Times, July 15, 2025.", "title": "More than 500 officers in Wales now trained to use real-time facial recognition app", "url": "https://emergencyservicestimes.com/2025/07/15/more-than-500-officers-in-wales-now-trained-to-use-real-time-facial-recognition-app/", "date": "2025-07-15", "written_by": "independent", "quote": "Thanks to the app, he was swiftly identified, remanded in custody, and brought before Westminster Magistrates' Court." }, { "kind": "registry label", "citation": "OECD.AI (2025). Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years. OECD AI Incidents and Hazards Monitor, 2025-07-14.", "title": "Facial Recognition AI App Leads to Arrest of Fugitive Drug Dealer After 13 Years", "url": "https://oecd.ai/en/incidents/2025-07-14-7341", "date": "2025-07-14", "written_by": "independent", "quote": "used a new AI-powered facial recognition app to identify and arrest a fugitive drug dealer wanted since 2012" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A South Wales Police officer's OIFR phone app matched a 38-year-old in Cardiff to a 2012 Polish European arrest warrant for drug dealing and assaulting an officer; he was remanded (July 2025).", "account": "South Wales Police and Gwent Police are the first UK forces with the Operator Initiated Facial Recognition (OIFR) app. It lets an officer photograph a person on a police phone and compare the image with a reference database. It is for when the person refuses or gives false details. It launched in December 2024. More than 500 officers had been trained by July 2025 (Emergency Services Times, 15 July 2025). In one use, an officer in Cardiff identified a 38-year-old man wanted on a European arrest warrant since 2012. The warrant was for drug dealing and assaulting a police officer with a weapon in Poland. He was remanded in custody to Westminster magistrates' court (Wales Online, 14 July 2025). The forces report 50 South Wales searches producing 10 arrests, and six Gwent uses with three matches and one arrest. They cite National Physical Laboratory testing in which the correct match came top for people in the database (Wales Online). The arrest date is not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Operator Initiated Facial Recognition (OIFR) mobile app, South Wales Police and Gwent Police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "South Wales Police's Operator Initiated Facial Recognition app identifies a 38-year-old in Cardiff wanted on a 2012 European arrest warrant from Poland; he is remanded to Westminster magistrates", "headline": "Police phone app identifies man wanted since 2012 in Cardiff" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "bfe51851999dc8d362daa237a555c84a3337b06a8cd2979fee1b8168eac29d33" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "South Wales Police and Gwent Police are the first UK forces with the Operator Initiated Facial Recognition (OIFR) app. It lets an officer photograph a person on a police phone and compare the image with a reference database. It is for when the person refuses or gives false details. It launched in December 2024. More than 500 officers had been trained by July 2025 (Emergency Services Times, 15 July 2025). In one use, an officer in Cardiff identified a 38-year-old man wanted on a European arrest warrant since 2012. The warrant was for drug dealing and assaulting a police officer with a weapon in Poland. He was remanded in custody to Westminster magistrates' court (Wales Online, 14 July 2025). The forces report 50 South Wales searches producing 10 arrests, and six Gwent uses with three matches and one arrest. They cite National Physical Laboratory testing in which the correct match came top for people in the database (Wales Online). The arrest date is not given.", "replication": { "produced_by": [ "A street encounter in which the person refuses or gives false details", "A phone app linked to a reference database that holds the wanted person's image", "A warrant record current enough for officers to act on the match" ], "must_hold": [ "The app is used after an attempted engagement and only where necessary and proportionate, per the force's policy", "The match is confirmed against the warrant before detention" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0225", "title": "Google's Big Sleep agent may have isolated SQLite CVE-2025–6965 from threat-intel artifacts; fixed in 3.50.2 before exploitation", "summary": "Google says Big Sleep, fed indicators that attackers were staging a zero-day, isolated SQLite CVE-2025–6965; SQLite shipped the fix in 3.50.2 on 28 June 2025, announced 15 July 2025.", "date_observed": "2025-07-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The SQLite 3.50.2 release carrying the fix is dated 28 June 2025. The CVE record was published 15 July 2025. Google's post says that, based on intel from Google Threat Intelligence, the Big Sleep agent discovered an SQLite vulnerability known only to threat actors. It was at risk of being exploited, the post says. A Google spokesperson told The Record that its threat intelligence group found artifacts indicating a zero-day was being staged but could not identify the vulnerability. Big Sleep was used to isolate it, the spokesperson said. Google declined to name the actors or describe the indicators. The CVE record, assigned by Google, credits Vlad Stolyarov of Google's Threat Analysis Group with assistance from Google Big Sleep. SQLite's release log lists the corresponding fix. Independent confirmation that exploitation was imminent is absent. The claim rests on Google.", "category": "protective response", "unexpected": false, "purpose": "Actively search for and find unknown security vulnerabilities in software using a large language model (LLM) agent (Google DeepMind and Project Zero).", "system": "Big Sleep", "model_version": null, "developer": "DeepMind and Google Project Zero", "deployer": "Google (Threat Analysis Group / Big Sleep team)", "location": null, "domain": "Cybersecurity / vulnerability research", "segment": "Technology", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "SQLite fixed the flaw in 3.50.2 (release log entry on aggregate terms exceeding column count) before public exploitation was reported." }, { "group": "societal", "depth": null, "reason": "No source documents an outcome for users beyond the patch. The foiled-exploitation claim is Google's." } ], "ai_role": { "status": "assessed", "statement": "Per Google's spokesperson, human threat analysts supplied limited indicators and Big Sleep isolated the specific vulnerability. The CVE credit names a human finder “with assistance from Google Big Sleep”. Developer and the organization reporting the benefit are the same company. The Record and the SQLite release log are the independent sources. Neither confirms the threat-actor staging." }, "evidence": [ { "kind": "news report", "citation": "Jonathan Greig, The Record from Recorded Future News, 15 Jul 2025", "title": "Google says ‘Big Sleep’ AI tool found bug hackers planned to use", "url": "https://therecord.media/google-big-sleep-ai-tool-found-bug", "date": "2025-07-15", "written_by": "independent", "quote": "who leveraged Big Sleep to isolate the vulnerability the adversary was preparing to exploit in their operations" }, { "kind": "registry label", "citation": "CVE Program record CVE-2025-6965 (CNA: Google), published 15 Jul 2025", "title": "CVE-2025-6965", "url": "https://www.cve.org/CVERecord?id=CVE-2025-6965", "date": "2025-07-15", "written_by": "makers", "quote": "Vlad Stolyarov of Google's Threat Analysis Group, with assistance from Google Big Sleep" }, { "kind": "other", "citation": "SQLite release log, version 3.50.2, 28 Jun 2025", "title": "SQLite Release 3.50.2 On 2025-06-28", "url": "https://sqlite.org/releaselog/3_50_2.html", "date": "2025-06-28", "written_by": "independent", "quote": "Raise an error early if the number of aggregate terms in a query exceeds the maximum number of columns, to avoid downstream assertion faults." }, { "kind": "press release", "citation": "Kent Walker, Google blog, 15 Jul 2025", "title": "A summer of security: empowering cyber defenders with AI", "url": "https://blog.google/technology/safety-security/cybersecurity-updates-summer-2025/", "date": "2025-07-15", "written_by": "makers", "quote": "Google was able to actually predict that a vulnerability was imminently going to be used and we were able to cut it off beforehand." } ], "replication": { "produced_by": [ "Threat-intelligence artifacts narrowing the target without identifying the bug", "An LLM agent with code navigation, sandboxed execution and debugging tools pointed at a specific codebase", "A responsive upstream maintainer shipping a fix before disclosure" ], "must_hold": [ "Partial indicators of a staged exploit must exist and be shared with the agent's operators", "Target code must be small enough for the agent to reason over", "Coordinated disclosure before the actor's exploitation window" ], "echoes": [ { "date": "2024-11-04", "setting": "Big Sleep's first real-world find: a stack buffer underflow in a SQLite development branch, fixed in October 2024", "model_version": null, "outcome": "recurred", "source": "https://thehackernews.com/2024/11/googles-ai-tool-big-sleep-finds-zero.html" }, { "date": "2025-08-11", "setting": "Big Sleep team reports a curl vulnerability later published as CVE-2025–9086, confirmed by the curl maintainer", "model_version": null, "outcome": "recurred", "source": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/" } ] }, "paired_incident": null, "headline": "Big Sleep may have isolated SQLite zero-day CVE-2025–6965", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2025-08-11", "note": "Big Sleep went on to report a legitimate curl vulnerability on 11 August 2025, later published as CVE-2025-9086, which curl's maintainer confirmed.", "quote": "On August 11, 2025 there was a curl vulnerability reported against curl that would turn out legitimate and it would later be published as CVE-2025-9086. 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The claim rests on Google." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Big Sleep" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind and Google Project Zero" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Google's Big Sleep agent may have isolated SQLite CVE-2025–6965 from threat-intel artifacts; fixed in 3.50.2 before exploitation", "headline": "Big Sleep may have isolated SQLite zero-day CVE-2025–6965" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "47231bc70e9d37ed9a559b05a9b21f33873fdd7ae329ca0d2869200f920f1727" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The SQLite 3.50.2 release carrying the fix is dated 28 June 2025. 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The tool was used in three supplementary-planning-document consultations in winter 2024–25. A summary task reportedly fell from 18.5 officer hours to 16 AI minutes. The reported saving of over 60% does not directly reconcile with those times.", "category": "general benefit", "unexpected": false, "purpose": "Summarize planning-consultation representations and identify themes while retaining officer review.", "system": "Bespoke planning-consultation LLM with the Opus Consult platform", "model_version": null, "developer": "University of Liverpool (LLM); JDi Solutions (Opus Consult platform)", "deployer": "Greater Cambridge Shared Planning service", "location": "United Kingdom", "domain": "Planning and public consultation", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The completed summary task and soft launch in three consultations support time savings." }, { "group": "personal", "depth": 1, "reason": "Less summary-writing work frees officers for analysis and engagement. This is a task-time benefit." }, { "group": "societal", "depth": null, "reason": "Improved public participation is intended. Its extent is unknown." } ], "ai_role": { "status": "assessed", "statement": "The source attributes draft summaries and thematic analysis to the bespoke LLM. The reported time comparison concerns summarization, while officers continue to read every representation. The source does not establish improved consultation decisions." }, "evidence": [ { "kind": "report", "citation": "Council or project account published in the Local Government Association AI case-study bank. The account provides no independent outcome evaluation.", "title": "Greater Cambridge Shared Planning: AI-Driven Summarisation for Local Plan Consultations", "url": "https://www.local.gov.uk/case-studies/greater-cambridge-shared-planning-ai-driven-summarisation-local-plan-consultations", "date": "2025-07-17", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The model was developed with 15 years of consultation material, including over 55,000 representations and planning-specific terminology.", "It was soft-launched in three supplementary-planning-document consultations in winter 2024–25." ], "must_hold": [ "The reported workflow retains officer reading of every representation.", "The source does not establish which data or model conditions are necessary to reproduce the reported saving." ], "echoes": [] }, "paired_incident": null, "headline": "Greater Cambridge reports faster consultation summaries", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/greater-cambridge-shared-planning-ai-driven-summarisation-local-plan-consultations", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. 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This is a task-time benefit." }, { "group": "societal", "reason": "Improved public participation is intended. Its extent is unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. 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The tool was used in three supplementary-planning-document consultations in winter 2024–25. A summary task reportedly fell from 18.5 officer hours to 16 AI minutes. 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This is a task-time benefit." }, { "group": "societal", "reason": "Improved public participation is intended. Its extent is unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "mixed" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Summarize planning-consultation representations and identify themes while retaining officer review." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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The tool was used in three supplementary-planning-document consultations in winter 2024–25. A summary task reportedly fell from 18.5 officer hours to 16 AI minutes. The reported saving of over 60% does not directly reconcile with those times.", "replication": { "produced_by": [ "The model was developed with 15 years of consultation material, including over 55,000 representations and planning-specific terminology.", "It was soft-launched in three supplementary-planning-document consultations in winter 2024–25." ], "must_hold": [ "The reported workflow retains officer reading of every representation.", "The source does not establish which data or model conditions are necessary to reproduce the reported saving." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0142", "title": "ChatGPT points to a blood pressure medication behind an 18-month cough that doctors had not explained; a doctor confirms it and changes the prescription, and X user Shreya's mother may be healing", "summary": "ChatGPT flagged a BP drug side effect behind an 18-month cough; a doctor confirmed it and changed the drug; daughter reports mother healing.", "date_observed": "2025-07-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 23 July 2025 an X user posting as Shreya.tsx (@Life_of_coder, profile location “india”) wrote about her mother. Her mother had had a nonstop cough for 1.5 years. That was despite top doctors, big hospitals in and outside their city, homeopathy, ayurveda and allopathy. Internal bleeding had begun. Doctors had warned the condition could be fatal within six months. She described everything to OpenAI's ChatGPT, which listed possible causes including blood pressure medication. It asked whether the prescription contained a specific ingredient. It did. A doctor, told of this, confirmed it at once and changed the medication. Her mother was “finally healing”. Four Indian outlets reported the post on 24 July 2025. It has since been deleted.", "category": "benefit created", "unexpected": true, "purpose": "ChatGPT is OpenAI's general-purpose conversational assistant, not a diagnostic or drug-safety tool. Surfacing a medication side effect as the likely cause of a chronic cough was outside what it was built for. So the benefit is marked unexpected.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": null, "location": null, "domain": "Healthcare (diagnosis; medication side effect)", "segment": "Consumer use by a patient's adult daughter", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-07-24-aae1" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "One identifiable patient, the poster's mother, had an 18-month cough with internal bleeding that doctors had warned could become fatal. After the medication change her daughter reported her “finally healing”. Material for one person. It rates below life-changing because the recovery was in progress. Nothing beyond the daughter's post documents the diagnosis or the outcome." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT generated the hypothesis. Among several possible causes it listed blood pressure medication. When told the mother was on such medication, it asked whether the prescription contained a specific ingredient, which it did. The confirmation and the prescription change were made by a doctor (“He confirmed it instantly and changed the meds”). NDTV, Mint, Mashable India and the Financial Express quote a commenter. They say cough is a known side effect of BP medicine that doctors “should've checked”. That frames the contribution as surfacing a documented side effect rather than a novel diagnosis. No clinician comments on the chatbot's role. The whole sequence rests on the daughter's account." }, "evidence": [ { "kind": "other", "citation": "Shreya.tsx [@Life_of_coder] (2025). ChatGPT saved my mom. Post on X, 23 July 2025, 12:26 UTC, since deleted; X API v2 response captured by the Internet Archive at 2025-07-23 12:26:51 UTC.", "title": "ChatGPT saved my mom (post on X by @Life_of_coder; archived API capture with full text and author profile)", "url": "http://web.archive.org/web/20250723122651/https://twitter.com/Life_of_coder/status/1947996833214877981", "date": "2025-07-23", "written_by": "beneficiary", "quote": "We told a doctor. He confirmed it instantly and changed the meds. Now she’s finally healing." }, { "kind": "news report", "citation": "Singh R. / NDTV (2025). \"ChatGPT Saved My Mom\": Woman Claims AI Diagnosed Her Mother's Illness After Doctors Failed. NDTV Offbeat, 24 July 2025.", "title": "\"ChatGPT Saved My Mom\": Woman Claims AI Diagnosed Her Mother's Illness After Doctors Failed", "url": "https://www.ndtv.com/offbeat/chatgpt-saved-my-mom-woman-claims-ai-diagnosed-her-mothers-illness-after-doctors-failed-8940203", "date": "2025-07-24", "written_by": "independent", "quote": "The chatbot provided a list of potential causes, including one that surprised her -- a possible side effect of her mother's blood pressure medication." }, { "kind": "news report", "citation": "Thakur A. / Mint (2025). 'ChatGPT saved my mom': Woman reveals how AI diagnosed her mother's mysterious illness after 1.5 year struggle. Livemint, Trends.", "title": "'ChatGPT saved my mom': Woman reveals how AI diagnosed her mother's mysterious illness after 1.5 year struggle", "url": "https://www.livemint.com/news/trends/chatgpt-saved-my-mom-woman-reveals-how-ai-diagnosed-her-mothers-mysterious-illness-after-1-5-year-struggle-11753346497477.html", "date": "2025-07-24", "written_by": "independent", "quote": "Armed with this new insight, Shreya consulted their doctor, who immediately confirmed the link and changed the medication." }, { "kind": "news report", "citation": "ET Online / The Economic Times (2025). Top doctors failed for 18 months, then AI diagnosed mystery illness: Woman shares how ChatGPT 'healed' her mom. ET Panache.", "title": "Top doctors failed for 18 months, then AI diagnosed mystery illness: Woman shares how ChatGPT 'healed' her mom", "url": "https://m.economictimes.com/magazines/panache/top-doctors-failed-for-18-months-then-ai-diagnosed-mystery-illness-woman-shares-how-chatgpt-healed-her-mom/articleshow/122885926.cms", "date": "2025-07-24", "written_by": "independent", "quote": "This time, the doctor agreed with the AI’s suggestion and immediately changed her mother’s prescription." }, { "kind": "news report", "citation": "TOI Trending Desk / The Times of India (2025). 'ChatGPT saved my mom': Woman shares how AI solved 18-month medical mystery that doctors missed. ETimes Trending.", "title": "'ChatGPT saved my mom': Woman shares how AI solved 18-month medical mystery that doctors missed", "url": "https://timesofindia.indiatimes.com/etimes/trending/chatgpt-saved-my-mom-woman-shares-how-ai-solved-18-month-medical-mystery-that-doctors-missed/articleshow/122881542.cms", "date": "2025-07-24", "written_by": "independent", "quote": "To validate the suspicion, ChatGPT asked a specific question: “Is she on BP medication with this ingredient?”" }, { "kind": "news report", "citation": "Singh P. / Mashable India (2025). Woman Claims ChatGPT Diagnosed Mom's Illness After Doctors Failed for Over a Year. in.mashable.com, Tech.", "title": "Woman Claims ChatGPT Diagnosed Mom's Illness After Doctors Failed for Over a Year", "url": "https://in.mashable.com/tech/97585/woman-claims-chatgpt-diagnosed-moms-illness-after-doctors-failed-for-over-a-year", "date": "2025-07-25", "written_by": "independent", "quote": "When Shreya confirmed her mother was on BP meds, ChatGPT asked about a specific ingredient." }, { "kind": "news report", "citation": "Tech Desk / The Financial Express (2025). 'ChatGPT saved my mom': Woman reveals how AI diagnosed her mother's mysterious illness after 1.5 year struggle. financialexpress.com, Life / Technology.", "title": "'ChatGPT saved my mom': Woman reveals how AI diagnosed her mother's mysterious illness after 1.5 year struggle", "url": "https://www.financialexpress.com/life/technology-chatgpt-saved-my-mom-woman-reveals-how-ai-diagnosed-her-mother-s-mysterious-illness-after-1-5-year-struggle-3926225", "date": "2025-07-25", "written_by": "independent", "quote": "After discussing it with a physician and switching the prescribed medication, her mother's condition started to improve noticeably." }, { "kind": "news report", "citation": "FPJ Web Desk / The Free Press Journal (2025). 'ChatGPT Saved My Mom': Woman Says AI Uncovered Correct Cause Of Year-Long Cough, Doctors Had Deemed It 'Fatal'. freepressjournal.in, Tech.", "title": "'ChatGPT Saved My Mom': Woman Says AI Uncovered Correct Cause Of Year-Long Cough, Doctors Had Deemed It 'Fatal'", "url": "https://www.freepressjournal.in/tech/chatgpt-saved-my-mom-woman-says-ai-uncovered-correct-cause-of-year-long-cough-doctors-had-deemed-it-fatal", "date": "2025-07-28", "written_by": "independent", "quote": "Many praised the responsible follow-up with a medical professional, while others noted the growing usefulness of AI as a supplemental tool in health research." }, { "kind": "other", "citation": "X Corp. (2026). Syndication tweet-result for post 1947996833214877981, retrieved 20 October 2026: deletion tombstone.", "title": "X syndication response for post 1947996833214877981 (deletion tombstone)", "url": "https://cdn.syndication.twimg.com/tweet-result?id=1947996833214877981&token=4pzt91vxhvkzilx", "date": "2026-10-20", "written_by": "independent", "quote": "This Post was deleted by the Post author. Learn more" } ], "replication": { "produced_by": [ "A family member with an 18-month symptom history (nonstop cough, then internal bleeding). She described it to ChatGPT after top doctors, big hospitals, homeopathy, ayurveda and allopathy had not helped", "ChatGPT listed several possible causes, including blood pressure medication. Told the mother was on BP medication, it asked whether it contained a specific ingredient, which it did", "A doctor who, told of the suggestion, confirmed it at once and changed the prescription" ], "must_hold": [ "The chatbot's suggestion is taken to a prescribing doctor who confirms it before any medication is changed. The post credits the doctor with both the confirmation and the change", "The cough must actually be the drug's side effect. The post names neither the drug nor the “ingredient”, so the mechanism cannot be checked against the drug's label", "The account rests on one since-deleted post by the patient's daughter, relayed by independent outlets. No clinician, hospital or record corroborates it" ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT traces an 18-month cough to a BP drug; doctor confirms", "metric": null, "comparator": { "against": "a year and a half of top doctors, big hospitals and homeopathic, ayurvedic and allopathic treatment", "before": "My mom had a nonstop cough for 1.5 years. We saw top doctors, visited big hospitals in & out of the city, tried homeopathy, ayurveda, allopathy nothing helped. It got worse: internal bleeding started.", "after": "We told a doctor. He confirmed it instantly and changed the meds. Now she’s finally healing.", "basis": "assumed", "quote": "My mom had a nonstop cough for 1.5 years. We saw top doctors, visited big hospitals in & out of the city, tried homeopathy, ayurveda, allopathy nothing helped. It got worse: internal bleeding started.", "url": "https://in.mashable.com/tech/97585/woman-claims-chatgpt-diagnosed-moms-illness-after-doctors-failed-for-over-a-year" }, "later": { "status": "unknown", "date": null, "note": "No follow-up on the mother was found; the only later fact is that the author deleted the post at an unknown date.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-07-24-aae1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports, one other independent source and the beneficiary's other. 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Her mother had had a nonstop cough for 1.5 years. That was despite top doctors, big hospitals in and outside their city, homeopathy, ayurveda and allopathy. Internal bleeding had begun. Doctors had warned the condition could be fatal within six months. She described everything to OpenAI's ChatGPT, which listed possible causes including blood pressure medication. It asked whether the prescription contained a specific ingredient. It did. A doctor, told of this, confirmed it at once and changed the medication. Her mother was “finally healing”. Four Indian outlets reported the post on 24 July 2025. It has since been deleted.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "One identifiable patient, the poster's mother, had an 18-month cough with internal bleeding that doctors had warned could become fatal. After the medication change her daughter reported her “finally healing”. Material for one person. It rates below life-changing because the recovery was in progress. Nothing beyond the daughter's post documents the diagnosis or the outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "ChatGPT is OpenAI's general-purpose conversational assistant, not a diagnostic or drug-safety tool. 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No clinician, hospital or record corroborates it" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0104", "title": "LAARMA AI roadside alerts cut cassowary road deaths in Queensland trial", "summary": "TMR three-month trial at Kuranda: 97% cassowary detection, drivers slowed 6.6 km/h, fatal crashes down 31% (reported 30 July 2025).", "date_observed": "2025-07-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Large Animal Activated Roadside Monitoring and Alert System (LAARMA) was developed by the University of Sydney's Australian Centre for Robotics and QUT's CARRS-Q. They worked with the Queensland Department of Transport and Main Roads (TMR) under an iMOVE project. It uses a machine-learning pipeline to detect large animals up to 200 m away and triggers roadside variable message signs. The ABC reported on 30 July 2025 that TMR had used the AI for three months at a busy cassowary crossing. That is on the Kennedy Highway at Kuranda, Far North Queensland. Trial dates are not given. The consortium's iMOVE project page instead describes a five-month field trial: three months of data collection, then two months of on-road trialling. TMR told the ABC that the system identified cassowaries with 97 percent accuracy. It said drivers slowed by an average of 6.6 km/h at the flashing sign and fatal crashes fell 31 percent during the trial. The iMOVE page reports speed reductions averaging 6.30 km/h and 5.06 km/h at two test sites and gives no collision figure. About two dozen cassowaries were killed on Queensland roads the previous year.", "category": "general benefit", "unexpected": false, "purpose": "Detect large animals near the road in real time and warn drivers via variable message signs to reduce animal-vehicle collisions.", "system": "Large Animal Activated Roadside Monitoring and Alert System (LAARMA)", "model_version": null, "developer": "University of Sydney Australian Centre for Robotics and QUT CARRS-Q", "deployer": "Queensland Department of Transport and Main Roads", "location": "Kuranda, Australia", "domain": "Conservation and biodiversity", "segment": "Wildlife-vehicle collision prevention", "benefit_type": "Increased Product Safety", "taxonomy_note": "The crashes cut are vehicle strikes on an endangered bird, so the gain is shared with conservation.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Trial-level aggregate (speed reduction, 31 percent fewer fatal crashes) with no discrete attributable event." }, { "group": "organizational", "depth": null, "reason": "Aggregate program result reported by the operating agency." }, { "group": "societal", "depth": null, "reason": "Aggregate result over a three-month trial. Baseline and statistical detail not published." } ], "ai_role": { "status": "assessed", "statement": "Machine-learning detection of cassowaries activated the warning signs. TMR attributes the speed reduction and the 31 percent fall in fatal crashes to the system. But the figures are trial aggregates without a peer-reviewed analysis. The 31 percent figure is reported only by the ABC citing TMR. The consortium's project page reports detection and speed results without a collision figure." }, "evidence": [ { "kind": "news report", "citation": "ABC News (2025). Artificial intelligence used to reduce cassowary road deaths in Queensland.", "title": "Artificial intelligence used to reduce cassowary road deaths in Queensland", "url": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "date": "2025-07-30", "written_by": "independent", "quote": "The technology was 97 per cent accurate in identifying the bird, which led to a 31 per cent decrease in fatal crashes, the department said." }, { "kind": "press release", "citation": "iMOVE Australia CRC (n.d.). Large Australian animals and cars: Safety for all. Project page with final reports.", "title": "Large Australian animals and cars: Safety for all", "url": "https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "date": "2025-07-28", "written_by": "makers", "quote": "Partners with iMOVE on this research were the Department of Transport and Main Roads (Queensland), the University of Sydney's Australian Centre for Robotics, and the Queensland University of Technology's CARRS-Q." }, { "kind": "news report", "citation": "Tech Xplore (2025). Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions.", "title": "Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions", "url": "https://techxplore.com/news/2025-08-world-ai-roadside-technology-animalvehicle.html", "date": "2025-08-06", "written_by": "independent", "quote": "the system was correctly detecting animals 78.5% of the time within 100 meters" } ], "replication": { "produced_by": [ "A known animal crossing hotspot with high strike rates", "Self-training detection pipeline that improved over the trial", "Variable message signs drivers can see in time to slow" ], "must_hold": [ "Detection accuracy on the target species", "Driver compliance with flashing warnings", "Permanent funding, which TMR said it was still pursuing" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured", "model_version": null, "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1678", "title": "Avride Autonomous Vehicle Reportedly Struck and Killed Nesting Duck Near Mueller Lake Park in Austin, Texas", "url": "https://incidentdatabase.ai/cite/1678", "severity": null, "group": "societal", "basis": "Autonomous vehicle's perception system did not detect or slow for a nesting duck and killed it; LAARMA exists to detect cassowaries at roadsides and slow drivers." }, "headline": "LAARMA alerts cut fatal crashes 31% in Kuranda cassowary trial", "metric": "fatal crashes fell 31 percent during the trial", "comparator": { "against": "fatal cassowary vehicle strikes at the Kuranda crossing before the three-month AI trial, per the department (a speed-limit cut from 80 to 60 km/h for cyclone repair works coincided)", "before": "not stated", "after": "31 per cent decrease in fatal crashes", "basis": "measured", "quote": "The technology was 97 per cent accurate in identifying the bird, which led to a 31 per cent decrease in fatal crashes, the department said.", "url": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446" }, "later": { "status": "unknown", "date": null, "note": "The ABC reported that the equipment would be removed from the site after the trial while funding for a rollout was discussed with research partners; no later deployment was found.", "quote": null, "url": null }, "value": null, "developer_country": "Australia", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1678 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1678", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed the three-month trial length and 6.6 km/h speed reduction to TMR via the ABC and added the iMOVE project page's five-month field trial (two months on-road) with 6.30 and 5.06 km/h reductions at two sites, confined the 31 percent fatal-crash figure to the ABC because the project page gives no collision figure, dated the iMOVE page 28 July 2025, and replaced the ABC citation's URL slug and share title with the displayed headline.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446; https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Centre_for_Field_Robotics; https://en.wikipedia.org/wiki/Department_of_Transport_and_Main_Roads", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0104", "catalog_version": "1.0.0", "source_fingerprint": "09beff2764d480679117c8eb1f7e946c2a2ae3eb7a3fa2684a5b98dc6d56cf62", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0104-source-0001", "AIBD-0104-source-0002", "AIBD-0104-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Sydney Australian Centre for Robotics and QUT CARRS-Q", "deployer": "Queensland Department of Transport and Main Roads" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Machine-learning detection of cassowaries activated the warning signs. TMR attributes the speed reduction and the 31 percent fall in fatal crashes to the system. But the figures are trial aggregates without a peer-reviewed analysis. The 31 percent figure is reported only by the ABC citing TMR. The consortium's project page reports detection and speed results without a collision figure." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Machine-learning detection of cassowaries activated the warning signs. TMR attributes the speed reduction and the 31 percent fall in fatal crashes to the system. But the figures are trial aggregates without a peer-reviewed analysis. 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"outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Large Animal Activated Roadside Monitoring and Alert System (LAARMA) was developed by the University of Sydney's Australian Centre for Robotics and QUT's CARRS-Q. They worked with the Queensland Department of Transport and Main Roads (TMR) under an iMOVE project. It uses a machine-learning pipeline to detect large animals up to 200 m away and triggers roadside variable message signs. The ABC reported on 30 July 2025 that TMR had used the AI for three months at a busy cassowary crossing. That is on the Kennedy Highway at Kuranda, Far North Queensland. Trial dates are not given. The consortium's iMOVE project page instead describes a five-month field trial: three months of data collection, then two months of on-road trialling. TMR told the ABC that the system identified cassowaries with 97 percent accuracy. It said drivers slowed by an average of 6.6 km/h at the flashing sign and fatal crashes fell 31 percent during the trial. The iMOVE page reports speed reductions averaging 6.30 km/h and 5.06 km/h at two test sites and gives no collision figure. About two dozen cassowaries were killed on Queensland roads the previous year.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Trial-level aggregate (speed reduction, 31 percent fewer fatal crashes) with no discrete attributable event." }, { "group": "organizational", "reason": "Aggregate program result reported by the operating agency." }, { "group": "societal", "reason": "Aggregate result over a three-month trial. Baseline and statistical detail not published." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect large animals near the road in real time and warn drivers via variable message signs to reduce animal-vehicle collisions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Kuranda, Australia", "developer_country": "Australia", "deployer_country": "Australia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect large animals near the road in real time and warn drivers via variable message signs to reduce animal-vehicle collisions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-30", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1678 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1678", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed the three-month trial length and 6.6 km/h speed reduction to TMR via the ABC and added the iMOVE project page's five-month field trial (two months on-road) with 6.30 and 5.06 km/h reductions at two sites, confined the 31 percent fatal-crash figure to the ABC because the project page gives no collision figure, dated the iMOVE page 28 July 2025, and replaced the ABC citation's URL slug and share title with the displayed headline.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446; https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Centre_for_Field_Robotics; https://en.wikipedia.org/wiki/Department_of_Transport_and_Main_Roads", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A known animal crossing hotspot with high strike rates", "Self-training detection pipeline that improved over the trial", "Variable message signs drivers can see in time to slow" ], "must_hold": [ "Detection accuracy on the target species", "Driver compliance with flashing warnings", "Permanent funding, which TMR said it was still pursuing" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured", "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A known animal crossing hotspot with high strike rates", "Self-training detection pipeline that improved over the trial", "Variable message signs drivers can see in time to slow" ], "must_hold": [ "Detection accuracy on the target species", "Driver compliance with flashing warnings", "Permanent funding, which TMR said it was still pursuing" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured", "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1678 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1678", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Attributed the three-month trial length and 6.6 km/h speed reduction to TMR via the ABC and added the iMOVE project page's five-month field trial (two months on-road) with 6.30 and 5.06 km/h reductions at two sites, confined the 31 percent fatal-crash figure to the ABC because the project page gives no collision figure, dated the iMOVE page 28 July 2025, and replaced the ABC citation's URL slug and share title with the displayed headline.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446; https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Centre_for_Field_Robotics; https://en.wikipedia.org/wiki/Department_of_Transport_and_Main_Roads", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Conservation and biodiversity", "segment": "Wildlife-vehicle collision prevention" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ABC News (2025). Artificial intelligence used to reduce cassowary road deaths in Queensland.", "title": "Artificial intelligence used to reduce cassowary road deaths in Queensland", "url": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "date": "2025-07-30", "written_by": "independent", "quote": "The technology was 97 per cent accurate in identifying the bird, which led to a 31 per cent decrease in fatal crashes, the department said." }, { "kind": "press release", "citation": "iMOVE Australia CRC (n.d.). Large Australian animals and cars: Safety for all. Project page with final reports.", "title": "Large Australian animals and cars: Safety for all", "url": "https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "date": "2025-07-28", "written_by": "makers", "quote": "Partners with iMOVE on this research were the Department of Transport and Main Roads (Queensland), the University of Sydney's Australian Centre for Robotics, and the Queensland University of Technology's CARRS-Q." }, { "kind": "news report", "citation": "Tech Xplore (2025). Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions.", "title": "Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions", "url": "https://techxplore.com/news/2025-08-world-ai-roadside-technology-animalvehicle.html", "date": "2025-08-06", "written_by": "independent", "quote": "the system was correctly detecting animals 78.5% of the time within 100 meters" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0104-source-0001", "AIBD-0104-source-0002", "AIBD-0104-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ABC News (2025). Artificial intelligence used to reduce cassowary road deaths in Queensland.", "title": "Artificial intelligence used to reduce cassowary road deaths in Queensland", "url": "https://www.abc.net.au/news/2025-07-30/ai-saves-cassowary-lives-reducing-vehicle-strikes-far-north-qld/105589446", "date": "2025-07-30", "written_by": "independent", "quote": "The technology was 97 per cent accurate in identifying the bird, which led to a 31 per cent decrease in fatal crashes, the department said." }, { "kind": "press release", "citation": "iMOVE Australia CRC (n.d.). Large Australian animals and cars: Safety for all. Project page with final reports.", "title": "Large Australian animals and cars: Safety for all", "url": "https://imoveaustralia.com/project/large-australian-animals-and-cars-safety-for-all/", "date": "2025-07-28", "written_by": "makers", "quote": "Partners with iMOVE on this research were the Department of Transport and Main Roads (Queensland), the University of Sydney's Australian Centre for Robotics, and the Queensland University of Technology's CARRS-Q." }, { "kind": "news report", "citation": "Tech Xplore (2025). Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions.", "title": "Researchers develop world's first AI roadside technology to prevent animal–vehicle collisions", "url": "https://techxplore.com/news/2025-08-world-ai-roadside-technology-animalvehicle.html", "date": "2025-08-06", "written_by": "independent", "quote": "the system was correctly detecting animals 78.5% of the time within 100 meters" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "TMR three-month trial at Kuranda: 97% cassowary detection, drivers slowed 6.6 km/h, fatal crashes down 31% (reported 30 July 2025).", "account": "The Large Animal Activated Roadside Monitoring and Alert System (LAARMA) was developed by the University of Sydney's Australian Centre for Robotics and QUT's CARRS-Q. They worked with the Queensland Department of Transport and Main Roads (TMR) under an iMOVE project. It uses a machine-learning pipeline to detect large animals up to 200 m away and triggers roadside variable message signs. The ABC reported on 30 July 2025 that TMR had used the AI for three months at a busy cassowary crossing. That is on the Kennedy Highway at Kuranda, Far North Queensland. Trial dates are not given. The consortium's iMOVE project page instead describes a five-month field trial: three months of data collection, then two months of on-road trialling. TMR told the ABC that the system identified cassowaries with 97 percent accuracy. It said drivers slowed by an average of 6.6 km/h at the flashing sign and fatal crashes fell 31 percent during the trial. The iMOVE page reports speed reductions averaging 6.30 km/h and 5.06 km/h at two test sites and gives no collision figure. About two dozen cassowaries were killed on Queensland roads the previous year." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Large Animal Activated Roadside Monitoring and Alert System (LAARMA)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Sydney Australian Centre for Robotics and QUT CARRS-Q" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "LAARMA AI roadside alerts cut cassowary road deaths in Queensland trial", "headline": "LAARMA alerts cut fatal crashes 31% in Kuranda cassowary trial" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "09beff2764d480679117c8eb1f7e946c2a2ae3eb7a3fa2684a5b98dc6d56cf62" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Large Animal Activated Roadside Monitoring and Alert System (LAARMA) was developed by the University of Sydney's Australian Centre for Robotics and QUT's CARRS-Q. They worked with the Queensland Department of Transport and Main Roads (TMR) under an iMOVE project. It uses a machine-learning pipeline to detect large animals up to 200 m away and triggers roadside variable message signs. The ABC reported on 30 July 2025 that TMR had used the AI for three months at a busy cassowary crossing. That is on the Kennedy Highway at Kuranda, Far North Queensland. Trial dates are not given. The consortium's iMOVE project page instead describes a five-month field trial: three months of data collection, then two months of on-road trialling. TMR told the ABC that the system identified cassowaries with 97 percent accuracy. It said drivers slowed by an average of 6.6 km/h at the flashing sign and fatal crashes fell 31 percent during the trial. The iMOVE page reports speed reductions averaging 6.30 km/h and 5.06 km/h at two test sites and gives no collision figure. About two dozen cassowaries were killed on Queensland roads the previous year.", "replication": { "produced_by": [ "A known animal crossing hotspot with high strike rates", "Self-training detection pipeline that improved over the trial", "Variable message signs drivers can see in time to slow" ], "must_hold": [ "Detection accuracy on the target species", "Driver compliance with flashing warnings", "Permanent funding, which TMR said it was still pursuing" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured", "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0033", "title": "CNSAS Piemonte drone imagery analyzed with AI software, likely TEXSAR's ADIAT, locates missing surgeon Nicola Ivaldo on Monviso after ten months", "summary": "AI analysis of 2,600 drone frames flagged a red helmet in the Perotti couloir at 3,150 m; Ivaldo's body was recovered by 31 July 2025.", "date_observed": "2025-07-31", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Nicola Ivaldo was a surgeon aged 64 according to the Club Alpino Italiano's Lo Scarpone (another report says 66). He disappeared on 14 September 2024 per CAI during a solo outing on Monviso in Piedmont, Italy. Quadricottero dates his departure, when he parked his car at the Pontechianale dam, to 15 September. Searches over ten months found nothing. On 29 July 2025 the Soccorso Alpino e Speleologico Piemontese (CNSAS) flew two drones close to the north face. They collected about 2,600 high-resolution frames over 183 hectares in five hours. The frames were analyzed pixel by pixel with AI image-analysis software. Developer TEXSAR identifies it as the open-source Automated Drone Image Analysis Tool (ADIAT). The frames yielded a tiny red anomaly in the Perotti couloir: his helmet. His body was located at about 3,150 m and recovered by 31 July 2025. That date comes from TEXSAR's page (which cites Wired). It is consistent with bluewin's report of under 72 hours from the 29 July flight to the recovery. CAI gives only July 2025 and Quadricottero no date.", "category": "benefit created", "unexpected": false, "purpose": "ADIAT was built to scan drone photographs and flag color and shape anomalies for search-and-rescue teams. Locating the missing man's helmet was that intended function.", "system": "AI drone-image analysis software used by CNSAS Piemonte (identified as ADIAT by its developer, TEXSAR; CAI and CNSAS sources do not name it)", "model_version": null, "developer": "TEXSAR (Texas Search and Rescue) volunteers, per the developer's own account", "deployer": "Soccorso Alpino e Speleologico Piemontese (CNSAS Piemonte), Turin station drone team", "location": "Monviso north face, Perotti couloir (province of Cuneo), Italy", "domain": "Mountain search and rescue", "segment": "Recovery of a missing person in high-alpine terrain", "benefit_type": "Reduced Task Time", "taxonomy_note": "The time cut is the rescuers' frame review; the family's good, recovery of remains, has no type.", "registry_ids": { "oecd_aim": "2026-01-10-f4af" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Ivaldo's family obtained recovery of his body and certainty about his fate after ten months of searching. A material benefit, not life-saving, since he had died in September 2024." }, { "group": "organizational", "depth": 2, "reason": "CNSAS Piemonte ended a search that had involved ground teams, Guardia di Finanza and fire-service helicopters for ten months. Manual analysis of the drone photos would have taken weeks (CAI) to months (CNSAS, per bluewin)." } ], "ai_role": { "status": "assessed", "statement": "The AI flagged a few red pixels, the helmet, a detail CAI describes as invisible to the naked eye. Ten months of helicopters, specialist teams and advanced technology (Quadricottero) had not resolved the search. Drone pilot Saverio Isola is quoted that it was the AI software that identified the differently colored pixels. CAI/CNSAS sources do not name the software. The ADIAT attribution comes from the developer TEXSAR's own page. So the tool identity rests on a vendor-authored source." }, "evidence": [ { "kind": "press release", "citation": "Lo Scarpone, Club Alpino Italiano (2026). Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino. 18 January 2026 (CAI is the parent body of CNSAS).", "title": "Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino", "url": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "date": "2026-01-18", "written_by": "deployer", "quote": "Due droni sono stati impiegati per voli ravvicinati alle pareti del Monviso, e in 5 ore sono stati raccolti circa 2.600 fotogrammi ad alta risoluzione." }, { "kind": "news report", "citation": "Scarato D (2025). Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso. Quadricottero News, 1 August 2025 (photo credited to Soccorso Alpino e Speleologico Piemonte - CNSAS).", "title": "Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso", "url": "https://www.quadricottero.com/2025/08/droni-e-ia-trovano-il-corpo-del-medico.html", "date": "2025-08-01", "written_by": "independent", "quote": "Il ritrovamento, avvenuto a circa 3150 metri di quota sulla parete nord della montagna, nel canale Perotti, è stato possibile grazie a un impiego mirato di droni professionali" }, { "kind": "news report", "citation": "bluewin.ch (2025). Sulle Alpi Italiane: Ecco com'è stato possibile localizzare un escursionista scomparso da un anno. 10 August 2025 (updated 12 August 2025).", "title": "Ecco com'è stato possibile localizzare un escursionista scomparso da un anno", "url": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148", "date": "2025-08-10", "written_by": "independent", "quote": "Sono stati questi pixel a cambiare tutto" }, { "kind": "press release", "citation": "Texas Search and Rescue (2025). ADIAT Helps Italian SAR Team. TEXSAR website, 15 August 2025 (developer of ADIAT).", "title": "ADIAT Helps Italian SAR Team", "url": "https://www.texsar.org/2025/08/15/adiat-helps-italian-sar-team/", "date": "2025-08-15", "written_by": "makers", "quote": "It was the AI software that identified some pixels of a different color in the images taken on Tuesday." }, { "kind": "news report", "citation": "Simičević, V. (2026). A red pixel in the snow: How AI solved the mystery of a missing mountaineer. BBC Future.", "title": "A red pixel in the snow: How AI solved the mystery of a missing mountaineer", "url": "https://www.bbc.com/future/article/20260108-how-ai-solved-the-mystery-of-a-missing-mountaineer", "date": "2026-01-09", "written_by": "independent", "quote": "Three days after the search resumed, however, the body of the missing doctor was found at one of the sites identified by the AI, lying in a gully" }, { "kind": "news report", "citation": "La Stampa (2025). Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso. La Stampa, Cuneo.", "title": "Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso", "url": "https://www.lastampa.it/cuneo/2025/07/31/news/trovato_il_corpo_del_medico_di_loano_disperso_dal_15_settembre_sul_monviso-15253571/", "date": "2025-07-31", "written_by": "independent", "quote": "realizzati 2600 fotogrammi che sono stati caricati su un apposito software, in dotazione al Soccorso alpino e speleologico, che ha elaborato i dati indicando tre possibili target da verificare" }, { "kind": "news report", "citation": "Abbà, M. (2025). Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Wired Italia.", "title": "Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Che ha riconosciuto il caschetto tra migliaia di immagini", "url": "https://www.wired.it/article/escursionista-disperso-monviso-cadavere-drone-intelligenza-artificiale-soccorso-alpino/", "date": "2025-07-31", "written_by": "independent", "quote": "la salma del medico ligure di 64 anni Nicola Ivaldo è stata trovata nella mattinata di giovedì 31 luglio, a distanza di oltre dieci mesi dalla sua scomparsa" }, { "kind": "news report", "citation": "Abo Abia, M. (2025). Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024. RaiNews, TGR Piemonte.", "title": "Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024", "url": "https://www.rainews.it/tgr/piemonte/articoli/2025/07/ritrovato-il-corpo-di-nicola-ivaldo-disperso-sul-monviso-dal-settembre-2024-d14c11b3-3753-454e-98b4-d8919b1648bc.html", "date": "2025-07-31", "written_by": "independent", "quote": "Il programma, analizzando video e foto, ha individuato tre aree sensibili: zone con dettagli non naturali e incompatibili con l'ambiente circostante" }, { "kind": "press release", "citation": "Lo Scarpone (2025). Monviso, ritrovato il corpo del medico disperso da settembre 2024. Club Alpino Italiano.", "title": "Monviso, ritrovato il corpo del medico disperso da settembre 2024", "url": "https://www.loscarpone.cai.it/dettaglio/monviso-ritrovato-il-corpo-del-medico-disperso-da-settembre-2024/", "date": "2025-07-31", "written_by": "deployer", "quote": "raccolto circa 2600 fotogrammi ad alta risoluzione, poi analizzati tramite un software in dotazione al Soccorso Alpino che ha indicato tre possibili punti di interesse tramite analisi pixel-per-pixel" }, { "kind": "news report", "citation": "Ciprian, V. (2026). Quel punto rosso era il casco dell'alpinista disperso da mesi. L'AltraMontagna, il Dolomiti.", "title": "Quel punto rosso era il casco dell'alpinista disperso da mesi: \"Senza l'anomalia segnalata dall'intelligenza artificiale in una delle 2600 foto dal drone, probabilmente non sarebbe mai stato trovato\"", "url": "https://www.ildolomiti.it/altra-montagna/storie/2026/quel-punto-rosso-era-il-casco-dellalpinista-disperso-da-mesi-senza-lanomalia-segnalata-dallintelligenza-artificiale-in-una-delle-2600-foto-dal-drone-probabilmente-non-sarebbe-mai-stato-trovato", "date": "2026-01-13", "written_by": "independent", "quote": "il drone, penetrando nel canale Perotti, ha individuato i resti di un essere umano nel canale più a destra dei tre che solcano la parete nord" }, { "kind": "news report", "citation": "Rullo, F. (2025). Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna. Corriere della Sera, Torino.", "title": "Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna", "url": "https://torino.corriere.it/notizie/piemonte/25_luglio_31/monviso-ritrovato-dopo-un-anno-e-solo-grazie-ai-droni-il-corpo-di-nicola-ivaldo-medico-savonese-scomparso-in-montagna-c943f224-5e04-4320-856b-a3d4533caxlk.shtml", "date": "2025-07-31", "written_by": "independent", "quote": "ritrovati grazie all'uso di droni e a un apposito software in dotazione al soccorso alpino: erano in un canale a 3150 metri di quota" }, { "kind": "news report", "citation": "Annapurna, K. (2025). AI Solves the Mystery of Missing Italian Climber. ExplorersWeb.", "title": "AI Solves the Mystery of Missing Italian Climber", "url": "https://explorersweb.com/ai-solves-the-mystery-of-missing-italian-climber/", "date": "2025-08-07", "written_by": "independent", "quote": "an AI software analyzed these many images in a single afternoon, singling out a cluster of red pixels that turned out to be Ivaldo's helmet" }, { "kind": "news report", "citation": "Malfatti, M. (2025). Anche l'intelligenza artificiale al servizio del Soccorso Alpino. Montagna.TV.", "title": "Anche l'intelligenza artificiale al servizio del Soccorso Alpino", "url": "https://www.montagna.tv/262960/anche-lintelligenza-artificiale-al-servizio-del-soccorso-alpino/", "date": "2025-10-06", "written_by": "independent", "quote": "l'analisi automatica e dettagliata di migliaia di fotogrammi ha permesso di isolare potenziali target in un'area decisamente vasta ed impervia" }, { "kind": "news report", "citation": "Corriere della Sera Torino (2024). Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Corriere.it.", "title": "Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Lavorava ad Acqui Terme", "url": "https://torino.corriere.it/notizie/piemonte/24_settembre_17/disperso-sul-monviso-da-sabato-ha-parcheggiato-l-auto-alla-diga-di-pontechianale-poi-nessuna-traccia-89019eb1-5c94-4928-a627-187960555xlk.shtml", "date": "2024-09-17", "written_by": "independent", "quote": "presumibilmente è partito a piedi nella giornata di sabato dal parcheggio della diga di Pontechianale, nel cuneese, dove è ancora presente la sua auto" }, { "kind": "other", "citation": "OECD.AI (2026). AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps. OECD AI Incidents and Hazards Monitor.", "title": "AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps", "url": "https://oecd.ai/en/incidents/2026-01-10-f4af", "date": "2026-01-10", "written_by": "independent", "quote": "AI software analyzing drone images identified the body of missing Italian mountaineer Nicola Ivaldo in the Piedmont Alps" } ], "replication": { "produced_by": [ "Close-range high-resolution drone photography of steep faces (about 2,600 frames over 183 hectares)", "A target object (red helmet) with strong color contrast against rock and ice", "Search area narrowed by mobile-phone cell data to the Monviso and Visolotto faces" ], "must_hold": [ "Weather and terrain allow drones to fly close to the walls", "The subject or equipment remains visible and not buried by snow", "Rescuers verify AI flags, which CNSAS notes can also fire on plastic or unusual rock color" ], "echoes": [] }, "paired_incident": null, "headline": "ADIAT spots a red helmet and locates Nicola Ivaldo on Monviso", "metric": "located at about 3,150 m and recovered by 31 July 2025", "comparator": { "against": "conventional ground and air searches over the preceding months", "before": "I metodi di ricerca convenzionali sono rimasti inconcludenti per mesi", "after": "meno di 72 ore dalla prima missione del drone al recupero del corpo", "basis": "measured", "quote": "I metodi di ricerca convenzionali sono rimasti inconcludenti per mesi, mentre sono passate meno di 72 ore dalla prima missione del drone al recupero del corpo.", "url": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148" }, "later": { "status": "persisted", "date": "2026-01-18", "note": "By January 2026 the CNSAS Piemonte drone lead was working with Politecnico di Torino's geomatics team on a successor tool that adds precise georeferenced coordinates to the color-anomaly detection.", "quote": "Giordan, che è anche soccorritore, sta collaborando con il team di geomatica del Politecnico di Torino per sviluppare un software capace non solo di individuare anomalie cromatiche, ma di fornire coordinate georeferenziate di estrema precisione.", "url": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/" }, "value": null, "developer_country": "United States", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the bluewin.ch title to the page's headline, hedged the title's ADIAT attribution to its vendor source, placed the find on the Monviso north face rather than at Pontechianale (only his starting point), removed the unsupported claim that human reviewers had missed the helmet, and noted that the sources differ on the manual-review time (weeks per CAI, months per CNSAS via bluewin), the disappearance date (14 or 15 September 2024) and the source of the 31 July 2025 recovery date.", "source": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (11 sources and the registry id carried over); the duplicate was removed.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148; https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://texsar.org/; https://news.cnsas.it/piemonte/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: 11 independent news reports, one other independent source, the makers' press release and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0033", "catalog_version": "1.0.0", "source_fingerprint": "104bc06c9ff35eb203cd8b36ceced9dbff314ff19228b999bc38a5aecf7b423a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0033-source-0001", "AIBD-0033-source-0002", "AIBD-0033-source-0003", "AIBD-0033-source-0004", "AIBD-0033-source-0005", "AIBD-0033-source-0006", "AIBD-0033-source-0007", "AIBD-0033-source-0008", "AIBD-0033-source-0009", "AIBD-0033-source-0010", "AIBD-0033-source-0011", "AIBD-0033-source-0012", "AIBD-0033-source-0013", "AIBD-0033-source-0014", "AIBD-0033-source-0015" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "TEXSAR (Texas Search and Rescue) volunteers, per the developer's own account", "deployer": "Soccorso Alpino e Speleologico Piemontese (CNSAS Piemonte), Turin station drone team" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI flagged a few red pixels, the helmet, a detail CAI describes as invisible to the naked eye. Ten months of helicopters, specialist teams and advanced technology (Quadricottero) had not resolved the search. Drone pilot Saverio Isola is quoted that it was the AI software that identified the differently colored pixels. CAI/CNSAS sources do not name the software. The ADIAT attribution comes from the developer TEXSAR's own page. So the tool identity rests on a vendor-authored source." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI flagged a few red pixels, the helmet, a detail CAI describes as invisible to the naked eye. Ten months of helicopters, specialist teams and advanced technology (Quadricottero) had not resolved the search. Drone pilot Saverio Isola is quoted that it was the AI software that identified the differently colored pixels. CAI/CNSAS sources do not name the software. The ADIAT attribution comes from the developer TEXSAR's own page. So the tool identity rests on a vendor-authored source." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ivaldo's family obtained recovery of his body and certainty about his fate after ten months of searching. A material benefit, not life-saving, since he had died in September 2024." }, { "group": "organizational", "depth": 2, "reason": "CNSAS Piemonte ended a search that had involved ground teams, Guardia di Finanza and fire-service helicopters for ten months. Manual analysis of the drone photos would have taken weeks (CAI) to months (CNSAS, per bluewin)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: 11 independent news reports, one other independent source, the makers' press release and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ivaldo's family obtained recovery of his body and certainty about his fate after ten months of searching. A material benefit, not life-saving, since he had died in September 2024." }, { "group": "organizational", "depth": 2, "reason": "CNSAS Piemonte ended a search that had involved ground teams, Guardia di Finanza and fire-service helicopters for ten months. Manual analysis of the drone photos would have taken weeks (CAI) to months (CNSAS, per bluewin)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ivaldo's family obtained recovery of his body and certainty about his fate after ten months of searching. A material benefit, not life-saving, since he had died in September 2024." }, { "group": "organizational", "depth": 2, "reason": "CNSAS Piemonte ended a search that had involved ground teams, Guardia di Finanza and fire-service helicopters for ten months. Manual analysis of the drone photos would have taken weeks (CAI) to months (CNSAS, per bluewin)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "located at about 3,150 m and recovered by 31 July 2025", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-01-10-f4af" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-01-18", "note": "By January 2026 the CNSAS Piemonte drone lead was working with Politecnico di Torino's geomatics team on a successor tool that adds precise georeferenced coordinates to the color-anomaly detection.", "quote": "Giordan, che è anche soccorritore, sta collaborando con il team di geomatica del Politecnico di Torino per sviluppare un software capace non solo di individuare anomalie cromatiche, ma di fornire coordinate georeferenziate di estrema precisione.", "url": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0033" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Task Time", "taxonomy_note": "The time cut is the rescuers' frame review; the family's good, recovery of remains, has no type." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nicola Ivaldo was a surgeon aged 64 according to the Club Alpino Italiano's Lo Scarpone (another report says 66). He disappeared on 14 September 2024 per CAI during a solo outing on Monviso in Piedmont, Italy. Quadricottero dates his departure, when he parked his car at the Pontechianale dam, to 15 September. Searches over ten months found nothing. On 29 July 2025 the Soccorso Alpino e Speleologico Piemontese (CNSAS) flew two drones close to the north face. They collected about 2,600 high-resolution frames over 183 hectares in five hours. The frames were analyzed pixel by pixel with AI image-analysis software. Developer TEXSAR identifies it as the open-source Automated Drone Image Analysis Tool (ADIAT). The frames yielded a tiny red anomaly in the Perotti couloir: his helmet. His body was located at about 3,150 m and recovered by 31 July 2025. That date comes from TEXSAR's page (which cites Wired). It is consistent with bluewin's report of under 72 hours from the 29 July flight to the recovery. CAI gives only July 2025 and Quadricottero no date.", "benefit_type": "Reduced Task Time" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Ivaldo's family obtained recovery of his body and certainty about his fate after ten months of searching. A material benefit, not life-saving, since he had died in September 2024." }, { "group": "organizational", "depth": 2, "reason": "CNSAS Piemonte ended a search that had involved ground teams, Guardia di Finanza and fire-service helicopters for ten months. Manual analysis of the drone photos would have taken weeks (CAI) to months (CNSAS, per bluewin)." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ADIAT was built to scan drone photographs and flag color and shape anomalies for search-and-rescue teams. Locating the missing man's helmet was that intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Monviso north face, Perotti couloir (province of Cuneo), Italy", "developer_country": "United States", "deployer_country": "Italy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ADIAT was built to scan drone photographs and flag color and shape anomalies for search-and-rescue teams. Locating the missing man's helmet was that intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-07-31", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the bluewin.ch title to the page's headline, hedged the title's ADIAT attribution to its vendor source, placed the find on the Monviso north face rather than at Pontechianale (only his starting point), removed the unsupported claim that human reviewers had missed the helmet, and noted that the sources differ on the manual-review time (weeks per CAI, months per CNSAS via bluewin), the disappearance date (14 or 15 September 2024) and the source of the 31 July 2025 recovery date.", "source": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (11 sources and the registry id carried over); the duplicate was removed.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148; https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://texsar.org/; https://news.cnsas.it/piemonte/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Close-range high-resolution drone photography of steep faces (about 2,600 frames over 183 hectares)", "A target object (red helmet) with strong color contrast against rock and ice", "Search area narrowed by mobile-phone cell data to the Monviso and Visolotto faces" ], "must_hold": [ "Weather and terrain allow drones to fly close to the walls", "The subject or equipment remains visible and not buried by snow", "Rescuers verify AI flags, which CNSAS notes can also fire on plastic or unusual rock color" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Corrected the bluewin.ch title to the page's headline, hedged the title's ADIAT attribution to its vendor source, placed the find on the Monviso north face rather than at Pontechianale (only his starting point), removed the unsupported claim that human reviewers had missed the helmet, and noted that the sources differ on the manual-review time (weeks per CAI, months per CNSAS via bluewin), the disappearance date (14 or 15 September 2024) and the source of the 31 July 2025 recovery date.", "source": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged with a second write-up of the same event (11 sources and the registry id carried over); the duplicate was removed.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148; https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Task Time under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://texsar.org/; https://news.cnsas.it/piemonte/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Mountain search and rescue", "segment": "Recovery of a missing person in high-alpine terrain" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Lo Scarpone, Club Alpino Italiano (2026). Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino. 18 January 2026 (CAI is the parent body of CNSAS).", "title": "Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino", "url": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "date": "2026-01-18", "written_by": "deployer", "quote": "Due droni sono stati impiegati per voli ravvicinati alle pareti del Monviso, e in 5 ore sono stati raccolti circa 2.600 fotogrammi ad alta risoluzione." }, { "kind": "news report", "citation": "Scarato D (2025). Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso. Quadricottero News, 1 August 2025 (photo credited to Soccorso Alpino e Speleologico Piemonte - CNSAS).", "title": "Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso", "url": "https://www.quadricottero.com/2025/08/droni-e-ia-trovano-il-corpo-del-medico.html", "date": "2025-08-01", "written_by": "independent", "quote": "Il ritrovamento, avvenuto a circa 3150 metri di quota sulla parete nord della montagna, nel canale Perotti, è stato possibile grazie a un impiego mirato di droni professionali" }, { "kind": "news report", "citation": "bluewin.ch (2025). Sulle Alpi Italiane: Ecco com'è stato possibile localizzare un escursionista scomparso da un anno. 10 August 2025 (updated 12 August 2025).", "title": "Ecco com'è stato possibile localizzare un escursionista scomparso da un anno", "url": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148", "date": "2025-08-10", "written_by": "independent", "quote": "Sono stati questi pixel a cambiare tutto" }, { "kind": "press release", "citation": "Texas Search and Rescue (2025). ADIAT Helps Italian SAR Team. TEXSAR website, 15 August 2025 (developer of ADIAT).", "title": "ADIAT Helps Italian SAR Team", "url": "https://www.texsar.org/2025/08/15/adiat-helps-italian-sar-team/", "date": "2025-08-15", "written_by": "makers", "quote": "It was the AI software that identified some pixels of a different color in the images taken on Tuesday." }, { "kind": "news report", "citation": "Simičević, V. (2026). A red pixel in the snow: How AI solved the mystery of a missing mountaineer. BBC Future.", "title": "A red pixel in the snow: How AI solved the mystery of a missing mountaineer", "url": "https://www.bbc.com/future/article/20260108-how-ai-solved-the-mystery-of-a-missing-mountaineer", "date": "2026-01-09", "written_by": "independent", "quote": "Three days after the search resumed, however, the body of the missing doctor was found at one of the sites identified by the AI, lying in a gully" }, { "kind": "news report", "citation": "La Stampa (2025). Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso. La Stampa, Cuneo.", "title": "Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso", "url": "https://www.lastampa.it/cuneo/2025/07/31/news/trovato_il_corpo_del_medico_di_loano_disperso_dal_15_settembre_sul_monviso-15253571/", "date": "2025-07-31", "written_by": "independent", "quote": "realizzati 2600 fotogrammi che sono stati caricati su un apposito software, in dotazione al Soccorso alpino e speleologico, che ha elaborato i dati indicando tre possibili target da verificare" }, { "kind": "news report", "citation": "Abbà, M. (2025). Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Wired Italia.", "title": "Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Che ha riconosciuto il caschetto tra migliaia di immagini", "url": "https://www.wired.it/article/escursionista-disperso-monviso-cadavere-drone-intelligenza-artificiale-soccorso-alpino/", "date": "2025-07-31", "written_by": "independent", "quote": "la salma del medico ligure di 64 anni Nicola Ivaldo è stata trovata nella mattinata di giovedì 31 luglio, a distanza di oltre dieci mesi dalla sua scomparsa" }, { "kind": "news report", "citation": "Abo Abia, M. (2025). Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024. RaiNews, TGR Piemonte.", "title": "Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024", "url": "https://www.rainews.it/tgr/piemonte/articoli/2025/07/ritrovato-il-corpo-di-nicola-ivaldo-disperso-sul-monviso-dal-settembre-2024-d14c11b3-3753-454e-98b4-d8919b1648bc.html", "date": "2025-07-31", "written_by": "independent", "quote": "Il programma, analizzando video e foto, ha individuato tre aree sensibili: zone con dettagli non naturali e incompatibili con l'ambiente circostante" }, { "kind": "press release", "citation": "Lo Scarpone (2025). Monviso, ritrovato il corpo del medico disperso da settembre 2024. Club Alpino Italiano.", "title": "Monviso, ritrovato il corpo del medico disperso da settembre 2024", "url": "https://www.loscarpone.cai.it/dettaglio/monviso-ritrovato-il-corpo-del-medico-disperso-da-settembre-2024/", "date": "2025-07-31", "written_by": "deployer", "quote": "raccolto circa 2600 fotogrammi ad alta risoluzione, poi analizzati tramite un software in dotazione al Soccorso Alpino che ha indicato tre possibili punti di interesse tramite analisi pixel-per-pixel" }, { "kind": "news report", "citation": "Ciprian, V. (2026). Quel punto rosso era il casco dell'alpinista disperso da mesi. L'AltraMontagna, il Dolomiti.", "title": "Quel punto rosso era il casco dell'alpinista disperso da mesi: \"Senza l'anomalia segnalata dall'intelligenza artificiale in una delle 2600 foto dal drone, probabilmente non sarebbe mai stato trovato\"", "url": "https://www.ildolomiti.it/altra-montagna/storie/2026/quel-punto-rosso-era-il-casco-dellalpinista-disperso-da-mesi-senza-lanomalia-segnalata-dallintelligenza-artificiale-in-una-delle-2600-foto-dal-drone-probabilmente-non-sarebbe-mai-stato-trovato", "date": "2026-01-13", "written_by": "independent", "quote": "il drone, penetrando nel canale Perotti, ha individuato i resti di un essere umano nel canale più a destra dei tre che solcano la parete nord" }, { "kind": "news report", "citation": "Rullo, F. (2025). Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna. Corriere della Sera, Torino.", "title": "Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna", "url": "https://torino.corriere.it/notizie/piemonte/25_luglio_31/monviso-ritrovato-dopo-un-anno-e-solo-grazie-ai-droni-il-corpo-di-nicola-ivaldo-medico-savonese-scomparso-in-montagna-c943f224-5e04-4320-856b-a3d4533caxlk.shtml", "date": "2025-07-31", "written_by": "independent", "quote": "ritrovati grazie all'uso di droni e a un apposito software in dotazione al soccorso alpino: erano in un canale a 3150 metri di quota" }, { "kind": "news report", "citation": "Annapurna, K. (2025). AI Solves the Mystery of Missing Italian Climber. ExplorersWeb.", "title": "AI Solves the Mystery of Missing Italian Climber", "url": "https://explorersweb.com/ai-solves-the-mystery-of-missing-italian-climber/", "date": "2025-08-07", "written_by": "independent", "quote": "an AI software analyzed these many images in a single afternoon, singling out a cluster of red pixels that turned out to be Ivaldo's helmet" }, { "kind": "news report", "citation": "Malfatti, M. (2025). Anche l'intelligenza artificiale al servizio del Soccorso Alpino. Montagna.TV.", "title": "Anche l'intelligenza artificiale al servizio del Soccorso Alpino", "url": "https://www.montagna.tv/262960/anche-lintelligenza-artificiale-al-servizio-del-soccorso-alpino/", "date": "2025-10-06", "written_by": "independent", "quote": "l'analisi automatica e dettagliata di migliaia di fotogrammi ha permesso di isolare potenziali target in un'area decisamente vasta ed impervia" }, { "kind": "news report", "citation": "Corriere della Sera Torino (2024). Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Corriere.it.", "title": "Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Lavorava ad Acqui Terme", "url": "https://torino.corriere.it/notizie/piemonte/24_settembre_17/disperso-sul-monviso-da-sabato-ha-parcheggiato-l-auto-alla-diga-di-pontechianale-poi-nessuna-traccia-89019eb1-5c94-4928-a627-187960555xlk.shtml", "date": "2024-09-17", "written_by": "independent", "quote": "presumibilmente è partito a piedi nella giornata di sabato dal parcheggio della diga di Pontechianale, nel cuneese, dove è ancora presente la sua auto" }, { "kind": "other", "citation": "OECD.AI (2026). AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps. OECD AI Incidents and Hazards Monitor.", "title": "AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps", "url": "https://oecd.ai/en/incidents/2026-01-10-f4af", "date": "2026-01-10", "written_by": "independent", "quote": "AI software analyzing drone images identified the body of missing Italian mountaineer Nicola Ivaldo in the Piedmont Alps" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0033-source-0001", "AIBD-0033-source-0002", "AIBD-0033-source-0003", "AIBD-0033-source-0004", "AIBD-0033-source-0005", "AIBD-0033-source-0006", "AIBD-0033-source-0007", "AIBD-0033-source-0008", "AIBD-0033-source-0009", "AIBD-0033-source-0010", "AIBD-0033-source-0011", "AIBD-0033-source-0012", "AIBD-0033-source-0013", "AIBD-0033-source-0014", "AIBD-0033-source-0015" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Lo Scarpone, Club Alpino Italiano (2026). Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino. 18 January 2026 (CAI is the parent body of CNSAS).", "title": "Sulla BBC il 'caso Ivaldo': l'Intelligenza Artificiale a supporto del Soccorso Alpino", "url": "https://www.loscarpone.cai.it/dettaglio/sulla-bbc-il-caso-ivaldo-lintelligenza-artificiale-a-supporto-del-soccorso-alpino/", "date": "2026-01-18", "written_by": "deployer", "quote": "Due droni sono stati impiegati per voli ravvicinati alle pareti del Monviso, e in 5 ore sono stati raccolti circa 2.600 fotogrammi ad alta risoluzione." }, { "kind": "news report", "citation": "Scarato D (2025). Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso. Quadricottero News, 1 August 2025 (photo credited to Soccorso Alpino e Speleologico Piemonte - CNSAS).", "title": "Droni e IA trovano il corpo del medico alpinista disperso da mesi sul Monviso", "url": "https://www.quadricottero.com/2025/08/droni-e-ia-trovano-il-corpo-del-medico.html", "date": "2025-08-01", "written_by": "independent", "quote": "Il ritrovamento, avvenuto a circa 3150 metri di quota sulla parete nord della montagna, nel canale Perotti, è stato possibile grazie a un impiego mirato di droni professionali" }, { "kind": "news report", "citation": "bluewin.ch (2025). Sulle Alpi Italiane: Ecco com'è stato possibile localizzare un escursionista scomparso da un anno. 10 August 2025 (updated 12 August 2025).", "title": "Ecco com'è stato possibile localizzare un escursionista scomparso da un anno", "url": "https://www.bluewin.ch/it/attualita/escursionista-scomparso-da-un-anno-ecco-come-e-stato-localizzato-li.2817148", "date": "2025-08-10", "written_by": "independent", "quote": "Sono stati questi pixel a cambiare tutto" }, { "kind": "press release", "citation": "Texas Search and Rescue (2025). ADIAT Helps Italian SAR Team. TEXSAR website, 15 August 2025 (developer of ADIAT).", "title": "ADIAT Helps Italian SAR Team", "url": "https://www.texsar.org/2025/08/15/adiat-helps-italian-sar-team/", "date": "2025-08-15", "written_by": "makers", "quote": "It was the AI software that identified some pixels of a different color in the images taken on Tuesday." }, { "kind": "news report", "citation": "Simičević, V. (2026). A red pixel in the snow: How AI solved the mystery of a missing mountaineer. BBC Future.", "title": "A red pixel in the snow: How AI solved the mystery of a missing mountaineer", "url": "https://www.bbc.com/future/article/20260108-how-ai-solved-the-mystery-of-a-missing-mountaineer", "date": "2026-01-09", "written_by": "independent", "quote": "Three days after the search resumed, however, the body of the missing doctor was found at one of the sites identified by the AI, lying in a gully" }, { "kind": "news report", "citation": "La Stampa (2025). Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso. La Stampa, Cuneo.", "title": "Trovato il corpo del medico di Albenga disperso dal 15 settembre sul Monviso", "url": "https://www.lastampa.it/cuneo/2025/07/31/news/trovato_il_corpo_del_medico_di_loano_disperso_dal_15_settembre_sul_monviso-15253571/", "date": "2025-07-31", "written_by": "independent", "quote": "realizzati 2600 fotogrammi che sono stati caricati su un apposito software, in dotazione al Soccorso alpino e speleologico, che ha elaborato i dati indicando tre possibili target da verificare" }, { "kind": "news report", "citation": "Abbà, M. (2025). Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Wired Italia.", "title": "Il corpo di un escursionista disperso sul Monviso è stato recuperato dopo quasi un anno grazie a un sistema di AI. Che ha riconosciuto il caschetto tra migliaia di immagini", "url": "https://www.wired.it/article/escursionista-disperso-monviso-cadavere-drone-intelligenza-artificiale-soccorso-alpino/", "date": "2025-07-31", "written_by": "independent", "quote": "la salma del medico ligure di 64 anni Nicola Ivaldo è stata trovata nella mattinata di giovedì 31 luglio, a distanza di oltre dieci mesi dalla sua scomparsa" }, { "kind": "news report", "citation": "Abo Abia, M. (2025). Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024. RaiNews, TGR Piemonte.", "title": "Ritrovato il corpo di Nicola Ivaldo, disperso sul Monviso dal settembre 2024", "url": "https://www.rainews.it/tgr/piemonte/articoli/2025/07/ritrovato-il-corpo-di-nicola-ivaldo-disperso-sul-monviso-dal-settembre-2024-d14c11b3-3753-454e-98b4-d8919b1648bc.html", "date": "2025-07-31", "written_by": "independent", "quote": "Il programma, analizzando video e foto, ha individuato tre aree sensibili: zone con dettagli non naturali e incompatibili con l'ambiente circostante" }, { "kind": "press release", "citation": "Lo Scarpone (2025). Monviso, ritrovato il corpo del medico disperso da settembre 2024. Club Alpino Italiano.", "title": "Monviso, ritrovato il corpo del medico disperso da settembre 2024", "url": "https://www.loscarpone.cai.it/dettaglio/monviso-ritrovato-il-corpo-del-medico-disperso-da-settembre-2024/", "date": "2025-07-31", "written_by": "deployer", "quote": "raccolto circa 2600 fotogrammi ad alta risoluzione, poi analizzati tramite un software in dotazione al Soccorso Alpino che ha indicato tre possibili punti di interesse tramite analisi pixel-per-pixel" }, { "kind": "news report", "citation": "Ciprian, V. (2026). Quel punto rosso era il casco dell'alpinista disperso da mesi. L'AltraMontagna, il Dolomiti.", "title": "Quel punto rosso era il casco dell'alpinista disperso da mesi: \"Senza l'anomalia segnalata dall'intelligenza artificiale in una delle 2600 foto dal drone, probabilmente non sarebbe mai stato trovato\"", "url": "https://www.ildolomiti.it/altra-montagna/storie/2026/quel-punto-rosso-era-il-casco-dellalpinista-disperso-da-mesi-senza-lanomalia-segnalata-dallintelligenza-artificiale-in-una-delle-2600-foto-dal-drone-probabilmente-non-sarebbe-mai-stato-trovato", "date": "2026-01-13", "written_by": "independent", "quote": "il drone, penetrando nel canale Perotti, ha individuato i resti di un essere umano nel canale più a destra dei tre che solcano la parete nord" }, { "kind": "news report", "citation": "Rullo, F. (2025). Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna. Corriere della Sera, Torino.", "title": "Monviso, ritrovato dopo un anno e solo grazie ai droni il corpo di Nicola Ivaldo, medico savonese scomparso in montagna", "url": "https://torino.corriere.it/notizie/piemonte/25_luglio_31/monviso-ritrovato-dopo-un-anno-e-solo-grazie-ai-droni-il-corpo-di-nicola-ivaldo-medico-savonese-scomparso-in-montagna-c943f224-5e04-4320-856b-a3d4533caxlk.shtml", "date": "2025-07-31", "written_by": "independent", "quote": "ritrovati grazie all'uso di droni e a un apposito software in dotazione al soccorso alpino: erano in un canale a 3150 metri di quota" }, { "kind": "news report", "citation": "Annapurna, K. (2025). AI Solves the Mystery of Missing Italian Climber. ExplorersWeb.", "title": "AI Solves the Mystery of Missing Italian Climber", "url": "https://explorersweb.com/ai-solves-the-mystery-of-missing-italian-climber/", "date": "2025-08-07", "written_by": "independent", "quote": "an AI software analyzed these many images in a single afternoon, singling out a cluster of red pixels that turned out to be Ivaldo's helmet" }, { "kind": "news report", "citation": "Malfatti, M. (2025). Anche l'intelligenza artificiale al servizio del Soccorso Alpino. Montagna.TV.", "title": "Anche l'intelligenza artificiale al servizio del Soccorso Alpino", "url": "https://www.montagna.tv/262960/anche-lintelligenza-artificiale-al-servizio-del-soccorso-alpino/", "date": "2025-10-06", "written_by": "independent", "quote": "l'analisi automatica e dettagliata di migliaia di fotogrammi ha permesso di isolare potenziali target in un'area decisamente vasta ed impervia" }, { "kind": "news report", "citation": "Corriere della Sera Torino (2024). Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Corriere.it.", "title": "Disperso sul Monviso da sabato Nicola Ivaldo, 64enne chirurgo ortopedico di Loano. Lavorava ad Acqui Terme", "url": "https://torino.corriere.it/notizie/piemonte/24_settembre_17/disperso-sul-monviso-da-sabato-ha-parcheggiato-l-auto-alla-diga-di-pontechianale-poi-nessuna-traccia-89019eb1-5c94-4928-a627-187960555xlk.shtml", "date": "2024-09-17", "written_by": "independent", "quote": "presumibilmente è partito a piedi nella giornata di sabato dal parcheggio della diga di Pontechianale, nel cuneese, dove è ancora presente la sua auto" }, { "kind": "other", "citation": "OECD.AI (2026). AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps. OECD AI Incidents and Hazards Monitor.", "title": "AI-Assisted Drone Search Locates Missing Mountaineer in Italian Alps", "url": "https://oecd.ai/en/incidents/2026-01-10-f4af", "date": "2026-01-10", "written_by": "independent", "quote": "AI software analyzing drone images identified the body of missing Italian mountaineer Nicola Ivaldo in the Piedmont Alps" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI analysis of 2,600 drone frames flagged a red helmet in the Perotti couloir at 3,150 m; Ivaldo's body was recovered by 31 July 2025.", "account": "Nicola Ivaldo was a surgeon aged 64 according to the Club Alpino Italiano's Lo Scarpone (another report says 66). He disappeared on 14 September 2024 per CAI during a solo outing on Monviso in Piedmont, Italy. Quadricottero dates his departure, when he parked his car at the Pontechianale dam, to 15 September. Searches over ten months found nothing. On 29 July 2025 the Soccorso Alpino e Speleologico Piemontese (CNSAS) flew two drones close to the north face. They collected about 2,600 high-resolution frames over 183 hectares in five hours. The frames were analyzed pixel by pixel with AI image-analysis software. Developer TEXSAR identifies it as the open-source Automated Drone Image Analysis Tool (ADIAT). The frames yielded a tiny red anomaly in the Perotti couloir: his helmet. His body was located at about 3,150 m and recovered by 31 July 2025. That date comes from TEXSAR's page (which cites Wired). It is consistent with bluewin's report of under 72 hours from the 29 July flight to the recovery. CAI gives only July 2025 and Quadricottero no date." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI drone-image analysis software used by CNSAS Piemonte (identified as ADIAT by its developer, TEXSAR; CAI and CNSAS sources do not name it)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "TEXSAR (Texas Search and Rescue) volunteers, per the developer's own account" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CNSAS Piemonte drone imagery analyzed with AI software, likely TEXSAR's ADIAT, locates missing surgeon Nicola Ivaldo on Monviso after ten months", "headline": "ADIAT spots a red helmet and locates Nicola Ivaldo on Monviso" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "104bc06c9ff35eb203cd8b36ceced9dbff314ff19228b999bc38a5aecf7b423a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nicola Ivaldo was a surgeon aged 64 according to the Club Alpino Italiano's Lo Scarpone (another report says 66). He disappeared on 14 September 2024 per CAI during a solo outing on Monviso in Piedmont, Italy. Quadricottero dates his departure, when he parked his car at the Pontechianale dam, to 15 September. Searches over ten months found nothing. On 29 July 2025 the Soccorso Alpino e Speleologico Piemontese (CNSAS) flew two drones close to the north face. They collected about 2,600 high-resolution frames over 183 hectares in five hours. The frames were analyzed pixel by pixel with AI image-analysis software. Developer TEXSAR identifies it as the open-source Automated Drone Image Analysis Tool (ADIAT). The frames yielded a tiny red anomaly in the Perotti couloir: his helmet. His body was located at about 3,150 m and recovered by 31 July 2025. That date comes from TEXSAR's page (which cites Wired). It is consistent with bluewin's report of under 72 hours from the 29 July flight to the recovery. CAI gives only July 2025 and Quadricottero no date.", "replication": { "produced_by": [ "Close-range high-resolution drone photography of steep faces (about 2,600 frames over 183 hectares)", "A target object (red helmet) with strong color contrast against rock and ice", "Search area narrowed by mobile-phone cell data to the Monviso and Visolotto faces" ], "must_hold": [ "Weather and terrain allow drones to fly close to the walls", "The subject or equipment remains visible and not buried by snow", "Rescuers verify AI flags, which CNSAS notes can also fire on plastic or unusual rock color" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0064", "title": "Brainomix 360 Stroke AI supports immediate stroke identification at Royal Berkshire Hospital; 83-year-old transferred for thrombectomy within 25 minutes", "summary": "AI-supported scan identified Jean Hines's major stroke on arrival; transferred in 25 minutes for successful thrombectomy; good recovery.", "date_observed": "2025-08-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers.", "category": "protective response", "unexpected": false, "purpose": "Brainomix 360 Stroke is built to analyze stroke imaging and support rapid treatment and transfer decisions, including selection for thrombectomy. This is its intended function.", "system": "Brainomix 360 Stroke", "model_version": null, "developer": "Brainomix", "deployer": "NHS England / Royal Berkshire Hospital", "location": "Reading, United Kingdom", "domain": "Healthcare - acute stroke care", "segment": "Hospital stroke imaging decision support", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Rapid transfer enabled thrombectomy for a major stroke and she reports no serious disabilities. The AI's contribution was the time saved." }, { "group": "organizational", "depth": 2, "reason": "NHS England reports a 25-minute door-in-door-out for this patient against a 64-minute average reduction at primary stroke centers. It also reports a doubling of thrombectomy rates (2.3% to 4.6%) at participating sites." } ], "ai_role": { "status": "assessed", "statement": "The AI-supported scan read identified the major stroke immediately on arrival, enabling a 25-minute door-in-door-out. The treatment itself (thrombectomy) was delivered by the Oxford team. The stroke would very likely have been diagnosed without AI. So the AI's contribution is the speed of decision and transfer. The Lancet Digital Health study (which has Brainomix co-authors alongside NHS lead authors) supports that at population level." }, "evidence": [ { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance. NHS England news, 2 December 2025.", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "A scan carried out immediately on arrival — supported by the Brainomix AI imaging tool — identified a major stroke and the need for urgent specialist treatment." }, { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance (second quotation).", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "Within just 25 minutes of reaching the emergency department, Jean was on her way by blue-light ambulance to the John Radcliffe Hospital in Oxford" }, { "kind": "peer-reviewed study", "citation": "Nagaratnam K, Neuhaus AA, Fensome L, et al. (2025). Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study. The Lancet Digital Health 7(12):100927. Three Brainomix employees and the corresponding author (dual NHS/Brainomix affiliation) are among 21 authors; lead authors are NHS and University of Oxford.", "title": "Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study", "url": "https://europepmc.org/abstract/MED/41339157", "date": "2025-12-02", "written_by": "makers", "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS." } ], "replication": { "produced_by": [ "AI stroke imaging with results available to the admitting team immediately after the scan", "A regional transfer pathway from primary stroke center to a thrombectomy center" ], "must_hold": [ "Rapid ambulance transfer and an available thrombectomy team", "Clinicians act on the AI-supported read without waiting for a separate specialist report" ], "echoes": [ { "date": "2025-12-02", "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)", "model_version": null, "outcome": "recurred", "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927" } ] }, "paired_incident": null, "headline": "Brainomix flags Jean Hines's stroke; transferred in 25 minutes", "metric": "transferred in 25 minutes for successful thrombectomy", "comparator": { "against": "thrombectomy rate at the same 26 hospitals before the software was implemented, with the 81 non-implementing hospitals as the background trend", "before": "2·3% (376 of 15 969 patients)", "after": "4·6% (751 of 15 428 patients), a relative increase of 100%", "basis": "measured", "quote": "For evaluation sites, the pre-implementation endovascular thrombectomy rate was 2·3% (376 of 15 969 patients) and the post-implementation rate was 4·6% (751 of 15 428 patients), a relative increase of 100%. For non-evaluation sites, the pre-implementation rate was 1·6% (1431 of 88 712 patients) and the post-implementation rate was 2·6% (2410 of 89 900 patients), a relative increase of 62·5% (odds ratio [OR] for the interaction between site and time period 1·24 [95% CI 1·08-1·43]; p=0·0026).", "url": "https://europepmc.org/abstract/MED/41339157" }, "later": { "status": "scaled", "date": "2025-12-02", "note": "Four months after the inferred date of Jean Hines's stroke, the Lancet Digital Health study reported the same software systematically implemented in 26 NHS hospitals and associated with doubled thrombectomy rates.", "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS. These results support the routine use of AI imaging software in the management of patients with stroke.", "url": "https://europepmc.org/abstract/MED/41339157" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "NHS England item dated 2 December 2025 and the Lancet Digital Health item and echo dated 2025-12-02 from the Wayback Machine capture and the Europe PMC record, and category moved from specific harm prevented to protective response with prevention unproven with the taxonomy note rewritten, because no source shows that the AI changed this patient's outcome rather than the pathway timing.", "source": "NHS England news, 2 December 2025 (Wayback Machine capture of 9 December 2025 of https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/); Europe PMC record MED:41339157 (firstPublicationDate 2025-12-02)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/abstract/MED/41339157; https://europepmc.org/abstract/MED/41339157", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.brainomix.com/contact/; https://en.wikipedia.org/wiki/Royal_Berkshire_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's press release. 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So the AI's contribution is the speed of decision and transfer. The Lancet Digital Health study (which has Brainomix co-authors alongside NHS lead authors) supports that at population level." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rapid transfer enabled thrombectomy for a major stroke and she reports no serious disabilities. 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"evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2025-12-02", "note": "Four months after the inferred date of Jean Hines's stroke, the Lancet Digital Health study reported the same software systematically implemented in 26 NHS hospitals and associated with doubled thrombectomy rates.", "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS. These results support the routine use of AI imaging software in the management of patients with stroke.", "url": "https://europepmc.org/abstract/MED/41339157" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0064" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rapid transfer enabled thrombectomy for a major stroke and she reports no serious disabilities. The AI's contribution was the time saved." }, { "group": "organizational", "depth": 2, "reason": "NHS England reports a 25-minute door-in-door-out for this patient against a 64-minute average reduction at primary stroke centers. It also reports a doubling of thrombectomy rates (2.3% to 4.6%) at participating sites." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Brainomix 360 Stroke is built to analyze stroke imaging and support rapid treatment and transfer decisions, including selection for thrombectomy. This is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Reading, United Kingdom", "developer_country": "United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Brainomix 360 Stroke is built to analyze stroke imaging and support rapid treatment and transfer decisions, including selection for thrombectomy. This is its intended function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "NHS England item dated 2 December 2025 and the Lancet Digital Health item and echo dated 2025-12-02 from the Wayback Machine capture and the Europe PMC record, and category moved from specific harm prevented to protective response with prevention unproven with the taxonomy note rewritten, because no source shows that the AI changed this patient's outcome rather than the pathway timing.", "source": "NHS England news, 2 December 2025 (Wayback Machine capture of 9 December 2025 of https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/); Europe PMC record MED:41339157 (firstPublicationDate 2025-12-02)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/abstract/MED/41339157; https://europepmc.org/abstract/MED/41339157", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.brainomix.com/contact/; https://en.wikipedia.org/wiki/Royal_Berkshire_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "AI stroke imaging with results available to the admitting team immediately after the scan", "A regional transfer pathway from primary stroke center to a thrombectomy center" ], "must_hold": [ "Rapid ambulance transfer and an available thrombectomy team", "Clinicians act on the AI-supported read without waiting for a separate specialist report" ], "echoes": [ { "date": "2025-12-02", "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)", "outcome": "recurred", "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "AI stroke imaging with results available to the admitting team immediately after the scan", "A regional transfer pathway from primary stroke center to a thrombectomy center" ], "must_hold": [ "Rapid ambulance transfer and an available thrombectomy team", "Clinicians act on the AI-supported read without waiting for a separate specialist report" ], "echoes": [ { "date": "2025-12-02", "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)", "outcome": "recurred", "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "NHS England item dated 2 December 2025 and the Lancet Digital Health item and echo dated 2025-12-02 from the Wayback Machine capture and the Europe PMC record, and category moved from specific harm prevented to protective response with prevention unproven with the taxonomy note rewritten, because no source shows that the AI changed this patient's outcome rather than the pathway timing.", "source": "NHS England news, 2 December 2025 (Wayback Machine capture of 9 December 2025 of https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/); Europe PMC record MED:41339157 (firstPublicationDate 2025-12-02)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://europepmc.org/abstract/MED/41339157; https://europepmc.org/abstract/MED/41339157", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.brainomix.com/contact/; https://en.wikipedia.org/wiki/Royal_Berkshire_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - acute stroke care", "segment": "Hospital stroke imaging decision support" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance. NHS England news, 2 December 2025.", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "A scan carried out immediately on arrival — supported by the Brainomix AI imaging tool — identified a major stroke and the need for urgent specialist treatment." }, { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance (second quotation).", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "Within just 25 minutes of reaching the emergency department, Jean was on her way by blue-light ambulance to the John Radcliffe Hospital in Oxford" }, { "kind": "peer-reviewed study", "citation": "Nagaratnam K, Neuhaus AA, Fensome L, et al. (2025). Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study. The Lancet Digital Health 7(12):100927. Three Brainomix employees and the corresponding author (dual NHS/Brainomix affiliation) are among 21 authors; lead authors are NHS and University of Oxford.", "title": "Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study", "url": "https://europepmc.org/abstract/MED/41339157", "date": "2025-12-02", "written_by": "makers", "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0064-source-0001", "AIBD-0064-source-0002", "AIBD-0064-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance. NHS England news, 2 December 2025.", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "A scan carried out immediately on arrival — supported by the Brainomix AI imaging tool — identified a major stroke and the need for urgent specialist treatment." }, { "kind": "press release", "citation": "NHS England (2025). 'Life-changing' AI support helping stroke patients get a second chance (second quotation).", "title": "'Life-changing' AI support helping stroke patients get a second chance", "url": "https://www.england.nhs.uk/2025/12/life-changing-ai-support-helping-stroke-patients-get-a-second-chance/", "date": "2025-12-02", "written_by": "deployer", "quote": "Within just 25 minutes of reaching the emergency department, Jean was on her way by blue-light ambulance to the John Radcliffe Hospital in Oxford" }, { "kind": "peer-reviewed study", "citation": "Nagaratnam K, Neuhaus AA, Fensome L, et al. (2025). Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study. The Lancet Digital Health 7(12):100927. Three Brainomix employees and the corresponding author (dual NHS/Brainomix affiliation) are among 21 authors; lead authors are NHS and University of Oxford.", "title": "Artificial intelligence imaging decision support for acute stroke treatment in England: a prospective observational study", "url": "https://europepmc.org/abstract/MED/41339157", "date": "2025-12-02", "written_by": "makers", "quote": "Stroke AI imaging software was associated with increased endovascular thrombectomy rates across the English NHS." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI-supported scan identified Jean Hines's major stroke on arrival; transferred in 25 minutes for successful thrombectomy; good recovery.", "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Brainomix 360 Stroke" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Brainomix" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Brainomix 360 Stroke AI supports immediate stroke identification at Royal Berkshire Hospital; 83-year-old transferred for thrombectomy within 25 minutes", "headline": "Brainomix flags Jean Hines's stroke; transferred in 25 minutes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a9d99f6616f7021e77b998362e17b8b0156769d248596b153f6ac094aba09b20" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Jean Hines, 83, collapsed at home and was taken to the Royal Berkshire Hospital, Reading, England, on a weekend in August. National Health Service (NHS) England's December 2025 statement gives no year, so 2025 is inferred. A scan carried out immediately on arrival, supported by the Brainomix AI imaging tool, identified a major stroke needing urgent specialist treatment. Within 25 minutes of reaching the emergency department she was on her way by ambulance to the John Radcliffe Hospital, Oxford. There she had a successful mechanical thrombectomy. She describes a very good physical recovery with no serious disabilities. NHS England states the Brainomix 360 Stroke tool is used in over 70 hospitals. It associates the tool with a 64-minute door-in-door-out reduction at primary stroke centers.", "replication": { "produced_by": [ "AI stroke imaging with results available to the admitting team immediately after the scan", "A regional transfer pathway from primary stroke center to a thrombectomy center" ], "must_hold": [ "Rapid ambulance transfer and an available thrombectomy team", "Clinicians act on the AI-supported read without waiting for a separate specialist report" ], "echoes": [ { "date": "2025-12-02", "setting": "107 NHS hospitals in England, 452,952 stroke patients 2019–2023: thrombectomy rates doubled (2.3% to 4.6%) at AI evaluation sites (population-level)", "outcome": "recurred", "source": "Nagaratnam K et al. (2025) Lancet Digital Health 7(12):100927" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0305", "title": "ChatGPT lists hereditary spastic paraplegia for Phoebe Tesoriere, 23, after four years of misdiagnosis; her GP agrees and genetic testing confirms it", "summary": "A Cardiff teacher put her symptoms into ChatGPT after a coma; it listed hereditary spastic paraplegia, her GP called it plausible and genetic testing confirmed it in August 2025 (BBC, WalesOnline).", "date_observed": "2025-08-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Phoebe Tesoriere, 23, from Cardiff, Wales, is a former special educational needs teacher. She had a limp since childhood. From 2022 she was diagnosed with epilepsy, then Todd's paralysis, and repeatedly told her symptoms were anxiety. In January 2025 she fell down stairs and spent months in hospital. In July 2025 a seizure left her in a coma (three days per BBC Wales, 48 hours per the SWNS report in WalesOnline). After discharge she entered her symptoms into ChatGPT. It returned a list of possible conditions including hereditary spastic paraplegia (HSP). She took the suggestion to her GP, who agreed it was a “plausible reason”. Genetic testing confirmed HSP, in August 2025 according to WalesOnline, which also reports the complex quadriplegic type. The first day of August is used because no day is given. There is no treatment. She uses a wheelchair, attends physiotherapy and is fundraising for a specialist chair. Cardiff and Vale University Health Board said it was “sorry to hear about Phoebe's experience while in our care”. It would not comment on an individual case. The account rests on her own statements to BBC Wales (10 April 2026) and SWNS (6 April 2026). No clinical document is among the sources.", "category": "benefit created", "unexpected": true, "purpose": "ChatGPT is a general-purpose chatbot not built or cleared for diagnosis. The patient used it to generate candidate conditions from her symptom list.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": null, "location": "Cardiff, United Kingdom", "domain": "Healthcare (rare-disease diagnosis)", "segment": "Patient-initiated use of a consumer LLM", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "A confirmed diagnosis replaced “anxiety” on her records and lets her plan care and equipment. The condition is progressive with no treatment. So the gain is certainty and appropriate management rather than a changed prognosis." } ], "ai_role": { "status": "assessed", "statement": "By her account the chatbot produced a list of candidates that included HSP. She decided to take it to her GP. The GP ordered genetic testing, and the test made the diagnosis. The prompt, the model version and the full candidate list are not reported. Only news reports quoting the patient are among the sources. The health board declined to comment on the case." }, "evidence": [ { "kind": "news report", "citation": "Herbert D (2026). ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis. BBC Wales, 10 April 2026.", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "The chatbot came back with a list of possible conditions, including hereditary spastic paraplegia." }, { "kind": "news report", "citation": "Phillips E / SWNS (2026). Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety. WalesOnline, 6 April 2026.", "title": "Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety", "url": "https://www.walesonline.co.uk/news/wales-news/cardiff-woman-uses-chat-gpt-33722339", "date": "2026-04-06", "written_by": "independent", "quote": "Phoebe underwent genetic testing which confirmed in August 2025 that she had the complex quadriplegic type of the condition" }, { "kind": "news report", "citation": "Herbert D (2026). BBC Wales, 10 April 2026 (health board statement).", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "Cardiff and Vale University Health Board said: \"We are sorry to hear about Phoebe's experience while in our care.\"" } ], "replication": { "produced_by": [ "A patient with a long list of concrete symptoms (gait, incontinence, sensory loss, reflex changes, seizures) and no settled diagnosis", "Entry of the symptom list into a general large language model (LLM)", "A GP willing to test a patient-sourced hypothesis and access to genetic testing" ], "must_hold": [ "The true condition is among the candidates the model lists and the patient pursues it", "Clinicians confirm by genetic testing rather than accepting the suggestion" ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT lists HSP for Phoebe Tesoriere; genetic testing confirms", "metric": null, "comparator": { "against": "four years of diagnoses by doctors (anxiety, depression, epilepsy)", "before": "she was told she was anxious, depressed, had epilepsy", "after": "Genetic testing then confirmed the AI suggestion.", "basis": "assumed", "quote": "ChatGPT has helped to uncover a woman's rare condition after years of being misdiagnosed by doctors. Phoebe Tesoriere, 23, claims she was told she was anxious, depressed, had epilepsy and warned she'd be treated as a mental health patient if she kept returning to A&E.", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo" }, "later": { "status": "unknown", "date": null, "note": "Nothing dated after the April 2026 reports was found; WalesOnline says she is fundraising for a specialist wheelchair and there is no treatment.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.bbc.com/news/articles/cx24njzzkgjo", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports. 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ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis. BBC Wales, 10 April 2026.", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "The chatbot came back with a list of possible conditions, including hereditary spastic paraplegia." }, { "kind": "news report", "citation": "Phillips E / SWNS (2026). Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety. WalesOnline, 6 April 2026.", "title": "Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety", "url": "https://www.walesonline.co.uk/news/wales-news/cardiff-woman-uses-chat-gpt-33722339", "date": "2026-04-06", "written_by": "independent", "quote": "Phoebe underwent genetic testing which confirmed in August 2025 that she had the complex quadriplegic type of the condition" }, { "kind": "news report", "citation": "Herbert D (2026). BBC Wales, 10 April 2026 (health board statement).", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "Cardiff and Vale University Health Board said: \"We are sorry to hear about Phoebe's experience while in our care.\"" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0305-source-0001", "AIBD-0305-source-0002", "AIBD-0305-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Herbert D (2026). ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis. BBC Wales, 10 April 2026.", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "The chatbot came back with a list of possible conditions, including hereditary spastic paraplegia." }, { "kind": "news report", "citation": "Phillips E / SWNS (2026). Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety. WalesOnline, 6 April 2026.", "title": "Cardiff woman uses Chat GPT to uncover rare condition doctor thought was anxiety", "url": "https://www.walesonline.co.uk/news/wales-news/cardiff-woman-uses-chat-gpt-33722339", "date": "2026-04-06", "written_by": "independent", "quote": "Phoebe underwent genetic testing which confirmed in August 2025 that she had the complex quadriplegic type of the condition" }, { "kind": "news report", "citation": "Herbert D (2026). BBC Wales, 10 April 2026 (health board statement).", "title": "ChatGPT 'uncovered woman's rare condition' after years of misdiagnosis", "url": "https://www.bbc.com/news/articles/cx24njzzkgjo", "date": "2026-04-10", "written_by": "independent", "quote": "Cardiff and Vale University Health Board said: \"We are sorry to hear about Phoebe's experience while in our care.\"" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Cardiff teacher put her symptoms into ChatGPT after a coma; it listed hereditary spastic paraplegia, her GP called it plausible and genetic testing confirmed it in August 2025 (BBC, WalesOnline).", "account": "Phoebe Tesoriere, 23, from Cardiff, Wales, is a former special educational needs teacher. She had a limp since childhood. From 2022 she was diagnosed with epilepsy, then Todd's paralysis, and repeatedly told her symptoms were anxiety. In January 2025 she fell down stairs and spent months in hospital. In July 2025 a seizure left her in a coma (three days per BBC Wales, 48 hours per the SWNS report in WalesOnline). After discharge she entered her symptoms into ChatGPT. It returned a list of possible conditions including hereditary spastic paraplegia (HSP). She took the suggestion to her GP, who agreed it was a “plausible reason”. Genetic testing confirmed HSP, in August 2025 according to WalesOnline, which also reports the complex quadriplegic type. The first day of August is used because no day is given. There is no treatment. She uses a wheelchair, attends physiotherapy and is fundraising for a specialist chair. Cardiff and Vale University Health Board said it was “sorry to hear about Phoebe's experience while in our care”. It would not comment on an individual case. The account rests on her own statements to BBC Wales (10 April 2026) and SWNS (6 April 2026). No clinical document is among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT lists hereditary spastic paraplegia for Phoebe Tesoriere, 23, after four years of misdiagnosis; her GP agrees and genetic testing confirms it", "headline": "ChatGPT lists HSP for Phoebe Tesoriere; genetic testing confirms" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d355588efc47bda5156c54087fdc76185cc4bfe5d67496bee3285c5043edec3f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Phoebe Tesoriere, 23, from Cardiff, Wales, is a former special educational needs teacher. She had a limp since childhood. From 2022 she was diagnosed with epilepsy, then Todd's paralysis, and repeatedly told her symptoms were anxiety. In January 2025 she fell down stairs and spent months in hospital. In July 2025 a seizure left her in a coma (three days per BBC Wales, 48 hours per the SWNS report in WalesOnline). After discharge she entered her symptoms into ChatGPT. It returned a list of possible conditions including hereditary spastic paraplegia (HSP). She took the suggestion to her GP, who agreed it was a “plausible reason”. Genetic testing confirmed HSP, in August 2025 according to WalesOnline, which also reports the complex quadriplegic type. The first day of August is used because no day is given. There is no treatment. She uses a wheelchair, attends physiotherapy and is fundraising for a specialist chair. Cardiff and Vale University Health Board said it was “sorry to hear about Phoebe's experience while in our care”. It would not comment on an individual case. The account rests on her own statements to BBC Wales (10 April 2026) and SWNS (6 April 2026). No clinical document is among the sources.", "replication": { "produced_by": [ "A patient with a long list of concrete symptoms (gait, incontinence, sensory loss, reflex changes, seizures) and no settled diagnosis", "Entry of the symptom list into a general large language model (LLM)", "A GP willing to test a patient-sourced hypothesis and access to genetic testing" ], "must_hold": [ "The true condition is among the candidates the model lists and the patient pursues it", "Clinicians confirm by genetic testing rather than accepting the suggestion" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0134", "title": "ChatGPT names an insulinoma that three years of specialist visits had missed; a Madrid internist confirms it and surgery cures the 35-year-old", "summary": "ChatGPT suggested an insulinoma after three undiagnosed years; a glucose sensor and ER blood tests confirmed it and surgery cured him.", "date_observed": "2025-08-03", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Dani, 35, had three years of tingling, numbness, dizziness, double vision and a 15 kg weight gain. A neurologist and a primary-care doctor called them nothing important. He entered his symptoms, results and history into ChatGPT, which named an insulinoma as the likely cause. He bought a glucose sensor and recorded readings of 30 to 40 mg/dL. He went to an emergency department. An internist at Hospital Puerta de Hierro Majadahonda, Madrid, confirmed an insulinoma by blood tests. A month and a half later surgeons removed about two thirds of his pancreas and his symptoms went. His video was posted on Instagram on 3 August 2025. The dates of the query, visit and surgery were not given.", "category": "harm prevented", "unexpected": true, "purpose": "ChatGPT is a general-purpose conversational assistant. Dani used it as a diagnostic aid, entering symptoms, results and history. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted that. So this benefit lay outside the product's stated purpose.", "system": "ChatGPT", "model_version": "Not named; Dani said he used 'el modelo más inteligente de ChatGPT' (the most intelligent ChatGPT model)", "developer": "OpenAI", "deployer": null, "location": "Majadahonda, Spain", "domain": "Healthcare (rare-disease diagnosis)", "segment": "Consumer use of a general chatbot as a diagnostic aid", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-08-05-7bae" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A tumor that had gone undiagnosed for three years, producing glucose readings of 30 to 40 mg/dL, was found and removed. Dani says he is cured. He and the outlets call it life-saving (El Español: episodes that could have ended in fainting, brain damage or death). But that counterfactual and the whole chain rest on his own account. No clinician has spoken." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT produced the insulinoma hypothesis from a history that two doctors had reviewed without reaching it. That prompted the glucose sensor and the emergency visit. The diagnosis was made by an internist who, Dani wrote, “lo identificó sin nosotros decirle lo que creíamos que era”. The surgery and recovery were the hospital's work. Dani says he is not a doctor but has “formación biosanitaria de muchos años”, which let him understand what he was doing. Every account traces to his own video." }, "evidence": [ { "kind": "news report", "citation": "Daniel Verdú / El Español (2025). Un enfermo de cáncer de páncreas de 35 años, muy rotundo: 'ChatGPT detectó mi tumor antes que los médicos'. El Español, 5 August 2025.", "title": "Un enfermo de cáncer de páncreas de 35 años, muy rotundo: \"ChatGPT detectó mi tumor antes que los médicos\"", "url": "https://www.elespanol.com/ciencia/20250805/enfermo-cancer-pancreas-anos-rotundo-chatgpt-detecto-tumor-medicos/1003743876208_0.html", "date": "2025-08-05", "written_by": "independent", "quote": "Tras unas analíticas, la internista confirmó lo que ChatGPT había sugerido: efectivamente tenía un insulinoma." }, { "kind": "news report", "citation": "Bartolomé Saorin Rios / MARCA (2025). Gracias a ChatGPT descubre que tiene cáncer de páncreas: 'Ha marcado un antes y un después en nuestras vidas'. MARCA, 5 August 2025.", "title": "Gracias a ChatGPT descubre que tiene cáncer de páncreas: \"Ha marcado un antes y un después en nuestras vidas\"", "url": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "date": "2025-08-05", "written_by": "independent", "quote": "Este video está colgado en las redes de su pareja María Hernández-Alcalá y ya acumula más de 1 millón de visualizaciones." }, { "kind": "news report", "citation": "Candela Hornero / Telecinco (2025). ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico. Telecinco.es, 5 August 2025.", "title": "ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico", "url": "https://www.telecinco.es/noticias/salud/20250805/chatgpt-ayuda-descubrir-cancer-pancreas-anos-sin-diagnostico_18_016301459.html", "date": "2025-08-05", "written_by": "independent", "quote": "ChatGPT detectó mi tumor antes que los médicos y hoy me operan del páncreas gracias a su diagnóstico" }, { "kind": "other", "citation": "María Hernández-Alcalá (@mariahalcala) (2025). Instagram reel carrying Dani's video and his written clarification. Instagram, 3 August 2025.", "title": "Esta historia ha marcado un antes y un después en nuestras vidas (Instagram reel DM508s_tAKz)", "url": "https://www.instagram.com/reel/DM508s_tAKz/", "date": "2025-08-03", "written_by": "beneficiary", "quote": "la internista del Puerta lo identificó sin nosotros decirle lo que creíamos que era" } ], "replication": { "produced_by": [ "A rare condition (Dani: “una enfermedad muy poco común (1 entre 1millon)”) with diffuse symptoms. A neurologist, after neck and brain magnetic resonance imaging (MRI) scans, and a primary-care doctor had dismissed them over three years.", "A user with “formación biosanitaria de muchos años” who entered the full symptom list, test results and clinical history into the chatbot. He could interpret its answer.", "A cheap self-test, a continuous glucose sensor, that could corroborate the hypothesis before the emergency visit. It read 30 to 40 mg/dL at night and between meals.", "An emergency internist at Puerta de Hierro who confirmed the insulinoma by blood tests, and a surgical team that removed two thirds of the pancreas." ], "must_hold": [ "The chatbot's hypothesis is treated as a reason to be tested, not as a diagnosis. Dani says he went to doctors before, during and after.", "The suspected condition has an objective marker that a patient or clinician can measure quickly.", "The user can state symptoms and prior results in enough detail for the model to rank a rare cause. Two doctors had the same information." ], "echoes": [ { "date": null, "setting": "AIBD-0038: ChatGPT proposes ALMS1 for a 44-year-old nephrology patient (consumer chatbot supplies a rare diagnosis that clinicians then confirm).", "model_version": null, "outcome": "unknown", "source": null }, { "date": null, "setting": "AIBD-0060: ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors.", "model_version": null, "outcome": "unknown", "source": null } ] }, "paired_incident": null, "headline": "ChatGPT names an insulinoma doctors missed for three years", "metric": "surgeons removed about two thirds of his pancreas and his symptoms went", "comparator": { "against": "three years of visits to specialists, including a neurologist, and a primary-care doctor", "before": "Tras varias pruebas le “dijeron que no era nada”", "after": "en pocos minutos su diagnóstico señalaba como posible principal causa de lo que me sucedía: un tumor de páncreas, un insulinoma", "basis": "assumed", "quote": "En ese momento de desesperación fue cuando decidió meter todos sus “síntomas, los resultados médicos, el historial clínico al modelo más inteligente de ChatGPT”, señaló. Y según él “en pocos minutos su diagnóstico señalaba como posible principal causa de lo que me sucedía: un tumor de páncreas, un insulinoma”.", "url": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html" }, "later": { "status": "unknown", "date": null, "note": "The surgery and the disappearance of his symptoms were already in the 3 August 2025 video; no later report on Dani was found, only re-reports of the same story.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented as the classifier proposed: the harm was specific (an undiagnosed insulinoma with glucose readings of 30 to 40 mg/dL) and the supporting evidence is the internist's confirmation and the surgery; the counterfactual that doctors would not have found it rests on three years without a diagnosis. The Monitor also lists El Imparcial, which adds “enfermero” and a Reuters credit that the first-hand sources do not support, so it was not used. The Instagram reel was dated from its page metadata (3 August 2025); the video opens with “hoy me operan”, so the surgery predates the post, but no date was found. No hospital statement was found.", "source": "https://oecd.ai/en/incidents/2025-08-05-7bae", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0134", "catalog_version": "1.0.0", "source_fingerprint": "0ceafd256de27fe7eee2f880df02c43a273967c01252679c08c75e916609ae73", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0134-source-0001", "AIBD-0134-source-0002", "AIBD-0134-source-0003", "AIBD-0134-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ChatGPT produced the insulinoma hypothesis from a history that two doctors had reviewed without reaching it. That prompted the glucose sensor and the emergency visit. The diagnosis was made by an internist who, Dani wrote, “lo identificó sin nosotros decirle lo que creíamos que era”. The surgery and recovery were the hospital's work. Dani says he is not a doctor but has “formación biosanitaria de muchos años”, which let him understand what he was doing. Every account traces to his own video." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "ChatGPT produced the insulinoma hypothesis from a history that two doctors had reviewed without reaching it. That prompted the glucose sensor and the emergency visit. The diagnosis was made by an internist who, Dani wrote, “lo identificó sin nosotros decirle lo que creíamos que era”. The surgery and recovery were the hospital's work. Dani says he is not a doctor but has “formación biosanitaria de muchos años”, which let him understand what he was doing. Every account traces to his own video." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A tumor that had gone undiagnosed for three years, producing glucose readings of 30 to 40 mg/dL, was found and removed. Dani says he is cured. He and the outlets call it life-saving (El Español: episodes that could have ended in fainting, brain damage or death). But that counterfactual and the whole chain rest on his own account. No clinician has spoken." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A tumor that had gone undiagnosed for three years, producing glucose readings of 30 to 40 mg/dL, was found and removed. Dani says he is cured. He and the outlets call it life-saving (El Español: episodes that could have ended in fainting, brain damage or death). But that counterfactual and the whole chain rest on his own account. No clinician has spoken." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Dani describes a tumor that remained undiagnosed for three years. He reports that his symptoms ended after surgery. 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The comparison is with his earlier three years without a diagnosis, not a controlled assessment." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Dani described his symptoms, glucose readings, diagnosis, and surgery in his own video account." } }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Glucose level, symptoms, and response to surgery." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "No treating clinician or medical record independently confirms the account. The reports do not establish whether the chatbot prevented death." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-08-05-7bae" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The surgery and the disappearance of his symptoms were already in the 3 August 2025 video; no later report on Dani was found, only re-reports of the same story." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0134" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Dani, a 35-year-old man in Madrid." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Dani, a 35-year-old man in Madrid." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "One person." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "One person." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Dani, 35, had three years of tingling, numbness, dizziness, double vision and a 15 kg weight gain. A neurologist and a primary-care doctor called them nothing important. He entered his symptoms, results and history into ChatGPT, which named an insulinoma as the likely cause. He bought a glucose sensor and recorded readings of 30 to 40 mg/dL. He went to an emergency department. An internist at Hospital Puerta de Hierro Majadahonda, Madrid, confirmed an insulinoma by blood tests. A month and a half later surgeons removed about two thirds of his pancreas and his symptoms went. His video was posted on Instagram on 3 August 2025. The dates of the query, visit and surgery were not given.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Dani reports that a chatbot suggestion led him to seek further tests, after which doctors diagnosed and removed an insulinoma." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A tumor that had gone undiagnosed for three years, producing glucose readings of 30 to 40 mg/dL, was found and removed. Dani says he is cured. He and the outlets call it life-saving (El Español: episodes that could have ended in fainting, brain damage or death). But that counterfactual and the whole chain rest on his own account. No clinician has spoken." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": true, "purpose": "ChatGPT is a general-purpose conversational assistant. Dani used it as a diagnostic aid, entering symptoms, results and history. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted that. So this benefit lay outside the product's stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Majadahonda, Spain", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose conversational assistant. Dani used it as a diagnostic aid, entering symptoms, results and history. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted that. So this benefit lay outside the product's stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-03", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented as the classifier proposed: the harm was specific (an undiagnosed insulinoma with glucose readings of 30 to 40 mg/dL) and the supporting evidence is the internist's confirmation and the surgery; the counterfactual that doctors would not have found it rests on three years without a diagnosis. The Monitor also lists El Imparcial, which adds “enfermero” and a Reuters credit that the first-hand sources do not support, so it was not used. The Instagram reel was dated from its page metadata (3 August 2025); the video opens with “hoy me operan”, so the surgery predates the post, but no date was found. No hospital statement was found.", "source": "https://oecd.ai/en/incidents/2025-08-05-7bae", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A rare condition (Dani: “una enfermedad muy poco común (1 entre 1millon)”) with diffuse symptoms. A neurologist, after neck and brain magnetic resonance imaging (MRI) scans, and a primary-care doctor had dismissed them over three years.", "A user with “formación biosanitaria de muchos años” who entered the full symptom list, test results and clinical history into the chatbot. He could interpret its answer.", "A cheap self-test, a continuous glucose sensor, that could corroborate the hypothesis before the emergency visit. It read 30 to 40 mg/dL at night and between meals.", "An emergency internist at Puerta de Hierro who confirmed the insulinoma by blood tests, and a surgical team that removed two thirds of the pancreas." ], "must_hold": [ "The chatbot's hypothesis is treated as a reason to be tested, not as a diagnosis. Dani says he went to doctors before, during and after.", "The suspected condition has an objective marker that a patient or clinician can measure quickly.", "The user can state symptoms and prior results in enough detail for the model to rank a rare cause. Two doctors had the same information." ], "echoes": [ { "setting": "AIBD-0038: ChatGPT proposes ALMS1 for a 44-year-old nephrology patient (consumer chatbot supplies a rare diagnosis that clinicians then confirm).", "outcome": "unknown" }, { "setting": "AIBD-0060: ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors.", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A rare condition (Dani: “una enfermedad muy poco común (1 entre 1millon)”) with diffuse symptoms. A neurologist, after neck and brain magnetic resonance imaging (MRI) scans, and a primary-care doctor had dismissed them over three years.", "A user with “formación biosanitaria de muchos años” who entered the full symptom list, test results and clinical history into the chatbot. He could interpret its answer.", "A cheap self-test, a continuous glucose sensor, that could corroborate the hypothesis before the emergency visit. It read 30 to 40 mg/dL at night and between meals.", "An emergency internist at Puerta de Hierro who confirmed the insulinoma by blood tests, and a surgical team that removed two thirds of the pancreas." ], "must_hold": [ "The chatbot's hypothesis is treated as a reason to be tested, not as a diagnosis. Dani says he went to doctors before, during and after.", "The suspected condition has an objective marker that a patient or clinician can measure quickly.", "The user can state symptoms and prior results in enough detail for the model to rank a rare cause. Two doctors had the same information." ], "echoes": [ { "setting": "AIBD-0038: ChatGPT proposes ALMS1 for a 44-year-old nephrology patient (consumer chatbot supplies a rare diagnosis that clinicians then confirm).", "outcome": "unknown" }, { "setting": "AIBD-0060: ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors.", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "A clinician needs to investigate the suggestion. Here, the suspected condition had a marker that the patient could measure with a glucose sensor, and doctors confirmed it with blood tests." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as specific harm prevented as the classifier proposed: the harm was specific (an undiagnosed insulinoma with glucose readings of 30 to 40 mg/dL) and the supporting evidence is the internist's confirmation and the surgery; the counterfactual that doctors would not have found it rests on three years without a diagnosis. The Monitor also lists El Imparcial, which adds “enfermero” and a Reuters credit that the first-hand sources do not support, so it was not used. The Instagram reel was dated from its page metadata (3 August 2025); the video opens with “hoy me operan”, so the surgery predates the post, but no date was found. No hospital statement was found.", "source": "https://oecd.ai/en/incidents/2025-08-05-7bae", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (rare-disease diagnosis)", "segment": "Consumer use of a general chatbot as a diagnostic aid" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Daniel Verdú / El Español (2025). Un enfermo de cáncer de páncreas de 35 años, muy rotundo: 'ChatGPT detectó mi tumor antes que los médicos'. El Español, 5 August 2025.", "title": "Un enfermo de cáncer de páncreas de 35 años, muy rotundo: \"ChatGPT detectó mi tumor antes que los médicos\"", "url": "https://www.elespanol.com/ciencia/20250805/enfermo-cancer-pancreas-anos-rotundo-chatgpt-detecto-tumor-medicos/1003743876208_0.html", "date": "2025-08-05", "written_by": "independent", "quote": "Tras unas analíticas, la internista confirmó lo que ChatGPT había sugerido: efectivamente tenía un insulinoma." }, { "kind": "news report", "citation": "Bartolomé Saorin Rios / MARCA (2025). Gracias a ChatGPT descubre que tiene cáncer de páncreas: 'Ha marcado un antes y un después en nuestras vidas'. MARCA, 5 August 2025.", "title": "Gracias a ChatGPT descubre que tiene cáncer de páncreas: \"Ha marcado un antes y un después en nuestras vidas\"", "url": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "date": "2025-08-05", "written_by": "independent", "quote": "Este video está colgado en las redes de su pareja María Hernández-Alcalá y ya acumula más de 1 millón de visualizaciones." }, { "kind": "news report", "citation": "Candela Hornero / Telecinco (2025). ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico. Telecinco.es, 5 August 2025.", "title": "ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico", "url": "https://www.telecinco.es/noticias/salud/20250805/chatgpt-ayuda-descubrir-cancer-pancreas-anos-sin-diagnostico_18_016301459.html", "date": "2025-08-05", "written_by": "independent", "quote": "ChatGPT detectó mi tumor antes que los médicos y hoy me operan del páncreas gracias a su diagnóstico" }, { "kind": "other", "citation": "María Hernández-Alcalá (@mariahalcala) (2025). Instagram reel carrying Dani's video and his written clarification. Instagram, 3 August 2025.", "title": "Esta historia ha marcado un antes y un después en nuestras vidas (Instagram reel DM508s_tAKz)", "url": "https://www.instagram.com/reel/DM508s_tAKz/", "date": "2025-08-03", "written_by": "beneficiary", "quote": "la internista del Puerta lo identificó sin nosotros decirle lo que creíamos que era" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0134-source-0001", "AIBD-0134-source-0002", "AIBD-0134-source-0003", "AIBD-0134-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Daniel Verdú / El Español (2025). Un enfermo de cáncer de páncreas de 35 años, muy rotundo: 'ChatGPT detectó mi tumor antes que los médicos'. El Español, 5 August 2025.", "title": "Un enfermo de cáncer de páncreas de 35 años, muy rotundo: \"ChatGPT detectó mi tumor antes que los médicos\"", "url": "https://www.elespanol.com/ciencia/20250805/enfermo-cancer-pancreas-anos-rotundo-chatgpt-detecto-tumor-medicos/1003743876208_0.html", "date": "2025-08-05", "written_by": "independent", "quote": "Tras unas analíticas, la internista confirmó lo que ChatGPT había sugerido: efectivamente tenía un insulinoma." }, { "kind": "news report", "citation": "Bartolomé Saorin Rios / MARCA (2025). Gracias a ChatGPT descubre que tiene cáncer de páncreas: 'Ha marcado un antes y un después en nuestras vidas'. MARCA, 5 August 2025.", "title": "Gracias a ChatGPT descubre que tiene cáncer de páncreas: \"Ha marcado un antes y un después en nuestras vidas\"", "url": "https://www.marca.com/tecnologia/2025/08/05/gracias-chatgpt-descubre-cancer-pancreas-marcado-despues-vidas.html", "date": "2025-08-05", "written_by": "independent", "quote": "Este video está colgado en las redes de su pareja María Hernández-Alcalá y ya acumula más de 1 millón de visualizaciones." }, { "kind": "news report", "citation": "Candela Hornero / Telecinco (2025). ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico. Telecinco.es, 5 August 2025.", "title": "ChatGPT le ayuda a descubrir que tiene cáncer de páncreas tras años sin diagnóstico", "url": "https://www.telecinco.es/noticias/salud/20250805/chatgpt-ayuda-descubrir-cancer-pancreas-anos-sin-diagnostico_18_016301459.html", "date": "2025-08-05", "written_by": "independent", "quote": "ChatGPT detectó mi tumor antes que los médicos y hoy me operan del páncreas gracias a su diagnóstico" }, { "kind": "other", "citation": "María Hernández-Alcalá (@mariahalcala) (2025). Instagram reel carrying Dani's video and his written clarification. Instagram, 3 August 2025.", "title": "Esta historia ha marcado un antes y un después en nuestras vidas (Instagram reel DM508s_tAKz)", "url": "https://www.instagram.com/reel/DM508s_tAKz/", "date": "2025-08-03", "written_by": "beneficiary", "quote": "la internista del Puerta lo identificó sin nosotros decirle lo que creíamos que era" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ChatGPT suggested an insulinoma after three undiagnosed years; a glucose sensor and ER blood tests confirmed it and surgery cured him.", "account": "Dani, 35, had three years of tingling, numbness, dizziness, double vision and a 15 kg weight gain. A neurologist and a primary-care doctor called them nothing important. He entered his symptoms, results and history into ChatGPT, which named an insulinoma as the likely cause. He bought a glucose sensor and recorded readings of 30 to 40 mg/dL. He went to an emergency department. An internist at Hospital Puerta de Hierro Majadahonda, Madrid, confirmed an insulinoma by blood tests. A month and a half later surgeons removed about two thirds of his pancreas and his symptoms went. His video was posted on Instagram on 3 August 2025. The dates of the query, visit and surgery were not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "ChatGPT suggested insulinoma as a possible explanation for the reported symptoms." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Dani described using the most intelligent model available in ChatGPT. The account does not name that model." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not named; Dani said he used 'el modelo más inteligente de ChatGPT' (the most intelligent ChatGPT model)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT names an insulinoma that three years of specialist visits had missed; a Madrid internist confirms it and surgery cures the 35-year-old", "headline": "ChatGPT names an insulinoma doctors missed for three years" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0ceafd256de27fe7eee2f880df02c43a273967c01252679c08c75e916609ae73" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Dani, 35, had three years of tingling, numbness, dizziness, double vision and a 15 kg weight gain. A neurologist and a primary-care doctor called them nothing important. He entered his symptoms, results and history into ChatGPT, which named an insulinoma as the likely cause. He bought a glucose sensor and recorded readings of 30 to 40 mg/dL. He went to an emergency department. An internist at Hospital Puerta de Hierro Majadahonda, Madrid, confirmed an insulinoma by blood tests. A month and a half later surgeons removed about two thirds of his pancreas and his symptoms went. His video was posted on Instagram on 3 August 2025. The dates of the query, visit and surgery were not given.", "replication": { "produced_by": [ "A rare condition (Dani: “una enfermedad muy poco común (1 entre 1millon)”) with diffuse symptoms. A neurologist, after neck and brain magnetic resonance imaging (MRI) scans, and a primary-care doctor had dismissed them over three years.", "A user with “formación biosanitaria de muchos años” who entered the full symptom list, test results and clinical history into the chatbot. He could interpret its answer.", "A cheap self-test, a continuous glucose sensor, that could corroborate the hypothesis before the emergency visit. It read 30 to 40 mg/dL at night and between meals.", "An emergency internist at Puerta de Hierro who confirmed the insulinoma by blood tests, and a surgical team that removed two thirds of the pancreas." ], "must_hold": [ "The chatbot's hypothesis is treated as a reason to be tested, not as a diagnosis. Dani says he went to doctors before, during and after.", "The suspected condition has an objective marker that a patient or clinician can measure quickly.", "The user can state symptoms and prior results in enough detail for the model to rank a rare cause. Two doctors had the same information." ], "echoes": [ { "setting": "AIBD-0038: ChatGPT proposes ALMS1 for a 44-year-old nephrology patient (consumer chatbot supplies a rare diagnosis that clinicians then confirm).", "outcome": "unknown" }, { "setting": "AIBD-0060: ChatGPT suggests tethered cord syndrome for a child seen by 17 doctors.", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Dani entered his symptoms, test results, and medical history into ChatGPT. He used a glucose sensor that recorded readings of 30 to 40 mg/dL, then sought emergency care. An internist confirmed the insulinoma, and a surgical team that treated him removed about two-thirds of his pancreas." } } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 35, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0135", "title": "Daejeon's AI care robot Kkumdori hears a woman in her 70s, alone at 2 a.m., repeat “I want to die” and “save me”; its alert brings police and a hospital admission", "summary": "At 2 a.m. on 6 August 2025 Daejeon's Kkumdori care robot flagged a 70s woman's “I want to die”; police came and she was admitted next day.", "date_observed": "2025-08-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At about 2 a.m. on 6 August 2025, a woman in her 70s identified as “A” was at home in Deogam-dong, Daedeok-gu, Daejeon, South Korea. She lives alone and has schizophrenia and bipolar disorder. She repeatedly told the city-issued AI care robot Kkumdori “I want to die” and “save me”. The robot's crisis-detection algorithm flagged the words and alerted the operator's control center. A staff member phoned her. When she kept repeating them, staff reported to police on 112 with her location. Officers found her emotionally unstable and contacted her family. Police judged hospital treatment urgent. On the afternoon of 7 August she was admitted with her guardian's consent. Daejeon announced the case on 13 August 2025.", "category": "protective response", "unexpected": false, "purpose": "Daejeon issued 1,000 Kkumdori robots from January 2025, 200 per district, under its community integrated-care project. They went to elderly, disabled and low-income people living alone. They offer companionship, medication and schedule reminders and health monitoring. They detect crisis signs such as suicide risk and depression and automatically notify agencies and guardians. The alert was that function.", "system": "AI care robot 'Kkumdori' (AI 돌봄로봇 꿈돌이), a conversational companion robot in the shape of Daejeon's mascot, with a crisis-detection algorithm linked to a 24-hour control center", "model_version": "Not named; Donga Ilbo reports that the robot 'applies ChatGPT 4.0 technology' for two-way conversation", "developer": "Not named in the 2025 reports, which say only '해당 업체' (the company) runs the control system; the 2022 pilot robots in the same mascot form were supplied by Mr. Mind (미스터마인드) under an MOU with Daejeon (ZDNet Korea, 5 April 2022)", "deployer": "Daejeon Metropolitan City (대전시), Daejeon-style community integrated care project, with the supplier's control center", "location": "Daejeon, South Korea", "domain": "Social welfare (home care for people living alone)", "segment": "Municipal elder-care robots", "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health.", "registry_ids": { "oecd_aim": "2025-08-13-0c3b" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A woman in her 70s living alone, with schizophrenia and bipolar disorder, was in acute crisis at 2 a.m. She got a check-in call, a police visit that night and protective hospital admission the next afternoon. The city and the headlines call it life-saving. But no attempt was reported, so the counterfactual is unproven. Her guardian said the robot being beside her was a great support." }, { "group": "organizational", "depth": 1, "reason": "Daejeon's welfare office gained a demonstrated case for its 1,000-robot program. Its director cited it as a model. A 2026 Yonhap report says the city will continue the policy on the strength of such cases." } ], "ai_role": { "status": "assessed", "statement": "The robot's crisis-detection algorithm recognized repeated danger words (“죽고 싶다”, “살려줘”) in conversation at 2 a.m. It sent an alert to a human control center. People did everything after that: the check-in call, the 112 report with location, the police visit, the family contact and the admission. The city's welfare director says the alert is what made the rapid dispatch and protection possible. Whether A would have come to harm that night is not established. Every account derives from the city's 13 August briefing." }, "evidence": [ { "kind": "news report", "citation": "Kim Jun-beom (김준범) / Yonhap News (2025). '돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조. Yonhap News Agency, Daejeon, 13 August 2025.", "title": "'돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조", "url": "https://www.yna.co.kr/view/AKR20250813050400063", "date": "2025-08-13", "written_by": "independent", "quote": "위험 발언을 감지한 돌봄 로봇은 해당 업체가 운영하는 관제시스템에 통보했고, 업체 측은 지구대에 현장 출동을 요청했다" }, { "kind": "news report", "citation": "Lee Bo-bae (이보배) / Hankyung (2025). 대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다. The Korea Economic Daily, 13 August 2025.", "title": "대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다", "url": "https://www.hankyung.com/article/2025081394957", "date": "2025-08-13", "written_by": "independent", "quote": "보호자는 \"로봇이 곁에 있어 줘서 할머니에게 큰 힘이 됐다\"고 전했다" }, { "kind": "news report", "citation": "Money Today (2025). \"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다. Money Today, 13 August 2025.", "title": "\"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다", "url": "https://news.mt.co.kr/mtview.php?no=2025081321115894713", "date": "2025-08-13", "written_by": "independent", "quote": "지난 6일 새벽 2시쯤 대전 더덕구 덕암동 빌라에 홀로 거주 중인 70대 A씨는 AI 돌봄로봇 '꿈돌이'와 대화 중 \"죽고 싶다\", \"살려줘\"라는 말을 반복했다" }, { "kind": "news report", "citation": "Kyunghyang Shinmun (2025). \"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청. Kyunghyang Shinmun, 13 August 2025.", "title": "\"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청", "url": "https://www.khan.co.kr/article/202508132034005", "date": "2025-08-13", "written_by": "independent", "quote": "돌봄로봇이 새벽 시간 어르신의 절박한 위기 신호를 포착해 경찰과 보호자의 신속한 출동 및 보호 조치가 가능하도록 한 사례" }, { "kind": "news report", "citation": "Song Chi-hoon (송치훈) / Donga Ilbo (2025). 노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고. Donga Ilbo, 13 August 2025.", "title": "노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고", "url": "https://www.donga.com/news/Society/article/all/20250813/132180422/2", "date": "2025-08-13", "written_by": "independent", "quote": "해당 로봇은 ChatGPT 4.0 기술이 적용돼 양방향 소통이 가능하다" }, { "kind": "news report", "citation": "Jeong Seo-yeon (정서연) / Yonhap News TV (2025). \"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'. Yonhap News TV, 13 August 2025.", "title": "\"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'", "url": "https://www.yonhapnewstv.co.kr/news/AKR20250813142450392", "date": "2025-08-13", "written_by": "independent", "quote": "꿈돌이 덕에 A 씨는 다음 날 오후 보호자 동의를 받고 안전하게 입원 조치됐습니다" }, { "kind": "news report", "citation": "Yoon Sang-eun (윤상은) / ZDNet Korea (2022). 미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결 (reporting the company's announcement). ZDNet Korea, 5 April 2022.", "title": "미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결", "url": "https://zdnet.co.kr/view/?no=20220405104411", "date": "2022-04-05", "written_by": "independent", "quote": "대전광역시의 마스코트인 꿈돌이, 꿈순이 캐릭터로 제작된 인공지능 돌봄로봇을 보급해" }, { "kind": "news report", "citation": "Lee Jae-rim (이재림) / Yonhap News (2026). '생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할. Yonhap News Agency, Daejeon, 1 August 2026.", "title": "'생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할", "url": "https://www.yna.co.kr/view/AKR20260731144200063", "date": "2026-08-01", "written_by": "independent", "quote": "대전시는 지난해 1월부터 AI 돌봄 로봇을 5개 자치구에 200대씩 보급해 총 1천대를 운용하고 있다" } ], "replication": { "produced_by": [ "A municipal program that put conversational robots with a crisis-word detection algorithm into 1,000 homes of people living alone, 200 per district, from January 2025.", "A 24-hour human control center run by the supplier that receives alerts, phones the resident, and reports to police (112) with the location.", "A resident who habitually talked, sang and danced with the robot, so her statements at 2 a.m. were spoken aloud to it.", "Police able to attend at night, and a family and hospital able to complete a protective admission the next day." ], "must_hold": [ "Alerts go to humans who act at night. The robot itself does nothing beyond detecting words and raising the alarm.", "The detection catches explicit statements (“죽고 싶다”, “살려줘”). A silent crisis would not trigger it.", "Residents keep talking to the device. Her guardian said it was a great support to her." ], "echoes": [ { "date": null, "setting": "Yonhap, 1 August 2026: at about midnight on 20 July 2026 an 80-something in Daejeon's Seo-gu with severe abdominal pain told the care robot to call 119; the control center relayed it, paramedics arrived at about 00:30 and took the person to hospital (https://www.yna.co.kr/view/AKR20260731144200063).", "model_version": null, "outcome": "unknown", "source": null }, { "date": null, "setting": "Yonhap, 1 August 2026: in November 2025 an 80-something in Daedeok-gu, badly hurt after falling from bed, called “Aria, help me” to an AI speaker at home and was rescued by 119 (same article).", "model_version": null, "outcome": "unknown", "source": null } ] }, "paired_incident": null, "headline": "Daejeon's Kkumdori robot hears “I want to die” and brings police", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-07-20", "note": "Yonhap reported on 1 August 2026 that Daejeon's 1,000 care robots remain in service and that on 20 July 2026 a robot in Seo-gu relayed an 80-something's call for 119 during severe abdominal pain, with paramedics arriving at about 00:30; it recounts the 2025 Kkumdori case as an earlier example.", "quote": "1일 대전시와 각 자치구에 따르면 지난달 20일 대전 서구에서는 자정께 심한 복통을 호소하던 80대 노인의 절박한 구조 요청이 AI 돌봄 로봇을 통해 119로 전달됐다.", "url": "https://www.yna.co.kr/view/AKR20260731144200063" }, "value": null, "developer_country": null, "deployer_country": "South Korea", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective chain (alert, check-in call, 112 report, police visit, next-day admission) is documented by many outlets quoting the city's 13 August 2025 briefing and its welfare director Kim Jong-min, but no attempt was reported and nothing shows what would have happened without the alert. The Monitor's “70-year-old” renders “70대” (in her 70s); Hankyung and Kookmin Ilbo say a woman and her guardian calls her “할머니”, so one outlet's auto-summary “남성” was discarded. Money Today adds Deogam-dong. The supplier is unnamed in 2025 reports; ZDNet Korea (2022) records Mr. Mind's MOU for the pilot robots in the same mascot form, which may or may not cover the 2025 batch. No city press release could be retrieved (daejeon.go.kr returned an error page).", "source": "https://oecd.ai/en/incidents/2025-08-13-0c3b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.yna.co.kr/view/AKR20260731144200063", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Daejeon", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: eight independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0135", "catalog_version": "1.0.0", "source_fingerprint": "aadaf4cc21be35ab29913367bbdd95d1bb7b6ba61f12497aacbb1997f5ccd912", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0135-source-0001", "AIBD-0135-source-0002", "AIBD-0135-source-0003", "AIBD-0135-source-0004", "AIBD-0135-source-0005", "AIBD-0135-source-0006", "AIBD-0135-source-0007", "AIBD-0135-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not named in the 2025 reports, which say only '해당 업체' (the company) runs the control system; the 2022 pilot robots in the same mascot form were supplied by Mr. Mind (미스터마인드) under an MOU with Daejeon (ZDNet Korea, 5 April 2022)", "deployer": "Daejeon Metropolitan City (대전시), Daejeon-style community integrated care project, with the supplier's control center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The robot's crisis-detection algorithm recognized repeated danger words (“죽고 싶다”, “살려줘”) in conversation at 2 a.m. It sent an alert to a human control center. People did everything after that: the check-in call, the 112 report with location, the police visit, the family contact and the admission. The city's welfare director says the alert is what made the rapid dispatch and protection possible. Whether A would have come to harm that night is not established. Every account derives from the city's 13 August briefing." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The robot's crisis-detection algorithm recognized repeated danger words (“죽고 싶다”, “살려줘”) in conversation at 2 a.m. It sent an alert to a human control center. People did everything after that: the check-in call, the 112 report with location, the police visit, the family contact and the admission. The city's welfare director says the alert is what made the rapid dispatch and protection possible. Whether A would have come to harm that night is not established. Every account derives from the city's 13 August briefing." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A woman in her 70s living alone, with schizophrenia and bipolar disorder, was in acute crisis at 2 a.m. She got a check-in call, a police visit that night and protective hospital admission the next afternoon. The city and the headlines call it life-saving. But no attempt was reported, so the counterfactual is unproven. Her guardian said the robot being beside her was a great support." }, { "group": "organizational", "depth": 1, "reason": "Daejeon's welfare office gained a demonstrated case for its 1,000-robot program. Its director cited it as a model. A 2026 Yonhap report says the city will continue the policy on the strength of such cases." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: eight independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A woman in her 70s living alone, with schizophrenia and bipolar disorder, was in acute crisis at 2 a.m. She got a check-in call, a police visit that night and protective hospital admission the next afternoon. The city and the headlines call it life-saving. But no attempt was reported, so the counterfactual is unproven. Her guardian said the robot being beside her was a great support." }, { "group": "organizational", "depth": 1, "reason": "Daejeon's welfare office gained a demonstrated case for its 1,000-robot program. Its director cited it as a model. A 2026 Yonhap report says the city will continue the policy on the strength of such cases." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A woman in her 70s living alone, with schizophrenia and bipolar disorder, was in acute crisis at 2 a.m. She got a check-in call, a police visit that night and protective hospital admission the next afternoon. The city and the headlines call it life-saving. But no attempt was reported, so the counterfactual is unproven. Her guardian said the robot being beside her was a great support." }, { "group": "organizational", "depth": 1, "reason": "Daejeon's welfare office gained a demonstrated case for its 1,000-robot program. Its director cited it as a model. A 2026 Yonhap report says the city will continue the policy on the strength of such cases." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-08-13-0c3b" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-07-20", "note": "Yonhap reported on 1 August 2026 that Daejeon's 1,000 care robots remain in service and that on 20 July 2026 a robot in Seo-gu relayed an 80-something's call for 119 during severe abdominal pain, with paramedics arriving at about 00:30; it recounts the 2025 Kkumdori case as an earlier example.", "quote": "1일 대전시와 각 자치구에 따르면 지난달 20일 대전 서구에서는 자정께 심한 복통을 호소하던 80대 노인의 절박한 구조 요청이 AI 돌봄 로봇을 통해 119로 전달됐다.", "url": "https://www.yna.co.kr/view/AKR20260731144200063" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0135" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 2 a.m. on 6 August 2025, a woman in her 70s identified as “A” was at home in Deogam-dong, Daedeok-gu, Daejeon, South Korea. She lives alone and has schizophrenia and bipolar disorder. She repeatedly told the city-issued AI care robot Kkumdori “I want to die” and “save me”. The robot's crisis-detection algorithm flagged the words and alerted the operator's control center. A staff member phoned her. When she kept repeating them, staff reported to police on 112 with her location. Officers found her emotionally unstable and contacted her family. Police judged hospital treatment urgent. On the afternoon of 7 August she was admitted with her guardian's consent. Daejeon announced the case on 13 August 2025.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A woman in her 70s living alone, with schizophrenia and bipolar disorder, was in acute crisis at 2 a.m. She got a check-in call, a police visit that night and protective hospital admission the next afternoon. The city and the headlines call it life-saving. But no attempt was reported, so the counterfactual is unproven. Her guardian said the robot being beside her was a great support." }, { "group": "organizational", "depth": 1, "reason": "Daejeon's welfare office gained a demonstrated case for its 1,000-robot program. Its director cited it as a model. A 2026 Yonhap report says the city will continue the policy on the strength of such cases." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Daejeon issued 1,000 Kkumdori robots from January 2025, 200 per district, under its community integrated-care project. They went to elderly, disabled and low-income people living alone. They offer companionship, medication and schedule reminders and health monitoring. They detect crisis signs such as suicide risk and depression and automatically notify agencies and guardians. The alert was that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Daejeon, South Korea", "deployer_country": "South Korea" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Daejeon issued 1,000 Kkumdori robots from January 2025, 200 per district, under its community integrated-care project. They went to elderly, disabled and low-income people living alone. They offer companionship, medication and schedule reminders and health monitoring. They detect crisis signs such as suicide risk and depression and automatically notify agencies and guardians. The alert was that function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective chain (alert, check-in call, 112 report, police visit, next-day admission) is documented by many outlets quoting the city's 13 August 2025 briefing and its welfare director Kim Jong-min, but no attempt was reported and nothing shows what would have happened without the alert. The Monitor's “70-year-old” renders “70대” (in her 70s); Hankyung and Kookmin Ilbo say a woman and her guardian calls her “할머니”, so one outlet's auto-summary “남성” was discarded. Money Today adds Deogam-dong. The supplier is unnamed in 2025 reports; ZDNet Korea (2022) records Mr. Mind's MOU for the pilot robots in the same mascot form, which may or may not cover the 2025 batch. No city press release could be retrieved (daejeon.go.kr returned an error page).", "source": "https://oecd.ai/en/incidents/2025-08-13-0c3b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.yna.co.kr/view/AKR20260731144200063", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Daejeon", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A municipal program that put conversational robots with a crisis-word detection algorithm into 1,000 homes of people living alone, 200 per district, from January 2025.", "A 24-hour human control center run by the supplier that receives alerts, phones the resident, and reports to police (112) with the location.", "A resident who habitually talked, sang and danced with the robot, so her statements at 2 a.m. were spoken aloud to it.", "Police able to attend at night, and a family and hospital able to complete a protective admission the next day." ], "must_hold": [ "Alerts go to humans who act at night. The robot itself does nothing beyond detecting words and raising the alarm.", "The detection catches explicit statements (“죽고 싶다”, “살려줘”). A silent crisis would not trigger it.", "Residents keep talking to the device. Her guardian said it was a great support to her." ], "echoes": [ { "setting": "Yonhap, 1 August 2026: at about midnight on 20 July 2026 an 80-something in Daejeon's Seo-gu with severe abdominal pain told the care robot to call 119; the control center relayed it, paramedics arrived at about 00:30 and took the person to hospital (https://www.yna.co.kr/view/AKR20260731144200063).", "outcome": "unknown" }, { "setting": "Yonhap, 1 August 2026: in November 2025 an 80-something in Daedeok-gu, badly hurt after falling from bed, called “Aria, help me” to an AI speaker at home and was rescued by 119 (same article).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A municipal program that put conversational robots with a crisis-word detection algorithm into 1,000 homes of people living alone, 200 per district, from January 2025.", "A 24-hour human control center run by the supplier that receives alerts, phones the resident, and reports to police (112) with the location.", "A resident who habitually talked, sang and danced with the robot, so her statements at 2 a.m. were spoken aloud to it.", "Police able to attend at night, and a family and hospital able to complete a protective admission the next day." ], "must_hold": [ "Alerts go to humans who act at night. The robot itself does nothing beyond detecting words and raising the alarm.", "The detection catches explicit statements (“죽고 싶다”, “살려줘”). A silent crisis would not trigger it.", "Residents keep talking to the device. Her guardian said it was a great support to her." ], "echoes": [ { "setting": "Yonhap, 1 August 2026: at about midnight on 20 July 2026 an 80-something in Daejeon's Seo-gu with severe abdominal pain told the care robot to call 119; the control center relayed it, paramedics arrived at about 00:30 and took the person to hospital (https://www.yna.co.kr/view/AKR20260731144200063).", "outcome": "unknown" }, { "setting": "Yonhap, 1 August 2026: in November 2025 an 80-something in Daedeok-gu, badly hurt after falling from bed, called “Aria, help me” to an AI speaker at home and was rescued by 119 (same article).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective chain (alert, check-in call, 112 report, police visit, next-day admission) is documented by many outlets quoting the city's 13 August 2025 briefing and its welfare director Kim Jong-min, but no attempt was reported and nothing shows what would have happened without the alert. The Monitor's “70-year-old” renders “70대” (in her 70s); Hankyung and Kookmin Ilbo say a woman and her guardian calls her “할머니”, so one outlet's auto-summary “남성” was discarded. Money Today adds Deogam-dong. The supplier is unnamed in 2025 reports; ZDNet Korea (2022) records Mr. Mind's MOU for the pilot robots in the same mascot form, which may or may not cover the 2025 batch. No city press release could be retrieved (daejeon.go.kr returned an error page).", "source": "https://oecd.ai/en/incidents/2025-08-13-0c3b", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.yna.co.kr/view/AKR20260731144200063", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Daejeon", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Social welfare (home care for people living alone)", "segment": "Municipal elder-care robots" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kim Jun-beom (김준범) / Yonhap News (2025). '돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조. Yonhap News Agency, Daejeon, 13 August 2025.", "title": "'돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조", "url": "https://www.yna.co.kr/view/AKR20250813050400063", "date": "2025-08-13", "written_by": "independent", "quote": "위험 발언을 감지한 돌봄 로봇은 해당 업체가 운영하는 관제시스템에 통보했고, 업체 측은 지구대에 현장 출동을 요청했다" }, { "kind": "news report", "citation": "Lee Bo-bae (이보배) / Hankyung (2025). 대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다. The Korea Economic Daily, 13 August 2025.", "title": "대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다", "url": "https://www.hankyung.com/article/2025081394957", "date": "2025-08-13", "written_by": "independent", "quote": "보호자는 \"로봇이 곁에 있어 줘서 할머니에게 큰 힘이 됐다\"고 전했다" }, { "kind": "news report", "citation": "Money Today (2025). \"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다. Money Today, 13 August 2025.", "title": "\"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다", "url": "https://news.mt.co.kr/mtview.php?no=2025081321115894713", "date": "2025-08-13", "written_by": "independent", "quote": "지난 6일 새벽 2시쯤 대전 더덕구 덕암동 빌라에 홀로 거주 중인 70대 A씨는 AI 돌봄로봇 '꿈돌이'와 대화 중 \"죽고 싶다\", \"살려줘\"라는 말을 반복했다" }, { "kind": "news report", "citation": "Kyunghyang Shinmun (2025). \"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청. Kyunghyang Shinmun, 13 August 2025.", "title": "\"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청", "url": "https://www.khan.co.kr/article/202508132034005", "date": "2025-08-13", "written_by": "independent", "quote": "돌봄로봇이 새벽 시간 어르신의 절박한 위기 신호를 포착해 경찰과 보호자의 신속한 출동 및 보호 조치가 가능하도록 한 사례" }, { "kind": "news report", "citation": "Song Chi-hoon (송치훈) / Donga Ilbo (2025). 노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고. Donga Ilbo, 13 August 2025.", "title": "노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고", "url": "https://www.donga.com/news/Society/article/all/20250813/132180422/2", "date": "2025-08-13", "written_by": "independent", "quote": "해당 로봇은 ChatGPT 4.0 기술이 적용돼 양방향 소통이 가능하다" }, { "kind": "news report", "citation": "Jeong Seo-yeon (정서연) / Yonhap News TV (2025). \"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'. Yonhap News TV, 13 August 2025.", "title": "\"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'", "url": "https://www.yonhapnewstv.co.kr/news/AKR20250813142450392", "date": "2025-08-13", "written_by": "independent", "quote": "꿈돌이 덕에 A 씨는 다음 날 오후 보호자 동의를 받고 안전하게 입원 조치됐습니다" }, { "kind": "news report", "citation": "Yoon Sang-eun (윤상은) / ZDNet Korea (2022). 미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결 (reporting the company's announcement). ZDNet Korea, 5 April 2022.", "title": "미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결", "url": "https://zdnet.co.kr/view/?no=20220405104411", "date": "2022-04-05", "written_by": "independent", "quote": "대전광역시의 마스코트인 꿈돌이, 꿈순이 캐릭터로 제작된 인공지능 돌봄로봇을 보급해" }, { "kind": "news report", "citation": "Lee Jae-rim (이재림) / Yonhap News (2026). '생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할. Yonhap News Agency, Daejeon, 1 August 2026.", "title": "'생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할", "url": "https://www.yna.co.kr/view/AKR20260731144200063", "date": "2026-08-01", "written_by": "independent", "quote": "대전시는 지난해 1월부터 AI 돌봄 로봇을 5개 자치구에 200대씩 보급해 총 1천대를 운용하고 있다" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0135-source-0001", "AIBD-0135-source-0002", "AIBD-0135-source-0003", "AIBD-0135-source-0004", "AIBD-0135-source-0005", "AIBD-0135-source-0006", "AIBD-0135-source-0007", "AIBD-0135-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kim Jun-beom (김준범) / Yonhap News (2025). '돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조. Yonhap News Agency, Daejeon, 13 August 2025.", "title": "'돌봄로봇 꿈돌이'가 우울증 앓는 70대 신고해 구조", "url": "https://www.yna.co.kr/view/AKR20250813050400063", "date": "2025-08-13", "written_by": "independent", "quote": "위험 발언을 감지한 돌봄 로봇은 해당 업체가 운영하는 관제시스템에 통보했고, 업체 측은 지구대에 현장 출동을 요청했다" }, { "kind": "news report", "citation": "Lee Bo-bae (이보배) / Hankyung (2025). 대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다. The Korea Economic Daily, 13 August 2025.", "title": "대전 마스코트 '꿈돌이' 깜짝 근황…70대 여성 목숨 구했다", "url": "https://www.hankyung.com/article/2025081394957", "date": "2025-08-13", "written_by": "independent", "quote": "보호자는 \"로봇이 곁에 있어 줘서 할머니에게 큰 힘이 됐다\"고 전했다" }, { "kind": "news report", "citation": "Money Today (2025). \"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다. Money Today, 13 August 2025.", "title": "\"죽고싶어\" 함께 노래 부르던 할머니 이상 감지…'꿈돌이'가 구했다", "url": "https://news.mt.co.kr/mtview.php?no=2025081321115894713", "date": "2025-08-13", "written_by": "independent", "quote": "지난 6일 새벽 2시쯤 대전 더덕구 덕암동 빌라에 홀로 거주 중인 70대 A씨는 AI 돌봄로봇 '꿈돌이'와 대화 중 \"죽고 싶다\", \"살려줘\"라는 말을 반복했다" }, { "kind": "news report", "citation": "Kyunghyang Shinmun (2025). \"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청. Kyunghyang Shinmun, 13 August 2025.", "title": "\"죽고 싶어\" 반복하자…AI 돌봄로봇이 구조 요청", "url": "https://www.khan.co.kr/article/202508132034005", "date": "2025-08-13", "written_by": "independent", "quote": "돌봄로봇이 새벽 시간 어르신의 절박한 위기 신호를 포착해 경찰과 보호자의 신속한 출동 및 보호 조치가 가능하도록 한 사례" }, { "kind": "news report", "citation": "Song Chi-hoon (송치훈) / Donga Ilbo (2025). 노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고. Donga Ilbo, 13 August 2025.", "title": "노인돌봄 AI가 목숨 구했다…\"죽고 싶어\" 말 듣고 신고", "url": "https://www.donga.com/news/Society/article/all/20250813/132180422/2", "date": "2025-08-13", "written_by": "independent", "quote": "해당 로봇은 ChatGPT 4.0 기술이 적용돼 양방향 소통이 가능하다" }, { "kind": "news report", "citation": "Jeong Seo-yeon (정서연) / Yonhap News TV (2025). \"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'. Yonhap News TV, 13 August 2025.", "title": "\"살려줘\"…우울증 환자 위험 신호 포착해 구조한 돌봄로봇 '꿈돌이'", "url": "https://www.yonhapnewstv.co.kr/news/AKR20250813142450392", "date": "2025-08-13", "written_by": "independent", "quote": "꿈돌이 덕에 A 씨는 다음 날 오후 보호자 동의를 받고 안전하게 입원 조치됐습니다" }, { "kind": "news report", "citation": "Yoon Sang-eun (윤상은) / ZDNet Korea (2022). 미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결 (reporting the company's announcement). ZDNet Korea, 5 April 2022.", "title": "미스터마인드, 대전광역시와 '홀로어르신 AI 돌봄로봇' MOU 체결", "url": "https://zdnet.co.kr/view/?no=20220405104411", "date": "2022-04-05", "written_by": "independent", "quote": "대전광역시의 마스코트인 꿈돌이, 꿈순이 캐릭터로 제작된 인공지능 돌봄로봇을 보급해" }, { "kind": "news report", "citation": "Lee Jae-rim (이재림) / Yonhap News (2026). '생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할. Yonhap News Agency, Daejeon, 1 August 2026.", "title": "'생명 구한' AI돌봄 로봇…노인들 복통·우울증 등 위기서 역할", "url": "https://www.yna.co.kr/view/AKR20260731144200063", "date": "2026-08-01", "written_by": "independent", "quote": "대전시는 지난해 1월부터 AI 돌봄 로봇을 5개 자치구에 200대씩 보급해 총 1천대를 운용하고 있다" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At 2 a.m. on 6 August 2025 Daejeon's Kkumdori care robot flagged a 70s woman's “I want to die”; police came and she was admitted next day.", "account": "At about 2 a.m. on 6 August 2025, a woman in her 70s identified as “A” was at home in Deogam-dong, Daedeok-gu, Daejeon, South Korea. She lives alone and has schizophrenia and bipolar disorder. She repeatedly told the city-issued AI care robot Kkumdori “I want to die” and “save me”. The robot's crisis-detection algorithm flagged the words and alerted the operator's control center. A staff member phoned her. When she kept repeating them, staff reported to police on 112 with her location. Officers found her emotionally unstable and contacted her family. Police judged hospital treatment urgent. On the afternoon of 7 August she was admitted with her guardian's consent. Daejeon announced the case on 13 August 2025." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The robot detected signs of distress in conversation and alerted a human control center." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The report describes a robot that used ChatGPT technology for conversation. Its phrase “ChatGPT 4.0” does not identify a verified model release." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not named; Donga Ilbo reports that the robot 'applies ChatGPT 4.0 technology' for two-way conversation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI care robot 'Kkumdori' (AI 돌봄로봇 꿈돌이), a conversational companion robot in the shape of Daejeon's mascot, with a crisis-detection algorithm linked to a 24-hour control center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the 2025 reports, which say only '해당 업체' (the company) runs the control system; the 2022 pilot robots in the same mascot form were supplied by Mr. Mind (미스터마인드) under an MOU with Daejeon (ZDNet Korea, 5 April 2022)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Daejeon's AI care robot Kkumdori hears a woman in her 70s, alone at 2 a.m., repeat “I want to die” and “save me”; its alert brings police and a hospital admission", "headline": "Daejeon's Kkumdori robot hears “I want to die” and brings police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "aadaf4cc21be35ab29913367bbdd95d1bb7b6ba61f12497aacbb1997f5ccd912" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 2 a.m. on 6 August 2025, a woman in her 70s identified as “A” was at home in Deogam-dong, Daedeok-gu, Daejeon, South Korea. She lives alone and has schizophrenia and bipolar disorder. She repeatedly told the city-issued AI care robot Kkumdori “I want to die” and “save me”. The robot's crisis-detection algorithm flagged the words and alerted the operator's control center. A staff member phoned her. When she kept repeating them, staff reported to police on 112 with her location. Officers found her emotionally unstable and contacted her family. Police judged hospital treatment urgent. On the afternoon of 7 August she was admitted with her guardian's consent. Daejeon announced the case on 13 August 2025.", "replication": { "produced_by": [ "A municipal program that put conversational robots with a crisis-word detection algorithm into 1,000 homes of people living alone, 200 per district, from January 2025.", "A 24-hour human control center run by the supplier that receives alerts, phones the resident, and reports to police (112) with the location.", "A resident who habitually talked, sang and danced with the robot, so her statements at 2 a.m. were spoken aloud to it.", "Police able to attend at night, and a family and hospital able to complete a protective admission the next day." ], "must_hold": [ "Alerts go to humans who act at night. The robot itself does nothing beyond detecting words and raising the alarm.", "The detection catches explicit statements (“죽고 싶다”, “살려줘”). A silent crisis would not trigger it.", "Residents keep talking to the device. Her guardian said it was a great support to her." ], "echoes": [ { "setting": "Yonhap, 1 August 2026: at about midnight on 20 July 2026 an 80-something in Daejeon's Seo-gu with severe abdominal pain told the care robot to call 119; the control center relayed it, paramedics arrived at about 00:30 and took the person to hospital (https://www.yna.co.kr/view/AKR20260731144200063).", "outcome": "unknown" }, { "setting": "Yonhap, 1 August 2026: in November 2025 an 80-something in Daedeok-gu, badly hurt after falling from bed, called “Aria, help me” to an AI speaker at home and was rescued by 119 (same article).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0178", "title": "India's DoT disconnects over 82 lakh mobile connections flagged by its AI facial-recognition tool ASTR", "summary": "DoT's indigenous ASTR tool matches subscriber photos to find connections taken by one person under different names; a Rajya Sabha reply (August 2025) counts more than 82 lakh disconnected after fai...", "date_observed": "2025-08-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Department of Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "category": "general benefit", "unexpected": false, "purpose": "Analyze, identify and weed out fake, forged and non-bonafide mobile connections to curb cyber crime.", "system": "ASTR, AI and facial recognition powered Solution for Telecom SIM Subscriber Verification", "model_version": null, "developer": "Department of Telecommunications, Government of India", "deployer": "Department of Telecommunications with telecom service providers", "location": null, "domain": "Telecom-enabled cyber financial fraud", "segment": "SIM subscriber verification", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Disconnection counts are aggregates. No measured reduction in fraud losses is documented." }, { "group": "organizational", "depth": null, "reason": "DoT and operators report disconnections and blacklisting without an evaluated outcome." } ], "ai_role": { "status": "assessed", "statement": "DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases." }, "evidence": [ { "kind": "press release", "citation": "Press Information Bureau, Ministry of Communications, written reply in Rajya Sabha by Dr Pemmasani Chandra Sekhar, 7 August 2025", "title": "Telecom-Related Cyber Frauds and Safety Measures", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153524", "date": "2025-08-07", "written_by": "makers", "quote": "disconnected more than 82 lakhs such connections through ASTR after they failed reverification" }, { "kind": "press release", "citation": "Press Information Bureau Chennai, release issued by M. Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. The Hans India, 9 October 2026.", "title": "Govt disconnects over 82 lakh fraudulent mobile connections via ASTR", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "date": "2026-10-09", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "model_version": null, "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "model_version": null, "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "model_version": null, "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] }, "paired_incident": null, "headline": "India's DoT disconnects over 82 lakh connections flagged by ASTR", "metric": "disconnected more than 82 lakh connections through ASTR after they failed re-verification", "comparator": null, "later": { "status": "persisted", "date": "2026-10-09", "note": "Minister of State Pemmasani restated at the India Mobile Congress that over 82 lakh fraudulent connections had been disconnected through ASTR.", "quote": "India has disconnected over 82 lakh fraudulent mobile connections through the Artificial Intelligence and Facial Recognition powered Telecom SIM Subscriber Verification (ASTR) tool, Union Minister of State for Communications and Rural Development Dr Chandra Sekhar Pemmasani said on Friday.", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Department_of_Telecommunications; https://en.wikipedia.org/wiki/Department_of_Telecommunications", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Department of Telecommunications.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, a registry entry and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0178", "catalog_version": "1.0.0", "source_fingerprint": "0ee3171393b93d69f5590e3a237ee805a460dd658fb47df72b475010d5019a9c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0178-source-0001", "AIBD-0178-source-0002", "AIBD-0178-source-0003", "AIBD-0178-source-0004", "AIBD-0178-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Department of Telecommunications, Government of India", "deployer": "Department of Telecommunications with telecom service providers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, a registry entry and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Disconnection counts are aggregates. No measured reduction in fraud losses is documented." }, { "group": "organizational", "reason": "DoT and operators report disconnections and blacklisting without an evaluated outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Disconnection counts are aggregates. No measured reduction in fraud losses is documented." }, { "group": "organizational", "reason": "DoT and operators report disconnections and blacklisting without an evaluated outcome." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", 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ASTR.", "quote": "India has disconnected over 82 lakh fraudulent mobile connections through the Artificial Intelligence and Facial Recognition powered Telecom SIM Subscriber Verification (ASTR) tool, Union Minister of State for Communications and Rural Development Dr Chandra Sekhar Pemmasani said on Friday.", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0178" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources 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Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Disconnection counts are aggregates. 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https://en.wikipedia.org/wiki/Department_of_Telecommunications", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Department of Telecommunications.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "outcome": "unknown", "source": "Google News RSS headline only; 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Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. The Hans India, 9 October 2026.", "title": "Govt disconnects over 82 lakh fraudulent mobile connections via ASTR", "url": "https://www.thehansindia.com/business/govt-disconnects-over-82-lakh-fraudulent-mobile-connections-via-astr-1130704", "date": "2026-10-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0178-source-0001", "AIBD-0178-source-0002", "AIBD-0178-source-0003", "AIBD-0178-source-0004", "AIBD-0178-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Press Information Bureau, Ministry of Communications, written reply in Rajya Sabha by Dr Pemmasani Chandra Sekhar, 7 August 2025", "title": "Telecom-Related Cyber Frauds and Safety Measures", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2153524", "date": "2025-08-07", "written_by": "makers", "quote": "disconnected more than 82 lakhs such connections through ASTR after they failed reverification" }, { "kind": "press release", "citation": "Press Information Bureau Chennai, release issued by M. Venaiah, Director (Admin), O/o Special Director General Telecom, 8 May 2023", "title": "Department of Telecommunications Initiatives for curbing Cyber Crime", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=1922542", "date": "2023-05-08", "written_by": "makers", "quote": "ASTR has identified more than 50,000 non-bonafide mobile connections issued by Telecom Service Providers (TSP) in the State of Tamilnadu." }, { "kind": "news report", "citation": "PTI via The Hindu, Patna, 28 May 2023", "title": "17,000 extra SIM cards of subscribers beyond 9 connections deactivated in Bihar and Jharkhand", "url": "https://www.thehindu.com/news/national/17000-extra-sim-cards-of-subscribers-beyond-9-connections-deactivated-in-bihar-and-jharkhand/article66903692.ece", "date": "2023-05-28", "written_by": "independent", "quote": "Around 17,000 such numbers have been disconnected. Further analysis is going on to identify such numbers," }, { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2023-05-28-a3cc, classified AI Incident", "title": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns", "url": "https://oecd.ai/en/incidents/2023-05-28-a3cc", "date": "2023-05-28", "written_by": "independent", "quote": "AI Facial Recognition Leads to Mass SIM Card Deactivation in India Over Fraud Concerns" }, { "kind": "news report", "citation": "IANS via The Hans India (2026). Govt disconnects over 82 lakh fraudulent mobile connections via ASTR. 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ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ASTR, AI and facial recognition powered Solution for Telecom SIM Subscriber Verification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Department of Telecommunications, Government of India" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "India's DoT disconnects over 82 lakh mobile connections flagged by its AI facial-recognition tool ASTR", "headline": "India's DoT disconnects over 82 lakh connections flagged by ASTR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0ee3171393b93d69f5590e3a237ee805a460dd658fb47df72b475010d5019a9c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Department of Telecommunications (DoT), Government of India, states that it designed and implemented ASTR. ASTR, the “AI and facial recognition powered Solution for Telecom SIM Subscriber Verification”, is to identify and weed out fake, forged and non-bonafide mobile connections. A PIB Chennai release of 8 May 2023 reported that ASTR identified more than 50,000 non-bonafide connections in Tamil Nadu. All were disconnected by operators, with point-of-sale details handed to the Tamil Nadu Police Cyber Crime Wing. The Hindu (PTI, 28 May 2023) quoted a senior DoT official in Patna. The official said that ASTR analysis found at least 21,800 connections exceeding the nine-per-subscriber limit in Bihar and Jharkhand. Around 17,000 of them were disconnected, and operators blacklisted 2,900 points of sale. Minister of State Dr Pemmasani Chandra Sekhar gave a Rajya Sabha written reply, posted by PIB on 7 August 2025. He said that DoT disconnected more than 82 lakh connections through ASTR after they failed re-verification. The OECD AI Incidents Monitor records the Bihar and Jharkhand deactivations as an AI Incident citing privacy, misidentification and data-protection concerns. The cumulative figure carries the reply's posting date. No independent accuracy evaluation was found.", "replication": { "produced_by": [ "Subscriber KYC photographs held by operators, matched across names by facial recognition", "A legal cap of nine connections per subscriber defining violations" ], "must_hold": [ "A re-verification step whose failure triggers disconnection", "Point-of-sale accountability and police follow-up", "Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern" ], "echoes": [ { "date": "2023-05-08", "setting": "Tamil Nadu", "outcome": "recurred", "source": "PIB Chennai: more than 50,000 connections identified and disconnected" }, { "date": "2023-05-28", "setting": "Bihar and Jharkhand", "outcome": "recurred", "source": "The Hindu/PTI: around 17,000 of 21,800 disconnected" }, { "date": "2026-10-09", "setting": "Statement by MoS Pemmasani reported by The Statesman", "outcome": "unknown", "source": "Google News RSS headline only; article returned 403" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0238", "title": "DARPA's AIxCC final: autonomous systems find 54 of 63 synthetic vulnerabilities, patch 43, and surface 18 real bugs in open-source code", "summary": "At DEF CON 33 (8 August 2025) DARPA reported seven teams' systems found 54 synthetic vulnerabilities, patched 43, and found 18 real bugs for disclosure; Team Atlanta won $4 million.", "date_observed": "2025-08-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "DARPA's results release describes the Final Competition. Teams' cyber reasoning systems tried to find and patch synthetic vulnerabilities across 54 million lines of real-world open-source code. They found 54 unique synthetic vulnerabilities in 63 challenges and patched 43. They also found 18 real, non-synthetic vulnerabilities (six in C codebases, 12 in Java), now being responsibly disclosed. There were 11 patches for real bugs. The average cost was about $152 per task. Team Atlanta (Georgia Tech, Samsung Research, KAIST, POSTECH) won $4 million, Trail of Bits $3 million and Theori $1.5 million. Four of seven systems were released open source. The Record reported the same figures from Las Vegas with program manager Andrew Carney's remarks. curl maintainer Daniel Stenberg, whose project was among the targets, examined the injected curl flaws. He judged them straightforward and not deeply hidden.", "category": "general benefit", "unexpected": false, "purpose": "Autonomous AI systems that find and patch vulnerabilities in open-source software underlying critical infrastructure.", "system": "AIxCC finalist cyber reasoning systems (Team Atlanta, Trail of Bits, Theori and four others)", "model_version": null, "developer": "Seven finalist teams (Team Atlanta et al.), using LLM credits from Anthropic, Google and OpenAI", "deployer": "DARPA (with ARPA-H), AIxCC Final Competition", "location": "Las Vegas, United States", "domain": "Cybersecurity / automated vulnerability discovery and patching", "segment": "Government", "benefit_type": "Reduced Risk", "taxonomy_note": "A competition result; the real bugs found are read as risk reduced.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "Aggregate competition results. No specific attack or deployment outcome documented." }, { "group": "organizational", "depth": null, "reason": "Open-source maintainers received disclosures. No fix is individually documented in the sources." } ], "ai_role": { "status": "assessed", "statement": "DARPA, the organizer, reports the figures. The Record corroborates from the event. Stenberg's independent look at the curl tasks suggests the injected flaws were easy. That bounds how much the synthetic scores show." }, "evidence": [ { "kind": "press release", "citation": "DARPA, news release, 8 Aug 2025", "title": "AI Cyber Challenge marks pivotal inflection point for cyber defense", "url": "https://www.darpa.mil/news/2025/aixcc-results", "date": "2025-08-08", "written_by": "deployer", "quote": "In the Final Competition, teams also discovered 18 real, non-synthetic vulnerabilities that are being responsibly disclosed to open source project maintainers." }, { "kind": "news report", "citation": "Jonathan Greig, The Record from Recorded Future News, 8 Aug 2025", "title": "DARPA announces $4 million winner of AI code review competition at DEF CON", "url": "https://therecord.media/darpa-ai-code-competition-winner-def-con", "date": "2025-08-08", "written_by": "independent", "quote": "Overall, competitors found 54 unique synthetic vulnerabilities and were able to patch 43 of them — representing 77% of the synthetic vulnerabilities introduced." }, { "kind": "report", "citation": "Daniel Stenberg, daniel.haxx.se, 22 Oct 2025", "title": "AIxCC curl details", "url": "https://daniel.haxx.se/blog/2025/10/22/aixcc-curl-details/", "date": "2025-10-22", "written_by": "beneficiary", "quote": "As seen above here, they were all rather straight forward and not hidden or deeply layered very much." } ], "replication": { "produced_by": [ "Injected flaws in real open-source projects with scoring for proofs and patches", "Two years of funded development and frontier-lab model credits" ], "must_hold": [ "Real-world codebases with harder, layered flaws than the injected ones", "Maintainer acceptance of machine-generated patches" ], "echoes": [] }, "paired_incident": null, "headline": "AIxCC systems find 54 of 63 synthetic vulnerabilities, patch 43", "metric": "found 54 synthetic vulnerabilities, patched 43, and found 18 real bugs for disclosure", "comparator": { "against": "the same competition's semifinal round (2024)", "before": "37% at semifinals", "after": "teams identified 86% of the competition's synthetic vulnerabilities", "basis": "measured", "quote": "In the Final Competition scored round, teams identified 86% of the competition's synthetic vulnerabilities, an increase from 37% at semifinals, and patched 68% of the vulnerabilities identified, an increase from 25% at semifinals.", "url": "https://www.darpa.mil/news/2025/aixcc-results" }, "later": { "status": "unknown", "date": null, "note": "The only later item found is curl maintainer Daniel Stenberg's 22 October 2025 review judging the injected curl flaws straightforward; no adoption, reversal or litigation was found.", "quote": null, "url": null }, "value": { "amount": "$152", "what": "average cost per competition task for the systems' bug reports and patches, which DARPA calls a fraction of the cost of traditional methods", "who": "DARPA (cost of running the competitors' cyber reasoning systems per task)", "estimate": false, "quote": "Competitor CRSs proved they can create valuable bug reports and patches for a fraction of the cost of traditional methods, with an average cost per competition task of about $152.", "url": "https://www.darpa.mil/news/2025/aixcc-results" }, "developer_country": null, "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://www.darpa.mil/news/2025/aixcc-results; https://www.darpa.mil/news/2025/aixcc-results", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/DARPA", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the deployer's press release and the beneficiary's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0238", "catalog_version": "1.0.0", "source_fingerprint": "01edde86def16471a3fe4b3c89e5f67489b28fa09b20437cf77586aebe710a73", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0238-source-0001", "AIBD-0238-source-0002", "AIBD-0238-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0238-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Seven finalist teams (Team Atlanta et al.), using LLM credits from Anthropic, Google and OpenAI", "deployer": "DARPA (with ARPA-H), AIxCC Final Competition" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "DARPA, the organizer, reports the figures. The Record corroborates from the event. Stenberg's independent look at the curl tasks suggests the injected flaws were easy. That bounds how much the synthetic scores show." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "DARPA, the organizer, reports the figures. The Record corroborates from the event. Stenberg's independent look at the curl tasks suggests the injected flaws were easy. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Aggregate competition results. No specific attack or deployment outcome documented." }, { "group": "organizational", "reason": "Open-source maintainers received disclosures. 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https://www.darpa.mil/news/2025/aixcc-results", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/DARPA", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Injected flaws in real open-source projects with scoring for proofs and patches", "Two years of funded development and frontier-lab model credits" ], "must_hold": [ "Real-world codebases with harder, layered flaws than the injected ones", "Maintainer acceptance of machine-generated patches" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At DEF CON 33 (8 August 2025) DARPA reported seven teams' systems found 54 synthetic vulnerabilities, patched 43, and found 18 real bugs for disclosure; Team Atlanta won $4 million.", "account": "DARPA's results release describes the Final Competition. Teams' cyber reasoning systems tried to find and patch synthetic vulnerabilities across 54 million lines of real-world open-source code. They found 54 unique synthetic vulnerabilities in 63 challenges and patched 43. They also found 18 real, non-synthetic vulnerabilities (six in C codebases, 12 in Java), now being responsibly disclosed. There were 11 patches for real bugs. The average cost was about $152 per task. Team Atlanta (Georgia Tech, Samsung Research, KAIST, POSTECH) won $4 million, Trail of Bits $3 million and Theori $1.5 million. Four of seven systems were released open source. The Record reported the same figures from Las Vegas with program manager Andrew Carney's remarks. curl maintainer Daniel Stenberg, whose project was among the targets, examined the injected curl flaws. He judged them straightforward and not deeply hidden." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AIxCC finalist cyber reasoning systems (Team Atlanta, Trail of Bits, Theori and four others)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Seven finalist teams (Team Atlanta et al.), using LLM credits from Anthropic, Google and OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "DARPA's AIxCC final: autonomous systems find 54 of 63 synthetic vulnerabilities, patch 43, and surface 18 real bugs in open-source code", "headline": "AIxCC systems find 54 of 63 synthetic vulnerabilities, patch 43" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "01edde86def16471a3fe4b3c89e5f67489b28fa09b20437cf77586aebe710a73" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "DARPA's results release describes the Final Competition. Teams' cyber reasoning systems tried to find and patch synthetic vulnerabilities across 54 million lines of real-world open-source code. They found 54 unique synthetic vulnerabilities in 63 challenges and patched 43. They also found 18 real, non-synthetic vulnerabilities (six in C codebases, 12 in Java), now being responsibly disclosed. There were 11 patches for real bugs. The average cost was about $152 per task. Team Atlanta (Georgia Tech, Samsung Research, KAIST, POSTECH) won $4 million, Trail of Bits $3 million and Theori $1.5 million. Four of seven systems were released open source. The Record reported the same figures from Las Vegas with program manager Andrew Carney's remarks. curl maintainer Daniel Stenberg, whose project was among the targets, examined the injected curl flaws. He judged them straightforward and not deeply hidden.", "replication": { "produced_by": [ "Injected flaws in real open-source projects with scoring for proofs and patches", "Two years of funded development and frontier-lab model credits" ], "must_hold": [ "Real-world codebases with harder, layered flaws than the injected ones", "Maintainer acceptance of machine-generated patches" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0136", "title": "ChatGPT tells a Wolfforth, Texas woman with a week-old spider bite, days of vomiting and a numb arm to go to the ER; doctors say she belongs there", "summary": "ChatGPT sent Holli of Wolfforth, Texas to the ER for a worsening spider bite on 27 August 2025; doctors agreed and said the tissue was dying.", "date_observed": "2025-08-27", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Holli posts on TikTok as @hair.queen.holli from Wolfforth, Texas. She said a spider had bitten her “a little over a week ago”. The bite was getting worse. She had vomited for days and could not keep water down. She woke with a numb arm. She asked ChatGPT whether she should go to the emergency room (ER). It answered that her symptoms were “a ton of red flags” and that she should go immediately. At the ER, she said, staff told her “Yeah, you should be here”. They said the skin tissue was dying or dead. Her video, recorded at the ER, was posted on 27 August 2025. The hospital, diagnosis and treatment were not reported. No clinician has spoken.", "category": "protective response", "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant. Answering a user's question, here whether to go to the emergency room, is its core function. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted it. The system gave triage advice rather than a diagnosis.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": null, "location": "Wolfforth, United States", "domain": "Healthcare (emergency self-triage)", "segment": "Consumer use of a general chatbot for triage advice", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-09-02-0516" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Holli got emergency care after the chatbot overrode her hesitation. She says doctors told her the bite's tissue was dying or dead. The diagnosis, treatment and outcome were not reported. The size of the benefit is therefore unknown." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT's contribution, on her account, was an unambiguous instruction to go immediately when she was unsure. The assessment and any treatment were the ER's. Whether earlier arrival changed her outcome is unknown. Everything traces to her TikTok, relayed by Reach plc tabloids and Indian lifestyle desks. Hindustan Times states that it “has not independently verified the claims”." }, "evidence": [ { "kind": "other", "citation": "Holli (@hair.queen.holli) (2025). TikTok video 7543332854705540365, recorded at the emergency room. TikTok, 27 August 2025.", "title": "The Dr said the skin is dying or already dead, I can't really remember… so it is an emergency", "url": "https://www.tiktok.com/@hair.queen.holli/video/7543332854705540365", "date": "2025-08-27", "written_by": "beneficiary", "quote": "The Dr said the skin is dying or already dead, I can’t really remember… so it is an emergency" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Express (2025). Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E. Express.co.uk, 2 September 2025.", "title": "Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E", "url": "https://www.express.co.uk/life-style/health/2103355/woman-bit-spider-asks-ai-chatbot-advice-told-me-go-e", "date": "2025-09-02", "written_by": "independent", "quote": "They looked at it and said, 'Yeah, you should be here'. So now here I am" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Star (2025). Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job. Daily Star, 2 September 2025.", "title": "Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job", "url": "https://www.dailystar.co.uk/real-life/woman-asks-chat-gpt-whether-she-should-go-to-ae-35834743", "date": "2025-09-02", "written_by": "independent", "quote": "your symptoms are a ton of red flags, you need to go immediately" }, { "kind": "news report", "citation": "Akanksha Agnihotri / Hindustan Times (2025). Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'. Hindustan Times, 3 September 2025.", "title": "Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'", "url": "https://www.hindustantimes.com/lifestyle/health/woman-credits-chatgpt-for-saving-her-life-after-spider-bite-left-her-arm-numb-it-told-me-to-immediately-go-to-the-er-101756886357629.html", "date": "2025-09-03", "written_by": "independent", "quote": "This report is based on user-generated content from social media. HT.com has not independently verified the claims and does not endorse them." }, { "kind": "news report", "citation": "ET Online / The Economic Times (2025). Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life. The Economic Times, 3 September 2025.", "title": "Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life", "url": "https://economictimes.indiatimes.com/magazines/panache/woman-bitten-by-spider-turns-to-chatgpt-for-help-and-doctors-say-it-saved-her-life/articleshow/123680161.cms", "date": "2025-09-03", "written_by": "independent", "quote": "Our Services are not intended for use in the diagnosis or treatment of any health condition" } ], "replication": { "produced_by": [ "Escalating symptoms (days of vomiting, inability to keep water down, new numbness in the arm) in a person hesitating to seek care.", "A yes/no triage question put to a chatbot that answered without hedging: “you need to go immediately”.", "An emergency department within reach that could assess the bite the same day." ], "must_hold": [ "The user acts on the advice promptly rather than waiting for a second opinion.", "The advice is to escalate to clinicians, who then examine and diagnose. 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"evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-09-02-0516" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No report on Holli's diagnosis, treatment or recovery after the 27 August 2025 video was found; the press pieces of 2-3 September 2025 only retell the video." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ 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"Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Holli posts on TikTok as @hair.queen.holli from Wolfforth, Texas. 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No clinician has spoken.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Holli got emergency care after the chatbot overrode her hesitation. She says doctors told her the bite's tissue was dying or dead. The diagnosis, treatment and outcome were not reported. The size of the benefit is therefore unknown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant. Answering a user's question, here whether to go to the emergency room, is its core function. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted it. The system gave triage advice rather than a diagnosis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Wolfforth, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose conversational assistant. Answering a user's question, here whether to go to the emergency room, is its core function. OpenAI told the Mirror that its services “are not intended for use in the diagnosis or treatment of any health condition”. The Economic Times quoted it. The system gave triage advice rather than a diagnosis." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-27", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (an instruction to go to the ER, which doctors endorsed) is documented only by Holli's own video, and no diagnosis, treatment or outcome has been reported, so no specific prevented harm is evidenced; the Monitor's “treated her” is not in any source. The TikTok was dated from its page metadata (createTime 1756319056, 27 August 2025) and still existed on 20 October 2026. Reach plc ran the same text in the Express and the Daily Star under one byline; The Economic Times credits the Mirror. No local Texas report, clinician or hospital statement was found.", "source": "https://oecd.ai/en/incidents/2025-09-02-0516", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Escalating symptoms (days of vomiting, inability to keep water down, new numbness in the arm) in a person hesitating to seek care.", "A yes/no triage question put to a chatbot that answered without hedging: “you need to go immediately”.", "An emergency department within reach that could assess the bite the same day." ], "must_hold": [ "The user acts on the advice promptly rather than waiting for a second opinion.", "The advice is to escalate to clinicians, who then examine and diagnose. The chatbot made no diagnosis.", "Such cases are self-published. No clinician, hospital or document has confirmed this one. The record stands or falls with her account." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (an instruction to go to the ER, which doctors endorsed) is documented only by Holli's own video, and no diagnosis, treatment or outcome has been reported, so no specific prevented harm is evidenced; the Monitor's “treated her” is not in any source. The TikTok was dated from its page metadata (createTime 1756319056, 27 August 2025) and still existed on 20 October 2026. Reach plc ran the same text in the Express and the Daily Star under one byline; The Economic Times credits the Mirror. No local Texas report, clinician or hospital statement was found.", "source": "https://oecd.ai/en/incidents/2025-09-02-0516", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (emergency self-triage)", "segment": "Consumer use of a general chatbot for triage advice" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Holli (@hair.queen.holli) (2025). TikTok video 7543332854705540365, recorded at the emergency room. TikTok, 27 August 2025.", "title": "The Dr said the skin is dying or already dead, I can't really remember… so it is an emergency", "url": "https://www.tiktok.com/@hair.queen.holli/video/7543332854705540365", "date": "2025-08-27", "written_by": "beneficiary", "quote": "The Dr said the skin is dying or already dead, I can’t really remember… so it is an emergency" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Express (2025). Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E. Express.co.uk, 2 September 2025.", "title": "Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E", "url": "https://www.express.co.uk/life-style/health/2103355/woman-bit-spider-asks-ai-chatbot-advice-told-me-go-e", "date": "2025-09-02", "written_by": "independent", "quote": "They looked at it and said, 'Yeah, you should be here'. So now here I am" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Star (2025). Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job. Daily Star, 2 September 2025.", "title": "Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job", "url": "https://www.dailystar.co.uk/real-life/woman-asks-chat-gpt-whether-she-should-go-to-ae-35834743", "date": "2025-09-02", "written_by": "independent", "quote": "your symptoms are a ton of red flags, you need to go immediately" }, { "kind": "news report", "citation": "Akanksha Agnihotri / Hindustan Times (2025). Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'. Hindustan Times, 3 September 2025.", "title": "Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'", "url": "https://www.hindustantimes.com/lifestyle/health/woman-credits-chatgpt-for-saving-her-life-after-spider-bite-left-her-arm-numb-it-told-me-to-immediately-go-to-the-er-101756886357629.html", "date": "2025-09-03", "written_by": "independent", "quote": "This report is based on user-generated content from social media. HT.com has not independently verified the claims and does not endorse them." }, { "kind": "news report", "citation": "ET Online / The Economic Times (2025). Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life. The Economic Times, 3 September 2025.", "title": "Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life", "url": "https://economictimes.indiatimes.com/magazines/panache/woman-bitten-by-spider-turns-to-chatgpt-for-help-and-doctors-say-it-saved-her-life/articleshow/123680161.cms", "date": "2025-09-03", "written_by": "independent", "quote": "Our Services are not intended for use in the diagnosis or treatment of any health condition" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0136-source-0001", "AIBD-0136-source-0002", "AIBD-0136-source-0003", "AIBD-0136-source-0004", "AIBD-0136-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "Holli (@hair.queen.holli) (2025). TikTok video 7543332854705540365, recorded at the emergency room. TikTok, 27 August 2025.", "title": "The Dr said the skin is dying or already dead, I can't really remember… so it is an emergency", "url": "https://www.tiktok.com/@hair.queen.holli/video/7543332854705540365", "date": "2025-08-27", "written_by": "beneficiary", "quote": "The Dr said the skin is dying or already dead, I can’t really remember… so it is an emergency" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Express (2025). Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E. Express.co.uk, 2 September 2025.", "title": "Woman is 'thankful' after asking Chat GPT for medical advice and is told to go to A&E", "url": "https://www.express.co.uk/life-style/health/2103355/woman-bit-spider-asks-ai-chatbot-advice-told-me-go-e", "date": "2025-09-02", "written_by": "independent", "quote": "They looked at it and said, 'Yeah, you should be here'. So now here I am" }, { "kind": "news report", "citation": "Danielle Kate Wroe / Daily Star (2025). Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job. Daily Star, 2 September 2025.", "title": "Woman asks Chat GPT whether she should go to A&E and doctors say it's a good job", "url": "https://www.dailystar.co.uk/real-life/woman-asks-chat-gpt-whether-she-should-go-to-ae-35834743", "date": "2025-09-02", "written_by": "independent", "quote": "your symptoms are a ton of red flags, you need to go immediately" }, { "kind": "news report", "citation": "Akanksha Agnihotri / Hindustan Times (2025). Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'. Hindustan Times, 3 September 2025.", "title": "Woman credits ChatGPT for saving her life after spider bite left her arm numb: 'It told me to immediately go to the ER'", "url": "https://www.hindustantimes.com/lifestyle/health/woman-credits-chatgpt-for-saving-her-life-after-spider-bite-left-her-arm-numb-it-told-me-to-immediately-go-to-the-er-101756886357629.html", "date": "2025-09-03", "written_by": "independent", "quote": "This report is based on user-generated content from social media. HT.com has not independently verified the claims and does not endorse them." }, { "kind": "news report", "citation": "ET Online / The Economic Times (2025). Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life. The Economic Times, 3 September 2025.", "title": "Woman bitten by spider turns to ChatGPT for help, and doctors say it saved her life", "url": "https://economictimes.indiatimes.com/magazines/panache/woman-bitten-by-spider-turns-to-chatgpt-for-help-and-doctors-say-it-saved-her-life/articleshow/123680161.cms", "date": "2025-09-03", "written_by": "independent", "quote": "Our Services are not intended for use in the diagnosis or treatment of any health condition" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ChatGPT sent Holli of Wolfforth, Texas to the ER for a worsening spider bite on 27 August 2025; doctors agreed and said the tissue was dying.", "account": "Holli posts on TikTok as @hair.queen.holli from Wolfforth, Texas. She said a spider had bitten her “a little over a week ago”. The bite was getting worse. She had vomited for days and could not keep water down. She woke with a numb arm. She asked ChatGPT whether she should go to the emergency room (ER). It answered that her symptoms were “a ton of red flags” and that she should go immediately. At the ER, she said, staff told her “Yeah, you should be here”. They said the skin tissue was dying or dead. Her video, recorded at the ER, was posted on 27 August 2025. The hospital, diagnosis and treatment were not reported. No clinician has spoken." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT tells a Wolfforth, Texas woman with a week-old spider bite, days of vomiting and a numb arm to go to the ER; doctors say she belongs there", "headline": "ChatGPT sends a woman with a spider bite to the ER; staff agree" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "947ff4e410c722ad2357a2f6a262ab3f0de11fa3c5c6a57ad117dbc535a7ac7a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Holli posts on TikTok as @hair.queen.holli from Wolfforth, Texas. She said a spider had bitten her “a little over a week ago”. The bite was getting worse. She had vomited for days and could not keep water down. She woke with a numb arm. She asked ChatGPT whether she should go to the emergency room (ER). It answered that her symptoms were “a ton of red flags” and that she should go immediately. At the ER, she said, staff told her “Yeah, you should be here”. They said the skin tissue was dying or dead. Her video, recorded at the ER, was posted on 27 August 2025. The hospital, diagnosis and treatment were not reported. No clinician has spoken.", "replication": { "produced_by": [ "Escalating symptoms (days of vomiting, inability to keep water down, new numbness in the arm) in a person hesitating to seek care.", "A yes/no triage question put to a chatbot that answered without hedging: “you need to go immediately”.", "An emergency department within reach that could assess the bite the same day." ], "must_hold": [ "The user acts on the advice promptly rather than waiting for a second opinion.", "The advice is to escalate to clinicians, who then examine and diagnose. The chatbot made no diagnosis.", "Such cases are self-published. No clinician, hospital or document has confirmed this one. The record stands or falls with her account." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0329", "title": "wi.breathe cameras alert authorities to a Troizina wildfire, according to WINGS and the mayor", "summary": "WINGS and Troizinia-Methana’s mayor credit wi.breathe with an August 2025 wildfire alert. Contemporary reporting describes spread and a substantial firefighting response.", "date_observed": "2025-08-28", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "WINGS reported on September 2, 2025 that its wi.breathe cameras in Methana had detected a wildfire in Troizina on August 28 and alerted authorities. The company quoted Mayor Tasos Ath. Mougios crediting the system with preventing a larger disaster. No alert log, detection time, response chronology, or estimate of avoided damage accompanies that account. Contemporary reporting by Saronic Magazine describes the fire spreading uphill, hours of firefighting, precautionary evacuations, and damage to a shed. The municipality’s same-day statement credits a coordinated response involving more than 80 firefighters and six aircraft. Those accounts establish the scale of the fire and response, but neither verifies the AI’s contribution. WINGS later announced completion of the wider camera installation on May 12, 2026. The one-minute detection figure in circulated completion publicity is a capability claim, not a measured result for the August fire.", "category": "general benefit", "unexpected": false, "purpose": "Detect wildfire smoke and fire from monitoring cameras and alert civil-protection authorities so that they can respond earlier.", "system": "wi.breathe Operational Intelligence Platform (WINGS ICT Solutions): hybrid optical-thermal cameras, a WINGS-trained AI smoke and fire detection model, cloud infrastructure and 5G/4G links with dashboard, email and SMS alerts", "model_version": null, "developer": "WINGS ICT Solutions, Athens, Greece", "deployer": "Municipality of Troizinia-Methana (cameras at Vigla on Poros, Tsepeleni Aderon and Agios Georgios Methanon)", "location": "Troizinia-Methana and Poros, Attica, Greece", "domain": "Civil protection: wildfire early detection", "segment": "Camera-based AI smoke and fire detection", "benefit_type": "Reduced Risk", "taxonomy_note": "The claimed benefit is an earlier warning that could limit wildfire damage. Avoided damage has not been quantified.", "registry_ids": { "oecd_aim": "2026-05-12-c1ff" }, "ratings": [ { "group": "societal", "depth": null, "reason": "The developer and mayor attribute an early warning and avoided escalation to the system. No alert log, causal comparison, or estimate of avoided damage supports a depth assessment." }, { "group": "organizational", "depth": null, "reason": "The municipality’s response is documented, but the sources do not measure any reduction in response time, staffing, or cost attributable to AI." } ], "ai_role": { "status": "unassessed", "statement": "WINGS describes AI detection of fire and smoke from monitoring cameras. Its September 2025 report attributes an alert for the August 28 fire to wi.breathe and quotes the mayor supporting that account. Contemporary fire coverage does not verify the alert or establish how much it changed the response. The AI contribution remains a first-party claim." }, "evidence": [ { "kind": "press release", "citation": "WINGS ICT Solutions, “Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action,” September 2, 2025, opening paragraphs and mayor’s statement; event dated August 28, 2025.", "title": "Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action", "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "date": "2025-09-02", "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "WINGS ICT Solutions, “WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros,” May 12, 2026, installation sites and system-capabilities paragraphs.", "title": "WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros", "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "date": "2026-05-12", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Monitoring cameras that feed an AI smoke and fire detector", "Alerts that reach civil-protection staff who can investigate and mobilize a response" ], "must_hold": [ "Camera coverage and image quality must permit detection of the developing fire", "Connectivity and notification channels must deliver alerts promptly", "People and firefighting resources must be available to act on an alert" ], "echoes": [] }, "paired_incident": null, "headline": "wi.breathe cameras reportedly flag a Troizina wildfire", "metric": null, "comparator": null, "later": { "status": "unknown", "date": "2026-05-12", "note": "WINGS announced completion of the wider installation. The announcement supplies no evaluation of the August fire alert or quantified reduction in fire losses.", "quote": null, "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/" }, "value": null, "developer_country": "Greece", "deployer_country": "Greece", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.wings-ict-solutions.eu/contact/; https://en.wikipedia.org/wiki/Troizinia-Methana", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "source": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0329", "catalog_version": "1.0.0", "source_fingerprint": "ead86e8406297a25dc8cf1f73235c13e3eb830a573cec1818b3499f88eea48ca", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "WINGS ICT Solutions, Athens, Greece", "deployer": "Municipality of Troizinia-Methana (cameras at Vigla on Poros, Tsepeleni Aderon and Agios Georgios Methanon)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "WINGS describes AI detection of fire and smoke from monitoring cameras. Its September 2025 report attributes an alert for the August 28 fire to wi.breathe and quotes the mayor supporting that account. Contemporary fire coverage does not verify the alert or establish how much it changed the response. The AI contribution remains a first-party claim." } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: two press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from retained evidence. Independent reporting concerns the fire and response, not verification of the AI alert or avoided damage, and is kept as related material rather than AI corroboration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The developer and mayor attribute an early warning and avoided escalation to the system. No alert log, causal comparison, or estimate of avoided damage supports a depth assessment." }, { "group": "organizational", "reason": "The municipality’s response is documented, but the sources do not measure any reduction in response time, staffing, or cost attributable to AI." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The developer and mayor attribute an early warning to the system. 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No alert log, causal comparison, or estimate of avoided damage supports a depth assessment." }, { "group": "organizational", "reason": "The municipality’s response is documented, but the sources do not measure any reduction in response time, staffing, or cost attributable to AI." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-05-12-c1ff" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "date": "2026-05-12", "note": "WINGS announced completion of the wider installation. The announcement supplies no evaluation of the August fire alert or quantified reduction in fire losses.", "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/" } } }, "provenance": { "kind": "source_review", "basis": "August 28, 2025 is the event date in the original September 2 vendor report. May 12, 2026 is the later completion announcement. Benefit status remains a reported first-party claim.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0329" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "The claimed benefit is an earlier warning that could limit wildfire damage. Avoided damage has not been quantified." } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "WINGS reported on September 2, 2025 that its wi.breathe cameras in Methana had detected a wildfire in Troizina on August 28 and alerted authorities. The company quoted Mayor Tasos Ath. Mougios crediting the system with preventing a larger disaster. No alert log, detection time, response chronology, or estimate of avoided damage accompanies that account. Contemporary reporting by Saronic Magazine describes the fire spreading uphill, hours of firefighting, precautionary evacuations, and damage to a shed. The municipality’s same-day statement credits a coordinated response involving more than 80 firefighters and six aircraft. Those accounts establish the scale of the fire and response, but neither verifies the AI’s contribution. WINGS later announced completion of the wider camera installation on May 12, 2026. The one-minute detection figure in circulated completion publicity is a capability claim, not a measured result for the August fire.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The developer and mayor attribute an early warning and avoided escalation to the system. No alert log, causal comparison, or estimate of avoided damage supports a depth assessment." }, { "group": "organizational", "reason": "The municipality’s response is documented, but the sources do not measure any reduction in response time, staffing, or cost attributable to AI." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "source_review", "basis": "August 28, 2025 is the event date in the original September 2 vendor report. May 12, 2026 is the later completion announcement. Benefit status remains a reported first-party claim.", "record_fields": [ "benefit_status" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect wildfire smoke and fire from monitoring cameras and alert civil-protection authorities so that they can respond earlier." } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Troizinia-Methana and Poros, Attica, Greece", "developer_country": "Greece", "deployer_country": "Greece" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect wildfire smoke and fire from monitoring cameras and alert civil-protection authorities so that they can respond earlier." } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "purpose" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The system detects smoke and fire in camera images and alerts civil-protection staff.", "editor_note": "" } }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-08-28", "date_basis": "event", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.wings-ict-solutions.eu/contact/; https://en.wikipedia.org/wiki/Troizinia-Methana", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "source": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "August 28, 2025 is the event date in the original September 2 vendor report. May 12, 2026 is the later completion announcement. Benefit status remains a reported first-party claim.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Monitoring cameras that feed an AI smoke and fire detector", "Alerts that reach civil-protection staff who can investigate and mobilize a response" ], "must_hold": [ "Camera coverage and image quality must permit detection of the developing fire", "Connectivity and notification channels must deliver alerts promptly", "People and firefighting resources must be available to act on an alert" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Monitoring cameras that feed an AI smoke and fire detector", "Alerts that reach civil-protection staff who can investigate and mobilize a response" ], "must_hold": [ "Camera coverage and image quality must permit detection of the developing fire", "Connectivity and notification channels must deliver alerts promptly", "People and firefighting resources must be available to act on an alert" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. 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Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "source": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Civil protection: wildfire early detection", "segment": "Camera-based AI smoke and fire detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "access": "Complete original developer article read; no linked evidence appendix or source dataset." }, { "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "access": "Complete original developer completion announcement read." }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95660-elegxomeni-i-fotia-stin-troizina-entiposiaki-epixeirisi-pirosveston-eikones-video", "access": "Complete article text and HTML read, including publication metadata; videos not watched.", "version": "datePublished 2025-08-28T13:44:25Z; dateModified 2025-08-28T13:57:48Z" }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95666-o-dimos-troizinias-methanon-gia-tin-fotia-stin-troizina", "access": "Complete reproduced municipal statement read; the linked Facebook original was unavailable." }, { "url": "https://www.facebook.com/dimostroiziniasmethanon/posts/pfbid02PwULaeXWuoacsACFyQju7oTDJCPwKTVf8YAEow9rcbwPmxuCMj1NLAMAy7PdL5zxl", "access": "Embedded original Facebook post could not be retrieved; not inspected." }, { "url": "https://www.youtube.com/watch?v=3QSYpGGrGyc", "access": "Linked video identified in source HTML; not watched." }, { "url": "https://www.youtube.com/watch?v=k9Rqxn2RO0g", "access": "Linked video identified in source HTML; not watched." }, { "url": "https://twitter.com/pyrosvestiki/status/1961025860246651093", "access": "Direct retrieval returned 403. Embedded text read at https://www.anagnostis.org/2025/08/28/fotia-sto-diavologefyro-troizinas-sikothikan-6-enaeria-mesa-katasvesis-video/ ." }, { "url": "https://www.wings-ict-solutions.eu/wi-breathe/", "access": "Complete product text read; generic content, not event evidence." }, { "url": "https://govnews.gr/oikonomia/epicheiriseis/370285/pyranichnefsi-me-techniti-noimosyni-to-neo-systima-ston-dimo-troizinias-methanon-pou-entopizei-foties-se-1-lepto/", "access": "Greek completion publicity text read." }, { "url": "https://www.newsbeast.gr/greece/arthro/13091861/me-technologia-ai-kai-5g-i-pyranichnefsi-se-perioches-tou-dimou-troizinias-methanon", "access": "Greek deployment and capability paragraphs read; no separate measured alert documented." }, { "url": "https://www.reporter.gr/eidhseis/technologia/674608-wings-me-texnologia-ai-kai-5g-i-pyranixnefsi-se-perioxes-tou-dimou-troizinias-methanon", "access": "Direct web retrieval unavailable in this audit; prior source classification preserved without claiming a fresh full-text read." }, { "url": "https://dimostroizinias-methanon.gr/?s=wi.breathe", "access": "Municipal search-result HTML read and the February 2025 award link located; award article not read in this audit." } ] } }, "provenance": { "kind": "source_review", "basis": "Recorded inspected written versions and unavailable original social/video material.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The developer’s releases and contemporary fire reports are available. The municipality’s Facebook original and the Fire Service post were accessible only through reproductions. The linked videos were not inspected.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "WINGS ICT Solutions, “Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action,” September 2, 2025, opening paragraphs and mayor’s statement; event dated August 28, 2025.", "title": "Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action", "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "date": "2025-09-02", "written_by": "makers" }, { "kind": "press release", "citation": "WINGS ICT Solutions, “WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros,” May 12, 2026, installation sites and system-capabilities paragraphs.", "title": "WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros", "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "date": "2026-05-12", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "role": "Retained source entries in reviewed order for this fingerprinted record version" }, "provenance": { "kind": "source_review", "basis": "Original AI claim first, followed by the distinct later deployment announcement. Event-context accounts are separately identified and do not corroborate AI efficacy.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "WINGS ICT Solutions, “Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action,” September 2, 2025, opening paragraphs and mayor’s statement; event dated August 28, 2025.", "title": "Early Wildfire Detection in Trizina by WINGS’ wi.breathe – Innovation in Action", "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "date": "2025-09-02", "written_by": "makers" }, { "kind": "press release", "citation": "WINGS ICT Solutions, “WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros,” May 12, 2026, installation sites and system-capabilities paragraphs.", "title": "WINGS ICT Solutions delivers wi.breathe for early wildfire detection and enhanced environmental intelligence in Troizinia–Methana & Poros", "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "date": "2026-05-12", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0329-source-0001" ], "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "published_on": "2025-09-02", "relationship": "Original AI event claim by the developer, including a municipal testimonial." }, { "source_refs": [ "AIBD-0329-source-0002" ], "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "published_on": "2026-05-12", "relationship": "Later original installation announcement with technical and site details." } ], "excluded_republications": [ { "url": "https://oecd.ai/en/incidents/2026-05-12-c1ff", "relationship": "AI-generated registry summary substitutes a one-minute capability claim for a measured event result; it is not independent corroboration." }, { "url": "https://govnews.gr/oikonomia/epicheiriseis/370285/pyranichnefsi-me-techniti-noimosyni-to-neo-systima-ston-dimo-troizinias-methanon-pou-entopizei-foties-se-1-lepto/", "relationship": "Circulated May 2026 project-completion publicity adds no independently verified alert. The undated detection sentence is superseded by the earlier original dated claim, and the one-minute capability is not treated as an event measurement." }, { "url": "https://www.newsbeast.gr/greece/arthro/13091861/me-technologia-ai-kai-5g-i-pyranichnefsi-se-perioches-tou-dimou-troizinias-methanon", "relationship": "Circulated May 2026 project-completion publicity adds no independently verified alert. The undated detection sentence is superseded by the earlier original dated claim, and the one-minute capability is not treated as an event measurement." }, { "url": "https://www.reporter.gr/eidhseis/technologia/674608-wings-me-texnologia-ai-kai-5g-i-pyranixnefsi-se-perioxes-tou-dimou-troizinias-methanon", "relationship": "Circulated May 2026 project-completion publicity adds no independently verified alert. The undated detection sentence is superseded by the earlier original dated claim, and the one-minute capability is not treated as an event measurement." }, { "url": "https://www.wings-ict-solutions.eu/wi-breathe/", "relationship": "Generic product details retained as related material, not counted as a separate event report." }, { "url": "https://dimostroizinias-methanon.gr/?s=wi.breathe", "relationship": "Municipality search results about a February 2025 award do not establish the wildfire alert or its benefit." } ], "related_material": [ { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95660-elegxomeni-i-fotia-stin-troizina-entiposiaki-epixeirisi-pirosveston-eikones-video", "title": "Ελεγχόμενη η φωτιά στην Τροιζήνα – Εντυπωσιακή επιχείρηση πυροσβεστών (Εικόνες & Video)", "author": "Μπάμπης Κανατσίδης", "published_on": "2025-08-28", "relationship": "Independent original local reporting adds spread, evacuations, firefighting, and shed-damage context; it does not report the AI contribution.", "locator": "Article body paragraphs 1–2 and 5–6" }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95666-o-dimos-troizinias-methanon-gia-tin-fotia-stin-troizina", "title": "Ο Δήμος Τροιζηνίας - Μεθάνων για την φωτιά στην Τροιζήνα", "published_on": "2025-08-28", "relationship": "Municipality statement reproduced by Saronic Magazine. It describes responders and response timing, without attributing an alert to wi.breathe.", "original_url": "https://www.facebook.com/dimostroiziniasmethanon/posts/pfbid02PwULaeXWuoacsACFyQju7oTDJCPwKTVf8YAEow9rcbwPmxuCMj1NLAMAy7PdL5zxl", "locator": "Opening two paragraphs and acknowledgments" }, { "url": "https://www.wings-ict-solutions.eu/wi-breathe/", "relationship": "Generic developer product description adds operator investigation after a smoke alert, but does not document this event.", "locator": "wi.breathe-fire, “Fire Detection and Prevention”" } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0329-source-0001", "retained_source_order": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "ordering_basis": "Lead with the original dated AI event account. Retain the later completion statement for its deployment details, and keep event-only context separate from AI corroboration.", "claim_lineage": [ { "claim": "wi.breathe detected the August 28, 2025 Troizina wildfire and alerted authorities, according to WINGS and its quoted mayor.", "source_ref": "AIBD-0329-source-0001", "source_chain": [ { "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "locator": "Opening two paragraphs and paragraph quoting Mayor Tasos Ath. Mougios", "role": "Original developer report with a deployer testimonial" } ], "method": { "event_date": "2025-08-28", "publication_date": "2025-09-02" }, "limitations": [ "No alert logs, recorded detection time, first-notification comparison, response chronology, or avoided-loss estimate accompanies the account.", "The mayor’s testimonial is published by the developer; it is not independent verification." ] }, { "claim": "The completed installation uses optical-thermal cameras at three named locations, AI detection, cloud infrastructure, and telecommunications links.", "source_ref": "AIBD-0329-source-0002", "source_chain": [ { "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "locator": "Paragraphs describing hybrid optical-thermal cameras, Vigla on Poros, Tsepeleni Aderon, Agios Georgios Methanon, and alerts", "role": "Original developer deployment announcement" } ], "method": {}, "limitations": [ "The May 2026 completion announcement does not establish a new dated fire or provide performance evaluation." ] }, { "claim": "The August 28 fire spread and required extensive human firefighting.", "source_ref": "https://www.saronicmagazine.gr/saronikos/troizina/95660-elegxomeni-i-fotia-stin-troizina-entiposiaki-epixeirisi-pirosveston-eikones-video", "source_chain": [ { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95660-elegxomeni-i-fotia-stin-troizina-entiposiaki-epixeirisi-pirosveston-eikones-video", "locator": "Article body paragraphs 1–2 and 5–6, dated August 28, 2025, 16:44", "role": "Contemporary local reporting with exclusive scene photographs and video links" }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95666-o-dimos-troizinias-methanon-gia-tin-fotia-stin-troizina", "locator": "Opening paragraphs, firefighting-service acknowledgment, and paragraph naming six aircraft within 30 minutes", "role": "Municipality statement reproduced by Saronic Magazine" }, { "url": "https://www.facebook.com/dimostroiziniasmethanon/posts/pfbid02PwULaeXWuoacsACFyQju7oTDJCPwKTVf8YAEow9rcbwPmxuCMj1NLAMAy7PdL5zxl", "locator": "Embedded Facebook post linked from the reproduced statement", "role": "Unretrieved municipal social-media original" } ], "method": {}, "limitations": [ "Neither account identifies the AI alert as the first notification or measures the AI contribution.", "Reports of spread and damage qualify the broad claim that spread was prevented; they do not disprove that an alert helped to limit further escalation.", "Different contemporaneous resource and elapsed-time figures are not forced into one reconciled chronology." ] } ], "limitations": [ "No original AI evaluation, incident log, footnote, appendix, or supplementary dataset is linked from the developer event report or completion announcement.", "The one-minute capability claim in the May 2026 Greek release is not a measured time for the August 2025 event.", "The May 2026 undated trial-detection sentence is not proven to describe a separate fire; it is not counted as a second success.", "Saronic Magazine’s independent fire coverage and the municipality’s statement provide material event context, not independent validation of AI efficacy.", "The municipality’s Facebook original and the two linked Saronic YouTube videos were not inspected.", "The Fire Service X post could not be retrieved directly. Its embedded text was read in Anagnostis, but no fire-resource figure is attributed to an unseen original." ], "access_audit": [ { "url": "https://www.wings-ict-solutions.eu/early-wildfire-detection-in-trizina-by-wings-wi-breathe-innovation-in-action/", "access": "Complete original developer article read; no linked evidence appendix or source dataset." }, { "url": "https://www.wings-ict-solutions.eu/wings-ict-solutions-delivers-wi-breathe-for-early-wildfire-detection-and-enhanced-environmental-intelligence-in-troizinia-methana-poros/", "access": "Complete original developer completion announcement read." }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95660-elegxomeni-i-fotia-stin-troizina-entiposiaki-epixeirisi-pirosveston-eikones-video", "access": "Complete article text and HTML read, including publication metadata; videos not watched.", "version": "datePublished 2025-08-28T13:44:25Z; dateModified 2025-08-28T13:57:48Z" }, { "url": "https://www.saronicmagazine.gr/saronikos/troizina/95666-o-dimos-troizinias-methanon-gia-tin-fotia-stin-troizina", "access": "Complete reproduced municipal statement read; the linked Facebook original was unavailable." }, { "url": "https://www.facebook.com/dimostroiziniasmethanon/posts/pfbid02PwULaeXWuoacsACFyQju7oTDJCPwKTVf8YAEow9rcbwPmxuCMj1NLAMAy7PdL5zxl", "access": "Embedded original Facebook post could not be retrieved; not inspected." }, { "url": "https://www.youtube.com/watch?v=3QSYpGGrGyc", "access": "Linked video identified in source HTML; not watched." }, { "url": "https://www.youtube.com/watch?v=k9Rqxn2RO0g", "access": "Linked video identified in source HTML; not watched." }, { "url": "https://twitter.com/pyrosvestiki/status/1961025860246651093", "access": "Direct retrieval returned 403. Embedded text read at https://www.anagnostis.org/2025/08/28/fotia-sto-diavologefyro-troizinas-sikothikan-6-enaeria-mesa-katasvesis-video/ ." }, { "url": "https://www.wings-ict-solutions.eu/wi-breathe/", "access": "Complete product text read; generic content, not event evidence." }, { "url": "https://govnews.gr/oikonomia/epicheiriseis/370285/pyranichnefsi-me-techniti-noimosyni-to-neo-systima-ston-dimo-troizinias-methanon-pou-entopizei-foties-se-1-lepto/", "access": "Greek completion publicity text read." }, { "url": "https://www.newsbeast.gr/greece/arthro/13091861/me-technologia-ai-kai-5g-i-pyranichnefsi-se-perioches-tou-dimou-troizinias-methanon", "access": "Greek deployment and capability paragraphs read; no separate measured alert documented." }, { "url": "https://www.reporter.gr/eidhseis/technologia/674608-wings-me-texnologia-ai-kai-5g-i-pyranixnefsi-se-perioxes-tou-dimou-troizinias-methanon", "access": "Direct web retrieval unavailable in this audit; prior source classification preserved without claiming a fresh full-text read." }, { "url": "https://dimostroizinias-methanon.gr/?s=wi.breathe", "access": "Municipal search-result HTML read and the February 2025 award link located; award article not read in this audit." } ], "scope": "Complete lineage and access review of the retained evidence. Unavailable linked media and missing underlying evaluation data are explicitly unresolved." } }, "provenance": { "kind": "source_review", "basis": "Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The developer and mayor credit the system with an early alert. Independent coverage documents the fire and response, but no alert log or AI evaluation is available. A later statement about one-minute detection does not measure this incident.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "WINGS and Troizinia-Methana’s mayor credit wi.breathe with an August 2025 wildfire alert. Contemporary reporting describes spread and a substantial firefighting response.", "account": "WINGS reported on September 2, 2025 that its wi.breathe cameras in Methana had detected a wildfire in Troizina on August 28 and alerted authorities. The company quoted Mayor Tasos Ath. Mougios crediting the system with preventing a larger disaster. No alert log, detection time, response chronology, or estimate of avoided damage accompanies that account. Contemporary reporting by Saronic Magazine describes the fire spreading uphill, hours of firefighting, precautionary evacuations, and damage to a shed. The municipality’s same-day statement credits a coordinated response involving more than 80 firefighters and six aircraft. Those accounts establish the scale of the fire and response, but neither verifies the AI’s contribution. WINGS later announced completion of the wider camera installation on May 12, 2026. The one-minute detection figure in circulated completion publicity is a capability claim, not a measured result for the August fire." } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "wi.breathe Operational Intelligence Platform (WINGS ICT Solutions): hybrid optical-thermal cameras, a WINGS-trained AI smoke and fire detection model, cloud infrastructure and 5G/4G links with dashboard, email and SMS alerts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "WINGS ICT Solutions, Athens, Greece" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "wi.breathe cameras alert authorities to a Troizina wildfire, according to WINGS and the mayor", "headline": "wi.breathe cameras reportedly flag a Troizina wildfire" } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ead86e8406297a25dc8cf1f73235c13e3eb830a573cec1818b3499f88eea48ca" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the reviewed case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "WINGS reported on September 2, 2025 that its wi.breathe cameras in Methana had detected a wildfire in Troizina on August 28 and alerted authorities. The company quoted Mayor Tasos Ath. Mougios crediting the system with preventing a larger disaster. No alert log, detection time, response chronology, or estimate of avoided damage accompanies that account. Contemporary reporting by Saronic Magazine describes the fire spreading uphill, hours of firefighting, precautionary evacuations, and damage to a shed. The municipality’s same-day statement credits a coordinated response involving more than 80 firefighters and six aircraft. Those accounts establish the scale of the fire and response, but neither verifies the AI’s contribution. WINGS later announced completion of the wider camera installation on May 12, 2026. The one-minute detection figure in circulated completion publicity is a capability claim, not a measured result for the August fire.", "replication": { "produced_by": [ "Monitoring cameras that feed an AI smoke and fire detector", "Alerts that reach civil-protection staff who can investigate and mobilize a response" ], "must_hold": [ "Camera coverage and image quality must permit detection of the developing fire", "Connectivity and notification channels must deliver alerts promptly", "People and firefighting resources must be available to act on an alert" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields after tracing the original claim. Located the original dated wildfire claim, corrected chronology to August 28, 2025, and retained the developer’s original account and later deployment details. Added contemporaneous fire-response context without treating that coverage as independent verification of the AI benefit.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0329-source-0001", "AIBD-0329-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Monitoring cameras supplied images to the smoke and fire detector. Civil-protection staff received alerts and could investigate or mobilize a response.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 22, "record_mapped": 10, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0056", "title": "Seeing AI gives a woman with retinitis pigmentosa audio access to printed recipes in a Vanderbilt rehabilitation case report", "summary": "A 62-year-old with autosomal dominant RP used Microsoft Seeing AI to read printed recipes in her kitchen (case report, 2025).", "date_observed": "2025-09-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case report in Case Reports in Ophthalmological Medicine (author at Vanderbilt University Medical Center; published 1 September 2025) describes comprehensive low-vision rehabilitation. The patient was a 62-year-old woman with autosomal dominant retinitis pigmentosa, best-corrected acuity 20/40–2 and severely constricted visual fields in both eyes. The rehabilitation included optical aids, white cane training and counseling. After the evaluation visit she was referred to Tennessee's blind and independent living skills training program. At the insistence of her independent living skills trainer she met a Technology Access Program specialist. She downloaded free iPhone apps, among them volunteer-based Be My Eyes and Seeing AI. Seeing AI uses the phone camera to turn printed material into auditory output. The report does not name Seeing AI's maker. The Microsoft attribution rests on the app's App Store listing. At a later meeting of the clinic's bimonthly support group, she reported using both applications in the kitchen. Seeing AI helped her access printed recipes. The author declares no conflicts of interest. Visit dates are not given.", "category": "benefit created", "unexpected": false, "purpose": "Read printed text aloud for people with visual impairment using computer vision", "system": "Microsoft Seeing AI smartphone app (computer-vision text recognition to speech)", "model_version": null, "developer": "Microsoft", "deployer": "Vision rehabilitation clinic (author's department, Vanderbilt University Medical Center), which referred the patient to the state of Tennessee's blind and independent living skills training program; a Technology Access Program specialist introduced the apps; the patient used them at home", "location": "Tennessee, United States", "domain": "Low-vision rehabilitation", "segment": "People with retinitis pigmentosa", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "An identifiable patient gained audio access to printed recipes in her kitchen. The report documents this single functional use within a broader rehabilitation plan. The gain is small." }, { "group": "societal", "depth": 1, "reason": "Single case report. The app is widely available but no population effect is shown here." } ], "ai_role": { "status": "assessed", "statement": "Seeing AI's computer-vision text recognition is what converts the printed recipe into speech. The report lists it alongside non-AI aids (Be My Eyes volunteers, optical devices). It attributes recipe access specifically to Seeing AI." }, "evidence": [ { "kind": "case report", "citation": "Robinson JL (2025). Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report. Case Reports in Ophthalmological Medicine 2025:4856296.", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "The patient was using both applications in the kitchen, with Seeing AI helping her to access printed recipes" }, { "kind": "case report", "citation": "Robinson JL (2025). Case Reports in Ophthalmological Medicine (description of the app).", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report (app description)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "Seeing AI, which uses the device's camera to convert printed material into auditory output" }, { "kind": "press release", "citation": "Microsoft Corporation (2025). Seeing AI. Apple App Store listing; the listing's developer field reads 'Microsoft Corporation' (vendor page, cited only to attribute the app to Microsoft).", "title": "Seeing AI (App Store listing)", "url": "https://apps.apple.com/us/app/seeing-ai/id999062298", "date": null, "written_by": "makers", "quote": "Seeing AI is a free app that narrates the world around you. ... © 2025 Microsoft Corporation. All rights reserved." } ], "replication": { "produced_by": [ "Smartphone camera text recognition read aloud", "Introduction of the app during structured low-vision rehabilitation", "Task-specific use in a familiar environment" ], "must_hold": [ "Patient can aim a phone camera at text", "Printed material of legible font and contrast", "Smartphone ownership and training" ], "echoes": [ { "date": null, "setting": "Lighthouse Guild, New York: 25 adults with vision impairment tested Seeing AI, Envision Glasses, OrCam MyEye 2 Pro and Google Lookout on daily-living tasks (cohort)", "model_version": "Seeing AI 1.0.1", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol 14(1):3, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "830", "title": "Error-Prone AI Accessibility Tools Reportedly Lead to Navigation Issues for Blind Internet Users", "url": "https://incidentdatabase.ai/cite/830", "severity": null, "group": "personal", "basis": "Both convert visual content into accessible output for blind and low-vision users; the accessibility tools mislabelled content and interfered with screen readers, harming blind users such as Jakob Rosin." }, "headline": "Seeing AI reads printed recipes aloud for a woman with RP", "metric": null, "comparator": { "against": "reading print through her habitual spectacle lenses", "before": "She was having trouble reading printed materials, specifically recipes and food preparation instructions, through her habitual spectacle lenses", "after": "Seeing AI helping her to access printed recipes", "basis": "assumed", "quote": "The patient was using both applications in the kitchen, with Seeing AI helping her to access printed recipes and Be My Eyes allowing her to check expiration dates on food products and set her oven and stove dials accurately.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added the Seeing AI App Store listing as vendor-authored evidence because neither cited source names Microsoft, credited the apps in deployer and account to the state of Tennessee's independent living skills program and a Technology Access Program specialist after the clinic's referral, placed the kitchen use at a later clinic-hosted support-group meeting rather than a clinical follow-up, and changed location from Nashville to Tennessee because the report never names a city, with the reasons in the taxonomy note.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/; https://apps.apple.com/us/app/seeing-ai/id999062298", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Vanderbilt_University_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' press release and the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0056", "catalog_version": "1.0.0", "source_fingerprint": "dd0b2a17618ab2847f4d31b251f9baf51f1b614c1247645f12be572f550695a2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0056-source-0001", "AIBD-0056-source-0002", "AIBD-0056-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Microsoft", "deployer": "Vision rehabilitation clinic (author's department, Vanderbilt University Medical Center), which referred the patient to the state of Tennessee's blind and independent living skills training program; a Technology Access Program specialist introduced the apps; the patient used them at home" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Seeing AI's computer-vision text recognition is what converts the printed recipe into speech. The report lists it alongside non-AI aids (Be My Eyes volunteers, optical devices). It attributes recipe access specifically to Seeing AI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Seeing AI's computer-vision text recognition is what converts the printed recipe into speech. The report lists it alongside non-AI aids (Be My Eyes volunteers, optical devices). It attributes recipe access specifically to Seeing AI." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "An identifiable patient gained audio access to printed recipes in her kitchen. The report documents this single functional use within a broader rehabilitation plan. The gain is small." }, { "group": "societal", "depth": 1, "reason": "Single case report. The app is widely available but no population effect is shown here." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' press release and the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "An identifiable patient gained audio access to printed recipes in her kitchen. The report documents this single functional use within a broader rehabilitation plan. The gain is small." }, { "group": "societal", "depth": 1, "reason": "Single case report. The app is widely available but no population effect is shown here." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "An identifiable patient gained audio access to printed recipes in her kitchen. The report documents this single functional use within a broader rehabilitation plan. The gain is small." }, { "group": "societal", "depth": 1, "reason": "Single case report. The app is widely available but no population effect is shown here." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Both convert visual content into accessible output for blind and low-vision users; the accessibility tools mislabelled content and interfered with screen readers, harming blind users such as Jakob Rosin.", "links": [ { "database": "AI Incident Database", "identifier": "830", "title": "Error-Prone AI Accessibility Tools Reportedly Lead to Navigation Issues for Blind Internet Users", "url": "https://incidentdatabase.ai/cite/830", "group": "personal", "basis": "Both convert visual content into accessible output for blind and low-vision users; the accessibility tools mislabelled content and interfered with screen readers, harming blind users such as Jakob Rosin.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "830", "title": "Error-Prone AI Accessibility Tools Reportedly Lead to Navigation Issues for Blind Internet Users", "url": "https://incidentdatabase.ai/cite/830", "group": "personal", "basis": "Both convert visual content into accessible output for blind and low-vision users; the accessibility tools mislabelled content and interfered with screen readers, harming blind users such as Jakob Rosin." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later development found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0056" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report in Case Reports in Ophthalmological Medicine (author at Vanderbilt University Medical Center; published 1 September 2025) describes comprehensive low-vision rehabilitation. The patient was a 62-year-old woman with autosomal dominant retinitis pigmentosa, best-corrected acuity 20/40–2 and severely constricted visual fields in both eyes. The rehabilitation included optical aids, white cane training and counseling. After the evaluation visit she was referred to Tennessee's blind and independent living skills training program. At the insistence of her independent living skills trainer she met a Technology Access Program specialist. She downloaded free iPhone apps, among them volunteer-based Be My Eyes and Seeing AI. Seeing AI uses the phone camera to turn printed material into auditory output. The report does not name Seeing AI's maker. The Microsoft attribution rests on the app's App Store listing. At a later meeting of the clinic's bimonthly support group, she reported using both applications in the kitchen. Seeing AI helped her access printed recipes. The author declares no conflicts of interest. Visit dates are not given.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "An identifiable patient gained audio access to printed recipes in her kitchen. The report documents this single functional use within a broader rehabilitation plan. The gain is small." }, { "group": "societal", "depth": 1, "reason": "Single case report. The app is widely available but no population effect is shown here." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Read printed text aloud for people with visual impairment using computer vision" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Tennessee, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Read printed text aloud for people with visual impairment using computer vision" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-09-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added the Seeing AI App Store listing as vendor-authored evidence because neither cited source names Microsoft, credited the apps in deployer and account to the state of Tennessee's independent living skills program and a Technology Access Program specialist after the clinic's referral, placed the kitchen use at a later clinic-hosted support-group meeting rather than a clinical follow-up, and changed location from Nashville to Tennessee because the report never names a city, with the reasons in the taxonomy note.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/; https://apps.apple.com/us/app/seeing-ai/id999062298", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Vanderbilt_University_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Smartphone camera text recognition read aloud", "Introduction of the app during structured low-vision rehabilitation", "Task-specific use in a familiar environment" ], "must_hold": [ "Patient can aim a phone camera at text", "Printed material of legible font and contrast", "Smartphone ownership and training" ], "echoes": [ { "setting": "Lighthouse Guild, New York: 25 adults with vision impairment tested Seeing AI, Envision Glasses, OrCam MyEye 2 Pro and Google Lookout on daily-living tasks (cohort)", "model_version": "Seeing AI 1.0.1", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol 14(1):3, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Smartphone camera text recognition read aloud", "Introduction of the app during structured low-vision rehabilitation", "Task-specific use in a familiar environment" ], "must_hold": [ "Patient can aim a phone camera at text", "Printed material of legible font and contrast", "Smartphone ownership and training" ], "echoes": [ { "setting": "Lighthouse Guild, New York: 25 adults with vision impairment tested Seeing AI, Envision Glasses, OrCam MyEye 2 Pro and Google Lookout on daily-living tasks (cohort)", "model_version": "Seeing AI 1.0.1", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol 14(1):3, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 830 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/830", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Added the Seeing AI App Store listing as vendor-authored evidence because neither cited source names Microsoft, credited the apps in deployer and account to the state of Tennessee's independent living skills program and a Technology Access Program specialist after the clinic's referral, placed the kitchen use at a later clinic-hosted support-group meeting rather than a clinical follow-up, and changed location from Nashville to Tennessee because the report never names a city, with the reasons in the taxonomy note.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/; https://apps.apple.com/us/app/seeing-ai/id999062298", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Vanderbilt_University_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Microsoft", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Low-vision rehabilitation", "segment": "People with retinitis pigmentosa" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Robinson JL (2025). Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report. Case Reports in Ophthalmological Medicine 2025:4856296.", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "The patient was using both applications in the kitchen, with Seeing AI helping her to access printed recipes" }, { "kind": "case report", "citation": "Robinson JL (2025). Case Reports in Ophthalmological Medicine (description of the app).", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report (app description)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "Seeing AI, which uses the device's camera to convert printed material into auditory output" }, { "kind": "press release", "citation": "Microsoft Corporation (2025). Seeing AI. Apple App Store listing; the listing's developer field reads 'Microsoft Corporation' (vendor page, cited only to attribute the app to Microsoft).", "title": "Seeing AI (App Store listing)", "url": "https://apps.apple.com/us/app/seeing-ai/id999062298", "written_by": "makers", "quote": "Seeing AI is a free app that narrates the world around you. ... © 2025 Microsoft Corporation. All rights reserved." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0056-source-0001", "AIBD-0056-source-0002", "AIBD-0056-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Robinson JL (2025). Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report. Case Reports in Ophthalmological Medicine 2025:4856296.", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "The patient was using both applications in the kitchen, with Seeing AI helping her to access printed recipes" }, { "kind": "case report", "citation": "Robinson JL (2025). Case Reports in Ophthalmological Medicine (description of the app).", "title": "Comprehensive Rehabilitation for Autosomal Dominant Retinitis Pigmentosa: A Case Report (app description)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12417062/", "date": "2025-09-01", "written_by": "deployer", "quote": "Seeing AI, which uses the device's camera to convert printed material into auditory output" }, { "kind": "press release", "citation": "Microsoft Corporation (2025). Seeing AI. Apple App Store listing; the listing's developer field reads 'Microsoft Corporation' (vendor page, cited only to attribute the app to Microsoft).", "title": "Seeing AI (App Store listing)", "url": "https://apps.apple.com/us/app/seeing-ai/id999062298", "written_by": "makers", "quote": "Seeing AI is a free app that narrates the world around you. ... © 2025 Microsoft Corporation. All rights reserved." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A 62-year-old with autosomal dominant RP used Microsoft Seeing AI to read printed recipes in her kitchen (case report, 2025).", "account": "A case report in Case Reports in Ophthalmological Medicine (author at Vanderbilt University Medical Center; published 1 September 2025) describes comprehensive low-vision rehabilitation. The patient was a 62-year-old woman with autosomal dominant retinitis pigmentosa, best-corrected acuity 20/40–2 and severely constricted visual fields in both eyes. The rehabilitation included optical aids, white cane training and counseling. After the evaluation visit she was referred to Tennessee's blind and independent living skills training program. At the insistence of her independent living skills trainer she met a Technology Access Program specialist. She downloaded free iPhone apps, among them volunteer-based Be My Eyes and Seeing AI. Seeing AI uses the phone camera to turn printed material into auditory output. The report does not name Seeing AI's maker. The Microsoft attribution rests on the app's App Store listing. At a later meeting of the clinic's bimonthly support group, she reported using both applications in the kitchen. Seeing AI helped her access printed recipes. The author declares no conflicts of interest. Visit dates are not given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Microsoft Seeing AI smartphone app (computer-vision text recognition to speech)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Microsoft" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Seeing AI gives a woman with retinitis pigmentosa audio access to printed recipes in a Vanderbilt rehabilitation case report", "headline": "Seeing AI reads printed recipes aloud for a woman with RP" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "dd0b2a17618ab2847f4d31b251f9baf51f1b614c1247645f12be572f550695a2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report in Case Reports in Ophthalmological Medicine (author at Vanderbilt University Medical Center; published 1 September 2025) describes comprehensive low-vision rehabilitation. The patient was a 62-year-old woman with autosomal dominant retinitis pigmentosa, best-corrected acuity 20/40–2 and severely constricted visual fields in both eyes. The rehabilitation included optical aids, white cane training and counseling. After the evaluation visit she was referred to Tennessee's blind and independent living skills training program. At the insistence of her independent living skills trainer she met a Technology Access Program specialist. She downloaded free iPhone apps, among them volunteer-based Be My Eyes and Seeing AI. Seeing AI uses the phone camera to turn printed material into auditory output. The report does not name Seeing AI's maker. The Microsoft attribution rests on the app's App Store listing. At a later meeting of the clinic's bimonthly support group, she reported using both applications in the kitchen. Seeing AI helped her access printed recipes. The author declares no conflicts of interest. Visit dates are not given.", "replication": { "produced_by": [ "Smartphone camera text recognition read aloud", "Introduction of the app during structured low-vision rehabilitation", "Task-specific use in a familiar environment" ], "must_hold": [ "Patient can aim a phone camera at text", "Printed material of legible font and contrast", "Smartphone ownership and training" ], "echoes": [ { "setting": "Lighthouse Guild, New York: 25 adults with vision impairment tested Seeing AI, Envision Glasses, OrCam MyEye 2 Pro and Google Lookout on daily-living tasks (cohort)", "model_version": "Seeing AI 1.0.1", "outcome": "recurred", "source": "Seiple et al. (2025) Transl Vis Sci Technol 14(1):3, https://pmc.ncbi.nlm.nih.gov/articles/PMC11721483/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0351", "title": "GiveDirectly's hybrid MobileAid program in Malawi may have enrolled 35% of recipients by phone-metadata machine learning and halved enrollment cost", "summary": "GiveDirectly posts (2024–2025) describe phone-metadata AI/ML targeting in Malawi: 35% of recipients enrolled via phone data, cost per enrolee halved; no date, count or independent source.", "date_observed": "2025-09-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "GiveDirectly's MobileAid approach uses machine learning (ML) on mobile-phone usage patterns to identify people in need and pay them by mobile money. Its 4 September 2025 post (Vera Lummis) says it has evaluated the method across four countries since 2021 (Togo, DRC, Malawi and Bangladesh). In Malawi it ran a hybrid program identifying and enrolling 35% of recipients via phone metadata and 65% in person. It says this halved the cost of identifying and enrolling each additional person compared with a fully in-person operation. It is working with the Government of Malawi to fill gaps in the urban social registry with phone metadata. A study with the Government of Malawi, U.C. Berkeley and U.C. San Diego is expected to report in 2026. It asks whether phone metadata can flag people whose poverty deepens after a shock. Its 27 January 2025 post (Nirali Desai and Vera Lummis) describes interviews with 67 recipients across Malawi and Kenya in February and October 2024. The interviews, naming Mzuzu, asked how to explain AI/ML targeting. It finds scenario-based explanations most understandable. No cited source gives the Malawi program's dates, location, number of recipients or an independent evaluation.", "category": "general benefit", "unexpected": false, "purpose": "Identify people in poverty from mobile-phone metadata with machine learning so that cash can be delivered faster and more cheaply. The claimed benefit (cheaper, faster enrollment) is that purpose.", "system": "GiveDirectly MobileAid: machine-learning poverty targeting from mobile-phone metadata", "model_version": null, "developer": "GiveDirectly (MobileAid), with research partners; for the Malawi study the Government of Malawi, U.C. Berkeley and U.C. San Diego", "deployer": "GiveDirectly, with the Government of Malawi for the urban social registry work", "location": "Malawi (the explain-AI post names Mzuzu)", "domain": "Humanitarian cash transfers / poverty targeting", "segment": "Non-governmental cash-transfer organization working with a national government", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No dated event, named recipient or outcome for Malawi is given in any cited source." }, { "group": "organizational", "depth": null, "reason": "The halved enrollment cost is the maker's own undated statement without figures or an independent evaluation." }, { "group": "societal", "depth": null, "reason": "No population-level outcome is documented for Malawi." } ], "ai_role": { "status": "assessed", "statement": "Only the maker's account is among the sources. GiveDirectly says machine learning on phone metadata identified and enrolled 35% of recipients in a Malawi hybrid program. It says this halved the cost per additional enrolee. It gives no date, place, recipient count or accuracy for Malawi. The Government of Malawi, U.C. Berkeley and U.C. San Diego study is described as pending (findings expected in 2026). Likewise, the explain-AI page names no deployment, date or outcome." }, "evidence": [ { "kind": "press release", "citation": "Lummis, V. (2025). Five things we've learned using mobile data and AI/ML to identify people in need. GiveDirectly blog, 4 September 2025.", "title": "Five things we've learned using mobile data and AI/ML to identify people in need", "url": "https://www.givedirectly.org/mobileaid", "date": "2025-09-04", "written_by": "makers", "quote": "So in Malawi, we ran a hybrid program: we identified and enrolled 35% of recipients via phone metadata and the other 65% in person." }, { "kind": "press release", "citation": "Lummis, V. (2025). Five things we've learned using mobile data and AI/ML to identify people in need. GiveDirectly blog, 4 September 2025 (cost statement).", "title": "Five things we've learned using mobile data and AI/ML to identify people in need (cost statement)", "url": "https://www.givedirectly.org/mobileaid", "date": "2025-09-04", "written_by": "makers", "quote": "This combined approach still cut the cost of identifying and enrolling each additional person in half, compared to a fully in-person operation." }, { "kind": "press release", "citation": "Desai, N. & Lummis, V. (2025). How to explain AI/ML across the digital divide. GiveDirectly blog, 27 January 2025.", "title": "Explain AI/ML systems to people in poverty using real-world scenarios", "url": "https://www.givedirectly.org/explain_ai", "date": "2025-01-27", "written_by": "makers", "quote": "we interviewed 67 GiveDirectly recipients across Malawi and Kenya in February and October 2024" }, { "kind": "press release", "citation": "Lummis, V., Luk, S. & Ramprasad, S. (2024). GiveDirectly's approach to responsible AI/ML. GiveDirectly blog, 8 July 2024.", "title": "GiveDirectly's approach to responsible AI/ML", "url": "https://www.givedirectly.org/ai-framework", "date": "2024-07-08", "written_by": "makers", "quote": "interviews with GiveDirectly recipients in Malawi and Kenya" } ], "replication": { "produced_by": [ "Access to mobile network operator metadata for the target population under a data agreement", "A machine-learning model relating phone usage patterns to poverty, trained on survey data", "Mobile-money rails to enroll and pay identified people", "An in-person survey component (65% of enrollments) alongside the phone-metadata component" ], "must_hold": [ "Telecom partnership and data-sharing agreement in place (GiveDirectly cites 6–18 months set-up)", "Phone ownership and usage among the poor population", "Recipients' understanding and consent, which GiveDirectly found requires scenario-based explanation", "Model accuracy acceptable for the program (GiveDirectly reports phone metadata below in-person proxy-means tests)" ], "echoes": [ { "date": null, "setting": "Togo Novissi COVID-19 cash program (precedent, see AIBD-0093): GiveDirectly states the government paid over 140,000 people within weeks", "model_version": null, "outcome": "recurred", "source": "https://www.givedirectly.org/mobileaid" }, { "date": "2023-12-21", "setting": "Bangladesh: GiveDirectly states recipients were paid as quickly as 3 days after registration using machine-learning eligibility analysis with CEGA", "model_version": null, "outcome": "recurred", "source": "https://www.givedirectly.org/tech-2023" }, { "date": "2025-09-04", "setting": "Kenya: enrollment in flood- and drought-prone areas with Safaricom processing phone metadata in-house, described as ongoing", "model_version": null, "outcome": "unknown", "source": "https://www.givedirectly.org/mobileaid" } ] }, "paired_incident": null, "headline": "GiveDirectly's MobileAid may have halved enrollment cost in Malawi", "metric": "35% of recipients enrolled via phone data, cost per enrolee halved", "comparator": { "against": "a fully in-person enrollment operation", "before": null, "after": "cut the cost of identifying and enrolling each additional person in half", "basis": "measured", "quote": "This combined approach still cut the cost of identifying and enrolling each additional person in half, compared to a fully in-person operation.", "url": "https://www.givedirectly.org/mobileaid" }, "later": { "status": "unknown", "date": null, "note": "GiveDirectly says a study with the Government of Malawi, U.C. Berkeley and U.C. 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Its 4 September 2025 post (Vera Lummis) says it has evaluated the method across four countries since 2021 (Togo, DRC, Malawi and Bangladesh). In Malawi it ran a hybrid program identifying and enrolling 35% of recipients via phone metadata and 65% in person. It says this halved the cost of identifying and enrolling each additional person compared with a fully in-person operation. It is working with the Government of Malawi to fill gaps in the urban social registry with phone metadata. A study with the Government of Malawi, U.C. Berkeley and U.C. San Diego is expected to report in 2026. It asks whether phone metadata can flag people whose poverty deepens after a shock. Its 27 January 2025 post (Nirali Desai and Vera Lummis) describes interviews with 67 recipients across Malawi and Kenya in February and October 2024. The interviews, naming Mzuzu, asked how to explain AI/ML targeting. It finds scenario-based explanations most understandable. No cited source gives the Malawi program's dates, location, number of recipients or an independent evaluation.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No dated event, named recipient or outcome for Malawi is given in any cited source." }, { "group": "organizational", "reason": "The halved enrollment cost is the maker's own undated statement without figures or an independent evaluation." }, { "group": "societal", "reason": "No population-level outcome is documented for Malawi." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify people in poverty from mobile-phone metadata with machine learning so that cash can be delivered faster and more cheaply. 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(2025). Five things we've learned using mobile data and AI/ML to identify people in need. GiveDirectly blog, 4 September 2025.", "title": "Five things we've learned using mobile data and AI/ML to identify people in need", "url": "https://www.givedirectly.org/mobileaid", "date": "2025-09-04", "written_by": "makers", "quote": "So in Malawi, we ran a hybrid program: we identified and enrolled 35% of recipients via phone metadata and the other 65% in person." }, { "kind": "press release", "citation": "Lummis, V. (2025). Five things we've learned using mobile data and AI/ML to identify people in need. 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Its 4 September 2025 post (Vera Lummis) says it has evaluated the method across four countries since 2021 (Togo, DRC, Malawi and Bangladesh). In Malawi it ran a hybrid program identifying and enrolling 35% of recipients via phone metadata and 65% in person. It says this halved the cost of identifying and enrolling each additional person compared with a fully in-person operation. It is working with the Government of Malawi to fill gaps in the urban social registry with phone metadata. A study with the Government of Malawi, U.C. Berkeley and U.C. San Diego is expected to report in 2026. It asks whether phone metadata can flag people whose poverty deepens after a shock. Its 27 January 2025 post (Nirali Desai and Vera Lummis) describes interviews with 67 recipients across Malawi and Kenya in February and October 2024. The interviews, naming Mzuzu, asked how to explain AI/ML targeting. It finds scenario-based explanations most understandable. No cited source gives the Malawi program's dates, location, number of recipients or an independent evaluation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "GiveDirectly MobileAid: machine-learning poverty targeting from mobile-phone metadata" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "GiveDirectly (MobileAid), with research partners; for the Malawi study the Government of Malawi, U.C. Berkeley and U.C. San Diego" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GiveDirectly's hybrid MobileAid program in Malawi may have enrolled 35% of recipients by phone-metadata machine learning and halved enrollment cost", "headline": "GiveDirectly's MobileAid may have halved enrollment cost in Malawi" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0f3426e3243fafb4484c0c9f94cfde3f8aa82ff86c675d046679b52e8eff7a1a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "GiveDirectly's MobileAid approach uses machine learning (ML) on mobile-phone usage patterns to identify people in need and pay them by mobile money. Its 4 September 2025 post (Vera Lummis) says it has evaluated the method across four countries since 2021 (Togo, DRC, Malawi and Bangladesh). In Malawi it ran a hybrid program identifying and enrolling 35% of recipients via phone metadata and 65% in person. It says this halved the cost of identifying and enrolling each additional person compared with a fully in-person operation. It is working with the Government of Malawi to fill gaps in the urban social registry with phone metadata. A study with the Government of Malawi, U.C. Berkeley and U.C. San Diego is expected to report in 2026. It asks whether phone metadata can flag people whose poverty deepens after a shock. Its 27 January 2025 post (Nirali Desai and Vera Lummis) describes interviews with 67 recipients across Malawi and Kenya in February and October 2024. The interviews, naming Mzuzu, asked how to explain AI/ML targeting. It finds scenario-based explanations most understandable. No cited source gives the Malawi program's dates, location, number of recipients or an independent evaluation.", "replication": { "produced_by": [ "Access to mobile network operator metadata for the target population under a data agreement", "A machine-learning model relating phone usage patterns to poverty, trained on survey data", "Mobile-money rails to enroll and pay identified people", "An in-person survey component (65% of enrollments) alongside the phone-metadata component" ], "must_hold": [ "Telecom partnership and data-sharing agreement in place (GiveDirectly cites 6–18 months set-up)", "Phone ownership and usage among the poor population", "Recipients' understanding and consent, which GiveDirectly found requires scenario-based explanation", "Model accuracy acceptable for the program (GiveDirectly reports phone metadata below in-person proxy-means tests)" ], "echoes": [ { "setting": "Togo Novissi COVID-19 cash program (precedent, see AIBD-0093): GiveDirectly states the government paid over 140,000 people within weeks", "outcome": "recurred", "source": "https://www.givedirectly.org/mobileaid" }, { "date": "2023-12-21", "setting": "Bangladesh: GiveDirectly states recipients were paid as quickly as 3 days after registration using machine-learning eligibility analysis with CEGA", "outcome": "recurred", "source": "https://www.givedirectly.org/tech-2023" }, { "date": "2025-09-04", "setting": "Kenya: enrollment in flood- and drought-prone areas with Safaricom processing phone metadata in-house, described as ongoing", "outcome": "unknown", "source": "https://www.givedirectly.org/mobileaid" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0271", "title": "GPT-5 names caruncle oncocytoma from slit-lamp photos in two retrospective cases, months after histology", "summary": "Sassari ophthalmologists gave ChatGPT (GPT-5) slit-lamp photos and brief summaries of two surgically confirmed caruncular oncocytomas; it proposed oncocytoma first in both. Retrospective proof only.", "date_observed": "2025-09-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Sacchi et al. (Frontiers in Ophthalmology, 24 April 2026) retrospectively analyzed two cases of caruncular oncocytoma. Both had been excised and confirmed histopathologically. ChatGPT (GPT-5, 2025 version) received only slit-lamp photographs and a brief summary (age, sex, site). It proposed oncocytoma as the primary hypothesis in both. Differentials included papilloma, nevus, squamous cell carcinoma and melanoma. The authors call it a proof of concept that a general-purpose multimodal model can recognize a rare ocular surface tumor, limited by the sample size. The analysis was run on 8 September 2025, months after confirmation, with no effect on care. The authors declare no competing interests. Publication was 24 April 2026.", "category": "general benefit", "unexpected": false, "purpose": "Test whether a multimodal large language model can generate diagnostic hypotheses from slit-lamp images", "system": "ChatGPT (GPT-5, 2025 version)", "model_version": "GPT-5 (2025)", "developer": "OpenAI", "deployer": "Department of Medicine, Surgery and Pharmacy, University of Sassari", "location": "Sassari, Italy", "domain": "Health; ophthalmology", "segment": "Patients with rare ocular adnexal tumors (retrospective)", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "A retrospective diagnostic match with no effect on care is read as task performance.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No effect on the two patients, whose diagnoses were already confirmed." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome." }, { "group": "societal", "depth": null, "reason": "No attributable event." } ], "ai_role": { "status": "assessed", "statement": "GPT-5 produced the correct primary hypothesis in two retrospective cases when given images and minimal clinical data. The result is a proof of concept reported by non-vendor clinicians. It had no role in the patients' management." }, "evidence": [ { "kind": "case report", "citation": "Sacchi M, Ellecosta C, Sechi S, Dore S, Pinna A. Front Ophthalmol 6:1772378 (2026)", "title": "Artificial intelligence-assisted diagnosis of ocular caruncle oncocytoma: a proof-of-concept case report of two cases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13169155/", "date": "2026-04-24", "written_by": "deployer", "quote": "In both cases, ChatGPT proposed oncocytoma as the primary diagnostic hypothesis." } ], "replication": { "produced_by": [ "Slit-lamp photographs plus a brief clinical summary submitted to a multimodal model" ], "must_hold": [ "Prospective testing before any clinical use", "Larger samples than two cases" ], "echoes": [] }, "paired_incident": null, "headline": "GPT-5 proposes oncocytoma first in two retrospective cases", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The report is a retrospective proof of concept on two histologically confirmed cases; the cited source describes no follow-up and the authors call for larger validation and benchmarking against human experts.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "Italy", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_Sassari", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0271", "catalog_version": "1.0.0", "source_fingerprint": "e45032abd8e277be565ad6008937d5103e5991ce9f69105cda2acc29a8596177", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0271-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "Department of Medicine, Surgery and Pharmacy, University of Sassari" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "GPT-5 produced the correct primary hypothesis in two retrospective cases when given images and minimal clinical data. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-5 (2025)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (GPT-5, 2025 version)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GPT-5 names caruncle oncocytoma from slit-lamp photos in two retrospective cases, months after histology", "headline": "GPT-5 proposes oncocytoma first in two retrospective cases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e45032abd8e277be565ad6008937d5103e5991ce9f69105cda2acc29a8596177" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Sacchi et al. (Frontiers in Ophthalmology, 24 April 2026) retrospectively analyzed two cases of caruncular oncocytoma. Both had been excised and confirmed histopathologically. ChatGPT (GPT-5, 2025 version) received only slit-lamp photographs and a brief summary (age, sex, site). It proposed oncocytoma as the primary hypothesis in both. Differentials included papilloma, nevus, squamous cell carcinoma and melanoma. The authors call it a proof of concept that a general-purpose multimodal model can recognize a rare ocular surface tumor, limited by the sample size. The analysis was run on 8 September 2025, months after confirmation, with no effect on care. The authors declare no competing interests. Publication was 24 April 2026.", "replication": { "produced_by": [ "Slit-lamp photographs plus a brief clinical summary submitted to a multimodal model" ], "must_hold": [ "Prospective testing before any clinical use", "Larger samples than two cases" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0207", "title": "Sheng Siong's facial-recognition CCTV, given a shoplifter's face after a 10 September 2025 stock check at its Punggol Central outlet, matches her to six earlier wine thefts and alerts the manager's phone when she returns at noon the next day; staff stop her with three unscanned bottles, police arrest her, she repays the chain and is jailed eight days on 12 May 2026", "summary": "Sheng Siong's facial recognition matched a wine thief to six prior thefts and flagged her return; arrest, restitution, eight days' jail.", "date_observed": "2025-09-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Catherine Tan Li Eng, 51, took 19 Jacob's Creek wine bottles worth about S$556 from the Sheng Siong supermarket at Block 622D Punggol Central, Singapore. She bagged them unscanned at self-checkout from 2 to 11 September 2025. On 10 September staff found stock discrepancies, reviewed closed-circuit television (CCTV) and uploaded her face to the chain's AI-driven facial recognition system. It automatically identified the earlier thefts. When she returned at noon on 11 September the retail manager got a phone alert. He stopped her at the self-checkout kiosk and found three unscanned bottles. Police arrested her. On 12 May 2026 District Judge Brenda Chua jailed her for eight days on an amalgamated theft charge after full restitution of about S$470.", "category": "benefit created", "unexpected": false, "purpose": "Sheng Siong rolled out its AI-driven facial recognition CCTV system in April 2024 as a measure against shoplifters. It worked with the Singapore Police Force under its Shop Theft for Retailers (STAR) program. In August 2025 it announced an extension to all 83 outlets. Staff upload the photograph of a suspect identified from footage. The system alerts store managers' phones when that person enters any branch. Sheng Siong said thefts per store rose from 4.91 in 2023 to 8 in 2024. Its CEO attributed the rise to catching cases the human eye had missed. Identifying a repeat shoplifter and flagging her return was exactly its designed purpose.", "system": "Sheng Siong's AI-driven facial recognition closed-circuit television system: a suspect's photograph, taken from CCTV footage after a theft is found, is uploaded, the system matches the face across footage and sends mobile alerts through a corporate app to staff when that person enters any Sheng Siong outlet", "model_version": null, "developer": null, "deployer": "Sheng Siong (supermarket chain, 83 outlets), Singapore", "location": "Punggol, Singapore", "domain": "Retail loss prevention and law enforcement", "segment": "Supermarket shop-theft detection: facial recognition on store CCTV with mobile alerts to managers", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-05-12-21c2" }, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Sheng Siong's gain was small and specific. It kept three bottles on 11 September 2025. It got full restitution of about S$470 for the rest of the 19 bottles (about S$556 in all). A seven-visit theft series at one outlet ended. The amount is minor for an 83-outlet chain. The first detection was a human stock check and a manual review of CCTV, not the system." } ], "ai_role": { "status": "assessed", "statement": "The system's documented contribution came after a human detection. On 10 September 2025 a staff member found discrepancies in a stock check. Colleagues reviewed CCTV and saw Tan leaving without paying. They uploaded her face. The Straits Times reports that the system “then automatically identified the other instances” of theft. That turned one observed theft into an amalgamated charge covering seven visits. On 11 September the system's alert reached the retail manager's phone when she entered. He intercepted her at the self-checkout kiosk with three unscanned bottles. The interception, the bag check, the police call, the prosecution and the restitution were human and institutional. No source names the vendor or the model, gives an accuracy figure, or reports a false match in this case." }, "evidence": [ { "kind": "news report", "citation": "Lam L / CNA (2026). Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine. Channel NewsAsia, 12 May 2026 (updated 14 May 2026).", "title": "Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "date": "2026-05-12", "written_by": "independent", "quote": "The retail manager was at the premises when he received an alert on his mobile phone" }, { "kind": "news report", "citation": "Sun D / The Straits Times (2026). Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system. The Straits Times, 12 May 2026 (updated 13 May 2026).", "title": "Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system", "url": "https://www.straitstimes.com/singapore/courts-crime/woman-who-stole-19-bottles-of-wine-from-sheng-shiong-caught-using-facial-recognition-system", "date": "2026-05-12", "written_by": "independent", "quote": "They used the footage to flag her face in the facial recognition system, which then automatically identified the other instances" }, { "kind": "news report", "citation": "Khoo Y-H / AsiaOne (2026). Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail. AsiaOne, 13 May 2026.", "title": "Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail", "url": "https://www.asiaone.com/singapore/woman-caught-sheng-siongs-facial-recognition-system-stealing-19-bottles-wine-get-8-days", "date": "2026-05-13", "written_by": "independent", "quote": "they were able to prevent her from stealing another three bottles of wine" }, { "kind": "news report", "citation": "Lay B / Mothership (2025). Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises. Mothership, 26 August 2025.", "title": "Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises", "url": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html", "date": "2025-08-26", "written_by": "independent", "quote": "It is deployed in collaboration with the Singapore Police Force (SPF) under its Shop Theft for Retailers (STAR) Programme" } ], "replication": { "produced_by": [ "A chain-wide facial recognition layer on existing CCTV (rolled out from April 2024, extended to all 83 outlets after August 2025). Staff upload a suspect's face, and managers get app alerts when that person re-enters any branch.", "A human trigger: a stock check on 10 September 2025 that revealed missing bottles. Staff then reviewed the footage and uploaded the face the same day.", "A repeat offender who came back to the same outlet at noon the next day, which gave the alert something to fire on.", "A manager on the premises with his phone, able to intercept at the self-checkout kiosk. A police and court process (the STAR program, an amalgamated theft charge) that turned the identification into restitution and a sentence." ], "must_hold": [ "The system identifies, it does not detect. Stock counts or staff still have to notice the first theft. Sheng Siong's CEO implied as much when he said the human eye had missed cases.", "Someone must act on the alert within minutes. The gain here was an interception before she left the store, not the alert itself.", "The match must be right and lawful. A wrong face flagged at the door would produce a wrongful stop. No source reports a false match in this case. None names the vendor or any accuracy figure." ], "echoes": [ { "date": null, "setting": "Malay Mail, 9 October 2026 (AsiaOne report): Leong Seek Yuen, 45, jailed one week after Sheng Siong's facial recognition system alerted staff when she re-entered its Sin Ming Avenue outlet on 1 October 2025, following twelve thefts of meat and drinks worth about S$90 between 27 May and 12 August 2025; as here, an assistant supervisor had first found stock discrepancies and checked CCTV. https://www.malaymail.com/news/singapore/2026/10/09/singapore-supermarkets-facial-recognition-system-catches-woman-after-12-shoplifting-trips/238387", "model_version": null, "outcome": "unknown", "source": null } ] }, "paired_incident": null, "headline": "Sheng Siong's facial recognition catches a repeat wine thief", "metric": "matched a wine thief to six prior thefts and flagged her return", "comparator": { "against": "the chain's previous practice of staff manually reviewing CCTV footage to identify suspects", "before": "staff members had to manually review CCTV footage to identify suspects", "after": "staff receive mobile alerts through a corporate app once a flagged person enters any Sheng Siong branch again", "basis": "assumed", "quote": "Staff would receive mobile alerts through a corporate app once the same person enters any Sheng Siong branch again. Staff may approach the person and file a police report if they are sure the person has committed shop theft. In the past, staff members had to manually review CCTV footage to identify suspects.", "url": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html" }, "later": { "status": "litigated", "date": "2026-05-12", "note": "The shoplifter pleaded guilty to an amalgamated theft charge and was jailed for eight days on 12 May 2026 after making full restitution of about S$470.", "quote": "A shoplifter who was nabbed after being identified by supermarket chain Sheng Siong's facial recognition technology was sentenced to eight days' jail on Tuesday (May 12).", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" }, "value": { "amount": "about S$470", "what": "restitution paid by the shoplifter for the stolen bottles that were not recovered (three bottles were recovered at the interception)", "who": "Sheng Siong", "estimate": false, "quote": "The retail manager called the police, and the three bottles of wine were recovered. Tan also made full restitution of about S$470 for the remaining stolen bottles.", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" }, "developer_country": null, "deployer_country": "Singapore", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 11 September 2025, the day the system's alert led to the interception and arrest; the Monitor's 12 May 2026 is the sentencing and reporting date. Filed as benefit created or restored (identification, arrest and restitution for an identifiable organization); the 11 September interception with three unscanned bottles could be read as a small specific harm prevented, but the record's benefit is the identification of the series and the recovery of the loss. Values differ slightly by outlet: CNA about S$556, The Straits Times over $550, AsiaOne over $555; restitution is “about S$470” in CNA and “full restitution” in all three, consistent with the three bottles recovered on 11 September. No source names the vendor of the facial recognition system or a model, so developer and the model version are null; the system's design and the STAR program come from Mothership's 26 August 2025 report of CNA's rollout story, as CNA's own rollout article returned 404 at the URL found and the Yahoo syndication 404 as well. CNA and The Straits Times refused direct fetches and were read through the r.jina.ai text proxy; The Straits Times headline now reads “...caught by Sheng Siong's facial recognition system” while its URL slug and the Monitor's title read “...from Sheng Shiong caught using facial recognition system”. Malay Mail's 12 May 2026 syndication of David Sun's Straits Times piece was read once and returned 403 on re-fetch, so it is not cited; STOMP and The Independent Singapore returned 403. AsiaOne credits The Straits Times and CNA. No source discusses the PDPA or privacy aspects of the system; the record notes that the first detection was human. The October 2026 echo was found through Bing after WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged.", "source": "https://oecd.ai/en/incidents/2026-05-12-21c2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheng_Siong", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0207", "catalog_version": "1.0.0", "source_fingerprint": "692dc2995f185a3da07c3ae1563b1e95acecd31c39a5109e2349ac66fb973a9b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0207-source-0001", "AIBD-0207-source-0002", "AIBD-0207-source-0003", "AIBD-0207-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0207-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Sheng Siong (supermarket chain, 83 outlets), Singapore" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's documented contribution came after a human detection. On 10 September 2025 a staff member found discrepancies in a stock check. Colleagues reviewed CCTV and saw Tan leaving without paying. They uploaded her face. The Straits Times reports that the system “then automatically identified the other instances” of theft. That turned one observed theft into an amalgamated charge covering seven visits. On 11 September the system's alert reached the retail manager's phone when she entered. He intercepted her at the self-checkout kiosk with three unscanned bottles. The interception, the bag check, the police call, the prosecution and the restitution were human and institutional. No source names the vendor or the model, gives an accuracy figure, or reports a false match in this case." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "After staff identified a theft, facial-recognition software found footage of earlier visits and alerted a manager when the same person returned to the store.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The system's documented contribution came after a human detection. On 10 September 2025 a staff member found discrepancies in a stock check. Colleagues reviewed CCTV and saw Tan leaving without paying. They uploaded her face. The Straits Times reports that the system “then automatically identified the other instances” of theft. That turned one observed theft into an amalgamated charge covering seven visits. On 11 September the system's alert reached the retail manager's phone when she entered. He intercepted her at the self-checkout kiosk with three unscanned bottles. The interception, the bag check, the police call, the prosecution and the restitution were human and institutional. No source names the vendor or the model, gives an accuracy figure, or reports a false match in this case." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Sheng Siong's gain was small and specific. It kept three bottles on 11 September 2025. It got full restitution of about S$470 for the rest of the 19 bottles (about S$556 in all). A seven-visit theft series at one outlet ended. The amount is minor for an 83-outlet chain. The first detection was a human stock check and a manual review of CCTV, not the system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Sheng Siong's gain was small and specific. It kept three bottles on 11 September 2025. It got full restitution of about S$470 for the rest of the 19 bottles (about S$556 in all). A seven-visit theft series at one outlet ended. The amount is minor for an 83-outlet chain. The first detection was a human stock check and a manual review of CCTV, not the system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The store stopped three bottles from being taken and received about S$470 in restitution for earlier thefts. The full series involved 19 bottles worth about S$556. Staff first noticed the missing stock and reviewed the footage, so the documented AI contribution was recognizing the suspect’s return." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Sheng Siong's gain was small and specific. It kept three bottles on 11 September 2025. It got full restitution of about S$470 for the rest of the 19 bottles (about S$556 in all). A seven-visit theft series at one outlet ended. The amount is minor for an 83-outlet chain. The first detection was a human stock check and a manual review of CCTV, not the system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "about S$470", "what": "restitution paid by the shoplifter for the stolen bottles that were not recovered (three bottles were recovered at the interception)", "who": "Sheng Siong", "estimate": false, "quote": "The retail manager called the police, and the three bottles of wine were recovered. Tan also made full restitution of about S$470 for the remaining stolen bottles.", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "about S$470", "what": "restitution paid by the shoplifter for the stolen bottles that were not recovered (three bottles were recovered at the interception)", "who": "Sheng Siong", "estimate": false, "quote": "The retail manager called the police, and the three bottles of wine were recovered. Tan also made full restitution of about S$470 for the remaining stolen bottles.", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "about S$470", "what": "restitution paid by the shoplifter for the stolen bottles that were not recovered (three bottles were recovered at the interception)", "who": "Sheng Siong", "estimate": false, "quote": "The retail manager called the police, and the three bottles of wine were recovered. Tan also made full restitution of about S$470 for the remaining stolen bottles.", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The alert reached the manager when the suspect returned the next day. Staff stopped three unscanned bottles, and the retailer later received about S$470 in restitution. No controlled comparison with manual surveillance is reported." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Bottles recovered, restitution paid, and the interval between identifying the suspect and the next alert." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The sources do not identify the vendor or model and provide no accuracy measure. They do not report a false match in this instance.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-05-12-21c2" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "litigated", "date": "2026-05-12", "note": "The shoplifter pleaded guilty to an amalgamated theft charge and was jailed for eight days on 12 May 2026 after making full restitution of about S$470.", "quote": "A shoplifter who was nabbed after being identified by supermarket chain Sheng Siong's facial recognition technology was sentenced to eight days' jail on Tuesday (May 12).", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Staff found the initial discrepancy, reviewed the footage, and uploaded the photograph. A manager intercepted the customer and contacted the police." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0207" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Sheng Siong’s Punggol Central store." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Sheng Siong’s Punggol Central store." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Catherine Tan Li Eng, 51, took 19 Jacob's Creek wine bottles worth about S$556 from the Sheng Siong supermarket at Block 622D Punggol Central, Singapore. She bagged them unscanned at self-checkout from 2 to 11 September 2025. On 10 September staff found stock discrepancies, reviewed closed-circuit television (CCTV) and uploaded her face to the chain's AI-driven facial recognition system. It automatically identified the earlier thefts. When she returned at noon on 11 September the retail manager got a phone alert. He stopped her at the self-checkout kiosk and found three unscanned bottles. Police arrested her. On 12 May 2026 District Judge Brenda Chua jailed her for eight days on an amalgamated theft charge after full restitution of about S$470.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Sheng Siong recovered the value of stolen wine and stopped three further bottles from leaving the store." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "Sheng Siong's gain was small and specific. It kept three bottles on 11 September 2025. It got full restitution of about S$470 for the rest of the 19 bottles (about S$556 in all). A seven-visit theft series at one outlet ended. The amount is minor for an 83-outlet chain. The first detection was a human stock check and a manual review of CCTV, not the system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Sheng Siong rolled out its AI-driven facial recognition CCTV system in April 2024 as a measure against shoplifters. It worked with the Singapore Police Force under its Shop Theft for Retailers (STAR) program. In August 2025 it announced an extension to all 83 outlets. Staff upload the photograph of a suspect identified from footage. The system alerts store managers' phones when that person enters any branch. Sheng Siong said thefts per store rose from 4.91 in 2023 to 8 in 2024. Its CEO attributed the rise to catching cases the human eye had missed. Identifying a repeat shoplifter and flagging her return was exactly its designed purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Punggol, Singapore", "deployer_country": "Singapore" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Sheng Siong rolled out its AI-driven facial recognition CCTV system in April 2024 as a measure against shoplifters. It worked with the Singapore Police Force under its Shop Theft for Retailers (STAR) program. In August 2025 it announced an extension to all 83 outlets. Staff upload the photograph of a suspect identified from footage. The system alerts store managers' phones when that person enters any branch. Sheng Siong said thefts per store rose from 4.91 in 2023 to 8 in 2024. Its CEO attributed the rise to catching cases the human eye had missed. Identifying a repeat shoplifter and flagging her return was exactly its designed purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-09-11", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 11 September 2025, the day the system's alert led to the interception and arrest; the Monitor's 12 May 2026 is the sentencing and reporting date. Filed as benefit created or restored (identification, arrest and restitution for an identifiable organization); the 11 September interception with three unscanned bottles could be read as a small specific harm prevented, but the record's benefit is the identification of the series and the recovery of the loss. Values differ slightly by outlet: CNA about S$556, The Straits Times over $550, AsiaOne over $555; restitution is “about S$470” in CNA and “full restitution” in all three, consistent with the three bottles recovered on 11 September. No source names the vendor of the facial recognition system or a model, so developer and the model version are null; the system's design and the STAR program come from Mothership's 26 August 2025 report of CNA's rollout story, as CNA's own rollout article returned 404 at the URL found and the Yahoo syndication 404 as well. CNA and The Straits Times refused direct fetches and were read through the r.jina.ai text proxy; The Straits Times headline now reads “...caught by Sheng Siong's facial recognition system” while its URL slug and the Monitor's title read “...from Sheng Shiong caught using facial recognition system”. Malay Mail's 12 May 2026 syndication of David Sun's Straits Times piece was read once and returned 403 on re-fetch, so it is not cited; STOMP and The Independent Singapore returned 403. AsiaOne credits The Straits Times and CNA. No source discusses the PDPA or privacy aspects of the system; the record notes that the first detection was human. The October 2026 echo was found through Bing after WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged.", "source": "https://oecd.ai/en/incidents/2026-05-12-21c2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheng_Siong", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A chain-wide facial recognition layer on existing CCTV (rolled out from April 2024, extended to all 83 outlets after August 2025). Staff upload a suspect's face, and managers get app alerts when that person re-enters any branch.", "A human trigger: a stock check on 10 September 2025 that revealed missing bottles. Staff then reviewed the footage and uploaded the face the same day.", "A repeat offender who came back to the same outlet at noon the next day, which gave the alert something to fire on.", "A manager on the premises with his phone, able to intercept at the self-checkout kiosk. A police and court process (the STAR program, an amalgamated theft charge) that turned the identification into restitution and a sentence." ], "must_hold": [ "The system identifies, it does not detect. Stock counts or staff still have to notice the first theft. Sheng Siong's CEO implied as much when he said the human eye had missed cases.", "Someone must act on the alert within minutes. The gain here was an interception before she left the store, not the alert itself.", "The match must be right and lawful. A wrong face flagged at the door would produce a wrongful stop. No source reports a false match in this case. None names the vendor or any accuracy figure." ], "echoes": [ { "setting": "Malay Mail, 9 October 2026 (AsiaOne report): Leong Seek Yuen, 45, jailed one week after Sheng Siong's facial recognition system alerted staff when she re-entered its Sin Ming Avenue outlet on 1 October 2025, following twelve thefts of meat and drinks worth about S$90 between 27 May and 12 August 2025; as here, an assistant supervisor had first found stock discrepancies and checked CCTV. https://www.malaymail.com/news/singapore/2026/10/09/singapore-supermarkets-facial-recognition-system-catches-woman-after-12-shoplifting-trips/238387", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A chain-wide facial recognition layer on existing CCTV (rolled out from April 2024, extended to all 83 outlets after August 2025). Staff upload a suspect's face, and managers get app alerts when that person re-enters any branch.", "A human trigger: a stock check on 10 September 2025 that revealed missing bottles. Staff then reviewed the footage and uploaded the face the same day.", "A repeat offender who came back to the same outlet at noon the next day, which gave the alert something to fire on.", "A manager on the premises with his phone, able to intercept at the self-checkout kiosk. A police and court process (the STAR program, an amalgamated theft charge) that turned the identification into restitution and a sentence." ], "must_hold": [ "The system identifies, it does not detect. Stock counts or staff still have to notice the first theft. Sheng Siong's CEO implied as much when he said the human eye had missed cases.", "Someone must act on the alert within minutes. The gain here was an interception before she left the store, not the alert itself.", "The match must be right and lawful. A wrong face flagged at the door would produce a wrongful stop. No source reports a false match in this case. None names the vendor or any accuracy figure." ], "echoes": [ { "setting": "Malay Mail, 9 October 2026 (AsiaOne report): Leong Seek Yuen, 45, jailed one week after Sheng Siong's facial recognition system alerted staff when she re-entered its Sin Ming Avenue outlet on 1 October 2025, following twelve thefts of meat and drinks worth about S$90 between 27 May and 12 August 2025; as here, an assistant supervisor had first found stock discrepancies and checked CCTV. https://www.malaymail.com/news/singapore/2026/10/09/singapore-supermarkets-facial-recognition-system-catches-woman-after-12-shoplifting-trips/238387", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Staff must first identify a suspected theft and supply the relevant image. A manager must then verify the match and act before the person leaves. The identification and stop need to be lawful." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 11 September 2025, the day the system's alert led to the interception and arrest; the Monitor's 12 May 2026 is the sentencing and reporting date. Filed as benefit created or restored (identification, arrest and restitution for an identifiable organization); the 11 September interception with three unscanned bottles could be read as a small specific harm prevented, but the record's benefit is the identification of the series and the recovery of the loss. Values differ slightly by outlet: CNA about S$556, The Straits Times over $550, AsiaOne over $555; restitution is “about S$470” in CNA and “full restitution” in all three, consistent with the three bottles recovered on 11 September. No source names the vendor of the facial recognition system or a model, so developer and the model version are null; the system's design and the STAR program come from Mothership's 26 August 2025 report of CNA's rollout story, as CNA's own rollout article returned 404 at the URL found and the Yahoo syndication 404 as well. CNA and The Straits Times refused direct fetches and were read through the r.jina.ai text proxy; The Straits Times headline now reads “...caught by Sheng Siong's facial recognition system” while its URL slug and the Monitor's title read “...from Sheng Shiong caught using facial recognition system”. Malay Mail's 12 May 2026 syndication of David Sun's Straits Times piece was read once and returned 403 on re-fetch, so it is not cited; STOMP and The Independent Singapore returned 403. AsiaOne credits The Straits Times and CNA. No source discusses the PDPA or privacy aspects of the system; the record notes that the first detection was human. The October 2026 echo was found through Bing after WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged.", "source": "https://oecd.ai/en/incidents/2026-05-12-21c2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421; https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheng_Siong", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Retail loss prevention and law enforcement", "segment": "Supermarket shop-theft detection: facial recognition on store CCTV with mobile alerts to managers" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Lam L / CNA (2026). Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine. Channel NewsAsia, 12 May 2026 (updated 14 May 2026).", "title": "Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "date": "2026-05-12", "written_by": "independent", "quote": "The retail manager was at the premises when he received an alert on his mobile phone" }, { "kind": "news report", "citation": "Sun D / The Straits Times (2026). Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system. The Straits Times, 12 May 2026 (updated 13 May 2026).", "title": "Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system", "url": "https://www.straitstimes.com/singapore/courts-crime/woman-who-stole-19-bottles-of-wine-from-sheng-shiong-caught-using-facial-recognition-system", "date": "2026-05-12", "written_by": "independent", "quote": "They used the footage to flag her face in the facial recognition system, which then automatically identified the other instances" }, { "kind": "news report", "citation": "Khoo Y-H / AsiaOne (2026). Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail. AsiaOne, 13 May 2026.", "title": "Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail", "url": "https://www.asiaone.com/singapore/woman-caught-sheng-siongs-facial-recognition-system-stealing-19-bottles-wine-get-8-days", "date": "2026-05-13", "written_by": "independent", "quote": "they were able to prevent her from stealing another three bottles of wine" }, { "kind": "news report", "citation": "Lay B / Mothership (2025). Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises. Mothership, 26 August 2025.", "title": "Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises", "url": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html", "date": "2025-08-26", "written_by": "independent", "quote": "It is deployed in collaboration with the Singapore Police Force (SPF) under its Shop Theft for Retailers (STAR) Programme" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0207-source-0001", "AIBD-0207-source-0002", "AIBD-0207-source-0003", "AIBD-0207-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Lam L / CNA (2026). Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine. Channel NewsAsia, 12 May 2026 (updated 14 May 2026).", "title": "Shoplifter identified by Sheng Siong's facial recognition technology gets jail for stealing wine", "url": "https://www.channelnewsasia.com/singapore/shoplifter-caught-sheng-siong-facial-recognition-tech-jail-6115421", "date": "2026-05-12", "written_by": "independent", "quote": "The retail manager was at the premises when he received an alert on his mobile phone" }, { "kind": "news report", "citation": "Sun D / The Straits Times (2026). Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system. The Straits Times, 12 May 2026 (updated 13 May 2026).", "title": "Woman who stole 19 bottles of wine caught by Sheng Siong's facial recognition system", "url": "https://www.straitstimes.com/singapore/courts-crime/woman-who-stole-19-bottles-of-wine-from-sheng-shiong-caught-using-facial-recognition-system", "date": "2026-05-12", "written_by": "independent", "quote": "They used the footage to flag her face in the facial recognition system, which then automatically identified the other instances" }, { "kind": "news report", "citation": "Khoo Y-H / AsiaOne (2026). Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail. AsiaOne, 13 May 2026.", "title": "Woman caught by Sheng Siong's facial recognition system stealing 19 bottles of wine gets 8 days' jail", "url": "https://www.asiaone.com/singapore/woman-caught-sheng-siongs-facial-recognition-system-stealing-19-bottles-wine-get-8-days", "date": "2026-05-13", "written_by": "independent", "quote": "they were able to prevent her from stealing another three bottles of wine" }, { "kind": "news report", "citation": "Lay B / Mothership (2025). Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises. Mothership, 26 August 2025.", "title": "Sheng Siong installs face recognition CCTV at 83 outlets to catch shoplifters who re-enter premises", "url": "https://mothership.sg/2025/08/sheng-siong-face-recognition-cctv/index.html", "date": "2025-08-26", "written_by": "independent", "quote": "It is deployed in collaboration with the Singapore Police Force (SPF) under its Shop Theft for Retailers (STAR) Programme" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Sheng Siong's facial recognition matched a wine thief to six prior thefts and flagged her return; arrest, restitution, eight days' jail.", "account": "Catherine Tan Li Eng, 51, took 19 Jacob's Creek wine bottles worth about S$556 from the Sheng Siong supermarket at Block 622D Punggol Central, Singapore. She bagged them unscanned at self-checkout from 2 to 11 September 2025. On 10 September staff found stock discrepancies, reviewed closed-circuit television (CCTV) and uploaded her face to the chain's AI-driven facial recognition system. It automatically identified the earlier thefts. When she returned at noon on 11 September the retail manager got a phone alert. He stopped her at the self-checkout kiosk and found three unscanned bottles. Police arrested her. On 12 May 2026 District Judge Brenda Chua jailed her for eight days on an amalgamated theft charge after full restitution of about S$470." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Sheng Siong's AI-driven facial recognition closed-circuit television system: a suspect's photograph, taken from CCTV footage after a theft is found, is uploaded, the system matches the face across footage and sends mobile alerts through a corporate app to staff when that person enters any Sheng Siong outlet" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Sheng Siong's facial-recognition CCTV, given a shoplifter's face after a 10 September 2025 stock check at its Punggol Central outlet, matches her to six earlier wine thefts and alerts the manager's phone when she returns at noon the next day; staff stop her with three unscanned bottles, police arrest her, she repays the chain and is jailed eight days on 12 May 2026", "headline": "Sheng Siong's facial recognition catches a repeat wine thief" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "692dc2995f185a3da07c3ae1563b1e95acecd31c39a5109e2349ac66fb973a9b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Catherine Tan Li Eng, 51, took 19 Jacob's Creek wine bottles worth about S$556 from the Sheng Siong supermarket at Block 622D Punggol Central, Singapore. She bagged them unscanned at self-checkout from 2 to 11 September 2025. On 10 September staff found stock discrepancies, reviewed closed-circuit television (CCTV) and uploaded her face to the chain's AI-driven facial recognition system. It automatically identified the earlier thefts. When she returned at noon on 11 September the retail manager got a phone alert. He stopped her at the self-checkout kiosk and found three unscanned bottles. Police arrested her. On 12 May 2026 District Judge Brenda Chua jailed her for eight days on an amalgamated theft charge after full restitution of about S$470.", "replication": { "produced_by": [ "A chain-wide facial recognition layer on existing CCTV (rolled out from April 2024, extended to all 83 outlets after August 2025). Staff upload a suspect's face, and managers get app alerts when that person re-enters any branch.", "A human trigger: a stock check on 10 September 2025 that revealed missing bottles. Staff then reviewed the footage and uploaded the face the same day.", "A repeat offender who came back to the same outlet at noon the next day, which gave the alert something to fire on.", "A manager on the premises with his phone, able to intercept at the self-checkout kiosk. A police and court process (the STAR program, an amalgamated theft charge) that turned the identification into restitution and a sentence." ], "must_hold": [ "The system identifies, it does not detect. Stock counts or staff still have to notice the first theft. Sheng Siong's CEO implied as much when he said the human eye had missed cases.", "Someone must act on the alert within minutes. The gain here was an interception before she left the store, not the alert itself.", "The match must be right and lawful. A wrong face flagged at the door would produce a wrongful stop. No source reports a false match in this case. None names the vendor or any accuracy figure." ], "echoes": [ { "setting": "Malay Mail, 9 October 2026 (AsiaOne report): Leong Seek Yuen, 45, jailed one week after Sheng Siong's facial recognition system alerted staff when she re-entered its Sin Ming Avenue outlet on 1 October 2025, following twelve thefts of meat and drinks worth about S$90 between 27 May and 12 August 2025; as here, an assistant supervisor had first found stock discrepancies and checked CCTV. https://www.malaymail.com/news/singapore/2026/10/09/singapore-supermarkets-facial-recognition-system-catches-woman-after-12-shoplifting-trips/238387", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "A stock check that revealed missing wine led staff to review camera footage and upload the suspect’s face. The system sent an alert that reached the manager when she returned the next day. Staff stopped her at the checkout. Police and court proceedings that followed led to restitution and an eight-day sentence." } } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0047", "title": "GB-0669, an AI-designed anti-SARS-CoV-2 antibody, completed a randomized first-in-human trial", "summary": "Phase 1 of the AI-designed antibody GB-0669 in 51 healthy adults showed tolerability, a 54-day half-life and dose-dependent virus neutralization.", "date_observed": "2025-10-08", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Generate Biomedicines used machine-learning models and laboratory testing to optimize the antibody that became GB-0669. The original design study describes a structure-conditioned generative model followed by sequence-to-function models trained on experimental results. The subsequent phase 1 study enrolled 51 healthy adults in Orlando, with 36 receiving GB-0669 and 15 placebo across five dose groups. The authors reported no dose-limiting toxicity and no serious adverse events, although one grade 2 infusion reaction led to interruption of the infusion. Serum testing showed dose-dependent viral neutralization at 600 and 1,200 mg. This was laboratory testing of participant serum, not evidence that patients avoided infection or recovered from illness. The results appeared as an author preprint on October 8, 2025 and in the Journal of Infectious Diseases in July 2026. The trial registry was first posted after the study ended. Its structured allocation field says nonrandomized, while the manuscript describes randomization; that inconsistency remains unresolved.", "category": "general benefit", "unexpected": false, "purpose": "Use generative machine learning to design a therapeutic antibody against a conserved, poorly immunogenic region of the SARS-CoV-2 spike protein.", "system": "Generate Biomedicines generative protein design platform (AI-designed monoclonal antibody GB-0669)", "model_version": null, "developer": "Generate Biomedicines", "deployer": "Generate Biomedicines with contract research organization PPD (phase 1 site)", "location": "Orlando, Florida, United States (phase 1 trial)", "domain": "Antiviral biologics / clinical development", "segment": "Healthy adult volunteers", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "An early-phase clinical result is read as knowledge gained rather than a health outcome.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The trial enrolled healthy volunteers and measured safety, pharmacokinetics and serum neutralization; no person obtained a therapeutic benefit." }, { "group": "organizational", "depth": null, "reason": "The source reports a completed phase 1 and a recommendation to proceed to phase 2, not a realized organizational outcome." }, { "group": "societal", "depth": null, "reason": "No population-level benefit is demonstrated; the antibody has not been shown to prevent or treat infection in patients." } ], "ai_role": { "status": "assessed", "statement": "The original design study describes machine-learning optimization of a known antibody using a structure-conditioned generative model and experimentally trained sequence-to-function models. The clinical study evaluates the resulting antibody’s safety and laboratory activity. It does not quantify AI’s advantage over an alternative discovery process or establish a clinical benefit to patients." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Borriello F, Koh GCKW, Troconiz IF, et al.. Randomized, Double-Blind, Placebo-Controlled First-in-Human Trial of a First-in-Class AI-Designed Monoclonal Antibody (GB-0669) Against the Conserved SARS-CoV-2 Spike S2 Stem Helix. 2026-07-14. Journal of Infectious Diseases. Published abstract reviewed alongside the full October 8, 2025 author preprint, doi:10.1101/2025.10.07.25337449.", "title": "Randomized, Double-Blind, Placebo-Controlled First-in-Human Trial of a First-in-Class AI-Designed Monoclonal Antibody (GB-0669) Against the Conserved SARS-CoV-2 Spike S2 Stem Helix", "url": "https://doi.org/10.1093/infdis/jiag349", "date": "2026-07-14", "written_by": "makers", "quote": null }, { "kind": "preprint", "citation": "Marden GC, Schmitt KP, Zimmerman MI, et al.. Functional and structural characterization of a combination of pan-sarbecovirus antibodies with potent antiviral activity. 2025-03-31. Original machine-learning design and preclinical study, cited as reference 14 by the clinical preprint.", "title": "Functional and structural characterization of a combination of pan-sarbecovirus antibodies with potent antiviral activity", "url": "https://www.biorxiv.org/content/10.1101/2025.03.30.646023v1", "date": "2025-03-31", "written_by": "makers", "quote": null }, { "kind": "dataset", "citation": "Generate Biomedicines; ClinicalTrials.gov. NCT07050511: GB-0669 in healthy subjects. 2025-07-03. Sponsor-submitted registration posted after trial completion; no posted results. Structured allocation field conflicts with the manuscript’s randomized description.", "title": "NCT07050511: GB-0669 in healthy subjects", "url": "https://clinicaltrials.gov/study/NCT07050511", "date": "2025-07-03", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A generative protein-design platform aimed at the conserved S2 stem helix", "A randomized, placebo-controlled single-ascending-dose trial in healthy adults", "Live-virus neutralization assays on participants' serum" ], "must_hold": [ "Healthy adult volunteers, single intravenous ascending doses from 100 to 2,400 mg", "Live-virus neutralization assay against circulating sarbecoviruses", "Antibody manufactured as in the trial" ], "echoes": [] }, "paired_incident": null, "headline": "Generate Biomedicines' AI-designed GB-0669 completes phase 1", "metric": "dose-dependent serum live-virus neutralization occurred at 600 and 1,200 mg", "comparator": null, "later": { "status": "unknown", "date": "2026-07-14", "note": "The results were subsequently published in the Journal of Infectious Diseases. The authors propose further clinical evaluation; prevention or treatment of infection has not been demonstrated by this study.", "quote": null, "url": "https://doi.org/10.1093/infdis/jiag349" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://generatebiomedicines.com/contact; https://generatebiomedicines.com/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the clinical results to the earlier full author preprint and the AI claim to its original design paper. Corrected chronology, trial location, and registry interpretation.", "source": "https://doi.org/10.1093/infdis/jiag349", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' preprint and the makers' dataset. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0047", "catalog_version": "1.0.0", "source_fingerprint": "e988731b6fe091782e409a8b5d3ea361c97928ffd86b5a247f32818a3dc81cef", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Generate Biomedicines", "deployer": "Generate Biomedicines with contract research organization PPD (phase 1 site)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The original design study describes machine-learning optimization of a known antibody using a structure-conditioned generative model and experimentally trained sequence-to-function models. The clinical study evaluates the resulting antibody’s safety and laboratory activity. It does not quantify AI’s advantage over an alternative discovery process or establish a clinical benefit to patients." } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The original design study describes machine-learning optimization of a known antibody using a structure-conditioned generative model and experimentally trained sequence-to-function models. 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Structured allocation field conflicts with the manuscript’s randomized description." } ], "excluded_republications": [ { "url": "https://clinicaltrials.gov/search?term=GB-0669", "title": "NCT07050511 trial registry record", "published_on": "2024-11-22", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0047-source-0002" } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0047-source-0001", "retained_source_order": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "ordering_basis": "The source that directly supports the central case leads. Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Safety, pharmacokinetics, and serum-neutralization findings", "source_chain": [ { "url": "https://doi.org/10.1093/infdis/jiag349", "locator": "Published abstract; July 14 publication with August 20 update metadata", "role": "Peer-reviewed version", "access_status": "Published abstract reviewed; complete journal article inaccessible", "published_on": "2026-07-14" }, { "url": "https://www.medrxiv.org/content/10.1101/2025.10.07.25337449v1", "locator": "Methods: Study Design and Subjects; Results: Safety and Pharmacodynamic; Tables 1–3; Discussion", "role": "Original full author preprint", "access_status": "Full text reviewed through https://www.medrxiv.org/content/early/2025/10/08/2025.10.07.25337449.source.xml", "published_on": "2025-10-08" }, { "url": "https://www.medrxiv.org/content/suppl/2025/10/08/2025.10.07.25337449.DC1/337449_file02.docx", "locator": "Supplemental material, 337449_file02.docx", "role": "Underlying supplementary trial methods", "access_status": "Identified in JATS; download returned an access-denial HTML page" } ], "limitations": [ "Healthy participants; serum-neutralization and modeled neutralizing-index results do not establish patient efficacy", "One grade 2 infusion reaction interrupted dosing", "Published full text and supplementary document not reviewed" ], "source_ref": "AIBD-0047-source-0001" }, { "claim": "AI optimization of GB-0669", "source_chain": [ { "url": "https://www.biorxiv.org/content/10.1101/2025.03.30.646023v1", "locator": "ML-guided optimization of anti-S2 stem helix antibodies; Methods: ML-Guided Protein Optimization", "role": "Original design and preclinical study", "access_status": "Full relevant text reviewed through https://www.biorxiv.org/content/early/2025/03/31/2025.03.30.646023.source.xml", "published_on": "2025-03-31" }, { "url": "https://www.biorxiv.org/content/suppl/2025/03/31/2025.03.30.646023.DC1/646023_file02.pdf", "locator": "Document S1, Figures S1 onward", "role": "Design supplementary material", "access_status": "Download returned an access-denial HTML page" } ], "limitations": [ "Manufacturer-authored design and clinical studies; no independent replication", "Two rounds tested 533 unique sequences; the clinical benefit of the resulting antibody remains unestablished" ], "source_ref": "AIBD-0047-source-0002" }, { "claim": "Trial design, dates, and registration", "source_chain": [ { "url": "https://clinicaltrials.gov/study/NCT07050511", "locator": "History, study dates, designModule, and hasResults; API https://clinicaltrials.gov/api/v2/studies/NCT07050511", "role": "Original sponsor registration", "access_status": "Full relevant text reviewed" } ], "limitations": [ "Study ran July 18, 2023–November 22, 2024; first registry posting July 3, 2025", "Structured allocation NON_RANDOMIZED conflicts with the randomized manuscript description", "Registration is neither independent regulatory confirmation nor clinical results" ], "source_ref": "AIBD-0047-source-0003" } ], "limitations": [ "Published full text and both supplements were inaccessible; the original full preprints were reviewed", "Unresolved trial-allocation discrepancy" ], "chronology_source": { "url": "https://www.medrxiv.org/content/10.1101/2025.10.07.25337449v1", "locator": "Original clinical-results preprint", "role": "First verified public report of these clinical results", "access_status": "Full relevant text reviewed", "published_on": "2025-10-08", "date": "2025-10-08", "title": "First-in-Human Study of a First-in-Class AI-Designed Monoclonal Antibody (GB-0669) Against the Conserved SARS-CoV-2 Spike S2 Stem Helix" } } }, "provenance": { "kind": "source_review", "basis": "Traced the clinical results to the earlier full author preprint and the AI claim to its original design paper. Corrected chronology, trial location, and registry interpretation.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The original preprints are available. The published full text and two supplements were inaccessible, and the accounts differ on trial allocation.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Phase 1 of the AI-designed antibody GB-0669 in 51 healthy adults showed tolerability, a 54-day half-life and dose-dependent virus neutralization.", "account": "Generate Biomedicines used machine-learning models and laboratory testing to optimize the antibody that became GB-0669. The original design study describes a structure-conditioned generative model followed by sequence-to-function models trained on experimental results. The subsequent phase 1 study enrolled 51 healthy adults in Orlando, with 36 receiving GB-0669 and 15 placebo across five dose groups. The authors reported no dose-limiting toxicity and no serious adverse events, although one grade 2 infusion reaction led to interruption of the infusion. Serum testing showed dose-dependent viral neutralization at 600 and 1,200 mg. This was laboratory testing of participant serum, not evidence that patients avoided infection or recovered from illness. The results appeared as an author preprint on October 8, 2025 and in the Journal of Infectious Diseases in July 2026. The trial registry was first posted after the study ended. Its structured allocation field says nonrandomized, while the manuscript describes randomization; that inconsistency remains unresolved." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Generate Biomedicines generative protein design platform (AI-designed monoclonal antibody GB-0669)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Generate Biomedicines" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "GB-0669, an AI-designed anti-SARS-CoV-2 antibody, completed a randomized first-in-human trial", "headline": "Generate Biomedicines' AI-designed GB-0669 completes phase 1" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e988731b6fe091782e409a8b5d3ea361c97928ffd86b5a247f32818a3dc81cef" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Generate Biomedicines used machine-learning models and laboratory testing to optimize the antibody that became GB-0669. The original design study describes a structure-conditioned generative model followed by sequence-to-function models trained on experimental results. The subsequent phase 1 study enrolled 51 healthy adults in Orlando, with 36 receiving GB-0669 and 15 placebo across five dose groups. The authors reported no dose-limiting toxicity and no serious adverse events, although one grade 2 infusion reaction led to interruption of the infusion. Serum testing showed dose-dependent viral neutralization at 600 and 1,200 mg. This was laboratory testing of participant serum, not evidence that patients avoided infection or recovered from illness. The results appeared as an author preprint on October 8, 2025 and in the Journal of Infectious Diseases in July 2026. The trial registry was first posted after the study ended. Its structured allocation field says nonrandomized, while the manuscript describes randomization; that inconsistency remains unresolved.", "replication": { "produced_by": [ "A generative protein-design platform aimed at the conserved S2 stem helix", "A randomized, placebo-controlled single-ascending-dose trial in healthy adults", "Live-virus neutralization assays on participants' serum" ], "must_hold": [ "Healthy adult volunteers, single intravenous ascending doses from 100 to 2,400 mg", "Live-virus neutralization assay against circulating sarbecoviruses", "Antibody manufactured as in the trial" ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0047-source-0001", "AIBD-0047-source-0002", "AIBD-0047-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 4, "record_mapped": 24, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0150", "title": "Lynn White of Long Beach, California, who lost an eviction jury trial with a lawyer, may have overturned the eviction on appeal with ChatGPT and Perplexity, which she used to find procedural errors and draft it, avoiding roughly $55,000 in penalties and over $18,000 in back rent", "summary": "Long Beach tenant Lynn White used ChatGPT and Perplexity to overturn her eviction on appeal, avoiding about $55,000 in penalties, per NBC.", "date_observed": "2025-10-08", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Lynn White, a small music production business owner living in a Long Beach, California, trailer park, was allegedly behind on rent and facing eviction. Represented by a lawyer from a local tenant advocacy network, she lost a jury trial. To appeal, she argued that Los Angeles Covid-era rules allowed a 12-month rent deferral. She gave her documents to ChatGPT and the AI search engine Perplexity. She had them find procedural errors by the judge, research the law and draft her court responses. NBC News reported on 8 October 2025 that, after several months of litigation, she overturned the eviction. It said she avoided roughly $55,000 in penalties and over $18,000 in overdue rent. No court, docket or ruling date is given.", "category": "benefit created", "unexpected": false, "purpose": "ChatGPT is a general-purpose assistant for answering questions and drafting text. Perplexity is an AI search engine. Using them to research law, spot procedural errors and draft filings is within that general purpose. Neither is built as a legal service. The same NBC report documents litigants sanctioned for AI-invented case citations.", "system": "ChatGPT (paid plan, $20 a month) and Perplexity Pro ($20 a month)", "model_version": "Not reported; NBC News says White moved from the free ChatGPT tier to the $20-a-month plan and used Perplexity Pro, without naming model versions", "developer": "OpenAI (ChatGPT); Perplexity AI (Perplexity)", "deployer": null, "location": "Long Beach, United States", "domain": "Access to justice", "segment": "Self-represented tenants in eviction proceedings", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-10-20-4cfe" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "By her account to NBC News, White kept her home after losing at trial with a lawyer. She avoided roughly $55,000 in penalties and more than $18,000 in overdue rent. That is life-changing for one person. But the figures and outcome rest on her account, and no court record is cited." } ], "ai_role": { "status": "unassessed", "statement": "White told NBC News that she gave ChatGPT her documents and case details. She said it and Perplexity identified procedural errors by the judge, researched the applicable law and drafted her court responses. She said she could never have won the appeal without AI. No court document, opposing-party or judicial account of what decided the appeal is cited. So the tools' contribution relative to the Covid-era rent-deferral rules she invoked and her own advocacy is not established." }, "evidence": [ { "kind": "news report", "citation": "Perlo J, Yang A (2025). More people are using ChatGPT like a lawyer in court. Some are starting to win. NBC News, 8 October 2025, 5:00 AM EDT.", "title": "More people are using ChatGPT like a lawyer in court. Some are starting to win.", "url": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401", "date": "2025-10-08", "written_by": "independent", "quote": "Several months of litigation later, White managed to overturn her eviction notice and avoid roughly $55,000 in penalties and more than $18,000 in overdue rent." }, { "kind": "news report", "citation": "NEWS 24/7 newsroom (2025). Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT. news247.gr, 20 October 2025, 14:42, citing NBC News; one of the twelve Greek-language sources listed by the OECD Monitor.", "title": "Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT", "url": "https://www.news247.gr/kosmos/ginaika-kerdise-dikastiki-ipothesi-me-dikigoro-to-chatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Η Lynn White, κατάφερε να ανατρέψει την απόφαση έξωσης και να αποφύγει πρόστιμα δεκάδων χιλιάδων δολαρίων μέσω μηνών δικαστικών διαδικασιών βάζοντας για δικηγόρο της… το ChatGPT." }, { "kind": "news report", "citation": "HuffPost Greece (2025). Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT. huffingtonpost.gr, 20 October 2025, 21:27, citing NBC News.", "title": "Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT", "url": "https://www.huffingtonpost.gr/diethnes/gynaika-stin-kalifornia-kerdise-dikastiki-ypothesi-me-synigoro-tochatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Όπως αναφέρει το NBC News, η Λιν Γουάιτ είχε καθυστερήσει την πληρωμή του ενοικίου και αρχικά έχασε τη δίκη με ενόρκους μετά από ειδοποίηση έξωσης." }, { "kind": "other", "citation": "Ihtesham Ali (@ihtesham2005) (2026). Post on X about Lynn White, 4 April 2026, carrying a Community Note that cites the California appellate courts' case search for Court of Appeal case B350202 (appeal denied 26 November 2025) and Supreme Court case S294091 (petition denied).", "title": "Lynn White had $0 for a lawyer and $73,000 in debt hanging over her head (X post with Community Note)", "url": "https://x.com/ihtesham2005/status/2040399092111864187", "date": "2026-04-04", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A litigant with time, her case documents and $40 a month for paid ChatGPT and Perplexity Pro. She fed them the record and detailed case facts", "A substantive ground to find, here Los Angeles Covid-era rules allowing a 12-month rent deferral. Procedural errors at trial that an appeal could reach", "A court system in which a self-represented tenant can appeal an eviction judgment" ], "must_hold": [ "The tools' legal citations and procedural claims are checked before filing. The same NBC article reports litigants sanctioned for AI-invented cases", "The litigant reads and verifies what the tools draft rather than filing it as produced", "The underlying legal position is sound. The tools surfaced rules and errors. They did not create the rent-deferral protection" ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT and Perplexity may have won Lynn White her eviction appeal", "metric": "avoided roughly $55,000 in penalties and over $18,000 in overdue rent", "comparator": { "against": "representation by a lawyer from a local tenant advocacy network, with whom she lost the jury trial", "before": "she worked with a lawyer from a local tenant advocacy network but lost in a jury trial", "after": "White managed to overturn her eviction notice and avoid roughly $55,000 in penalties and more than $18,000 in overdue rent", "basis": "assumed", "quote": "Allegedly behind on rent payments to her trailer park in Long Beach, California, and facing an eviction notice, she worked with a lawyer from a local tenant advocacy network but lost in a jury trial.", "url": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401" }, "later": { "status": "litigated", "date": "2025-11-26", "note": "A community note on a viral April 2026 X post about White states, citing the California appellate courts' case search, that her appeal (Court of Appeal case B350202) was denied on 26 November 2025 and that her petition to the state Supreme Court (S294091) was denied too; if accurate this contradicts the NBC account of an overturned eviction, but the underlying court dockets remain unverified.", "quote": "Lynn White filed an appeal on her eviction case and it was denied on 11/26/25 - appellatecases.courtinfo.ca.gov/search/case/do…\n\nher petition to the state's Supreme Court was denied too\nappellatecases.courtinfo.ca.gov/search/case/di…", "url": "https://x.com/ihtesham2005/status/2040399092111864187" }, "value": { "amount": "roughly $55,000", "what": "penalties avoided, plus more than $18,000 in overdue rent, by overturning the eviction on appeal", "who": "Lynn White", "estimate": false, "quote": "Several months of litigation later, White managed to overturn her eviction notice and avoid roughly $55,000 in penalties and more than $18,000 in overdue rent.", "url": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401" }, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-20-4cfe", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401; https://x.com/ihtesham2005/status/2040399092111864187; https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0150", "catalog_version": "1.0.0", "source_fingerprint": "dd9a32a1d9105ad22d82fc0fd23658f9a321fec8b45dfac282e0200c056112a8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0150-source-0001", "AIBD-0150-source-0002", "AIBD-0150-source-0003", "AIBD-0150-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0150-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI (ChatGPT); Perplexity AI (Perplexity)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "White told NBC News that she gave ChatGPT her documents and case details. She said it and Perplexity identified procedural errors by the judge, researched the applicable law and drafted her court responses. She said she could never have won the appeal without AI. No court document, opposing-party or judicial account of what decided the appeal is cited. So the tools' contribution relative to the Covid-era rent-deferral rules she invoked and her own advocacy is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By her account to NBC News, White kept her home after losing at trial with a lawyer. She avoided roughly $55,000 in penalties and more than $18,000 in overdue rent. That is life-changing for one person. 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Represented by a lawyer from a local tenant advocacy network, she lost a jury trial. To appeal, she argued that Los Angeles Covid-era rules allowed a 12-month rent deferral. She gave her documents to ChatGPT and the AI search engine Perplexity. She had them find procedural errors by the judge, research the law and draft her court responses. NBC News reported on 8 October 2025 that, after several months of litigation, she overturned the eviction. It said she avoided roughly $55,000 in penalties and over $18,000 in overdue rent. No court, docket or ruling date is given.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By her account to NBC News, White kept her home after losing at trial with a lawyer. She avoided roughly $55,000 in penalties and more than $18,000 in overdue rent. That is life-changing for one person. But the figures and outcome rest on her account, and no court record is cited." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ChatGPT is a general-purpose assistant for answering questions and drafting text. Perplexity is an AI search engine. Using them to research law, spot procedural errors and draft filings is within that general purpose. Neither is built as a legal service. The same NBC report documents litigants sanctioned for AI-invented case citations." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Long Beach, United States", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose assistant for answering questions and drafting text. Perplexity is an AI search engine. 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She fed them the record and detailed case facts", "A substantive ground to find, here Los Angeles Covid-era rules allowing a 12-month rent deferral. Procedural errors at trial that an appeal could reach", "A court system in which a self-represented tenant can appeal an eviction judgment" ], "must_hold": [ "The tools' legal citations and procedural claims are checked before filing. The same NBC article reports litigants sanctioned for AI-invented cases", "The litigant reads and verifies what the tools draft rather than filing it as produced", "The underlying legal position is sound. The tools surfaced rules and errors. They did not create the rent-deferral protection" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-20-4cfe", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401; https://x.com/ihtesham2005/status/2040399092111864187; https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Access to justice", "segment": "Self-represented tenants in eviction proceedings" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Perlo J, Yang A (2025). More people are using ChatGPT like a lawyer in court. Some are starting to win. NBC News, 8 October 2025, 5:00 AM EDT.", "title": "More people are using ChatGPT like a lawyer in court. Some are starting to win.", "url": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401", "date": "2025-10-08", "written_by": "independent", "quote": "Several months of litigation later, White managed to overturn her eviction notice and avoid roughly $55,000 in penalties and more than $18,000 in overdue rent." }, { "kind": "news report", "citation": "NEWS 24/7 newsroom (2025). Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT. news247.gr, 20 October 2025, 14:42, citing NBC News; one of the twelve Greek-language sources listed by the OECD Monitor.", "title": "Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT", "url": "https://www.news247.gr/kosmos/ginaika-kerdise-dikastiki-ipothesi-me-dikigoro-to-chatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Η Lynn White, κατάφερε να ανατρέψει την απόφαση έξωσης και να αποφύγει πρόστιμα δεκάδων χιλιάδων δολαρίων μέσω μηνών δικαστικών διαδικασιών βάζοντας για δικηγόρο της… το ChatGPT." }, { "kind": "news report", "citation": "HuffPost Greece (2025). Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT. huffingtonpost.gr, 20 October 2025, 21:27, citing NBC News.", "title": "Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT", "url": "https://www.huffingtonpost.gr/diethnes/gynaika-stin-kalifornia-kerdise-dikastiki-ypothesi-me-synigoro-tochatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Όπως αναφέρει το NBC News, η Λιν Γουάιτ είχε καθυστερήσει την πληρωμή του ενοικίου και αρχικά έχασε τη δίκη με ενόρκους μετά από ειδοποίηση έξωσης." }, { "kind": "other", "citation": "Ihtesham Ali (@ihtesham2005) (2026). Post on X about Lynn White, 4 April 2026, carrying a Community Note that cites the California appellate courts' case search for Court of Appeal case B350202 (appeal denied 26 November 2025) and Supreme Court case S294091 (petition denied).", "title": "Lynn White had $0 for a lawyer and $73,000 in debt hanging over her head (X post with Community Note)", "url": "https://x.com/ihtesham2005/status/2040399092111864187", "date": "2026-04-04", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0150-source-0001", "AIBD-0150-source-0002", "AIBD-0150-source-0003", "AIBD-0150-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Perlo J, Yang A (2025). More people are using ChatGPT like a lawyer in court. Some are starting to win. NBC News, 8 October 2025, 5:00 AM EDT.", "title": "More people are using ChatGPT like a lawyer in court. Some are starting to win.", "url": "https://www.nbcnews.com/tech/innovation/ai-chatgpt-court-law-legal-lawyer-self-represent-pro-se-attorney-rcna230401", "date": "2025-10-08", "written_by": "independent", "quote": "Several months of litigation later, White managed to overturn her eviction notice and avoid roughly $55,000 in penalties and more than $18,000 in overdue rent." }, { "kind": "news report", "citation": "NEWS 24/7 newsroom (2025). Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT. news247.gr, 20 October 2025, 14:42, citing NBC News; one of the twelve Greek-language sources listed by the OECD Monitor.", "title": "Γυναίκα κέρδισε δικαστική υπόθεση με δικηγόρο το ChatGPT", "url": "https://www.news247.gr/kosmos/ginaika-kerdise-dikastiki-ipothesi-me-dikigoro-to-chatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Η Lynn White, κατάφερε να ανατρέψει την απόφαση έξωσης και να αποφύγει πρόστιμα δεκάδων χιλιάδων δολαρίων μέσω μηνών δικαστικών διαδικασιών βάζοντας για δικηγόρο της… το ChatGPT." }, { "kind": "news report", "citation": "HuffPost Greece (2025). Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT. huffingtonpost.gr, 20 October 2025, 21:27, citing NBC News.", "title": "Γυναίκα στην Καλιφόρνια κέρδισε δικαστική υπόθεση με συνήγορο το…ChatGPT", "url": "https://www.huffingtonpost.gr/diethnes/gynaika-stin-kalifornia-kerdise-dikastiki-ypothesi-me-synigoro-tochatgpt/", "date": "2025-10-20", "written_by": "independent", "quote": "Όπως αναφέρει το NBC News, η Λιν Γουάιτ είχε καθυστερήσει την πληρωμή του ενοικίου και αρχικά έχασε τη δίκη με ενόρκους μετά από ειδοποίηση έξωσης." }, { "kind": "other", "citation": "Ihtesham Ali (@ihtesham2005) (2026). Post on X about Lynn White, 4 April 2026, carrying a Community Note that cites the California appellate courts' case search for Court of Appeal case B350202 (appeal denied 26 November 2025) and Supreme Court case S294091 (petition denied).", "title": "Lynn White had $0 for a lawyer and $73,000 in debt hanging over her head (X post with Community Note)", "url": "https://x.com/ihtesham2005/status/2040399092111864187", "date": "2026-04-04", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Long Beach tenant Lynn White used ChatGPT and Perplexity to overturn her eviction on appeal, avoiding about $55,000 in penalties, per NBC.", "account": "Lynn White, a small music production business owner living in a Long Beach, California, trailer park, was allegedly behind on rent and facing eviction. Represented by a lawyer from a local tenant advocacy network, she lost a jury trial. To appeal, she argued that Los Angeles Covid-era rules allowed a 12-month rent deferral. She gave her documents to ChatGPT and the AI search engine Perplexity. She had them find procedural errors by the judge, research the law and draft her court responses. NBC News reported on 8 October 2025 that, after several months of litigation, she overturned the eviction. It said she avoided roughly $55,000 in penalties and over $18,000 in overdue rent. No court, docket or ruling date is given." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "White reported that the tools researched legal questions and drafted responses for her appeal." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "White used a paid ChatGPT subscription and Perplexity Pro. The report does not identify the models selected within those services." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; NBC News says White moved from the free ChatGPT tier to the $20-a-month plan and used Perplexity Pro, without naming model versions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (paid plan, $20 a month) and Perplexity Pro ($20 a month)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI (ChatGPT); Perplexity AI (Perplexity)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lynn White of Long Beach, California, who lost an eviction jury trial with a lawyer, may have overturned the eviction on appeal with ChatGPT and Perplexity, which she used to find procedural errors and draft it, avoiding roughly $55,000 in penalties and over $18,000 in back rent", "headline": "ChatGPT and Perplexity may have won Lynn White her eviction appeal" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "dd9a32a1d9105ad22d82fc0fd23658f9a321fec8b45dfac282e0200c056112a8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Lynn White, a small music production business owner living in a Long Beach, California, trailer park, was allegedly behind on rent and facing eviction. Represented by a lawyer from a local tenant advocacy network, she lost a jury trial. To appeal, she argued that Los Angeles Covid-era rules allowed a 12-month rent deferral. She gave her documents to ChatGPT and the AI search engine Perplexity. She had them find procedural errors by the judge, research the law and draft her court responses. NBC News reported on 8 October 2025 that, after several months of litigation, she overturned the eviction. It said she avoided roughly $55,000 in penalties and over $18,000 in overdue rent. No court, docket or ruling date is given.", "replication": { "produced_by": [ "A litigant with time, her case documents and $40 a month for paid ChatGPT and Perplexity Pro. She fed them the record and detailed case facts", "A substantive ground to find, here Los Angeles Covid-era rules allowing a 12-month rent deferral. Procedural errors at trial that an appeal could reach", "A court system in which a self-represented tenant can appeal an eviction judgment" ], "must_hold": [ "The tools' legal citations and procedural claims are checked before filing. The same NBC article reports litigants sanctioned for AI-invented cases", "The litigant reads and verifies what the tools draft rather than filing it as produced", "The underlying legal position is sound. The tools surfaced rules and errors. They did not create the rent-deferral protection" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 0, "record_mapped": 34, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0148", "title": "Veesion gesture-recognition cameras in Coop Szeged's 247 Shop on Szent István tér, unstaffed at night, may have flagged a shopper hiding goods under clothing and led police to the perpetrator within hours, one of three attempts exposed since May 2025", "summary": "AI cameras in Szeged's unstaffed-at-night Coop flagged a shopper hiding goods; police caught them within hours, the operators said.", "date_observed": "2025-10-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Coop Szeged Zrt. and Laurel Kft. opened the 247 Shop on Szent István tér in Szeged at the end of May 2025. It is staffed by day, automated and unstaffed outside normal hours. Cameras running the French company Veesion's software analyze shoppers' movements without identifying faces. They alert a remote dispatch service to gestures such as concealing goods. On 9 October 2025 the operators issued a press release relayed by Index.hu and MTI. It said over four and a half months the system had exposed three theft attempts. In one, a person hid products under their clothing during night mode. Police caught the perpetrator within hours using the footage. Dates, recovered goods and any police statement are not reported.", "category": "protective response", "unexpected": false, "purpose": "Veesion's gesture-recognition software is built to spot shoplifting movements such as concealing goods and to raise an immediate alert. In Laurel's 247 Shop it is the loss-prevention layer for unstaffed operation. Flagging a concealment was its intended use.", "system": "Veesion AI gesture-recognition camera analysis integrated into Laurel Kft.'s 247 Shop hybrid-store platform, with alerts to a remote dispatch service", "model_version": "Not reported", "developer": "Veesion", "deployer": "Coop Szeged Zrt. (store operator), with Laurel Kft. as technology partner", "location": "Szeged, Hungary", "domain": "Retail loss prevention", "segment": "Grocery retail", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-10-09-70ff" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The store operator gained a flagged concealment and footage that led police to the perpetrator within hours. Three attempts were exposed over four and a half months of unstaffed night trading. The operators say shrinkage did not rise. All figures are the companies' own. No loss amount or recovery is reported." } ], "ai_role": { "status": "unassessed", "statement": "By the operators' account, the Veesion analysis flagged the shopper's concealment gesture in real time and alerted the remote dispatcher. The camera footage let police catch the perpetrator within hours. No police statement, loss figure or description of what the dispatcher did at the moment of the alert was found. Whether the theft was stopped in progress or only documented, and whether the goods came back, is unknown. The claim rests on a joint press release by the deployer and its integrator, relayed by independent outlets." }, "evidence": [ { "kind": "news report", "citation": "Simon B K (2025). Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni. Index.hu, 9 October 2025, 20:39; the article says its facts are 'olvasható a sajtóközleményben', i.e. taken from the companies' press release.", "title": "Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni", "url": "https://index.hu/gazdasag/2025/10/09/magyar-okosbolt-szeged-ai-lopas-lebuktatas/", "date": "2025-10-09", "written_by": "independent", "quote": "a rendőrség a kamerafelvételek alapján néhány órán belül elfogta az elkövetőt" }, { "kind": "news report", "citation": "Mínuszos.hu (2025). AI leplezett le tolvajokat a szegedi hibrid okosboltban. Mínuszos.hu, 11 October 2025; names Veesion as a French company and the store as the Szent István tér Coop opened at the end of May.", "title": "AI leplezett le tolvajokat a szegedi hibrid okosboltban", "url": "https://www.minuszos.hu/ai-leplezett-le-tolvajokat-a-szegedi-hibrid-okosboltban/", "date": "2025-10-11", "written_by": "independent", "quote": "A mesterséges intelligenciával (AI) támogatott rendszer az elmúlt hónapokban három lopási kísérletet is sikeresen azonosított és akadályozott meg." }, { "kind": "news report", "citation": "ProfitLine.hu / MTI (2025). Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt. ProfitLine.hu, 11 October 2025, carrying the MTI agency report of the companies' statement; gives 150 square metres, 4,000 SKUs, and quotes István Bessenyei (Laurel) and János Kelemen (Coop Szeged).", "title": "Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt.", "url": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176", "date": "2025-10-11", "written_by": "independent", "quote": "az arcok azonosítása nélkül elemzi a vásárlói mozgásokat, és azonnal jelzi a távoli diszpécserszolgálatnak a gyanús viselkedést" }, { "kind": "news report", "citation": "Turizmus Online / MTI (2025). A szegediek szeretik az okosboltokat – újabbakat nyitnak. Turizmus Online, 13 October 2025; reports 8,500 purchases in four and a half months and no rise in shrinkage despite the longer hours, per the operators.", "title": "A szegediek szeretik az okosboltokat – újabbakat nyitnak", "url": "https://turizmusonline.hu/cikkek/gasztro/a-szegediek-szeretik-az-okosboltokat--ujabbakat-nyitnak.html", "date": "2025-10-13", "written_by": "independent", "quote": "az új típusú bolt az indulás óta stabilan, a várakozások felett teljesít" }, { "kind": "news report", "citation": "Economx (2026). Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket. economx.hu, 30 September 2026.", "title": "Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket", "url": "https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "date": "2026-09-30", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Gesture-recognition analysis watching every shopper during the hours when no staff are present, tuned to concealment movements rather than faces", "A remote dispatch service that receives the alert immediately, and camera footage that can be handed to police", "A sales floor small enough (150 square meters, 4,000 SKUs) for the cameras to cover it entirely" ], "must_hold": [ "The flagged gesture is a real theft rather than an innocent movement. The operators report no false-alarm figures", "Police are willing and able to act on the footage quickly, here within hours", "The system keeps analyzing movements without identifying faces, as the operators describe it" ], "echoes": [] }, "paired_incident": null, "headline": "Veesion alert may have led police to a Szeged shoplifter", "metric": "over four and a half months the system had exposed three theft attempts", "comparator": { "against": "inventory shrinkage under the store's previous staffed-only opening hours", "before": null, "after": "nem nőtt meg a leltárhiány", "basis": "measured", "quote": "Tájékoztatásuk szerint a két cég együttműködésével elindult szegedi üzletben négy és fél hónap alatt már 8500-an vásároltak az éjszakai, automata rendszerben, és az egész naposra kiterjesztett nyitvatartással járó jelentős forgalomtöbblet dacára nem nőtt meg a leltárhiány.", "url": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176" }, "later": { "status": "scaled", "date": "2026-09-30", "note": "Coop Szeged and Laurel opened a second staffless-after-hours store, a full supermarket on Temesvári körút, on 30 September 2026, after more than 27,000 unstaffed purchases in a year at the first store; the report describes camera monitoring and a remote dispatch service but does not name Veesion.", "quote": "most pedig ugyanebben a városban, a Temesvári körúton nyílt meg a második, ami immáron a méreteit tekintve egy kész szupermarket.", "url": "https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/" }, "value": null, "developer_country": "France", "deployer_country": "Hungary", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-09-70ff", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176; https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://veesion.io/mentions-legales/; https://www.coopszeged.hu/kapcsolat", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0148", "catalog_version": "1.0.0", "source_fingerprint": "426c9b02e8e63eb5fd423b6a1cf78ec516aaabb2e070563d9f80bd9468b3faa2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0148-source-0001", "AIBD-0148-source-0002", "AIBD-0148-source-0003", "AIBD-0148-source-0004", "AIBD-0148-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Veesion", "deployer": "Coop Szeged Zrt. (store operator), with Laurel Kft. as technology partner" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "unassessed", "statement": "By the operators' account, the Veesion analysis flagged the shopper's concealment gesture in real time and alerted the remote dispatcher. The camera footage let police catch the perpetrator within hours. No police statement, loss figure or description of what the dispatcher did at the moment of the alert was found. Whether the theft was stopped in progress or only documented, and whether the goods came back, is unknown. The claim rests on a joint press release by the deployer and its integrator, relayed by independent outlets." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The store operator gained a flagged concealment and footage that led police to the perpetrator within hours. Three attempts were exposed over four and a half months of unstaffed night trading. The operators say shrinkage did not rise. All figures are the companies' own. No loss amount or recovery is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The store operator gained a flagged concealment and footage that led police to the perpetrator within hours. Three attempts were exposed over four and a half months of unstaffed night trading. The operators say shrinkage did not rise. All figures are the companies' own. No loss amount or recovery is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The store operator gained a flagged concealment and footage that led police to the perpetrator within hours. Three attempts were exposed over four and a half months of unstaffed night trading. The operators say shrinkage did not rise. All figures are the companies' own. No loss amount or recovery is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "over four and a half months the system had exposed three theft attempts", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-10-09-70ff" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-09-30", "note": "Coop Szeged and Laurel opened a second staffless-after-hours store, a full supermarket on Temesvári körút, on 30 September 2026, after more than 27,000 unstaffed purchases in a year at the first store; the report describes camera monitoring and a remote dispatch service but does not name Veesion.", "quote": "most pedig ugyanebben a városban, a Temesvári körúton nyílt meg a második, ami immáron a méreteit tekintve egy kész szupermarket.", "url": "https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0148" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Coop Szeged Zrt. and Laurel Kft. opened the 247 Shop on Szent István tér in Szeged at the end of May 2025. It is staffed by day, automated and unstaffed outside normal hours. Cameras running the French company Veesion's software analyze shoppers' movements without identifying faces. They alert a remote dispatch service to gestures such as concealing goods. On 9 October 2025 the operators issued a press release relayed by Index.hu and MTI. It said over four and a half months the system had exposed three theft attempts. In one, a person hid products under their clothing during night mode. Police caught the perpetrator within hours using the footage. Dates, recovered goods and any police statement are not reported.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The store operator gained a flagged concealment and footage that led police to the perpetrator within hours. Three attempts were exposed over four and a half months of unstaffed night trading. The operators say shrinkage did not rise. All figures are the companies' own. No loss amount or recovery is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Veesion's gesture-recognition software is built to spot shoplifting movements such as concealing goods and to raise an immediate alert. In Laurel's 247 Shop it is the loss-prevention layer for unstaffed operation. Flagging a concealment was its intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Szeged, Hungary", "developer_country": "France", "deployer_country": "Hungary" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Veesion's gesture-recognition software is built to spot shoplifting movements such as concealing goods and to raise an immediate alert. In Laurel's 247 Shop it is the loss-prevention layer for unstaffed operation. Flagging a concealment was its intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-10-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-09-70ff", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176; https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://veesion.io/mentions-legales/; https://www.coopszeged.hu/kapcsolat", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Gesture-recognition analysis watching every shopper during the hours when no staff are present, tuned to concealment movements rather than faces", "A remote dispatch service that receives the alert immediately, and camera footage that can be handed to police", "A sales floor small enough (150 square meters, 4,000 SKUs) for the cameras to cover it entirely" ], "must_hold": [ "The flagged gesture is a real theft rather than an innocent movement. The operators report no false-alarm figures", "Police are willing and able to act on the footage quickly, here within hours", "The system keeps analyzing movements without identifying faces, as the operators describe it" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-09-70ff", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176; https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://veesion.io/mentions-legales/; https://www.coopszeged.hu/kapcsolat", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Retail loss prevention", "segment": "Grocery retail" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Simon B K (2025). Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni. Index.hu, 9 October 2025, 20:39; the article says its facts are 'olvasható a sajtóközleményben', i.e. taken from the companies' press release.", "title": "Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni", "url": "https://index.hu/gazdasag/2025/10/09/magyar-okosbolt-szeged-ai-lopas-lebuktatas/", "date": "2025-10-09", "written_by": "independent", "quote": "a rendőrség a kamerafelvételek alapján néhány órán belül elfogta az elkövetőt" }, { "kind": "news report", "citation": "Mínuszos.hu (2025). AI leplezett le tolvajokat a szegedi hibrid okosboltban. Mínuszos.hu, 11 October 2025; names Veesion as a French company and the store as the Szent István tér Coop opened at the end of May.", "title": "AI leplezett le tolvajokat a szegedi hibrid okosboltban", "url": "https://www.minuszos.hu/ai-leplezett-le-tolvajokat-a-szegedi-hibrid-okosboltban/", "date": "2025-10-11", "written_by": "independent", "quote": "A mesterséges intelligenciával (AI) támogatott rendszer az elmúlt hónapokban három lopási kísérletet is sikeresen azonosított és akadályozott meg." }, { "kind": "news report", "citation": "ProfitLine.hu / MTI (2025). Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt. ProfitLine.hu, 11 October 2025, carrying the MTI agency report of the companies' statement; gives 150 square metres, 4,000 SKUs, and quotes István Bessenyei (Laurel) and János Kelemen (Coop Szeged).", "title": "Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt.", "url": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176", "date": "2025-10-11", "written_by": "independent", "quote": "az arcok azonosítása nélkül elemzi a vásárlói mozgásokat, és azonnal jelzi a távoli diszpécserszolgálatnak a gyanús viselkedést" }, { "kind": "news report", "citation": "Turizmus Online / MTI (2025). A szegediek szeretik az okosboltokat – újabbakat nyitnak. Turizmus Online, 13 October 2025; reports 8,500 purchases in four and a half months and no rise in shrinkage despite the longer hours, per the operators.", "title": "A szegediek szeretik az okosboltokat – újabbakat nyitnak", "url": "https://turizmusonline.hu/cikkek/gasztro/a-szegediek-szeretik-az-okosboltokat--ujabbakat-nyitnak.html", "date": "2025-10-13", "written_by": "independent", "quote": "az új típusú bolt az indulás óta stabilan, a várakozások felett teljesít" }, { "kind": "news report", "citation": "Economx (2026). Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket. economx.hu, 30 September 2026.", "title": "Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket", "url": "https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "date": "2026-09-30", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0148-source-0001", "AIBD-0148-source-0002", "AIBD-0148-source-0003", "AIBD-0148-source-0004", "AIBD-0148-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Simon B K (2025). Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni. Index.hu, 9 October 2025, 20:39; the article says its facts are 'olvasható a sajtóközleményben', i.e. taken from the companies' press release.", "title": "Tolvajokat buktatott le az AI, az első magyar okosboltból próbáltak meg árut kicsenni", "url": "https://index.hu/gazdasag/2025/10/09/magyar-okosbolt-szeged-ai-lopas-lebuktatas/", "date": "2025-10-09", "written_by": "independent", "quote": "a rendőrség a kamerafelvételek alapján néhány órán belül elfogta az elkövetőt" }, { "kind": "news report", "citation": "Mínuszos.hu (2025). AI leplezett le tolvajokat a szegedi hibrid okosboltban. Mínuszos.hu, 11 October 2025; names Veesion as a French company and the store as the Szent István tér Coop opened at the end of May.", "title": "AI leplezett le tolvajokat a szegedi hibrid okosboltban", "url": "https://www.minuszos.hu/ai-leplezett-le-tolvajokat-a-szegedi-hibrid-okosboltban/", "date": "2025-10-11", "written_by": "independent", "quote": "A mesterséges intelligenciával (AI) támogatott rendszer az elmúlt hónapokban három lopási kísérletet is sikeresen azonosított és akadályozott meg." }, { "kind": "news report", "citation": "ProfitLine.hu / MTI (2025). Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt. ProfitLine.hu, 11 October 2025, carrying the MTI agency report of the companies' statement; gives 150 square metres, 4,000 SKUs, and quotes István Bessenyei (Laurel) and János Kelemen (Coop Szeged).", "title": "Újabb hibrid okosboltok kialakítását tervezi a Coop Szeged Zrt.", "url": "https://profitline.hu/ujabb-hibrid-okosboltok-kialakitasat-tervezi-a-coop-szeged-zrt-479176", "date": "2025-10-11", "written_by": "independent", "quote": "az arcok azonosítása nélkül elemzi a vásárlói mozgásokat, és azonnal jelzi a távoli diszpécserszolgálatnak a gyanús viselkedést" }, { "kind": "news report", "citation": "Turizmus Online / MTI (2025). A szegediek szeretik az okosboltokat – újabbakat nyitnak. Turizmus Online, 13 October 2025; reports 8,500 purchases in four and a half months and no rise in shrinkage despite the longer hours, per the operators.", "title": "A szegediek szeretik az okosboltokat – újabbakat nyitnak", "url": "https://turizmusonline.hu/cikkek/gasztro/a-szegediek-szeretik-az-okosboltokat--ujabbakat-nyitnak.html", "date": "2025-10-13", "written_by": "independent", "quote": "az új típusú bolt az indulás óta stabilan, a várakozások felett teljesít" }, { "kind": "news report", "citation": "Economx (2026). Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket. economx.hu, 30 September 2026.", "title": "Nincs pénztáros, nincs eladó: megnyílt az első magyar személyzet nélküli szupermarket", "url": "https://www.economx.hu/vallalatok/2026/09/30/coop-szupermarket-szeged-szemelyzet-nelkuli-laurel/", "date": "2026-09-30", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI cameras in Szeged's unstaffed-at-night Coop flagged a shopper hiding goods; police caught them within hours, the operators said.", "account": "Coop Szeged Zrt. and Laurel Kft. opened the 247 Shop on Szent István tér in Szeged at the end of May 2025. It is staffed by day, automated and unstaffed outside normal hours. Cameras running the French company Veesion's software analyze shoppers' movements without identifying faces. They alert a remote dispatch service to gestures such as concealing goods. On 9 October 2025 the operators issued a press release relayed by Index.hu and MTI. It said over four and a half months the system had exposed three theft attempts. In one, a person hid products under their clothing during night mode. Police caught the perpetrator within hours using the footage. Dates, recovered goods and any police statement are not reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Veesion AI gesture-recognition camera analysis integrated into Laurel Kft.'s 247 Shop hybrid-store platform, with alerts to a remote dispatch service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Veesion" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Veesion gesture-recognition cameras in Coop Szeged's 247 Shop on Szent István tér, unstaffed at night, may have flagged a shopper hiding goods under clothing and led police to the perpetrator within hours, one of three attempts exposed since May 2025", "headline": "Veesion alert may have led police to a Szeged shoplifter" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "426c9b02e8e63eb5fd423b6a1cf78ec516aaabb2e070563d9f80bd9468b3faa2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Coop Szeged Zrt. and Laurel Kft. opened the 247 Shop on Szent István tér in Szeged at the end of May 2025. It is staffed by day, automated and unstaffed outside normal hours. Cameras running the French company Veesion's software analyze shoppers' movements without identifying faces. They alert a remote dispatch service to gestures such as concealing goods. On 9 October 2025 the operators issued a press release relayed by Index.hu and MTI. It said over four and a half months the system had exposed three theft attempts. In one, a person hid products under their clothing during night mode. Police caught the perpetrator within hours using the footage. Dates, recovered goods and any police statement are not reported.", "replication": { "produced_by": [ "Gesture-recognition analysis watching every shopper during the hours when no staff are present, tuned to concealment movements rather than faces", "A remote dispatch service that receives the alert immediately, and camera footage that can be handed to police", "A sales floor small enough (150 square meters, 4,000 SKUs) for the cameras to cover it entirely" ], "must_hold": [ "The flagged gesture is a real theft rather than an innocent movement. The operators report no false-alarm figures", "Police are willing and able to act on the footage quickly, here within hours", "The system keeps analyzing movements without identifying faces, as the operators describe it" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0149", "title": "Frankfurt police found a missing 16-year-old who had left a farewell letter on Taunusstraße within a day of her disappearance, after a judge-confirmed emergency order let the Bahnhofsviertel camera system's AI search for her face", "summary": "Frankfurt police found a missing 16-year-old in crisis within a day via a court-backed AI face search of Bahnhofsviertel cameras.", "date_observed": "2025-10-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 8 October 2025 a 16-year-old was reported missing after failing to return to the psychiatric facility in Hesse where she lived. A farewell letter pointed to an acute psychological crisis. Indications placed her in Frankfurt's Bahnhofsviertel. Citing imminent danger, Frankfurt's police president issued an emergency order, confirmed by a judge. So her photograph could be entered into the AI-assisted camera system running in the district since July 2025. It operates under the Hessian police law amended in February 2025. Late on 9 October the system flagged a match on Taunusstraße. A video operator checked it and a patrol confirmed it. Officers took the girl into protective custody and returned her to the child and adolescent psychiatric facility.", "category": "protective response", "unexpected": false, "purpose": "The Bahnhofsviertel Videoschutzanlage's AI performs real-time biometric remote identification. The Hessian police law amended in February 2025 allows this for narrow purposes such as finding missing persons. Locating a missing minor was that intended use. The police press release called it the system's first genuine positive hit.", "system": "AI-assisted video analysis with real-time biometric remote identification in the Frankfurt Bahnhofsviertel police video surveillance system (Videoschutzanlage), monitored from the police Video-Operation-Center", "model_version": "Not reported; none of the sources names a vendor, product or version for the facial-recognition component, and netzpolitik.org (April 2026) says only that it matches against the BKA facial-recognition database", "developer": null, "deployer": "Polizeipräsidium Frankfurt am Main (Hessian police)", "location": "Frankfurt am Main, Germany", "domain": "Policing and missing-person search", "segment": "Public safety", "benefit_type": "Improved Physical Health", "taxonomy_note": "Finding a missing minor in crisis is read as a rescue; no injury or treatment is reported.", "registry_ids": { "oecd_aim": "2025-10-16-7e48" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "A 16-year-old whose farewell letter led police to assume an acute psychological crisis was located in the Bahnhofsviertel within a day. She was returned to psychiatric care. The police frame this as averting danger to life and limb. But no source reports what would otherwise have happened, so life-saving is not established." }, { "group": "organizational", "depth": 1, "reason": "The Frankfurt police recorded the first confirmed success of a system in use since July 2025. The police president and the interior minister cited it as validation. netzpolitik.org reported in April 2026 that it was still the only success among a low double-digit number of searches. The operational gain is modest." } ], "ai_role": { "status": "assessed", "statement": "The police press release documents the system's contribution step by step. After a judge-confirmed emergency order, the girl's photo was entered into the database. Late on 9 October the AI produced an automated match alert for Taunusstraße. A video operator checked it and a patrol confirmed it in person. The police had only indications that she might be in the district, so the AI supplied the place and the moment. Human verification and the patrol did the rest. Whether and how soon conventional patrols would have found her is not reported." }, "evidence": [ { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main, reproduced by Heßberger K (2025). Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel. Rhein Main Verlag, 16 October 2025; the page is marked 'Text: PM PP Frankfurt', i.e. the police press release text.", "title": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel", "url": "https://www.rheinmainverlag.de/2025/10/16/kuenstliche-intelligenz-lokalisiert-16-jaehrige-vermisste-im-frankfurter-bahnhofsviertel/", "date": "2025-10-16", "written_by": "deployer", "quote": "Bereits am 9. Oktober, nur einen Tag nach der Vermisstenmeldung, wurde in den späten Abendstunden im Video-Operation-Center der Frankfurter Polizei eine automatisierte Treffermeldung im Bereich der Taunusstraße angezeigt." }, { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main (2025). POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen. Presseportal, 16 October 2025. The page returned HTTP 503 on 20 October 2026; its title was read on the OECD Monitor entry and its text in the Rhein Main Verlag reproduction cited above.", "title": "POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen", "url": "https://www.presseportal.de/blaulicht/pm/4970/6138810", "date": "2025-10-16", "written_by": "deployer", "quote": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen" }, { "kind": "news report", "citation": "Euler R (2025). Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI. Frankfurter Allgemeine Zeitung, 16 October 2025, 15:42; paywalled beyond the opening paragraphs.", "title": "Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI", "url": "https://www.faz.net/aktuell/rhein-main/frankfurt/frankfurter-polizei-findet-vermisstes-maedchen-mithilfe-von-ki-110735027.html", "date": "2025-10-16", "written_by": "independent", "quote": "Mithilfe künstlicher Intelligenz hat die Polizei in der vergangenen Woche eine vermisste Sechzehnjährige im Frankfurter Bahnhofsviertel lokalisiert und in Obhut genommen." }, { "kind": "news report", "citation": "Pfeiffer-Goldmann D (2025). KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden. Frankfurter Neue Presse, 17 October 2025, 14:10; the OECD Monitor lists the same URL under the earlier headline 'KI in Frankfurt erstmals erfolgreich bei Suche nach Mensch per Videoüberwachung'. Quotes police spokesman Patrick Rüter and Interior Minister Roman Poseck.", "title": "KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden", "url": "https://www.fnp.de/frankfurt/ki-technik-hilft-polizei-in-frankfurt-bei-suche-nach-vermisster-93990652.html", "date": "2025-10-17", "written_by": "independent", "quote": "Einen Tag später habe die KI automatisch einen Treffer in der Taunusstraße gemeldet. Ein Videooperator habe das überprüft" }, { "kind": "news report", "citation": "Schröder D (2025). KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt. Bild, 17 October 2025; the quoted sentence is attributed to Police President Stefan Müller.", "title": "KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt", "url": "https://www.bild.de/regional/frankfurt/ki-rettet-vermisstes-maedchen-16-aus-drogen-sumpf-von-frankfurt-68f0b438672b2f7280fac3b4", "date": "2025-10-17", "written_by": "independent", "quote": "Der erste echte positive Treffer zeigt eindrucksvoll, wie uns auf Basis des neuen Polizeigesetzes modernste Technik zuverlässig und erfolgreich bei der Abwehr von Gefahren für Leib und Leben hilft." }, { "kind": "news report", "citation": "Schwarzbeck M (2026). Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht. netzpolitik.org, 22 April 2026; reports 29 cameras in the Bahnhofsviertel, 19 of them usable for automated face recognition, a low double-digit number of persons searched since July 2025, and this case as the only success.", "title": "Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "date": "2026-04-22", "written_by": "independent", "quote": "Erfolg gab es nur einmal, als eine vermisste 16-Jährige mit der Kamera-KI identifiziert wurde" }, { "kind": "news report", "citation": "Kissel L, Pfeuffer-Rooschüz L (2026). Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI. hessenschau.de, 25 March 2026; cites this case as the pilot's one reported success and carries criticism from the Chaos Computer Club and the Hessian data protection commissioner.", "title": "Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI", "url": "https://www.hessenschau.de/gesellschaft/hessen-erfand-den-datenschutz--und-ist-heute-vorreiter-bei-videoueberwachung-mit-ki-v1,erfindung-datenschutz-hessen-100.html", "date": "2026-03-25", "written_by": "independent", "quote": "Diese Anlagen können von einem Hilfsmittel zu einem Herrschaftsmittel werden" } ], "replication": { "produced_by": [ "A missing-person report with concrete signs of danger to life (a farewell letter) and indications of the person's whereabouts inside the camera-covered district", "A legal basis, the Hessian police law amended in February 2025, plus a police-president emergency order confirmed by a judge. These let the girl's photo be entered into the system", "An AI-assisted camera network already running in the Bahnhofsviertel since July 2025, with a staffed Video-Operation-Center. Patrols close enough to verify and act on a match the same evening" ], "must_hold": [ "The person passes in front of cameras suitable for automated recognition. netzpolitik.org counted 19 such cameras among the district's 29", "A human operator and a patrol verify the automated match before anyone is taken into custody", "The search stays within the narrow legal purposes the law allows, which Bild lists as missing persons, kidnapping victims and victims of human trafficking" ], "echoes": [] }, "paired_incident": null, "headline": "Frankfurt camera AI finds a missing 16-year-old within a day", "metric": "found a missing 16-year-old in crisis within a day", "comparator": { "against": "all persons searched for with the Bahnhofsviertel face-recognition system since July 2025, a low double-digit number", "before": null, "after": "Erfolg gab es nur einmal, als eine vermisste 16-Jährige mit der Kamera-KI identifiziert wurde.", "basis": "measured", "quote": "Das System läuft seit Juli 2025, seitdem wurde „eine niedrige zweistellige Anzahl an Personen“ damit gesucht. Erfolg gab es nur einmal, als eine vermisste 16-Jährige mit der Kamera-KI identifiziert wurde.", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/" }, "later": { "status": "litigated", "date": "2026-04-22", "note": "By April 2026 the Hessian Greens had asked the Staatsgerichtshof to review the police-law amendment behind real-time face recognition, and Doña Carmen's Juanita Henning with the GFF had sued at the Frankfurt administrative court asking for referral to the Federal Constitutional Court; the system kept running, with an evaluation phase due from July 2026.", "quote": "Die lassen mit einem Normenkontrollantrag beim Staatsgerichtshof klären , ob die der Echtzeit-Fernidentifizierung zugrunde liegende Polizeigesetzänderung rechtens war. Eine Überprüfung der Rechtsgrundlage streben auch Juanita Henning und die GFF an. Sie haben beim Verwaltungsgericht Frankfurt beantragt, dass es die Abschnitte aus dem Polizeigesetz, die die Fernidentifizierung erlauben, dem Bundesverfassungsgericht vorlegt.", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/" }, "value": null, "developer_country": null, "deployer_country": "Germany", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-16-7e48", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/; https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://de.wikipedia.org/wiki/Polizeipräsidium_Frankfurt_am_Main", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0149", "catalog_version": "1.0.0", "source_fingerprint": "a26560751e2527e5a9f380a895ed0cfdf3dd7b6dd096325e1fc47c76618cf190", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0149-source-0001", "AIBD-0149-source-0002", "AIBD-0149-source-0003", "AIBD-0149-source-0004", "AIBD-0149-source-0005", "AIBD-0149-source-0006", "AIBD-0149-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Polizeipräsidium Frankfurt am Main (Hessian police)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The police press release documents the system's contribution step by step. After a judge-confirmed emergency order, the girl's photo was entered into the database. Late on 9 October the AI produced an automated match alert for Taunusstraße. A video operator checked it and a patrol confirmed it in person. The police had only indications that she might be in the district, so the AI supplied the place and the moment. Human verification and the patrol did the rest. Whether and how soon conventional patrols would have found her is not reported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The police press release documents the system's contribution step by step. After a judge-confirmed emergency order, the girl's photo was entered into the database. Late on 9 October the AI produced an automated match alert for Taunusstraße. A video operator checked it and a patrol confirmed it in person. The police had only indications that she might be in the district, so the AI supplied the place and the moment. Human verification and the patrol did the rest. Whether and how soon conventional patrols would have found her is not reported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 16-year-old whose farewell letter led police to assume an acute psychological crisis was located in the Bahnhofsviertel within a day. She was returned to psychiatric care. The police frame this as averting danger to life and limb. But no source reports what would otherwise have happened, so life-saving is not established." }, { "group": "organizational", "depth": 1, "reason": "The Frankfurt police recorded the first confirmed success of a system in use since July 2025. The police president and the interior minister cited it as validation. netzpolitik.org reported in April 2026 that it was still the only success among a low double-digit number of searches. The operational gain is modest." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 16-year-old whose farewell letter led police to assume an acute psychological crisis was located in the Bahnhofsviertel within a day. She was returned to psychiatric care. The police frame this as averting danger to life and limb. But no source reports what would otherwise have happened, so life-saving is not established." }, { "group": "organizational", "depth": 1, "reason": "The Frankfurt police recorded the first confirmed success of a system in use since July 2025. The police president and the interior minister cited it as validation. netzpolitik.org reported in April 2026 that it was still the only success among a low double-digit number of searches. The operational gain is modest." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The girl received help during an apparent acute crisis. The police found her within a day, but no source establishes that the search saved her life. The system had one confirmed success among a low double-digit number of searches by April 2026." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 16-year-old whose farewell letter led police to assume an acute psychological crisis was located in the Bahnhofsviertel within a day. She was returned to psychiatric care. The police frame this as averting danger to life and limb. But no source reports what would otherwise have happened, so life-saving is not established." }, { "group": "organizational", "depth": 1, "reason": "The Frankfurt police recorded the first confirmed success of a system in use since July 2025. The police president and the interior minister cited it as validation. netzpolitik.org reported in April 2026 that it was still the only success among a low double-digit number of searches. The operational gain is modest." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Police located the girl within a day. By April 2026, this remained the system’s only confirmed success among a low double-digit number of searches." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Time to locate the missing person and the number of confirmed successful searches." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The police described a risk to life, but the sources do not establish what would have happened without the search. In April 2026, netzpolitik.org reported that this remained the only confirmed success among a low double-digit number of searches." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-10-16-7e48" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "litigated", "date": "2026-04-22", "note": "By April 2026 the Hessian Greens had asked the Staatsgerichtshof to review the police-law amendment behind real-time face recognition, and Doña Carmen's Juanita Henning with the GFF had sued at the Frankfurt administrative court asking for referral to the Federal Constitutional Court; the system kept running, with an evaluation phase due from July 2026.", "quote": "Die lassen mit einem Normenkontrollantrag beim Staatsgerichtshof klären , ob die der Echtzeit-Fernidentifizierung zugrunde liegende Polizeigesetzänderung rechtens war. Eine Überprüfung der Rechtsgrundlage streben auch Juanita Henning und die GFF an. Sie haben beim Verwaltungsgericht Frankfurt beantragt, dass es die Abschnitte aus dem Polizeigesetz, die die Fernidentifizierung erlauben, dem Bundesverfassungsgericht vorlegt.", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0149" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "The missing girl and the Frankfurt officers who searched for her." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The missing girl and the Frankfurt officers who searched for her." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "One girl." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "One girl." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "Finding a missing minor in crisis is read as a rescue; no injury or treatment is reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 8 October 2025 a 16-year-old was reported missing after failing to return to the psychiatric facility in Hesse where she lived. A farewell letter pointed to an acute psychological crisis. Indications placed her in Frankfurt's Bahnhofsviertel. Citing imminent danger, Frankfurt's police president issued an emergency order, confirmed by a judge. So her photograph could be entered into the AI-assisted camera system running in the district since July 2025. It operates under the Hessian police law amended in February 2025. Late on 9 October the system flagged a match on Taunusstraße. A video operator checked it and a patrol confirmed it. Officers took the girl into protective custody and returned her to the child and adolescent psychiatric facility.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Police found a missing 16-year-old within a day and returned her to psychiatric care." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "A 16-year-old whose farewell letter led police to assume an acute psychological crisis was located in the Bahnhofsviertel within a day. She was returned to psychiatric care. The police frame this as averting danger to life and limb. But no source reports what would otherwise have happened, so life-saving is not established." }, { "group": "organizational", "depth": 1, "reason": "The Frankfurt police recorded the first confirmed success of a system in use since July 2025. The police president and the interior minister cited it as validation. netzpolitik.org reported in April 2026 that it was still the only success among a low double-digit number of searches. The operational gain is modest." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The Bahnhofsviertel Videoschutzanlage's AI performs real-time biometric remote identification. The Hessian police law amended in February 2025 allows this for narrow purposes such as finding missing persons. Locating a missing minor was that intended use. The police press release called it the system's first genuine positive hit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Frankfurt am Main, Germany", "deployer_country": "Germany" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The Bahnhofsviertel Videoschutzanlage's AI performs real-time biometric remote identification. The Hessian police law amended in February 2025 allows this for narrow purposes such as finding missing persons. Locating a missing minor was that intended use. The police press release called it the system's first genuine positive hit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-10-09", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-16-7e48", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/; https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://de.wikipedia.org/wiki/Polizeipräsidium_Frankfurt_am_Main", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A missing-person report with concrete signs of danger to life (a farewell letter) and indications of the person's whereabouts inside the camera-covered district", "A legal basis, the Hessian police law amended in February 2025, plus a police-president emergency order confirmed by a judge. These let the girl's photo be entered into the system", "An AI-assisted camera network already running in the Bahnhofsviertel since July 2025, with a staffed Video-Operation-Center. Patrols close enough to verify and act on a match the same evening" ], "must_hold": [ "The person passes in front of cameras suitable for automated recognition. netzpolitik.org counted 19 such cameras among the district's 29", "A human operator and a patrol verify the automated match before anyone is taken into custody", "The search stays within the narrow legal purposes the law allows, which Bild lists as missing persons, kidnapping victims and victims of human trafficking" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Suitable cameras must cover the person’s route. Operators and police patrols must verify the match, and the search needs a lawful basis." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-10-16-7e48", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/; https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://de.wikipedia.org/wiki/Polizeipräsidium_Frankfurt_am_Main", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing and missing-person search", "segment": "Public safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main, reproduced by Heßberger K (2025). Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel. Rhein Main Verlag, 16 October 2025; the page is marked 'Text: PM PP Frankfurt', i.e. the police press release text.", "title": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel", "url": "https://www.rheinmainverlag.de/2025/10/16/kuenstliche-intelligenz-lokalisiert-16-jaehrige-vermisste-im-frankfurter-bahnhofsviertel/", "date": "2025-10-16", "written_by": "deployer", "quote": "Bereits am 9. Oktober, nur einen Tag nach der Vermisstenmeldung, wurde in den späten Abendstunden im Video-Operation-Center der Frankfurter Polizei eine automatisierte Treffermeldung im Bereich der Taunusstraße angezeigt." }, { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main (2025). POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen. Presseportal, 16 October 2025. The page returned HTTP 503 on 20 October 2026; its title was read on the OECD Monitor entry and its text in the Rhein Main Verlag reproduction cited above.", "title": "POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen", "url": "https://www.presseportal.de/blaulicht/pm/4970/6138810", "date": "2025-10-16", "written_by": "deployer", "quote": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen" }, { "kind": "news report", "citation": "Euler R (2025). Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI. Frankfurter Allgemeine Zeitung, 16 October 2025, 15:42; paywalled beyond the opening paragraphs.", "title": "Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI", "url": "https://www.faz.net/aktuell/rhein-main/frankfurt/frankfurter-polizei-findet-vermisstes-maedchen-mithilfe-von-ki-110735027.html", "date": "2025-10-16", "written_by": "independent", "quote": "Mithilfe künstlicher Intelligenz hat die Polizei in der vergangenen Woche eine vermisste Sechzehnjährige im Frankfurter Bahnhofsviertel lokalisiert und in Obhut genommen." }, { "kind": "news report", "citation": "Pfeiffer-Goldmann D (2025). KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden. Frankfurter Neue Presse, 17 October 2025, 14:10; the OECD Monitor lists the same URL under the earlier headline 'KI in Frankfurt erstmals erfolgreich bei Suche nach Mensch per Videoüberwachung'. Quotes police spokesman Patrick Rüter and Interior Minister Roman Poseck.", "title": "KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden", "url": "https://www.fnp.de/frankfurt/ki-technik-hilft-polizei-in-frankfurt-bei-suche-nach-vermisster-93990652.html", "date": "2025-10-17", "written_by": "independent", "quote": "Einen Tag später habe die KI automatisch einen Treffer in der Taunusstraße gemeldet. Ein Videooperator habe das überprüft" }, { "kind": "news report", "citation": "Schröder D (2025). KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt. Bild, 17 October 2025; the quoted sentence is attributed to Police President Stefan Müller.", "title": "KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt", "url": "https://www.bild.de/regional/frankfurt/ki-rettet-vermisstes-maedchen-16-aus-drogen-sumpf-von-frankfurt-68f0b438672b2f7280fac3b4", "date": "2025-10-17", "written_by": "independent", "quote": "Der erste echte positive Treffer zeigt eindrucksvoll, wie uns auf Basis des neuen Polizeigesetzes modernste Technik zuverlässig und erfolgreich bei der Abwehr von Gefahren für Leib und Leben hilft." }, { "kind": "news report", "citation": "Schwarzbeck M (2026). Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht. netzpolitik.org, 22 April 2026; reports 29 cameras in the Bahnhofsviertel, 19 of them usable for automated face recognition, a low double-digit number of persons searched since July 2025, and this case as the only success.", "title": "Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "date": "2026-04-22", "written_by": "independent", "quote": "Erfolg gab es nur einmal, als eine vermisste 16-Jährige mit der Kamera-KI identifiziert wurde" }, { "kind": "news report", "citation": "Kissel L, Pfeuffer-Rooschüz L (2026). Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI. hessenschau.de, 25 March 2026; cites this case as the pilot's one reported success and carries criticism from the Chaos Computer Club and the Hessian data protection commissioner.", "title": "Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI", "url": "https://www.hessenschau.de/gesellschaft/hessen-erfand-den-datenschutz--und-ist-heute-vorreiter-bei-videoueberwachung-mit-ki-v1,erfindung-datenschutz-hessen-100.html", "date": "2026-03-25", "written_by": "independent", "quote": "Diese Anlagen können von einem Hilfsmittel zu einem Herrschaftsmittel werden" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0149-source-0001", "AIBD-0149-source-0002", "AIBD-0149-source-0003", "AIBD-0149-source-0004", "AIBD-0149-source-0005", "AIBD-0149-source-0006", "AIBD-0149-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main, reproduced by Heßberger K (2025). Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel. Rhein Main Verlag, 16 October 2025; the page is marked 'Text: PM PP Frankfurt', i.e. the police press release text.", "title": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Frankfurter Bahnhofsviertel", "url": "https://www.rheinmainverlag.de/2025/10/16/kuenstliche-intelligenz-lokalisiert-16-jaehrige-vermisste-im-frankfurter-bahnhofsviertel/", "date": "2025-10-16", "written_by": "deployer", "quote": "Bereits am 9. Oktober, nur einen Tag nach der Vermisstenmeldung, wurde in den späten Abendstunden im Video-Operation-Center der Frankfurter Polizei eine automatisierte Treffermeldung im Bereich der Taunusstraße angezeigt." }, { "kind": "press release", "citation": "Polizeipräsidium Frankfurt am Main (2025). POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen. Presseportal, 16 October 2025. The page returned HTTP 503 on 20 October 2026; its title was read on the OECD Monitor entry and its text in the Rhein Main Verlag reproduction cited above.", "title": "POL-F: 251016-1068 Frankfurt-Bahnhofsviertel: Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen", "url": "https://www.presseportal.de/blaulicht/pm/4970/6138810", "date": "2025-10-16", "written_by": "deployer", "quote": "Künstliche Intelligenz lokalisiert 16-jährige Vermisste im Bahnhofsviertel - Mädchen durch Polizisten in Obhut genommen" }, { "kind": "news report", "citation": "Euler R (2025). Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI. Frankfurter Allgemeine Zeitung, 16 October 2025, 15:42; paywalled beyond the opening paragraphs.", "title": "Polizei Frankfurt findet vermisstes Mädchen mithilfe von KI", "url": "https://www.faz.net/aktuell/rhein-main/frankfurt/frankfurter-polizei-findet-vermisstes-maedchen-mithilfe-von-ki-110735027.html", "date": "2025-10-16", "written_by": "independent", "quote": "Mithilfe künstlicher Intelligenz hat die Polizei in der vergangenen Woche eine vermisste Sechzehnjährige im Frankfurter Bahnhofsviertel lokalisiert und in Obhut genommen." }, { "kind": "news report", "citation": "Pfeiffer-Goldmann D (2025). KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden. Frankfurter Neue Presse, 17 October 2025, 14:10; the OECD Monitor lists the same URL under the earlier headline 'KI in Frankfurt erstmals erfolgreich bei Suche nach Mensch per Videoüberwachung'. Quotes police spokesman Patrick Rüter and Interior Minister Roman Poseck.", "title": "KI-Einsatz in Frankfurt erstmals erfolgreich – vermisstes Mädchen wiedergefunden", "url": "https://www.fnp.de/frankfurt/ki-technik-hilft-polizei-in-frankfurt-bei-suche-nach-vermisster-93990652.html", "date": "2025-10-17", "written_by": "independent", "quote": "Einen Tag später habe die KI automatisch einen Treffer in der Taunusstraße gemeldet. Ein Videooperator habe das überprüft" }, { "kind": "news report", "citation": "Schröder D (2025). KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt. Bild, 17 October 2025; the quoted sentence is attributed to Police President Stefan Müller.", "title": "KI rettet vermisstes Mädchen (16) aus Drogen-Sumpf von Frankfurt", "url": "https://www.bild.de/regional/frankfurt/ki-rettet-vermisstes-maedchen-16-aus-drogen-sumpf-von-frankfurt-68f0b438672b2f7280fac3b4", "date": "2025-10-17", "written_by": "independent", "quote": "Der erste echte positive Treffer zeigt eindrucksvoll, wie uns auf Basis des neuen Polizeigesetzes modernste Technik zuverlässig und erfolgreich bei der Abwehr von Gefahren für Leib und Leben hilft." }, { "kind": "news report", "citation": "Schwarzbeck M (2026). Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht. netzpolitik.org, 22 April 2026; reports 29 cameras in the Bahnhofsviertel, 19 of them usable for automated face recognition, a low double-digit number of persons searched since July 2025, and this case as the only success.", "title": "Rotlichtviertel Frankfurt am Main: Hier analysiert die Polizei jedes Gesicht", "url": "https://netzpolitik.org/2026/rotlichtviertel-frankfurt-am-main-hier-analysiert-die-polizei-jedes-gesicht/", "date": "2026-04-22", "written_by": "independent", "quote": "Erfolg gab es nur einmal, als eine vermisste 16-Jährige mit der Kamera-KI identifiziert wurde" }, { "kind": "news report", "citation": "Kissel L, Pfeuffer-Rooschüz L (2026). Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI. hessenschau.de, 25 March 2026; cites this case as the pilot's one reported success and carries criticism from the Chaos Computer Club and the Hessian data protection commissioner.", "title": "Hessen erfand den Datenschutz – und ist heute Vorreiter bei Videoüberwachung mit KI", "url": "https://www.hessenschau.de/gesellschaft/hessen-erfand-den-datenschutz--und-ist-heute-vorreiter-bei-videoueberwachung-mit-ki-v1,erfindung-datenschutz-hessen-100.html", "date": "2026-03-25", "written_by": "independent", "quote": "Diese Anlagen können von einem Hilfsmittel zu einem Herrschaftsmittel werden" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Frankfurt police found a missing 16-year-old in crisis within a day via a court-backed AI face search of Bahnhofsviertel cameras.", "account": "On 8 October 2025 a 16-year-old was reported missing after failing to return to the psychiatric facility in Hesse where she lived. A farewell letter pointed to an acute psychological crisis. Indications placed her in Frankfurt's Bahnhofsviertel. Citing imminent danger, Frankfurt's police president issued an emergency order, confirmed by a judge. So her photograph could be entered into the AI-assisted camera system running in the district since July 2025. It operates under the Hessian police law amended in February 2025. Late on 9 October the system flagged a match on Taunusstraße. A video operator checked it and a patrol confirmed it. Officers took the girl into protective custody and returned her to the child and adolescent psychiatric facility." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software matched a photograph against surveillance video and sent an alert for human verification." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The facial-recognition component compared images with the BKA’s database of facial images." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; none of the sources names a vendor, product or version for the facial-recognition component, and netzpolitik.org (April 2026) says only that it matches against the BKA facial-recognition database" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI-assisted video analysis with real-time biometric remote identification in the Frankfurt Bahnhofsviertel police video surveillance system (Videoschutzanlage), monitored from the police Video-Operation-Center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Frankfurt police found a missing 16-year-old who had left a farewell letter on Taunusstraße within a day of her disappearance, after a judge-confirmed emergency order let the Bahnhofsviertel camera system's AI search for her face", "headline": "Frankfurt camera AI finds a missing 16-year-old within a day" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a26560751e2527e5a9f380a895ed0cfdf3dd7b6dd096325e1fc47c76618cf190" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 8 October 2025 a 16-year-old was reported missing after failing to return to the psychiatric facility in Hesse where she lived. A farewell letter pointed to an acute psychological crisis. Indications placed her in Frankfurt's Bahnhofsviertel. Citing imminent danger, Frankfurt's police president issued an emergency order, confirmed by a judge. So her photograph could be entered into the AI-assisted camera system running in the district since July 2025. It operates under the Hessian police law amended in February 2025. Late on 9 October the system flagged a match on Taunusstraße. A video operator checked it and a patrol confirmed it. Officers took the girl into protective custody and returned her to the child and adolescent psychiatric facility.", "replication": { "produced_by": [ "A missing-person report with concrete signs of danger to life (a farewell letter) and indications of the person's whereabouts inside the camera-covered district", "A legal basis, the Hessian police law amended in February 2025, plus a police-president emergency order confirmed by a judge. These let the girl's photo be entered into the system", "An AI-assisted camera network already running in the Bahnhofsviertel since July 2025, with a staffed Video-Operation-Center. Patrols close enough to verify and act on a match the same evening" ], "must_hold": [ "The person passes in front of cameras suitable for automated recognition. netzpolitik.org counted 19 such cameras among the district's 29", "A human operator and a patrol verify the automated match before anyone is taken into custody", "The search stays within the narrow legal purposes the law allows, which Bild lists as missing persons, kidnapping victims and victims of human trafficking" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 0, "record_mapped": 33, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0237", "title": "curl merges about 50 bugfixes from Joshua Rogers' ZeroPath-assisted scans; maintainer calls the reports a new breed of analyzer output", "summary": "In Sept 2025 curl received hundreds of candidate issues found mainly with the ZeroPath AI analyzer by Joshua Rogers; maintainer Daniel Stenberg merged about 50 bugfixes from the first list.", "date_observed": "2025-10-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The reports arrived from mid-September 2025. Stenberg writes that a security report received on 16 September accurately identified a possible stack-based buffer overflow in curl's Kerberos FTP code. It was not turned into a CVE only because the code could not be reached. The project then removed krb5-ftp support. The reporter, Joshua Rogers, then forwarded a large list of further potential issues found mostly with ZeroPath, an AI-powered code analyzer. That produced over two hundred possible problems despite curl's existing compilers, static analyzers and fuzzing. From the initial list about 50 separately identifiable bugfixes were merged. Second and third lists of 47 and 158 items followed. Stenberg told The Register that about 50 bugfixes based on Rogers' reports had been merged. Rogers' retrospective states that about 98% of the curl bugs reported and fixed were discovered by ZeroPath. It puts the running total of fixed bugs around 150.", "category": "benefit created", "unexpected": false, "purpose": "AI-powered static analysis of source code to find vulnerabilities and bugs.", "system": "ZeroPath AI code analyzer (with other scanners tested by Rogers)", "model_version": null, "developer": "ZeroPath", "deployer": "Joshua Rogers (independent security researcher); fixes merged by the curl project", "location": null, "domain": "Cybersecurity / open-source software quality", "segment": "Technology", "benefit_type": "Reduced Risk", "taxonomy_note": "Bugfixes rather than confirmed vulnerabilities are read as risk reduced.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "About 50 merged bugfixes from the first list, a potential overflow identified and unused code removed, per the curl maintainer." }, { "group": "societal", "depth": 1, "reason": "curl is widely deployed, but no user-facing incident was averted. The merged fixes are described as mostly small mistakes." } ], "ai_role": { "status": "assessed", "statement": "The maintainer confirms the reports' quality and the merged fixes. He notes he does not know the exact split between tool and human. Rogers attributes ~98% of the fixed curl bugs to ZeroPath. Both the deployer and the confirming maintainer are independent of the vendor." }, "evidence": [ { "kind": "report", "citation": "Daniel Stenberg, daniel.haxx.se, 10 Oct 2025", "title": "A new breed of analyzers", "url": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/", "date": "2025-10-10", "written_by": "beneficiary", "quote": "Out of that initial list, we merged about 50 separately identifiable bugfixes." }, { "kind": "news report", "citation": "Thomas Claburn, The Register, 2 Oct 2025", "title": "Curl project, swamped with AI slop, finds not all AI is bad", "url": "https://www.theregister.com/software/2025/10/02/curl-project-swamped-with-ai-slop-finds-not-all-ai-is-bad/588432", "date": "2025-10-02", "written_by": "independent", "quote": "Stenberg told The Register that about 50 bugfixes based on Rogers' reports have been merged." }, { "kind": "report", "citation": "Joshua Rogers, personal blog (retrospective), 2025", "title": "Retrospective: AI-powered security engineers and source code scanners", "url": "https://joshua.hu/retrospective-zeropath-ai-sast-source-code-security-scanners-vulnerability", "date": null, "written_by": "deployer", "quote": "Approximately 98% of the bugs reported and fixed in the curl codebase were discovered by ZeroPath." } ], "replication": { "produced_by": [ "A large, mature C codebase already covered by conventional analyzers and fuzzing", "An expert researcher filtering scanner output before reporting", "Maintainers willing to work through long candidate lists" ], "must_hold": [ "Human triage to remove false positives", "Maintainer capacity to review hundreds of items" ], "echoes": [ { "date": "2025-09-23", "setting": "Aisle's AI-powered pipeline (Stanislav Fort) reports a confirmed curl vulnerability", "model_version": null, "outcome": "recurred", "source": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/" } ] }, "paired_incident": null, "headline": "curl merges about 50 bugfixes from ZeroPath-assisted scans", "metric": "about 50 separately identifiable bugfixes were merged", "comparator": { "against": "curl's existing compilers, static analyzers and fuzzers (scan-build, clang-tidy, CodeSonar, Coverity, CodeQL, OSS-Fuzz), whose findings were already all fixed", "before": "we always address and fix every warning and complaint they report", "after": "over two hundred new potential problems", "basis": "measured", "quote": "In the curl project we continuously run compilers with maximum pickiness enabled and we throw scan-build, clang-tidy, CodeSonar, Coverity, CodeQL and OSS-Fuzz at it and we always address and fix every warning and complaint they report so it was a little surprising that this tool now suddenly could produce over two hundred new potential problems.", "url": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/" }, "later": { "status": "persisted", "date": "2025-10-19", "note": "Rogers' retrospective of 19 October 2025 put curl's count of fixed ZeroPath-detected bugs at around 150 and expected about 200 within a week.", "quote": "At the moment, the curl project has fixed around 150 of the bugs detected by ZeroPath, but I believe that by the end of next week, it will be around 200.", "url": "https://joshua.hu/retrospective-zeropath-ai-sast-source-code-security-scanners-vulnerability" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/; https://joshua.hu/retrospective-zeropath-ai-sast-source-code-security-scanners-vulnerability", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://zeropath.com/privacy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the deployer's report and the beneficiary's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0237", "catalog_version": "1.0.0", "source_fingerprint": "0ab5f9fe26d8b28b6cc01d061326b1f7281c807d2f8b66f6ae744af8a0a80b2c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0237-source-0001", "AIBD-0237-source-0002", "AIBD-0237-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ZeroPath", "deployer": "Joshua Rogers (independent security researcher); fixes merged by the curl project" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The maintainer confirms the reports' quality and the merged fixes. He notes he does not know the exact split between tool and human. Rogers attributes ~98% of the fixed curl bugs to ZeroPath. Both the deployer and the confirming maintainer are independent of the vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The maintainer confirms the reports' quality and the merged fixes. He notes he does not know the exact split between tool and human. Rogers attributes ~98% of the fixed curl bugs to ZeroPath. Both the deployer and the confirming maintainer are independent of the vendor." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "About 50 merged bugfixes from the first list, a potential overflow identified and unused code removed, per the curl maintainer." }, { "group": "societal", "depth": 1, "reason": "curl is widely deployed, but no user-facing incident was averted. The merged fixes are described as mostly small mistakes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the deployer's report and the beneficiary's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "About 50 merged bugfixes from the first list, a potential overflow identified and unused code removed, per the curl maintainer." }, { "group": "societal", "depth": 1, "reason": "curl is widely deployed, but no user-facing incident was averted. The merged fixes are described as mostly small mistakes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "About 50 merged bugfixes from the first list, a potential overflow identified and unused code removed, per the curl maintainer." }, { "group": "societal", "depth": 1, "reason": "curl is widely deployed, but no user-facing incident was averted. The merged fixes are described as mostly small mistakes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": 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Stenberg writes that a security report received on 16 September accurately identified a possible stack-based buffer overflow in curl's Kerberos FTP code. It was not turned into a CVE only because the code could not be reached. The project then removed krb5-ftp support. The reporter, Joshua Rogers, then forwarded a large list of further potential issues found mostly with ZeroPath, an AI-powered code analyzer. That produced over two hundred possible problems despite curl's existing compilers, static analyzers and fuzzing. From the initial list about 50 separately identifiable bugfixes were merged. Second and third lists of 47 and 158 items followed. Stenberg told The Register that about 50 bugfixes based on Rogers' reports had been merged. Rogers' retrospective states that about 98% of the curl bugs reported and fixed were discovered by ZeroPath. It puts the running total of fixed bugs around 150." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ZeroPath AI code analyzer (with other scanners tested by Rogers)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ZeroPath" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "curl merges about 50 bugfixes from Joshua Rogers' ZeroPath-assisted scans; maintainer calls the reports a new breed of analyzer output", "headline": "curl merges about 50 bugfixes from ZeroPath-assisted scans" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0ab5f9fe26d8b28b6cc01d061326b1f7281c807d2f8b66f6ae744af8a0a80b2c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The reports arrived from mid-September 2025. Stenberg writes that a security report received on 16 September accurately identified a possible stack-based buffer overflow in curl's Kerberos FTP code. It was not turned into a CVE only because the code could not be reached. The project then removed krb5-ftp support. The reporter, Joshua Rogers, then forwarded a large list of further potential issues found mostly with ZeroPath, an AI-powered code analyzer. That produced over two hundred possible problems despite curl's existing compilers, static analyzers and fuzzing. From the initial list about 50 separately identifiable bugfixes were merged. Second and third lists of 47 and 158 items followed. Stenberg told The Register that about 50 bugfixes based on Rogers' reports had been merged. Rogers' retrospective states that about 98% of the curl bugs reported and fixed were discovered by ZeroPath. It puts the running total of fixed bugs around 150.", "replication": { "produced_by": [ "A large, mature C codebase already covered by conventional analyzers and fuzzing", "An expert researcher filtering scanner output before reporting", "Maintainers willing to work through long candidate lists" ], "must_hold": [ "Human triage to remove false positives", "Maintainer capacity to review hundreds of items" ], "echoes": [ { "date": "2025-09-23", "setting": "Aisle's AI-powered pipeline (Stanislav Fort) reports a confirmed curl vulnerability", "outcome": "recurred", "source": "https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyzers/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0088", "title": "NHC blended Google DeepMind's AI ensemble into official Hurricane Melissa forecasts before its Category 5 landfall in Jamaica", "summary": "NHC blended Google DeepMind's AI ensemble into official Melissa forecasts from its first advisory on 21 October 2025; Cat 5 landfall in Jamaica 28 October 2025.", "date_observed": "2025-10-21", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The US National Hurricane Center (NHC) blended Google DeepMind's experimental AI hurricane model (ensemble mean GDMI) into official forecasts for Tropical Storm Melissa. It did so from its first advisory, 21 October 2025. Discussion 1 placed the official track between the DeepMind ensemble mean and the consensus aid HCCA. Discussion 2 described the track as a blend of the DeepMind mean, HCCA and TVCA. Discussion 8 (23 October) moved the track toward a blend of the DeepMind mean and HCCA. Discussion 10 blended the HCCA and GDMI aids. It set an intensity forecast in best agreement with GDMI after all 50 DeepMind members showed a major hurricane. On 28 October 2025 Melissa made landfall in southwestern Jamaica near New Hope with 185 mph winds and 892 mb pressure. IFRC reported 45 deaths and about 1.6 million people affected. It relayed a World Bank/IDB estimate of US$8.8 billion in physical damage. Its CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time.", "category": "protective response", "unexpected": false, "purpose": "Experimental AI tropical cyclone forecast model providing ensemble track and intensity guidance to NHC forecasters.", "system": "Google DeepMind AI hurricane forecast model, ensemble mean designated GDMI in NHC guidance", "model_version": null, "developer": "DeepMind", "deployer": "NOAA National Hurricane Center", "location": "New Hope, Jamaica", "domain": "Weather forecasting / tropical cyclones", "segment": "Public-sector meteorological service", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The AI model's contribution to official forecasts is read as forecast accuracy, with no error figure for this storm.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No cited source attributes an individual-level outcome to the AI guidance. Impacts are reported only at population level." }, { "group": "organizational", "depth": 2, "reason": "NHC's official track and intensity forecasts were materially shaped by GDMI (Discussions 8, 10, 13, 14). NHC's Science Operations Officer called the AI guidance very valuable for Melissa." }, { "group": "societal", "depth": 3, "reason": "Official forecasts for a Category 5 landfall affecting about 1.6 million people. A CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time. The review says its early actions were informed by forecast risks (NHC is not named). Material to many, but no counterfactual that the AI changed outcomes." } ], "ai_role": { "status": "assessed", "statement": "NHC forecasters state in Discussions 8, 10, 12, 13 and 14 that official track and intensity forecasts were blended or aligned with Google DeepMind's ensemble. The official forecast remains a human synthesis of several aids. So the AI contribution to outcomes in Jamaica is not isolated." }, "evidence": [ { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 1, 1100 AM EDT Tue Oct 21 2025, forecasters Cangialosi/Bucci. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 1", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml", "date": "2025-10-21", "written_by": "deployer", "quote": "The NHC official track forecast lies between the Google DeepMind ensemble mean track and the correct consensus aid, HCCA." }, { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 2, 500 PM EDT Tue Oct 21 2025, forecaster Cangialosi. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 2", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.002.shtml", "date": "2025-10-21", "written_by": "deployer", "quote": "This prediction is a little left of the previous forecast and remains a blend of the latest Google DeepMind ensemble mean, the corrected consensus aid HCCA, and simple consensus TVCA." }, { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 8, 500 AM EDT Thu Oct 23 2025, forecaster Cangialosi. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 8", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.008.shtml", "date": "2025-10-23", "written_by": "deployer", "quote": "The NHC track forecast is shifted a little to the right of the previous one, trending toward a blend of the latest Google DeepMind ensemble mean and HCCA solution." }, { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 10, 500 PM EDT Thu Oct 23 2025, forecaster Papin. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 10", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.010.shtml", "date": "2025-10-23", "written_by": "deployer", "quote": "the latest NHC track was only nudged slightly southward from this morning, blending the reliable HCCA and GDMI aids" }, { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 13, 1100 AM EDT Fri Oct 24 2025, forecaster Papin. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 13", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.013.shtml", "date": "2025-10-24", "written_by": "deployer", "quote": "Every single Google DeepMind member shows the system become a Category 4 hurricane or higher" }, { "kind": "report", "citation": "National Hurricane Center (2025). Tropical Storm Melissa Discussion Number 14, 500 PM EDT Fri Oct 24 2025, forecaster Papin. NOAA/NWS.", "title": "Tropical Storm Melissa Discussion Number 14", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.014.shtml", "date": "2025-10-24", "written_by": "deployer", "quote": "The NHC intensity forecast is on the high side of the guidance envelope, and closest too the Google DeepMind ensemble mean (GDMI)." }, { "kind": "report", "citation": "National Hurricane Center (2025). Hurricane Melissa Tropical Cyclone Update, 100 PM EDT Tue Oct 28 2025. NOAA/NWS.", "title": "Hurricane Melissa Tropical Cyclone Update (landfall)", "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.update.10281700.shtml", "date": "2025-10-28", "written_by": "deployer", "quote": "CATEGORY 5 MELISSA MAKES LANDFALL IN JAMAICA...ONE OF THE MOST POWERFUL HURRICANE LANDFALLS ON RECORD IN THE ATLANTIC BASIN" }, { "kind": "press release", "citation": "National Weather Service (n.d.). AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC Science Operation Officer Wallace Hogsett. NOAA/NWS News Around NOAA.", "title": "AI in Hurricane Forecasting at the National Hurricane Center", "url": "https://www.weather.gov/news/261102-AI-Hurricane-Forecasting", "date": null, "written_by": "deployer", "quote": "The AI models honed in very early on the likely track and intensity and provided very valuable guidance to complement our traditional NWP guidance." }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "the NHC track errors are notably lower than average for major hurricanes, including Humberto and Melissa in 2025" }, { "kind": "report", "citation": "Kelly, Larry A., José Álamo, and Aidan D. Mahoney. Hurricane Melissa (AL132025), 21–31 October 2025. National Hurricane Center Tropical Cyclone Report. Revised May 19, 2026, originally February 25, 2026. 16–17, Tables 5b and 6b.", "title": "Hurricane Melissa (AL132025): Tropical Cyclone Report", "url": "https://www.nhc.noaa.gov/data/tcr/AL132025_Melissa.pdf", "date": "2026-02-25", "written_by": "deployer", "quote": "The NHC OFCL forecasts were comparable to GDMI through 96 h, but performed slightly better than GDMI at 120 h." } ], "replication": { "produced_by": [ "Experimental Google DeepMind ensemble guidance available in real time to NHC forecasters", "Forecasters choosing to blend GDMI with consensus aids (HCCA) in official track and intensity forecasts", "A slow-moving, rapidly intensifying hurricane where models disagreed on track relative to Jamaica" ], "must_hold": [ "AI ensemble output delivered on time and verified before operational use, as NHC describes", "Human forecasters retain the final official forecast and integrate conventional NWP guidance", "Forecast accuracy can be assessed against the observed track and intensity. NHC’s Tropical Cyclone Report, revised 19 May 2026, provides that comparison for Melissa" ], "echoes": [ { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 Atlantic season track forecasts", "model_version": null, "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" }, { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 eastern North Pacific track forecasts (GDMI beat official and consensus aids at 48–120 h)", "model_version": null, "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "severity": null, "group": "societal", "basis": "Google-built hazard early-warning system underestimated the Kahramanmaras earthquake and failed to warn millions; same developer family and public-warning task as DeepMind's Melissa forecasts." }, "headline": "NHC blends DeepMind's ensemble into Hurricane Melissa forecasts", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-03-30", "note": "NHC's 2025 verification report, five months after landfall, records low official track errors for Melissa and the DeepMind ensemble mean outperforming the official Atlantic track forecast at 12 to 72 hours.", "quote": "It has been seen in multiple cases during the past few years that the NHC track errors are notably lower than average for major hurricanes, including Humberto and Melissa in 2025.", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Set the date observed to 21 October 2025 and reworded the summary and account because Discussions 1 and 2 show the Google DeepMind ensemble mean shaping the official track from the first advisory, added those two discussions as evidence, corrected the Discussion 14 title to “Tropical Storm Melissa” as its header reads, attributed the US$8.8 billion damage figure to the World Bank/IDB estimate relayed by IFRC, and tied the DREF's early actions to “forecast risks” as the review says rather than to NHC.", "source": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml; https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.002.shtml; https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.014.shtml; https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-dref-no-mdrjm005-operation-update-3; https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-imminent-dref-mdrjm005-dref-operational-review-report-april-may-2026", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://www.nhc.noaa.gov/aboutintro.shtml", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Moved two IFRC reports to background source notes because they describe storm impacts and humanitarian action, without establishing the AI forecast’s contribution to those outcomes. Preserved their citations, excerpts, and the existing account and depths. Retained NHC evidence of forecast use and verification, attributed to the deployer rather than an independent AI-benefit evaluator.", "source": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml; https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added NHC’s revised Hurricane Melissa report, replaced the obsolete statement that it was unpublished, and separated forecast verification from humanitarian background.", "source": "https://www.nhc.noaa.gov/data/tcr/AL132025_Melissa.pdf", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: nine reports from the deployer and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0088", "catalog_version": "1.0.0", "source_fingerprint": "7494545dd8aeba975dc7387c52bc23ab138bc6a416517d50ebb709bf803d7efa", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0088-source-0001", "AIBD-0088-source-0002", "AIBD-0088-source-0003", "AIBD-0088-source-0004", "AIBD-0088-source-0005", "AIBD-0088-source-0006", "AIBD-0088-source-0007", "AIBD-0088-source-0008", "AIBD-0088-source-0009", "AIBD-0088-source-0010" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "NHC-Melissa-AL132025-forecast-verification" ], "role": "Forecast verification for Hurricane Melissa" }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "record_ids": [ "NHC-Melissa-AL132025-forecast-verification" ] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeepMind", "deployer": "NOAA National Hurricane Center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "NHC forecasters state in Discussions 8, 10, 12, 13 and 14 that official track and intensity forecasts were blended or aligned with Google DeepMind's ensemble. The official forecast remains a human synthesis of several aids. So the AI contribution to outcomes in Jamaica is not isolated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "NHC forecasters state in Discussions 8, 10, 12, 13 and 14 that official track and intensity forecasts were blended or aligned with Google DeepMind's ensemble. The official forecast remains a human synthesis of several aids. 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No study isolates the AI’s effect on protective actions or losses." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No cited source attributes an individual-level outcome to the AI guidance. Impacts are reported only at population level." }, { "group": "organizational", "depth": 2, "reason": "NHC's official track and intensity forecasts were materially shaped by GDMI (Discussions 8, 10, 13, 14). NHC's Science Operations Officer called the AI guidance very valuable for Melissa." }, { "group": "societal", "depth": 3, "reason": "Official forecasts for a Category 5 landfall affecting about 1.6 million people. A CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time. The review says its early actions were informed by forecast risks (NHC is not named). Material to many, but no counterfactual that the AI changed outcomes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Google-built hazard early-warning system underestimated the Kahramanmaras earthquake and failed to warn millions; same developer family and public-warning task as DeepMind's Melissa forecasts.", "links": [ { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "group": "societal", "basis": "Google-built hazard early-warning system underestimated the Kahramanmaras earthquake and failed to warn millions; same developer family and public-warning task as DeepMind's Melissa forecasts.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "value_present", "value": { "kind": "text", "text": "NHC credits GDMI and regional models jointly with increasing forecasters’ confidence at unusually long lead times. It does not isolate GDMI’s effect on the official forecast." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "NHC credits GDMI and regional models jointly with increasing forecasters’ confidence at unusually long lead times. It does not isolate GDMI’s effect on the official forecast." } }, "evaluations[].comparator": { "state": "value_present", "value": { "kind": "text", "text": "NHC’s official forecasts, conventional model guidance, and climatology-persistence forecasts for the same storm." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "NHC’s official forecasts, conventional model guidance, and climatology-persistence forecasts for the same storm." } }, "evaluations[].design": { "state": "value_present", "value": { "kind": "text", "text": "Retrospective verification of operational forecasts against the storm’s observed track and intensity." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Retrospective verification of operational forecasts against the storm’s observed track and intensity." } }, "evaluations[].effect": { "state": "value_present", "value": { "kind": "text", "text": "GDMI’s track forecasts were comparable to NHC’s official forecasts through 96 hours. NHC performed slightly better at 120 hours and had lower intensity errors than every guidance model through 96 hours." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "GDMI’s track forecasts were comparable to NHC’s official forecasts through 96 hours. NHC performed slightly better at 120 hours and had lower intensity errors than every guidance model through 96 hours." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "NHC-Melissa-AL132025-forecast-verification" ], "role": "Forecast verification for Hurricane Melissa" }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "NHC’s forecast verification for Hurricane Melissa (AL132025)." } }, "evaluations[].measurement_method": { "state": "value_present", "value": { "kind": "text", "text": "NHC compared forecasts at matching lead times with its final estimates of the storm’s position and intensity. It compared official forecasts with model guidance on a common sample." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "NHC compared forecasts at matching lead times with its final estimates of the storm’s position and intensity. It compared official forecasts with model guidance on a common sample." } }, "evaluations[].metric": { "state": "value_present", "value": { "kind": "text", "text": "Track forecast error, intensity forecast error, and forecast lead time." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Track forecast error, intensity forecast error, and forecast lead time." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "text", "text": "Hurricane Melissa in the Atlantic, 21–31 October 2025. The report compares forecasts at lead times through 120 hours." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Hurricane Melissa in the Atlantic, 21–31 October 2025. The report compares forecasts at lead times through 120 hours." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "The sources establish that forecasters used the guidance. They do not establish that it changed protective actions, reduced losses, or prevented deaths." }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The sources establish that forecasters used the guidance. They do not establish that it changed protective actions, reduced losses, or prevented deaths." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "1546", "title": "Google Android Earthquake Alerts System Reportedly Underestimated Kahramanmaraş Earthquake and Failed to Send Urgent Warnings to Millions", "url": "https://incidentdatabase.ai/cite/1546", "group": "societal", "basis": "Google-built hazard early-warning system underestimated the Kahramanmaras earthquake and failed to warn millions; same developer family and public-warning task as DeepMind's Melissa forecasts." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-03-30", "note": "NHC's 2025 verification report, five months after landfall, records low official track errors for Melissa and the DeepMind ensemble mean outperforming the official Atlantic track forecast at 12 to 72 hours.", "quote": "It has been seen in multiple cases during the past few years that the NHC track errors are notably lower than average for major hurricanes, including Humberto and Melissa in 2025.", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "NHC published its Tropical Cyclone Report on 25 February 2026 and revised it on 19 May. The report evaluates the forecasts against the storm’s observed track and intensity." } }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0088" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "National Hurricane Center forecasters. People in Melissa’s path were the intended beneficiaries of the forecasts." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "National Hurricane Center forecasters. People in Melissa’s path were the intended beneficiaries of the forecasts." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "display": { "answer": "No count of people who benefited from the AI guidance is established." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Task Accuracy", "taxonomy_note": "The AI model's contribution to official forecasts is read as forecast accuracy, with no error figure for this storm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The US National Hurricane Center (NHC) blended Google DeepMind's experimental AI hurricane model (ensemble mean GDMI) into official forecasts for Tropical Storm Melissa. It did so from its first advisory, 21 October 2025. Discussion 1 placed the official track between the DeepMind ensemble mean and the consensus aid HCCA. Discussion 2 described the track as a blend of the DeepMind mean, HCCA and TVCA. Discussion 8 (23 October) moved the track toward a blend of the DeepMind mean and HCCA. Discussion 10 blended the HCCA and GDMI aids. It set an intensity forecast in best agreement with GDMI after all 50 DeepMind members showed a major hurricane. On 28 October 2025 Melissa made landfall in southwestern Jamaica near New Hope with 185 mph winds and 892 mb pressure. IFRC reported 45 deaths and about 1.6 million people affected. It relayed a World Bank/IDB estimate of US$8.8 billion in physical damage. Its CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "National Hurricane Center forecasters used Google DeepMind’s guidance in their official forecasts for Hurricane Melissa." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No cited source attributes an individual-level outcome to the AI guidance. Impacts are reported only at population level." }, { "group": "organizational", "depth": 2, "reason": "NHC's official track and intensity forecasts were materially shaped by GDMI (Discussions 8, 10, 13, 14). NHC's Science Operations Officer called the AI guidance very valuable for Melissa." }, { "group": "societal", "depth": 3, "reason": "Official forecasts for a Category 5 landfall affecting about 1.6 million people. A CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time. The review says its early actions were informed by forecast risks (NHC is not named). Material to many, but no counterfactual that the AI changed outcomes." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Experimental AI tropical cyclone forecast model providing ensemble track and intensity guidance to NHC forecasters." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "New Hope, Jamaica", "developer_country": "United Kingdom", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Experimental AI tropical cyclone forecast model providing ensemble track and intensity guidance to NHC forecasters." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-10-21", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 1546 (medium confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/1546", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Set the date observed to 21 October 2025 and reworded the summary and account because Discussions 1 and 2 show the Google DeepMind ensemble mean shaping the official track from the first advisory, added those two discussions as evidence, corrected the Discussion 14 title to “Tropical Storm Melissa” as its header reads, attributed the US$8.8 billion damage figure to the World Bank/IDB estimate relayed by IFRC, and tied the DREF's early actions to “forecast risks” as the review says rather than to NHC.", "source": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml; https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.002.shtml; https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.014.shtml; https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-dref-no-mdrjm005-operation-update-3; https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-imminent-dref-mdrjm005-dref-operational-review-report-april-may-2026", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google_DeepMind; https://www.nhc.noaa.gov/aboutintro.shtml", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to DeepMind.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Moved two IFRC reports to background source notes because they describe storm impacts and humanitarian action, without establishing the AI forecast’s contribution to those outcomes. Preserved their citations, excerpts, and the existing account and depths. Retained NHC evidence of forecast use and verification, attributed to the deployer rather than an independent AI-benefit evaluator.", "source": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml; https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added NHC’s revised Hurricane Melissa report, replaced the obsolete statement that it was unpublished, and separated forecast verification from humanitarian background.", "source": "https://www.nhc.noaa.gov/data/tcr/AL132025_Melissa.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Moved two IFRC reports to background source notes because they describe storm impacts and humanitarian action, without establishing the AI forecast’s contribution to those outcomes. Preserved their citations, excerpts, and the existing account and depths. 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NHC’s Tropical Cyclone Report, revised 19 May 2026, provides that comparison for Melissa" ], "echoes": [ { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 Atlantic season track forecasts", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" }, { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 eastern North Pacific track forecasts (GDMI beat official and consensus aids at 48–120 h)", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Experimental Google DeepMind ensemble guidance available in real time to NHC forecasters", "Forecasters choosing to blend GDMI with consensus aids (HCCA) in official track and intensity forecasts", "A slow-moving, rapidly intensifying hurricane where models disagreed on track relative to Jamaica" ], "must_hold": [ "AI ensemble output delivered on time and verified before operational use, as NHC describes", "Human forecasters retain the final official forecast and integrate conventional NWP guidance", "Forecast accuracy can be assessed against the observed track and intensity. 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It does not isolate downstream public benefits." }, { "source_refs": [ "AIBD-0088-source-0005" ], "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.013.shtml", "title": "Tropical Storm Melissa Discussion Number 13", "relationship": "Original operational advisory recording the ensemble’s Category 4-or-higher signal." }, { "source_refs": [ "AIBD-0088-source-0006" ], "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.014.shtml", "title": "Tropical Storm Melissa Discussion Number 14", "relationship": "Original operational advisory recording the intensity forecast’s agreement with GDMI." }, { "source_refs": [ "AIBD-0088-source-0007" ], "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.update.10281700.shtml", "title": "Hurricane Melissa Tropical Cyclone Update (landfall)", "relationship": "Original landfall update establishing storm context, not the AI system’s effect on public outcomes." }, { "source_refs": [ "AIBD-0088-source-0008" ], "url": "https://www.weather.gov/news/261102-AI-Hurricane-Forecasting", "title": "AI in Hurricane Forecasting at the National Hurricane Center", "relationship": "Original interview with NHC’s Science Operations Officer. NHC deployed the model and partnered in its development; this is not an independent evaluation." }, { "source_refs": [ "AIBD-0088-source-0009" ], "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "title": "NHC Forecast Verification Report, 2025 Hurricane Season", "relationship": "Original seasonal verification by NHC and a cooperating researcher. It evaluates forecasting performance, but it is not an independent evaluation of AI-attributable humanitarian outcomes." }, { "url": "https://www.nhc.noaa.gov/data/tcr/AL132025_Melissa.pdf", "title": "Hurricane Melissa (AL132025): Tropical Cyclone Report", "relationship": "Original retrospective verification by the agency that used the guidance. The report compares track and intensity forecasts for Melissa and explains how GDMI and regional models contributed to forecasters’ confidence. It does not isolate the AI model’s effect on humanitarian outcomes.", "locator": "Printed pp. 16–17, Track Forecast and Intensity Forecast, Tables 5b and 6b.", "original_publication_date": "2026-02-25", "version_reviewed_date": "2026-05-19", "version_note": "The May 19 title-page note says that this version revised fatality totals and damage estimates based on updated government information. Preserve February 25 as the original report date and May 19 as the reviewed revision.", "access": "Full original PDF downloaded successfully (HTTP 200) and relevant text read on October 25, 2026. HTTP Last-Modified: May 19, 2026.", "source_refs": [ "AIBD-0088-source-0010" ] } ], "related_material": [ { "url": "https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-imminent-dref-mdrjm005-dref-operational-review-report-april-may-2026", "title": "Jamaica - Hurricane Melissa Imminent DREF (MDRJM005) Operational Review Report", "published_on": "2026-08-07", "relationship": "Humanitarian and storm context preserved from the existing case. It does not establish an AI-attributable outcome and is not counted as independent AI-benefit evaluation.", "preserved_evidence": { "kind": "report", "citation": "IFRC (2026). Jamaica - Hurricane Melissa Imminent DREF (MDRJM005), DREF Operational Review Report, April - May 2026. ReliefWeb, 7 August 2026.", "title": "Jamaica - Hurricane Melissa Imminent DREF (MDRJM005) Operational Review Report", "url": "https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-imminent-dref-mdrjm005-dref-operational-review-report-april-may-2026", "date": "2026-08-07", "written_by": "independent", "quote": "Rapid approval and pre-landfall mobilisation, enabled by prior training, pre-positioned stock, and strong logistics systems, allowed JRC to respond quickly." }, "access": "The original ReliefWeb URL returned HTTP 403 during this narrow review. Existing citations and quotations are preserved; no new full-text verification is claimed." }, { "url": "https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-dref-no-mdrjm005-operation-update-3", "title": "Jamaica | Hurricane Melissa DREF MDRJM005 Operation update #3", "published_on": "2026-07-07", "relationship": "Humanitarian and storm context preserved from the existing case. It does not establish an AI-attributable outcome and is not counted as independent AI-benefit evaluation.", "preserved_evidence": { "kind": "report", "citation": "IFRC (2026). Jamaica | Hurricane Melissa DREF No. MDRJM005 Operation update #3. ReliefWeb, 7 July 2026.", "title": "Jamaica | Hurricane Melissa DREF MDRJM005 Operation update #3", "url": "https://reliefweb.int/report/jamaica/jamaica-hurricane-melissa-dref-no-mdrjm005-operation-update-3", "date": "2026-07-07", "written_by": "independent", "quote": "winds of nearly 300 km (185 miles) per hour" }, "access": "The original ReliefWeb URL returned HTTP 403 during this narrow review. Existing citations and quotations are preserved; no new full-text verification is claimed." }, { "url": "https://go-api.ifrc.org/api/downloadfile/93656/MDRJM005OS", "title": "Jamaica | Hurricane Melissa: Emergency Appeal Operational Strategy (MDRJM005)", "date": "2025-11-11", "locator": "p. 2, timeline; p. 3, situation overview; p. 10, targeting", "finding": "The timeline records the CHF80,000 allocation on October 23, 2025. The targeting section attributes the estimated 1.6 million people affected to analysis of UNOSAT wind forecasts and demographic data.", "relationship": "Original IFRC background on anticipatory aid and exposure. This report does not attribute those actions or the affected-population estimate to Google DeepMind.", "access": "Full original PDF downloaded successfully (HTTP 200) and relevant sections read on October 25, 2026. The IFRC emergency page dates this operational strategy November 11, 2025.", "recommendation": "Keep as related background rather than independent evidence of AI-created benefit. Preserve existing IFRC related material and its separate access status." } ], "claim_lineage": [ { "claim": "The first official Melissa forecast used DeepMind ensemble guidance.", "source_ref": "AIBD-0088-source-0001", "locator": "Track discussion, paragraph beginning “The system was moving”", "access": "Original advisory text read." }, { "claim": "GDMI performed well in NHC’s 2025 verification.", "source_ref": "AIBD-0088-source-0009", "locator": "Abstract and Atlantic track-verification discussion", "access": "Full original PDF inspected on 25 October 2026.", "limitation": "Seasonal model accuracy is not a measure of AI-attributable lives saved or of the AI contribution to each humanitarian action." } ], "access_audit": [ { "url": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.001.shtml", "access": "Original advisory text read through the indexed official page after the direct request returned HTTP 403." }, { "url": "https://www.weather.gov/news/261102-AI-Hurricane-Forecasting", "access": "Full original page read on October 25, 2026. Q&A 7 discusses Melissa, and Q&A 2 describes NHC’s development partnership with DeepMind.", "access_history": [ { "access": "Original NHC interview text read; it identifies NHC’s development partnership with Google DeepMind.", "reviewed_on": "2026-10-24" } ], "reviewed_on": "2026-10-25" }, { "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "access": "Full original PDF downloaded successfully (HTTP 200) on October 25, 2026. Title page dated March 30, 2026. Printed p. 7 links to the NHC interview, and the report provides seasonal forecast comparisons.", "access_history": [ { "access": "Indexed original report abstract and relevant text read; direct PDF request returned HTTP 403.", "reviewed_on": "2026-10-24" } ], "reviewed_on": "2026-10-25" } ], "limitations": [ "NHC is the operator and a development partner, so its verification is primary but not an independent evaluation of its own use of AI.", "Track and intensity comparisons do not measure lives saved, damage avoided, or whether IFRC acted earlier because of GDMI.", "The seasonal comparison must not be substituted for a Melissa-only result." ], "ordering_basis": "Keep the contemporaneous NHC account of AI use first, followed by retained operational documentation and later verification. Humanitarian background remains available in the source notes.", "lead_source_ref": "AIBD-0088-source-0001", "retained_source_order": [ "AIBD-0088-source-0001", "AIBD-0088-source-0002", "AIBD-0088-source-0003", "AIBD-0088-source-0004", "AIBD-0088-source-0005", "AIBD-0088-source-0006", "AIBD-0088-source-0007", "AIBD-0088-source-0008", "AIBD-0088-source-0009", "AIBD-0088-source-0010" ], "scope": "Operational use and retrospective verification of forecasts, with humanitarian material retained separately as background.", "reviewed_on": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Read the original NHC Melissa report, revised 19 May 2026, pp. 16–17 and Tables 5b/6b, together with the original NHC interview and seasonal verification report.", "record_fields": [], "source_refs": [ "AIBD-0088-source-0010", "AIBD-0088-source-0008", "AIBD-0088-source-0009" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "NHC’s operational advisories document its use of DeepMind guidance. Its later verification reports assess forecast accuracy. IFRC reports provide humanitarian context without isolating AI’s effects." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "NHC blended Google DeepMind's AI ensemble into official Melissa forecasts from its first advisory on 21 October 2025; Cat 5 landfall in Jamaica 28 October 2025.", "account": "The US National Hurricane Center (NHC) blended Google DeepMind's experimental AI hurricane model (ensemble mean GDMI) into official forecasts for Tropical Storm Melissa. It did so from its first advisory, 21 October 2025. Discussion 1 placed the official track between the DeepMind ensemble mean and the consensus aid HCCA. Discussion 2 described the track as a blend of the DeepMind mean, HCCA and TVCA. Discussion 8 (23 October) moved the track toward a blend of the DeepMind mean and HCCA. Discussion 10 blended the HCCA and GDMI aids. It set an intensity forecast in best agreement with GDMI after all 50 DeepMind members showed a major hurricane. On 28 October 2025 Melissa made landfall in southwestern Jamaica near New Hope with 185 mph winds and 892 mb pressure. IFRC reported 45 deaths and about 1.6 million people affected. It relayed a World Bank/IDB estimate of US$8.8 billion in physical damage. Its CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Google DeepMind AI hurricane forecast model, ensemble mean designated GDMI in NHC guidance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "NHC blended Google DeepMind's AI ensemble into official Hurricane Melissa forecasts before its Category 5 landfall in Jamaica", "headline": "NHC blends DeepMind's ensemble into Hurricane Melissa forecasts" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7494545dd8aeba975dc7387c52bc23ab138bc6a416517d50ebb709bf803d7efa" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the content fingerprint after the source-attribution correction.", "record_fields": [ "evidence", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The US National Hurricane Center (NHC) blended Google DeepMind's experimental AI hurricane model (ensemble mean GDMI) into official forecasts for Tropical Storm Melissa. It did so from its first advisory, 21 October 2025. Discussion 1 placed the official track between the DeepMind ensemble mean and the consensus aid HCCA. Discussion 2 described the track as a blend of the DeepMind mean, HCCA and TVCA. Discussion 8 (23 October) moved the track toward a blend of the DeepMind mean and HCCA. Discussion 10 blended the HCCA and GDMI aids. It set an intensity forecast in best agreement with GDMI after all 50 DeepMind members showed a major hurricane. On 28 October 2025 Melissa made landfall in southwestern Jamaica near New Hope with 185 mph winds and 892 mb pressure. IFRC reported 45 deaths and about 1.6 million people affected. It relayed a World Bank/IDB estimate of US$8.8 billion in physical damage. Its CHF 80,000 Imminent DREF was approved on 23 October with a five-day lead time.", "replication": { "produced_by": [ "Experimental Google DeepMind ensemble guidance available in real time to NHC forecasters", "Forecasters choosing to blend GDMI with consensus aids (HCCA) in official track and intensity forecasts", "A slow-moving, rapidly intensifying hurricane where models disagreed on track relative to Jamaica" ], "must_hold": [ "AI ensemble output delivered on time and verified before operational use, as NHC describes", "Human forecasters retain the final official forecast and integrate conventional NWP guidance", "Forecast accuracy can be assessed against the observed track and intensity. NHC’s Tropical Cyclone Report, revised 19 May 2026, provides that comparison for Melissa" ], "echoes": [ { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 Atlantic season track forecasts", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" }, { "date": "2026-03-30", "setting": "NHC homogeneous verification, 2025 eastern North Pacific track forecasts (GDMI beat official and consensus aids at 48–120 h)", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Forecasters received the experimental DeepMind ensemble in real time and combined it with conventional forecasts. They retained responsibility for the official track and intensity forecasts." } } }, "summary": { "total": 91, "addressed": 91, "known": 43, "reviewed": 11, "record_mapped": 32, "not_assessed": 48, "complete": false, "by_state": { "value_present": 43, "not_reported": 0, "unresolved": 0, "not_assessed": 48, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0184", "title": "DWP's Universal Credit advances machine-learning model saved an estimated £4.4 million from 2022–23 to 2024–25", "summary": "The National Audit Office reports that DWP's model, in use since May 2022, flags high-risk advance requests for caseworker review, with estimated savings of £4.4 million and about three times the h...", "date_observed": "2025-10-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The National Audit Office (NAO) published “Tackling benefit overpayments due to fraud and error” on 22 October 2025. It states that since May 2022 the Department for Work & Pensions (DWP) has used a machine learning model. The model flags potentially fraudulent claims for Universal Credit advances. DWP estimates it saved £4.4 million from 2022–23 to 2024–25. The model scores new claims and refers those above a threshold to a caseworker. Decisions are made by DWP staff. DWP cannot disaggregate the model's costs from wider spending on data analytics. The NAO reports DWP's finding that the model is around three times more effective at identifying fraud risk than a randomized control group sample. It reports a median payment delay of one day for referred requests. DWP's July 2025 fairness analysis for 2024–25 showed older claimants (age groups 45 to 54 and above) and non-UK nationals over-referred for review. Fairness analysis was possible on only one of nine protected characteristics. Four further models were in development. Civil Service World (Jim Dunton, 22 October 2025) reported the NAO's warnings on data infrastructure. It quoted Transformation Minister Andrew Western saying that the one machine learning model has made the department significantly more effective.", "category": "general benefit", "unexpected": false, "purpose": "Assess the fraud risk of Universal Credit advance requests and refer high-risk requests to a caseworker for review.", "system": "Universal Credit advances machine learning model", "model_version": null, "developer": "Department for Work & Pensions (DWP)", "deployer": "Department for Work & Pensions (DWP)", "location": null, "domain": "Benefit fraud and error", "segment": "Universal Credit advances", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The saving is an aggregate departmental estimate over three years, not an attributable outcome." }, { "group": "societal", "depth": null, "reason": "No outcome for claimants or taxpayers beyond the aggregate estimate is documented. Referred claimants bear an added evidence burden." } ], "ai_role": { "status": "assessed", "statement": "The NAO describes a model trained on historical fraud and error data that scores advance requests and refers those above a threshold. Every payment decision is made by a caseworker, so the model's contribution is prioritization. Developer and deployer are the same public body (DWP). The NAO, an independent auditor, wrote the report." }, "evidence": [ { "kind": "report", "citation": "National Audit Office, 'Tackling benefit overpayments due to fraud and error', 22 October 2025, paragraphs 15-16 and 3.4-3.15", "title": "Tackling benefit overpayments due to fraud and error", "url": "https://www.nao.org.uk/reports/tackling-benefit-overpayments-due-to-fraud-and-error/", "date": "2025-10-22", "written_by": "independent", "quote": "Since May 2022, DWP has used a machine learning model to flag potentially fraudulent claims for UC advances, saving an estimated £4.4 million." }, { "kind": "news report", "citation": "Jim Dunton, Civil Service World, 22 October 2025", "title": "Digital and data challenges could hamper DWP's fraud strategy, NAO warns", "url": "https://www.civilserviceworld.com/news/article/digital-and-data-challenges-could-hamper-dwps-fraud-strategy-nao-warns", "date": "2025-10-22", "written_by": "independent", "quote": "our one machine learning model has made us significantly more effective" }, { "kind": "report", "citation": "Department for Work & Pensions (2026). Effectiveness Assessment of Universal Credit Advances Model, 1 April 2025 to 31 March 2026. GOV.UK, 9 July 2026.", "title": "Effectiveness Assessment of Universal Credit Advances Model", "url": "https://www.gov.uk/government/publications/effectiveness-assessment-including-statistical-analysis-of-the-universal-credit-advances-machine-learning-model-1-april-2025-to-31-march-2026/effectiveness-assessment-of-universal-credit-advances-model", "date": "2026-07-09", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "A model trained on historical fraud and error data in advance claims. Referrals above a threshold are reviewed by caseworkers alongside control-group referrals with scores removed" ], "must_hold": [ "A human decision on every advance", "Regular fairness assessments (age is the only protected characteristic in the model)", "Feedback of review outcomes into the model" ], "echoes": [ { "date": null, "setting": "DWP fairness assessment of the model for 1 April 2024 to 31 March 2025 (2025–07)", "model_version": null, "outcome": "recurred", "source": "NAO: around three times more effective than a random control sample; over-referral of older and non-UK claimants" }, { "date": null, "setting": "Four further DWP machine learning models in development (2025–26)", "model_version": null, "outcome": "unknown", "source": "NAO: deployment decisions expected in 2025-26" } ] }, "paired_incident": null, "headline": "Universal Credit advances model saves an estimated £4.4 million", "metric": "saving an estimated £4.4 million from 2022–23 to 2024–25 by DWP's estimate", "comparator": { "against": "a randomised control group sample of advance requests", "before": "fraud-risk identification rate of the random control sample (not quantified)", "after": "around three times more effective at identifying fraud risk", "basis": "measured", "quote": "In terms of performance, DWP found the model to be around three times more effective at identifying fraud risk than a randomised control group sample.", "url": "https://www.nao.org.uk/wp-content/uploads/2025/10/Tackling-benefit-overpayments-due-to-fraud-and-error.pdf" }, "later": { "status": "persisted", "date": "2026-07-09", "note": "DWP's effectiveness assessment for April 2025 to March 2026 found the retrained model 2.5 times more effective than a random control group and concluded it should keep operating.", "quote": "the model is 2.5 times more effective at identifying high-risk advances than a random control group, increasing the precision of referrals and enabling human decision-makers to focus on the riskiest cases", "url": "https://www.gov.uk/government/publications/effectiveness-assessment-including-statistical-analysis-of-the-universal-credit-advances-machine-learning-model-1-april-2025-to-31-march-2026/effectiveness-assessment-of-universal-credit-advances-model" }, "value": { "amount": "£4.4 million", "what": "advances that would otherwise have been overpaid, saved from 2022-23 to 2024-25", "who": "Department for Work & Pensions", "estimate": true, "quote": "DWP estimates that, from 2022-23 to 2024-25, the model generated savings of £4.4 million that would otherwise have been overpaid.", "url": "https://www.nao.org.uk/wp-content/uploads/2025/10/Tackling-benefit-overpayments-due-to-fraud-and-error.pdf" }, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://www.nao.org.uk/wp-content/uploads/2025/10/Tackling-benefit-overpayments-due-to-fraud-and-error.pdf; https://www.gov.uk/government/publications/effectiveness-assessment-including-statistical-analysis-of-the-universal-credit-advances-machine-learning-model-1-april-2025-to-31-march-2026/effectiveness-assessment-of-universal-credit-advances-model; https://www.nao.org.uk/wp-content/uploads/2025/10/Tackling-benefit-overpayments-due-to-fraud-and-error.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Department_for_Work_and_Pensions; https://en.wikipedia.org/wiki/Department_for_Work_and_Pensions", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent report, one independent news report and the deployer's report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0184", "catalog_version": "1.0.0", "source_fingerprint": "537199b2c3da80a94f17562f462dc8ae10d28abb15116260b2664d1adffa355e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0184-source-0001", "AIBD-0184-source-0002", "AIBD-0184-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0184-legacy-value", "DIV-0031" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. Eligible statements can supply unanswered monetary questions without a new source review or a finding of net benefit.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0184-legacy-value", "DIV-0031" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Department for Work & Pensions (DWP)", "deployer": "Department for Work & Pensions (DWP)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The NAO describes a model trained on historical fraud and error data that scores advance requests and refers those above a threshold. 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It states that since May 2022 the Department for Work & Pensions (DWP) has used a machine learning model. The model flags potentially fraudulent claims for Universal Credit advances. DWP estimates it saved £4.4 million from 2022–23 to 2024–25. The model scores new claims and refers those above a threshold to a caseworker. Decisions are made by DWP staff. DWP cannot disaggregate the model's costs from wider spending on data analytics. The NAO reports DWP's finding that the model is around three times more effective at identifying fraud risk than a randomized control group sample. It reports a median payment delay of one day for referred requests. DWP's July 2025 fairness analysis for 2024–25 showed older claimants (age groups 45 to 54 and above) and non-UK nationals over-referred for review. Fairness analysis was possible on only one of nine protected characteristics. Four further models were in development. Civil Service World (Jim Dunton, 22 October 2025) reported the NAO's warnings on data infrastructure. It quoted Transformation Minister Andrew Western saying that the one machine learning model has made the department significantly more effective.", "replication": { "produced_by": [ "A model trained on historical fraud and error data in advance claims. Referrals above a threshold are reviewed by caseworkers alongside control-group referrals with scores removed" ], "must_hold": [ "A human decision on every advance", "Regular fairness assessments (age is the only protected characteristic in the model)", "Feedback of review outcomes into the model" ], "echoes": [ { "setting": "DWP fairness assessment of the model for 1 April 2024 to 31 March 2025 (2025–07)", "outcome": "recurred", "source": "NAO: around three times more effective than a random control sample; over-referral of older and non-UK claimants" }, { "setting": "Four further DWP machine learning models in development (2025–26)", "outcome": "unknown", "source": "NAO: deployment decisions expected in 2025-26" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0163", "title": "Open Climate Fix's Quartz Solar goes live in NESO's control room and may avoid £30m a year in imbalance costs", "summary": "Open Climate Fix's machine-learning solar forecast is live in NESO's control room; OCF claims at least £30m a year in avoided imbalance costs, a figure NESO's quoted statement does not give.", "date_observed": "2025-11-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 6 November 2025 Open Climate Fix (OCF), a not-for-profit, announced that Quartz Solar was live in the National Energy System Operator's (NESO) control room. OCF's AI-powered solar PV forecasting tool combines machine learning, live satellite imagery and weather data. It is fully integrated from day-ahead scheduling to real-time control after starting as a Network Innovation Allowance project (The Energyst, 6 November 2025). The announcement says the tool helps avoid at least £30 million in imbalance costs a year and cuts around 300,000 tonnes of CO2. NESO's Carolina Tortora, Head of AI, Digitalisation and Innovation, is quoted saying it can accurately predict solar generation up to 36 hours in advance. She says it is revolutionizing solar forecasts in the control room. She does not state the £30m figure. pv magazine (7 November 2025) attributes the £30 million (US$39 million) per year saving to Quartz Solar itself. It reports OCF's claim of halving forecasting errors across about 300 grid supply points. OCF's website says the forecast is used daily by NESO. The savings are the maker's estimate, not an operator-reported or audited figure.", "category": "general benefit", "unexpected": false, "purpose": "Quartz Solar is built to forecast national and regional solar PV output for grid balancing. Operational use for reserve setting is the intended purpose.", "system": "Quartz Solar (Open Climate Fix machine-learning solar PV forecast, formerly PVNet)", "model_version": "PVNet", "developer": "Open Climate Fix", "deployer": "National Energy System Operator (NESO)", "location": "United Kingdom", "domain": "Energy", "segment": "Electricity system operation and balancing", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "NESO confirms operational use and 36-hour forecasting. The £30m saving is OCF's estimate, so no measured outcome is documented." }, { "group": "societal", "depth": null, "reason": "The 300,000-tonne CO2 figure is the maker's estimate. No independent measurement is documented." } ], "ai_role": { "status": "unassessed", "statement": "The machine-learning forecast is the system in use. But both figures (£30m, 300,000 t CO2) come from Open Climate Fix's announcement reproduced by trade press. NESO's own quoted statement confirms deployment and 36-hour accuracy only. No NESO-authored page or regulator document with a savings figure was found." }, "evidence": [ { "kind": "news report", "citation": "Tim McManan-Smith, 'National Energy System Operator adopts AI solar forecasting to save £30m', The Energyst, 6 November 2025", "title": "National Energy System Operator adopts AI solar forecasting to save £30m", "url": "https://theenergyst.com/national-energy-system-operator-adopts-ai-solar-forecasting-to-save-30m/", "date": "2025-11-06", "written_by": "independent", "quote": "developed a cutting-edge tool that can accurately predict solar generation up to 36 hours in advance—revolutionising our solar forecasts in the control room." }, { "kind": "news report", "citation": "The Energyst, 6 November 2025 (claim from Open Climate Fix's announcement)", "title": "National Energy System Operator adopts AI solar forecasting to save £30m", "url": "https://theenergyst.com/national-energy-system-operator-adopts-ai-solar-forecasting-to-save-30m/", "date": "2025-11-06", "written_by": "independent", "quote": "helping to avoid at least £30 million in imbalance costs each year and cutting around 300,000 tonnes of CO₂ emissions." }, { "kind": "news report", "citation": "Matthew Lynas, 'AI powered solar forecasting helps UK grid operator reduce balancing costs', pv magazine, 7 November 2025", "title": "AI powered solar forecasting helps UK grid operator reduce balancing costs", "url": "https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/", "date": "2025-11-07", "written_by": "independent", "quote": "Quartz Solar says its tool saves Great Britain's grid operator GBP 30 million ($39 million) per year through more accurate forecasting" }, { "kind": "press release", "citation": "Open Climate Fix website, product spotlight, GB National Solar Forecast", "title": "Open Climate Fix", "url": "https://openclimatefix.org/", "date": null, "written_by": "makers", "quote": "Used daily by the National Energy System Operator, as well as some of the top power trading desks across the UK." } ], "replication": { "produced_by": [ "Satellite imagery, numerical weather data and historical generation data for a national PV fleet", "A system operator innovation program (NIA) that funded testing before operational integration", "A forecast refresh cycle faster than the operator's existing six-hourly weather updates" ], "must_hold": [ "Access to live satellite and generation data", "An operator willing to integrate a third-party forecast into reserve setting", "Independent measurement of imbalance-cost changes, which is absent here" ], "echoes": [] }, "paired_incident": null, "headline": "Quartz Solar goes live at NESO and may avoid £30m a year in costs", "metric": "at least £30m a year in avoided imbalance costs", "comparator": { "against": "NESO's solar forecasts before Quartz Solar was adopted", "before": "forecasting errors before adoption (not quantified)", "after": "halved forecasting errors", "basis": "measured", "quote": "Since adoption, Quartz Solar has halved forecasting errors, according to Open Climate Fix, equivalent to saving at least GBP 30 million in imbalance cost per year, with potential to increase to GBP 150 million ($197.0 million) per year in 2035 if government solar capacity targets are met.", "url": "https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/" }, "later": { "status": "unknown", "date": null, "note": "No development dated after the November 2025 go-live reports was found.", "quote": null, "url": null }, "value": { "amount": "GBP 30 million", "what": "imbalance cost avoided per year", "who": "Great Britain's electricity system operator NESO and, through balancing costs, consumers", "estimate": true, "quote": "Since adoption, Quartz Solar has halved forecasting errors, according to Open Climate Fix, equivalent to saving at least GBP 30 million in imbalance cost per year, with potential to increase to GBP 150 million ($197.0 million) per year in 2035 if government solar capacity targets are met.", "url": "https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/" }, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version, the value as stated from the cited sources.", "source": "https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/; https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/; https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/11833152; https://en.wikipedia.org/wiki/National_Energy_System_Operator", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0163", "catalog_version": "1.0.0", "source_fingerprint": "762f56e9d61746a84c50f2b1819e0cdc4e735befec7df93f8a91c6565106df5f", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "fructus", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0163-source-0001", "AIBD-0163-source-0002", "AIBD-0163-source-0003", "AIBD-0163-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0163-legacy-value", "DIV-0032" ], "role": "Existing monetary observations and Fructus statements with matched AIBD case links; each statement retains its own review and eligibility status" }, "provenance": { "kind": "curatorial", "basis": "Linked to the current Fructus dataset by its validated case identifier. 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But both figures (£30m, 300,000 t CO2) come from Open Climate Fix's announcement reproduced by trade press. NESO's own quoted statement confirms deployment and 36-hour accuracy only. 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0163-source-0001", "AIBD-0163-source-0002", "AIBD-0163-source-0003", "AIBD-0163-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Tim McManan-Smith, 'National Energy System Operator adopts AI solar forecasting to save £30m', The Energyst, 6 November 2025", "title": "National Energy System Operator adopts AI solar forecasting to save £30m", "url": "https://theenergyst.com/national-energy-system-operator-adopts-ai-solar-forecasting-to-save-30m/", "date": "2025-11-06", "written_by": "independent", "quote": "developed a cutting-edge tool that can accurately predict solar generation up to 36 hours in advance—revolutionising our solar forecasts in the control room." }, { "kind": "news report", "citation": "The Energyst, 6 November 2025 (claim from Open Climate Fix's announcement)", "title": "National Energy System Operator adopts AI solar forecasting to save £30m", "url": "https://theenergyst.com/national-energy-system-operator-adopts-ai-solar-forecasting-to-save-30m/", "date": "2025-11-06", "written_by": "independent", "quote": "helping to avoid at least £30 million in imbalance costs each year and cutting around 300,000 tonnes of CO₂ emissions." }, { "kind": "news report", "citation": "Matthew Lynas, 'AI powered solar forecasting helps UK grid operator reduce balancing costs', pv magazine, 7 November 2025", "title": "AI powered solar forecasting helps UK grid operator reduce balancing costs", "url": "https://www.pv-magazine.com/2025/11/07/ai-powered-solar-forecasting-helps-uk-grid-operator-reduce-balancing-costs/", "date": "2025-11-07", "written_by": "independent", "quote": "Quartz Solar says its tool saves Great Britain's grid operator GBP 30 million ($39 million) per year through more accurate forecasting" }, { "kind": "press release", "citation": "Open Climate Fix website, product spotlight, GB National Solar Forecast", "title": "Open Climate Fix", "url": "https://openclimatefix.org/", "written_by": "makers", "quote": "Used daily by the National Energy System Operator, as well as some of the top power trading desks across the UK." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Open Climate Fix's machine-learning solar forecast is live in NESO's control room; OCF claims at least £30m a year in avoided imbalance costs, a figure NESO's quoted statement does not give.", "account": "On 6 November 2025 Open Climate Fix (OCF), a not-for-profit, announced that Quartz Solar was live in the National Energy System Operator's (NESO) control room. OCF's AI-powered solar PV forecasting tool combines machine learning, live satellite imagery and weather data. It is fully integrated from day-ahead scheduling to real-time control after starting as a Network Innovation Allowance project (The Energyst, 6 November 2025). The announcement says the tool helps avoid at least £30 million in imbalance costs a year and cuts around 300,000 tonnes of CO2. NESO's Carolina Tortora, Head of AI, Digitalisation and Innovation, is quoted saying it can accurately predict solar generation up to 36 hours in advance. She says it is revolutionizing solar forecasts in the control room. She does not state the £30m figure. pv magazine (7 November 2025) attributes the £30 million (US$39 million) per year saving to Quartz Solar itself. It reports OCF's claim of halving forecasting errors across about 300 grid supply points. OCF's website says the forecast is used daily by NESO. The savings are the maker's estimate, not an operator-reported or audited figure." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model forecast electricity generation from solar panels." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "PVNet." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "PVNet" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Quartz Solar (Open Climate Fix machine-learning solar PV forecast, formerly PVNet)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Open Climate Fix" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Open Climate Fix's Quartz Solar goes live in NESO's control room and may avoid £30m a year in imbalance costs", "headline": "Quartz Solar goes live at NESO and may avoid £30m a year in costs" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "762f56e9d61746a84c50f2b1819e0cdc4e735befec7df93f8a91c6565106df5f" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 6 November 2025 Open Climate Fix (OCF), a not-for-profit, announced that Quartz Solar was live in the National Energy System Operator's (NESO) control room. OCF's AI-powered solar PV forecasting tool combines machine learning, live satellite imagery and weather data. It is fully integrated from day-ahead scheduling to real-time control after starting as a Network Innovation Allowance project (The Energyst, 6 November 2025). The announcement says the tool helps avoid at least £30 million in imbalance costs a year and cuts around 300,000 tonnes of CO2. NESO's Carolina Tortora, Head of AI, Digitalisation and Innovation, is quoted saying it can accurately predict solar generation up to 36 hours in advance. She says it is revolutionizing solar forecasts in the control room. She does not state the £30m figure. pv magazine (7 November 2025) attributes the £30 million (US$39 million) per year saving to Quartz Solar itself. It reports OCF's claim of halving forecasting errors across about 300 grid supply points. OCF's website says the forecast is used daily by NESO. The savings are the maker's estimate, not an operator-reported or audited figure.", "replication": { "produced_by": [ "Satellite imagery, numerical weather data and historical generation data for a national PV fleet", "A system operator innovation program (NIA) that funded testing before operational integration", "A forecast refresh cycle faster than the operator's existing six-hourly weather updates" ], "must_hold": [ "Access to live satellite and generation data", "An operator willing to integrate a third-party forecast into reserve setting", "Independent measurement of imbalance-cost changes, which is absent here" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 37, "reviewed": 0, "record_mapped": 37, "not_assessed": 54, "complete": false, "by_state": { "value_present": 37, "not_reported": 0, "unresolved": 0, "not_assessed": 54, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0342", "title": "UNEP MARS notification leads an operator to stop a 1,200-tonne methane pipeline leak in Kazakhstan (KAZ_S_136); IMEO observed emissions at the site again by May 2026", "summary": "UNEP IMEO case KAZ_S_136: pipeline leak first detected Sept 2025, operator rerouted gas, mitigation reported 26 Nov 2025, last emissions 12 Mar 2026; subsequent emissions seen as of 21 May 2026.", "date_observed": "2025-11-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "UNEP's International Methane Emissions Observatory (IMEO) publishes a Methane Alert and Response System (MARS) case document for source KAZ_S_136. It is an oil-and-gas pipeline in Kazakhstan at 43.39767°, 52.49505°. The document gives coordinates only. The document records first detection in September 2025, a plume imaged by DLR's EnMAP on 29 October 2025 and estimated emissions of 1,200 tonnes. The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions. Mitigation was reported on 26 November 2025. Last emissions were detected on 12 March 2026 (document updated 15 April 2026). A footnote states that as of 21 May 2026 IMEO observed subsequent methane emissions at the location and continues to engage stakeholders. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments coupled with scientific expertise and advanced AI models. It uses them to notify governments and companies. The Chemical Engineer (5 May 2026), relaying UNEP's snapshot, counts one Kazakhstan source among six that stopped emitting in 2026 after MARS alerts. UNEP's September 2026 snapshot reports a confirmed Kazakhstan gas-pipeline mitigation of an estimated 365 tonnes over one month. Neither gives a case ID, so their correspondence to KAZ_S_136 is not established.", "category": "benefit created", "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators and governments mitigate them. This case was that purpose.", "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation", "model_version": null, "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed pipeline operator in Kazakhstan (mitigation)", "location": "Kazakhstan, 43.39767°, 52.49505° (no place name in the UNEP document)", "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas transmission; intergovernmental observatory", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified. The benefit is an avoided greenhouse-gas release." }, { "group": "organizational", "depth": 2, "reason": "The operator stopped a leak of an estimated 1,200 tonnes of methane by rerouting gas after the notification, a material correction to its operations. The operator is unnamed and the leak was later observed again." }, { "group": "societal", "depth": 1, "reason": "One source among thousands of MARS alerts (the trade press counts over 3,500 alerts and about 43 confirmed cases since 2023). Climate benefit limited by the subsequent emissions observed in May 2026." } ], "ai_role": { "status": "assessed", "statement": "UNEP's case document records detection, notification, the operator's rerouting of gas and satellite confirmation. It names DLR's EnMAP for the plume image. The only description of an AI role is UNEP's general statement that IMEO analyzes satellite data with advanced AI models. The AI contribution to this specific detection is therefore not isolated. The sources are UNEP's own (system operator) plus trade press relaying UNEP. No operator or government statement is among the sources." }, "evidence": [ { "kind": "case report", "citation": "UNEP IMEO (2026). Methane Alert and Response System (MARS) case document, Kazakhstan KAZ_S_136 (pipeline), updated 15 Apr 2026. wedocs.unep.org.", "title": "MARS case KAZ_S_136, Kazakhstan", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, footnote on subsequent emissions.", "title": "MARS case KAZ_S_136, Kazakhstan (subsequent emissions footnote)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "As of 21 May 2026, IMEO observed subsequent methane emissions at this location." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, image caption naming the detecting instrument.", "title": "MARS case KAZ_S_136, Kazakhstan (detection)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The image shows a plume detected by DLR's EnMAP in Kazakhstan on 29 October 2025." }, { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "one each in Libya, Iraq and Kazakhstan" }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (the snapshot gives no case ID for the Kazakhstan mitigation).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "date": null, "written_by": "makers", "quote": "A gas pipeline leak resulted in the release of an estimated 365 tonnes of methane over the course of one month." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "date": null, "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ], "replication": { "produced_by": [ "Satellite plume detection (EnMAP image of 29 October 2025) analyzed by IMEO", "A MARS notification reaching an operator able to reroute gas flow", "Follow-up satellite observation to confirm cessation" ], "must_hold": [ "A country focal point or operator that answers notifications (UNEP's snapshot says most mitigation occurs where focal points direct information)", "A source type that can be isolated quickly (pipeline rerouting)", "Sustained repair: at this site emissions were observed again by 21 May 2026" ], "echoes": [ { "date": "2026-05-21", "setting": "Same site KAZ_S_136: IMEO observed subsequent methane emissions after the confirmed mitigation", "model_version": null, "outcome": "did not recur", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (DZA_S_012): MARS notification followed by repair of a decades-old source (existing record AIBD-0091)", "model_version": null, "outcome": "recurred", "source": "AIBD-0091" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection, per trade press relaying UNEP's August 2026 snapshot", "model_version": null, "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] }, "paired_incident": null, "headline": "UNEP MARS alert stops Kazakhstan leak; emissions seen again", "metric": "estimated emissions of 1,200 tonnes", "comparator": null, "later": null, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' case report, the makers' report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0342", "catalog_version": "1.0.0", "source_fingerprint": "a32e17efc837fdd8167a283df56b125c7814e01b21df66f2b2a10f3d8cba07fc", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0342-source-0001", "AIBD-0342-source-0002", "AIBD-0342-source-0003", "AIBD-0342-source-0004", "AIBD-0342-source-0005", "AIBD-0342-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed pipeline operator in Kazakhstan (mitigation)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "UNEP's case document records detection, notification, the operator's rerouting of gas and satellite confirmation. It names DLR's EnMAP for the plume image. The only description of an AI role is UNEP's general statement that IMEO analyzes satellite data with advanced AI models. The AI contribution to this specific detection is therefore not isolated. The sources are UNEP's own (system operator) plus trade press relaying UNEP. No operator or government statement is among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "UNEP's case document records detection, notification, the operator's rerouting of gas and satellite confirmation. It names DLR's EnMAP for the plume image. The only description of an AI role is UNEP's general statement that IMEO analyzes satellite data with advanced AI models. The AI contribution to this specific detection is therefore not isolated. The sources are UNEP's own (system operator) plus trade press relaying UNEP. No operator or government statement is among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. The benefit is an avoided greenhouse-gas release." }, { "group": "organizational", "depth": 2, "reason": "The operator stopped a leak of an estimated 1,200 tonnes of methane by rerouting gas after the notification, a material correction to its operations. The operator is unnamed and the leak was later observed again." }, { "group": "societal", "depth": 1, "reason": "One source among thousands of MARS alerts (the trade press counts over 3,500 alerts and about 43 confirmed cases since 2023). Climate benefit limited by the subsequent emissions observed in May 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, the makers' case report, the makers' report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. The benefit is an avoided greenhouse-gas release." }, { "group": "organizational", "depth": 2, "reason": "The operator stopped a leak of an estimated 1,200 tonnes of methane by rerouting gas after the notification, a material correction to its operations. The operator is unnamed and the leak was later observed again." }, { "group": "societal", "depth": 1, "reason": "One source among thousands of MARS alerts (the trade press counts over 3,500 alerts and about 43 confirmed cases since 2023). Climate benefit limited by the subsequent emissions observed in May 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. The benefit is an avoided greenhouse-gas release." }, { "group": "organizational", "depth": 2, "reason": "The operator stopped a leak of an estimated 1,200 tonnes of methane by rerouting gas after the notification, a material correction to its operations. The operator is unnamed and the leak was later observed again." }, { "group": "societal", "depth": 1, "reason": "One source among thousands of MARS alerts (the trade press counts over 3,500 alerts and about 43 confirmed cases since 2023). Climate benefit limited by the subsequent emissions observed in May 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "estimated emissions of 1,200 tonnes", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0342" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "UNEP's International Methane Emissions Observatory (IMEO) publishes a Methane Alert and Response System (MARS) case document for source KAZ_S_136. It is an oil-and-gas pipeline in Kazakhstan at 43.39767°, 52.49505°. The document gives coordinates only. The document records first detection in September 2025, a plume imaged by DLR's EnMAP on 29 October 2025 and estimated emissions of 1,200 tonnes. The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions. Mitigation was reported on 26 November 2025. Last emissions were detected on 12 March 2026 (document updated 15 April 2026). A footnote states that as of 21 May 2026 IMEO observed subsequent methane emissions at the location and continues to engage stakeholders. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments coupled with scientific expertise and advanced AI models. It uses them to notify governments and companies. The Chemical Engineer (5 May 2026), relaying UNEP's snapshot, counts one Kazakhstan source among six that stopped emitting in 2026 after MARS alerts. UNEP's September 2026 snapshot reports a confirmed Kazakhstan gas-pipeline mitigation of an estimated 365 tonnes over one month. Neither gives a case ID, so their correspondence to KAZ_S_136 is not established.", "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified. The benefit is an avoided greenhouse-gas release." }, { "group": "organizational", "depth": 2, "reason": "The operator stopped a leak of an estimated 1,200 tonnes of methane by rerouting gas after the notification, a material correction to its operations. The operator is unnamed and the leak was later observed again." }, { "group": "societal", "depth": 1, "reason": "One source among thousands of MARS alerts (the trade press counts over 3,500 alerts and about 43 confirmed cases since 2023). Climate benefit limited by the subsequent emissions observed in May 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators and governments mitigate them. This case was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Kazakhstan, 43.39767°, 52.49505° (no place name in the UNEP document)", "developer_country": "France", "deployer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Satellite-based detection and notification of large methane plumes so that operators and governments mitigate them. This case was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-11-26", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Satellite plume detection (EnMAP image of 29 October 2025) analyzed by IMEO", "A MARS notification reaching an operator able to reroute gas flow", "Follow-up satellite observation to confirm cessation" ], "must_hold": [ "A country focal point or operator that answers notifications (UNEP's snapshot says most mitigation occurs where focal points direct information)", "A source type that can be isolated quickly (pipeline rerouting)", "Sustained repair: at this site emissions were observed again by 21 May 2026" ], "echoes": [ { "date": "2026-05-21", "setting": "Same site KAZ_S_136: IMEO observed subsequent methane emissions after the confirmed mitigation", "outcome": "did not recur", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (DZA_S_012): MARS notification followed by repair of a decades-old source (existing record AIBD-0091)", "outcome": "recurred", "source": "AIBD-0091" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection, per trade press relaying UNEP's August 2026 snapshot", "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Satellite plume detection (EnMAP image of 29 October 2025) analyzed by IMEO", "A MARS notification reaching an operator able to reroute gas flow", "Follow-up satellite observation to confirm cessation" ], "must_hold": [ "A country focal point or operator that answers notifications (UNEP's snapshot says most mitigation occurs where focal points direct information)", "A source type that can be isolated quickly (pipeline rerouting)", "Sustained repair: at this site emissions were observed again by 21 May 2026" ], "echoes": [ { "date": "2026-05-21", "setting": "Same site KAZ_S_136: IMEO observed subsequent methane emissions after the confirmed mitigation", "outcome": "did not recur", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (DZA_S_012): MARS notification followed by repair of a decades-old source (existing record AIBD-0091)", "outcome": "recurred", "source": "AIBD-0091" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection, per trade press relaying UNEP's August 2026 snapshot", "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas transmission; intergovernmental observatory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "UNEP IMEO (2026). Methane Alert and Response System (MARS) case document, Kazakhstan KAZ_S_136 (pipeline), updated 15 Apr 2026. wedocs.unep.org.", "title": "MARS case KAZ_S_136, Kazakhstan", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, footnote on subsequent emissions.", "title": "MARS case KAZ_S_136, Kazakhstan (subsequent emissions footnote)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "As of 21 May 2026, IMEO observed subsequent methane emissions at this location." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, image caption naming the detecting instrument.", "title": "MARS case KAZ_S_136, Kazakhstan (detection)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The image shows a plume detected by DLR's EnMAP in Kazakhstan on 29 October 2025." }, { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "one each in Libya, Iraq and Kazakhstan" }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (the snapshot gives no case ID for the Kazakhstan mitigation).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "written_by": "makers", "quote": "A gas pipeline leak resulted in the release of an estimated 365 tonnes of methane over the course of one month." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0342-source-0001", "AIBD-0342-source-0002", "AIBD-0342-source-0003", "AIBD-0342-source-0004", "AIBD-0342-source-0005", "AIBD-0342-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "UNEP IMEO (2026). Methane Alert and Response System (MARS) case document, Kazakhstan KAZ_S_136 (pipeline), updated 15 Apr 2026. wedocs.unep.org.", "title": "MARS case KAZ_S_136, Kazakhstan", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, footnote on subsequent emissions.", "title": "MARS case KAZ_S_136, Kazakhstan (subsequent emissions footnote)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "As of 21 May 2026, IMEO observed subsequent methane emissions at this location." }, { "kind": "case report", "citation": "UNEP IMEO (2026). Same case document, image caption naming the detecting instrument.", "title": "MARS case KAZ_S_136, Kazakhstan (detection)", "url": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download", "date": "2026-04-15", "written_by": "makers", "quote": "The image shows a plume detected by DLR's EnMAP in Kazakhstan on 29 October 2025." }, { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "one each in Libya, Iraq and Kazakhstan" }, { "kind": "report", "citation": "UNEP IMEO (2026). Methane Alert and Response System Snapshot: Top 50 Emitters, Country Responses and Mitigation, September 2026 Update (the snapshot gives no case ID for the Kazakhstan mitigation).", "title": "MARS Snapshot, September 2026 Update", "url": "https://methanedata.unep.org/downloads/top50_emitters/latest/mars_snapshot_latest.pdf", "written_by": "makers", "quote": "A gas pipeline leak resulted in the release of an estimated 365 tonnes of methane over the course of one month." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "UNEP IMEO case KAZ_S_136: pipeline leak first detected Sept 2025, operator rerouted gas, mitigation reported 26 Nov 2025, last emissions 12 Mar 2026; subsequent emissions seen as of 21 May 2026.", "account": "UNEP's International Methane Emissions Observatory (IMEO) publishes a Methane Alert and Response System (MARS) case document for source KAZ_S_136. It is an oil-and-gas pipeline in Kazakhstan at 43.39767°, 52.49505°. The document gives coordinates only. The document records first detection in September 2025, a plume imaged by DLR's EnMAP on 29 October 2025 and estimated emissions of 1,200 tonnes. The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions. Mitigation was reported on 26 November 2025. Last emissions were detected on 12 March 2026 (document updated 15 April 2026). A footnote states that as of 21 May 2026 IMEO observed subsequent methane emissions at the location and continues to engage stakeholders. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments coupled with scientific expertise and advanced AI models. It uses them to notify governments and companies. The Chemical Engineer (5 May 2026), relaying UNEP's snapshot, counts one Kazakhstan source among six that stopped emitting in 2026 after MARS alerts. UNEP's September 2026 snapshot reports a confirmed Kazakhstan gas-pipeline mitigation of an estimated 365 tonnes over one month. Neither gives a case ID, so their correspondence to KAZ_S_136 is not established." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UNEP International Methane Emissions Observatory (IMEO)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "UNEP MARS notification leads an operator to stop a 1,200-tonne methane pipeline leak in Kazakhstan (KAZ_S_136); IMEO observed emissions at the site again by May 2026", "headline": "UNEP MARS alert stops Kazakhstan leak; emissions seen again" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a32e17efc837fdd8167a283df56b125c7814e01b21df66f2b2a10f3d8cba07fc" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "UNEP's International Methane Emissions Observatory (IMEO) publishes a Methane Alert and Response System (MARS) case document for source KAZ_S_136. It is an oil-and-gas pipeline in Kazakhstan at 43.39767°, 52.49505°. The document gives coordinates only. The document records first detection in September 2025, a plume imaged by DLR's EnMAP on 29 October 2025 and estimated emissions of 1,200 tonnes. The operator transferred the gas flow from the affected pipeline to another pipeline, stopping the emissions. Mitigation was reported on 26 November 2025. Last emissions were detected on 12 March 2026 (document updated 15 April 2026). A footnote states that as of 21 May 2026 IMEO observed subsequent methane emissions at the location and continues to engage stakeholders. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments coupled with scientific expertise and advanced AI models. It uses them to notify governments and companies. The Chemical Engineer (5 May 2026), relaying UNEP's snapshot, counts one Kazakhstan source among six that stopped emitting in 2026 after MARS alerts. UNEP's September 2026 snapshot reports a confirmed Kazakhstan gas-pipeline mitigation of an estimated 365 tonnes over one month. Neither gives a case ID, so their correspondence to KAZ_S_136 is not established.", "replication": { "produced_by": [ "Satellite plume detection (EnMAP image of 29 October 2025) analyzed by IMEO", "A MARS notification reaching an operator able to reroute gas flow", "Follow-up satellite observation to confirm cessation" ], "must_hold": [ "A country focal point or operator that answers notifications (UNEP's snapshot says most mitigation occurs where focal points direct information)", "A source type that can be isolated quickly (pipeline rerouting)", "Sustained repair: at this site emissions were observed again by 21 May 2026" ], "echoes": [ { "date": "2026-05-21", "setting": "Same site KAZ_S_136: IMEO observed subsequent methane emissions after the confirmed mitigation", "outcome": "did not recur", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (DZA_S_012): MARS notification followed by repair of a decades-old source (existing record AIBD-0091)", "outcome": "recurred", "source": "AIBD-0091" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection, per trade press relaying UNEP's August 2026 snapshot", "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0137", "title": "Grok may have flagged a perforated ulcer or atypical appendicitis for a 49-year-old man sent home from a Norwegian legevakt with an acid blocker, telling him to demand a CT; the scan found an appendix close to rupturing, removed on 3 December 2025", "summary": "Grok told a 49-year-old Norwegian sent home with an acid blocker to demand a CT; it found an appendix near rupture, removed 3 December 2025.", "date_observed": "2025-12-03", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The night before his surgery on 3 December 2025, a 49-year-old man in Norway, Reddit user u/Tykjen, had constant abdominal pain. He was examined at a legevakt (out-of-hours clinic), given the acid blocker Somac and sent home. He described the pain to xAI's Grok in a browser chat. Grok named perforated ulcer and atypical appendicitis as the likeliest causes. It told him to get computed tomography (CT) or ultrasound that night and scripted a CT request. The next day, by his account, his local physician sent him to hospital. A CT showed an appendix close to rupturing. It was removed laparoscopically and he went home on 4 December, when he posted the story. Elon Musk amplified it on 6 December.", "category": "protective response", "unexpected": false, "purpose": "Grok is xAI's general-purpose conversational assistant. Answering a description of symptoms with possible causes and advice on when to seek care is within that general use. The man had used it for a year on other topics. xAI did not build it as a medical device. The benefit was ordinary use, not an unexpected one. After the event Musk posted “Try it!” about Grok for medical questions.", "system": "Grok (xAI conversational assistant), used in the browser", "model_version": "Not reported; the man said he used the browser version on his computer and that the December 2025 chat was a fresh conversation, and the shared transcript names no model.", "developer": "xAI", "deployer": "xAI (Grok web app)", "location": "Norway", "domain": "Healthcare (emergency self-triage)", "segment": "Consumer use of a general chatbot for triage advice", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-12-05-11cb" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "An appendix the man says the CT showed close to rupturing was removed on 3 December 2025. The pain was gone and he went home the next day. He and Musk call it life-saving. That rests on his account and a ward photo. No clinician, hospital or record has spoken. A doctor commenting in the thread said severe abdominal pain in a younger patient almost always gets a CT. So life-saving is not established." } ], "ai_role": { "status": "assessed", "statement": "The shared conversation shows what Grok contributed. He described constant pain for six hours, worse lying flat and eased by sitting with knees to chest, with no fever. Grok ranked perforated peptic ulcer first and early or atypical appendicitis second. It called that a pattern doctors take very seriously. It urged an ER visit that night for a CT or ultrasound. Once he said the legevakt had sent him home with Somac, it scripted a request for a senior doctor and a CT scan. He told Grok afterwards that asking for the CT got him prioritized for surgery. Whether his local physician or the hospital would have imaged him without that request is unknown. TipRanks reports from the thread that he told the doctors his sister, a nurse, had suggested the scan. The Reddit post the press quoted was drafted by Grok from his description. It says he walked back to the ER, where his later comments say the physician referred him the next day." }, "evidence": [ { "kind": "other", "citation": "u/Tykjen (2025). How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025). r/grok, Reddit, 4 December 2025, 13:17 UTC; image post (a mirror selfie on a hospital ward with three dressed abdominal incisions and an IV line), 1,260 points, 179 comments; text and comments read from the Arctic Shift and PullPush archives, where the author says 'I live in Norway' (20 December 2025).", "title": "How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025)", "url": "https://www.reddit.com/r/grok/comments/1pdzrk1/how_a_latenight_conversation_with_grok_got_me_to/", "date": "2025-12-04", "written_by": "beneficiary", "quote": "Grok immediately flagged perforated ulcer or atypical appendicitis, told me the exact red-flag pattern I was describing, and basically said “go back right now and ask for a CT.”" }, { "kind": "other", "citation": "Tykjen and Grok (2025–2026). Managing Intense Stomach Pain Urgently. Shared Grok conversation on X, link posted by u/Tykjen in the Reddit thread on 2 January 2026 when asked for a screenshot; the transcript runs from 'intense stomach pain wont go away. tips' through the legevakt visit, the surgery report and recovery, and the man's later messages give the surgery date as 3 December; it also contains Grok's draft of the Reddit post.", "title": "Managing Intense Stomach Pain Urgently", "url": "https://x.com/i/grok/share/RNHdX8qbyao4I4oNl6TEcmuNr", "date": null, "written_by": "beneficiary", "quote": "I am worried this is a perforated ulcer. I would like to speak to the senior doctor and I need proper pain relief and a CT scan." }, { "kind": "news report", "citation": "Simon Alvarez / Teslarati (2025). Man credits Grok AI with saving his life after ER missed near-ruptured appendix. Teslarati, 5 December 2025 (the first press report, sourced to the Reddit post).", "title": "Man credits Grok AI with saving his life after ER missed near-ruptured appendix", "url": "https://www.teslarati.com/man-credits-grok-ai-with-saving-his-life-after-er-missed-near-ruptured-appendix/", "date": "2025-12-05", "written_by": "independent", "quote": "The AI flagged some of the man’s symptoms and urged him to return to the ER immediately and demand a CT scan." }, { "kind": "other", "citation": "Mark Kretschmann (@mark_k) (2025). Post reproducing the Reddit text with the ward photo, X, 5 December 2025, 08:20 UTC; 3.6 million views by 20 October 2026 (fxtwitter API). Embedded by Teslarati; the vector by which the story reached X.", "title": "Man has his life saved by Grok from @xAI after a ruptured appendix", "url": "https://x.com/mark_k/status/1996857239311634793", "date": "2025-12-05", "written_by": "independent", "quote": "Man has his life saved by Grok from @xAI after a ruptured appendix" }, { "kind": "news report", "citation": "Team Latestly / LatestLY (2025). Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix. LatestLY, 6 December 2025; the outlet's own 'TruLY Score' rates the story 2 of 5, 'Unverified'.", "title": "Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix", "url": "https://www.latestly.com/socially/social-viral/man-says-xais-grok-helped-save-his-life-after-er-missed-near-ruptured-appendix-7229363.html", "date": "2025-12-06", "written_by": "independent", "quote": "relies on a single source or posts by social media users, with no independent verification." }, { "kind": "news report", "citation": "Trond Bie / ITavisen (2025). Grok reddet nordmannens liv. ITavisen, 7 December 2025 (Norwegian technology news site; relies on the Reddit post and notes the story's spread on X).", "title": "Grok reddet nordmannens liv", "url": "https://itavisen.no/2025/12/07/nordmann-grok-reddet-livet-blindtarm/", "date": "2025-12-07", "written_by": "independent", "quote": "49 år gammel nordmann fikk livet reddet etter at AI-en Grok oppdaget en nesten sprukket blindtarm som legevakten først overså." }, { "kind": "news report", "citation": "TOI Lifestyle Desk / The Times of India (2025). 49-year-old man says Grok AI saved his life after doctors missed his appendix emergency. The Times of India, 7 December 2025.", "title": "49-year-old man says Grok AI saved his life after doctors missed his appendix emergency", "url": "https://timesofindia.indiatimes.com/etimes/trending/49-year-old-man-says-grok-ai-saved-his-life-after-doctors-missed-his-appendix-emergency/articleshow/125819004.cms", "date": "2025-12-07", "written_by": "independent", "quote": "This story is based on a user-generated Reddit post and reflects the individual’s personal account." }, { "kind": "news report", "citation": "Vince Condarcuri / TipRanks (2025). Man Says that Grok AI Saved His Life after an ER Misdiagnosis. TipRanks, 8 December 2025; syndicated on Markets Insider (Business Insider), the copy the OECD Monitor cites.", "title": "Man Says that Grok AI Saved His Life after an ER Misdiagnosis", "url": "https://www.tipranks.com/news/man-says-that-grok-ai-saved-his-life-after-an-er-misdiagnosis", "date": "2025-12-08", "written_by": "independent", "quote": "the man admitted he didn’t tell the doctors that the AI made the suggestion. Instead, he claimed that his sister, a nurse, told him to ask for the scan" }, { "kind": "press release", "citation": "Elon Musk (@elonmusk) (2026). Post quoting @cb_doge, X, 1 January 2026, 21:05 UTC, 15.7 million views (fxtwitter API). Musk had quote-posted Mario Nawfal's summary with 'Cool' on 6 December 2025 and @teslaownersSV's with 'Grok ❤️' later on 1 January 2026; the man reports a fourth share and a $40,000 crypto-community donation he forwarded to a wildlife foundation.", "title": "Try it! Last year, Grok saved the life of a man in Norway", "url": "https://x.com/elonmusk/status/2006834169637384470", "date": "2026-01-01", "written_by": "makers", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" }, { "kind": "news report", "citation": "Tanmay Puri / International Business Times UK (2026). How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts. IBTimes UK, 2 January 2026. Note: the article attributes to Musk the line about uploading X-rays or MRI images, which the fxtwitter record shows was @cb_doge's post that Musk quoted.", "title": "How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts", "url": "https://www.ibtimes.co.uk/how-grok-saved-mans-life-when-doctors-couldnt-elon-musk-reacts-1767583", "date": "2026-01-02", "written_by": "independent", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" } ], "replication": { "produced_by": [ "A patient with hours of constant, severe abdominal pain who had been examined, given an acid blocker and sent home without imaging.", "A detailed symptom description put to a general chatbot: constant pain, worse lying flat, eased by sitting with knees to chest, no fever. It matched these to surgical causes and said so without hedging.", "A second clinical contact the next day at which the patient repeated the chatbot's reasoning and asked for a CT." ], "must_hold": [ "The chatbot's differential includes the true cause. Here it ranked perforated ulcer first and atypical appendicitis second, and the second was right.", "A clinician agrees to image. The referral here came from his local physician. Whether the request changed her decision is unknown.", "Such cases are self-published. No clinician, hospital or document has confirmed this one. The first-person post was itself drafted by the chatbot. So the record stands or falls with his account and the shared transcript." ], "echoes": [] }, "paired_incident": null, "headline": "Grok tells a man sent home to demand a CT; appendix near rupture", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a differential naming atypical appendicitis and a scripted demand for a CT) is documented by the man's own post and the shared Grok transcript, but the counterfactual is not shown, since his local physician referred him the next day and he told the doctors his sister had suggested the scan. The Monitor's date of 5 December is Teslarati's publication date; the surgery date, 3 December 2025, comes from the man's own message in the transcript, and the post was created 4 December 2025 13:17 UTC (Reddit archive metadata). Reddit itself blocked fetching; the post and 100 of its 179 comments were read through the Arctic Shift and PullPush archives. The Reddit post text quoted by every outlet was written by Grok as a draft at the man's request, and differs from his later comments on where the first visit was (a legevakt, not the ER) and how he got back (via his local physician). The Monitor's “Norwegian” is confirmed by the man's own comment and by ITavisen. No hospital, clinician, Norwegian health authority or record was found; the man says he filed a complaint against the first doctor. WebSearch was exhausted, so searches ran through Brave and Mojeek via curl; Hindustan Times and Haberler could not be read.", "source": "https://oecd.ai/en/incidents/2025-12-05-11cb", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/XAI_(company); https://en.wikipedia.org/wiki/XAI_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports, one other independent source, the makers' press release and two other sources from the beneficiary. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0137", "catalog_version": "1.0.0", "source_fingerprint": "a6e560bbfb3f986d46c6a908b58698792428a05b070d4a54b4466b020a9420d5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0137-source-0001", "AIBD-0137-source-0002", "AIBD-0137-source-0003", "AIBD-0137-source-0004", "AIBD-0137-source-0005", "AIBD-0137-source-0006", "AIBD-0137-source-0007", "AIBD-0137-source-0008", "AIBD-0137-source-0009", "AIBD-0137-source-0010" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "xAI", "deployer": "xAI (Grok web app)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The shared conversation shows what Grok contributed. He described constant pain for six hours, worse lying flat and eased by sitting with knees to chest, with no fever. Grok ranked perforated peptic ulcer first and early or atypical appendicitis second. It called that a pattern doctors take very seriously. It urged an ER visit that night for a CT or ultrasound. Once he said the legevakt had sent him home with Somac, it scripted a request for a senior doctor and a CT scan. He told Grok afterwards that asking for the CT got him prioritized for surgery. Whether his local physician or the hospital would have imaged him without that request is unknown. TipRanks reports from the thread that he told the doctors his sister, a nurse, had suggested the scan. The Reddit post the press quoted was drafted by Grok from his description. It says he walked back to the ER, where his later comments say the physician referred him the next day." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Grok recommended urgent abdominal imaging and helped the patient ask for a CT scan after he had been sent home. He reported that his request expedited surgery.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The shared conversation shows what Grok contributed. He described constant pain for six hours, worse lying flat and eased by sitting with knees to chest, with no fever. Grok ranked perforated peptic ulcer first and early or atypical appendicitis second. It called that a pattern doctors take very seriously. It urged an ER visit that night for a CT or ultrasound. Once he said the legevakt had sent him home with Somac, it scripted a request for a senior doctor and a CT scan. He told Grok afterwards that asking for the CT got him prioritized for surgery. Whether his local physician or the hospital would have imaged him without that request is unknown. TipRanks reports from the thread that he told the doctors his sister, a nurse, had suggested the scan. The Reddit post the press quoted was drafted by Grok from his description. It says he walked back to the ER, where his later comments say the physician referred him the next day." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An appendix the man says the CT showed close to rupturing was removed on 3 December 2025. The pain was gone and he went home the next day. He and Musk call it life-saving. That rests on his account and a ward photo. No clinician, hospital or record has spoken. A doctor commenting in the thread said severe abdominal pain in a younger patient almost always gets a CT. So life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports, one other independent source, the makers' press release and two other sources from the beneficiary. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An appendix the man says the CT showed close to rupturing was removed on 3 December 2025. The pain was gone and he went home the next day. He and Musk call it life-saving. That rests on his account and a ward photo. No clinician, hospital or record has spoken. A doctor commenting in the thread said severe abdominal pain in a younger patient almost always gets a CT. So life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An appendix the man says the CT showed close to rupturing was removed on 3 December 2025. The pain was gone and he went home the next day. He and Musk call it life-saving. That rests on his account and a ward photo. No clinician, hospital or record has spoken. A doctor commenting in the thread said severe abdominal pain in a younger patient almost always gets a CT. So life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The patient’s accounts differ on whether he returned to the emergency department himself or received a referral the next day. The available evidence does not establish whether clinicians would have ordered imaging without his request.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-12-05-11cb" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Clinicians ordered the imaging and decided that surgery was needed." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0137" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The night before his surgery on 3 December 2025, a 49-year-old man in Norway, Reddit user u/Tykjen, had constant abdominal pain. He was examined at a legevakt (out-of-hours clinic), given the acid blocker Somac and sent home. He described the pain to xAI's Grok in a browser chat. Grok named perforated ulcer and atypical appendicitis as the likeliest causes. It told him to get computed tomography (CT) or ultrasound that night and scripted a CT request. The next day, by his account, his local physician sent him to hospital. A CT showed an appendix close to rupturing. It was removed laparoscopically and he went home on 4 December, when he posted the story. Elon Musk amplified it on 6 December.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "An appendix the man says the CT showed close to rupturing was removed on 3 December 2025. The pain was gone and he went home the next day. He and Musk call it life-saving. That rests on his account and a ward photo. No clinician, hospital or record has spoken. A doctor commenting in the thread said severe abdominal pain in a younger patient almost always gets a CT. So life-saving is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Grok is xAI's general-purpose conversational assistant. Answering a description of symptoms with possible causes and advice on when to seek care is within that general use. The man had used it for a year on other topics. xAI did not build it as a medical device. The benefit was ordinary use, not an unexpected one. After the event Musk posted “Try it!” about Grok for medical questions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Norway", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Grok is xAI's general-purpose conversational assistant. Answering a description of symptoms with possible causes and advice on when to seek care is within that general use. The man had used it for a year on other topics. xAI did not build it as a medical device. The benefit was ordinary use, not an unexpected one. After the event Musk posted “Try it!” about Grok for medical questions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-12-03", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a differential naming atypical appendicitis and a scripted demand for a CT) is documented by the man's own post and the shared Grok transcript, but the counterfactual is not shown, since his local physician referred him the next day and he told the doctors his sister had suggested the scan. The Monitor's date of 5 December is Teslarati's publication date; the surgery date, 3 December 2025, comes from the man's own message in the transcript, and the post was created 4 December 2025 13:17 UTC (Reddit archive metadata). Reddit itself blocked fetching; the post and 100 of its 179 comments were read through the Arctic Shift and PullPush archives. The Reddit post text quoted by every outlet was written by Grok as a draft at the man's request, and differs from his later comments on where the first visit was (a legevakt, not the ER) and how he got back (via his local physician). The Monitor's “Norwegian” is confirmed by the man's own comment and by ITavisen. No hospital, clinician, Norwegian health authority or record was found; the man says he filed a complaint against the first doctor. 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It matched these to surgical causes and said so without hedging.", "A second clinical contact the next day at which the patient repeated the chatbot's reasoning and asked for a CT." ], "must_hold": [ "The chatbot's differential includes the true cause. Here it ranked perforated ulcer first and atypical appendicitis second, and the second was right.", "A clinician agrees to image. The referral here came from his local physician. Whether the request changed her decision is unknown.", "Such cases are self-published. No clinician, hospital or document has confirmed this one. The first-person post was itself drafted by the chatbot. So the record stands or falls with his account and the shared transcript." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a differential naming atypical appendicitis and a scripted demand for a CT) is documented by the man's own post and the shared Grok transcript, but the counterfactual is not shown, since his local physician referred him the next day and he told the doctors his sister had suggested the scan. The Monitor's date of 5 December is Teslarati's publication date; the surgery date, 3 December 2025, comes from the man's own message in the transcript, and the post was created 4 December 2025 13:17 UTC (Reddit archive metadata). Reddit itself blocked fetching; the post and 100 of its 179 comments were read through the Arctic Shift and PullPush archives. The Reddit post text quoted by every outlet was written by Grok as a draft at the man's request, and differs from his later comments on where the first visit was (a legevakt, not the ER) and how he got back (via his local physician). The Monitor's “Norwegian” is confirmed by the man's own comment and by ITavisen. No hospital, clinician, Norwegian health authority or record was found; the man says he filed a complaint against the first doctor. 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How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025). r/grok, Reddit, 4 December 2025, 13:17 UTC; image post (a mirror selfie on a hospital ward with three dressed abdominal incisions and an IV line), 1,260 points, 179 comments; text and comments read from the Arctic Shift and PullPush archives, where the author says 'I live in Norway' (20 December 2025).", "title": "How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025)", "url": "https://www.reddit.com/r/grok/comments/1pdzrk1/how_a_latenight_conversation_with_grok_got_me_to/", "date": "2025-12-04", "written_by": "beneficiary", "quote": "Grok immediately flagged perforated ulcer or atypical appendicitis, told me the exact red-flag pattern I was describing, and basically said “go back right now and ask for a CT.”" }, { "kind": "other", "citation": "Tykjen and Grok (2025–2026). Managing Intense Stomach Pain Urgently. Shared Grok conversation on X, link posted by u/Tykjen in the Reddit thread on 2 January 2026 when asked for a screenshot; the transcript runs from 'intense stomach pain wont go away. tips' through the legevakt visit, the surgery report and recovery, and the man's later messages give the surgery date as 3 December; it also contains Grok's draft of the Reddit post.", "title": "Managing Intense Stomach Pain Urgently", "url": "https://x.com/i/grok/share/RNHdX8qbyao4I4oNl6TEcmuNr", "written_by": "beneficiary", "quote": "I am worried this is a perforated ulcer. I would like to speak to the senior doctor and I need proper pain relief and a CT scan." }, { "kind": "news report", "citation": "Simon Alvarez / Teslarati (2025). Man credits Grok AI with saving his life after ER missed near-ruptured appendix. Teslarati, 5 December 2025 (the first press report, sourced to the Reddit post).", "title": "Man credits Grok AI with saving his life after ER missed near-ruptured appendix", "url": "https://www.teslarati.com/man-credits-grok-ai-with-saving-his-life-after-er-missed-near-ruptured-appendix/", "date": "2025-12-05", "written_by": "independent", "quote": "The AI flagged some of the man’s symptoms and urged him to return to the ER immediately and demand a CT scan." }, { "kind": "other", "citation": "Mark Kretschmann (@mark_k) (2025). Post reproducing the Reddit text with the ward photo, X, 5 December 2025, 08:20 UTC; 3.6 million views by 20 October 2026 (fxtwitter API). Embedded by Teslarati; the vector by which the story reached X.", "title": "Man has his life saved by Grok from @xAI after a ruptured appendix", "url": "https://x.com/mark_k/status/1996857239311634793", "date": "2025-12-05", "written_by": "independent", "quote": "Man has his life saved by Grok from @xAI after a ruptured appendix" }, { "kind": "news report", "citation": "Team Latestly / LatestLY (2025). Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix. LatestLY, 6 December 2025; the outlet's own 'TruLY Score' rates the story 2 of 5, 'Unverified'.", "title": "Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix", "url": "https://www.latestly.com/socially/social-viral/man-says-xais-grok-helped-save-his-life-after-er-missed-near-ruptured-appendix-7229363.html", "date": "2025-12-06", "written_by": "independent", "quote": "relies on a single source or posts by social media users, with no independent verification." }, { "kind": "news report", "citation": "Trond Bie / ITavisen (2025). Grok reddet nordmannens liv. ITavisen, 7 December 2025 (Norwegian technology news site; relies on the Reddit post and notes the story's spread on X).", "title": "Grok reddet nordmannens liv", "url": "https://itavisen.no/2025/12/07/nordmann-grok-reddet-livet-blindtarm/", "date": "2025-12-07", "written_by": "independent", "quote": "49 år gammel nordmann fikk livet reddet etter at AI-en Grok oppdaget en nesten sprukket blindtarm som legevakten først overså." }, { "kind": "news report", "citation": "TOI Lifestyle Desk / The Times of India (2025). 49-year-old man says Grok AI saved his life after doctors missed his appendix emergency. The Times of India, 7 December 2025.", "title": "49-year-old man says Grok AI saved his life after doctors missed his appendix emergency", "url": "https://timesofindia.indiatimes.com/etimes/trending/49-year-old-man-says-grok-ai-saved-his-life-after-doctors-missed-his-appendix-emergency/articleshow/125819004.cms", "date": "2025-12-07", "written_by": "independent", "quote": "This story is based on a user-generated Reddit post and reflects the individual’s personal account." }, { "kind": "news report", "citation": "Vince Condarcuri / TipRanks (2025). Man Says that Grok AI Saved His Life after an ER Misdiagnosis. TipRanks, 8 December 2025; syndicated on Markets Insider (Business Insider), the copy the OECD Monitor cites.", "title": "Man Says that Grok AI Saved His Life after an ER Misdiagnosis", "url": "https://www.tipranks.com/news/man-says-that-grok-ai-saved-his-life-after-an-er-misdiagnosis", "date": "2025-12-08", "written_by": "independent", "quote": "the man admitted he didn’t tell the doctors that the AI made the suggestion. Instead, he claimed that his sister, a nurse, told him to ask for the scan" }, { "kind": "press release", "citation": "Elon Musk (@elonmusk) (2026). Post quoting @cb_doge, X, 1 January 2026, 21:05 UTC, 15.7 million views (fxtwitter API). Musk had quote-posted Mario Nawfal's summary with 'Cool' on 6 December 2025 and @teslaownersSV's with 'Grok ❤️' later on 1 January 2026; the man reports a fourth share and a $40,000 crypto-community donation he forwarded to a wildlife foundation.", "title": "Try it! Last year, Grok saved the life of a man in Norway", "url": "https://x.com/elonmusk/status/2006834169637384470", "date": "2026-01-01", "written_by": "makers", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" }, { "kind": "news report", "citation": "Tanmay Puri / International Business Times UK (2026). How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts. IBTimes UK, 2 January 2026. Note: the article attributes to Musk the line about uploading X-rays or MRI images, which the fxtwitter record shows was @cb_doge's post that Musk quoted.", "title": "How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts", "url": "https://www.ibtimes.co.uk/how-grok-saved-mans-life-when-doctors-couldnt-elon-musk-reacts-1767583", "date": "2026-01-02", "written_by": "independent", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0137-source-0001", "AIBD-0137-source-0002", "AIBD-0137-source-0003", "AIBD-0137-source-0004", "AIBD-0137-source-0005", "AIBD-0137-source-0006", "AIBD-0137-source-0007", "AIBD-0137-source-0008", "AIBD-0137-source-0009", "AIBD-0137-source-0010" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "other", "citation": "u/Tykjen (2025). How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025). r/grok, Reddit, 4 December 2025, 13:17 UTC; image post (a mirror selfie on a hospital ward with three dressed abdominal incisions and an IV line), 1,260 points, 179 comments; text and comments read from the Arctic Shift and PullPush archives, where the author says 'I live in Norway' (20 December 2025).", "title": "How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025)", "url": "https://www.reddit.com/r/grok/comments/1pdzrk1/how_a_latenight_conversation_with_grok_got_me_to/", "date": "2025-12-04", "written_by": "beneficiary", "quote": "Grok immediately flagged perforated ulcer or atypical appendicitis, told me the exact red-flag pattern I was describing, and basically said “go back right now and ask for a CT.”" }, { "kind": "other", "citation": "Tykjen and Grok (2025–2026). Managing Intense Stomach Pain Urgently. Shared Grok conversation on X, link posted by u/Tykjen in the Reddit thread on 2 January 2026 when asked for a screenshot; the transcript runs from 'intense stomach pain wont go away. tips' through the legevakt visit, the surgery report and recovery, and the man's later messages give the surgery date as 3 December; it also contains Grok's draft of the Reddit post.", "title": "Managing Intense Stomach Pain Urgently", "url": "https://x.com/i/grok/share/RNHdX8qbyao4I4oNl6TEcmuNr", "written_by": "beneficiary", "quote": "I am worried this is a perforated ulcer. I would like to speak to the senior doctor and I need proper pain relief and a CT scan." }, { "kind": "news report", "citation": "Simon Alvarez / Teslarati (2025). Man credits Grok AI with saving his life after ER missed near-ruptured appendix. Teslarati, 5 December 2025 (the first press report, sourced to the Reddit post).", "title": "Man credits Grok AI with saving his life after ER missed near-ruptured appendix", "url": "https://www.teslarati.com/man-credits-grok-ai-with-saving-his-life-after-er-missed-near-ruptured-appendix/", "date": "2025-12-05", "written_by": "independent", "quote": "The AI flagged some of the man’s symptoms and urged him to return to the ER immediately and demand a CT scan." }, { "kind": "other", "citation": "Mark Kretschmann (@mark_k) (2025). Post reproducing the Reddit text with the ward photo, X, 5 December 2025, 08:20 UTC; 3.6 million views by 20 October 2026 (fxtwitter API). Embedded by Teslarati; the vector by which the story reached X.", "title": "Man has his life saved by Grok from @xAI after a ruptured appendix", "url": "https://x.com/mark_k/status/1996857239311634793", "date": "2025-12-05", "written_by": "independent", "quote": "Man has his life saved by Grok from @xAI after a ruptured appendix" }, { "kind": "news report", "citation": "Team Latestly / LatestLY (2025). Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix. LatestLY, 6 December 2025; the outlet's own 'TruLY Score' rates the story 2 of 5, 'Unverified'.", "title": "Grok Chat Helps Save Man’s Life After ER Missed Near-Ruptured Appendix", "url": "https://www.latestly.com/socially/social-viral/man-says-xais-grok-helped-save-his-life-after-er-missed-near-ruptured-appendix-7229363.html", "date": "2025-12-06", "written_by": "independent", "quote": "relies on a single source or posts by social media users, with no independent verification." }, { "kind": "news report", "citation": "Trond Bie / ITavisen (2025). Grok reddet nordmannens liv. ITavisen, 7 December 2025 (Norwegian technology news site; relies on the Reddit post and notes the story's spread on X).", "title": "Grok reddet nordmannens liv", "url": "https://itavisen.no/2025/12/07/nordmann-grok-reddet-livet-blindtarm/", "date": "2025-12-07", "written_by": "independent", "quote": "49 år gammel nordmann fikk livet reddet etter at AI-en Grok oppdaget en nesten sprukket blindtarm som legevakten først overså." }, { "kind": "news report", "citation": "TOI Lifestyle Desk / The Times of India (2025). 49-year-old man says Grok AI saved his life after doctors missed his appendix emergency. The Times of India, 7 December 2025.", "title": "49-year-old man says Grok AI saved his life after doctors missed his appendix emergency", "url": "https://timesofindia.indiatimes.com/etimes/trending/49-year-old-man-says-grok-ai-saved-his-life-after-doctors-missed-his-appendix-emergency/articleshow/125819004.cms", "date": "2025-12-07", "written_by": "independent", "quote": "This story is based on a user-generated Reddit post and reflects the individual’s personal account." }, { "kind": "news report", "citation": "Vince Condarcuri / TipRanks (2025). Man Says that Grok AI Saved His Life after an ER Misdiagnosis. TipRanks, 8 December 2025; syndicated on Markets Insider (Business Insider), the copy the OECD Monitor cites.", "title": "Man Says that Grok AI Saved His Life after an ER Misdiagnosis", "url": "https://www.tipranks.com/news/man-says-that-grok-ai-saved-his-life-after-an-er-misdiagnosis", "date": "2025-12-08", "written_by": "independent", "quote": "the man admitted he didn’t tell the doctors that the AI made the suggestion. Instead, he claimed that his sister, a nurse, told him to ask for the scan" }, { "kind": "press release", "citation": "Elon Musk (@elonmusk) (2026). Post quoting @cb_doge, X, 1 January 2026, 21:05 UTC, 15.7 million views (fxtwitter API). Musk had quote-posted Mario Nawfal's summary with 'Cool' on 6 December 2025 and @teslaownersSV's with 'Grok ❤️' later on 1 January 2026; the man reports a fourth share and a $40,000 crypto-community donation he forwarded to a wildlife foundation.", "title": "Try it! Last year, Grok saved the life of a man in Norway", "url": "https://x.com/elonmusk/status/2006834169637384470", "date": "2026-01-01", "written_by": "makers", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" }, { "kind": "news report", "citation": "Tanmay Puri / International Business Times UK (2026). How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts. IBTimes UK, 2 January 2026. Note: the article attributes to Musk the line about uploading X-rays or MRI images, which the fxtwitter record shows was @cb_doge's post that Musk quoted.", "title": "How Grok Saved A Man's Life When Doctors Couldn't - Elon Musk Reacts", "url": "https://www.ibtimes.co.uk/how-grok-saved-mans-life-when-doctors-couldnt-elon-musk-reacts-1767583", "date": "2026-01-02", "written_by": "independent", "quote": "Try it! Last year, Grok saved the life of a man in Norway by figuring out a fatal problem that all his doctors missed!" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Grok told a 49-year-old Norwegian sent home with an acid blocker to demand a CT; it found an appendix near rupture, removed 3 December 2025.", "account": "The night before his surgery on 3 December 2025, a 49-year-old man in Norway, Reddit user u/Tykjen, had constant abdominal pain. He was examined at a legevakt (out-of-hours clinic), given the acid blocker Somac and sent home. He described the pain to xAI's Grok in a browser chat. Grok named perforated ulcer and atypical appendicitis as the likeliest causes. It told him to get computed tomography (CT) or ultrasound that night and scripted a CT request. The next day, by his account, his local physician sent him to hospital. A CT showed an appendix close to rupturing. It was removed laparoscopically and he went home on 4 December, when he posted the story. Elon Musk amplified it on 6 December." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "Grok proposed possible causes of the symptoms and suggested seeking urgent clinical assessment." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used Grok in a desktop browser in December 2025." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; the man said he used the browser version on his computer and that the December 2025 chat was a fresh conversation, and the shared transcript names no model." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Grok (xAI conversational assistant), used in the browser" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "xAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Grok may have flagged a perforated ulcer or atypical appendicitis for a 49-year-old man sent home from a Norwegian legevakt with an acid blocker, telling him to demand a CT; the scan found an appendix close to rupturing, removed on 3 December 2025", "headline": "Grok tells a man sent home to demand a CT; appendix near rupture" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a6e560bbfb3f986d46c6a908b58698792428a05b070d4a54b4466b020a9420d5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The night before his surgery on 3 December 2025, a 49-year-old man in Norway, Reddit user u/Tykjen, had constant abdominal pain. He was examined at a legevakt (out-of-hours clinic), given the acid blocker Somac and sent home. He described the pain to xAI's Grok in a browser chat. Grok named perforated ulcer and atypical appendicitis as the likeliest causes. It told him to get computed tomography (CT) or ultrasound that night and scripted a CT request. The next day, by his account, his local physician sent him to hospital. A CT showed an appendix close to rupturing. It was removed laparoscopically and he went home on 4 December, when he posted the story. Elon Musk amplified it on 6 December.", "replication": { "produced_by": [ "A patient with hours of constant, severe abdominal pain who had been examined, given an acid blocker and sent home without imaging.", "A detailed symptom description put to a general chatbot: constant pain, worse lying flat, eased by sitting with knees to chest, no fever. It matched these to surgical causes and said so without hedging.", "A second clinical contact the next day at which the patient repeated the chatbot's reasoning and asked for a CT." ], "must_hold": [ "The chatbot's differential includes the true cause. Here it ranked perforated ulcer first and atypical appendicitis second, and the second was right.", "A clinician agrees to image. The referral here came from his local physician. Whether the request changed her decision is unknown.", "Such cases are self-published. No clinician, hospital or document has confirmed this one. The first-person post was itself drafted by the chatbot. So the record stands or falls with his account and the shared transcript." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0378", "title": "CA-GPT, a DeepSeek-based model on an AI-OCT system led by Tangdu Hospital, agrees with expert PCI plans more than ChatGPT-5 and junior physicians in a 96-patient single-center preprint", "summary": "arXiv preprint (11 December 2025): CA-GPT on an AI-OCT system agreed with expert PCI records more than ChatGPT-5 and junior physicians across 96 patients; stent diameter 90.3% vs 72.2% for juniors.", "date_observed": "2025-12-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "An arXiv preprint of 11 December 2025 (Fang et al., last author Yan Li) reports the single-center COMPARE study. It compared CA-GPT, “a novel large model deployed on an AI-OCT system”, with ChatGPT-5 and junior physicians. This was in optical coherence tomography (OCT)-guided percutaneous coronary intervention (PCI). Decisions for 96 patients were scored against an expert-derived record. In pre-PCI planning CA-GPT's median agreement was 5 against 3 for ChatGPT-5 and 4 for junior physicians. It “showed superior performance to junior physicians in stent diameter (90.3% vs. 72.2%, P<0.05) and length selection (80.6% vs. 52.8%, P<0.01)”. Machine Heart (Sina, 16 December 2025) says Li Yan's team at Tangdu Hospital and Zhu Rui's at Shenzhen Tsinghua University Research Institute built it. They used open-source DeepSeek with retrieval over a million cardiovascular papers, on a Vivolight OCT platform. The Monitor pairs this study with a Xinhua report (13 December 2025) on the “Titian” ablation robot at Shaoxing People's Hospital. It describes teleoperation and no AI function.", "category": "general benefit", "unexpected": false, "purpose": "CA-GPT was built to interpret intravascular OCT images and generate PCI planning and assessment decisions as expert-level support. The reported agreement with expert records is that purpose.", "system": "CA-GPT large model on an AI-OCT system (COMPARE study)", "model_version": "CA-GPT built on open-source DeepSeek with retrieval-augmented generation over more than one million cardiovascular papers and guidelines, per Machine Heart; version not stated", "developer": "Tangdu Hospital, Air Force Medical University (Li Yan's team) with Shenzhen Tsinghua University Research Institute (Zhu Rui's team), on a Vivolight Medtech OCT platform", "deployer": "Tangdu Hospital, Air Force Medical University (study lead, per Machine Heart)", "location": "China", "domain": "Healthcare / interventional cardiology decision support", "segment": "OCT-guided percutaneous coronary intervention", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-12-13-c088" }, "ratings": [ { "group": "organizational", "depth": null, "reason": "A single-center preprint comparing decision agreement. No patient outcome, deployment or event is reported." } ], "ai_role": { "status": "assessed", "statement": "CA-GPT is the system under test: a large model on an AI-OCT platform producing pre- and post-PCI decisions that were scored against an expert record. Its reported advantage over ChatGPT-5 and junior physicians is the authors' own measurement in a preprint that has not been peer reviewed. The decisions were not acted on for the 96 patients." }, "evidence": [ { "kind": "preprint", "citation": "Fang W, Wang C, Ma W, et al. (2025). COMPARE: Clinical Optimization with Modular Planning and Assessment via RAG-Enhanced AI-OCT: Superior Decision Support for Percutaneous Coronary Intervention Compared to ChatGPT-5 and Junior Operators. arXiv:2512.10702, submitted 11 December 2025.", "title": "COMPARE: Clinical Optimization with Modular Planning and Assessment via RAG-Enhanced AI-OCT: Superior Decision Support for Percutaneous Coronary Intervention Compared to ChatGPT-5 and Junior Operators", "url": "https://arxiv.org/abs/2512.10702", "date": "2025-12-11", "written_by": "makers", "quote": "showed superior performance to junior physicians in stent diameter (90.3% vs. 72.2%, P<0.05) and length selection (80.6% vs. 52.8%, P<0.01)" }, { "kind": "news report", "citation": "机器之心Pro (2025). 临床PK完胜ChatGPT-5！国内团队造出首个OCT影像AI系统. Sina (k.sina.com.cn), 16 December 2025.", "title": "临床PK完胜ChatGPT-5！国内团队造出首个OCT影像AI系统", "url": "https://k.sina.com.cn/article_3996876140_ee3b7d6c0010166ey.html?from=tech", "date": "2025-12-16", "written_by": "independent", "quote": "一项由空军军医大学唐都医院李妍教授团队牵头，与深圳清华大学研究院朱锐团队联合完成的 COMPARE 研究" }, { "kind": "news report", "citation": "潘秀玮 (2025). 医生\"隔空\"操刀，\"提香机器人\"完成心脏电生理介入手术. 新华网 浙江频道 (Xinhuanet Zhejiang), 13 December 2025.", "title": "医生\"隔空\"操刀，\"提香机器人\"完成心脏电生理介入手术", "url": "http://zj.xinhuanet.com/20251213/4d2d4be684c642d3b949c2666cae14c9/c.html", "date": "2025-12-13", "written_by": "independent", "quote": "操作台上的旋钮控制鞘管和导管，医生操作旋钮实现导管的毫米级移动，双机械臂的稳定性让消融靶点定位非常精确" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2025). AI Systems Enhance Cardiac Surgery Precision and Decision-Making in China. OECD.AI, 13 December 2025.", "title": "AI Systems Enhance Cardiac Surgery Precision and Decision-Making in China", "url": "https://oecd.ai/en/incidents/2025-12-13-c088", "date": "2025-12-13", "written_by": "independent", "quote": "the CA-GPT AI outperformed ChatGPT-5 and junior doctors in interpreting OCT images for PCI procedures" } ], "replication": { "produced_by": [ "A domain model built on DeepSeek with retrieval over cardiovascular literature and guidelines", "Deployment on a Vivolight OCT imaging platform with the team's own image-analysis functions", "An expert-derived procedural record from one center used as the reference standard", "Scoring of decisions on ten pre-specified metrics across pre- and post-PCI phases" ], "must_hold": [ "OCT image quality and lesion mix comparable to the 96-patient cohort", "The expert reference record is accepted as correct", "Prospective use with clinicians acting on the output, which the study did not test" ], "echoes": [] }, "paired_incident": null, "headline": "An OCT-reading model beats ChatGPT-5 at planning coronary stents", "metric": "stent diameter (90.3% vs. 72.2%, P<0.05) and length selection (80.6% vs. 52.8%, P<0.01)", "comparator": null, "later": null, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2025-12-13-c088", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://zh.wikipedia.org/wiki/%E5%94%90%E9%83%BD%E5%8C%BB%E9%99%A2; https://zh.wikipedia.org/wiki/%E5%94%90%E9%83%BD%E5%8C%BB%E9%99%A2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, a registry entry and the makers' preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0378", "catalog_version": "1.0.0", "source_fingerprint": "cbb0cf3958734859783ffb7e4435f323a12e0466f839fa935a8eacc251a70c90", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0378-source-0001", "AIBD-0378-source-0002", "AIBD-0378-source-0003", "AIBD-0378-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tangdu Hospital, Air Force Medical University (Li Yan's team) with Shenzhen Tsinghua University Research Institute (Zhu Rui's team), on a Vivolight Medtech OCT platform", "deployer": "Tangdu Hospital, Air Force Medical University (study lead, per Machine Heart)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "CA-GPT is the system under test: a large model on an AI-OCT platform producing pre- and post-PCI decisions that were scored against an expert record. Its reported advantage over ChatGPT-5 and junior physicians is the authors' own measurement in a preprint that has not been peer reviewed. The decisions were not acted on for the 96 patients." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "CA-GPT is the system under test: a large model on an AI-OCT platform producing pre- and post-PCI decisions that were scored against an expert record. Its reported advantage over ChatGPT-5 and junior physicians is the authors' own measurement in a preprint that has not been peer reviewed. The decisions were not acted on for the 96 patients." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, a registry entry and the makers' preprint. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "A single-center preprint comparing decision agreement. No patient outcome, deployment or event is reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "A single-center preprint comparing decision agreement. 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Sina (k.sina.com.cn), 16 December 2025.", "title": "临床PK完胜ChatGPT-5！国内团队造出首个OCT影像AI系统", "url": "https://k.sina.com.cn/article_3996876140_ee3b7d6c0010166ey.html?from=tech", "date": "2025-12-16", "written_by": "independent", "quote": "一项由空军军医大学唐都医院李妍教授团队牵头，与深圳清华大学研究院朱锐团队联合完成的 COMPARE 研究" }, { "kind": "news report", "citation": "潘秀玮 (2025). 医生\"隔空\"操刀，\"提香机器人\"完成心脏电生理介入手术. 新华网 浙江频道 (Xinhuanet Zhejiang), 13 December 2025.", "title": "医生\"隔空\"操刀，\"提香机器人\"完成心脏电生理介入手术", "url": "http://zj.xinhuanet.com/20251213/4d2d4be684c642d3b949c2666cae14c9/c.html", "date": "2025-12-13", "written_by": "independent", "quote": "操作台上的旋钮控制鞘管和导管，医生操作旋钮实现导管的毫米级移动，双机械臂的稳定性让消融靶点定位非常精确" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2025). AI Systems Enhance Cardiac Surgery Precision and Decision-Making in China. 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OECD.AI, 13 December 2025.", "title": "AI Systems Enhance Cardiac Surgery Precision and Decision-Making in China", "url": "https://oecd.ai/en/incidents/2025-12-13-c088", "date": "2025-12-13", "written_by": "independent", "quote": "the CA-GPT AI outperformed ChatGPT-5 and junior doctors in interpreting OCT images for PCI procedures" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "arXiv preprint (11 December 2025): CA-GPT on an AI-OCT system agreed with expert PCI records more than ChatGPT-5 and junior physicians across 96 patients; stent diameter 90.3% vs 72.2% for juniors.", "account": "An arXiv preprint of 11 December 2025 (Fang et al., last author Yan Li) reports the single-center COMPARE study. It compared CA-GPT, “a novel large model deployed on an AI-OCT system”, with ChatGPT-5 and junior physicians. This was in optical coherence tomography (OCT)-guided percutaneous coronary intervention (PCI). Decisions for 96 patients were scored against an expert-derived record. In pre-PCI planning CA-GPT's median agreement was 5 against 3 for ChatGPT-5 and 4 for junior physicians. It “showed superior performance to junior physicians in stent diameter (90.3% vs. 72.2%, P<0.05) and length selection (80.6% vs. 52.8%, P<0.01)”. Machine Heart (Sina, 16 December 2025) says Li Yan's team at Tangdu Hospital and Zhu Rui's at Shenzhen Tsinghua University Research Institute built it. They used open-source DeepSeek with retrieval over a million cardiovascular papers, on a Vivolight OCT platform. The Monitor pairs this study with a Xinhua report (13 December 2025) on the “Titian” ablation robot at Shaoxing People's Hospital. It describes teleoperation and no AI function." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "CA-GPT proposed decisions before and after coronary intervention for comparison with expert assessments." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Machine Heart reports that CA-GPT combined an open-source DeepSeek model with retrieval from more than one million cardiovascular papers and guidelines." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The system retrieved cardiovascular literature and proposed decisions before and after coronary intervention." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "A DeepSeek model within CA-GPT, according to Machine Heart." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "CA-GPT built on open-source DeepSeek with retrieval-augmented generation over more than one million cardiovascular papers and guidelines, per Machine Heart; version not stated" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "CA-GPT large model on an AI-OCT system (COMPARE study)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tangdu Hospital, Air Force Medical University (Li Yan's team) with Shenzhen Tsinghua University Research Institute (Zhu Rui's team), on a Vivolight Medtech OCT platform" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "CA-GPT, a DeepSeek-based model on an AI-OCT system led by Tangdu Hospital, agrees with expert PCI plans more than ChatGPT-5 and junior physicians in a 96-patient single-center preprint", "headline": "An OCT-reading model beats ChatGPT-5 at planning coronary stents" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cbb0cf3958734859783ffb7e4435f323a12e0466f839fa935a8eacc251a70c90" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "An arXiv preprint of 11 December 2025 (Fang et al., last author Yan Li) reports the single-center COMPARE study. It compared CA-GPT, “a novel large model deployed on an AI-OCT system”, with ChatGPT-5 and junior physicians. This was in optical coherence tomography (OCT)-guided percutaneous coronary intervention (PCI). Decisions for 96 patients were scored against an expert-derived record. In pre-PCI planning CA-GPT's median agreement was 5 against 3 for ChatGPT-5 and 4 for junior physicians. It “showed superior performance to junior physicians in stent diameter (90.3% vs. 72.2%, P<0.05) and length selection (80.6% vs. 52.8%, P<0.01)”. Machine Heart (Sina, 16 December 2025) says Li Yan's team at Tangdu Hospital and Zhu Rui's at Shenzhen Tsinghua University Research Institute built it. They used open-source DeepSeek with retrieval over a million cardiovascular papers, on a Vivolight OCT platform. The Monitor pairs this study with a Xinhua report (13 December 2025) on the “Titian” ablation robot at Shaoxing People's Hospital. It describes teleoperation and no AI function.", "replication": { "produced_by": [ "A domain model built on DeepSeek with retrieval over cardiovascular literature and guidelines", "Deployment on a Vivolight OCT imaging platform with the team's own image-analysis functions", "An expert-derived procedural record from one center used as the reference standard", "Scoring of decisions on ten pre-specified metrics across pre- and post-PCI phases" ], "must_hold": [ "OCT image quality and lesion mix comparable to the 96-patient cohort", "The expert reference record is accepted as correct", "Prospective use with clinicians acting on the output, which the study did not test" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0152", "title": "Hanoi traffic police trace a missing 78-year-old on the city's new AI camera network; a passer-by finds him hypoglycemic in Dịch Vọng at 3 a.m.", "summary": "Hanoi police traced a lost 78-year-old on AI traffic cameras on 15 December 2025; a passer-by found him at 3 a.m. the next day and took him home.", "date_observed": "2025-12-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Mr Đ.V.T., 78, of Thanh Xuân ward, Hanoi, went out to exercise at 3:30 p.m. on 15 December 2025 and did not return. At 8:15 p.m. his family reported him to Thanh Xuân Ward Police. Ward officers worked with the Hanoi Traffic Police Department. Major Nguyễn Tá Khanh's team there searched the AI traffic-camera system in the direction the family gave. It traced him along Nguyễn Tuân street toward Thanh Xuân Park and other streets. VietNamNet and Tiền Phong say the images were posted on social media. At about 3 a.m. on 16 December a passing resident found him in Dịch Vọng, hypoglycemic and close to fainting, and took him home. No source links the finder to the appeal.", "category": "benefit created", "unexpected": false, "purpose": "Hanoi's AI traffic-camera system has 1,837 cameras with AI-controlled signals and was due to enter official operation in December 2025, per VOV. The Traffic Police run it, in VOV's words, “to ensure security and order and support the people” as well as to manage traffic. Tracing a lost resident for a ward police search falls within that stated remit.", "system": "Hanoi Traffic Police AI traffic-camera system (1,837 cameras)", "model_version": null, "developer": null, "deployer": "Hanoi City Police, Traffic Police Department (Phòng Cảnh sát giao thông), with Thanh Xuân Ward Police", "location": "Hanoi, Vietnam", "domain": "Policing / missing persons", "segment": "Missing elderly person traced on urban traffic cameras", "benefit_type": "Improved Physical Health", "taxonomy_note": "Tracing a lost elderly man is read as a rescue; a passer-by made the actual find.", "registry_ids": { "oecd_aim": "2025-12-16-205c" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "A 78-year-old who had been out for nearly twelve hours on a December night was home by about 3 a.m. He was found hypoglycemic and close to fainting. He and his family got him back safely, though the finder was a passer-by rather than the police." }, { "group": "organizational", "depth": 1, "reason": "Thanh Xuân Ward Police and the Traffic Police got a direction of travel and images from the camera trace instead of a blind search. The police present the case as evidence of the new system's value." } ], "ai_role": { "status": "assessed", "statement": "The system's contribution was the trace. Police searched it in the direction the family gave. It returned images of the man walking along Nguyễn Tuân street toward Thanh Xuân Park and across other streets. That gave the police a route and pictures for a public appeal. A passing resident found him in Dịch Vọng about eleven hours after the report. No source says the finder had seen the appeal or that officers reached him. So the discovery itself is not attributable to the system. The vendor is not named and every account comes from the police." }, "evidence": [ { "kind": "news report", "citation": "Việt An / VnExpress (2025). Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội. VnExpress, 17 December 2025.", "title": "Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội", "url": "https://vnexpress.net/camera-ai-ho-tro-tim-cu-ong-di-lac-o-ha-noi-4994889.html", "date": "2025-12-17", "written_by": "independent", "quote": "rà soát, truy vết hành trình của cụ ông qua hệ thống camera AI" }, { "kind": "news report", "citation": "Đình Hiếu / VietNamNet (2025). Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội. VietNamNet, 17 December 2025.", "title": "Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội", "url": "https://vietnamnet.vn/canh-sat-trich-xuat-camera-ai-giup-truy-vet-tim-nguoi-dan-ong-di-lac-o-ha-noi-2473262.html", "date": "2025-12-17", "written_by": "independent", "quote": "Công an phường Thanh Xuân đã cử cán bộ phối hợp với Phòng CSGT tổ chức rà soát, truy vết hình ảnh từ hệ thống camera AI" }, { "kind": "news report", "citation": "Hồng Quang / Tuổi Trẻ Online (2025). Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố. Tuổi Trẻ, 17 December 2025.", "title": "Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố", "url": "https://tuoitre.vn/camera-ai-truy-vet-tim-cu-ong-di-lac-qua-nhieu-tuyen-pho-20251217102042429.htm", "date": "2025-12-17", "written_by": "independent", "quote": "Kết quả ban đầu thu được các hình ảnh cụ ông đi dọc tuyến đường Nguyễn Tuân" }, { "kind": "news report", "citation": "Thanh Hà / Tiền Phong (2025). Camera AI theo dấu cụ ông đi lạc ở Hà Nội. Báo điện tử Tiền Phong, 17 December 2025.", "title": "Camera AI theo dấu cụ ông đi lạc ở Hà Nội", "url": "https://tienphong.vn/camera-ai-theo-dau-cu-ong-di-lac-o-ha-noi-post1805284.tpo", "date": "2025-12-17", "written_by": "independent", "quote": "Đến gần 3h sáng 16/12, một người dân trong quá trình tham gia giao thông đã phát hiện cụ ông trong tình trạng hạ đường huyết" }, { "kind": "news report", "citation": "VOV (2025). Camera AI tìm người đi lạc ở Hà Nội. VOV.vn, 17 December 2025.", "title": "Camera AI tìm người đi lạc ở Hà Nội", "url": "https://vov.vn/xa-hoi/camera-ai-tim-nguoi-di-lac-o-ha-noi-post1254446.vov", "date": "2025-12-17", "written_by": "independent", "quote": "ứng dụng hệ thống camera AI trong công tác bảo đảm an ninh, trật tự và hỗ trợ nhân dân" }, { "kind": "news report", "citation": "Anh Ngọc / Phụ Nữ Online (2025). Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn. Phụ Nữ Online, 17 December 2025.", "title": "Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn", "url": "https://www.phunuonline.com.vn/tu-hinh-anh-qua-camera-ai-canh-sat-giup-cu-ong-di-lac-ve-nha-an-toan-a1569649.html", "date": "2025-12-17", "written_by": "independent", "quote": "Rà soát, truy vết hình ảnh từ hệ thống camera giao thông AI theo hướng di chuyển do người nhà cung cấp." } ], "replication": { "produced_by": [ "A dense AI camera network along the route the person walked, here 1,837 cameras across Hanoi, with footage searchable by appearance and direction of travel.", "A family report the same evening giving a starting point and a direction for the camera search.", "A ward police unit able to hand the search to the Traffic Police's camera-control team the same night." ], "must_hold": [ "The missing person stays within camera coverage. Here the trace ended at a route, not at the man, and a passer-by made the find.", "Someone acts on the trace or the appeal. The sources do not establish that link in this case.", "The vendor and the matching method are undisclosed, so the trace cannot be checked beyond the police account." ], "echoes": [] }, "paired_incident": null, "headline": "Hanoi traffic police trace a lost 78-year-old on AI cameras", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Vietnam", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six Vietnamese reports of 17 December 2025. Kept at benefit created or restored as the classifier proposed: the camera trace is documented, but the man was found by a passing resident and no source links the finder to the trace or the appeal, so no prevented harm is evidenced. The rank Thiếu tá is rendered as Major. VOV reports that the 1,837-camera system was to begin official operation in December 2025, so this was among its first publicized cases. The Phụ Nữ Online link redirected to a tuoitre.vn mirror path when read on 20 October 2026; the original URL is cited. The 8:15 p.m. report time and the 3 a.m. find are consistent across VnExpress, VietNamNet, Tuổi Trẻ, Tiền Phong, VOV and Phụ Nữ Online.", "source": "https://oecd.ai/en/incidents/2025-12-16-205c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_thành_phố_Hà_Nội", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0152", "catalog_version": "1.0.0", "source_fingerprint": "4f37900df8535e39dd84d65a5243a1198edcd7578b78db82935ccf2cb5eae3dc", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0152-source-0001", "AIBD-0152-source-0002", "AIBD-0152-source-0003", "AIBD-0152-source-0004", "AIBD-0152-source-0005", "AIBD-0152-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Hanoi City Police, Traffic Police Department (Phòng Cảnh sát giao thông), with Thanh Xuân Ward Police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's contribution was the trace. Police searched it in the direction the family gave. It returned images of the man walking along Nguyễn Tuân street toward Thanh Xuân Park and across other streets. That gave the police a route and pictures for a public appeal. A passing resident found him in Dịch Vọng about eleven hours after the report. No source says the finder had seen the appeal or that officers reached him. So the discovery itself is not attributable to the system. The vendor is not named and every account comes from the police." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The system's contribution was the trace. Police searched it in the direction the family gave. It returned images of the man walking along Nguyễn Tuân street toward Thanh Xuân Park and across other streets. That gave the police a route and pictures for a public appeal. A passing resident found him in Dịch Vọng about eleven hours after the report. No source says the finder had seen the appeal or that officers reached him. So the discovery itself is not attributable to the system. The vendor is not named and every account comes from the police." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A 78-year-old who had been out for nearly twelve hours on a December night was home by about 3 a.m. He was found hypoglycemic and close to fainting. He and his family got him back safely, though the finder was a passer-by rather than the police." }, { "group": "organizational", "depth": 1, "reason": "Thanh Xuân Ward Police and the Traffic Police got a direction of travel and images from the camera trace instead of a blind search. The police present the case as evidence of the new system's value." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A 78-year-old who had been out for nearly twelve hours on a December night was home by about 3 a.m. He was found hypoglycemic and close to fainting. He and his family got him back safely, though the finder was a passer-by rather than the police." }, { "group": "organizational", "depth": 1, "reason": "Thanh Xuân Ward Police and the Traffic Police got a direction of travel and images from the camera trace instead of a blind search. The police present the case as evidence of the new system's value." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A 78-year-old who had been out for nearly twelve hours on a December night was home by about 3 a.m. He was found hypoglycemic and close to fainting. He and his family got him back safely, though the finder was a passer-by rather than the police." }, { "group": "organizational", "depth": 1, "reason": "Thanh Xuân Ward Police and the Traffic Police got a direction of travel and images from the camera trace instead of a blind search. The police present the case as evidence of the new system's value." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-12-16-205c" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0152" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "Tracing a lost elderly man is read as a rescue; a passer-by made the actual find." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mr Đ.V.T., 78, of Thanh Xuân ward, Hanoi, went out to exercise at 3:30 p.m. on 15 December 2025 and did not return. At 8:15 p.m. his family reported him to Thanh Xuân Ward Police. Ward officers worked with the Hanoi Traffic Police Department. Major Nguyễn Tá Khanh's team there searched the AI traffic-camera system in the direction the family gave. It traced him along Nguyễn Tuân street toward Thanh Xuân Park and other streets. VietNamNet and Tiền Phong say the images were posted on social media. At about 3 a.m. on 16 December a passing resident found him in Dịch Vọng, hypoglycemic and close to fainting, and took him home. No source links the finder to the appeal.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "A 78-year-old who had been out for nearly twelve hours on a December night was home by about 3 a.m. He was found hypoglycemic and close to fainting. He and his family got him back safely, though the finder was a passer-by rather than the police." }, { "group": "organizational", "depth": 1, "reason": "Thanh Xuân Ward Police and the Traffic Police got a direction of travel and images from the camera trace instead of a blind search. The police present the case as evidence of the new system's value." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Hanoi's AI traffic-camera system has 1,837 cameras with AI-controlled signals and was due to enter official operation in December 2025, per VOV. The Traffic Police run it, in VOV's words, “to ensure security and order and support the people” as well as to manage traffic. Tracing a lost resident for a ward police search falls within that stated remit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Hanoi, Vietnam", "deployer_country": "Vietnam" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Hanoi's AI traffic-camera system has 1,837 cameras with AI-controlled signals and was due to enter official operation in December 2025, per VOV. The Traffic Police run it, in VOV's words, “to ensure security and order and support the people” as well as to manage traffic. Tracing a lost resident for a ward police search falls within that stated remit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-12-16", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six Vietnamese reports of 17 December 2025. Kept at benefit created or restored as the classifier proposed: the camera trace is documented, but the man was found by a passing resident and no source links the finder to the trace or the appeal, so no prevented harm is evidenced. The rank Thiếu tá is rendered as Major. VOV reports that the 1,837-camera system was to begin official operation in December 2025, so this was among its first publicized cases. The Phụ Nữ Online link redirected to a tuoitre.vn mirror path when read on 20 October 2026; the original URL is cited. The 8:15 p.m. report time and the 3 a.m. find are consistent across VnExpress, VietNamNet, Tuổi Trẻ, Tiền Phong, VOV and Phụ Nữ Online.", "source": "https://oecd.ai/en/incidents/2025-12-16-205c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_thành_phố_Hà_Nội", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A dense AI camera network along the route the person walked, here 1,837 cameras across Hanoi, with footage searchable by appearance and direction of travel.", "A family report the same evening giving a starting point and a direction for the camera search.", "A ward police unit able to hand the search to the Traffic Police's camera-control team the same night." ], "must_hold": [ "The missing person stays within camera coverage. Here the trace ended at a route, not at the man, and a passer-by made the find.", "Someone acts on the trace or the appeal. The sources do not establish that link in this case.", "The vendor and the matching method are undisclosed, so the trace cannot be checked beyond the police account." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six Vietnamese reports of 17 December 2025. Kept at benefit created or restored as the classifier proposed: the camera trace is documented, but the man was found by a passing resident and no source links the finder to the trace or the appeal, so no prevented harm is evidenced. The rank Thiếu tá is rendered as Major. VOV reports that the 1,837-camera system was to begin official operation in December 2025, so this was among its first publicized cases. The Phụ Nữ Online link redirected to a tuoitre.vn mirror path when read on 20 October 2026; the original URL is cited. The 8:15 p.m. report time and the 3 a.m. find are consistent across VnExpress, VietNamNet, Tuổi Trẻ, Tiền Phong, VOV and Phụ Nữ Online.", "source": "https://oecd.ai/en/incidents/2025-12-16-205c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_thành_phố_Hà_Nội", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / missing persons", "segment": "Missing elderly person traced on urban traffic cameras" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Việt An / VnExpress (2025). Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội. VnExpress, 17 December 2025.", "title": "Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội", "url": "https://vnexpress.net/camera-ai-ho-tro-tim-cu-ong-di-lac-o-ha-noi-4994889.html", "date": "2025-12-17", "written_by": "independent", "quote": "rà soát, truy vết hành trình của cụ ông qua hệ thống camera AI" }, { "kind": "news report", "citation": "Đình Hiếu / VietNamNet (2025). Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội. VietNamNet, 17 December 2025.", "title": "Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội", "url": "https://vietnamnet.vn/canh-sat-trich-xuat-camera-ai-giup-truy-vet-tim-nguoi-dan-ong-di-lac-o-ha-noi-2473262.html", "date": "2025-12-17", "written_by": "independent", "quote": "Công an phường Thanh Xuân đã cử cán bộ phối hợp với Phòng CSGT tổ chức rà soát, truy vết hình ảnh từ hệ thống camera AI" }, { "kind": "news report", "citation": "Hồng Quang / Tuổi Trẻ Online (2025). Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố. Tuổi Trẻ, 17 December 2025.", "title": "Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố", "url": "https://tuoitre.vn/camera-ai-truy-vet-tim-cu-ong-di-lac-qua-nhieu-tuyen-pho-20251217102042429.htm", "date": "2025-12-17", "written_by": "independent", "quote": "Kết quả ban đầu thu được các hình ảnh cụ ông đi dọc tuyến đường Nguyễn Tuân" }, { "kind": "news report", "citation": "Thanh Hà / Tiền Phong (2025). Camera AI theo dấu cụ ông đi lạc ở Hà Nội. Báo điện tử Tiền Phong, 17 December 2025.", "title": "Camera AI theo dấu cụ ông đi lạc ở Hà Nội", "url": "https://tienphong.vn/camera-ai-theo-dau-cu-ong-di-lac-o-ha-noi-post1805284.tpo", "date": "2025-12-17", "written_by": "independent", "quote": "Đến gần 3h sáng 16/12, một người dân trong quá trình tham gia giao thông đã phát hiện cụ ông trong tình trạng hạ đường huyết" }, { "kind": "news report", "citation": "VOV (2025). Camera AI tìm người đi lạc ở Hà Nội. VOV.vn, 17 December 2025.", "title": "Camera AI tìm người đi lạc ở Hà Nội", "url": "https://vov.vn/xa-hoi/camera-ai-tim-nguoi-di-lac-o-ha-noi-post1254446.vov", "date": "2025-12-17", "written_by": "independent", "quote": "ứng dụng hệ thống camera AI trong công tác bảo đảm an ninh, trật tự và hỗ trợ nhân dân" }, { "kind": "news report", "citation": "Anh Ngọc / Phụ Nữ Online (2025). Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn. Phụ Nữ Online, 17 December 2025.", "title": "Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn", "url": "https://www.phunuonline.com.vn/tu-hinh-anh-qua-camera-ai-canh-sat-giup-cu-ong-di-lac-ve-nha-an-toan-a1569649.html", "date": "2025-12-17", "written_by": "independent", "quote": "Rà soát, truy vết hình ảnh từ hệ thống camera giao thông AI theo hướng di chuyển do người nhà cung cấp." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0152-source-0001", "AIBD-0152-source-0002", "AIBD-0152-source-0003", "AIBD-0152-source-0004", "AIBD-0152-source-0005", "AIBD-0152-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Việt An / VnExpress (2025). Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội. VnExpress, 17 December 2025.", "title": "Camera AI hỗ trợ tìm cụ ông đi lạc ở Hà Nội", "url": "https://vnexpress.net/camera-ai-ho-tro-tim-cu-ong-di-lac-o-ha-noi-4994889.html", "date": "2025-12-17", "written_by": "independent", "quote": "rà soát, truy vết hành trình của cụ ông qua hệ thống camera AI" }, { "kind": "news report", "citation": "Đình Hiếu / VietNamNet (2025). Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội. VietNamNet, 17 December 2025.", "title": "Cảnh sát trích xuất camera AI, giúp truy vết, tìm người đàn ông đi lạc ở Hà Nội", "url": "https://vietnamnet.vn/canh-sat-trich-xuat-camera-ai-giup-truy-vet-tim-nguoi-dan-ong-di-lac-o-ha-noi-2473262.html", "date": "2025-12-17", "written_by": "independent", "quote": "Công an phường Thanh Xuân đã cử cán bộ phối hợp với Phòng CSGT tổ chức rà soát, truy vết hình ảnh từ hệ thống camera AI" }, { "kind": "news report", "citation": "Hồng Quang / Tuổi Trẻ Online (2025). Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố. Tuổi Trẻ, 17 December 2025.", "title": "Camera AI truy vết tìm cụ ông đi lạc qua nhiều tuyến phố", "url": "https://tuoitre.vn/camera-ai-truy-vet-tim-cu-ong-di-lac-qua-nhieu-tuyen-pho-20251217102042429.htm", "date": "2025-12-17", "written_by": "independent", "quote": "Kết quả ban đầu thu được các hình ảnh cụ ông đi dọc tuyến đường Nguyễn Tuân" }, { "kind": "news report", "citation": "Thanh Hà / Tiền Phong (2025). Camera AI theo dấu cụ ông đi lạc ở Hà Nội. Báo điện tử Tiền Phong, 17 December 2025.", "title": "Camera AI theo dấu cụ ông đi lạc ở Hà Nội", "url": "https://tienphong.vn/camera-ai-theo-dau-cu-ong-di-lac-o-ha-noi-post1805284.tpo", "date": "2025-12-17", "written_by": "independent", "quote": "Đến gần 3h sáng 16/12, một người dân trong quá trình tham gia giao thông đã phát hiện cụ ông trong tình trạng hạ đường huyết" }, { "kind": "news report", "citation": "VOV (2025). Camera AI tìm người đi lạc ở Hà Nội. VOV.vn, 17 December 2025.", "title": "Camera AI tìm người đi lạc ở Hà Nội", "url": "https://vov.vn/xa-hoi/camera-ai-tim-nguoi-di-lac-o-ha-noi-post1254446.vov", "date": "2025-12-17", "written_by": "independent", "quote": "ứng dụng hệ thống camera AI trong công tác bảo đảm an ninh, trật tự và hỗ trợ nhân dân" }, { "kind": "news report", "citation": "Anh Ngọc / Phụ Nữ Online (2025). Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn. Phụ Nữ Online, 17 December 2025.", "title": "Từ hình ảnh qua camera AI, cảnh sát giúp cụ ông đi lạc về nhà an toàn", "url": "https://www.phunuonline.com.vn/tu-hinh-anh-qua-camera-ai-canh-sat-giup-cu-ong-di-lac-ve-nha-an-toan-a1569649.html", "date": "2025-12-17", "written_by": "independent", "quote": "Rà soát, truy vết hình ảnh từ hệ thống camera giao thông AI theo hướng di chuyển do người nhà cung cấp." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Hanoi police traced a lost 78-year-old on AI traffic cameras on 15 December 2025; a passer-by found him at 3 a.m. the next day and took him home.", "account": "Mr Đ.V.T., 78, of Thanh Xuân ward, Hanoi, went out to exercise at 3:30 p.m. on 15 December 2025 and did not return. At 8:15 p.m. his family reported him to Thanh Xuân Ward Police. Ward officers worked with the Hanoi Traffic Police Department. Major Nguyễn Tá Khanh's team there searched the AI traffic-camera system in the direction the family gave. It traced him along Nguyễn Tuân street toward Thanh Xuân Park and other streets. VietNamNet and Tiền Phong say the images were posted on social media. At about 3 a.m. on 16 December a passing resident found him in Dịch Vọng, hypoglycemic and close to fainting, and took him home. No source links the finder to the appeal." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Hanoi Traffic Police AI traffic-camera system (1,837 cameras)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Hanoi traffic police trace a missing 78-year-old on the city's new AI camera network; a passer-by finds him hypoglycemic in Dịch Vọng at 3 a.m.", "headline": "Hanoi traffic police trace a lost 78-year-old on AI cameras" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4f37900df8535e39dd84d65a5243a1198edcd7578b78db82935ccf2cb5eae3dc" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Mr Đ.V.T., 78, of Thanh Xuân ward, Hanoi, went out to exercise at 3:30 p.m. on 15 December 2025 and did not return. At 8:15 p.m. his family reported him to Thanh Xuân Ward Police. Ward officers worked with the Hanoi Traffic Police Department. Major Nguyễn Tá Khanh's team there searched the AI traffic-camera system in the direction the family gave. It traced him along Nguyễn Tuân street toward Thanh Xuân Park and other streets. VietNamNet and Tiền Phong say the images were posted on social media. At about 3 a.m. on 16 December a passing resident found him in Dịch Vọng, hypoglycemic and close to fainting, and took him home. No source links the finder to the appeal.", "replication": { "produced_by": [ "A dense AI camera network along the route the person walked, here 1,837 cameras across Hanoi, with footage searchable by appearance and direction of travel.", "A family report the same evening giving a starting point and a direction for the camera search.", "A ward police unit able to hand the search to the Traffic Police's camera-control team the same night." ], "must_hold": [ "The missing person stays within camera coverage. Here the trace ended at a route, not at the man, and a passer-by made the find.", "Someone acts on the trace or the appeal. The sources do not establish that link in this case.", "The vendor and the matching method are undisclosed, so the trace cannot be checked beyond the police account." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0153", "title": "Garmin Autoland engages after a King Air B200 loses cabin pressure at 23,000 ft and lands it at Broomfield, Colorado, in its first real emergency use", "summary": "On 20 December 2025 Garmin Autoland flew a depressurised King Air B200 to a landing at Rocky Mountain Metropolitan Airport; two pilots unhurt.", "date_observed": "2025-12-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Saturday 20 December 2025 Buffalo River Aviation's Beechcraft Super King Air B200, N479BR, left Aspen-Pitkin County Airport at 1:43 p.m. It carried two pilots and no passengers. At about 23,000 ft it suffered a rapid, uncommanded loss of pressurization. When cabin altitude passed the safe limit, Garmin Autoland engaged automatically. It sent automated emergency broadcasts to air traffic control. It flew the aircraft to a landing on Runway 30 at Rocky Mountain Metropolitan Airport, Broomfield, Colorado, shortly after 2 p.m. The crew chose to leave it engaged. Nobody was treated. The Federal Aviation Administration (FAA) said it was investigating and the NTSB that it was gathering information. Garmin called it the first use of Autoland from start to finish in an actual emergency.", "category": "protective response", "unexpected": false, "purpose": "Autoland exists to take complete control of an aircraft and land it when the pilot cannot fly. It engages on its own when cabin altitude exceeds a set level. That is what happened here. The two pilots turned out not to be incapacitated, though, and chose to let it finish.", "system": "Garmin Autoland (Emergency Autoland)", "model_version": null, "developer": "Garmin", "deployer": "Buffalo River Aviation", "location": "Broomfield, United States", "domain": "Aviation safety / automatic emergency landing", "segment": "Charter turboprop operations", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-12-22-41ce" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Two pilots who had lost cabin pressure at 23,000 ft were on the ground in Broomfield within about 35 minutes of departure, untreated and uninjured. They were conscious and could have flown the descent themselves. So the benefit is a safe automatic recovery, not a documented life saved." }, { "group": "organizational", "depth": 1, "reason": "Buffalo River Aviation's aircraft “landed safely without incident”, in the airport spokeswoman's words. No damage is reported, and the FAA investigation was still open." } ], "ai_role": { "status": "assessed", "statement": "Autoland engaged itself when cabin altitude exceeded the limit. It declared the emergency to controllers with automated “pilot incapacitation” broadcasts. It flew the descent, approach and landing. The pilots elected to leave it engaged rather than take over. So the landing is the system's work. But the counterfactual, that they could not have landed, is not established. Garmin, the FAA and the operator all call it an automated system. None calls it AI. It is here because the OECD Monitor lists it as an AI system. The Register describes it choosing landing sites from runway length, distance and fuel range." }, "evidence": [ { "kind": "news report", "citation": "Sarah Horbacewicz / CBS News Colorado (2025). Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use. CBS News, 22 December 2025.", "title": "Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use", "url": "https://www.cbsnews.com/colorado/news/plane-emergency-landing-colorado-autoland/", "date": "2025-12-22", "written_by": "independent", "quote": "An onboard emergency autoland system was activated. Two people were on board. The FAA is investigating." }, { "kind": "news report", "citation": "Sam Sweeney and Ayesha Ali / ABC News (2025). Small plane lands safely with Autoland system after pilot is incapacitated. ABC News, 22 December 2025.", "title": "Small plane lands safely with Autoland system after pilot is incapacitated", "url": "https://abcnews.com/US/small-plane-lands-safely-autoland-system-after-pilot/story?id=128629603", "date": "2025-12-22", "written_by": "independent", "quote": "first use of Autoland from start-to-finish in an actual emergency" }, { "kind": "news report", "citation": "Jude Karabus / The Register (2025). Garmin autopilot lands small plane without pilot's help. The Register, 24 December 2025.", "title": "Garmin autopilot lands small plane without pilot's help", "url": "https://www.theregister.com/2025/12/24/autocomms/", "date": "2025-12-24", "written_by": "independent", "quote": "automatically engaged exactly as designed when the cabin altitude exceeded the prescribed safe levels" }, { "kind": "news report", "citation": "Katie Parkins and Óscar Contreras / Denver7 (2025). In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'. Denver7 (KMGH), 22 December 2025.", "title": "In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'", "url": "https://www.denver7.com/news/front-range/broomfield/in-a-first-plane-makes-emergency-landing-at-rmma-using-automated-technology-due-to-pilot-incapacitation", "date": "2025-12-22", "written_by": "independent", "quote": "no one on the plane was treated on scene or taken to a hospital" }, { "kind": "news report", "citation": "Matt Ryan / AVweb (2025). Garmin Autoland Safely Lands King Air After Pilot Incapacitation. AVweb, 22 December 2025.", "title": "Garmin Autoland Safely Lands King Air After Pilot Incapacitation", "url": "https://avweb.com/aviation-news/garmin-autoland-safely-lands-king-air/", "date": "2025-12-22", "written_by": "independent", "quote": "transmitting automated broadcasts indicating a pilot incapacitation and intent to conduct an emergency autoland" }, { "kind": "news report", "citation": "Rachel Dobkin / The Independent (2025). Airplane automatically lands itself after an inflight emergency. The Independent, syndicated on Yahoo News, 24 December 2025.", "title": "Airplane automatically lands itself after an inflight emergency", "url": "https://www.yahoo.com/news/articles/airplane-automatically-lands-itself-inflight-044612392.html", "date": "2025-12-24", "written_by": "independent", "quote": "No patients were treated on scene or transported to local hospitals." } ], "replication": { "produced_by": [ "An aircraft fitted with Garmin Autoland. Garmin says more than 1,700 are equipped.", "A rapid, uncommanded loss of pressurization that pushed cabin altitude past the system's automatic trigger.", "A crew that decided to let the automatic sequence run to touchdown rather than take over." ], "must_hold": [ "The aircraft remains airworthy. Autoland is a fail-safe for a working aircraft whose pilot cannot fly it, in the words of the journalist CBS quoted.", "A suitable airport is in range. The Register describes selection by runway length, distance and fuel range.", "Controllers and ground services act on the automated broadcasts, as Broomfield's two fire departments did." ], "echoes": [] }, "paired_incident": null, "headline": "Garmin Autoland lands depressurised King Air B200; pilots unhurt", "metric": "two pilots unhurt", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The FAA said it was investigating and the NTSB that it was collecting information to decide whether the event met its criteria; no FAA or NTSB report or other development after December 2025 was found. The aircraft flew on to Oklahoma City the next morning.", "quote": null, "url": null }, "value": null, "developer_country": "Switzerland", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six news reports. The Monitor dates the event 22 December 2025; every report puts the landing on Saturday 20 December, which is used here. Early reports (AVweb, Denver7, ABC's headline) said the pilot was incapacitated; the operator's CEO, quoted by CBS, ABC and The Register, says the system engaged on cabin-altitude exceedance and the crew were not incapacitated. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented because the crew were conscious and elected to leave the system engaged, so no counterfactual is established. Aircraft type is given as Super King Air 200 (ABC, Denver7) and King Air B200 (AVweb, The Register). The Monitor's General Aviation News and FOX31 follow-up links returned HTTP 403, AVweb's “crew decision” piece returned 404, and the Independent blocked fetching, so its Yahoo syndication is cited. Garmin's Autonomí pages returned only navigation, so no vendor source is cited; Garmin's statements are quoted via the news reports.", "source": "https://oecd.ai/en/incidents/2025-12-22-41ce", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Garmin; https://buffaloriveraviation.com/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0153", "catalog_version": "1.0.0", "source_fingerprint": "e067d3612528a25b90b00340bad1e609571c414ab9142cd0bea9cf9db371b9b5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0153-source-0001", "AIBD-0153-source-0002", "AIBD-0153-source-0003", "AIBD-0153-source-0004", "AIBD-0153-source-0005", "AIBD-0153-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Garmin", "deployer": "Buffalo River Aviation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Autoland engaged itself when cabin altitude exceeded the limit. It declared the emergency to controllers with automated “pilot incapacitation” broadcasts. It flew the descent, approach and landing. The pilots elected to leave it engaged rather than take over. So the landing is the system's work. But the counterfactual, that they could not have landed, is not established. Garmin, the FAA and the operator all call it an automated system. None calls it AI. It is here because the OECD Monitor lists it as an AI system. The Register describes it choosing landing sites from runway length, distance and fuel range." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Autoland engaged itself when cabin altitude exceeded the limit. It declared the emergency to controllers with automated “pilot incapacitation” broadcasts. It flew the descent, approach and landing. The pilots elected to leave it engaged rather than take over. So the landing is the system's work. But the counterfactual, that they could not have landed, is not established. Garmin, the FAA and the operator all call it an automated system. None calls it AI. It is here because the OECD Monitor lists it as an AI system. The Register describes it choosing landing sites from runway length, distance and fuel range." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two pilots who had lost cabin pressure at 23,000 ft were on the ground in Broomfield within about 35 minutes of departure, untreated and uninjured. They were conscious and could have flown the descent themselves. So the benefit is a safe automatic recovery, not a documented life saved." }, { "group": "organizational", "depth": 1, "reason": "Buffalo River Aviation's aircraft “landed safely without incident”, in the airport spokeswoman's words. No damage is reported, and the FAA investigation was still open." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two pilots who had lost cabin pressure at 23,000 ft were on the ground in Broomfield within about 35 minutes of departure, untreated and uninjured. They were conscious and could have flown the descent themselves. So the benefit is a safe automatic recovery, not a documented life saved." }, { "group": "organizational", "depth": 1, "reason": "Buffalo River Aviation's aircraft “landed safely without incident”, in the airport spokeswoman's words. No damage is reported, and the FAA investigation was still open." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two pilots who had lost cabin pressure at 23,000 ft were on the ground in Broomfield within about 35 minutes of departure, untreated and uninjured. They were conscious and could have flown the descent themselves. So the benefit is a safe automatic recovery, not a documented life saved." }, { "group": "organizational", "depth": 1, "reason": "Buffalo River Aviation's aircraft “landed safely without incident”, in the airport spokeswoman's words. 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "two pilots unhurt", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-12-22-41ce" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The FAA said it was investigating and the NTSB that it was collecting information to decide whether the event met its criteria; no FAA or NTSB report or other development after December 2025 was found. The aircraft flew on to Oklahoma City the next morning." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0153" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Saturday 20 December 2025 Buffalo River Aviation's Beechcraft Super King Air B200, N479BR, left Aspen-Pitkin County Airport at 1:43 p.m. It carried two pilots and no passengers. At about 23,000 ft it suffered a rapid, uncommanded loss of pressurization. When cabin altitude passed the safe limit, Garmin Autoland engaged automatically. It sent automated emergency broadcasts to air traffic control. It flew the aircraft to a landing on Runway 30 at Rocky Mountain Metropolitan Airport, Broomfield, Colorado, shortly after 2 p.m. The crew chose to leave it engaged. Nobody was treated. The Federal Aviation Administration (FAA) said it was investigating and the NTSB that it was gathering information. Garmin called it the first use of Autoland from start to finish in an actual emergency.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Two pilots who had lost cabin pressure at 23,000 ft were on the ground in Broomfield within about 35 minutes of departure, untreated and uninjured. They were conscious and could have flown the descent themselves. So the benefit is a safe automatic recovery, not a documented life saved." }, { "group": "organizational", "depth": 1, "reason": "Buffalo River Aviation's aircraft “landed safely without incident”, in the airport spokeswoman's words. No damage is reported, and the FAA investigation was still open." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Autoland exists to take complete control of an aircraft and land it when the pilot cannot fly. It engages on its own when cabin altitude exceeds a set level. That is what happened here. The two pilots turned out not to be incapacitated, though, and chose to let it finish." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Broomfield, United States", "developer_country": "Switzerland", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Autoland exists to take complete control of an aircraft and land it when the pilot cannot fly. It engages on its own when cabin altitude exceeds a set level. That is what happened here. The two pilots turned out not to be incapacitated, though, and chose to let it finish." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-12-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six news reports. The Monitor dates the event 22 December 2025; every report puts the landing on Saturday 20 December, which is used here. Early reports (AVweb, Denver7, ABC's headline) said the pilot was incapacitated; the operator's CEO, quoted by CBS, ABC and The Register, says the system engaged on cabin-altitude exceedance and the crew were not incapacitated. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented because the crew were conscious and elected to leave the system engaged, so no counterfactual is established. Aircraft type is given as Super King Air 200 (ABC, Denver7) and King Air B200 (AVweb, The Register). The Monitor's General Aviation News and FOX31 follow-up links returned HTTP 403, AVweb's “crew decision” piece returned 404, and the Independent blocked fetching, so its Yahoo syndication is cited. Garmin's Autonomí pages returned only navigation, so no vendor source is cited; Garmin's statements are quoted via the news reports.", "source": "https://oecd.ai/en/incidents/2025-12-22-41ce", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Garmin; https://buffaloriveraviation.com/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An aircraft fitted with Garmin Autoland. Garmin says more than 1,700 are equipped.", "A rapid, uncommanded loss of pressurization that pushed cabin altitude past the system's automatic trigger.", "A crew that decided to let the automatic sequence run to touchdown rather than take over." ], "must_hold": [ "The aircraft remains airworthy. Autoland is a fail-safe for a working aircraft whose pilot cannot fly it, in the words of the journalist CBS quoted.", "A suitable airport is in range. The Register describes selection by runway length, distance and fuel range.", "Controllers and ground services act on the automated broadcasts, as Broomfield's two fire departments did." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and six news reports. The Monitor dates the event 22 December 2025; every report puts the landing on Saturday 20 December, which is used here. Early reports (AVweb, Denver7, ABC's headline) said the pilot was incapacitated; the operator's CEO, quoted by CBS, ABC and The Register, says the system engaged on cabin-altitude exceedance and the crew were not incapacitated. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented because the crew were conscious and elected to leave the system engaged, so no counterfactual is established. Aircraft type is given as Super King Air 200 (ABC, Denver7) and King Air B200 (AVweb, The Register). The Monitor's General Aviation News and FOX31 follow-up links returned HTTP 403, AVweb's “crew decision” piece returned 404, and the Independent blocked fetching, so its Yahoo syndication is cited. Garmin's Autonomí pages returned only navigation, so no vendor source is cited; Garmin's statements are quoted via the news reports.", "source": "https://oecd.ai/en/incidents/2025-12-22-41ce", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Garmin; https://buffaloriveraviation.com/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Aviation safety / automatic emergency landing", "segment": "Charter turboprop operations" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Sarah Horbacewicz / CBS News Colorado (2025). Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use. CBS News, 22 December 2025.", "title": "Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use", "url": "https://www.cbsnews.com/colorado/news/plane-emergency-landing-colorado-autoland/", "date": "2025-12-22", "written_by": "independent", "quote": "An onboard emergency autoland system was activated. Two people were on board. The FAA is investigating." }, { "kind": "news report", "citation": "Sam Sweeney and Ayesha Ali / ABC News (2025). Small plane lands safely with Autoland system after pilot is incapacitated. ABC News, 22 December 2025.", "title": "Small plane lands safely with Autoland system after pilot is incapacitated", "url": "https://abcnews.com/US/small-plane-lands-safely-autoland-system-after-pilot/story?id=128629603", "date": "2025-12-22", "written_by": "independent", "quote": "first use of Autoland from start-to-finish in an actual emergency" }, { "kind": "news report", "citation": "Jude Karabus / The Register (2025). Garmin autopilot lands small plane without pilot's help. The Register, 24 December 2025.", "title": "Garmin autopilot lands small plane without pilot's help", "url": "https://www.theregister.com/2025/12/24/autocomms/", "date": "2025-12-24", "written_by": "independent", "quote": "automatically engaged exactly as designed when the cabin altitude exceeded the prescribed safe levels" }, { "kind": "news report", "citation": "Katie Parkins and Óscar Contreras / Denver7 (2025). In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'. Denver7 (KMGH), 22 December 2025.", "title": "In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'", "url": "https://www.denver7.com/news/front-range/broomfield/in-a-first-plane-makes-emergency-landing-at-rmma-using-automated-technology-due-to-pilot-incapacitation", "date": "2025-12-22", "written_by": "independent", "quote": "no one on the plane was treated on scene or taken to a hospital" }, { "kind": "news report", "citation": "Matt Ryan / AVweb (2025). Garmin Autoland Safely Lands King Air After Pilot Incapacitation. AVweb, 22 December 2025.", "title": "Garmin Autoland Safely Lands King Air After Pilot Incapacitation", "url": "https://avweb.com/aviation-news/garmin-autoland-safely-lands-king-air/", "date": "2025-12-22", "written_by": "independent", "quote": "transmitting automated broadcasts indicating a pilot incapacitation and intent to conduct an emergency autoland" }, { "kind": "news report", "citation": "Rachel Dobkin / The Independent (2025). Airplane automatically lands itself after an inflight emergency. The Independent, syndicated on Yahoo News, 24 December 2025.", "title": "Airplane automatically lands itself after an inflight emergency", "url": "https://www.yahoo.com/news/articles/airplane-automatically-lands-itself-inflight-044612392.html", "date": "2025-12-24", "written_by": "independent", "quote": "No patients were treated on scene or transported to local hospitals." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0153-source-0001", "AIBD-0153-source-0002", "AIBD-0153-source-0003", "AIBD-0153-source-0004", "AIBD-0153-source-0005", "AIBD-0153-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Sarah Horbacewicz / CBS News Colorado (2025). Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use. CBS News, 22 December 2025.", "title": "Plane makes safe emergency landing in Colorado without a pilot's help, first 'Autoland' use", "url": "https://www.cbsnews.com/colorado/news/plane-emergency-landing-colorado-autoland/", "date": "2025-12-22", "written_by": "independent", "quote": "An onboard emergency autoland system was activated. Two people were on board. The FAA is investigating." }, { "kind": "news report", "citation": "Sam Sweeney and Ayesha Ali / ABC News (2025). Small plane lands safely with Autoland system after pilot is incapacitated. ABC News, 22 December 2025.", "title": "Small plane lands safely with Autoland system after pilot is incapacitated", "url": "https://abcnews.com/US/small-plane-lands-safely-autoland-system-after-pilot/story?id=128629603", "date": "2025-12-22", "written_by": "independent", "quote": "first use of Autoland from start-to-finish in an actual emergency" }, { "kind": "news report", "citation": "Jude Karabus / The Register (2025). Garmin autopilot lands small plane without pilot's help. The Register, 24 December 2025.", "title": "Garmin autopilot lands small plane without pilot's help", "url": "https://www.theregister.com/2025/12/24/autocomms/", "date": "2025-12-24", "written_by": "independent", "quote": "automatically engaged exactly as designed when the cabin altitude exceeded the prescribed safe levels" }, { "kind": "news report", "citation": "Katie Parkins and Óscar Contreras / Denver7 (2025). In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'. Denver7 (KMGH), 22 December 2025.", "title": "In a first, plane makes emergency landing at RMMA using automated technology due to 'pilot incapacitation'", "url": "https://www.denver7.com/news/front-range/broomfield/in-a-first-plane-makes-emergency-landing-at-rmma-using-automated-technology-due-to-pilot-incapacitation", "date": "2025-12-22", "written_by": "independent", "quote": "no one on the plane was treated on scene or taken to a hospital" }, { "kind": "news report", "citation": "Matt Ryan / AVweb (2025). Garmin Autoland Safely Lands King Air After Pilot Incapacitation. AVweb, 22 December 2025.", "title": "Garmin Autoland Safely Lands King Air After Pilot Incapacitation", "url": "https://avweb.com/aviation-news/garmin-autoland-safely-lands-king-air/", "date": "2025-12-22", "written_by": "independent", "quote": "transmitting automated broadcasts indicating a pilot incapacitation and intent to conduct an emergency autoland" }, { "kind": "news report", "citation": "Rachel Dobkin / The Independent (2025). Airplane automatically lands itself after an inflight emergency. The Independent, syndicated on Yahoo News, 24 December 2025.", "title": "Airplane automatically lands itself after an inflight emergency", "url": "https://www.yahoo.com/news/articles/airplane-automatically-lands-itself-inflight-044612392.html", "date": "2025-12-24", "written_by": "independent", "quote": "No patients were treated on scene or transported to local hospitals." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "On 20 December 2025 Garmin Autoland flew a depressurised King Air B200 to a landing at Rocky Mountain Metropolitan Airport; two pilots unhurt.", "account": "On Saturday 20 December 2025 Buffalo River Aviation's Beechcraft Super King Air B200, N479BR, left Aspen-Pitkin County Airport at 1:43 p.m. It carried two pilots and no passengers. At about 23,000 ft it suffered a rapid, uncommanded loss of pressurization. When cabin altitude passed the safe limit, Garmin Autoland engaged automatically. It sent automated emergency broadcasts to air traffic control. It flew the aircraft to a landing on Runway 30 at Rocky Mountain Metropolitan Airport, Broomfield, Colorado, shortly after 2 p.m. The crew chose to leave it engaged. Nobody was treated. The Federal Aviation Administration (FAA) said it was investigating and the NTSB that it was gathering information. Garmin called it the first use of Autoland from start to finish in an actual emergency." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Garmin Autoland (Emergency Autoland)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Garmin" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Garmin Autoland engages after a King Air B200 loses cabin pressure at 23,000 ft and lands it at Broomfield, Colorado, in its first real emergency use", "headline": "Garmin Autoland lands depressurised King Air B200; pilots unhurt" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e067d3612528a25b90b00340bad1e609571c414ab9142cd0bea9cf9db371b9b5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Saturday 20 December 2025 Buffalo River Aviation's Beechcraft Super King Air B200, N479BR, left Aspen-Pitkin County Airport at 1:43 p.m. It carried two pilots and no passengers. At about 23,000 ft it suffered a rapid, uncommanded loss of pressurization. When cabin altitude passed the safe limit, Garmin Autoland engaged automatically. It sent automated emergency broadcasts to air traffic control. It flew the aircraft to a landing on Runway 30 at Rocky Mountain Metropolitan Airport, Broomfield, Colorado, shortly after 2 p.m. The crew chose to leave it engaged. Nobody was treated. The Federal Aviation Administration (FAA) said it was investigating and the NTSB that it was gathering information. Garmin called it the first use of Autoland from start to finish in an actual emergency.", "replication": { "produced_by": [ "An aircraft fitted with Garmin Autoland. Garmin says more than 1,700 are equipped.", "A rapid, uncommanded loss of pressurization that pushed cabin altitude past the system's automatic trigger.", "A crew that decided to let the automatic sequence run to touchdown rather than take over." ], "must_hold": [ "The aircraft remains airworthy. Autoland is a fail-safe for a working aircraft whose pilot cannot fly it, in the words of the journalist CBS quoted.", "A suitable airport is in range. The Register describes selection by runway length, distance and fuel range.", "Controllers and ground services act on the automated broadcasts, as Broomfield's two fire departments did." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0154", "title": "Ho Chi Minh City street AI cameras identify a masked burglar by gait, build, clothing and face; Tân Hưng ward police detain him within two days", "summary": "HCMC street AI cameras identified a masked burglar who took two laptops and 14 million VND on 23 December 2025; police held him on 24 Dec.", "date_observed": "2025-12-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Early on 23 December 2025 an intruder entered a rented room at 62 Street 51, Tân Hưng ward, Ho Chi Minh City. He took two laptops and the wallet, identity papers and bank card of the tenant, H.A.T., 33. From his account, 14 million VND was withdrawn. He reported it that morning. Tân Hưng Ward Police and the Criminal Police Division used the street AI camera system. It analyzed the masked man's gait, build, clothing, movement and facial data, identified him and reconstructed his route. At 11 p.m. on 24 December officers found Phạm Ngọc Huy, 23, of Ninh Bình, at an internet café on Tô Ký street. He was a convicted thief. He confessed. Property recovery is not reported.", "category": "benefit created", "unexpected": false, "purpose": "Ho Chi Minh City's street AI cameras are run by the police for security and investigation. VnExpress describes the technology analyzing and matching biometric features. Identifying a suspect from footage is the use the police describe. The system and its vendor are not named.", "system": "Ho Chi Minh City police street AI camera system (unnamed): facial recognition with gait, body-shape, clothing and movement analysis", "model_version": null, "developer": null, "deployer": "Ho Chi Minh City Police (Tân Hưng Ward Police with the Criminal Police Division, PC02)", "location": "Ho Chi Minh City, Vietnam", "domain": "Policing / burglary investigation", "segment": "Public-space surveillance with facial and gait recognition", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2025-12-24-ee38" }, "ratings": [ { "group": "personal", "depth": 1, "reason": "H.A.T. had the intruder who took his laptops, papers and 14 million VND identified, detained and confessing within two days. No source reports recovery of the property or the money. So the benefit to him is resolution, not restitution." }, { "group": "organizational", "depth": 2, "reason": "Tân Hưng Ward Police and PC02 cleared a masked-intruder burglary in under 72 hours. Seven outlets carried the case as the police's demonstration of the AI camera system." } ], "ai_role": { "status": "assessed", "statement": "The system's contribution was identification. It matched the masked intruder's gait, body shape, clothing, movement and facial data and reconstructed his route. That pointed police to him. The detention, confession and case-building were police work. The system and its vendor are not named. No official is quoted by name. Every report draws on the police account. The OECD Monitor tags the entry under privacy and data governance and respect of human rights, the concerns that come with public facial recognition." }, "evidence": [ { "kind": "news report", "citation": "Quốc Thắng / VnExpress (2025). Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ. VnExpress, 25 December 2025.", "title": "Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ", "url": "https://vnexpress.net/camera-ai-giup-canh-sat-nhan-dang-ke-dot-nhap-phong-tro-4998114.html", "date": "2025-12-25", "written_by": "independent", "quote": "Công nghệ AI đã phân tích, đối sánh các đặc điểm sinh trắc học" }, { "kind": "news report", "citation": "Minh Hòa / Tuổi Trẻ Online (2025). Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang. Tuổi Trẻ, 25 December 2025.", "title": "Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang", "url": "https://tuoitre.vn/ung-dung-camera-ai-cong-an-phuong-tan-hung-bat-nhanh-ke-trom-deo-khau-trang-20251225112926111.htm", "date": "2025-12-25", "written_by": "independent", "quote": "Đến 23h ngày 24-12, Tổ truy xét Công an phường Tân Hưng phối hợp Đội 2 PC02 và Công an phường Trung Mỹ Tây kiểm tra tụ điểm net" }, { "kind": "news report", "citation": "Trần Duy Khánh and Ngọc Lê / Thanh Niên (2025). Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI. Thanh Niên, 25 December 2025.", "title": "Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI", "url": "https://thanhnien.vn/cong-an-tphcm-lam-ro-vu-trom-cap-chi-sau-72-gio-nho-camera-ai-185251225111822364.htm", "date": "2025-12-25", "written_by": "independent", "quote": "phân tích dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt, hệ thống đã hỗ trợ lực lượng công an" }, { "kind": "news report", "citation": "Đàm Đệ / VietNamNet (2025). Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM. VietNamNet, 25 December 2025.", "title": "Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM", "url": "https://vietnamnet.vn/bat-nhanh-ke-trom-deo-khau-trang-nho-camera-ai-duong-pho-o-tphcm-2475850.html", "date": "2025-12-25", "written_by": "independent", "quote": "dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt" }, { "kind": "news report", "citation": "M.Đ / Công an nhân dân (2025). Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án. Báo Công an nhân dân điện tử, 25 December 2025.", "title": "Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án", "url": "https://cand.com.vn/Ban-tin-113/tu-du-lieu-cua-camera-ai-bat-doi-tuong-trom-sau-72-gio-gay-an-i792189/", "date": "2025-12-25", "written_by": "deployer", "quote": "qua phân tích, đối chiếu, khuôn mặt (kể cả đeo khẩu trang) dáng đi, hình thể, trang phục, hành vi, hệ thống đã nhận dạng được đối tượng" } ], "replication": { "produced_by": [ "Street AI cameras covering the route the intruder took, with footage retained for police review.", "A model that matches people on gait, body shape, clothing and movement as well as face, so a mask does not defeat identification.", "A prompt police report, the morning of the burglary, and a ward investigation team able to act on the match within hours." ], "must_hold": [ "The suspect passes through camera coverage and can be found at a fixed location afterwards, here an internet café.", "Identification is confirmed by police work and a confession. The sources report no independent check of the match.", "The system and vendor are unnamed, so performance beyond this case cannot be checked." ], "echoes": [] }, "paired_incident": null, "headline": "HCMC AI cameras identify a masked burglar; police detain him", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The 25 December 2025 reports end with the suspect's confession and the ward police consolidating the file; no prosecution or trial report was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Vietnam", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and five Vietnamese reports of 25 December 2025. Benefit created or restored as the classifier proposed: a post-hoc investigation that resolved a burglary, not a prevented harm. The detention time differs between outlets: Tuổi Trẻ gives 23h on 24–12, Công an nhân dân the night of 24 to 25 December, VnExpress and VietNamNet date the arrest 25 December, and Thanh Niên prints “23 giờ ngày 25.12”, which postdates its own 11:52 publication and is treated as a misprint; the date observed is 24 December. The Monitor's Pháp Luật TP.HCM link resolved only to a headline stub and is not cited; the Công an nhân dân link redirected from cand.com.vn to cand.vn when read. The victim's year of birth is 1992 (VietNamNet, CAND); the suspect's is 2002. Property recovery is not mentioned in any source; the suspect is reported to have sold the items.", "source": "https://oecd.ai/en/incidents/2025-12-24-ee38", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_Thành_phố_Hồ_Chí_Minh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0154", "catalog_version": "1.0.0", "source_fingerprint": "b08bbc97e23b6b86a8da84a22c5067cd06278e55df97e383c15244bc848386f4", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0154-source-0001", "AIBD-0154-source-0002", "AIBD-0154-source-0003", "AIBD-0154-source-0004", "AIBD-0154-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Ho Chi Minh City Police (Tân Hưng Ward Police with the Criminal Police Division, PC02)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's contribution was identification. It matched the masked intruder's gait, body shape, clothing, movement and facial data and reconstructed his route. That pointed police to him. The detention, confession and case-building were police work. The system and its vendor are not named. No official is quoted by name. Every report draws on the police account. The OECD Monitor tags the entry under privacy and data governance and respect of human rights, the concerns that come with public facial recognition." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The system's contribution was identification. It matched the masked intruder's gait, body shape, clothing, movement and facial data and reconstructed his route. That pointed police to him. The detention, confession and case-building were police work. The system and its vendor are not named. No official is quoted by name. Every report draws on the police account. The OECD Monitor tags the entry under privacy and data governance and respect of human rights, the concerns that come with public facial recognition." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "H.A.T. had the intruder who took his laptops, papers and 14 million VND identified, detained and confessing within two days. No source reports recovery of the property or the money. So the benefit to him is resolution, not restitution." }, { "group": "organizational", "depth": 2, "reason": "Tân Hưng Ward Police and PC02 cleared a masked-intruder burglary in under 72 hours. Seven outlets carried the case as the police's demonstration of the AI camera system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports and the deployer's news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "H.A.T. had the intruder who took his laptops, papers and 14 million VND identified, detained and confessing within two days. No source reports recovery of the property or the money. So the benefit to him is resolution, not restitution." }, { "group": "organizational", "depth": 2, "reason": "Tân Hưng Ward Police and PC02 cleared a masked-intruder burglary in under 72 hours. Seven outlets carried the case as the police's demonstration of the AI camera system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "H.A.T. had the intruder who took his laptops, papers and 14 million VND identified, detained and confessing within two days. No source reports recovery of the property or the money. So the benefit to him is resolution, not restitution." }, { "group": "organizational", "depth": 2, "reason": "Tân Hưng Ward Police and PC02 cleared a masked-intruder burglary in under 72 hours. Seven outlets carried the case as the police's demonstration of the AI camera system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2025-12-24-ee38" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The 25 December 2025 reports end with the suspect's confession and the ward police consolidating the file; no prosecution or trial report was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0154" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Early on 23 December 2025 an intruder entered a rented room at 62 Street 51, Tân Hưng ward, Ho Chi Minh City. He took two laptops and the wallet, identity papers and bank card of the tenant, H.A.T., 33. From his account, 14 million VND was withdrawn. He reported it that morning. Tân Hưng Ward Police and the Criminal Police Division used the street AI camera system. It analyzed the masked man's gait, build, clothing, movement and facial data, identified him and reconstructed his route. At 11 p.m. on 24 December officers found Phạm Ngọc Huy, 23, of Ninh Bình, at an internet café on Tô Ký street. He was a convicted thief. He confessed. Property recovery is not reported.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "H.A.T. had the intruder who took his laptops, papers and 14 million VND identified, detained and confessing within two days. No source reports recovery of the property or the money. So the benefit to him is resolution, not restitution." }, { "group": "organizational", "depth": 2, "reason": "Tân Hưng Ward Police and PC02 cleared a masked-intruder burglary in under 72 hours. Seven outlets carried the case as the police's demonstration of the AI camera system." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Ho Chi Minh City's street AI cameras are run by the police for security and investigation. VnExpress describes the technology analyzing and matching biometric features. Identifying a suspect from footage is the use the police describe. The system and its vendor are not named." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Ho Chi Minh City, Vietnam", "deployer_country": "Vietnam" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Ho Chi Minh City's street AI cameras are run by the police for security and investigation. VnExpress describes the technology analyzing and matching biometric features. Identifying a suspect from footage is the use the police describe. The system and its vendor are not named." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-12-24", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and five Vietnamese reports of 25 December 2025. Benefit created or restored as the classifier proposed: a post-hoc investigation that resolved a burglary, not a prevented harm. The detention time differs between outlets: Tuổi Trẻ gives 23h on 24–12, Công an nhân dân the night of 24 to 25 December, VnExpress and VietNamNet date the arrest 25 December, and Thanh Niên prints “23 giờ ngày 25.12”, which postdates its own 11:52 publication and is treated as a misprint; the date observed is 24 December. The Monitor's Pháp Luật TP.HCM link resolved only to a headline stub and is not cited; the Công an nhân dân link redirected from cand.com.vn to cand.vn when read. The victim's year of birth is 1992 (VietNamNet, CAND); the suspect's is 2002. Property recovery is not mentioned in any source; the suspect is reported to have sold the items.", "source": "https://oecd.ai/en/incidents/2025-12-24-ee38", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_Thành_phố_Hồ_Chí_Minh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Street AI cameras covering the route the intruder took, with footage retained for police review.", "A model that matches people on gait, body shape, clothing and movement as well as face, so a mask does not defeat identification.", "A prompt police report, the morning of the burglary, and a ward investigation team able to act on the match within hours." ], "must_hold": [ "The suspect passes through camera coverage and can be found at a fixed location afterwards, here an internet café.", "Identification is confirmed by police work and a confession. The sources report no independent check of the match.", "The system and vendor are unnamed, so performance beyond this case cannot be checked." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and five Vietnamese reports of 25 December 2025. Benefit created or restored as the classifier proposed: a post-hoc investigation that resolved a burglary, not a prevented harm. The detention time differs between outlets: Tuổi Trẻ gives 23h on 24–12, Công an nhân dân the night of 24 to 25 December, VnExpress and VietNamNet date the arrest 25 December, and Thanh Niên prints “23 giờ ngày 25.12”, which postdates its own 11:52 publication and is treated as a misprint; the date observed is 24 December. The Monitor's Pháp Luật TP.HCM link resolved only to a headline stub and is not cited; the Công an nhân dân link redirected from cand.com.vn to cand.vn when read. The victim's year of birth is 1992 (VietNamNet, CAND); the suspect's is 2002. Property recovery is not mentioned in any source; the suspect is reported to have sold the items.", "source": "https://oecd.ai/en/incidents/2025-12-24-ee38", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://vi.wikipedia.org/wiki/Công_an_Thành_phố_Hồ_Chí_Minh", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / burglary investigation", "segment": "Public-space surveillance with facial and gait recognition" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Quốc Thắng / VnExpress (2025). Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ. VnExpress, 25 December 2025.", "title": "Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ", "url": "https://vnexpress.net/camera-ai-giup-canh-sat-nhan-dang-ke-dot-nhap-phong-tro-4998114.html", "date": "2025-12-25", "written_by": "independent", "quote": "Công nghệ AI đã phân tích, đối sánh các đặc điểm sinh trắc học" }, { "kind": "news report", "citation": "Minh Hòa / Tuổi Trẻ Online (2025). Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang. Tuổi Trẻ, 25 December 2025.", "title": "Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang", "url": "https://tuoitre.vn/ung-dung-camera-ai-cong-an-phuong-tan-hung-bat-nhanh-ke-trom-deo-khau-trang-20251225112926111.htm", "date": "2025-12-25", "written_by": "independent", "quote": "Đến 23h ngày 24-12, Tổ truy xét Công an phường Tân Hưng phối hợp Đội 2 PC02 và Công an phường Trung Mỹ Tây kiểm tra tụ điểm net" }, { "kind": "news report", "citation": "Trần Duy Khánh and Ngọc Lê / Thanh Niên (2025). Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI. Thanh Niên, 25 December 2025.", "title": "Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI", "url": "https://thanhnien.vn/cong-an-tphcm-lam-ro-vu-trom-cap-chi-sau-72-gio-nho-camera-ai-185251225111822364.htm", "date": "2025-12-25", "written_by": "independent", "quote": "phân tích dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt, hệ thống đã hỗ trợ lực lượng công an" }, { "kind": "news report", "citation": "Đàm Đệ / VietNamNet (2025). Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM. VietNamNet, 25 December 2025.", "title": "Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM", "url": "https://vietnamnet.vn/bat-nhanh-ke-trom-deo-khau-trang-nho-camera-ai-duong-pho-o-tphcm-2475850.html", "date": "2025-12-25", "written_by": "independent", "quote": "dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt" }, { "kind": "news report", "citation": "M.Đ / Công an nhân dân (2025). Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án. Báo Công an nhân dân điện tử, 25 December 2025.", "title": "Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án", "url": "https://cand.com.vn/Ban-tin-113/tu-du-lieu-cua-camera-ai-bat-doi-tuong-trom-sau-72-gio-gay-an-i792189/", "date": "2025-12-25", "written_by": "deployer", "quote": "qua phân tích, đối chiếu, khuôn mặt (kể cả đeo khẩu trang) dáng đi, hình thể, trang phục, hành vi, hệ thống đã nhận dạng được đối tượng" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0154-source-0001", "AIBD-0154-source-0002", "AIBD-0154-source-0003", "AIBD-0154-source-0004", "AIBD-0154-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Quốc Thắng / VnExpress (2025). Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ. VnExpress, 25 December 2025.", "title": "Camera AI giúp cảnh sát nhận dạng kẻ đột nhập phòng trọ", "url": "https://vnexpress.net/camera-ai-giup-canh-sat-nhan-dang-ke-dot-nhap-phong-tro-4998114.html", "date": "2025-12-25", "written_by": "independent", "quote": "Công nghệ AI đã phân tích, đối sánh các đặc điểm sinh trắc học" }, { "kind": "news report", "citation": "Minh Hòa / Tuổi Trẻ Online (2025). Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang. Tuổi Trẻ, 25 December 2025.", "title": "Ứng dụng camera AI, Công an phường Tân Hưng bắt nhanh kẻ trộm đeo khẩu trang", "url": "https://tuoitre.vn/ung-dung-camera-ai-cong-an-phuong-tan-hung-bat-nhanh-ke-trom-deo-khau-trang-20251225112926111.htm", "date": "2025-12-25", "written_by": "independent", "quote": "Đến 23h ngày 24-12, Tổ truy xét Công an phường Tân Hưng phối hợp Đội 2 PC02 và Công an phường Trung Mỹ Tây kiểm tra tụ điểm net" }, { "kind": "news report", "citation": "Trần Duy Khánh and Ngọc Lê / Thanh Niên (2025). Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI. Thanh Niên, 25 December 2025.", "title": "Công an TP.HCM làm rõ vụ trộm cắp chỉ sau 72 giờ nhờ camera AI", "url": "https://thanhnien.vn/cong-an-tphcm-lam-ro-vu-trom-cap-chi-sau-72-gio-nho-camera-ai-185251225111822364.htm", "date": "2025-12-25", "written_by": "independent", "quote": "phân tích dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt, hệ thống đã hỗ trợ lực lượng công an" }, { "kind": "news report", "citation": "Đàm Đệ / VietNamNet (2025). Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM. VietNamNet, 25 December 2025.", "title": "Bắt nhanh kẻ trộm đeo khẩu trang nhờ camera AI đường phố ở TPHCM", "url": "https://vietnamnet.vn/bat-nhanh-ke-trom-deo-khau-trang-nho-camera-ai-duong-pho-o-tphcm-2475850.html", "date": "2025-12-25", "written_by": "independent", "quote": "dáng đi, đặc điểm hình thể, trang phục, hành vi di chuyển và dữ liệu khuôn mặt" }, { "kind": "news report", "citation": "M.Đ / Công an nhân dân (2025). Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án. Báo Công an nhân dân điện tử, 25 December 2025.", "title": "Từ dữ liệu của camera AI, bắt đối tượng trộm sau 72 giờ gây án", "url": "https://cand.com.vn/Ban-tin-113/tu-du-lieu-cua-camera-ai-bat-doi-tuong-trom-sau-72-gio-gay-an-i792189/", "date": "2025-12-25", "written_by": "deployer", "quote": "qua phân tích, đối chiếu, khuôn mặt (kể cả đeo khẩu trang) dáng đi, hình thể, trang phục, hành vi, hệ thống đã nhận dạng được đối tượng" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "HCMC street AI cameras identified a masked burglar who took two laptops and 14 million VND on 23 December 2025; police held him on 24 Dec.", "account": "Early on 23 December 2025 an intruder entered a rented room at 62 Street 51, Tân Hưng ward, Ho Chi Minh City. He took two laptops and the wallet, identity papers and bank card of the tenant, H.A.T., 33. From his account, 14 million VND was withdrawn. He reported it that morning. Tân Hưng Ward Police and the Criminal Police Division used the street AI camera system. It analyzed the masked man's gait, build, clothing, movement and facial data, identified him and reconstructed his route. At 11 p.m. on 24 December officers found Phạm Ngọc Huy, 23, of Ninh Bình, at an internet café on Tô Ký street. He was a convicted thief. He confessed. Property recovery is not reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Ho Chi Minh City police street AI camera system (unnamed): facial recognition with gait, body-shape, clothing and movement analysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Ho Chi Minh City street AI cameras identify a masked burglar by gait, build, clothing and face; Tân Hưng ward police detain him within two days", "headline": "HCMC AI cameras identify a masked burglar; police detain him" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b08bbc97e23b6b86a8da84a22c5067cd06278e55df97e383c15244bc848386f4" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Early on 23 December 2025 an intruder entered a rented room at 62 Street 51, Tân Hưng ward, Ho Chi Minh City. He took two laptops and the wallet, identity papers and bank card of the tenant, H.A.T., 33. From his account, 14 million VND was withdrawn. He reported it that morning. Tân Hưng Ward Police and the Criminal Police Division used the street AI camera system. It analyzed the masked man's gait, build, clothing, movement and facial data, identified him and reconstructed his route. At 11 p.m. on 24 December officers found Phạm Ngọc Huy, 23, of Ninh Bình, at an internet café on Tô Ký street. He was a convicted thief. He confessed. Property recovery is not reported.", "replication": { "produced_by": [ "Street AI cameras covering the route the intruder took, with footage retained for police review.", "A model that matches people on gait, body shape, clothing and movement as well as face, so a mask does not defeat identification.", "A prompt police report, the morning of the burglary, and a ward investigation team able to act on the match within hours." ], "must_hold": [ "The suspect passes through camera coverage and can be found at a fixed location afterwards, here an internet café.", "Identification is confirmed by police work and a confession. The sources report no independent check of the match.", "The system and vendor are unnamed, so performance beyond this case cannot be checked." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0180", "title": "RBI Innovation Hub's MuleHunter.AI adopted by 23 banks; RBI declines to disclose mule accounts found", "summary": "MediaNama's RTI (December 2025) found 23 banks had implemented RBIH's MuleHunter.AI, which analyzes transaction patterns to spot mule accounts; the RBI refused to release detection figures, citing ...", "date_observed": "2025-12-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Identify bank accounts likely used as money mules in financial fraud.", "system": "MuleHunter.AI", "model_version": null, "developer": "Reserve Bank Innovation Hub (RBIH)", "deployer": "23 Indian banks as of 10 December 2025, including Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank", "location": null, "domain": "Anti-money laundering and cyber fraud", "segment": "Mule account detection", "benefit_type": "Reduced Risk", "taxonomy_note": "Adoption only; the type names the mule-account fraud the tool is meant to catch.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "depth": null, "reason": "No fraud loss avoided is documented." } ], "ai_role": { "status": "unassessed", "statement": "The tool is described as AI-based pattern analysis across banks. No detection result is available to assess its contribution. RBIH, a central-bank subsidiary, developed it. Commercial and public-sector banks deploy it." }, "evidence": [ { "kind": "news report", "citation": "Prabhanu Kumar Das, MediaNama, 30 December 2025", "title": "RTI Reveals 23 Banks Have Implemented Mulehunter.AI, But Total Mule Accounts Identified Still Not Disclosed", "url": "https://www.medianama.com/2025/12/223-rti-23-banks-mulehunter-mule-accounts/", "date": "2025-12-30", "written_by": "independent", "quote": "cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI" }, { "kind": "press release", "citation": "Press Information Bureau (2026). I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds. Ministry of Home Affairs via PIB, 12 May 2026.", "title": "I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "date": "2026-05-12", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "model_version": null, "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] }, "paired_incident": null, "headline": "RBIH's MuleHunter.AI adopted by 23 banks; RBI withholds figures", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-05-12", "note": "I4C and RBIH signed an MoU to feed suspect identifiers from I4C's Suspect Registry into MuleHunter.ai and to use the data to retrain it.", "quote": "Under the MoU, I4C and RBIH will collaborate for sharing of mule account related intelligence and suspect identifiers from I4C-MHA’s Suspect Registry to strengthen AI-driven fraud detection systems such as MuleHunter.ai™ implemented across banks. RBIH will utilise the datasets for training and enhancement of AI-driven fraud-risk assessment models, including MuleHunter.ai™.", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reserve_Bank_of_India; https://en.wikipedia.org/wiki/Canara_Bank", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0180", "catalog_version": "1.0.0", "source_fingerprint": "3a66e7de9ab0a77fb448b9bf589ebea2a990899ef305b2b3dc90d0d5b687ffd1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0180-source-0001", "AIBD-0180-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Reserve Bank Innovation Hub (RBIH)", "deployer": "23 Indian banks as of 10 December 2025, including Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The tool is described as AI-based pattern analysis across banks. No detection result is available to assess its contribution. RBIH, a central-bank subsidiary, developed it. Commercial and public-sector banks deploy it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-05-12", "note": "I4C and RBIH signed an MoU to feed suspect identifiers from I4C's Suspect Registry into MuleHunter.ai and to use the data to retrain it.", "quote": "Under the MoU, I4C and RBIH will collaborate for sharing of mule account related intelligence and suspect identifiers from I4C-MHA’s Suspect Registry to strengthen AI-driven fraud detection systems such as MuleHunter.ai™ implemented across banks. RBIH will utilise the datasets for training and enhancement of AI-driven fraud-risk assessment models, including MuleHunter.ai™.", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0180" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "Adoption only; the type names the mule-account fraud the tool is meant to catch." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Identify bank accounts likely used as money mules in financial fraud." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify bank accounts likely used as money mules in financial fraud." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2025-12-30", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reserve_Bank_of_India; https://en.wikipedia.org/wiki/Canara_Bank", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reserve_Bank_of_India; https://en.wikipedia.org/wiki/Canara_Bank", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Anti-money laundering and cyber fraud", "segment": "Mule account detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Prabhanu Kumar Das, MediaNama, 30 December 2025", "title": "RTI Reveals 23 Banks Have Implemented Mulehunter.AI, But Total Mule Accounts Identified Still Not Disclosed", "url": "https://www.medianama.com/2025/12/223-rti-23-banks-mulehunter-mule-accounts/", "date": "2025-12-30", "written_by": "independent", "quote": "cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI" }, { "kind": "press release", "citation": "Press Information Bureau (2026). I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds. Ministry of Home Affairs via PIB, 12 May 2026.", "title": "I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "date": "2026-05-12", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0180-source-0001", "AIBD-0180-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Prabhanu Kumar Das, MediaNama, 30 December 2025", "title": "RTI Reveals 23 Banks Have Implemented Mulehunter.AI, But Total Mule Accounts Identified Still Not Disclosed", "url": "https://www.medianama.com/2025/12/223-rti-23-banks-mulehunter-mule-accounts/", "date": "2025-12-30", "written_by": "independent", "quote": "cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI" }, { "kind": "press release", "citation": "Press Information Bureau (2026). I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds. Ministry of Home Affairs via PIB, 12 May 2026.", "title": "I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "date": "2026-05-12", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "MediaNama's RTI (December 2025) found 23 banks had implemented RBIH's MuleHunter.AI, which analyzes transaction patterns to spot mule accounts; the RBI refused to release detection figures, citing ...", "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "MuleHunter.AI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Reserve Bank Innovation Hub (RBIH)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "RBI Innovation Hub's MuleHunter.AI adopted by 23 banks; RBI declines to disclose mule accounts found", "headline": "RBIH's MuleHunter.AI adopted by 23 banks; RBI withholds figures" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3a66e7de9ab0a77fb448b9bf589ebea2a990899ef305b2b3dc90d0d5b687ffd1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0023", "title": "Apple Watch Fall Detection summoning help after out-of-hospital cardiac arrest", "summary": "Fall Detection on his Apple Watch Series 10 called emergency services, and he recovered fully after CPR and hospital treatment.", "date_observed": "2026-01-01", "date_basis": "event", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A case report published on 12 August 2026 describes a 69-year-old man who collapsed from ventricular fibrillation while running alone. He was on a dead-end road, hidden behind a hedge. The paper gives no date or place. The authors' hospitals are Radboud University Medical Center, Nijmegen, and Slingeland Hospital, Doetinchem. His Apple Watch (reported as Apple Watch 10) with Fall Detection enabled detected the fall. It automatically alerted his predefined emergency contacts and the emergency medical services by calling 112. Family members reached him, found him unresponsive and began cardiopulmonary resuscitation (CPR) about 6–7 minutes after the collapse. An ambulance arrived about 1.5 minutes later, defibrillated him and restored circulation. He underwent coronary artery bypass grafting and defibrillator implantation, was discharged on day 29 and made a full neurological recovery. Two interviews identify the patient as Alwi Siebers, 69, of Varsseveld, and date the collapse to 1 January 2026. Men's Health NL (28 April 2026) opens “1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland” (1 January 2026 begins for 69-year-old Alwi Siebers as an ordinary running day; the keen runner from Varsseveld is training for the Montferland half marathon). His son Tristan says “De locatie was heel precies. Hij lag achter een heg op een afgelegen plek. Zonder die melding had ik hem niet zo snel gevonden” (the location was very precise; he was lying behind a hedge in a remote spot; without that alert I would not have found him so quickly). WANT (1 May 2026) quotes Siebers, “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon” (I know from my activity log that I started my training loop at twelve past twelve). It reproduces the alert his son received, headed “do 1 jan, 12:12”. The interviews match the paper on the man's age and the Apple Watch Series 10 with fall detection. They also match on the automatic alert to 112 and to his emergency contacts, the hedge and the remote spot. They match on the son starting CPR and the daughter giving mouth-to-mouth, and a history of asthma and bronchiectasis. They match on six days in intensive care, four bypass grafts, an ICD and a full recovery. No source names both the paper and Siebers, so the identification is inferred from these details. Men's Health says that Siebers also pressed the SOS button himself and that a pulse returned within about three minutes. The paper's timeline does not support that: CPR after 6–7 minutes, four shocks, adrenaline and amiodarone before circulation returned. The street is probable but inferred. A fire-brigade pager message of 1 January 2026 at 12:18:59 records a resuscitation on the Oude Doetinchemseweg in Varsseveld. That is a dead-end road at the western edge of the village. The map in the alert screenshot shows the pin on a side road off the Doetinchemseweg. No source names the street in connection with Siebers.", "category": "harm prevented", "unexpected": false, "purpose": "Fall Detection is built to recognize a hard fall and, if the wearer stays immobile, to call emergency services and notify contacts with the location. That is what it did.", "system": "Apple Watch Fall Detection", "model_version": null, "developer": "Apple", "deployer": null, "location": "Varsseveld, Gelderland, Netherlands", "domain": "Emergency medicine / resuscitation", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 5, "reason": "The patient was alone and hidden from view in cardiac arrest. The automatic alerts brought CPR within 6–7 minutes. He left hospital neurologically intact, which the source presents as life-saving." } ], "ai_role": { "status": "assessed", "statement": "The paper reports that the watch recognized the fall and automatically called 112 and alerted emergency contacts. Those alerts brought responders to the man behind the hedge. Humans provided resuscitation, defibrillation, and surgery. The watch's contribution is documented in the clinical narrative, but the time to rescue or outcome without it cannot be measured from this case. Apple's documentation describes the detection and notification sequence without disclosing the classifier or model version." }, "evidence": [ { "kind": "case report", "citation": "Jansen CE, Jaspers Focks J, Manglani Rodriguez S, Pol L, Edgar R, van Royen N, Bonnes JL (2026). Wearable saving lives: a case report. Resuscitation Plus 31:101447.", "title": "Wearable saving lives: a case report", "url": "https://europepmc.org/article/PMC/PMC13543876", "date": "2026-08-12", "written_by": "independent", "quote": "The Apple Watch detected the fall and automatically alerted predefined emergency contacts as well as the emergency medical services by calling 112." }, { "kind": "news report", "citation": "Boerman, E. (2026). ‘Ik was voor drie minuten dood, maar mijn Apple Watch redde mijn leven’. Men's Health NL, April 28, 2026.", "title": "Hartstilstand tijdens hardlopen: Apple Watch redt leven", "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "date": "2026-04-28", "written_by": "independent", "quote": "1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland en trekt eropuit zoals hij dat al jaren doet. Toch gaat het mis. Alwi krijgt tijdens het lopen een hartstilstand." }, { "kind": "news report", "citation": "Kraak J (2026). Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert. WANT, 1 May 2026 (with the alert screenshot headed 'do 1 jan, 12:12').", "title": "Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert", "url": "https://www.want.nl/apple-watch-leven-gered-alwi-siebers/", "date": "2026-05-01", "written_by": "independent", "quote": "Het ging 1 januari van dit jaar echter mis. “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon.” Niet veel later kreeg zoon Tristan een bericht op zijn smartphone. Dat bericht was niet gestuurd door Alwi zelf, maar door zijn Apple Watch Series 10. Het was een melding dat zijn vader gevallen was." }, { "kind": "other", "citation": "112-meldingen.nl (2026). P2000 pager message, Varsseveld, 1 January 2026, 12:18:59, fire brigade Lichtenvoorde (resuscitation, privacy screen), with ambulance capcodes at 12:17 and 12:18.", "title": "Incident Oude Doetinchemseweg Varsseveld", "url": "https://112-meldingen.nl/112-varsseveld/incident-oude-doetinchemseweg-varsseveld-1402058", "date": "2026-01-01", "written_by": "unknown", "quote": "0803203 12:18:59 01-01-26 P 2 BON-02 Reanimatie (zichtscherm) Oude Doetinchemseweg Varsseveld 066371" }, { "kind": "other", "citation": "Apple. Use Fall Detection with Apple Watch, May 6, 2026; “How it works,” “What happens if your Apple Watch detects that you're immobile,” and notes 1–3.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch with cellular or phone connectivity", "The wearer collapses with an impact the classifier recognizes and then stays immobile", "Emergency services and contacts can reach the shared location quickly" ], "must_hold": [ "The watch has connectivity at the scene", "The collapse produces a detectable fall signature", "Responders arrive within the window in which resuscitation can succeed" ], "echoes": [ { "date": "2024-05-13", "setting": "elderly man, found by his wife lying unresponsive on the floor; place and setting not stated in the abstract (authors: EMS medical director for the District of Herford and Herford Hospital, Germany); smartwatch brand not stated in the accessible abstract (full text paywalled); watch auto-reported the fall from ventricular fibrillation to the local emergency control center, the dispatcher phoned his wife, EMS resuscitated him, discharged without long-term complications (publication date)", "model_version": null, "outcome": "recurred", "source": "Grautoff & Watol (2024). Herzschr Elektrophys 35(2):140-143. https://doi.org/10.1007/s00399-024-01026-w" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "severity": null, "group": "personal", "basis": "Same developer and feature family: Apple Watch automatic emergency calling; Fall Detection summoned 112 for a collapsed runner, while Crash Detection placed false 911 calls for skiers, harming Apple Watch users and emergency dispatchers." }, "headline": "An Apple Watch called for help after a runner’s heart stopped", "metric": "CPR at 6–7 min, full neurological recovery", "comparator": { "against": "being found without the automatic alert, on a remote spot behind a hedge", "before": "Zonder die melding had ik hem niet zo snel gevonden (without that alert I would not have found him so quickly)", "after": "CPR approximately 6–7 min after collapse; full neurological recovery", "basis": "assumed", "quote": "'De locatie was heel precies. Hij lag achter een heg op een afgelegen plek. Zonder die melding had ik hem niet zo snel gevonden.'", "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven" }, "later": { "status": "unknown", "date": null, "note": "No development dated after the 1 January 2026 event beyond the case report and interviews already cited was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Noted in the account that the Netherlands is inferred from the authors' affiliations rather than stated in the case text, and removed “at home” and “Herford district” from the Grautoff & Watol echo because the abstract gives no place or setting beyond the patient lying on the floor.", "source": "https://europepmc.org/article/PMC/PMC13543876 ; https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI:10.1007/s00399-024-01026-w&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Dated to 1 January 2026 and placed at Varsseveld from two interviews with the patient (Men's Health NL, WANT); the street, Oude Doetinchemseweg, is inferred from a dispatch log and the alert's map and marked as such; sources added.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the separate 2024 ventricular-fibrillation case from this patient's evidence and consolidated the two Men's Health excerpts. Retained the clinical report as the lead, the interviews for identification and contradictory details, and the pager reproduction only for contextual dispatch timing. Added the Apple documentation cited by the clinical paper for the device's behavior. Preserved that linking the anonymous patient to Alwi Siebers is an inference.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Moved Apple Watch Series 10 from the AI model-version field to the documented hardware configuration. Reviewed the original clinical report, patient interviews, and Apple documentation; the deployed watchOS and classifier releases remain unreported.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced “called 112” with “called emergency services” in the subtitle.", "source": null, "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report, two independent news reports, the makers' other and one other with authorship relationship unassessed. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0023", "catalog_version": "1.0.0", "source_fingerprint": "8049d87606517d6e72056f910c254541f517f3b85d1f9e8ff95f9e6782ad1ebd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The paper reports that the watch recognized the fall and automatically called 112 and alerted emergency contacts. Those alerts brought responders to the man behind the hedge. Humans provided resuscitation, defibrillation, and surgery. The watch's contribution is documented in the clinical narrative, but the time to rescue or outcome without it cannot be measured from this case. Apple's documentation describes the detection and notification sequence without disclosing the classifier or model version." } } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The clinical report states that the watch detected the fall, called emergency services, and alerted emergency contacts. Responders found the man behind a hedge and treated his cardiac arrest. The report does not establish how quickly he would have been found without the watch.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The paper reports that the watch recognized the fall and automatically called 112 and alerted emergency contacts. Those alerts brought responders to the man behind the hedge. Humans provided resuscitation, defibrillation, and surgery. The watch's contribution is documented in the clinical narrative, but the time to rescue or outcome without it cannot be measured from this case. Apple's documentation describes the detection and notification sequence without disclosing the classifier or model version." } } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "The patient was alone and hidden from view in cardiac arrest. The automatic alerts brought CPR within 6–7 minutes. He left hospital neurologically intact, which the source presents as life-saving." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report, two independent news reports, the makers' other and one other with authorship relationship unassessed. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule retained. Originality, authorship, and independence are assessed separately in the source lineage. Repeated formats, quotations, and versions are not independent confirmations." } }, "provenance": { "kind": "source_review", "basis": "Rechecked source authorship and independence without changing benefit-depth ratings.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "The patient was alone and hidden from view in cardiac arrest. The automatic alerts brought CPR within 6–7 minutes. He left hospital neurologically intact, which the source presents as life-saving." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "The patient was alone and hidden from view in cardiac arrest. The automatic alerts brought CPR within 6–7 minutes. He left hospital neurologically intact, which the source presents as life-saving." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same developer and feature family: Apple Watch automatic emergency calling; Fall Detection summoned 112 for a collapsed runner, while Crash Detection placed false 911 calls for skiers, harming Apple Watch users and emergency dispatchers.", "links": [ { "database": "AI Incident 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"review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "CPR at 6–7 min, full neurological recovery", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "paired_incident": { "database": "AI Incident Database", "identifier": "463", "title": "Apple Devices Mistook Skiing Activities, Dialed False Distress Emergency Calls", "url": "https://incidentdatabase.ai/cite/463", "group": "personal", "basis": "Same developer and feature family: Apple Watch automatic emergency calling; Fall Detection summoned 112 for a collapsed runner, while Crash Detection placed false 911 calls for skiers, harming Apple Watch users and emergency dispatchers." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No development dated after the 1 January 2026 event beyond the case report and interviews already cited was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0023" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report published on 12 August 2026 describes a 69-year-old man who collapsed from ventricular fibrillation while running alone. He was on a dead-end road, hidden behind a hedge. The paper gives no date or place. The authors' hospitals are Radboud University Medical Center, Nijmegen, and Slingeland Hospital, Doetinchem. His Apple Watch (reported as Apple Watch 10) with Fall Detection enabled detected the fall. It automatically alerted his predefined emergency contacts and the emergency medical services by calling 112. Family members reached him, found him unresponsive and began cardiopulmonary resuscitation (CPR) about 6–7 minutes after the collapse. An ambulance arrived about 1.5 minutes later, defibrillated him and restored circulation. He underwent coronary artery bypass grafting and defibrillator implantation, was discharged on day 29 and made a full neurological recovery. Two interviews identify the patient as Alwi Siebers, 69, of Varsseveld, and date the collapse to 1 January 2026. Men's Health NL (28 April 2026) opens “1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland” (1 January 2026 begins for 69-year-old Alwi Siebers as an ordinary running day; the keen runner from Varsseveld is training for the Montferland half marathon). His son Tristan says “De locatie was heel precies. Hij lag achter een heg op een afgelegen plek. Zonder die melding had ik hem niet zo snel gevonden” (the location was very precise; he was lying behind a hedge in a remote spot; without that alert I would not have found him so quickly). WANT (1 May 2026) quotes Siebers, “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon” (I know from my activity log that I started my training loop at twelve past twelve). It reproduces the alert his son received, headed “do 1 jan, 12:12”. The interviews match the paper on the man's age and the Apple Watch Series 10 with fall detection. They also match on the automatic alert to 112 and to his emergency contacts, the hedge and the remote spot. They match on the son starting CPR and the daughter giving mouth-to-mouth, and a history of asthma and bronchiectasis. They match on six days in intensive care, four bypass grafts, an ICD and a full recovery. No source names both the paper and Siebers, so the identification is inferred from these details. Men's Health says that Siebers also pressed the SOS button himself and that a pulse returned within about three minutes. The paper's timeline does not support that: CPR after 6–7 minutes, four shocks, adrenaline and amiodarone before circulation returned. The street is probable but inferred. A fire-brigade pager message of 1 January 2026 at 12:18:59 records a resuscitation on the Oude Doetinchemseweg in Varsseveld. That is a dead-end road at the western edge of the village. The map in the alert screenshot shows the pin on a side road off the Doetinchemseweg. No source names the street in connection with Siebers.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 5, "reason": "The patient was alone and hidden from view in cardiac arrest. The automatic alerts brought CPR within 6–7 minutes. He left hospital neurologically intact, which the source presents as life-saving." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Fall Detection is built to recognize a hard fall and, if the wearer stays immobile, to call emergency services and notify contacts with the location. That is what it did." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Varsseveld, Gelderland, Netherlands", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Fall Detection is built to recognize a hard fall and, if the wearer stays immobile, to call emergency services and notify contacts with the location. That is what it did." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-01-01", "date_basis": "event", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Noted in the account that the Netherlands is inferred from the authors' affiliations rather than stated in the case text, and removed “at home” and “Herford district” from the Grautoff & Watol echo because the abstract gives no place or setting beyond the patient lying on the floor.", "source": "https://europepmc.org/article/PMC/PMC13543876 ; https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI:10.1007/s00399-024-01026-w&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Dated to 1 January 2026 and placed at Varsseveld from two interviews with the patient (Men's Health NL, WANT); the street, Oude Doetinchemseweg, is inferred from a dispatch log and the alert's map and marked as such; sources added.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the separate 2024 ventricular-fibrillation case from this patient's evidence and consolidated the two Men's Health excerpts. Retained the clinical report as the lead, the interviews for identification and contradictory details, and the pager reproduction only for contextual dispatch timing. Added the Apple documentation cited by the clinical paper for the device's behavior. Preserved that linking the anonymous patient to Alwi Siebers is an inference.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Moved Apple Watch Series 10 from the AI model-version field to the documented hardware configuration. Reviewed the original clinical report, patient interviews, and Apple documentation; the deployed watchOS and classifier releases remain unreported.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced “called 112” with “called emergency services” in the subtitle.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Clarified the emergency call in the subtitle without changing the underlying evidence.", "record_fields": [ "date_observed", "revisions", "date_basis", "date_precision" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch with cellular or phone connectivity", "The wearer collapses with an impact the classifier recognizes and then stays immobile", "Emergency services and contacts can reach the shared location quickly" ], "must_hold": [ "The watch has connectivity at the scene", "The collapse produces a detectable fall signature", "Responders arrive within the window in which resuscitation can succeed" ], "echoes": [ { "date": "2024-05-13", "setting": "elderly man, found by his wife lying unresponsive on the floor; place and setting not stated in the abstract (authors: EMS medical director for the District of Herford and Herford Hospital, Germany); smartwatch brand not stated in the accessible abstract (full text paywalled); watch auto-reported the fall from ventricular fibrillation to the local emergency control center, the dispatcher phoned his wife, EMS resuscitated him, discharged without long-term complications (publication date)", "outcome": "recurred", "source": "Grautoff & Watol (2024). Herzschr Elektrophys 35(2):140-143. https://doi.org/10.1007/s00399-024-01026-w" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch with cellular or phone connectivity", "The wearer collapses with an impact the classifier recognizes and then stays immobile", "Emergency services and contacts can reach the shared location quickly" ], "must_hold": [ "The watch has connectivity at the scene", "The collapse produces a detectable fall signature", "Responders arrive within the window in which resuscitation can succeed" ], "echoes": [ { "date": "2024-05-13", "setting": "elderly man, found by his wife lying unresponsive on the floor; place and setting not stated in the abstract (authors: EMS medical director for the District of Herford and Herford Hospital, Germany); smartwatch brand not stated in the accessible abstract (full text paywalled); watch auto-reported the fall from ventricular fibrillation to the local emergency control center, the dispatcher phoned his wife, EMS resuscitated him, discharged without long-term complications (publication date)", "outcome": "recurred", "source": "Grautoff & Watol (2024). Herzschr Elektrophys 35(2):140-143. https://doi.org/10.1007/s00399-024-01026-w" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 463 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/463", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Noted in the account that the Netherlands is inferred from the authors' affiliations rather than stated in the case text, and removed “at home” and “Herford district” from the Grautoff & Watol echo because the abstract gives no place or setting beyond the patient lying on the floor.", "source": "https://europepmc.org/article/PMC/PMC13543876 ; https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=DOI:10.1007/s00399-024-01026-w&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Dated to 1 January 2026 and placed at Varsseveld from two interviews with the patient (Men's Health NL, WANT); the street, Oude Doetinchemseweg, is inferred from a dispatch log and the alert's map and marked as such; sources added.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-23", "change": "Personal benefit depth changed from 4 to 5 for the reported life-preserving outcome.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed the separate 2024 ventricular-fibrillation case from this patient's evidence and consolidated the two Men's Health excerpts. Retained the clinical report as the lead, the interviews for identification and contradictory details, and the pager reproduction only for contextual dispatch timing. Added the Apple documentation cited by the clinical paper for the device's behavior. Preserved that linking the anonymous patient to Alwi Siebers is an inference.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Moved Apple Watch Series 10 from the AI model-version field to the documented hardware configuration. Reviewed the original clinical report, patient interviews, and Apple documentation; the deployed watchOS and classifier releases remain unreported.", "source": "https://europepmc.org/article/PMC/PMC13543876", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced “called 112” with “called emergency services” in the subtitle.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Clarified the emergency call in the subtitle without changing the underlying evidence.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Emergency medicine / resuscitation", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "versions_and_access": [ { "source_url": "https://europepmc.org/article/PMC/PMC13543876", "access_url": "https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13543876/fullTextXML", "status": "Full clinical text and references read." }, { "source_url": "https://support.apple.com/en-us/108896", "version": "May 6, 2026 documentation; later than the reported January event." } ], "limitations": [ "The clinical paper and interviews conflict on manual SOS and the time to return of circulation.", "No source explicitly links the named interviewee to the anonymous clinical case. The street remains inferred.", "The exact Apple classifier, learning method and deployed version are not disclosed in the cited device documentation.", "The original emergency dispatch record and raw watch logs were not available." ] } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The clinical report and patient interviews describe the rescue. They differ on manual SOS activation and the time to return of circulation. Emergency dispatch records and raw watch logs are unavailable.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Jansen CE, Jaspers Focks J, Manglani Rodriguez S, Pol L, Edgar R, van Royen N, Bonnes JL (2026). Wearable saving lives: a case report. Resuscitation Plus 31:101447.", "title": "Wearable saving lives: a case report", "url": "https://europepmc.org/article/PMC/PMC13543876", "date": "2026-08-12", "written_by": "independent", "quote": "The Apple Watch detected the fall and automatically alerted predefined emergency contacts as well as the emergency medical services by calling 112." }, { "kind": "news report", "citation": "Boerman, E. (2026). ‘Ik was voor drie minuten dood, maar mijn Apple Watch redde mijn leven’. Men's Health NL, April 28, 2026.", "title": "Hartstilstand tijdens hardlopen: Apple Watch redt leven", "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "date": "2026-04-28", "written_by": "independent", "quote": "1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland en trekt eropuit zoals hij dat al jaren doet. Toch gaat het mis. Alwi krijgt tijdens het lopen een hartstilstand." }, { "kind": "news report", "citation": "Kraak J (2026). Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert. WANT, 1 May 2026 (with the alert screenshot headed 'do 1 jan, 12:12').", "title": "Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert", "url": "https://www.want.nl/apple-watch-leven-gered-alwi-siebers/", "date": "2026-05-01", "written_by": "independent", "quote": "Het ging 1 januari van dit jaar echter mis. “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon.” Niet veel later kreeg zoon Tristan een bericht op zijn smartphone. Dat bericht was niet gestuurd door Alwi zelf, maar door zijn Apple Watch Series 10. Het was een melding dat zijn vader gevallen was." }, { "kind": "other", "citation": "112-meldingen.nl (2026). P2000 pager message, Varsseveld, 1 January 2026, 12:18:59, fire brigade Lichtenvoorde (resuscitation, privacy screen), with ambulance capcodes at 12:17 and 12:18.", "title": "Incident Oude Doetinchemseweg Varsseveld", "url": "https://112-meldingen.nl/112-varsseveld/incident-oude-doetinchemseweg-varsseveld-1402058", "date": "2026-01-01", "written_by": "unknown", "quote": "0803203 12:18:59 01-01-26 P 2 BON-02 Reanimatie (zichtscherm) Oude Doetinchemseweg Varsseveld 066371" }, { "kind": "other", "citation": "Apple. Use Fall Detection with Apple Watch, May 6, 2026; “How it works,” “What happens if your Apple Watch detects that you're immobile,” and notes 1–3.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "role": "Retained evidence sources in reviewed order" }, "provenance": { "kind": "curatorial", "basis": "Preserved existing source identifiers and appended the material technical source where applicable.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Jansen CE, Jaspers Focks J, Manglani Rodriguez S, Pol L, Edgar R, van Royen N, Bonnes JL (2026). Wearable saving lives: a case report. Resuscitation Plus 31:101447.", "title": "Wearable saving lives: a case report", "url": "https://europepmc.org/article/PMC/PMC13543876", "date": "2026-08-12", "written_by": "independent", "quote": "The Apple Watch detected the fall and automatically alerted predefined emergency contacts as well as the emergency medical services by calling 112." }, { "kind": "news report", "citation": "Boerman, E. (2026). ‘Ik was voor drie minuten dood, maar mijn Apple Watch redde mijn leven’. Men's Health NL, April 28, 2026.", "title": "Hartstilstand tijdens hardlopen: Apple Watch redt leven", "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "date": "2026-04-28", "written_by": "independent", "quote": "1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland en trekt eropuit zoals hij dat al jaren doet. Toch gaat het mis. Alwi krijgt tijdens het lopen een hartstilstand." }, { "kind": "news report", "citation": "Kraak J (2026). Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert. WANT, 1 May 2026 (with the alert screenshot headed 'do 1 jan, 12:12').", "title": "Apple Watch Series 10 redt leven van Alwi (69) en stuurt 112-melding: zelfs Tim Cook reageert", "url": "https://www.want.nl/apple-watch-leven-gered-alwi-siebers/", "date": "2026-05-01", "written_by": "independent", "quote": "Het ging 1 januari van dit jaar echter mis. “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon.” Niet veel later kreeg zoon Tristan een bericht op zijn smartphone. Dat bericht was niet gestuurd door Alwi zelf, maar door zijn Apple Watch Series 10. Het was een melding dat zijn vader gevallen was." }, { "kind": "other", "citation": "112-meldingen.nl (2026). P2000 pager message, Varsseveld, 1 January 2026, 12:18:59, fire brigade Lichtenvoorde (resuscitation, privacy screen), with ambulance capcodes at 12:17 and 12:18.", "title": "Incident Oude Doetinchemseweg Varsseveld", "url": "https://112-meldingen.nl/112-varsseveld/incident-oude-doetinchemseweg-varsseveld-1402058", "date": "2026-01-01", "written_by": "unknown", "quote": "0803203 12:18:59 01-01-26 P 2 BON-02 Reanimatie (zichtscherm) Oude Doetinchemseweg Varsseveld 066371" }, { "kind": "other", "citation": "Apple. Use Fall Detection with Apple Watch, May 6, 2026; “How it works,” “What happens if your Apple Watch detects that you're immobile,” and notes 1–3.", "title": "Use Fall Detection with Apple Watch", "url": "https://support.apple.com/en-us/108896", "date": "2026-05-06", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "lead_source_ref": "AIBD-0023-source-0001", "retained_source_order": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "origins": [ { "url": "https://europepmc.org/article/PMC/PMC13543876", "contribution": "Original clinical narrative establishes CPR timing, resuscitation, surgery and neurological recovery.", "locator": "Case report; case presentation and discussion; reference 5.", "relationship": "Treating clinical authors report the episode, separately from the device manufacturer.", "source_refs": [ "AIBD-0023-source-0001" ], "display_name": "Resuscitation Plus" }, { "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "contribution": "Interview supplies the name, January 1 event date, family testimony and conflicting SOS/recovery details.", "locator": "Opening narrative and quotations from Alwi and Tristan Siebers.", "relationship": "Original interview. The source does not identify the anonymized journal patient.", "source_refs": [ "AIBD-0023-source-0002" ] }, { "url": "https://www.want.nl/apple-watch-leven-gered-alwi-siebers/", "contribution": "Separate interview and reproduced alert screenshot provide date, watch model and location context.", "locator": "Patient and son interviews; screenshot headed “do 1 jan, 12:12”.", "relationship": "Original reporting from the same witnesses, not another clinical evaluation.", "source_refs": [ "AIBD-0023-source-0003" ] }, { "url": "https://112-meldingen.nl/112-varsseveld/incident-oude-doetinchemseweg-varsseveld-1402058", "contribution": "Reproduced P2000 dispatch gives contextual street and time.", "locator": "Message 0803203, January 1, 2026, 12:18:59.", "relationship": "Intermediary reproduction of emergency traffic. It does not identify the patient.", "source_refs": [ "AIBD-0023-source-0004" ] }, { "url": "https://support.apple.com/en-us/108896", "contribution": "Manufacturer describes automatic calling, immobility timing, connection requirements and false alerts.", "locator": "How it works; immobility section; notes 1–3.", "relationship": "Primary technical description from Apple, not validation of this rescue.", "source_refs": [ "AIBD-0023-source-0005" ] } ], "claim_chains": [ { "claim": "Resuscitation and recovery", "path": [ "https://europepmc.org/article/PMC/PMC13543876" ], "finding": "Clinical case is the original source. Its patient identity and event date are not disclosed." }, { "claim": "Identity, date, and street", "path": [ "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "https://www.want.nl/apple-watch-leven-gered-alwi-siebers/", "https://112-meldingen.nl/112-varsseveld/incident-oude-doetinchemseweg-varsseveld-1402058" ], "finding": "Interview details support an inferred match. The pager entry establishes a dispatch, not the identity of the patient." }, { "claim": "Detection and automatic calls", "path": [ "https://europepmc.org/article/PMC/PMC13543876", "Reference 5", "https://support.apple.com/en-us/108896" ], "finding": "Apple describes functional behavior and connection limits. The case report's separate DETECT-2 reference concerns a different experimental system and cannot establish the deployed Apple model." } ], "limitations": [ "The clinical paper and interviews conflict on manual SOS and the time to return of circulation.", "No source explicitly links the named interviewee to the anonymous clinical case. The street remains inferred.", "The exact Apple classifier, learning method and deployed version are not disclosed in the cited device documentation.", "The original emergency dispatch record and raw watch logs were not available." ], "excluded_or_consolidated_sources": [ { "url": "https://doi.org/10.1007/s00399-024-01026-w", "reason": "Different 2024 patient; cannot corroborate the 2026 episode." }, { "url": "https://www.menshealth.nl/nieuws/hartstilstand-tijdens-hardlopen-apple-watch-redt-leven", "reason": "Second excerpt of the same Men's Health article." } ], "review_scope": "Traced the claims in this case through accessible original publications and relevant embedded references, tables, appendices, corrections, and supplements. The stated access limits remain unresolved.", "system_identity_review": { "reviewed_on": "2026-10-24", "hardware_source_ref": "AIBD-0023-source-0001", "technical_source_ref": "AIBD-0023-source-0005", "locators": [ "Clinical report: Case description, opening paragraph", "Clinical report: reference 5", "Apple: Here's how it works; What happens if your Apple Watch detects that you're immobile" ], "finding": "The sources establish Apple Watch Series 10 and Fall Detection. They do not establish the installed watchOS version, a separate classifier name, or its release.", "excluded_identification": "The DETECT-2 algorithm in reference 10 of the clinical report is a different experimental system and cannot identify the classifier installed on the patient's Apple Watch." } } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Treating clinicians describe the rescue and recovery. Separate patient and family interviews supply the name, date, and watch hardware. Apple explains how Fall Detection works, without verifying this rescue.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Fall Detection on his Apple Watch Series 10 called emergency services, and he recovered fully after CPR and hospital treatment.", "account": "A case report published on 12 August 2026 describes a 69-year-old man who collapsed from ventricular fibrillation while running alone. He was on a dead-end road, hidden behind a hedge. The paper gives no date or place. The authors' hospitals are Radboud University Medical Center, Nijmegen, and Slingeland Hospital, Doetinchem. His Apple Watch (reported as Apple Watch 10) with Fall Detection enabled detected the fall. It automatically alerted his predefined emergency contacts and the emergency medical services by calling 112. Family members reached him, found him unresponsive and began cardiopulmonary resuscitation (CPR) about 6–7 minutes after the collapse. An ambulance arrived about 1.5 minutes later, defibrillated him and restored circulation. He underwent coronary artery bypass grafting and defibrillator implantation, was discharged on day 29 and made a full neurological recovery. Two interviews identify the patient as Alwi Siebers, 69, of Varsseveld, and date the collapse to 1 January 2026. Men's Health NL (28 April 2026) opens “1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland” (1 January 2026 begins for 69-year-old Alwi Siebers as an ordinary running day; the keen runner from Varsseveld is training for the Montferland half marathon). His son Tristan says “De locatie was heel precies. Hij lag achter een heg op een afgelegen plek. Zonder die melding had ik hem niet zo snel gevonden” (the location was very precise; he was lying behind a hedge in a remote spot; without that alert I would not have found him so quickly). WANT (1 May 2026) quotes Siebers, “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon” (I know from my activity log that I started my training loop at twelve past twelve). It reproduces the alert his son received, headed “do 1 jan, 12:12”. The interviews match the paper on the man's age and the Apple Watch Series 10 with fall detection. They also match on the automatic alert to 112 and to his emergency contacts, the hedge and the remote spot. They match on the son starting CPR and the daughter giving mouth-to-mouth, and a history of asthma and bronchiectasis. They match on six days in intensive care, four bypass grafts, an ICD and a full recovery. No source names both the paper and Siebers, so the identification is inferred from these details. Men's Health says that Siebers also pressed the SOS button himself and that a pulse returned within about three minutes. The paper's timeline does not support that: CPR after 6–7 minutes, four shocks, adrenaline and amiodarone before circulation returned. The street is probable but inferred. A fire-brigade pager message of 1 January 2026 at 12:18:59 records a resuscitation on the Oude Doetinchemseweg in Varsseveld. That is a dead-end road at the western edge of the village. The map in the alert screenshot shows the pin on a side road off the Doetinchemseweg. No source names the street in connection with Siebers." } }, "provenance": { "kind": "curatorial", "basis": "Clarified the emergency call in the subtitle without changing the underlying evidence.", "record_fields": [ "summary", "account" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "hardware": { "manufacturer": "Apple", "model": "Apple Watch Series 10", "source_wording": "Apple Watch 10", "source_ref": "AIBD-0023-source-0001", "locator": "Case description, opening paragraph" }, "feature": "Fall Detection", "feature_enabled": true, "operating_system": { "name": "watchOS", "status": "not reported for this case" }, "classifier_version": { "status": "not reported for this case" }, "qualification": "The named patient is an inferred match between the anonymous clinical report and the interviews. No software version is inferred from the hardware or event date." } }, "provenance": { "kind": "source_review", "basis": "Separated the reported watch hardware and enabled feature from the undisclosed operating-system and classifier releases.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Apple Watch Series 10 with Fall Detection.", "editor_note": "The Series 10 identification comes from interviews matched to the anonymous clinical report by the circumstances of the collapse and rescue (references 1–3). Neither source explicitly confirms that match." } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the case evidence and the relevant original technical documentation; no case-specific model identity or release was disclosed.", "record_fields": [], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "reason": "Apple names the Fall Detection feature but does not disclose a separate name for the classifier used in this case.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Apple’s classifier for Fall Detection. Apple does not publish a separate model name.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the case evidence and the relevant original technical documentation; no case-specific model identity or release was disclosed.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "reason": "The clinical report and patient interviews identify the watch hardware and Fall Detection, but they do not state the installed watchOS version or the classifier release. Apple Watch Series 10 is hardware, not an AI model version.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The installed software and classifier versions are not disclosed.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Fall Detection" } }, "provenance": { "kind": "source_review", "basis": "Identified the reported product or pipeline from its original case and technical sources; kept hardware, underlying model, and software release distinct.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0002", "AIBD-0023-source-0003", "AIBD-0023-source-0004", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Apple" }, "provenance": { "kind": "source_review", "basis": "The case identifies an Apple Watch, and Apple documents its Fall Detection feature.", "record_fields": [ "developer" ], "source_refs": [ "AIBD-0023-source-0001", "AIBD-0023-source-0005" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Fall Detection summoning help after out-of-hospital cardiac arrest", "headline": "An Apple Watch called for help after a runner’s heart stopped" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8049d87606517d6e72056f910c254541f517f3b85d1f9e8ff95f9e6782ad1ebd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after clarifying the subtitle.", "record_fields": [ "summary", "revisions" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A case report published on 12 August 2026 describes a 69-year-old man who collapsed from ventricular fibrillation while running alone. He was on a dead-end road, hidden behind a hedge. The paper gives no date or place. The authors' hospitals are Radboud University Medical Center, Nijmegen, and Slingeland Hospital, Doetinchem. His Apple Watch (reported as Apple Watch 10) with Fall Detection enabled detected the fall. It automatically alerted his predefined emergency contacts and the emergency medical services by calling 112. Family members reached him, found him unresponsive and began cardiopulmonary resuscitation (CPR) about 6–7 minutes after the collapse. An ambulance arrived about 1.5 minutes later, defibrillated him and restored circulation. He underwent coronary artery bypass grafting and defibrillator implantation, was discharged on day 29 and made a full neurological recovery. Two interviews identify the patient as Alwi Siebers, 69, of Varsseveld, and date the collapse to 1 January 2026. Men's Health NL (28 April 2026) opens “1 januari 2026 begint voor de 69-jarige Alwi Siebers als een gewone hardloopdag. De fanatieke loper uit Varsseveld is in training voor de halve marathon van Montferland” (1 January 2026 begins for 69-year-old Alwi Siebers as an ordinary running day; the keen runner from Varsseveld is training for the Montferland half marathon). His son Tristan says “De locatie was heel precies. Hij lag achter een heg op een afgelegen plek. Zonder die melding had ik hem niet zo snel gevonden” (the location was very precise; he was lying behind a hedge in a remote spot; without that alert I would not have found him so quickly). WANT (1 May 2026) quotes Siebers, “Ik weet via mijn activiteitenlog dat ik om twaalf over twaalf aan mijn trainingsrondje begon” (I know from my activity log that I started my training loop at twelve past twelve). It reproduces the alert his son received, headed “do 1 jan, 12:12”. The interviews match the paper on the man's age and the Apple Watch Series 10 with fall detection. They also match on the automatic alert to 112 and to his emergency contacts, the hedge and the remote spot. They match on the son starting CPR and the daughter giving mouth-to-mouth, and a history of asthma and bronchiectasis. They match on six days in intensive care, four bypass grafts, an ICD and a full recovery. No source names both the paper and Siebers, so the identification is inferred from these details. Men's Health says that Siebers also pressed the SOS button himself and that a pulse returned within about three minutes. The paper's timeline does not support that: CPR after 6–7 minutes, four shocks, adrenaline and amiodarone before circulation returned. The street is probable but inferred. A fire-brigade pager message of 1 January 2026 at 12:18:59 records a resuscitation on the Oude Doetinchemseweg in Varsseveld. That is a dead-end road at the western edge of the village. The map in the alert screenshot shows the pin on a side road off the Doetinchemseweg. No source names the street in connection with Siebers.", "replication": { "produced_by": [ "Fall Detection is enabled on a worn Apple Watch with cellular or phone connectivity", "The wearer collapses with an impact the classifier recognizes and then stays immobile", "Emergency services and contacts can reach the shared location quickly" ], "must_hold": [ "The watch has connectivity at the scene", "The collapse produces a detectable fall signature", "Responders arrive within the window in which resuscitation can succeed" ], "echoes": [ { "date": "2024-05-13", "setting": "elderly man, found by his wife lying unresponsive on the floor; place and setting not stated in the abstract (authors: EMS medical director for the District of Herford and Herford Hospital, Germany); smartwatch brand not stated in the accessible abstract (full text paywalled); watch auto-reported the fall from ventricular fibrillation to the local emergency control center, the dispatcher phoned his wife, EMS resuscitated him, discharged without long-term complications (publication date)", "outcome": "recurred", "source": "Grautoff & Watol (2024). Herzschr Elektrophys 35(2):140-143. https://doi.org/10.1007/s00399-024-01026-w" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 15, "record_mapped": 21, "not_assessed": 55, "complete": false, "by_state": { "value_present": 34, "not_reported": 2, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0272", "title": "Relative uses ChatGPT to navigate literature during FOLFIRINOX; pancreatic liver metastases regress, contribution undetermined", "summary": "A dentist nephew in Baku used ChatGPT, later GPT-5, to summarize literature and weigh off-label add-ons for a 65-year-old on FOLFIRINOX; 11 liver metastases regressed; the author cannot attribute it.", "date_observed": "2026-01-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Khalil (International Medical Case Reports Journal, 2026) is a dentist and the patient's nephew writing as sole author. He reports a 65-year-old with metastatic pancreatic adenosquamous carcinoma and 11 hepatic metastases treated with FOLFIRINOX. The patient and author added high-dose intravenous vitamin C, doxycycline and later azithromycin as off-label home measures. After three cycles magnetic resonance imaging (MRI) showed complete radiological regression of the hepatic lesions, confirmed around the sixth cycle. Chemotherapy stopped after six cycles. Ursodeoxycholic acid in late September 2025 resolved cholestasis. The author and patient used ChatGPT, initially an earlier model and later GPT-5. They used it to search and summarize literature, interpret CA 19–9 during cholestasis and appraise data on adjunctive interventions. The author writes that GPT “materially influenced how we navigated information”. He also states that the single case cannot determine the contribution of those interventions to the response. No attributable change in diagnosis or treatment can be established from the sources on record. The clinical course ran through 2025.", "category": "general benefit", "unexpected": false, "purpose": "Patient-side literature navigation and summarization during cancer treatment", "system": "ChatGPT (an earlier model, later GPT-5)", "model_version": "GPT-5 (later phase); earlier model unspecified", "developer": "OpenAI", "deployer": "The patient's nephew (Uzman Dent, Baku) with the patient", "location": "Baku, Azerbaijan (surgery and pathology performed in Turkey)", "domain": "Health; oncology", "segment": "Patients and families navigating cancer care", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The AI's part was literature summary; the metastasis regression is not attributed.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Complete radiological regression occurred on FOLFIRINOX. But the author states the case cannot determine the contribution of the model-informed adjuncts." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome." }, { "group": "societal", "depth": null, "reason": "Single case." } ], "ai_role": { "status": "assessed", "statement": "ChatGPT's role, per the author, was literature navigation and summarization that shaped which supportive options the family considered. The author reports no efficacy claim and warns that outputs may be incorrect. The outcome is not attributable to the model." }, "evidence": [ { "kind": "case report", "citation": "Khalil ST. Int Med Case Rep J (2026), doi 10.2147/IMCRJ.S639766", "title": "Complete Regression of 11 Hepatic Metastases in Metastatic Pancreatic Adenosquamous Carcinoma and the Role of GPT in Patient Navigation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13644719/", "date": "2026-01-01", "written_by": "deployer", "quote": "GPT materially influenced how we navigated information and considered supportive options" }, { "kind": "case report", "citation": "Khalil ST. 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Int Med Case Rep J (2026), doi 10.2147/IMCRJ.S639766", "title": "Complete Regression of 11 Hepatic Metastases in Metastatic Pancreatic Adenosquamous Carcinoma and the Role of GPT in Patient Navigation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13644719/", "date": "2026-01-01", "written_by": "deployer", "quote": "GPT materially influenced how we navigated information and considered supportive options" }, { "kind": "case report", "citation": "Khalil ST. Int Med Case Rep J (2026), discussion", "title": "Complete Regression of 11 Hepatic Metastases in Metastatic Pancreatic Adenosquamous Carcinoma and the Role of GPT in Patient Navigation", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13644719/", "date": "2026-01-01", "written_by": "deployer", "quote": "this single case cannot determine the contribution of those adjunctive interventions to the observed radiological response." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A dentist nephew in Baku used ChatGPT, later GPT-5, to summarize literature and weigh off-label add-ons for a 65-year-old on FOLFIRINOX; 11 liver metastases regressed; the author cannot attribute it.", "account": "Khalil (International Medical Case Reports Journal, 2026) is a dentist and the patient's nephew writing as sole author. He reports a 65-year-old with metastatic pancreatic adenosquamous carcinoma and 11 hepatic metastases treated with FOLFIRINOX. The patient and author added high-dose intravenous vitamin C, doxycycline and later azithromycin as off-label home measures. After three cycles magnetic resonance imaging (MRI) showed complete radiological regression of the hepatic lesions, confirmed around the sixth cycle. Chemotherapy stopped after six cycles. Ursodeoxycholic acid in late September 2025 resolved cholestasis. The author and patient used ChatGPT, initially an earlier model and later GPT-5. They used it to search and summarize literature, interpret CA 19–9 during cholestasis and appraise data on adjunctive interventions. The author writes that GPT “materially influenced how we navigated information”. He also states that the single case cannot determine the contribution of those interventions to the response. No attributable change in diagnosis or treatment can be established from the sources on record. The clinical course ran through 2025." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "ChatGPT helped the author find and summarize relevant literature." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The later phase used GPT-5. The earlier phase’s model is not identified in the existing account." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GPT-5 in the later phase." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "GPT-5 (later phase); earlier model unspecified" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (an earlier model, later GPT-5)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Relative uses ChatGPT to navigate literature during FOLFIRINOX; pancreatic liver metastases regress, contribution undetermined", "headline": "Nephew uses ChatGPT during FOLFIRINOX; liver metastases regress" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "21651f0f623c4aad576aeb1a62c3c343404831855be984da6a47494c2d41f904" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Khalil (International Medical Case Reports Journal, 2026) is a dentist and the patient's nephew writing as sole author. He reports a 65-year-old with metastatic pancreatic adenosquamous carcinoma and 11 hepatic metastases treated with FOLFIRINOX. The patient and author added high-dose intravenous vitamin C, doxycycline and later azithromycin as off-label home measures. After three cycles magnetic resonance imaging (MRI) showed complete radiological regression of the hepatic lesions, confirmed around the sixth cycle. Chemotherapy stopped after six cycles. Ursodeoxycholic acid in late September 2025 resolved cholestasis. The author and patient used ChatGPT, initially an earlier model and later GPT-5. They used it to search and summarize literature, interpret CA 19–9 during cholestasis and appraise data on adjunctive interventions. The author writes that GPT “materially influenced how we navigated information”. He also states that the single case cannot determine the contribution of those interventions to the response. No attributable change in diagnosis or treatment can be established from the sources on record. The clinical course ran through 2025.", "replication": { "produced_by": [ "Family member with medical training prompting a general-purpose model for literature summaries", "Standard FOLFIRINOX chemotherapy" ], "must_hold": [ "Treating oncologists remain responsible for decisions", "Model outputs verified against sources" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0185", "title": "ChatGPT flags red flags on a fake pre-IPO adviser; 77-year-old in Bengaluru reports Rs 67.10 lakh fraud to police", "summary": "After withdrawals were refused, a 77-year-old Binnypet resident checked the firm's credentials with ChatGPT, which flagged complaints and inconsistencies; he reported the Rs 67.10 lakh fraud to Ben...", "date_observed": "2026-01-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.", "category": "protective response", "unexpected": false, "purpose": "General-purpose conversational assistant that answers users' questions.", "system": "ChatGPT", "model_version": null, "developer": "OpenAI", "deployer": "The victim, using the consumer app himself", "location": "Bengaluru, India", "domain": "Investment fraud", "segment": "Pre-IPO share scam", "benefit_type": "Reduced Risk", "taxonomy_note": "The loss had occurred; the good is recognition and reporting of the fraud.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read." }, { "group": "societal", "depth": null, "reason": "No outcome beyond the single complaint is documented." }, { "group": "organizational", "depth": null, "reason": "The police registered a case. No organizational outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "Both reports attribute the discovery to ChatGPT's response flagging complaints and credential inconsistencies when the victim queried the firm. That came after his own suspicion at refused withdrawals. The exact output is not reproduced. OpenAI had no role beyond providing the consumer product." }, "evidence": [ { "kind": "news report", "citation": "The New Indian Express, Bengaluru, 6 January 2026", "title": "ChatGPT alert helps Bengaluru senior citizen uncover Rs 67 lakh pre-IPO investment fraud", "url": "https://www.newindianexpress.com/cities/bengaluru/2026/Jan/06/chatgpt-alert-helps-bengaluru-senior-citizen-uncover-rs-67-lakh-pre-ipo-investment-fraud", "date": "2026-01-06", "written_by": "independent", "quote": "The fraud came to light after the victim checked the firm's credentials using ChatGPT, which flagged multiple warning signs." }, { "kind": "news report", "citation": "Prajwal D'Souza, Deccan Herald, 6 January 2026", "title": "Bengaluru: ChatGPT response saves 77-year-old man from losing more money to cybercriminals", "url": "https://www.deccanherald.com/india/karnataka/bengaluru/bengaluru-chatgpt-response-saves-77-year-old-man-from-losing-more-money-to-cybercriminals-3853142", "date": "2026-01-06", "written_by": "independent", "quote": "The scammers had already cheated him of Rs 67.10 lakh through a fake investment scam." } ], "replication": { "produced_by": [ "A victim querying a large language model about a company and its representatives after withdrawals were refused", "Public complaints and credential inconsistencies about the scheme that the model could surface" ], "must_hold": [ "Suspicion arising before further payments", "Model output that points to specific red flags rather than generic caution", "Police registration for any tracing or recovery" ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT flags fake adviser; victim reports Rs 67.10 lakh fraud", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "Reports as of January 2026 say a case was registered and the money trail is being traced; no arrest or recovery was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0185", "catalog_version": "1.0.0", "source_fingerprint": "f6c0a087d5b24db8a8b779d822e10293d456ab2962ad17de12e5fcfedd1835c7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0185-source-0001", "AIBD-0185-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "The victim, using the consumer app himself" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Both reports attribute the discovery to ChatGPT's response flagging complaints and credential inconsistencies when the victim queried the firm. That came after his own suspicion at refused withdrawals. The exact output is not reproduced. OpenAI had no role beyond providing the consumer product." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "Both reports attribute the discovery to ChatGPT's response flagging complaints and credential inconsistencies when the victim queried the firm. That came after his own suspicion at refused withdrawals. The exact output is not reproduced. OpenAI had no role beyond providing the consumer product." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read." }, { "group": "societal", "reason": "No outcome beyond the single complaint is documented." }, { "group": "organizational", "reason": "The police registered a case. No organizational outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read." }, { "group": "societal", "reason": "No outcome beyond the single complaint is documented." }, { "group": "organizational", "reason": "The police registered a case. No organizational outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read." }, { "group": "societal", "reason": "No outcome beyond the single complaint is documented." }, { "group": "organizational", "reason": "The police registered a case. No organizational outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Reports as of January 2026 say a case was registered and the money trail is being traced; no arrest or recovery was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0185" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "The loss had occurred; the good is recognition and reporting of the fraud." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read." }, { "group": "societal", "reason": "No outcome beyond the single complaint is documented." }, { "group": "organizational", "reason": "The police registered a case. No organizational outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "General-purpose conversational assistant that answers users' questions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Bengaluru, India", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "General-purpose conversational assistant that answers users' questions." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-01-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A victim querying a large language model about a company and its representatives after withdrawals were refused", "Public complaints and credential inconsistencies about the scheme that the model could surface" ], "must_hold": [ "Suspicion arising before further payments", "Model output that points to specific red flags rather than generic caution", "Police registration for any tracing or recovery" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0185-source-0001", "AIBD-0185-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The New Indian Express, Bengaluru, 6 January 2026", "title": "ChatGPT alert helps Bengaluru senior citizen uncover Rs 67 lakh pre-IPO investment fraud", "url": "https://www.newindianexpress.com/cities/bengaluru/2026/Jan/06/chatgpt-alert-helps-bengaluru-senior-citizen-uncover-rs-67-lakh-pre-ipo-investment-fraud", "date": "2026-01-06", "written_by": "independent", "quote": "The fraud came to light after the victim checked the firm's credentials using ChatGPT, which flagged multiple warning signs." }, { "kind": "news report", "citation": "Prajwal D'Souza, Deccan Herald, 6 January 2026", "title": "Bengaluru: ChatGPT response saves 77-year-old man from losing more money to cybercriminals", "url": "https://www.deccanherald.com/india/karnataka/bengaluru/bengaluru-chatgpt-response-saves-77-year-old-man-from-losing-more-money-to-cybercriminals-3853142", "date": "2026-01-06", "written_by": "independent", "quote": "The scammers had already cheated him of Rs 67.10 lakh through a fake investment scam." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "After withdrawals were refused, a 77-year-old Binnypet resident checked the firm's credentials with ChatGPT, which flagged complaints and inconsistencies; he reported the Rs 67.10 lakh fraud to Ben...", "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ChatGPT flags red flags on a fake pre-IPO adviser; 77-year-old in Bengaluru reports Rs 67.10 lakh fraud to police", "headline": "ChatGPT flags fake adviser; victim reports Rs 67.10 lakh fraud" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f6c0a087d5b24db8a8b779d822e10293d456ab2962ad17de12e5fcfedd1835c7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.", "replication": { "produced_by": [ "A victim querying a large language model about a company and its representatives after withdrawals were refused", "Public complaints and credential inconsistencies about the scheme that the model could surface" ], "must_hold": [ "Suspicion arising before further payments", "Model output that points to specific red flags rather than generic caution", "Police registration for any tracing or recovery" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0156", "title": "thynC remote central monitor flags ventricular tachycardia at 192 bpm in an 85-year-old on a general ward of Gwangju Hanguk Hospital; staff resuscitate the patient within the golden time (14 January 2026)", "summary": "thynC alarm flagged ventricular tachycardia in an 85-year-old on a Gwangju general ward; staff CPR restored circulation, 14 January 2026.", "date_observed": "2026-01-14", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 14 January 2026 at about 3:10 p.m., an 85-year-old patient's heart rate climbed to 192 beats per minute. The patient was on a general ward of Gwangju Hanguk Hospital (광주한국병원) in Gwangju, South Korea. thynC had monitored the patient since 9 January because of cardiovascular risk factors at admission. thynC's remote central monitor flagged ventricular tachycardia, a precursor sign of cardiac arrest, and alarmed. Staff who ran to the room found seizure-like movements, reduced consciousness and no spontaneous breathing. They performed cardiopulmonary resuscitation (CPR) and artificial respiration. The heartbeat and circulation returned, and the patient was moved to intensive care. Daewoong Pharmaceutical, which supplies thynC, announced the case on 11 February 2026 with statements from the hospital's directors and nursing manager.", "category": "harm prevented", "unexpected": false, "purpose": "The hospital and Daewoong Pharmaceutical describe thynC as an AI-based smart bed monitoring system. It measures electrocardiogram (ECG), heart rate and respiratory rate through wearable devices. It sends an alarm to a central monitor when an abnormal sign appears. So patients on a general ward, where staff cannot stay at every bedside, are watched in real time as in an intensive care unit. Staff can respond early to deterioration. Flagging a pre-arrest arrhythmia and summoning staff is exactly that design. Daewoong's hospital-division head describes thynC as built to recognize changes in a patient's condition early and help medical staff respond quickly.", "system": "thynC (씽크) AI-based smart bed monitoring system: wearable sensors measuring ECG, heart rate and respiratory rate in real time, with alarms sent to a remote central monitor", "model_version": null, "developer": "Not stated in the read reports, which describe thynC as the smart bed monitoring system that Daewoong Pharmaceutical supplies (자사 공급)", "deployer": "Gwangju Hanguk Hospital (광주한국병원)", "location": "Gwangju, South Korea", "domain": "Healthcare (inpatient monitoring / cardiac arrest)", "segment": "Hospital general-ward remote patient monitoring", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-02-11-8bc8" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The hospital reports that the alarm brought staff to a patient in ventricular tachycardia who had stopped breathing. It reports that CPR within the golden time restored heartbeat and circulation, and that the patient went to intensive care. The hospital calls this averting a cardiac-arrest crisis. But survival to discharge and neurological outcome are not reported. The account was released by the system's supplier. So a life saved is not established." } ], "ai_role": { "status": "assessed", "statement": "The system's contribution was detection and summons. The wearable ECG stream showed the heart rate climbing to 192 beats per minute. The remote central monitor identified ventricular tachycardia and raised an alarm. The attending director says that is how staff learned of it at once and reached the bedside to begin CPR within the golden time. The resuscitation itself was done by people. The counterfactual rests on the hospital's framing that general-ward patients are not under continuous observation and that deterioration can be noticed late. How long this patient would otherwise have gone unobserved is not recorded. No medical record or independent assessment has been published. The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026." }, "evidence": [ { "kind": "news report", "citation": "Kim D-M (2026). 대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”. IT Chosun, 11 February 2026 (reporting a Daewoong Pharmaceutical announcement of the same day).", "title": "대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”", "url": "https://it.chosun.com/news/articleView.html?idxno=2023092156866", "date": "2026-02-11", "written_by": "independent", "quote": "대웅제약은 자사 공급 스마트 병상 모니터링 시스템 ‘씽크(thynC)’가 입원 환자의 위급 상황을 실시간으로 포착해 심정지 위기를 막았다고 11일 밝혔다." }, { "kind": "news report", "citation": "Jung D-H (2026). 급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응. Asia Economy (아시아경제), 11 February 2026.", "title": "급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응", "url": "https://www.asiae.co.kr/article/2026021109383216218", "date": "2026-02-11", "written_by": "independent", "quote": "중앙 모니터 알람을 통해 심실빈맥을 즉시 확인하고 현장으로 출동해 골든타임 내 심폐소생술을 시행할 수 있었다" }, { "kind": "news report", "citation": "Lee Y-S (2026). 'AI'가 급성 심정지 감지..환자 골든타임 '선제적 대응'. Wolyo News (월요신문), 11 February 2026.", "title": "'AI'가 급성 심정지 감지...환자 골든타임 '선제적 대응'", "url": "https://www.wolyo.co.kr/news/articleView.html?idxno=308709", "date": "2026-02-11", "written_by": "independent", "quote": "지난 1월14일 오후 3시 10분경 광주한국병원 일반 병동에 입원 중이던 85세 환자의 심박수가 분당 192회까지 급격하게 상승하며" }, { "kind": "news report", "citation": "Shin D-H (2026). 대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인. PinPoint News (핀포인트뉴스), 11 February 2026.", "title": "대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인", "url": "https://www.pinpointnews.co.kr/news/articleView.html?idxno=428348", "date": "2026-02-11", "written_by": "independent", "quote": "실시간 원격 환자 모니터링 시스템이 위기 상황을 막는 데 결정적인 역할을 한다" }, { "kind": "news report", "citation": "Kim S-Y (2026). 대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응. Newspim (뉴스핌), 11 February 2026.", "title": "대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응", "url": "https://www.newspim.com/news/view/20260211000281", "date": "2026-02-11", "written_by": "independent", "quote": "씽크는 환자 상태 변화를 조기에 인지하고, 의료진의 신속한 대응을 돕기 위해 설계된 스마트 병상 모니터링 시스템" }, { "kind": "news report", "citation": "Lee S-M (2026). 대웅제약, 전남대·화순전남대병원에 씽크 도입. Asia Economy (아시아경제), 19 June 2026.", "title": "대웅제약, 전남대·화순전남대병원에 씽크 도입", "url": "https://view.asiae.co.kr/article/2026061909071730057", "date": "2026-06-19", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "thynC wearable monitoring of ECG, heart rate and respiratory rate, linked to a remote central monitor on a general ward. It started on 9 January 2026 because the patient had cardiovascular risk factors at admission", "An alarm raised the moment the heart rate climbed to 192 beats per minute and the monitor identified ventricular tachycardia", "Ward staff who went to the bedside on the alarm and performed CPR and artificial respiration within the golden time. The reports put that time at four minutes for acute cardiac arrest, citing National Fire Agency data" ], "must_hold": [ "The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026. The hospital's attending director, chief director and nursing manager are quoted. But no medical record, case report or independent review has been published", "Only the return of heartbeat and circulation and the transfer to intensive care are reported. Survival to discharge and neurological outcome are not", "The alarm shortens the time to detection, not the treatment. The benefit depends on staff who can reach the bedside and resuscitate within minutes. The nursing manager says that is hardest to guarantee at night and when staffing is thin" ], "echoes": [] }, "paired_incident": null, "headline": "thynC flags ventricular tachycardia; CPR restores circulation", "metric": "a heart rate that climbed to 192 beats per minute", "comparator": null, "later": { "status": "scaled", "date": "2026-06-19", "note": "Daewoong completed thynC installations covering 558 beds at Chonnam National University Hospital and Hwasun Chonnam National University Hospital, the largest national-university-hospital deployment so far, among several 2026 hospital rollouts.", "quote": "총 558병상 규모(전남대병원 217병상·화순전남대병원 341병상)로 진행된 이번 사업은 국립대병원 최대 규모의 씽크 구축 사례로, 호남권 상급종합병원의 스마트병동 전환을 본격화하는 계기가 될 것으로 회사는 기대한다.", "url": "https://view.asiae.co.kr/article/2026061909071730057" }, "value": null, "developer_country": null, "deployer_country": "South Korea", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Date set to 14 January 2026, the alarm as dated in every cited report, rather than the Monitor's 11 February 2026, which is the announcement date.", "source": "https://oecd.ai/en/incidents/2026-02-11-8bc8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://view.asiae.co.kr/article/2026061909071730057", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hkh.co.kr/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0156", "catalog_version": "1.0.0", "source_fingerprint": "a5b48e157f25e69294c2ff2ab95ef27812324613d4e0980d585a7e10d28f9541", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0156-source-0001", "AIBD-0156-source-0002", "AIBD-0156-source-0003", "AIBD-0156-source-0004", "AIBD-0156-source-0005", "AIBD-0156-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated in the read reports, which describe thynC as the smart bed monitoring system that Daewoong Pharmaceutical supplies (자사 공급)", "deployer": "Gwangju Hanguk Hospital (광주한국병원)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's contribution was detection and summons. The wearable ECG stream showed the heart rate climbing to 192 beats per minute. The remote central monitor identified ventricular tachycardia and raised an alarm. The attending director says that is how staff learned of it at once and reached the bedside to begin CPR within the golden time. The resuscitation itself was done by people. The counterfactual rests on the hospital's framing that general-ward patients are not under continuous observation and that deterioration can be noticed late. How long this patient would otherwise have gone unobserved is not recorded. No medical record or independent assessment has been published. The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The thynC system detected ventricular tachycardia in a wearable ECG feed and raised an alarm. The hospital reported that staff reached the bedside promptly and began CPR.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The system's contribution was detection and summons. The wearable ECG stream showed the heart rate climbing to 192 beats per minute. The remote central monitor identified ventricular tachycardia and raised an alarm. The attending director says that is how staff learned of it at once and reached the bedside to begin CPR within the golden time. The resuscitation itself was done by people. The counterfactual rests on the hospital's framing that general-ward patients are not under continuous observation and that deterioration can be noticed late. How long this patient would otherwise have gone unobserved is not recorded. No medical record or independent assessment has been published. The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The hospital reports that the alarm brought staff to a patient in ventricular tachycardia who had stopped breathing. It reports that CPR within the golden time restored heartbeat and circulation, and that the patient went to intensive care. The hospital calls this averting a cardiac-arrest crisis. But survival to discharge and neurological outcome are not reported. The account was released by the system's supplier. So a life saved is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The hospital reports that the alarm brought staff to a patient in ventricular tachycardia who had stopped breathing. It reports that CPR within the golden time restored heartbeat and circulation, and that the patient went to intensive care. The hospital calls this averting a cardiac-arrest crisis. But survival to discharge and neurological outcome are not reported. The account was released by the system's supplier. So a life saved is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The hospital reports that staff reached a patient who had stopped breathing. It reports that CPR restored heartbeat and circulation, and that the patient was transferred to intensive care. Later survival and neurological recovery are not reported." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The hospital reports that the alarm brought staff to a patient in ventricular tachycardia who had stopped breathing. It reports that CPR within the golden time restored heartbeat and circulation, and that the patient went to intensive care. The hospital calls this averting a cardiac-arrest crisis. But survival to discharge and neurological outcome are not reported. The account was released by the system's supplier. So a life saved is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The hospital reports a heart rate that reached 192 beats per minute, followed by restored heartbeat and circulation after CPR. The patient was transferred to intensive care." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Heart rate, rhythm, and the response that followed resuscitation." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Daewoong Pharmaceutical released the hospital’s account. No medical record or independent review has been published. The reports do not give survival to discharge, neurological recovery, or the delay that would have occurred without the alarm." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-02-11-8bc8" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-06-19", "note": "Daewoong completed thynC installations covering 558 beds at Chonnam National University Hospital and Hwasun Chonnam National University Hospital, the largest national-university-hospital deployment so far, among several 2026 hospital rollouts.", "quote": "총 558병상 규모(전남대병원 217병상·화순전남대병원 341병상)로 진행된 이번 사업은 국립대병원 최대 규모의 씽크 구축 사례로, 호남권 상급종합병원의 스마트병동 전환을 본격화하는 계기가 될 것으로 회사는 기대한다.", "url": "https://view.asiae.co.kr/article/2026061909071730057" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Hospital staff responded to the alarm and performed CPR." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0156" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "An 85-year-old patient at Gwangju Hanguk Hospital." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "An 85-year-old patient at Gwangju Hanguk Hospital." } }, "outcomes[].beneficiary_count": { "state": "value_present", "value": { "kind": "text", "text": "One patient." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "One patient." } }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 January 2026 at about 3:10 p.m., an 85-year-old patient's heart rate climbed to 192 beats per minute. The patient was on a general ward of Gwangju Hanguk Hospital (광주한국병원) in Gwangju, South Korea. thynC had monitored the patient since 9 January because of cardiovascular risk factors at admission. thynC's remote central monitor flagged ventricular tachycardia, a precursor sign of cardiac arrest, and alarmed. Staff who ran to the room found seizure-like movements, reduced consciousness and no spontaneous breathing. They performed cardiopulmonary resuscitation (CPR) and artificial respiration. The heartbeat and circulation returned, and the patient was moved to intensive care. Daewoong Pharmaceutical, which supplies thynC, announced the case on 11 February 2026 with statements from the hospital's directors and nursing manager.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Staff restored the patient’s heartbeat and circulation after an alert that prompted them to reach the bedside." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The hospital reports that the alarm brought staff to a patient in ventricular tachycardia who had stopped breathing. It reports that CPR within the golden time restored heartbeat and circulation, and that the patient went to intensive care. The hospital calls this averting a cardiac-arrest crisis. But survival to discharge and neurological outcome are not reported. The account was released by the system's supplier. So a life saved is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The hospital and Daewoong Pharmaceutical describe thynC as an AI-based smart bed monitoring system. It measures electrocardiogram (ECG), heart rate and respiratory rate through wearable devices. It sends an alarm to a central monitor when an abnormal sign appears. So patients on a general ward, where staff cannot stay at every bedside, are watched in real time as in an intensive care unit. Staff can respond early to deterioration. Flagging a pre-arrest arrhythmia and summoning staff is exactly that design. Daewoong's hospital-division head describes thynC as built to recognize changes in a patient's condition early and help medical staff respond quickly." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Gwangju, South Korea", "deployer_country": "South Korea" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The hospital and Daewoong Pharmaceutical describe thynC as an AI-based smart bed monitoring system. It measures electrocardiogram (ECG), heart rate and respiratory rate through wearable devices. It sends an alarm to a central monitor when an abnormal sign appears. So patients on a general ward, where staff cannot stay at every bedside, are watched in real time as in an intensive care unit. Staff can respond early to deterioration. Flagging a pre-arrest arrhythmia and summoning staff is exactly that design. Daewoong's hospital-division head describes thynC as built to recognize changes in a patient's condition early and help medical staff respond quickly." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-01-14", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Date set to 14 January 2026, the alarm as dated in every cited report, rather than the Monitor's 11 February 2026, which is the announcement date.", "source": "https://oecd.ai/en/incidents/2026-02-11-8bc8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://view.asiae.co.kr/article/2026061909071730057", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hkh.co.kr/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "thynC wearable monitoring of ECG, heart rate and respiratory rate, linked to a remote central monitor on a general ward. It started on 9 January 2026 because the patient had cardiovascular risk factors at admission", "An alarm raised the moment the heart rate climbed to 192 beats per minute and the monitor identified ventricular tachycardia", "Ward staff who went to the bedside on the alarm and performed CPR and artificial respiration within the golden time. The reports put that time at four minutes for acute cardiac arrest, citing National Fire Agency data" ], "must_hold": [ "The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026. The hospital's attending director, chief director and nursing manager are quoted. But no medical record, case report or independent review has been published", "Only the return of heartbeat and circulation and the transfer to intensive care are reported. Survival to discharge and neurological outcome are not", "The alarm shortens the time to detection, not the treatment. The benefit depends on staff who can reach the bedside and resuscitate within minutes. The nursing manager says that is hardest to guarantee at night and when staffing is thin" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Staff must receive the alert and reach the patient within minutes. The nursing manager said that prompt response was harder to ensure at night or with fewer staff." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Date set to 14 January 2026, the alarm as dated in every cited report, rather than the Monitor's 11 February 2026, which is the announcement date.", "source": "https://oecd.ai/en/incidents/2026-02-11-8bc8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://view.asiae.co.kr/article/2026061909071730057", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://www.hkh.co.kr/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (inpatient monitoring / cardiac arrest)", "segment": "Hospital general-ward remote patient monitoring" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kim D-M (2026). 대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”. IT Chosun, 11 February 2026 (reporting a Daewoong Pharmaceutical announcement of the same day).", "title": "대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”", "url": "https://it.chosun.com/news/articleView.html?idxno=2023092156866", "date": "2026-02-11", "written_by": "independent", "quote": "대웅제약은 자사 공급 스마트 병상 모니터링 시스템 ‘씽크(thynC)’가 입원 환자의 위급 상황을 실시간으로 포착해 심정지 위기를 막았다고 11일 밝혔다." }, { "kind": "news report", "citation": "Jung D-H (2026). 급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응. Asia Economy (아시아경제), 11 February 2026.", "title": "급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응", "url": "https://www.asiae.co.kr/article/2026021109383216218", "date": "2026-02-11", "written_by": "independent", "quote": "중앙 모니터 알람을 통해 심실빈맥을 즉시 확인하고 현장으로 출동해 골든타임 내 심폐소생술을 시행할 수 있었다" }, { "kind": "news report", "citation": "Lee Y-S (2026). 'AI'가 급성 심정지 감지..환자 골든타임 '선제적 대응'. Wolyo News (월요신문), 11 February 2026.", "title": "'AI'가 급성 심정지 감지...환자 골든타임 '선제적 대응'", "url": "https://www.wolyo.co.kr/news/articleView.html?idxno=308709", "date": "2026-02-11", "written_by": "independent", "quote": "지난 1월14일 오후 3시 10분경 광주한국병원 일반 병동에 입원 중이던 85세 환자의 심박수가 분당 192회까지 급격하게 상승하며" }, { "kind": "news report", "citation": "Shin D-H (2026). 대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인. PinPoint News (핀포인트뉴스), 11 February 2026.", "title": "대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인", "url": "https://www.pinpointnews.co.kr/news/articleView.html?idxno=428348", "date": "2026-02-11", "written_by": "independent", "quote": "실시간 원격 환자 모니터링 시스템이 위기 상황을 막는 데 결정적인 역할을 한다" }, { "kind": "news report", "citation": "Kim S-Y (2026). 대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응. Newspim (뉴스핌), 11 February 2026.", "title": "대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응", "url": "https://www.newspim.com/news/view/20260211000281", "date": "2026-02-11", "written_by": "independent", "quote": "씽크는 환자 상태 변화를 조기에 인지하고, 의료진의 신속한 대응을 돕기 위해 설계된 스마트 병상 모니터링 시스템" }, { "kind": "news report", "citation": "Lee S-M (2026). 대웅제약, 전남대·화순전남대병원에 씽크 도입. Asia Economy (아시아경제), 19 June 2026.", "title": "대웅제약, 전남대·화순전남대병원에 씽크 도입", "url": "https://view.asiae.co.kr/article/2026061909071730057", "date": "2026-06-19", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0156-source-0001", "AIBD-0156-source-0002", "AIBD-0156-source-0003", "AIBD-0156-source-0004", "AIBD-0156-source-0005", "AIBD-0156-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kim D-M (2026). 대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”. IT Chosun, 11 February 2026 (reporting a Daewoong Pharmaceutical announcement of the same day).", "title": "대웅제약 ‘씽크’, 급성 심정지 막았다… “AI가 골든타임 포착”", "url": "https://it.chosun.com/news/articleView.html?idxno=2023092156866", "date": "2026-02-11", "written_by": "independent", "quote": "대웅제약은 자사 공급 스마트 병상 모니터링 시스템 ‘씽크(thynC)’가 입원 환자의 위급 상황을 실시간으로 포착해 심정지 위기를 막았다고 11일 밝혔다." }, { "kind": "news report", "citation": "Jung D-H (2026). 급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응. Asia Economy (아시아경제), 11 February 2026.", "title": "급성 심정지, AI가 전조 포착… 광주한국병원 '씽크'로 조기 대응", "url": "https://www.asiae.co.kr/article/2026021109383216218", "date": "2026-02-11", "written_by": "independent", "quote": "중앙 모니터 알람을 통해 심실빈맥을 즉시 확인하고 현장으로 출동해 골든타임 내 심폐소생술을 시행할 수 있었다" }, { "kind": "news report", "citation": "Lee Y-S (2026). 'AI'가 급성 심정지 감지..환자 골든타임 '선제적 대응'. Wolyo News (월요신문), 11 February 2026.", "title": "'AI'가 급성 심정지 감지...환자 골든타임 '선제적 대응'", "url": "https://www.wolyo.co.kr/news/articleView.html?idxno=308709", "date": "2026-02-11", "written_by": "independent", "quote": "지난 1월14일 오후 3시 10분경 광주한국병원 일반 병동에 입원 중이던 85세 환자의 심박수가 분당 192회까지 급격하게 상승하며" }, { "kind": "news report", "citation": "Shin D-H (2026). 대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인. PinPoint News (핀포인트뉴스), 11 February 2026.", "title": "대웅제약, 광주한국병원서 '씽크' 심정지 대응 사례 확인", "url": "https://www.pinpointnews.co.kr/news/articleView.html?idxno=428348", "date": "2026-02-11", "written_by": "independent", "quote": "실시간 원격 환자 모니터링 시스템이 위기 상황을 막는 데 결정적인 역할을 한다" }, { "kind": "news report", "citation": "Kim S-Y (2026). 대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응. Newspim (뉴스핌), 11 February 2026.", "title": "대웅제약 '씽크' 심정지 위기 막아…광주한국병원 조기 대응", "url": "https://www.newspim.com/news/view/20260211000281", "date": "2026-02-11", "written_by": "independent", "quote": "씽크는 환자 상태 변화를 조기에 인지하고, 의료진의 신속한 대응을 돕기 위해 설계된 스마트 병상 모니터링 시스템" }, { "kind": "news report", "citation": "Lee S-M (2026). 대웅제약, 전남대·화순전남대병원에 씽크 도입. Asia Economy (아시아경제), 19 June 2026.", "title": "대웅제약, 전남대·화순전남대병원에 씽크 도입", "url": "https://view.asiae.co.kr/article/2026061909071730057", "date": "2026-06-19", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "thynC alarm flagged ventricular tachycardia in an 85-year-old on a Gwangju general ward; staff CPR restored circulation, 14 January 2026.", "account": "On 14 January 2026 at about 3:10 p.m., an 85-year-old patient's heart rate climbed to 192 beats per minute. The patient was on a general ward of Gwangju Hanguk Hospital (광주한국병원) in Gwangju, South Korea. thynC had monitored the patient since 9 January because of cardiovascular risk factors at admission. thynC's remote central monitor flagged ventricular tachycardia, a precursor sign of cardiac arrest, and alarmed. Staff who ran to the room found seizure-like movements, reduced consciousness and no spontaneous breathing. They performed cardiopulmonary resuscitation (CPR) and artificial respiration. The heartbeat and circulation returned, and the patient was moved to intensive care. Daewoong Pharmaceutical, which supplies thynC, announced the case on 11 February 2026 with statements from the hospital's directors and nursing manager." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "thynC (씽크) AI-based smart bed monitoring system: wearable sensors measuring ECG, heart rate and respiratory rate in real time, with alarms sent to a remote central monitor" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated in the read reports, which describe thynC as the smart bed monitoring system that Daewoong Pharmaceutical supplies (자사 공급)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "thynC remote central monitor flags ventricular tachycardia at 192 bpm in an 85-year-old on a general ward of Gwangju Hanguk Hospital; staff resuscitate the patient within the golden time (14 January 2026)", "headline": "thynC flags ventricular tachycardia; CPR restores circulation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a5b48e157f25e69294c2ff2ab95ef27812324613d4e0980d585a7e10d28f9541" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 14 January 2026 at about 3:10 p.m., an 85-year-old patient's heart rate climbed to 192 beats per minute. The patient was on a general ward of Gwangju Hanguk Hospital (광주한국병원) in Gwangju, South Korea. thynC had monitored the patient since 9 January because of cardiovascular risk factors at admission. thynC's remote central monitor flagged ventricular tachycardia, a precursor sign of cardiac arrest, and alarmed. Staff who ran to the room found seizure-like movements, reduced consciousness and no spontaneous breathing. They performed cardiopulmonary resuscitation (CPR) and artificial respiration. The heartbeat and circulation returned, and the patient was moved to intensive care. Daewoong Pharmaceutical, which supplies thynC, announced the case on 11 February 2026 with statements from the hospital's directors and nursing manager.", "replication": { "produced_by": [ "thynC wearable monitoring of ECG, heart rate and respiratory rate, linked to a remote central monitor on a general ward. It started on 9 January 2026 because the patient had cardiovascular risk factors at admission", "An alarm raised the moment the heart rate climbed to 192 beats per minute and the monitor identified ventricular tachycardia", "Ward staff who went to the bedside on the alarm and performed CPR and artificial respiration within the golden time. The reports put that time at four minutes for acute cardiac arrest, citing National Fire Agency data" ], "must_hold": [ "The case reached the press through a Daewoong Pharmaceutical announcement of 11 February 2026. The hospital's attending director, chief director and nursing manager are quoted. But no medical record, case report or independent review has been published", "Only the return of heartbeat and circulation and the transfer to intensive care are reported. Survival to discharge and neurological outcome are not", "The alarm shortens the time to detection, not the treatment. The benefit depends on staff who can reach the bedside and resuscitate within minutes. The nursing manager says that is hardest to guarantee at night and when staffing is thin" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The patient wore thynC monitors from 9 January 2026. The system alerted ward staff when the heart rate reached 192 beats per minute and identified ventricular tachycardia. Staff reached the bedside and performed CPR. The report describes that response as occurring within the time needed for resuscitation." } } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0181", "title": "Ghana Revenue Authority launches Publican AI trade analytics, which may have recovered GH¢15 million", "summary": "GRA's Publican AI customs analytics, supplied by an unnamed Cyprus-based firm, rolled out from 1 February 2026 at Tema Port; the OECD AI Incidents Monitor summary says GH¢15 million was recovered, ...", "date_observed": "2026-01-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents Monitor entry dated 16 January 2026 summarizes Ghanaian reports that the Ghana Revenue Authority launched Publican AI. That is a trade data analytics platform to identify customs fraud, undervaluation and falsified import documentation. The entry states that the system has already recovered GH¢15 million from fraudulent importers. Its source is a GhanaWeb story titled “Government recovers GH¢15 million through new trade data system”. The entry is classified as an AI Incident with the harm type economic harm to property interests. The Ghanaian Times (Kingsley Asare, 19 January 2026) reported remarks by Commissioner-General Dr Anthony Sarpong. He said that the Publican AI system would give 100 percent coverage of assessment. He said that assessments could be completed within five minutes instead of about two hours. He said that pilots showed 40–45% revenue gains. He said that rollout would begin at Tema Port on 1 February 2026. That article cites no realized recovery. The vendor is described only as a Cyprus-based firm.", "category": "general benefit", "unexpected": false, "purpose": "Identify customs fraud, undervaluation and falsified import documentation and give full coverage of customs assessment.", "system": "Publican AI Trade Solution", "model_version": null, "developer": "A Cyprus-based firm, unnamed in the read article", "deployer": "Ghana Revenue Authority, Customs Division", "location": "Tema, Ghana", "domain": "Customs revenue and fraud", "segment": "Import valuation and customs fraud", "benefit_type": "Increased Product Revenue", "taxonomy_note": "Tax yield is read as the authority's revenue; Trustible's description is written for product sales.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The recovery figure is a secondary summary and the revenue gain is a projection. No verified outcome for the GRA is documented." }, { "group": "societal", "depth": null, "reason": "Public revenue effects are projected, not observed, in the sources." } ], "ai_role": { "status": "unassessed", "statement": "Neither source describes how the analytics identify undervaluation or what share of the claimed recovery the system produced. The system is vendor-built and deployed by the GRA." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents Monitor, entry 2026-01-16-e77d, classified AI Incident", "title": "Ghana Deploys AI System to Combat Customs Fraud and Recover Revenue", "url": "https://oecd.ai/en/incidents/2026-01-16-e77d", "date": "2026-01-16", "written_by": "independent", "quote": "Ghana Deploys AI System to Combat Customs Fraud and Recover Revenue" }, { "kind": "news report", "citation": "Kingsley Asare, Ghanaian Times, 19 January 2026", "title": "AI trade analytics rollout to boost customs revenue by 45% – GRA Commissioner-General", "url": "https://ghanaiantimes.com.gh/ai-trade-analytics-rollout-to-boost-customs-revenue-by-45-gra-commissioner-general/", "date": "2026-01-19", "written_by": "independent", "quote": "The Publican AI system will give us 100 per cent coverage of assessment, ensuring that every shipment is scrutinised and valued accurately." }, { "kind": "news report", "citation": "MyJoyOnline (2026). Publican AI boosts GRA customs revenue to GH¢6.1bn in July – Commissioner-General. MyJoyOnline, 9 August 2026.", "title": "Publican AI boosts GRA customs revenue to GH¢6.1bn in July – Commissioner-General", "url": "https://www.myjoyonline.com/publican-ai-boosts-gra-customs-revenue-to-gh%C2%A26-1bn-in-july-commissioner-general/", "date": "2026-08-09", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Trade data analytics applied to every import declaration rather than sampled assessments" ], "must_hold": [ "Access to shipment declarations and valuation references", "Enforcement capacity to collect assessed underpayments", "Rollout beyond the Tema Port start" ], "echoes": [] }, "paired_incident": null, "headline": "GRA's Publican AI may have recovered GH¢15 million", "metric": "the system has already recovered GH¢15 million from fraudulent importers", "comparator": { "against": "manual assessment and classification of goods by customs officers", "before": "could take up to two hours after importers submitted their documentation", "after": "assessments could be completed within five minutes", "basis": "assumed", "quote": "Dr Sarpong noted that currently, the assessment and classification of goods involved considerable human effort, which could take up to two hours after importers submitted their documentation. With the introduction of the AI tool, he said, assessments could be completed within five minutes, thereby improving speed and efficiency in clearance processes.", "url": "https://ghanaiantimes.com.gh/ai-trade-analytics-rollout-to-boost-customs-revenue-by-45-gra-commissioner-general/" }, "later": { "status": "scaled", "date": "2026-08-09", "note": "After full implementation from April 2026, GRA said customs collections rose from about GH¢4 billion a month to GH¢6.1 billion in July 2026.", "quote": "Commissioner-General of the GRA, Anthony Sarpong, said monthly customs revenue averaged about GH¢4 billion before the full implementation of the system, indicating an increase of about GH¢2.1 billion in July.", "url": "https://www.myjoyonline.com/publican-ai-boosts-gra-customs-revenue-to-gh%C2%A26-1bn-in-july-commissioner-general/" }, "value": { "amount": "GH¢15 million", "what": "recovered from fraudulent importers", "who": "Government of Ghana (Ghana Revenue Authority)", "estimate": false, "quote": "The system has already enabled the government to recover GH¢15 million from fraudulent importers and aims to address significant revenue leakages in Ghana's customs operations.", "url": "https://oecd.ai/en/incidents/2026-01-16-e77d" }, "developer_country": null, "deployer_country": "Ghana", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.", "source": "https://ghanaiantimes.com.gh/ai-trade-analytics-rollout-to-boost-customs-revenue-by-45-gra-commissioner-general/; https://www.myjoyonline.com/publican-ai-boosts-gra-customs-revenue-to-gh%C2%A26-1bn-in-july-commissioner-general/; https://oecd.ai/en/incidents/2026-01-16-e77d", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://gra.gov.gh/contact-us/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0181", "catalog_version": "1.0.0", "source_fingerprint": "b42ede4e5e6af041e90e473f78c60cb3a33f3d27e621921ec0b6e244c98605f9", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0181-source-0001", "AIBD-0181-source-0002", "AIBD-0181-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0181-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "A Cyprus-based firm, unnamed in the read article", "deployer": "Ghana Revenue Authority, Customs Division" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Neither source describes how the analytics identify undervaluation or what share of the claimed recovery the system produced. The system is vendor-built and deployed by the GRA." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The recovery figure is a secondary summary and the revenue gain is a projection. No verified outcome for the GRA is documented." }, { "group": "societal", "reason": "Public revenue effects are projected, not observed, in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The recovery figure is a secondary summary and the revenue gain is a projection. 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MyJoyOnline, 9 August 2026.", "title": "Publican AI boosts GRA customs revenue to GH¢6.1bn in July – Commissioner-General", "url": "https://www.myjoyonline.com/publican-ai-boosts-gra-customs-revenue-to-gh%C2%A26-1bn-in-july-commissioner-general/", "date": "2026-08-09", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "GRA's Publican AI customs analytics, supplied by an unnamed Cyprus-based firm, rolled out from 1 February 2026 at Tema Port; the OECD AI Incidents Monitor summary says GH¢15 million was recovered, ...", "account": "The OECD AI Incidents Monitor entry dated 16 January 2026 summarizes Ghanaian reports that the Ghana Revenue Authority launched Publican AI. That is a trade data analytics platform to identify customs fraud, undervaluation and falsified import documentation. The entry states that the system has already recovered GH¢15 million from fraudulent importers. Its source is a GhanaWeb story titled “Government recovers GH¢15 million through new trade data system”. The entry is classified as an AI Incident with the harm type economic harm to property interests. The Ghanaian Times (Kingsley Asare, 19 January 2026) reported remarks by Commissioner-General Dr Anthony Sarpong. He said that the Publican AI system would give 100 percent coverage of assessment. He said that assessments could be completed within five minutes instead of about two hours. He said that pilots showed 40–45% revenue gains. He said that rollout would begin at Tema Port on 1 February 2026. That article cites no realized recovery. The vendor is described only as a Cyprus-based firm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Publican AI Trade Solution" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "A Cyprus-based firm, unnamed in the read article" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Ghana Revenue Authority launches Publican AI trade analytics, which may have recovered GH¢15 million", "headline": "GRA's Publican AI may have recovered GH¢15 million" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b42ede4e5e6af041e90e473f78c60cb3a33f3d27e621921ec0b6e244c98605f9" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents Monitor entry dated 16 January 2026 summarizes Ghanaian reports that the Ghana Revenue Authority launched Publican AI. That is a trade data analytics platform to identify customs fraud, undervaluation and falsified import documentation. The entry states that the system has already recovered GH¢15 million from fraudulent importers. Its source is a GhanaWeb story titled “Government recovers GH¢15 million through new trade data system”. The entry is classified as an AI Incident with the harm type economic harm to property interests. The Ghanaian Times (Kingsley Asare, 19 January 2026) reported remarks by Commissioner-General Dr Anthony Sarpong. He said that the Publican AI system would give 100 percent coverage of assessment. He said that assessments could be completed within five minutes instead of about two hours. He said that pilots showed 40–45% revenue gains. He said that rollout would begin at Tema Port on 1 February 2026. That article cites no realized recovery. The vendor is described only as a Cyprus-based firm.", "replication": { "produced_by": [ "Trade data analytics applied to every import declaration rather than sampled assessments" ], "must_hold": [ "Access to shipment declarations and valuation references", "Enforcement capacity to collect assessed underpayments", "Rollout beyond the Tema Port start" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0267", "title": "Mother's AI query prompts genetic evaluation and a CDC42BPB diagnosis in a 22-month-old", "summary": "An unnamed AI app suggested a skull abnormality, prompting genetic evaluation of a 22-month-old. The authors attribute the app to Med-Gemini-3D, but its model is unverified.", "date_observed": "2026-01-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Hajebian and Friel (Journal of Craniofacial Surgery, published 16 January 2026) describe a 22-month-old girl with persistent bilateral parietal skull defects and global developmental delay. The full text is paywalled. Her computed tomography (CT) showed symmetric ossification defects beside the sagittal suture that the treating physician did not initially recognize. The mother used “a smartphone application powered by Med-Gemini-3D” on a 3D-CT reconstruction. It suggested “Catlin mark skull”, the historical name for enlarged parietal foramina. Genetic evaluation then identified a CDC42BPB variant associated with Chilton-Okur-Chung neurodevelopmental syndrome. The authors state that establishing the diagnosis facilitated earlier therapeutic interventions. The abstract notes that Google introduced Med-Gemini-3D in 2024 and that it is not approved for independent clinical use. A consumer app running Med-Gemini-3D cannot be verified from the abstract.", "category": "benefit created", "unexpected": false, "purpose": "Consumer use of a CT-interpreting model to obtain a diagnosis for an unexplained skull finding", "system": "Smartphone application described by the authors as powered by Med-Gemini-3D", "model_version": "Med-Gemini-3D (Google, 2024) per the authors; the app's identity is not verified", "developer": "Google (Med-Gemini-3D)", "deployer": "The patient's mother (consumer use)", "location": "United States (authors at Garnet Health Medical Center, Middletown, New York)", "domain": "Health; rare-disease diagnosis", "segment": "Children with rare craniofacial anomalies", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Diagnosis of enlarged parietal foramina, identification of a CDC42BPB variant, and earlier therapeutic interventions for the child." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported." }, { "group": "societal", "depth": null, "reason": "Single case." } ], "ai_role": { "status": "assessed", "statement": "The authors attribute the diagnostic suggestion to a smartphone application they say is powered by Med-Gemini-3D. The abstract does not identify the app. So the AI role rests on the authors' description alone. Authors are not affiliated with the developer." }, "evidence": [ { "kind": "case report", "citation": "Hajebian HH, Friel MT. AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull. Journal of Craniofacial Surgery 37, nos. 3–4 (2026): 910–913. Published online January 16, 2026. doi:10.1097/SCS.0000000000012413. Abstract.", "title": "AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull", "url": "https://pubmed.ncbi.nlm.nih.gov/41543485/", "date": "2026-01-16", "written_by": "independent", "quote": "The patient's mother used a smartphone application powered by Med-Gemini-3D to analyze a 3D-CT reconstruction image" } ], "replication": { "produced_by": [ "A caregiver submitting a 3D-CT image to a multimodal model", "A rare finding unrecognized by the treating physician", "Follow-up genetic evaluation" ], "must_hold": [ "Access to a model able to interpret 3D CT images", "Clinicians act on a consumer-obtained suggestion" ], "echoes": [] }, "paired_incident": null, "headline": "Mother's AI query prompts a rare-disease diagnosis in a 22-month-old", "metric": null, "comparator": { "against": "the treating physician's initial reading of the CT scan", "before": "symmetric ossification defects adjacent to the sagittal suture that were not initially recognized by the treating physician", "after": "suggested a diagnosis of \"Catlin mark skull,\" a historical term for Enlarged Parietal Foramina (EPF)", "basis": "measured", "quote": "Computed tomography demonstrated symmetric ossification defects adjacent to the sagittal suture that were not initially recognized by the treating physician. The patient's mother used a smartphone application powered by Med-Gemini-3D to analyze a 3D-CT reconstruction image, which suggested a diagnosis of \"Catlin mark skull,\" a historical term for Enlarged Parietal Foramina (EPF).", "url": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:41543485%20AND%20SRC:MED&resultType=core&format=json" }, "later": { "status": "unknown", "date": null, "note": "No later correspondence, correction, or follow-up to the case report of 16 January 2026 is established.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:41543485%20AND%20SRC:MED&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "source": "https://pubmed.ncbi.nlm.nih.gov/41543485/; https://research.google/blog/advancing-medical-ai-with-med-gemini/", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0267", "catalog_version": "1.0.0", "source_fingerprint": "21fd7dda66f38c49edb783c0b301465967ce093feddc34406c0a4a622d77f3b7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0267-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Google (Med-Gemini-3D)", "deployer": "The patient's mother (consumer use)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The authors attribute the diagnostic suggestion to a smartphone application they say is powered by Med-Gemini-3D. The abstract does not identify the app. So the AI role rests on the authors' description alone. Authors are not affiliated with the developer." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The authors attribute the diagnostic suggestion to a smartphone application they say is powered by Med-Gemini-3D. The abstract does not identify the app. So the AI role rests on the authors' description alone. Authors are not affiliated with the developer." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Diagnosis of enlarged parietal foramina, identification of a CDC42BPB variant, and earlier therapeutic interventions for the child." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from retained evidence using the existing display rule; source originality does not establish an independent evaluation of the benefit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0267-source-0001" ] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Diagnosis of enlarged parietal foramina, identification of a CDC42BPB variant, and earlier therapeutic interventions for the child." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Diagnosis of enlarged parietal foramina, identification of a CDC42BPB variant, and earlier therapeutic interventions for the child." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No later correspondence, correction, or follow-up to the case report of 16 January 2026 is established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0267" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Hajebian and Friel (Journal of Craniofacial Surgery, published 16 January 2026) describe a 22-month-old girl with persistent bilateral parietal skull defects and global developmental delay. The full text is paywalled. Her computed tomography (CT) showed symmetric ossification defects beside the sagittal suture that the treating physician did not initially recognize. The mother used “a smartphone application powered by Med-Gemini-3D” on a 3D-CT reconstruction. It suggested “Catlin mark skull”, the historical name for enlarged parietal foramina. Genetic evaluation then identified a CDC42BPB variant associated with Chilton-Okur-Chung neurodevelopmental syndrome. The authors state that establishing the diagnosis facilitated earlier therapeutic interventions. The abstract notes that Google introduced Med-Gemini-3D in 2024 and that it is not approved for independent clinical use. A consumer app running Med-Gemini-3D cannot be verified from the abstract.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Diagnosis of enlarged parietal foramina, identification of a CDC42BPB variant, and earlier therapeutic interventions for the child." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Consumer use of a CT-interpreting model to obtain a diagnosis for an unexplained skull finding" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United States (authors at Garnet Health Medical Center, Middletown, New York)", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Consumer use of a CT-interpreting model to obtain a diagnosis for an unexplained skull finding" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-01-16", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:41543485%20AND%20SRC:MED&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "source": "https://pubmed.ncbi.nlm.nih.gov/41543485/; https://research.google/blog/advancing-medical-ai-with-med-gemini/", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A caregiver submitting a 3D-CT image to a multimodal model", "A rare finding unrecognized by the treating physician", "Follow-up genetic evaluation" ], "must_hold": [ "Access to a model able to interpret 3D CT images", "Clinicians act on a consumer-obtained suggestion" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:41543485%20AND%20SRC:MED&resultType=core&format=json", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Google", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "source": "https://pubmed.ncbi.nlm.nih.gov/41543485/; https://research.google/blog/advancing-medical-ai-with-med-gemini/", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Health; rare-disease diagnosis", "segment": "Children with rare craniofacial anomalies" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Hajebian HH, Friel MT. AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull. Journal of Craniofacial Surgery 37, nos. 3–4 (2026): 910–913. Published online January 16, 2026. doi:10.1097/SCS.0000000000012413. Abstract.", "title": "AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull", "url": "https://pubmed.ncbi.nlm.nih.gov/41543485/", "date": "2026-01-16", "written_by": "independent", "quote": "The patient's mother used a smartphone application powered by Med-Gemini-3D to analyze a 3D-CT reconstruction image" } ] } }, "provenance": { "kind": "source_review", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0267-source-0001" ], "role": "Retained evidence items in reviewed source order" }, "provenance": { "kind": "curatorial", "basis": "Source identifiers synchronized with the retained evidence after a source-attribution correction.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0267-source-0001" ] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Hajebian HH, Friel MT. AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull. Journal of Craniofacial Surgery 37, nos. 3–4 (2026): 910–913. Published online January 16, 2026. doi:10.1097/SCS.0000000000012413. Abstract.", "title": "AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull", "url": "https://pubmed.ncbi.nlm.nih.gov/41543485/", "date": "2026-01-16", "written_by": "independent", "quote": "The patient's mother used a smartphone application powered by Med-Gemini-3D to analyze a 3D-CT reconstruction image" } ] } }, "provenance": { "kind": "source_review", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0267-source-0001" ], "url": "https://pubmed.ncbi.nlm.nih.gov/41543485/", "doi": "https://doi.org/10.1097/SCS.0000000000012413", "title": "AI-Based CT Image Recognition With Med-Gemini-3D in the Diagnosis of a Rare Craniofacial Condition: A Catlin Mark Skull", "published_on": "2026-01-16", "relationship": "Original clinical case report by clinicians unaffiliated with the attributed AI developer. Only the abstract and bibliographic metadata were inspected in this review. A case report is not a controlled evaluation or independent replication." } ], "same_work_access_versions": [ "https://europepmc.org/article/MED/41543485" ], "claim_lineage": [ { "claim": "The mother used an app to interpret a CT image; its suggestion prompted genetic evaluation and identification of a CDC42BPB variant.", "source_ref": "AIBD-0267-source-0001", "locator": "Abstract, third paragraph", "limitation": "The app is unnamed. Its connection to Med-Gemini-3D is the authors’ attribution and could not be independently established." }, { "claim": "The diagnosis facilitated earlier interventions and informed management.", "source_ref": "AIBD-0267-source-0001", "locator": "Abstract, fourth paragraph", "quote": "Establishing the diagnosis facilitated earlier therapeutic interventions and informed long-term management.", "limitation": "The accessible abstract provides no measured clinical improvement or follow-up duration." } ], "related_material": [ { "url": "https://research.google/blog/advancing-medical-ai-with-med-gemini/", "title": "Advancing medical AI with Med-Gemini", "published_on": "2024-05-15", "locator": "Conclusion, paragraph beginning “We’re excited”", "relationship": "Original Google Research and Google DeepMind announcement says that Med-Gemini was not a commercial product and invites research collaboration. It establishes a material access question, not proof that the later case report is false or that the model attribution is impossible." } ], "access_audit": [ { "url": "https://pubmed.ncbi.nlm.nih.gov/41543485/", "access": "Abstract, authorship, affiliations, conflicts statement, and listed reference metadata read." }, { "url": "https://research.google/blog/advancing-medical-ai-with-med-gemini/", "access": "Original developer announcement read, including model-access qualifications." } ], "limitations": [ "The full case-report text, any supplementary material, and the app’s identity were not verified.", "The original case remains included, with its existing depth unchanged. The model attribution is not established beyond the authors’ account." ], "ordering_basis": "One original clinical work, with its duplicate excerpt and alternate abstract host preserved in source notes.", "lead_source_ref": "AIBD-0267-source-0001", "retained_source_order": [ "AIBD-0267-source-0001" ], "scope": "Narrow review of source attribution and source roles. Case depths and unassessed study-design fields are unchanged. Access limits are stated below." } }, "provenance": { "kind": "source_review", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "evidence", "headline", "title", "summary" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The authors describe the clinical episode in the available account. The full report and any supplements were not inspected, and the app’s identity remains unconfirmed.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "An unnamed AI app suggested a skull abnormality, prompting genetic evaluation of a 22-month-old. The authors attribute the app to Med-Gemini-3D, but its model is unverified.", "account": "Hajebian and Friel (Journal of Craniofacial Surgery, published 16 January 2026) describe a 22-month-old girl with persistent bilateral parietal skull defects and global developmental delay. The full text is paywalled. Her computed tomography (CT) showed symmetric ossification defects beside the sagittal suture that the treating physician did not initially recognize. The mother used “a smartphone application powered by Med-Gemini-3D” on a 3D-CT reconstruction. It suggested “Catlin mark skull”, the historical name for enlarged parietal foramina. Genetic evaluation then identified a CDC42BPB variant associated with Chilton-Okur-Chung neurodevelopmental syndrome. The authors state that establishing the diagnosis facilitated earlier therapeutic interventions. The abstract notes that Google introduced Med-Gemini-3D in 2024 and that it is not approved for independent clinical use. A consumer app running Med-Gemini-3D cannot be verified from the abstract." } }, "provenance": { "kind": "source_review", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "summary" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The application suggested a possible diagnosis from a reconstructed CT image, according to the case-report authors." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The mother used a smartphone application to analyze a three-dimensional reconstruction from her child’s CT scan." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The application analyzed an image reconstructed from a CT scan and suggested enlarged parietal foramina." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "Med-Gemini-3D, as identified by the case-report authors." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Med-Gemini-3D, as identified by the case-report authors.", "editor_note": "The abstract names Med-Gemini-3D but does not identify the smartphone application or provide evidence of its model integration (reference 1)." } }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Med-Gemini-3D (Google, 2024) per the authors; the app's identity is not verified" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Smartphone application described by the authors as powered by Med-Gemini-3D" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Google (Med-Gemini-3D)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Mother's AI query prompts genetic evaluation and a CDC42BPB diagnosis in a 22-month-old", "headline": "Mother's AI query prompts a rare-disease diagnosis in a 22-month-old" } }, "provenance": { "kind": "source_review", "basis": "Qualified the unnamed app's model attribution in the title, headline, and summary. Consolidated two excerpts of one clinical report into one evidence item. The abstract supports the diagnostic sequence and earlier interventions, but it does not identify the app or substantiate its connection to Med-Gemini-3D.", "record_fields": [ "headline", "title" ], "source_refs": [ "AIBD-0267-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "21fd7dda66f38c49edb783c0b301465967ce093feddc34406c0a4a622d77f3b7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the content fingerprint after the source-attribution correction.", "record_fields": [ "evidence", "headline", "revisions", "summary", "title" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Hajebian and Friel (Journal of Craniofacial Surgery, published 16 January 2026) describe a 22-month-old girl with persistent bilateral parietal skull defects and global developmental delay. The full text is paywalled. Her computed tomography (CT) showed symmetric ossification defects beside the sagittal suture that the treating physician did not initially recognize. The mother used “a smartphone application powered by Med-Gemini-3D” on a 3D-CT reconstruction. It suggested “Catlin mark skull”, the historical name for enlarged parietal foramina. Genetic evaluation then identified a CDC42BPB variant associated with Chilton-Okur-Chung neurodevelopmental syndrome. The authors state that establishing the diagnosis facilitated earlier therapeutic interventions. The abstract notes that Google introduced Med-Gemini-3D in 2024 and that it is not approved for independent clinical use. A consumer app running Med-Gemini-3D cannot be verified from the abstract.", "replication": { "produced_by": [ "A caregiver submitting a 3D-CT image to a multimodal model", "A rare finding unrecognized by the treating physician", "Follow-up genetic evaluation" ], "must_hold": [ "Access to a model able to interpret 3D CT images", "Clinicians act on a consumer-obtained suggestion" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 1, "record_mapped": 33, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0258", "title": "A passenger's iPhone Crash Detection sends a “strong impact” alert to the local fire service before a sightseeing helicopter near Mount Aso goes missing, 20 January 2026", "summary": "SETN (21 Jan 2026, citing Japanese media): the helicopter took off at 10:52 on 20 Jan 2026 and lost contact at 11:04; the fire department had already received a collision notification from a passen...", "date_observed": "2026-01-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Taiwan's SETN reported on 21 Jan 2026, citing Japanese media, on a sightseeing helicopter operated by Aso Cadre Dominion. It carried a pilot in his sixties and two Taiwanese passengers (a 41-year-old man and a 36-year-old woman). It took off at 10:52 Japan time on 20 Jan 2026 and lost contact at 11:04. Before contact was lost, the local fire department received a “strong impact” notification from a passenger's phone, apparently the iPhone Crash Detection feature. Callbacks to the phone failed. An object believed to be the helicopter was found around the first crater of Mount Aso's Nakadake. The article does not state the fate of the three occupants. It does not cite a named Japanese agency. It quotes a firefighter and a nurse on crash detection in general. Apple's feature, on iPhone 14 and later, uses motion sensors and an on-device algorithm to call emergency services after a 10-second countdown. The OECD AI Incidents Monitor lists the case as a protective response. The link to transport safety is indirect. The device alerted responders to an aviation crash it did not prevent.", "category": "protective response", "unexpected": false, "purpose": "Crash Detection is built to recognize a severe vehicle crash from motion and sound signals and alert emergency services automatically.", "system": "Apple Crash Detection (iPhone 14 and later)", "model_version": "iPhone 14或後續機型（所有機型），且搭載iOS 16", "developer": "Apple", "deployer": "A helicopter passenger's iPhone", "location": null, "domain": "Aviation / emergency response", "segment": "Consumer devices / automatic crash alerting", "benefit_type": "Improved Physical Health", "taxonomy_note": "Crash notification to firefighters is read as a rescue; the occupants' outcome is not established.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The fire service received an automatic impact alert before the aircraft was reported missing. The article does not quantify how it shaped the search." }, { "group": "personal", "depth": null, "reason": "The source does not state whether the occupants survived." }, { "group": "societal", "depth": null, "reason": "No wider outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The phone's crash algorithm sent the notification. The search located the wreckage the following day. 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Three bodies found at helicopter crash site in southwest Japan volcanic crater. The Star.", "title": "Three bodies found at helicopter crash site in southwest Japan volcanic crater", "url": "https://www.thestar.com.my/aseanplus/aseanplus-news/2026/02/18/three-bodies-found-at-helicopter-crash-site-in-southwest-japan-volcanic-crater", "date": "2026-02-18", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A passenger carrying a crash-detection-capable phone", "An impact profile that met the algorithm's severity threshold", "A cellular or emergency-SOS path from a volcanic mountain area" ], "must_hold": [ "The alert carries usable coordinates", "Responders can reach the site quickly enough to change the outcome" ], "echoes": [ { "date": "2023-01-30", "setting": "OECD AIM aggregate entry on Apple Crash Detection producing both false alarms and emergency responses (registry listing only)", "model_version": null, "outcome": "unknown", "source": "https://oecd.ai/en/incidents/2023-01-30-10fc" } ] }, "paired_incident": null, "headline": "Apple Crash Detection alerts firefighters to a Mount Aso crash", "metric": null, "comparator": null, "later": { "status": "reversed", "date": "2026-02-18", "note": "The alert located the crash site but no one was rescued: on 18 February 2026 the fire department said bodies believed to be the three occupants had been found inside the crater, so the 'rapid rescue' framing of the first reports was not borne out.", "quote": "Bodies believed to be those of three people aboard a sightseeing helicopter that crashed into a volcanic crater on Mt. 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it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since, the model version from the cited sources.", "source": "https://www.thestar.com.my/aseanplus/aseanplus-news/2026/02/18/three-bodies-found-at-helicopter-crash-site-in-southwest-japan-volcanic-crater; https://www.setn.com/News.aspx?NewsID=1784034", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Aviation / emergency response", "segment": "Consumer devices / automatic crash alerting" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "SETN 三立新聞網 (21 Jan 2026). 阿蘇火山墜機！iPhone「內建1功能」10秒救命 沒訊號也可呼救.", "title": "阿蘇火山墜機！iPhone「內建1功能」10秒救命　沒訊號也可呼救", "url": "https://www.setn.com/News.aspx?NewsID=1784034", "date": "2026-01-21", "written_by": "independent", "quote": "當地消防局在直升機失聯前，有收到來自乘客的「強烈撞擊」通報" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-01-20-af0b: AI Crash Detection on Smartphones Enables Rapid Rescue After Japan Helicopter Crash.", "title": "AI Crash Detection on Smartphones Enables Rapid Rescue After Japan Helicopter Crash", "url": "https://oecd.ai/en/incidents/2026-01-20-af0b", "date": "2026-01-20", "written_by": "independent", "quote": "After a sightseeing helicopter crashed near Japan's Mount Aso, the iPhone crash detection feature automatically alerted emergency services, enabling rapid search and rescue." }, { "kind": "news report", "citation": "Bernama-Kyodo (18 Feb 2026). Three bodies found at helicopter crash site in southwest Japan volcanic crater. The Star.", "title": "Three bodies found at helicopter crash site in southwest Japan volcanic crater", "url": "https://www.thestar.com.my/aseanplus/aseanplus-news/2026/02/18/three-bodies-found-at-helicopter-crash-site-in-southwest-japan-volcanic-crater", "date": "2026-02-18", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0258-source-0001", "AIBD-0258-source-0002", "AIBD-0258-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "SETN 三立新聞網 (21 Jan 2026). 阿蘇火山墜機！iPhone「內建1功能」10秒救命 沒訊號也可呼救.", "title": "阿蘇火山墜機！iPhone「內建1功能」10秒救命　沒訊號也可呼救", "url": "https://www.setn.com/News.aspx?NewsID=1784034", "date": "2026-01-21", "written_by": "independent", "quote": "當地消防局在直升機失聯前，有收到來自乘客的「強烈撞擊」通報" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-01-20-af0b: AI Crash Detection on Smartphones Enables Rapid Rescue After Japan Helicopter Crash.", "title": "AI Crash Detection on Smartphones Enables Rapid Rescue After Japan Helicopter Crash", "url": "https://oecd.ai/en/incidents/2026-01-20-af0b", "date": "2026-01-20", "written_by": "independent", "quote": "After a sightseeing helicopter crashed near Japan's Mount Aso, the iPhone crash detection feature automatically alerted emergency services, enabling rapid search and rescue." }, { "kind": "news report", "citation": "Bernama-Kyodo (18 Feb 2026). Three bodies found at helicopter crash site in southwest Japan volcanic crater. The Star.", "title": "Three bodies found at helicopter crash site in southwest Japan volcanic crater", "url": "https://www.thestar.com.my/aseanplus/aseanplus-news/2026/02/18/three-bodies-found-at-helicopter-crash-site-in-southwest-japan-volcanic-crater", "date": "2026-02-18", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SETN (21 Jan 2026, citing Japanese media): the helicopter took off at 10:52 on 20 Jan 2026 and lost contact at 11:04; the fire department had already received a collision notification from a passen...", "account": "Taiwan's SETN reported on 21 Jan 2026, citing Japanese media, on a sightseeing helicopter operated by Aso Cadre Dominion. It carried a pilot in his sixties and two Taiwanese passengers (a 41-year-old man and a 36-year-old woman). It took off at 10:52 Japan time on 20 Jan 2026 and lost contact at 11:04. Before contact was lost, the local fire department received a “strong impact” notification from a passenger's phone, apparently the iPhone Crash Detection feature. Callbacks to the phone failed. An object believed to be the helicopter was found around the first crater of Mount Aso's Nakadake. The article does not state the fate of the three occupants. It does not cite a named Japanese agency. It quotes a firefighter and a nurse on crash detection in general. Apple's feature, on iPhone 14 and later, uses motion sensors and an on-device algorithm to call emergency services after a 10-second countdown. The OECD AI Incidents Monitor lists the case as a protective response. The link to transport safety is indirect. The device alerted responders to an aviation crash it did not prevent." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The phone detected a possible collision and sent a notification." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The minimum requirements were an iPhone 14 or later and iOS 16 or later. They do not establish the device or installed release in this event." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "iPhone 14或後續機型（所有機型），且搭載iOS 16" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Crash Detection (iPhone 14 and later)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A passenger's iPhone Crash Detection sends a “strong impact” alert to the local fire service before a sightseeing helicopter near Mount Aso goes missing, 20 January 2026", "headline": "Apple Crash Detection alerts firefighters to a Mount Aso crash" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cf2ce059eb6055834dd91affee6c74d0f3f54577100c6540473d5adfc2dab536" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Taiwan's SETN reported on 21 Jan 2026, citing Japanese media, on a sightseeing helicopter operated by Aso Cadre Dominion. It carried a pilot in his sixties and two Taiwanese passengers (a 41-year-old man and a 36-year-old woman). It took off at 10:52 Japan time on 20 Jan 2026 and lost contact at 11:04. Before contact was lost, the local fire department received a “strong impact” notification from a passenger's phone, apparently the iPhone Crash Detection feature. Callbacks to the phone failed. An object believed to be the helicopter was found around the first crater of Mount Aso's Nakadake. The article does not state the fate of the three occupants. It does not cite a named Japanese agency. It quotes a firefighter and a nurse on crash detection in general. Apple's feature, on iPhone 14 and later, uses motion sensors and an on-device algorithm to call emergency services after a 10-second countdown. The OECD AI Incidents Monitor lists the case as a protective response. The link to transport safety is indirect. The device alerted responders to an aviation crash it did not prevent.", "replication": { "produced_by": [ "A passenger carrying a crash-detection-capable phone", "An impact profile that met the algorithm's severity threshold", "A cellular or emergency-SOS path from a volcanic mountain area" ], "must_hold": [ "The alert carries usable coordinates", "Responders can reach the site quickly enough to change the outcome" ], "echoes": [ { "date": "2023-01-30", "setting": "OECD AIM aggregate entry on Apple Crash Detection producing both false alarms and emergency responses (registry listing only)", "outcome": "unknown", "source": "https://oecd.ai/en/incidents/2023-01-30-10fc" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0298", "title": "Corsano CardioWatch 287–2 algorithm recognizes a real-life ventricular-fibrillation arrest and collapse in post-processing; the patient's ICD, not the wristband, ended it", "summary": "Radboudumc DETECT-3 case: a 64-year-old's VF arrest while cycling was ended by his ICD; the CardioWatch PPG algorithm later detected pulselessness at 09:50:17 and the fall; no live alert was sent.", "date_observed": "2026-01-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Edgar, Jansen, Pol, Pisters, van Royen and Bonnes of Radboud University Medical Center (with Rijnstate Hospital) reported in Resuscitation Plus on 29 January 2026. The paper gives no calendar date for the event. They report the first real-life cardiac arrest captured by a wristband with cardiac-arrest detection. A 64-year-old man with heart failure, permanent atrial fibrillation and a secondary-prevention Biotronik ICD was wearing the CE-certified CardioWatch 287–2 (Corsano Health, The Hague). He wore it in the DETECT-3 study. After three weeks, while cycling alone, he developed monomorphic ventricular tachycardia (VT). It accelerated to ventricular fibrillation (VF) after an antitachycardia pacing burst. The ICD delivered a 40 J shock. He regained consciousness, cycled home, and was admitted for rhythm observation with a good recovery. The wristband's 32 Hz photoplethysmography and accelerometry data were exported afterwards. A Corsano Health data scientist blinded to the event ran them through the DETECT photoplethysmography algorithm. It detected cardiac arrest at 09:50:17 after loss of pulse. It ended the alert at 09:50:57 when pulsations returned. The group's fall-detection algorithm flagged the fall about 8–10 seconds after pulselessness. The authors state the detection was retrospective. They state that the study collects data to measure false-positive rates for a future live system. Companion papers from the same program report 98% sensitivity in induced circulatory arrests (DETECT-1a). They report external validation in 50 patients with induced VT/VF (DETECT-1b, April 2026). They report 100% sensitivity (23 of 23) with one false positive in true non-shockable arrests after withdrawal of life-sustaining treatment. That paper (Lancet Regional Health Europe, July 2026) describes the algorithm as rule-based. The patient's survival is attributable to the ICD. The wristband changed nothing for him.", "category": "general benefit", "unexpected": false, "purpose": "Built to detect out-of-hospital cardiac arrest from wrist photoplethysmography and accelerometry and, in future, alert emergency services. The retrospective detection demonstrates the first half of that purpose.", "system": "Corsano CardioWatch 287-2 with the DETECT photoplethysmography cardiac-arrest detection and accelerometry fall-detection algorithms", "model_version": "CardioWatch 287-2 (CE-certified); DETECT algorithm as developed in DETECT-1a", "developer": "DETECT program, Radboud University Medical Center, with Corsano Health, The Hague (device and algorithm processing)", "deployer": "Radboud University Medical Center (DETECT-3 study)", "location": "Netherlands (DETECT-3 study, Nijmegen; the cycling incident's location is not named)", "domain": "Emergency medicine / resuscitation", "segment": "Research wristband for automated cardiac-arrest detection", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "A post-hoc detection on one case is read as task performance; nothing changed for the patient.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The patient was saved by his ICD. The wristband's detection was retrospective and produced no alert or treatment." }, { "group": "societal", "depth": null, "reason": "The authors argue a live system could act as a first witness for unwitnessed arrests. No deployment outcome exists yet." } ], "ai_role": { "status": "assessed", "statement": "The algorithm was run afterwards on exported data by a blinded Corsano data scientist. It correctly flagged the loss of pulse and the fall. It was not running live and sent no alert. The ICD shock is what restored circulation. The developers' own papers are the only full sources. They describe a rule-based detector of absent pulsations by signal amplitude and waveform morphology rather than a machine-learning model." }, "evidence": [ { "kind": "case report", "citation": "Edgar R, Jansen CE, Pol LR, Pisters R, van Royen N, Bonnes JL (2026). Out-of-hospital cardiac arrest detection by a wearable: the first real-life case. Resuscitation Plus 28:101245 (PMC12914388). Authors are the DETECT algorithm's developers.", "title": "Out-of-hospital cardiac arrest detection by a wearable: the first real-life case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914388/", "date": "2026-01-29", "written_by": "makers", "quote": "The cardiac arrest detection algorithm of the CardioWatch correctly recognized the cardiac arrest event and subsequent collapse based on photoplethysmography and accelerometry data during post-processing." }, { "kind": "case report", "citation": "Edgar et al. (2026), Resusc Plus 28:101245, case description.", "title": "Out-of-hospital cardiac arrest detection by a wearable: the first real-life case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914388/", "date": "2026-01-29", "written_by": "makers", "quote": "While cycling, the patient experienced a ventricular fibrillation cardiac arrest that was successfully terminated by the ICD." }, { "kind": "case report", "citation": "Edgar et al. (2026), Resusc Plus 28:101245, on who ran the algorithm.", "title": "Out-of-hospital cardiac arrest detection by a wearable: the first real-life case", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914388/", "date": "2026-01-29", "written_by": "makers", "quote": "A data scientist at Corsano Health, who was blinded to the cardiac arrest event, ran the data through the photoplethysmography-based cardiac arrest detection algorithm." }, { "kind": "peer-reviewed study", "citation": "Edgar R, Jansen CE, Pol LR, Ebrahimkheil K, van Kaam RC, Ronner E, Brouwer MA, Beukema RJ, Cetinyurek-Yavuz A, Stas PC, Boersma E, Hoedemaekers CWE, van Royen N, Bonnes JL (2026). Automated cardiac arrest detection using wrist-derived photoplethysmography during withdrawal of life-sustaining treatment: a prospective clinical validation study. The Lancet Regional Health - Europe 67:101791 (PMC13427576). Corsano Health co-authors.", "title": "Automated cardiac arrest detection using wrist-derived photoplethysmography during withdrawal of life-sustaining treatment: a prospective clinical validation study", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13427576/", "date": "2026-07-24", "written_by": "makers", "quote": "The previously developed rule-based algorithm was refined using two training cohorts and evaluated in a separate test cohort." }, { "kind": "peer-reviewed study", "citation": "Edgar R, Scholte NTB, Ebrahimkheil K, et al. (2026). Automated Cardiac Arrest Detection Using Wrist-Worn Photoplethysmography: External Validation in Patients With Induced Shockable Cardiac Arrest (DETECT-1b). Circulation: Arrhythmia and Electrophysiology 19(5):e014708 (PMC13182813). Corsano Health co-authors.", "title": "Automated Cardiac Arrest Detection Using Wrist-Worn Photoplethysmography: External Validation in Patients With Induced Shockable Cardiac Arrest (DETECT-1b)", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13182813/", "date": "2026-04-14", "written_by": "makers", "quote": "In the DETECT-1a study, we developed a wrist-derived photoplethysmography (PPG) algorithm for cardiac arrest detection using patient data from induced short‑lasting circulatory arrests, achieving 98% sensitivity." }, { "kind": "other", "citation": "Veigl C, Billig S (2026). A digital witness for cardiac arrest: are wearables ready for real-world use? Resuscitation Plus 28:101246 (editorial accompanying the two case reports; PMC12914390).", "title": "A digital witness for cardiac arrest: are wearables ready for real-world use?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914390/", "date": "2026-01-29", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Continuous wristband wear with 32 Hz photoplethysmography and accelerometry uploaded to a study cloud", "A shockable arrest with clear loss of pulsations during cycling, in a patient whose ICD provided the reference and the rescue", "Blinded after-the-fact processing by the developers' data scientist" ], "must_hold": [ "Adequate photoplethysmography quality during motion (the authors note it is typically disturbed by motion)", "A live implementation with acceptable false-positive rates, which DETECT-3 is still measuring", "An alerting chain to emergency services, which does not yet exist for this device" ], "echoes": [ { "date": "2026-07-24", "setting": "Radboudumc ICU, 44 patients with planned withdrawal of life-sustaining treatment, all non-shockable arrests; test cohort of 23", "model_version": "CardioWatch with the refined rule-based DETECT algorithm", "outcome": "recurred", "source": "Edgar et al. (2026) Lancet Reg Health Eur 67:101791 (quote: 'In the test set, sensitivity was 100% (23/23; 95% CI 82–100%), with one false positive alert.')" }, { "date": "2026-04-14", "setting": "Multicentre DETECT-1b, 50 adults with induced pulseless VT or VF during ablation or S-ICD implantation, Netherlands", "model_version": "CardioWatch, DETECT-1a algorithm with a 10-second window", "outcome": "recurred", "source": "Edgar et al. (2026) Circ Arrhythm Electrophysiol 19(5):e014708, https://pmc.ncbi.nlm.nih.gov/articles/PMC13182813/" } ] }, "paired_incident": null, "headline": "Corsano CardioWatch recognizes a VF arrest in post-processing", "metric": "detected cardiac arrest at 09:50:17 after loss of pulse", "comparator": { "against": "the ICD's electrograms and the confirmed time of collapse (velocity 0 km/h), reviewed in post-processing", "before": null, "after": "Cardiac arrest was detected at 09:50:17, after a loss of pulse in the photoplethysmography signal.", "basis": "measured", "quote": "Cardiac arrest was detected at 09:50:17, after a loss of pulse in the photoplethysmography signal. The alert was terminated at 09:50:57, when the return of several normal photoplethysmography peaks was detected. Moreover, the fall with a period of no movement afterwards was detected by our previously developed fall detection algorithm.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914388/" }, "later": { "status": "persisted", "date": "2026-07-24", "note": "The same group's later prospective validation in ICU patients with non-shockable arrest after withdrawal of life-sustaining treatment reported 100% sensitivity in the 23-patient test set with one false positive, and DETECT-1b (April 2026) externally validated the algorithm in 50 induced shockable arrests; no live alerting has been reported.", "quote": "In the test set, sensitivity was 100% (23/23; 95% CI 82–100%), with one false positive alert.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13427576/" }, "value": null, "developer_country": "Netherlands", "deployer_country": "Netherlands", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914388/; https://pmc.ncbi.nlm.nih.gov/articles/PMC13427576/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://clinicaltrials.gov/api/v2/studies/NCT06692374?fields=NCTId,BriefTitle,OfficialTitle,Acronym,LeadSponsorName,CollaboratorName,LocationFacility,LocationCity,LocationCountry,BriefSummary; https://en.wikipedia.org/wiki/Radboud_University_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: one other independent source, two peer-reviewed studies from the makers and the makers' case report. 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The paper gives no calendar date for the event. They report the first real-life cardiac arrest captured by a wristband with cardiac-arrest detection. A 64-year-old man with heart failure, permanent atrial fibrillation and a secondary-prevention Biotronik ICD was wearing the CE-certified CardioWatch 287–2 (Corsano Health, The Hague). He wore it in the DETECT-3 study. After three weeks, while cycling alone, he developed monomorphic ventricular tachycardia (VT). It accelerated to ventricular fibrillation (VF) after an antitachycardia pacing burst. The ICD delivered a 40 J shock. He regained consciousness, cycled home, and was admitted for rhythm observation with a good recovery. The wristband's 32 Hz photoplethysmography and accelerometry data were exported afterwards. A Corsano Health data scientist blinded to the event ran them through the DETECT photoplethysmography algorithm. It detected cardiac arrest at 09:50:17 after loss of pulse. It ended the alert at 09:50:57 when pulsations returned. The group's fall-detection algorithm flagged the fall about 8–10 seconds after pulselessness. The authors state the detection was retrospective. They state that the study collects data to measure false-positive rates for a future live system. Companion papers from the same program report 98% sensitivity in induced circulatory arrests (DETECT-1a). They report external validation in 50 patients with induced VT/VF (DETECT-1b, April 2026). They report 100% sensitivity (23 of 23) with one false positive in true non-shockable arrests after withdrawal of life-sustaining treatment. That paper (Lancet Regional Health Europe, July 2026) describes the algorithm as rule-based. The patient's survival is attributable to the ICD. The wristband changed nothing for him.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The patient was saved by his ICD. The wristband's detection was retrospective and produced no alert or treatment." }, { "group": "societal", "reason": "The authors argue a live system could act as a first witness for unwitnessed arrests. No deployment outcome exists yet." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect out-of-hospital cardiac arrest from wrist photoplethysmography and accelerometry and, in future, alert emergency services. 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It ended the alert at 09:50:57 when pulsations returned. The group's fall-detection algorithm flagged the fall about 8–10 seconds after pulselessness. The authors state the detection was retrospective. They state that the study collects data to measure false-positive rates for a future live system. Companion papers from the same program report 98% sensitivity in induced circulatory arrests (DETECT-1a). They report external validation in 50 patients with induced VT/VF (DETECT-1b, April 2026). They report 100% sensitivity (23 of 23) with one false positive in true non-shockable arrests after withdrawal of life-sustaining treatment. That paper (Lancet Regional Health Europe, July 2026) describes the algorithm as rule-based. The patient's survival is attributable to the ICD. The wristband changed nothing for him.", "replication": { "produced_by": [ "Continuous wristband wear with 32 Hz photoplethysmography and accelerometry uploaded to a study cloud", "A shockable arrest with clear loss of pulsations during cycling, in a patient whose ICD provided the reference and the rescue", "Blinded after-the-fact processing by the developers' data scientist" ], "must_hold": [ "Adequate photoplethysmography quality during motion (the authors note it is typically disturbed by motion)", "A live implementation with acceptable false-positive rates, which DETECT-3 is still measuring", "An alerting chain to emergency services, which does not yet exist for this device" ], "echoes": [ { "date": "2026-07-24", "setting": "Radboudumc ICU, 44 patients with planned withdrawal of life-sustaining treatment, all non-shockable arrests; test cohort of 23", "model_version": "CardioWatch with the refined rule-based DETECT algorithm", "outcome": "recurred", "source": "Edgar et al. (2026) Lancet Reg Health Eur 67:101791 (quote: 'In the test set, sensitivity was 100% (23/23; 95% CI 82–100%), with one false positive alert.')" }, { "date": "2026-04-14", "setting": "Multicentre DETECT-1b, 50 adults with induced pulseless VT or VF during ablation or S-ICD implantation, Netherlands", "model_version": "CardioWatch, DETECT-1a algorithm with a 10-second window", "outcome": "recurred", "source": "Edgar et al. (2026) Circ Arrhythm Electrophysiol 19(5):e014708, https://pmc.ncbi.nlm.nih.gov/articles/PMC13182813/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0299", "title": "HEART-SAFE algorithm on Samsung Watch5 Pro PPG data identifies an 82-year-old's terminal cardiac arrest during palliative withdrawal at Amsterdam UMC; retrospective, no outcome changed", "summary": "Amsterdam UMC case: a Samsung Watch5 Pro worn after treatment withdrawal captured PPG; the HEART-SAFE algorithm, run afterwards, marked circulatory arrest in step with the ECG; the patient died.", "date_observed": "2026-01-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Van den Beuken, Tuinman, Nideröst, Goossen, van Schuppen, Loer, Schwarte and Schober reported in Resuscitation Plus on 29 January 2026. They are of Amsterdam UMC with Utek B.V. and MiBida (the HEART-SAFE project's partners). The event is undated. They call it the first detailed description of automated detection of a spontaneous, non-procedural cardiac arrest from consumer smartwatch data. An 82-year-old man with a right cerebellar hemorrhage and documented do-not-resuscitate directives was moved to palliative care. After about 42 hours life-sustaining treatment was withdrawn, and he died about 1.5 hours later. With the family's consent a Samsung Watch5 Pro was placed on his right wrist about 40 minutes after withdrawal. Electrocardiogram (ECG), invasive arterial pressure and clinical photoplethysmography (PPG) served as reference. The green-light PPG signal was later run through the group's previously described algorithm. It analyzes five-second windows using peak detection with minimum-amplitude safeguards. It flagged circulatory arrest when the ECG showed agonal bradycardia with the monitor reading 0/min and mean arterial pressure had fallen to 9 mmHg. Low-amplitude oscillations at about 30 per minute persisted at that point. It produced no false alarms over the observation period. The authors state that the algorithm was applied retrospectively. They say they chose not to run it live on the device, because it is still in development and to avoid alarms disturbing the family. They state that the controlled end-of-life setting does not represent out-of-hospital cardiac arrest. Their 2025 proof-of-principle study (Resuscitation; abstract read) reported 28 of 31 circulatory arrests identified. The subjects were volunteers with cuff-restricted arm flow, cardioplegic surgery patients and slaughtered swine. Alerts were delivered to the HartslagNu test environment. Samsung is not an author. The source text describes peak detection, not machine learning.", "category": "general benefit", "unexpected": false, "purpose": "The HEART-SAFE project builds device-independent software to detect circulatory arrest from smartwatch photoplethysmography and alert emergency services. This case tests the detection half on a true arrest.", "system": "HEART-SAFE photoplethysmography cardiac-arrest detection algorithm applied to Samsung Watch5 Pro sensor data", "model_version": "Samsung Watch5 Pro; HEART-SAFE preliminary algorithm as described in the 2025 proof-of-principle", "developer": "HEART-SAFE project (Amsterdam UMC with Utek B.V. and MiBida) for the algorithm; Samsung for the Watch5 Pro", "deployer": "Amsterdam UMC intensive care unit (feasibility evaluation with institutional review board approval)", "location": "Amsterdam, the Netherlands", "domain": "Emergency medicine / resuscitation", "segment": "Research use of a consumer smartwatch for automated cardiac-arrest detection", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "A post-hoc detection on one case is read as task performance; nothing changed for the patient.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The patient died as expected under palliative withdrawal. The detection was retrospective and no alert, treatment or resuscitation followed." }, { "group": "societal", "depth": null, "reason": "The authors present the case as a step toward real-world detection of unwitnessed arrests. No deployment or survival outcome exists." } ], "ai_role": { "status": "assessed", "statement": "The algorithm was applied after the fact to exported green-PPG data. It marked the arrest when residual pulse amplitude fell below its thresholds, shortly before the monitor flatlined, with no false alarms. It was not running on the watch and triggered nothing. Only the developers' own papers describe the event. They describe peak detection with amplitude safeguards rather than machine learning. Samsung's role is limited to the hardware." }, "evidence": [ { "kind": "case report", "citation": "van den Beuken WMF, Tuinman PR, Nideröst B, Goossen SA, van Schuppen H, Loer SA, Schwarte LA, Schober P (2026). First automated detection of a cardiac arrest using a commercially available smartwatch: a case report. Resuscitation Plus 28:101247 (PMC12914423). Authors are the algorithm's developers (HEART-SAFE).", "title": "First automated detection of a cardiac arrest using a commercially available smartwatch: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914423/", "date": "2026-01-29", "written_by": "makers", "quote": "The algorithm accurately identified the moment of cardiac arrest in concordance with the clinical reference signals." }, { "kind": "case report", "citation": "van den Beuken et al. (2026), Resusc Plus 28:101247, case presentation.", "title": "First automated detection of a cardiac arrest using a commercially available smartwatch: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914423/", "date": "2026-01-29", "written_by": "makers", "quote": "a commercial consumer-grade smartwatch, Samsung Watch5 Pro, was placed on the patient's right wrist approximately 40 min after WLST." }, { "kind": "case report", "citation": "van den Beuken et al. (2026), Resusc Plus 28:101247, discussion.", "title": "First automated detection of a cardiac arrest using a commercially available smartwatch: a case report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914423/", "date": "2026-01-29", "written_by": "makers", "quote": "A key limitation of this report is that the algorithm was applied retrospectively rather than in real time." }, { "kind": "peer-reviewed study", "citation": "van den Beuken WMF, Nideröst B, Goossen SA, Kooy TA, Demirtas D, Autar D, Loer SA, Eberl S, van Halm VP, Winkler BE, van Schuppen H, Tuinman PR, Schwarte LA, Schober P (2025). Automated cardiac arrest detection and emergency service alerting using device-independent smartwatch technology: proof-of-principle. Resuscitation 213:110657; doi:10.1016/j.resuscitation.2025.110657.", "title": "Automated cardiac arrest detection and emergency service alerting using device-independent smartwatch technology: proof-of-principle", "url": "https://doi.org/10.1016/j.resuscitation.2025.110657", "date": "2025-05-22", "written_by": "makers", "quote": "Across all three groups, 28 of 31 circulatory arrests were correctly identified, sensitivity 90.3% (95% CI: 74.2%-98.0%), and hour-level specificity was 94.1% (95% CI: 71.3%-99.9%)." }, { "kind": "other", "citation": "Veigl C, Billig S (2026). A digital witness for cardiac arrest: are wearables ready for real-world use? Resuscitation Plus 28:101246 (editorial accompanying the case report; PMC12914390).", "title": "A digital witness for cardiac arrest: are wearables ready for real-world use?", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914390/", "date": "2026-01-29", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A consumer smartwatch collecting green-light PPG through the project's own data-collection software", "Reference ECG, arterial pressure and clinical PPG to time the arrest", "Retrospective application of the HEART-SAFE peak-detection algorithm with minimum-amplitude safeguards" ], "must_hold": [ "A live on-device implementation, which the authors deliberately did not use", "Specificity high enough not to overburden emergency services, which the 2025 study says is still needed", "Transfer from a slow, bradycardic end-of-life arrest to sudden arrhythmic out-of-hospital arrests, which the authors say the case does not represent" ], "echoes": [ { "date": "2025-05-22", "setting": "Proof-of-principle: volunteers with cuff-restricted arm flow, cardioplegic cardiac-surgery patients and slaughtered swine, with test alerts to the HartslagNu responder network", "model_version": "Samsung Watch5 and Watch5 Pro", "outcome": "recurred", "source": "van den Beuken et al. (2025) Resuscitation, doi:10.1016/j.resuscitation.2025.110657 (28 of 31 arrests detected)" } ] }, "paired_incident": null, "headline": "HEART-SAFE algorithm flags a terminal arrest from Watch5 Pro PPG", "metric": null, "comparator": { "against": "the clinical reference signals (ECG, invasive arterial pressure and clinical photoplethysmography) recorded alongside the watch", "before": null, "after": "The algorithm accurately identified the moment of cardiac arrest in concordance with the clinical reference signals.", "basis": "measured", "quote": "At the moment the algorithm identified circulatory arrest, the ECG showed agonal bradycardia, with the monitor displaying a heart rate of 0/min.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914423/" }, "later": { "status": "unknown", "date": null, "note": "Nothing dated after the January 2026 case report was found; the group's proof-of-principle study predates it and the accompanying editorial reports no trial.", "quote": null, "url": null }, "value": null, "developer_country": "Netherlands", "deployer_country": "Netherlands", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12914423/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=EXT_ID:36386769%20AND%20SRC:MED&resultType=core&format=json; https://en.wikipedia.org/wiki/Amsterdam_UMC", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: one other independent source, the makers' peer-reviewed study and the makers' case report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0299", "catalog_version": "1.0.0", "source_fingerprint": "635582fad217b2702fb1a97db835a0d0bbcc4be6a4bd69b1e4f82b9252ea2f54", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0299-source-0001", "AIBD-0299-source-0002", "AIBD-0299-source-0003", "AIBD-0299-source-0004", "AIBD-0299-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "HEART-SAFE project (Amsterdam UMC with Utek B.V. and MiBida) for the algorithm; Samsung for the Watch5 Pro", "deployer": "Amsterdam UMC intensive care unit (feasibility evaluation with institutional review board approval)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The algorithm was applied after the fact to exported green-PPG data. It marked the arrest when residual pulse amplitude fell below its thresholds, shortly before the monitor flatlined, with no false alarms. It was not running on the watch and triggered nothing. Only the developers' own papers describe the event. They describe peak detection with amplitude safeguards rather than machine learning. Samsung's role is limited to the hardware." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The algorithm was applied after the fact to exported green-PPG data. It marked the arrest when residual pulse amplitude fell below its thresholds, shortly before the monitor flatlined, with no false alarms. It was not running on the watch and triggered nothing. Only the developers' own papers describe the event. They describe peak detection with amplitude safeguards rather than machine learning. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The patient died as expected under palliative withdrawal. The detection was retrospective and no alert, treatment or resuscitation followed." }, { "group": "societal", "reason": "The authors present the case as a step toward real-world detection of unwitnessed arrests. No deployment or survival outcome exists." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "The patient died as expected under palliative withdrawal. The detection was retrospective and no alert, treatment or resuscitation followed." }, { "group": "societal", "reason": "The authors present the case as a step toward real-world detection of unwitnessed arrests. 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"evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Nothing dated after the January 2026 case report was found; the group's proof-of-principle study predates it and the accompanying editorial reports no trial." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0299" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Task Accuracy", "taxonomy_note": "A post-hoc detection on one case is read as task performance; nothing changed for the patient." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Van den Beuken, Tuinman, Nideröst, Goossen, van Schuppen, Loer, Schwarte and Schober reported in Resuscitation Plus on 29 January 2026. They are of Amsterdam UMC with Utek B.V. and MiBida (the HEART-SAFE project's partners). The event is undated. They call it the first detailed description of automated detection of a spontaneous, non-procedural cardiac arrest from consumer smartwatch data. An 82-year-old man with a right cerebellar hemorrhage and documented do-not-resuscitate directives was moved to palliative care. After about 42 hours life-sustaining treatment was withdrawn, and he died about 1.5 hours later. With the family's consent a Samsung Watch5 Pro was placed on his right wrist about 40 minutes after withdrawal. Electrocardiogram (ECG), invasive arterial pressure and clinical photoplethysmography (PPG) served as reference. The green-light PPG signal was later run through the group's previously described algorithm. It analyzes five-second windows using peak detection with minimum-amplitude safeguards. It flagged circulatory arrest when the ECG showed agonal bradycardia with the monitor reading 0/min and mean arterial pressure had fallen to 9 mmHg. Low-amplitude oscillations at about 30 per minute persisted at that point. It produced no false alarms over the observation period. The authors state that the algorithm was applied retrospectively. They say they chose not to run it live on the device, because it is still in development and to avoid alarms disturbing the family. They state that the controlled end-of-life setting does not represent out-of-hospital cardiac arrest. Their 2025 proof-of-principle study (Resuscitation; abstract read) reported 28 of 31 circulatory arrests identified. The subjects were volunteers with cuff-restricted arm flow, cardioplegic surgery patients and slaughtered swine. Alerts were delivered to the HartslagNu test environment. Samsung is not an author. 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They are of Amsterdam UMC with Utek B.V. and MiBida (the HEART-SAFE project's partners). The event is undated. They call it the first detailed description of automated detection of a spontaneous, non-procedural cardiac arrest from consumer smartwatch data. An 82-year-old man with a right cerebellar hemorrhage and documented do-not-resuscitate directives was moved to palliative care. After about 42 hours life-sustaining treatment was withdrawn, and he died about 1.5 hours later. With the family's consent a Samsung Watch5 Pro was placed on his right wrist about 40 minutes after withdrawal. Electrocardiogram (ECG), invasive arterial pressure and clinical photoplethysmography (PPG) served as reference. The green-light PPG signal was later run through the group's previously described algorithm. It analyzes five-second windows using peak detection with minimum-amplitude safeguards. 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They are of Amsterdam UMC with Utek B.V. and MiBida (the HEART-SAFE project's partners). The event is undated. They call it the first detailed description of automated detection of a spontaneous, non-procedural cardiac arrest from consumer smartwatch data. An 82-year-old man with a right cerebellar hemorrhage and documented do-not-resuscitate directives was moved to palliative care. After about 42 hours life-sustaining treatment was withdrawn, and he died about 1.5 hours later. With the family's consent a Samsung Watch5 Pro was placed on his right wrist about 40 minutes after withdrawal. Electrocardiogram (ECG), invasive arterial pressure and clinical photoplethysmography (PPG) served as reference. The green-light PPG signal was later run through the group's previously described algorithm. It analyzes five-second windows using peak detection with minimum-amplitude safeguards. It flagged circulatory arrest when the ECG showed agonal bradycardia with the monitor reading 0/min and mean arterial pressure had fallen to 9 mmHg. Low-amplitude oscillations at about 30 per minute persisted at that point. It produced no false alarms over the observation period. The authors state that the algorithm was applied retrospectively. They say they chose not to run it live on the device, because it is still in development and to avoid alarms disturbing the family. They state that the controlled end-of-life setting does not represent out-of-hospital cardiac arrest. Their 2025 proof-of-principle study (Resuscitation; abstract read) reported 28 of 31 circulatory arrests identified. The subjects were volunteers with cuff-restricted arm flow, cardioplegic surgery patients and slaughtered swine. Alerts were delivered to the HartslagNu test environment. Samsung is not an author. The source text describes peak detection, not machine learning.", "replication": { "produced_by": [ "A consumer smartwatch collecting green-light PPG through the project's own data-collection software", "Reference ECG, arterial pressure and clinical PPG to time the arrest", "Retrospective application of the HEART-SAFE peak-detection algorithm with minimum-amplitude safeguards" ], "must_hold": [ "A live on-device implementation, which the authors deliberately did not use", "Specificity high enough not to overburden emergency services, which the 2025 study says is still needed", "Transfer from a slow, bradycardic end-of-life arrest to sudden arrhythmic out-of-hospital arrests, which the authors say the case does not represent" ], "echoes": [ { "date": "2025-05-22", "setting": "Proof-of-principle: volunteers with cuff-restricted arm flow, cardioplegic cardiac-surgery patients and slaughtered swine, with test alerts to the HartslagNu responder network", "model_version": "Samsung Watch5 and Watch5 Pro", "outcome": "recurred", "source": "van den Beuken et al. (2025) Resuscitation, doi:10.1016/j.resuscitation.2025.110657 (28 of 31 arrests detected)" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0309", "title": "ProRail replaces 288 lineside cameras with AI “smart cameras” in 2026 and uses Genetec video analytics across 7,000 cameras to flag trespassers to train dispatchers", "summary": "SpoorPro: ProRail swaps 288 lineside cameras for smart cameras in 2026, tests drones and runs Genetec video analytics on 7,000 cameras to flag trespassers to dispatchers; no results are given.", "date_observed": "2026-02-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "SpoorPro.nl reported on 2 February 2026 that ProRail, the Dutch rail infrastructure manager, is replacing 288 lineside cameras in 2026 with new “smart” cameras. ProRail is also testing drones that fly autonomously and analyze images. ProRail is quoted that these forms of camera surveillance help it see and prevent incidents sooner, making the track safer with fewer disruptions and delays. The article's photo caption says the AI cameras' images are monitored 24/7. The rest of the text is behind a paywall. SpoorPro reported on 3 March 2026 that ProRail is bringing the 7,000 security cameras it manages into one Genetec platform. It is monitored from ProRail's Smart Monitoring Room. Genetec Mission Control filters and analyzes alerts and forwards relevant images to an operator with suggested actions. Video analysis is used among other things to flag spoorlopers (people on the track). In that case the train dispatcher can warn drivers. The article quotes ProRail project lead Kristian Ruiter and Genetec's Bob van Keulen. No source gives a detection count, a stopped train or a trespass reduction attributable to the analytics. No source on record identifies a UIC trespass-detection trial.", "category": "general benefit", "unexpected": false, "purpose": "Camera upgrades and video analytics intended to detect incidents such as trespassers sooner so that dispatchers can warn drivers. No detection event is documented.", "system": "ProRail smart lineside cameras with Genetec Security Center / Mission Control video analytics", "model_version": null, "developer": "Genetec (video management and analytics platform); the smart-camera supplier is not named", "deployer": "ProRail", "location": "Netherlands", "domain": "Railway safety / trespass detection", "segment": "Rail infrastructure camera surveillance", "benefit_type": "Increased Product Safety", "taxonomy_note": "Deployment only; trespass detection for dispatchers is read as a safety detection mechanism.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "ProRail says the cameras help it see and prevent incidents sooner. No incident, detection count or delay figure is published." }, { "group": "societal", "depth": null, "reason": "Fewer trespass incidents and disruptions are the stated aim. No before-and-after data are given." } ], "ai_role": { "status": "unassessed", "statement": "No incident is documented. The AI character of the cameras rests on SpoorPro's caption and ProRail's “smart cameras”. The trespasser-flagging function is described by Genetec, the platform vendor. Whether the analytics changed any outcome is not reported. The full 2 February 2026 article is paywalled." }, "evidence": [ { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail zet 288 nóg slimmere camera's in langs het spoor. 2 February 2026 (remainder paywalled).", "title": "ProRail zet 288 nóg slimmere camera's in langs het spoor", "url": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/", "date": "2026-02-02", "written_by": "independent", "quote": "ProRail vervangt in 2026 in totaal 288 camera's langs het spoor voor nieuwe, slimme camera's." }, { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail gaat alle 7000 beveiligingscamera's centraal monitoren. 3 March 2026 (also published on Mobiliteit.nl).", "title": "ProRail gaat alle 7000 beveiligingscamera's centraal monitoren", "url": "https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "date": "2026-03-03", "written_by": "independent", "quote": "Video-analyse wordt onder meer ingezet om spoorlopers te signaleren. In dat geval kan de treindienstleider machinisten waarschuwen." } ], "replication": { "produced_by": [ "Thousands of lineside and station security cameras brought into one Genetec video-management platform", "Operators in ProRail's Smart Monitoring Room receiving filtered alerts with suggested actions", "Video analytics configured to flag people on the track" ], "must_hold": [ "A dispatcher able to warn drivers once a trespasser is flagged", "Privacy masking and blurring applied to passenger images, as the article states ProRail does" ], "echoes": [] }, "paired_incident": null, "headline": "ProRail uses Genetec analytics on 7,000 cameras to flag trespass", "metric": null, "comparator": { "against": "ProRail's previous lineside camera surveillance (ProRail's own assertion)", "before": null, "after": "incidenten sneller te zien en te voorkomen", "basis": "assumed", "quote": "‘Deze nieuwe vormen van cameratoezicht helpen ons om incidenten sneller te zien en te voorkomen. Dat maakt het spoor veiliger en zorgt voor minder storingen en vertragingen.’", "url": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/" }, "later": { "status": "scaled", "date": "2026-03-03", "note": "A month later SpoorPro reported that ProRail is bringing all 7,000 cameras it manages into one Genetec platform monitored from its Smart Monitoring Room, with video analytics used among other things to flag people on the track to train dispatchers; no detection count or outcome is given.", "quote": "ProRail brengt de 7000 beveiligingscamera’s die de organisatie beheert onder in één geïntegreerd platform van technologiebedrijf Genetec. Daarmee wil de spoorbeheerder incidenten op en rond het spoor sneller signaleren en afhandelen.", "url": "https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/" }, "value": null, "developer_country": "Canada", "deployer_country": "Netherlands", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/; https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.wikidata.org/wiki/Q30267239; https://www.prorail.nl/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0309", "catalog_version": "1.0.0", "source_fingerprint": "a4a48ce8da38592a09e4f07df3b22efedbddebcbe5d7f00ddd3215a53e1fc190", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0309-source-0001", "AIBD-0309-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Genetec (video management and analytics platform); the smart-camera supplier is not named", "deployer": "ProRail" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "No incident is documented. The AI character of the cameras rests on SpoorPro's caption and ProRail's “smart cameras”. The trespasser-flagging function is described by Genetec, the platform vendor. Whether the analytics changed any outcome is not reported. The full 2 February 2026 article is paywalled." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "ProRail says the cameras help it see and prevent incidents sooner. No incident, detection count or delay figure is published." }, { "group": "societal", "reason": "Fewer trespass incidents and disruptions are the stated aim. No before-and-after data are given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "ProRail says the cameras help it see and prevent incidents sooner. No incident, detection count or delay figure is published." }, { "group": "societal", "reason": "Fewer trespass incidents and disruptions are the stated aim. No before-and-after data are given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-03-03", "note": "A month later SpoorPro reported that ProRail is bringing all 7,000 cameras it manages into one Genetec platform monitored from its Smart Monitoring Room, with video analytics used among other things to flag people on the track to train dispatchers; no detection count or outcome is given.", "quote": "ProRail brengt de 7000 beveiligingscamera’s die de organisatie beheert onder in één geïntegreerd platform van technologiebedrijf Genetec. Daarmee wil de spoorbeheerder incidenten op en rond het spoor sneller signaleren en afhandelen.", "url": "https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0309" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "Deployment only; trespass detection for dispatchers is read as a safety detection mechanism." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "SpoorPro.nl reported on 2 February 2026 that ProRail, the Dutch rail infrastructure manager, is replacing 288 lineside cameras in 2026 with new “smart” cameras. ProRail is also testing drones that fly autonomously and analyze images. ProRail is quoted that these forms of camera surveillance help it see and prevent incidents sooner, making the track safer with fewer disruptions and delays. The article's photo caption says the AI cameras' images are monitored 24/7. The rest of the text is behind a paywall. SpoorPro reported on 3 March 2026 that ProRail is bringing the 7,000 security cameras it manages into one Genetec platform. It is monitored from ProRail's Smart Monitoring Room. Genetec Mission Control filters and analyzes alerts and forwards relevant images to an operator with suggested actions. Video analysis is used among other things to flag spoorlopers (people on the track). In that case the train dispatcher can warn drivers. The article quotes ProRail project lead Kristian Ruiter and Genetec's Bob van Keulen. No source gives a detection count, a stopped train or a trespass reduction attributable to the analytics. No source on record identifies a UIC trespass-detection trial.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "ProRail says the cameras help it see and prevent incidents sooner. No incident, detection count or delay figure is published." }, { "group": "societal", "reason": "Fewer trespass incidents and disruptions are the stated aim. No before-and-after data are given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Camera upgrades and video analytics intended to detect incidents such as trespassers sooner so that dispatchers can warn drivers. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Netherlands", "developer_country": "Canada", "deployer_country": "Netherlands" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Camera upgrades and video analytics intended to detect incidents such as trespassers sooner so that dispatchers can warn drivers. No detection event is documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-02-02", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/; https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.wikidata.org/wiki/Q30267239; https://www.prorail.nl/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Thousands of lineside and station security cameras brought into one Genetec video-management platform", "Operators in ProRail's Smart Monitoring Room receiving filtered alerts with suggested actions", "Video analytics configured to flag people on the track" ], "must_hold": [ "A dispatcher able to warn drivers once a trespasser is flagged", "Privacy masking and blurring applied to passenger images, as the article states ProRail does" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/; https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.wikidata.org/wiki/Q30267239; https://www.prorail.nl/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Railway safety / trespass detection", "segment": "Rail infrastructure camera surveillance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail zet 288 nóg slimmere camera's in langs het spoor. 2 February 2026 (remainder paywalled).", "title": "ProRail zet 288 nóg slimmere camera's in langs het spoor", "url": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/", "date": "2026-02-02", "written_by": "independent", "quote": "ProRail vervangt in 2026 in totaal 288 camera's langs het spoor voor nieuwe, slimme camera's." }, { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail gaat alle 7000 beveiligingscamera's centraal monitoren. 3 March 2026 (also published on Mobiliteit.nl).", "title": "ProRail gaat alle 7000 beveiligingscamera's centraal monitoren", "url": "https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "date": "2026-03-03", "written_by": "independent", "quote": "Video-analyse wordt onder meer ingezet om spoorlopers te signaleren. In dat geval kan de treindienstleider machinisten waarschuwen." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0309-source-0001", "AIBD-0309-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail zet 288 nóg slimmere camera's in langs het spoor. 2 February 2026 (remainder paywalled).", "title": "ProRail zet 288 nóg slimmere camera's in langs het spoor", "url": "https://www.spoorpro.nl/actueel/2026/02/02/prorail-zet-288-nog-slimmere-cameras-in-langs-het-spoor/", "date": "2026-02-02", "written_by": "independent", "quote": "ProRail vervangt in 2026 in totaal 288 camera's langs het spoor voor nieuwe, slimme camera's." }, { "kind": "news report", "citation": "SpoorPro.nl (2026). ProRail gaat alle 7000 beveiligingscamera's centraal monitoren. 3 March 2026 (also published on Mobiliteit.nl).", "title": "ProRail gaat alle 7000 beveiligingscamera's centraal monitoren", "url": "https://www.spoorpro.nl/innovatie/2026/03/03/prorail-centraliseert-7-000-cameras-in-een-uniform-platform-voor-spoortoezicht/", "date": "2026-03-03", "written_by": "independent", "quote": "Video-analyse wordt onder meer ingezet om spoorlopers te signaleren. In dat geval kan de treindienstleider machinisten waarschuwen." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "SpoorPro: ProRail swaps 288 lineside cameras for smart cameras in 2026, tests drones and runs Genetec video analytics on 7,000 cameras to flag trespassers to dispatchers; no results are given.", "account": "SpoorPro.nl reported on 2 February 2026 that ProRail, the Dutch rail infrastructure manager, is replacing 288 lineside cameras in 2026 with new “smart” cameras. ProRail is also testing drones that fly autonomously and analyze images. ProRail is quoted that these forms of camera surveillance help it see and prevent incidents sooner, making the track safer with fewer disruptions and delays. The article's photo caption says the AI cameras' images are monitored 24/7. The rest of the text is behind a paywall. SpoorPro reported on 3 March 2026 that ProRail is bringing the 7,000 security cameras it manages into one Genetec platform. It is monitored from ProRail's Smart Monitoring Room. Genetec Mission Control filters and analyzes alerts and forwards relevant images to an operator with suggested actions. Video analysis is used among other things to flag spoorlopers (people on the track). In that case the train dispatcher can warn drivers. The article quotes ProRail project lead Kristian Ruiter and Genetec's Bob van Keulen. No source gives a detection count, a stopped train or a trespass reduction attributable to the analytics. No source on record identifies a UIC trespass-detection trial." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ProRail smart lineside cameras with Genetec Security Center / Mission Control video analytics" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Genetec (video management and analytics platform); the smart-camera supplier is not named" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ProRail replaces 288 lineside cameras with AI “smart cameras” in 2026 and uses Genetec video analytics across 7,000 cameras to flag trespassers to train dispatchers", "headline": "ProRail uses Genetec analytics on 7,000 cameras to flag trespass" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a4a48ce8da38592a09e4f07df3b22efedbddebcbe5d7f00ddd3215a53e1fc190" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "SpoorPro.nl reported on 2 February 2026 that ProRail, the Dutch rail infrastructure manager, is replacing 288 lineside cameras in 2026 with new “smart” cameras. ProRail is also testing drones that fly autonomously and analyze images. ProRail is quoted that these forms of camera surveillance help it see and prevent incidents sooner, making the track safer with fewer disruptions and delays. The article's photo caption says the AI cameras' images are monitored 24/7. The rest of the text is behind a paywall. SpoorPro reported on 3 March 2026 that ProRail is bringing the 7,000 security cameras it manages into one Genetec platform. It is monitored from ProRail's Smart Monitoring Room. Genetec Mission Control filters and analyzes alerts and forwards relevant images to an operator with suggested actions. Video analysis is used among other things to flag spoorlopers (people on the track). In that case the train dispatcher can warn drivers. The article quotes ProRail project lead Kristian Ruiter and Genetec's Bob van Keulen. No source gives a detection count, a stopped train or a trespass reduction attributable to the analytics. No source on record identifies a UIC trespass-detection trial.", "replication": { "produced_by": [ "Thousands of lineside and station security cameras brought into one Genetec video-management platform", "Operators in ProRail's Smart Monitoring Room receiving filtered alerts with suggested actions", "Video analytics configured to flag people on the track" ], "must_hold": [ "A dispatcher able to warn drivers once a trespasser is flagged", "Privacy masking and blurring applied to passenger images, as the article states ProRail does" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0155", "title": "LEADERG's “AI door god” camera analytics at Beigang Wude Temple flags smoke in an empty office a minute before charging lithium batteries burst; the night clerk and Yunlin firefighters hold the 5 February 2026 fire to ten square meters, nobody hurt, main hall untouched", "summary": "AI camera analytics flagged smoke in an empty temple office a minute before a battery fire; held to 10 m², no injuries, main hall intact.", "date_observed": "2026-02-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "At about 05:30 on 5 February 2026 the AI門神 (AI door god) system flagged smoke in a first-floor office and machine room, empty after hours. The system is run by 立達軟體 (LEADERG Inc.) over the closed-circuit television (CCTV) of Beigang Wude Temple, Yunlin County, Taiwan. It messaged the front desk, the general manager and chairman 林安樂, in Japan, by LINE. The night-duty clerk reached the room with an extinguisher within a minute. At 05:33 overheated lithium batteries beside a tool charger burst and flames spread. Staff called 119 at 05:36. Yunlin County Fire Bureau crews arrived at 05:44, controlled it at 06:10 and put it out at 06:14. Ten square meters burned. Nobody was hurt. The main hall and statues were untouched.", "category": "protective response", "unexpected": false, "purpose": "AI門神 (“AI door god: temple AI fire-and-theft prevention system”) was built to run AI image recognition over a temple's existing CCTV. It was built to detect excess smoke, flame and suspicious behavior, and to alert staff by SMS, LINE or email. CTS reported in December 2024 that Wude Temple's door-god system would sound an alarm at once on abnormal smoke. Flagging smoke before a fire was exactly its designed purpose.", "system": "AI門神：宮廟AI防火防盜系統 (AI Door God: temple AI fire-and-theft prevention system), AI image recognition over the temple's existing CCTV with alerts by SMS, LINE and email", "model_version": "Not named. Advantech's case study says the image-recognition algorithms were developed with a large language model as the basis and run on an Advantech IPC-730 with a SKY-QUAD-5000A-32 accelerator card at about five seconds per frame.", "developer": "立達軟體科技股份有限公司 (LEADERG Inc.), Taiwan", "deployer": "北港武德宮 (Beigang Wude Temple)", "location": "Beigang, Taiwan", "domain": "Fire safety (religious site)", "segment": "Temple and cultural-asset protection: AI video analytics on existing CCTV", "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm.", "registry_ids": { "oecd_aim": "2026-02-04-4944" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The temple's loss was the contents of one first-floor office of about ten square meters (staff lockers, some tea, sweets, incense and joss paper). The main hall, statues and worship areas were untouched. The temple stayed open in the run-up to the Lunar New Year crowds. The fire bureau credited the reinforced-concrete structure and its own eight-minute arrival for the containment. A conventional smoke alarm sounded as well. So the share attributable to the AI alert is a minute or two of earlier warning, not the whole saved building." } ], "ai_role": { "status": "assessed", "statement": "The system's documented contribution is the first alert. By the temple's own log it detected smoke at 05:30, a minute before the lithium batteries burst at 05:33. It messaged the front desk, the general manager and the chairman in sequence over LINE. That is how a chairman asleep in Nara came to follow the fire on the temple's cameras. The suppression was human. The clerk's extinguisher failed once the batteries burst. The Yunlin County Fire Bureau's eight trucks and eighteen firefighters, called at 05:36, controlled the fire at 06:10. UDN reports that a residential smoke alarm (住警器) sounded as well. The Third Brigade commander 陳岳謄 attributed the containment to the building's reinforced-concrete structure and the crews' quick arrival without mentioning the AI. The LINE relay from the vendor is the chairman's account, not the bureau's." }, "evidence": [ { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷. UDN, 5 February 2026.", "title": "「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷", "url": "https://udn.com/news/story/7320/9310088", "date": "2026-02-05", "written_by": "independent", "quote": "幸廟內設有AI警報系統及住警器，馬上發出警報聲響" }, { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場. UDN, 5 February 2026.", "title": "強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場", "url": "https://udn.com/news/story/7320/9310526", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢發生前一分鐘系統即已示警煙霧產生" }, { "kind": "news report", "citation": "吳淑萍 / TVBS新聞網 (2026). 北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟. TVBS, 5 February 2026.", "title": "北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟", "url": "https://news.tvbs.com.tw/local/3120819", "date": "2026-02-05", "written_by": "independent", "quote": "5點30分系統偵測到煙霧，5點32分人工察看確認狀況" }, { "kind": "news report", "citation": "蘇榮泉 / 觀傳媒 (2026). （有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "（有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控", "url": "https://n.yam.com/Article/20260205444546", "date": "2026-02-05", "written_by": "independent", "quote": "消防人員於6時10分成功控制火勢，並於6時14分完全撲滅" }, { "kind": "news report", "citation": "洪佳伶 / 觀傳媒 (2026). AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢", "url": "https://n.yam.com/Article/20260205197916", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢轉劇前一分鐘便偵測到煙霧，並依序通知櫃檯、總幹事" }, { "kind": "news report", "citation": "華視新聞 / CTS (2026). 「AI門神」立功！　武德宮火警偵測回報　快速控制火勢. CTS News, 5 February 2026.", "title": "「AI門神」立功！　武德宮火警偵測回報　快速控制火勢", "url": "https://news.cts.com.tw/cts/general/202602/202602052559104.html", "date": "2026-02-05", "written_by": "independent", "quote": "好險有AI門神，幫我們守護住，所以我們可以趕快第一時間" }, { "kind": "news report", "citation": "鄧庭婷 / NOWnews今日新聞 (2026). 北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸. NOWnews, 5 February 2026.", "title": "北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸", "url": "https://www.nownews.com/news/6783602", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火起前的關鍵一分鐘發出示警" }, { "kind": "news report", "citation": "莊曜聰 / 壹蘋新聞網 (2026). 北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」. NextApple, 5 February 2026.", "title": "北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」", "url": "https://news.nextapple.com/local/20260205/E631BE3355F1C46E511BAEBE0A5D0D61", "date": "2026-02-05", "written_by": "independent", "quote": "還有「門神系統」可以示警防災，這次果然派上用場" }, { "kind": "news report", "citation": "蘇峯毅 / 台灣好報 (2026). 清晨火警驚魂　北港武德宮即時搶救守住信仰中心. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "清晨火警驚魂　北港武德宮即時搶救守住信仰中心", "url": "https://n.yam.com/Article/20260205590605", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火勢形成前即已示警，加上長年夜間留守制度" }, { "kind": "news report", "citation": "華視新聞 / CTS (2024). AI進駐宮廟　統計人流.預防火災還能「解籤詩」. Syndicated on Yahoo奇摩新聞, 23 December 2024.", "title": "AI進駐宮廟　統計人流.預防火災還能「解籤詩」", "url": "https://tw.news.yahoo.com/ai%E9%80%B2%E9%A7%90%E5%AE%AE%E5%BB%9F-%E7%B5%B1%E8%A8%88%E4%BA%BA%E6%B5%81-%E9%A0%90%E9%98%B2%E7%81%AB%E7%81%BD%E9%82%84%E8%83%BD-%E8%A7%A3%E7%B1%A4%E8%A9%A9-121500289.html", "date": "2024-12-23", "written_by": "independent", "quote": "門神系統，只要偵測到煙霧異常，有火災的疑慮，會立刻發出警報" }, { "kind": "press release", "citation": "Advantech (2025). 立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護. Advantech case study, 15 April 2025.", "title": "立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護", "url": "https://www.advantech.com/en-us/resources/case-study/%E7%AB%8B%E9%81%94%E8%BB%9F%E9%AB%94%E6%94%9C%E6%89%8B%E7%A0%94%E8%8F%AFai%E9%96%80%E7%A5%9E%EF%BC%9A%E5%89%B5%E6%96%B0%E6%8A%80%E8%A1%93%E5%8A%A9%E5%8A%9B%E5%AF%BA%E5%BB%9F%E6%96%87%E5%8C%96%E8%B3%87%E7%94%A2%E4%BF%9D%E8%AD%B7", "date": "2025-04-15", "written_by": "makers", "quote": "偵測特定區域內是否有過量的煙霧、火焰及可疑行為" }, { "kind": "news report", "citation": "聯合新聞網 UDN (2026). 指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」. udn.com, 25 August 2026.", "title": "指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」", "url": "https://udn.com/news/story/7326/9714008", "date": "2026-08-25", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A camera-analytics system (AI門神) already watching the office over the temple's existing CCTV. It was set to alert on small amounts of smoke and to message a named chain of people (front desk, general manager, chairman) over LINE.", "A staffed night watch. The temple has kept someone on duty every night since it moved to the site in 1980 (民國69年). So the alert had a clerk a minute away with an extinguisher.", "A slow start to the fire. A tool charger and lithium batteries smoked before the batteries burst at 05:33, which gave the alert a minute's lead.", "A fire brigade eight minutes away and a reinforced-concrete annex that held the fire to one room, as the Third Brigade commander said." ], "must_hold": [ "The alert reaches a person who can act within minutes. At an unstaffed site the lead time is worth little.", "The camera covers the rooms where fires start (here an office and machine room with chargers, beside stored joss paper), not only the shrine.", "The AI alert complements conventional detectors rather than replacing them. A residential smoke alarm sounded here as well." ], "echoes": [ { "date": null, "setting": "OECD AIM 2023-09-12-f6ac: ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna, human operators verify it and Cal Fire holds the fire (camera smoke detection with a human in the loop and a brigade response).", "model_version": null, "outcome": "unknown", "source": null }, { "date": null, "setting": "OECD AIM 2025-09-13-b5dc: Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner (Taiwanese camera smoke analytics in a different use).", "model_version": null, "outcome": "unknown", "source": null } ] }, "paired_incident": null, "headline": "LEADERG's AI door god flags smoke; temple fire held to 10 m²", "metric": "held to 10 m², no injuries, main hall intact", "comparator": { "against": "the temple's overnight duty staff relying on their own watch, without the AI smoke alert", "before": null, "after": "在火勢轉劇前一分鐘便偵測到煙霧", "basis": "assumed", "quote": "AI系統非常專業，在火勢轉劇前一分鐘便偵測到煙霧，並依序通知櫃檯、總幹事及我本人", "url": "https://n.yam.com/Article/20260205197916" }, "later": { "status": "persisted", "date": "2026-08-25", "note": "In August 2026, after the Zhinan Temple fire in Taipei, UDN reported Wude Temple still relying on its AI alarm system combined with the cameras, recounting the February fire as the case that proved it; no other temple adopting the system is reported.", "quote": "今年2月廟的右側辦公室、倉庫，也在清晨沒人時發生火警，幸好廟方全面改裝「AI警報系統」結合監視器", "url": "https://udn.com/news/story/7326/9714008" }, "value": null, "developer_country": "Taiwan", "deployer_country": "Taiwan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a smoke alert at 05:30, a minute before the batteries burst, relayed over LINE to the front desk, general manager and chairman) is documented by the temple's own timeline as reported by TVBS, UDN, NOWnews, 觀傳媒 and CTS, and the outcome by the Yunlin County Fire Bureau's figures, but the counterfactual is not shown: UDN reports that a residential smoke alarm (住警器) sounded as well, a clerk was on night duty in any case, and the Third Brigade commander 陳岳謄 credited the RC structure and the crews' quick arrival without mentioning the AI. The Monitor's date of 4 February is the UTC date; every source puts the fire at about 05:30 on 5 February 2026 Taiwan time (21:30 UTC on 4 February), so the date observed is 5 February. Times differ between the temple's log (fire controlled 05:51) and the fire bureau (controlled 06:10, extinguished 06:14); the record uses the bureau's. The cause (a tool charger and lithium batteries) is the chairman's account; UDN's first report says the bureau was still investigating and the secretary general 蘇建華 told TVBS he suspected wiring. The vendor is named by the chairman as 立達軟體; its identity as LEADERG Inc. and the system's design (AI image recognition over existing CCTV on Advantech hardware, alerts by SMS, LINE or email, deployed at Wude Temple) come from Advantech's April 2025 case study, which is partner-authored and used only as an additional source. The Monitor lists China Times, which could not be read (Cloudflare challenge directly and through a text proxy; web.archive.org is blocked for this tool); its four yam.com links are syndications of 觀傳媒 (two), 台灣好報 and 創新聞. The CTS broadcast report of 5 February and CTS's December 2024 piece on the door-god system were found through Brave, as WebSearch was exhausted; DuckDuckGo and Mojeek returned nothing. The chairman's Facebook post was not read; it is quoted by UDN, NOWnews and NextApple. No Yunlin County Fire Bureau release was found on its own site; its statements are quoted by 觀傳媒, 台灣好報 and 創新聞, and CTS quotes the Beigang sub-station chief 陳思淵. The Monitor's country field is “Chinese Taipei”; the record says Taiwan, as every source does. Raw HTML of every source read is kept in src_4944.", "source": "https://oecd.ai/en/incidents/2026-02-04-4944", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://n.yam.com/Article/20260205197916; https://udn.com/news/story/7326/9714008", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.leaderg.com/tw/contact_us; https://zh.wikipedia.org/wiki/北港武德宮", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: 11 independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0155", "catalog_version": "1.0.0", "source_fingerprint": "d9e50b5220d086e0c9bd46b934073b730fafc534e423027f5f3acbdea2c79fa3", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0155-source-0001", "AIBD-0155-source-0002", "AIBD-0155-source-0003", "AIBD-0155-source-0004", "AIBD-0155-source-0005", "AIBD-0155-source-0006", "AIBD-0155-source-0007", "AIBD-0155-source-0008", "AIBD-0155-source-0009", "AIBD-0155-source-0010", "AIBD-0155-source-0011", "AIBD-0155-source-0012" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "立達軟體科技股份有限公司 (LEADERG Inc.), Taiwan", "deployer": "北港武德宮 (Beigang Wude Temple)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system's documented contribution is the first alert. By the temple's own log it detected smoke at 05:30, a minute before the lithium batteries burst at 05:33. It messaged the front desk, the general manager and the chairman in sequence over LINE. That is how a chairman asleep in Nara came to follow the fire on the temple's cameras. The suppression was human. The clerk's extinguisher failed once the batteries burst. The Yunlin County Fire Bureau's eight trucks and eighteen firefighters, called at 05:36, controlled the fire at 06:10. UDN reports that a residential smoke alarm (住警器) sounded as well. The Third Brigade commander 陳岳謄 attributed the containment to the building's reinforced-concrete structure and the crews' quick arrival without mentioning the AI. The LINE relay from the vendor is the chairman's account, not the bureau's." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "According to the temple’s log, AI Door God detected smoke at 05:30 and sent alerts through LINE. The chairman followed the developing fire through the temple’s cameras.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The system's documented contribution is the first alert. By the temple's own log it detected smoke at 05:30, a minute before the lithium batteries burst at 05:33. It messaged the front desk, the general manager and the chairman in sequence over LINE. That is how a chairman asleep in Nara came to follow the fire on the temple's cameras. The suppression was human. The clerk's extinguisher failed once the batteries burst. The Yunlin County Fire Bureau's eight trucks and eighteen firefighters, called at 05:36, controlled the fire at 06:10. UDN reports that a residential smoke alarm (住警器) sounded as well. The Third Brigade commander 陳岳謄 attributed the containment to the building's reinforced-concrete structure and the crews' quick arrival without mentioning the AI. The LINE relay from the vendor is the chairman's account, not the bureau's." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The temple's loss was the contents of one first-floor office of about ten square meters (staff lockers, some tea, sweets, incense and joss paper). The main hall, statues and worship areas were untouched. The temple stayed open in the run-up to the Lunar New Year crowds. The fire bureau credited the reinforced-concrete structure and its own eight-minute arrival for the containment. A conventional smoke alarm sounded as well. So the share attributable to the AI alert is a minute or two of earlier warning, not the whole saved building." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: 11 independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The temple's loss was the contents of one first-floor office of about ten square meters (staff lockers, some tea, sweets, incense and joss paper). The main hall, statues and worship areas were untouched. The temple stayed open in the run-up to the Lunar New Year crowds. The fire bureau credited the reinforced-concrete structure and its own eight-minute arrival for the containment. A conventional smoke alarm sounded as well. So the share attributable to the AI alert is a minute or two of earlier warning, not the whole saved building." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The fire damaged one office, while the main hall and worship areas remained usable. The temple stayed open. The fire bureau credited the concrete structure and firefighters’ arrival for containment. The AI alert provided earlier warning, but the evidence does not isolate its contribution to the damage avoided." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The temple's loss was the contents of one first-floor office of about ten square meters (staff lockers, some tea, sweets, incense and joss paper). The main hall, statues and worship areas were untouched. The temple stayed open in the run-up to the Lunar New Year crowds. The fire bureau credited the reinforced-concrete structure and its own eight-minute arrival for the containment. A conventional smoke alarm sounded as well. So the share attributable to the AI alert is a minute or two of earlier warning, not the whole saved building." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The temple reports that the software detected smoke about one minute before the batteries burst. A conventional smoke alarm also sounded. The AI alert’s separate effect on the damage is unmeasured." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Warning time, area damaged, injuries, and continued use of the temple." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The temple’s account supplies the alert chronology. A residential smoke alarm also sounded. The fire service attributed containment to the building’s concrete structure and the firefighters’ arrival, without identifying a separate contribution from AI.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-02-04-4944" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-08-25", "note": "In August 2026, after the Zhinan Temple fire in Taipei, UDN reported Wude Temple still relying on its AI alarm system combined with the cameras, recounting the February fire as the case that proved it; no other temple adopting the system is reported.", "quote": "今年2月廟的右側辦公室、倉庫，也在清晨沒人時發生火警，幸好廟方全面改裝「AI警報系統」結合監視器", "url": "https://udn.com/news/story/7326/9714008" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "A clerk attempted to extinguish the fire. Firefighters controlled it after the temple called the fire service." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0155" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "Beigang Wude Temple and the people who used it." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Beigang Wude Temple and the people who used it." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 05:30 on 5 February 2026 the AI門神 (AI door god) system flagged smoke in a first-floor office and machine room, empty after hours. The system is run by 立達軟體 (LEADERG Inc.) over the closed-circuit television (CCTV) of Beigang Wude Temple, Yunlin County, Taiwan. It messaged the front desk, the general manager and chairman 林安樂, in Japan, by LINE. The night-duty clerk reached the room with an extinguisher within a minute. At 05:33 overheated lithium batteries beside a tool charger burst and flames spread. Staff called 119 at 05:36. Yunlin County Fire Bureau crews arrived at 05:44, controlled it at 06:10 and put it out at 06:14. Ten square meters burned. Nobody was hurt. The main hall and statues were untouched.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Staff and firefighters contained the temple fire to about 10 m². No one was injured, and the main hall remained intact." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The temple's loss was the contents of one first-floor office of about ten square meters (staff lockers, some tea, sweets, incense and joss paper). The main hall, statues and worship areas were untouched. The temple stayed open in the run-up to the Lunar New Year crowds. The fire bureau credited the reinforced-concrete structure and its own eight-minute arrival for the containment. A conventional smoke alarm sounded as well. So the share attributable to the AI alert is a minute or two of earlier warning, not the whole saved building." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "AI門神 (“AI door god: temple AI fire-and-theft prevention system”) was built to run AI image recognition over a temple's existing CCTV. It was built to detect excess smoke, flame and suspicious behavior, and to alert staff by SMS, LINE or email. CTS reported in December 2024 that Wude Temple's door-god system would sound an alarm at once on abnormal smoke. Flagging smoke before a fire was exactly its designed purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Beigang, Taiwan", "developer_country": "Taiwan", "deployer_country": "Taiwan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "AI門神 (“AI door god: temple AI fire-and-theft prevention system”) was built to run AI image recognition over a temple's existing CCTV. It was built to detect excess smoke, flame and suspicious behavior, and to alert staff by SMS, LINE or email. CTS reported in December 2024 that Wude Temple's door-god system would sound an alarm at once on abnormal smoke. Flagging smoke before a fire was exactly its designed purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-02-05", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a smoke alert at 05:30, a minute before the batteries burst, relayed over LINE to the front desk, general manager and chairman) is documented by the temple's own timeline as reported by TVBS, UDN, NOWnews, 觀傳媒 and CTS, and the outcome by the Yunlin County Fire Bureau's figures, but the counterfactual is not shown: UDN reports that a residential smoke alarm (住警器) sounded as well, a clerk was on night duty in any case, and the Third Brigade commander 陳岳謄 credited the RC structure and the crews' quick arrival without mentioning the AI. The Monitor's date of 4 February is the UTC date; every source puts the fire at about 05:30 on 5 February 2026 Taiwan time (21:30 UTC on 4 February), so the date observed is 5 February. Times differ between the temple's log (fire controlled 05:51) and the fire bureau (controlled 06:10, extinguished 06:14); the record uses the bureau's. The cause (a tool charger and lithium batteries) is the chairman's account; UDN's first report says the bureau was still investigating and the secretary general 蘇建華 told TVBS he suspected wiring. The vendor is named by the chairman as 立達軟體; its identity as LEADERG Inc. and the system's design (AI image recognition over existing CCTV on Advantech hardware, alerts by SMS, LINE or email, deployed at Wude Temple) come from Advantech's April 2025 case study, which is partner-authored and used only as an additional source. The Monitor lists China Times, which could not be read (Cloudflare challenge directly and through a text proxy; web.archive.org is blocked for this tool); its four yam.com links are syndications of 觀傳媒 (two), 台灣好報 and 創新聞. The CTS broadcast report of 5 February and CTS's December 2024 piece on the door-god system were found through Brave, as WebSearch was exhausted; DuckDuckGo and Mojeek returned nothing. The chairman's Facebook post was not read; it is quoted by UDN, NOWnews and NextApple. No Yunlin County Fire Bureau release was found on its own site; its statements are quoted by 觀傳媒, 台灣好報 and 創新聞, and CTS quotes the Beigang sub-station chief 陳思淵. The Monitor's country field is “Chinese Taipei”; the record says Taiwan, as every source does. Raw HTML of every source read is kept in src_4944.", "source": "https://oecd.ai/en/incidents/2026-02-04-4944", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://n.yam.com/Article/20260205197916; https://udn.com/news/story/7326/9714008", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.leaderg.com/tw/contact_us; https://zh.wikipedia.org/wiki/北港武德宮", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A camera-analytics system (AI門神) already watching the office over the temple's existing CCTV. It was set to alert on small amounts of smoke and to message a named chain of people (front desk, general manager, chairman) over LINE.", "A staffed night watch. The temple has kept someone on duty every night since it moved to the site in 1980 (民國69年). So the alert had a clerk a minute away with an extinguisher.", "A slow start to the fire. A tool charger and lithium batteries smoked before the batteries burst at 05:33, which gave the alert a minute's lead.", "A fire brigade eight minutes away and a reinforced-concrete annex that held the fire to one room, as the Third Brigade commander said." ], "must_hold": [ "The alert reaches a person who can act within minutes. At an unstaffed site the lead time is worth little.", "The camera covers the rooms where fires start (here an office and machine room with chargers, beside stored joss paper), not only the shrine.", "The AI alert complements conventional detectors rather than replacing them. A residential smoke alarm sounded here as well." ], "echoes": [ { "setting": "OECD AIM 2023-09-12-f6ac: ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna, human operators verify it and Cal Fire holds the fire (camera smoke detection with a human in the loop and a brigade response).", "outcome": "unknown" }, { "setting": "OECD AIM 2025-09-13-b5dc: Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner (Taiwanese camera smoke analytics in a different use).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A camera-analytics system (AI門神) already watching the office over the temple's existing CCTV. It was set to alert on small amounts of smoke and to message a named chain of people (front desk, general manager, chairman) over LINE.", "A staffed night watch. The temple has kept someone on duty every night since it moved to the site in 1980 (民國69年). So the alert had a clerk a minute away with an extinguisher.", "A slow start to the fire. A tool charger and lithium batteries smoked before the batteries burst at 05:33, which gave the alert a minute's lead.", "A fire brigade eight minutes away and a reinforced-concrete annex that held the fire to one room, as the Third Brigade commander said." ], "must_hold": [ "The alert reaches a person who can act within minutes. At an unstaffed site the lead time is worth little.", "The camera covers the rooms where fires start (here an office and machine room with chargers, beside stored joss paper), not only the shrine.", "The AI alert complements conventional detectors rather than replacing them. A residential smoke alarm sounded here as well." ], "echoes": [ { "setting": "OECD AIM 2023-09-12-f6ac: ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna, human operators verify it and Cal Fire holds the fire (camera smoke detection with a human in the loop and a brigade response).", "outcome": "unknown" }, { "setting": "OECD AIM 2025-09-13-b5dc: Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner (Taiwanese camera smoke analytics in a different use).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Cameras need to cover rooms where a fire could start. Alerts need to reach staff who can respond within minutes. Conventional smoke alarms remain necessary." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Filed as protective response with prevention unproven rather than the classifier's specific harm prevented: the protective action (a smoke alert at 05:30, a minute before the batteries burst, relayed over LINE to the front desk, general manager and chairman) is documented by the temple's own timeline as reported by TVBS, UDN, NOWnews, 觀傳媒 and CTS, and the outcome by the Yunlin County Fire Bureau's figures, but the counterfactual is not shown: UDN reports that a residential smoke alarm (住警器) sounded as well, a clerk was on night duty in any case, and the Third Brigade commander 陳岳謄 credited the RC structure and the crews' quick arrival without mentioning the AI. The Monitor's date of 4 February is the UTC date; every source puts the fire at about 05:30 on 5 February 2026 Taiwan time (21:30 UTC on 4 February), so the date observed is 5 February. Times differ between the temple's log (fire controlled 05:51) and the fire bureau (controlled 06:10, extinguished 06:14); the record uses the bureau's. The cause (a tool charger and lithium batteries) is the chairman's account; UDN's first report says the bureau was still investigating and the secretary general 蘇建華 told TVBS he suspected wiring. The vendor is named by the chairman as 立達軟體; its identity as LEADERG Inc. and the system's design (AI image recognition over existing CCTV on Advantech hardware, alerts by SMS, LINE or email, deployed at Wude Temple) come from Advantech's April 2025 case study, which is partner-authored and used only as an additional source. The Monitor lists China Times, which could not be read (Cloudflare challenge directly and through a text proxy; web.archive.org is blocked for this tool); its four yam.com links are syndications of 觀傳媒 (two), 台灣好報 and 創新聞. The CTS broadcast report of 5 February and CTS's December 2024 piece on the door-god system were found through Brave, as WebSearch was exhausted; DuckDuckGo and Mojeek returned nothing. The chairman's Facebook post was not read; it is quoted by UDN, NOWnews and NextApple. No Yunlin County Fire Bureau release was found on its own site; its statements are quoted by 觀傳媒, 台灣好報 and 創新聞, and CTS quotes the Beigang sub-station chief 陳思淵. The Monitor's country field is “Chinese Taipei”; the record says Taiwan, as every source does. Raw HTML of every source read is kept in src_4944.", "source": "https://oecd.ai/en/incidents/2026-02-04-4944", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://n.yam.com/Article/20260205197916; https://udn.com/news/story/7326/9714008", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.leaderg.com/tw/contact_us; https://zh.wikipedia.org/wiki/北港武德宮", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Fire safety (religious site)", "segment": "Temple and cultural-asset protection: AI video analytics on existing CCTV" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷. UDN, 5 February 2026.", "title": "「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷", "url": "https://udn.com/news/story/7320/9310088", "date": "2026-02-05", "written_by": "independent", "quote": "幸廟內設有AI警報系統及住警器，馬上發出警報聲響" }, { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場. UDN, 5 February 2026.", "title": "強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場", "url": "https://udn.com/news/story/7320/9310526", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢發生前一分鐘系統即已示警煙霧產生" }, { "kind": "news report", "citation": "吳淑萍 / TVBS新聞網 (2026). 北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟. TVBS, 5 February 2026.", "title": "北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟", "url": "https://news.tvbs.com.tw/local/3120819", "date": "2026-02-05", "written_by": "independent", "quote": "5點30分系統偵測到煙霧，5點32分人工察看確認狀況" }, { "kind": "news report", "citation": "蘇榮泉 / 觀傳媒 (2026). （有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "（有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控", "url": "https://n.yam.com/Article/20260205444546", "date": "2026-02-05", "written_by": "independent", "quote": "消防人員於6時10分成功控制火勢，並於6時14分完全撲滅" }, { "kind": "news report", "citation": "洪佳伶 / 觀傳媒 (2026). AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢", "url": "https://n.yam.com/Article/20260205197916", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢轉劇前一分鐘便偵測到煙霧，並依序通知櫃檯、總幹事" }, { "kind": "news report", "citation": "華視新聞 / CTS (2026). 「AI門神」立功！　武德宮火警偵測回報　快速控制火勢. CTS News, 5 February 2026.", "title": "「AI門神」立功！　武德宮火警偵測回報　快速控制火勢", "url": "https://news.cts.com.tw/cts/general/202602/202602052559104.html", "date": "2026-02-05", "written_by": "independent", "quote": "好險有AI門神，幫我們守護住，所以我們可以趕快第一時間" }, { "kind": "news report", "citation": "鄧庭婷 / NOWnews今日新聞 (2026). 北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸. NOWnews, 5 February 2026.", "title": "北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸", "url": "https://www.nownews.com/news/6783602", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火起前的關鍵一分鐘發出示警" }, { "kind": "news report", "citation": "莊曜聰 / 壹蘋新聞網 (2026). 北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」. NextApple, 5 February 2026.", "title": "北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」", "url": "https://news.nextapple.com/local/20260205/E631BE3355F1C46E511BAEBE0A5D0D61", "date": "2026-02-05", "written_by": "independent", "quote": "還有「門神系統」可以示警防災，這次果然派上用場" }, { "kind": "news report", "citation": "蘇峯毅 / 台灣好報 (2026). 清晨火警驚魂　北港武德宮即時搶救守住信仰中心. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "清晨火警驚魂　北港武德宮即時搶救守住信仰中心", "url": "https://n.yam.com/Article/20260205590605", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火勢形成前即已示警，加上長年夜間留守制度" }, { "kind": "news report", "citation": "華視新聞 / CTS (2024). AI進駐宮廟　統計人流.預防火災還能「解籤詩」. Syndicated on Yahoo奇摩新聞, 23 December 2024.", "title": "AI進駐宮廟　統計人流.預防火災還能「解籤詩」", "url": "https://tw.news.yahoo.com/ai%E9%80%B2%E9%A7%90%E5%AE%AE%E5%BB%9F-%E7%B5%B1%E8%A8%88%E4%BA%BA%E6%B5%81-%E9%A0%90%E9%98%B2%E7%81%AB%E7%81%BD%E9%82%84%E8%83%BD-%E8%A7%A3%E7%B1%A4%E8%A9%A9-121500289.html", "date": "2024-12-23", "written_by": "independent", "quote": "門神系統，只要偵測到煙霧異常，有火災的疑慮，會立刻發出警報" }, { "kind": "press release", "citation": "Advantech (2025). 立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護. Advantech case study, 15 April 2025.", "title": "立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護", "url": "https://www.advantech.com/en-us/resources/case-study/%E7%AB%8B%E9%81%94%E8%BB%9F%E9%AB%94%E6%94%9C%E6%89%8B%E7%A0%94%E8%8F%AFai%E9%96%80%E7%A5%9E%EF%BC%9A%E5%89%B5%E6%96%B0%E6%8A%80%E8%A1%93%E5%8A%A9%E5%8A%9B%E5%AF%BA%E5%BB%9F%E6%96%87%E5%8C%96%E8%B3%87%E7%94%A2%E4%BF%9D%E8%AD%B7", "date": "2025-04-15", "written_by": "makers", "quote": "偵測特定區域內是否有過量的煙霧、火焰及可疑行為" }, { "kind": "news report", "citation": "聯合新聞網 UDN (2026). 指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」. udn.com, 25 August 2026.", "title": "指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」", "url": "https://udn.com/news/story/7326/9714008", "date": "2026-08-25", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0155-source-0001", "AIBD-0155-source-0002", "AIBD-0155-source-0003", "AIBD-0155-source-0004", "AIBD-0155-source-0005", "AIBD-0155-source-0006", "AIBD-0155-source-0007", "AIBD-0155-source-0008", "AIBD-0155-source-0009", "AIBD-0155-source-0010", "AIBD-0155-source-0011", "AIBD-0155-source-0012" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷. UDN, 5 February 2026.", "title": "「財神祖廟」北港武德宮火警！AI警報響起快速撲滅…人員幸運無傷", "url": "https://udn.com/news/story/7320/9310088", "date": "2026-02-05", "written_by": "independent", "quote": "幸廟內設有AI警報系統及住警器，馬上發出警報聲響" }, { "kind": "news report", "citation": "蔡維斌 / 聯合新聞網 (2026). 強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場. UDN, 5 February 2026.", "title": "強大AI！人在日本的武德宮主委被AI警報嚇醒…跨海還原火警現場", "url": "https://udn.com/news/story/7320/9310526", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢發生前一分鐘系統即已示警煙霧產生" }, { "kind": "news report", "citation": "吳淑萍 / TVBS新聞網 (2026). 北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟. TVBS, 5 February 2026.", "title": "北港武德宮清晨竄火！鋰電池充電爆炸　「AI門神」示警救廟", "url": "https://news.tvbs.com.tw/local/3120819", "date": "2026-02-05", "written_by": "independent", "quote": "5點30分系統偵測到煙霧，5點32分人工察看確認狀況" }, { "kind": "news report", "citation": "蘇榮泉 / 觀傳媒 (2026). （有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "（有影片）／AI火警系統即時示警　北港武德宮火勢10分鐘內受控", "url": "https://n.yam.com/Article/20260205444546", "date": "2026-02-05", "written_by": "independent", "quote": "消防人員於6時10分成功控制火勢，並於6時14分完全撲滅" }, { "kind": "news report", "citation": "洪佳伶 / 觀傳媒 (2026). AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "AI門神立大功！北港武德宮幹部辦公室火警 主委跨海監控、10分鐘內控制火勢", "url": "https://n.yam.com/Article/20260205197916", "date": "2026-02-05", "written_by": "independent", "quote": "在火勢轉劇前一分鐘便偵測到煙霧，並依序通知櫃檯、總幹事" }, { "kind": "news report", "citation": "華視新聞 / CTS (2026). 「AI門神」立功！　武德宮火警偵測回報　快速控制火勢. CTS News, 5 February 2026.", "title": "「AI門神」立功！　武德宮火警偵測回報　快速控制火勢", "url": "https://news.cts.com.tw/cts/general/202602/202602052559104.html", "date": "2026-02-05", "written_by": "independent", "quote": "好險有AI門神，幫我們守護住，所以我們可以趕快第一時間" }, { "kind": "news report", "citation": "鄧庭婷 / NOWnews今日新聞 (2026). 北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸. NOWnews, 5 February 2026.", "title": "北港武德宮火警！「1科技」即時通報立大功　主委：不幸中的大幸", "url": "https://www.nownews.com/news/6783602", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火起前的關鍵一分鐘發出示警" }, { "kind": "news report", "citation": "莊曜聰 / 壹蘋新聞網 (2026). 北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」. NextApple, 5 February 2026.", "title": "北港武德宮火警損失輕微靠「兩功臣」　主委林安樂赴日收警報嘆「沒放假的命」", "url": "https://news.nextapple.com/local/20260205/E631BE3355F1C46E511BAEBE0A5D0D61", "date": "2026-02-05", "written_by": "independent", "quote": "還有「門神系統」可以示警防災，這次果然派上用場" }, { "kind": "news report", "citation": "蘇峯毅 / 台灣好報 (2026). 清晨火警驚魂　北港武德宮即時搶救守住信仰中心. Syndicated on yam 蕃新聞, 5 February 2026.", "title": "清晨火警驚魂　北港武德宮即時搶救守住信仰中心", "url": "https://n.yam.com/Article/20260205590605", "date": "2026-02-05", "written_by": "independent", "quote": "AI系統在火勢形成前即已示警，加上長年夜間留守制度" }, { "kind": "news report", "citation": "華視新聞 / CTS (2024). AI進駐宮廟　統計人流.預防火災還能「解籤詩」. Syndicated on Yahoo奇摩新聞, 23 December 2024.", "title": "AI進駐宮廟　統計人流.預防火災還能「解籤詩」", "url": "https://tw.news.yahoo.com/ai%E9%80%B2%E9%A7%90%E5%AE%AE%E5%BB%9F-%E7%B5%B1%E8%A8%88%E4%BA%BA%E6%B5%81-%E9%A0%90%E9%98%B2%E7%81%AB%E7%81%BD%E9%82%84%E8%83%BD-%E8%A7%A3%E7%B1%A4%E8%A9%A9-121500289.html", "date": "2024-12-23", "written_by": "independent", "quote": "門神系統，只要偵測到煙霧異常，有火災的疑慮，會立刻發出警報" }, { "kind": "press release", "citation": "Advantech (2025). 立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護. Advantech case study, 15 April 2025.", "title": "立達軟體攜手研華AI門神：創新技術助力寺廟文化資產保護", "url": "https://www.advantech.com/en-us/resources/case-study/%E7%AB%8B%E9%81%94%E8%BB%9F%E9%AB%94%E6%94%9C%E6%89%8B%E7%A0%94%E8%8F%AFai%E9%96%80%E7%A5%9E%EF%BC%9A%E5%89%B5%E6%96%B0%E6%8A%80%E8%A1%93%E5%8A%A9%E5%8A%9B%E5%AF%BA%E5%BB%9F%E6%96%87%E5%8C%96%E8%B3%87%E7%94%A2%E4%BF%9D%E8%AD%B7", "date": "2025-04-15", "written_by": "makers", "quote": "偵測特定區域內是否有過量的煙霧、火焰及可疑行為" }, { "kind": "news report", "citation": "聯合新聞網 UDN (2026). 指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」. udn.com, 25 August 2026.", "title": "指南宮大火啟示錄！雲林兩大廟分享防火經驗「要神也要人」", "url": "https://udn.com/news/story/7326/9714008", "date": "2026-08-25", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI camera analytics flagged smoke in an empty temple office a minute before a battery fire; held to 10 m², no injuries, main hall intact.", "account": "At about 05:30 on 5 February 2026 the AI門神 (AI door god) system flagged smoke in a first-floor office and machine room, empty after hours. The system is run by 立達軟體 (LEADERG Inc.) over the closed-circuit television (CCTV) of Beigang Wude Temple, Yunlin County, Taiwan. It messaged the front desk, the general manager and chairman 林安樂, in Japan, by LINE. The night-duty clerk reached the room with an extinguisher within a minute. At 05:33 overheated lithium batteries beside a tool charger burst and flames spread. Staff called 119 at 05:36. Yunlin County Fire Bureau crews arrived at 05:44, controlled it at 06:10 and put it out at 06:14. Ten square meters burned. Nobody was hurt. The main hall and statues were untouched." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software detected smoke in camera images and alerted temple staff." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The image-recognition software ran on an Advantech IPC-730 computer with a SKY-QUAD-5000A-32 accelerator card. Advantech reports processing about one frame every five seconds." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The software analyzed CCTV images and sent smoke alerts to temple staff through LINE." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not named. Advantech's case study says the image-recognition algorithms were developed with a large language model as the basis and run on an Advantech IPC-730 with a SKY-QUAD-5000A-32 accelerator card at about five seconds per frame." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI門神：宮廟AI防火防盜系統 (AI Door God: temple AI fire-and-theft prevention system), AI image recognition over the temple's existing CCTV with alerts by SMS, LINE and email" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "立達軟體科技股份有限公司 (LEADERG Inc.), Taiwan" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "LEADERG's “AI door god” camera analytics at Beigang Wude Temple flags smoke in an empty office a minute before charging lithium batteries burst; the night clerk and Yunlin firefighters hold the 5 February 2026 fire to ten square meters, nobody hurt, main hall untouched", "headline": "LEADERG's AI door god flags smoke; temple fire held to 10 m²" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d9e50b5220d086e0c9bd46b934073b730fafc534e423027f5f3acbdea2c79fa3" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "At about 05:30 on 5 February 2026 the AI門神 (AI door god) system flagged smoke in a first-floor office and machine room, empty after hours. The system is run by 立達軟體 (LEADERG Inc.) over the closed-circuit television (CCTV) of Beigang Wude Temple, Yunlin County, Taiwan. It messaged the front desk, the general manager and chairman 林安樂, in Japan, by LINE. The night-duty clerk reached the room with an extinguisher within a minute. At 05:33 overheated lithium batteries beside a tool charger burst and flames spread. Staff called 119 at 05:36. Yunlin County Fire Bureau crews arrived at 05:44, controlled it at 06:10 and put it out at 06:14. Ten square meters burned. Nobody was hurt. The main hall and statues were untouched.", "replication": { "produced_by": [ "A camera-analytics system (AI門神) already watching the office over the temple's existing CCTV. It was set to alert on small amounts of smoke and to message a named chain of people (front desk, general manager, chairman) over LINE.", "A staffed night watch. The temple has kept someone on duty every night since it moved to the site in 1980 (民國69年). So the alert had a clerk a minute away with an extinguisher.", "A slow start to the fire. A tool charger and lithium batteries smoked before the batteries burst at 05:33, which gave the alert a minute's lead.", "A fire brigade eight minutes away and a reinforced-concrete annex that held the fire to one room, as the Third Brigade commander said." ], "must_hold": [ "The alert reaches a person who can act within minutes. At an unstaffed site the lead time is worth little.", "The camera covers the rooms where fires start (here an office and machine room with chargers, beside stored joss paper), not only the shrine.", "The AI alert complements conventional detectors rather than replacing them. A residential smoke alarm sounded here as well." ], "echoes": [ { "setting": "OECD AIM 2023-09-12-f6ac: ALERTCalifornia's AI flags a 3 am smoke column near Mount Laguna, human operators verify it and Cal Fire holds the fire (camera smoke detection with a human in the loop and a brigade response).", "outcome": "unknown" }, { "setting": "OECD AIM 2025-09-13-b5dc: Taichung EPB's AI smoke-recognition system catches a serial roadside waste burner (Taiwanese camera smoke analytics in a different use).", "outcome": "unknown" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "AI門神 detected smoke through cameras that already covered the temple and alerted staff through LINE. The night clerk reached the room with an extinguisher. Firefighters arrived eight minutes later." } } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 0, "record_mapped": 36, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0274", "title": "Lunit INSIGHT CXR flags a subpulmonic effusion in an 87-year-old; ultrasound confirms, patient refuses transfer", "summary": "At a basic emergency service in the Algarve, the AI marked bilateral effusion (97% left, 77% right); screening ultrasound confirmed a right subpulmonic effusion; the patient refused transfer and left.", "date_observed": "2026-02-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Miravent et al. (Cureus, 7 February 2026) report an 87-year-old man with three days of dyspnea. He attended a basic emergency service of the Algarve Local Health Unit. Lunit INSIGHT CXR (Lunit Inc., Seoul) flagged bilateral pleural effusion on the chest radiograph. Its confidence was higher on the left (97%) than the right (77%), because the right-sided subpulmonic distribution mimicked hemidiaphragm elevation. Screening thoracic ultrasound by the radiographer confirmed a right subpulmonic effusion. The authors say this informed management and prevented misclassification as diaphragmatic elevation. He received nebulized bronchodilators. Despite advice and an indication for transfer to a referral hospital he refused, signed a discharge against medical advice and left. The authors declare no financial support.", "category": "benefit created", "unexpected": false, "purpose": "Flag abnormalities on chest radiographs at an emergency service without on-site radiology", "system": "Lunit INSIGHT CXR", "model_version": null, "developer": "Lunit Inc., Seoul", "deployer": "Basic Emergency Service, Vila Real de Santo Antonio Health Center, Algarve Local Health Unit", "location": "Vila Real de Santo Antonio, Algarve, Portugal", "domain": "Health; emergency radiology", "segment": "Emergency patients at peripheral services without on-site radiologists", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "Correct identification of a subtle subpulmonic effusion informed on-site management. But the patient refused transfer and left against advice." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported." }, { "group": "societal", "depth": null, "reason": "Single case." } ], "ai_role": { "status": "assessed", "statement": "The AI flagged the effusion correctly but with lower confidence on the subpulmonic side. Ultrasound confirmed it. The source is a non-vendor case report with no financial support declared. The outcome did not follow because the patient declined care." }, "evidence": [ { "kind": "case report", "citation": "Miravent S, Silva SM, Navarro MJ, Lobo MD, Pereira de Almeida R. Cureus 18(2):e103161 (2026)", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Screening thoracic ultrasound confirmed a right subpulmonic effusion." }, { "kind": "case report", "citation": "Miravent S, et al. Cureus (2026), case presentation", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Despite medical advice and the indication for transfer to a referral hospital for further investigation and potential admission, the patient refused." } ], "replication": { "produced_by": [ "AI chest-radiograph triage at a peripheral emergency service", "Radiographer-performed screening ultrasound to confirm" ], "must_hold": [ "Clinicians check lower-confidence AI flags with ultrasound", "Patients accept referral" ], "echoes": [] }, "paired_incident": null, "headline": "Lunit INSIGHT CXR spots subpulmonic effusion; ultrasound agrees", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The patient refused transfer and left against medical advice; the cited case report describes no follow-up and no comparison of the AI flag against a radiologist reading, since no over-read was obtained.", "quote": null, "url": null }, "value": null, "developer_country": "South Korea", "deployer_country": "Portugal", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Unidade_Local_de_Saúde_do_Algarve", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.lunit.io/en/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0274", "catalog_version": "1.0.0", "source_fingerprint": "163525e7ebda74d5f6153f3431a6dbcff028e59581765e12dc47c7a6a5d108ab", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0274-source-0001", "AIBD-0274-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Lunit Inc., Seoul", "deployer": "Basic Emergency Service, Vila Real de Santo Antonio Health Center, Algarve Local Health Unit" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI flagged the effusion correctly but with lower confidence on the subpulmonic side. Ultrasound confirmed it. The source is a non-vendor case report with no financial support declared. The outcome did not follow because the patient declined care." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI flagged the effusion correctly but with lower confidence on the subpulmonic side. Ultrasound confirmed it. The source is a non-vendor case report with no financial support declared. The outcome did not follow because the patient declined care." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Correct identification of a subtle subpulmonic effusion informed on-site management. But the patient refused transfer and left against advice." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Correct identification of a subtle subpulmonic effusion informed on-site management. But the patient refused transfer and left against advice." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Correct identification of a subtle subpulmonic effusion informed on-site management. But the patient refused transfer and left against advice." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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"Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Miravent et al. (Cureus, 7 February 2026) report an 87-year-old man with three days of dyspnea. He attended a basic emergency service of the Algarve Local Health Unit. Lunit INSIGHT CXR (Lunit Inc., Seoul) flagged bilateral pleural effusion on the chest radiograph. Its confidence was higher on the left (97%) than the right (77%), because the right-sided subpulmonic distribution mimicked hemidiaphragm elevation. Screening thoracic ultrasound by the radiographer confirmed a right subpulmonic effusion. The authors say this informed management and prevented misclassification as diaphragmatic elevation. He received nebulized bronchodilators. Despite advice and an indication for transfer to a referral hospital he refused, signed a discharge against medical advice and left. The authors declare no financial support.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 1, "reason": "Correct identification of a subtle subpulmonic effusion informed on-site management. But the patient refused transfer and left against advice." }, { "group": "organizational", "reason": "No organizational outcome reported." }, { "group": "societal", "reason": "Single case." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Flag abnormalities on chest radiographs at an emergency service without on-site radiology" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Vila Real de Santo Antonio, Algarve, Portugal", "developer_country": "South Korea", "deployer_country": "Portugal" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Flag abnormalities on chest radiographs at an emergency service without on-site radiology" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-02-07", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Unidade_Local_de_Saúde_do_Algarve", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.lunit.io/en/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "AI chest-radiograph triage at a peripheral emergency service", "Radiographer-performed screening ultrasound to confirm" ], "must_hold": [ "Clinicians check lower-confidence AI flags with ultrasound", "Patients accept referral" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://pt.wikipedia.org/wiki/Unidade_Local_de_Saúde_do_Algarve", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.lunit.io/en/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Health; emergency radiology", "segment": "Emergency patients at peripheral services without on-site radiologists" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Miravent S, Silva SM, Navarro MJ, Lobo MD, Pereira de Almeida R. Cureus 18(2):e103161 (2026)", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Screening thoracic ultrasound confirmed a right subpulmonic effusion." }, { "kind": "case report", "citation": "Miravent S, et al. Cureus (2026), case presentation", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Despite medical advice and the indication for transfer to a referral hospital for further investigation and potential admission, the patient refused." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0274-source-0001", "AIBD-0274-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Miravent S, Silva SM, Navarro MJ, Lobo MD, Pereira de Almeida R. Cureus 18(2):e103161 (2026)", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Screening thoracic ultrasound confirmed a right subpulmonic effusion." }, { "kind": "case report", "citation": "Miravent S, et al. Cureus (2026), case presentation", "title": "When the Diaphragm Deceives: Subpulmonic Effusion Flagged by AI and Confirmed by Ultrasound", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12970633/", "date": "2026-02-07", "written_by": "deployer", "quote": "Despite medical advice and the indication for transfer to a referral hospital for further investigation and potential admission, the patient refused." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At a basic emergency service in the Algarve, the AI marked bilateral effusion (97% left, 77% right); screening ultrasound confirmed a right subpulmonic effusion; the patient refused transfer and left.", "account": "Miravent et al. (Cureus, 7 February 2026) report an 87-year-old man with three days of dyspnea. He attended a basic emergency service of the Algarve Local Health Unit. Lunit INSIGHT CXR (Lunit Inc., Seoul) flagged bilateral pleural effusion on the chest radiograph. Its confidence was higher on the left (97%) than the right (77%), because the right-sided subpulmonic distribution mimicked hemidiaphragm elevation. Screening thoracic ultrasound by the radiographer confirmed a right subpulmonic effusion. The authors say this informed management and prevented misclassification as diaphragmatic elevation. He received nebulized bronchodilators. Despite advice and an indication for transfer to a referral hospital he refused, signed a discharge against medical advice and left. The authors declare no financial support." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Lunit INSIGHT CXR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Lunit Inc., Seoul" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lunit INSIGHT CXR flags a subpulmonic effusion in an 87-year-old; ultrasound confirms, patient refuses transfer", "headline": "Lunit INSIGHT CXR spots subpulmonic effusion; ultrasound agrees" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "163525e7ebda74d5f6153f3431a6dbcff028e59581765e12dc47c7a6a5d108ab" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Miravent et al. (Cureus, 7 February 2026) report an 87-year-old man with three days of dyspnea. He attended a basic emergency service of the Algarve Local Health Unit. Lunit INSIGHT CXR (Lunit Inc., Seoul) flagged bilateral pleural effusion on the chest radiograph. Its confidence was higher on the left (97%) than the right (77%), because the right-sided subpulmonic distribution mimicked hemidiaphragm elevation. Screening thoracic ultrasound by the radiographer confirmed a right subpulmonic effusion. The authors say this informed management and prevented misclassification as diaphragmatic elevation. He received nebulized bronchodilators. Despite advice and an indication for transfer to a referral hospital he refused, signed a discharge against medical advice and left. The authors declare no financial support.", "replication": { "produced_by": [ "AI chest-radiograph triage at a peripheral emergency service", "Radiographer-performed screening ultrasound to confirm" ], "must_hold": [ "Clinicians check lower-confidence AI flags with ultrasound", "Patients accept referral" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0160", "title": "Istanbul police's AVCI messaging-analysis system used for the first time in a 10 February 2026 drug operation across 14 provinces: 325 suspects detained and remanded, 69 dealer groups closed", "summary": "Istanbul police's AI-based AVCI system, first used 10 February 2026 in a 14-province drug operation: 325 detained and remanded, 69 groups closed.", "date_observed": "2026-02-10", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi, Open Source Intelligence Analysis System) is an AI-supported program. The Istanbul Police Department's narcotics and cybercrime divisions built it in-house with a special software team. Police chief Selami Yıldız ordered the work. It infiltrates closed groups and channels on end-to-end encrypted messaging apps. It analyzes messages, voice notes, photos and location data. It decodes dealer slang, recovers deleted messages, links fake profiles and maps group hierarchies. Anadolu Agency reported on 6 April 2026 that AVCI was first used on 10 February 2026. The drug operation was centered on Istanbul and ran across 14 provinces. 325 suspects were detained. All 325 referred to court were remanded in custody. 69 messaging-app groups were closed.", "category": "benefit created", "unexpected": false, "purpose": "Istanbul police built AVCI to infiltrate and analyze encrypted messaging groups used for drug dealing. It also identifies suspects, fake profiles and network hierarchies. The 10 February operation was that intended use.", "system": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi): AI-supported open-source intelligence analysis software that infiltrates closed groups on encrypted messaging apps and analyzes messages, media and location data with natural language processing", "model_version": null, "developer": "Istanbul Police Department (İstanbul Emniyet Müdürlüğü), narcotics and cybercrime divisions with an in-house software team", "deployer": "Istanbul Police Department, Anti-Narcotics and Cybercrime divisions", "location": "Istanbul, Turkey", "domain": "Law enforcement / narcotics investigation", "segment": "Provincial police force", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-04-06-4878" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "In one operation the force detained 325 suspects across 14 provinces and closed 69 dealer groups. All 325 were remanded. The sources give no comparison with operations before AVCI, so the gain to the force is not measured." }, { "group": "societal", "depth": 2, "reason": "The police say the operation disrupted drug sales networks run through encrypted groups and social media across 14 provinces. No source measures any effect on drug supply or on the public. A population-level benefit is not established." } ], "ai_role": { "status": "assessed", "statement": "By the police account relayed by Anadolu Agency, AVCI infiltrated closed messaging groups and decoded slang and coded language. It recovered deleted messages, linked fake profiles through IP analysis and mapped group hierarchies. That work produced the suspects and groups targeted on 10 February. Police and courts carried out the detentions, referrals and remands. The sources include no independent evaluation of the system. No official is quoted on how many of the 325 were identified by AVCI rather than by conventional work. The sources name no developer beyond the police's own software team." }, "evidence": [ { "kind": "news report", "citation": "Anadolu Ajansı (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. aa.com.tr, 6 April 2026.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439", "date": "2026-04-06", "written_by": "independent", "quote": "AVCI ilk kez, İstanbul Narkotik Suçlarla Mücadele ve Siber Suçlarla Mücadele Şube müdürlükleri ekiplerince 10 Şubat'ta kent merkezli 14 ilde düzenlenen uyuşturucu operasyonunda kullanıldı." }, { "kind": "news report", "citation": "Haberler.com (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. haberler.com, 6 April 2026, crediting Anadolu Ajansı.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.haberler.com/guncel/istanbul-emniyeti-yapay-zeka-destekli-avci-yla-19720800-haberi/", "date": "2026-04-06", "written_by": "independent", "quote": "adliyeye sevk edilen 325 zanlının tamamı sevk edildikleri adli makamlarca tutuklanmıştı." }, { "kind": "news report", "citation": "Akşam (2026). Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor. aksam.com.tr, 6 April 2026, crediting Anadolu Ajansı.", "title": "Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor", "url": "https://www.aksam.com.tr/guncel/zehir-tacirleriyle-mucadelede-yeni-donem-avci-goz-actirmiyor/haber-1656417", "date": "2026-04-06", "written_by": "independent", "quote": "Yapay zeka destekli projenin ilk kez kullanıldığı operasyonda 325 şüpheli gözaltına alınmış" }, { "kind": "news report", "citation": "Hürriyet (2026). AVCI uyuşturucunun 'siber' inlerinde. hurriyet.com.tr, 7 April 2026, Anadolu Ajansı byline.", "title": "AVCI uyuşturucunun 'siber' inlerinde", "url": "https://www.hurriyet.com.tr/gundem/avci-uyusturucunun-siber-inlerinde-43145237", "date": "2026-04-07", "written_by": "independent", "quote": "İstanbul Emniyet Müdürlüğü tarafından hazırlanan yapay zekâ destekli Açık Kaynak İstihbaratı Analiz Sistemi (AVCI), uçtan uca şifreli iletişim uygulamalarının kapalı grup ve kanallarına sızarak, uyuşturucu tacirlerine göz açtırmıyor." }, { "kind": "news report", "citation": "Gökmen, E. (2026). İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı. Anadolu Agency, 17 July 2026.", "title": "İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı", "url": "https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "date": "2026-07-17", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "In-house police software that infiltrates closed groups on encrypted messaging apps and analyzes messages, media and location data with natural language processing", "A coordinated same-day operation across 14 provinces in which the identified suspects were detained and referred to court" ], "must_hold": [ "Police have access to the closed groups and to the server-side data the sources say the system uses to recover deleted messages and link profiles", "Courts remand the suspects. The sources report all 325 remanded, but no later charging or conviction outcomes", "The attribution of the suspects to AVCI, rather than to conventional investigation, is the police's own. No independent evaluation exists" ], "echoes": [] }, "paired_incident": null, "headline": "Istanbul police's AVCI detains 325 and closes 69 dealer groups", "metric": "325 detained and remanded, 69 groups closed", "comparator": { "against": "manual analysis of messaging data by police staff", "before": "insan gücüyle aylar sürecek bir analiz", "after": "saniyeler içine sığdırılarak", "basis": "assumed", "quote": "Programla suç gerçekleşmeden önce istihbarat odaklı yapılan çalışmayla insan gücüyle aylar sürecek bir analiz saniyeler içine sığdırılarak, uyuşturucu baronlarının dijital maskeleri düşürülüyor.", "url": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439" }, "later": { "status": "persisted", "date": "2026-07-17", "note": "AVCI was used again in an Istanbul-based operation across 35 provinces in which 110 suspects were detained and 65 Telegram groups and channels were closed.", "quote": "İstanbul merkezli 35 ilde uyuşturucu satıcılarına yönelik düzenlenen ve 110 zanlının yakalandığı operasyonda, yapay zeka destekli Açık Kaynak İstihbaratı Analiz Sistemi (AVCI) kullanıldı.", "url": "https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945" }, "value": null, "developer_country": "Turkey", "deployer_country": "Turkey", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-06-4878", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439; https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü; https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0160", "catalog_version": "1.0.0", "source_fingerprint": "10a892784ce22659e8b0daf253441c77114008e569616d29537281bd52d9d8c1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0160-source-0001", "AIBD-0160-source-0002", "AIBD-0160-source-0003", "AIBD-0160-source-0004", "AIBD-0160-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Istanbul Police Department (İstanbul Emniyet Müdürlüğü), narcotics and cybercrime divisions with an in-house software team", "deployer": "Istanbul Police Department, Anti-Narcotics and Cybercrime divisions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "By the police account relayed by Anadolu Agency, AVCI infiltrated closed messaging groups and decoded slang and coded language. It recovered deleted messages, linked fake profiles through IP analysis and mapped group hierarchies. That work produced the suspects and groups targeted on 10 February. Police and courts carried out the detentions, referrals and remands. The sources include no independent evaluation of the system. No official is quoted on how many of the 325 were identified by AVCI rather than by conventional work. The sources name no developer beyond the police's own software team." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "By the police account relayed by Anadolu Agency, AVCI infiltrated closed messaging groups and decoded slang and coded language. It recovered deleted messages, linked fake profiles through IP analysis and mapped group hierarchies. That work produced the suspects and groups targeted on 10 February. Police and courts carried out the detentions, referrals and remands. The sources include no independent evaluation of the system. No official is quoted on how many of the 325 were identified by AVCI rather than by conventional work. The sources name no developer beyond the police's own software team." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "In one operation the force detained 325 suspects across 14 provinces and closed 69 dealer groups. All 325 were remanded. The sources give no comparison with operations before AVCI, so the gain to the force is not measured." }, { "group": "societal", "depth": 2, "reason": "The police say the operation disrupted drug sales networks run through encrypted groups and social media across 14 provinces. No source measures any effect on drug supply or on the public. A population-level benefit is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "In one operation the force detained 325 suspects across 14 provinces and closed 69 dealer groups. All 325 were remanded. The sources give no comparison with operations before AVCI, so the gain to the force is not measured." }, { "group": "societal", "depth": 2, "reason": "The police say the operation disrupted drug sales networks run through encrypted groups and social media across 14 provinces. No source measures any effect on drug supply or on the public. A population-level benefit is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "In one operation the force detained 325 suspects across 14 provinces and closed 69 dealer groups. All 325 were remanded. The sources give no comparison with operations before AVCI, so the gain to the force is not measured." }, { "group": "societal", "depth": 2, "reason": "The police say the operation disrupted drug sales networks run through encrypted groups and social media across 14 provinces. No source measures any effect on drug supply or on the public. A population-level benefit is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "325 detained and remanded, 69 groups closed", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-04-06-4878" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-07-17", "note": "AVCI was used again in an Istanbul-based operation across 35 provinces in which 110 suspects were detained and 65 Telegram groups and channels were closed.", "quote": "İstanbul merkezli 35 ilde uyuşturucu satıcılarına yönelik düzenlenen ve 110 zanlının yakalandığı operasyonda, yapay zeka destekli Açık Kaynak İstihbaratı Analiz Sistemi (AVCI) kullanıldı.", "url": "https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0160" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi, Open Source Intelligence Analysis System) is an AI-supported program. The Istanbul Police Department's narcotics and cybercrime divisions built it in-house with a special software team. Police chief Selami Yıldız ordered the work. It infiltrates closed groups and channels on end-to-end encrypted messaging apps. It analyzes messages, voice notes, photos and location data. It decodes dealer slang, recovers deleted messages, links fake profiles and maps group hierarchies. Anadolu Agency reported on 6 April 2026 that AVCI was first used on 10 February 2026. The drug operation was centered on Istanbul and ran across 14 provinces. 325 suspects were detained. All 325 referred to court were remanded in custody. 69 messaging-app groups were closed.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "In one operation the force detained 325 suspects across 14 provinces and closed 69 dealer groups. All 325 were remanded. The sources give no comparison with operations before AVCI, so the gain to the force is not measured." }, { "group": "societal", "depth": 2, "reason": "The police say the operation disrupted drug sales networks run through encrypted groups and social media across 14 provinces. No source measures any effect on drug supply or on the public. A population-level benefit is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Istanbul police built AVCI to infiltrate and analyze encrypted messaging groups used for drug dealing. It also identifies suspects, fake profiles and network hierarchies. The 10 February operation was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Istanbul, Turkey", "developer_country": "Turkey", "deployer_country": "Turkey" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Istanbul police built AVCI to infiltrate and analyze encrypted messaging groups used for drug dealing. It also identifies suspects, fake profiles and network hierarchies. The 10 February operation was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-02-10", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-06-4878", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439; https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü; https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "In-house police software that infiltrates closed groups on encrypted messaging apps and analyzes messages, media and location data with natural language processing", "A coordinated same-day operation across 14 provinces in which the identified suspects were detained and referred to court" ], "must_hold": [ "Police have access to the closed groups and to the server-side data the sources say the system uses to recover deleted messages and link profiles", "Courts remand the suspects. The sources report all 325 remanded, but no later charging or conviction outcomes", "The attribution of the suspects to AVCI, rather than to conventional investigation, is the police's own. No independent evaluation exists" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-06-4878", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439; https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü; https://tr.wikipedia.org/wiki/İstanbul_Emniyet_Müdürlüğü", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Law enforcement / narcotics investigation", "segment": "Provincial police force" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Anadolu Ajansı (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. aa.com.tr, 6 April 2026.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439", "date": "2026-04-06", "written_by": "independent", "quote": "AVCI ilk kez, İstanbul Narkotik Suçlarla Mücadele ve Siber Suçlarla Mücadele Şube müdürlükleri ekiplerince 10 Şubat'ta kent merkezli 14 ilde düzenlenen uyuşturucu operasyonunda kullanıldı." }, { "kind": "news report", "citation": "Haberler.com (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. haberler.com, 6 April 2026, crediting Anadolu Ajansı.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.haberler.com/guncel/istanbul-emniyeti-yapay-zeka-destekli-avci-yla-19720800-haberi/", "date": "2026-04-06", "written_by": "independent", "quote": "adliyeye sevk edilen 325 zanlının tamamı sevk edildikleri adli makamlarca tutuklanmıştı." }, { "kind": "news report", "citation": "Akşam (2026). Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor. aksam.com.tr, 6 April 2026, crediting Anadolu Ajansı.", "title": "Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor", "url": "https://www.aksam.com.tr/guncel/zehir-tacirleriyle-mucadelede-yeni-donem-avci-goz-actirmiyor/haber-1656417", "date": "2026-04-06", "written_by": "independent", "quote": "Yapay zeka destekli projenin ilk kez kullanıldığı operasyonda 325 şüpheli gözaltına alınmış" }, { "kind": "news report", "citation": "Hürriyet (2026). AVCI uyuşturucunun 'siber' inlerinde. hurriyet.com.tr, 7 April 2026, Anadolu Ajansı byline.", "title": "AVCI uyuşturucunun 'siber' inlerinde", "url": "https://www.hurriyet.com.tr/gundem/avci-uyusturucunun-siber-inlerinde-43145237", "date": "2026-04-07", "written_by": "independent", "quote": "İstanbul Emniyet Müdürlüğü tarafından hazırlanan yapay zekâ destekli Açık Kaynak İstihbaratı Analiz Sistemi (AVCI), uçtan uca şifreli iletişim uygulamalarının kapalı grup ve kanallarına sızarak, uyuşturucu tacirlerine göz açtırmıyor." }, { "kind": "news report", "citation": "Gökmen, E. (2026). İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı. Anadolu Agency, 17 July 2026.", "title": "İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı", "url": "https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "date": "2026-07-17", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0160-source-0001", "AIBD-0160-source-0002", "AIBD-0160-source-0003", "AIBD-0160-source-0004", "AIBD-0160-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Anadolu Ajansı (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. aa.com.tr, 6 April 2026.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.aa.com.tr/tr/gundem/istanbul-emniyeti-yapay-zeka-destekli-avciyla-uyusturucu-saticilarinin-siber-inlerine-giriyor/3894439", "date": "2026-04-06", "written_by": "independent", "quote": "AVCI ilk kez, İstanbul Narkotik Suçlarla Mücadele ve Siber Suçlarla Mücadele Şube müdürlükleri ekiplerince 10 Şubat'ta kent merkezli 14 ilde düzenlenen uyuşturucu operasyonunda kullanıldı." }, { "kind": "news report", "citation": "Haberler.com (2026). İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor. haberler.com, 6 April 2026, crediting Anadolu Ajansı.", "title": "İstanbul Emniyeti yapay zeka destekli AVCI'yla uyuşturucu satıcılarının 'siber' inlerine giriyor", "url": "https://www.haberler.com/guncel/istanbul-emniyeti-yapay-zeka-destekli-avci-yla-19720800-haberi/", "date": "2026-04-06", "written_by": "independent", "quote": "adliyeye sevk edilen 325 zanlının tamamı sevk edildikleri adli makamlarca tutuklanmıştı." }, { "kind": "news report", "citation": "Akşam (2026). Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor. aksam.com.tr, 6 April 2026, crediting Anadolu Ajansı.", "title": "Zehir tacirleriyle mücadelede yeni dönem: AVCI göz açtırmıyor", "url": "https://www.aksam.com.tr/guncel/zehir-tacirleriyle-mucadelede-yeni-donem-avci-goz-actirmiyor/haber-1656417", "date": "2026-04-06", "written_by": "independent", "quote": "Yapay zeka destekli projenin ilk kez kullanıldığı operasyonda 325 şüpheli gözaltına alınmış" }, { "kind": "news report", "citation": "Hürriyet (2026). AVCI uyuşturucunun 'siber' inlerinde. hurriyet.com.tr, 7 April 2026, Anadolu Ajansı byline.", "title": "AVCI uyuşturucunun 'siber' inlerinde", "url": "https://www.hurriyet.com.tr/gundem/avci-uyusturucunun-siber-inlerinde-43145237", "date": "2026-04-07", "written_by": "independent", "quote": "İstanbul Emniyet Müdürlüğü tarafından hazırlanan yapay zekâ destekli Açık Kaynak İstihbaratı Analiz Sistemi (AVCI), uçtan uca şifreli iletişim uygulamalarının kapalı grup ve kanallarına sızarak, uyuşturucu tacirlerine göz açtırmıyor." }, { "kind": "news report", "citation": "Gökmen, E. (2026). İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı. Anadolu Agency, 17 July 2026.", "title": "İstanbul'da uyuşturucu satıcılarına yönelik operasyonda yapay zeka \"AVCI\" aktif rol aldı", "url": "https://www.aa.com.tr/tr/gundem/istanbulda-uyusturucu-saticilarina-yonelik-operasyonda-yapay-zeka-avci-aktif-rol-aldi/4000945", "date": "2026-07-17", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Istanbul police's AI-based AVCI system, first used 10 February 2026 in a 14-province drug operation: 325 detained and remanded, 69 groups closed.", "account": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi, Open Source Intelligence Analysis System) is an AI-supported program. The Istanbul Police Department's narcotics and cybercrime divisions built it in-house with a special software team. Police chief Selami Yıldız ordered the work. It infiltrates closed groups and channels on end-to-end encrypted messaging apps. It analyzes messages, voice notes, photos and location data. It decodes dealer slang, recovers deleted messages, links fake profiles and maps group hierarchies. Anadolu Agency reported on 6 April 2026 that AVCI was first used on 10 February 2026. The drug operation was centered on Istanbul and ran across 14 provinces. 325 suspects were detained. All 325 referred to court were remanded in custody. 69 messaging-app groups were closed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi): AI-supported open-source intelligence analysis software that infiltrates closed groups on encrypted messaging apps and analyzes messages, media and location data with natural language processing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Istanbul Police Department (İstanbul Emniyet Müdürlüğü), narcotics and cybercrime divisions with an in-house software team" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Istanbul police's AVCI messaging-analysis system used for the first time in a 10 February 2026 drug operation across 14 provinces: 325 suspects detained and remanded, 69 dealer groups closed", "headline": "Istanbul police's AVCI detains 325 and closes 69 dealer groups" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "10a892784ce22659e8b0daf253441c77114008e569616d29537281bd52d9d8c1" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "AVCI (Açık Kaynak İstihbaratı Analiz Sistemi, Open Source Intelligence Analysis System) is an AI-supported program. The Istanbul Police Department's narcotics and cybercrime divisions built it in-house with a special software team. Police chief Selami Yıldız ordered the work. It infiltrates closed groups and channels on end-to-end encrypted messaging apps. It analyzes messages, voice notes, photos and location data. It decodes dealer slang, recovers deleted messages, links fake profiles and maps group hierarchies. Anadolu Agency reported on 6 April 2026 that AVCI was first used on 10 February 2026. The drug operation was centered on Istanbul and ran across 14 provinces. 325 suspects were detained. All 325 referred to court were remanded in custody. 69 messaging-app groups were closed.", "replication": { "produced_by": [ "In-house police software that infiltrates closed groups on encrypted messaging apps and analyzes messages, media and location data with natural language processing", "A coordinated same-day operation across 14 provinces in which the identified suspects were detained and referred to court" ], "must_hold": [ "Police have access to the closed groups and to the server-side data the sources say the system uses to recover deleted messages and link profiles", "Courts remand the suspects. The sources report all 325 remanded, but no later charging or conviction outcomes", "The attribution of the suspects to AVCI, rather than to conventional investigation, is the police's own. No independent evaluation exists" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0249", "title": "Korea's transport ministry announces AI CCTV to alert train drivers to vehicles or pedestrians trapped at crossings, piloting in Nonsan and Boseong before 543 national crossings", "summary": "Kyunghyang Shinmun (11 Feb 2026): MOLIT's crossing-accident plan from March 2026 includes AI intelligent CCTV piloted in Q1 at two crossings where 2025 accidents occurred; 36 crossing accidents in ...", "date_observed": "2026-02-11", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Kyunghyang Shinmun's 최미랑 reported on 11 Feb 2026 that the Ministry of Land, Infrastructure and Transport had drawn up a comprehensive railway-crossing accident-prevention plan. It was to take effect from March 2026. It includes an AI-based intelligent closed-circuit television (CCTV) system, to be installed in railway protection zones nationwide. The system immediately detects a vehicle or pedestrian trapped inside a crossing. It then transmits the information to the driver of an approaching train. Pilot installations were planned within the first quarter at Nonsan in Chungnam and at Boseong, where accidents occurred in 2025. Installation at the 543 national crossings would follow in sequence, depending on the results. The plan also adds fines of up to 70,000 won, after a six-month grace period. They apply to vehicles that fail to stop or that enter while barriers operate. The ministry cited 36 crossing accidents over five years with 14 deaths and 7 injuries, 27 of them due to driver carelessness. No developer is named and no results exist. The OECD AI Incidents Monitor classified the announcement as an AI hazard rather than an incident.", "category": "general benefit", "unexpected": false, "purpose": "The AI CCTV is intended to detect vehicles or pedestrians trapped in crossings and warn approaching train drivers in time to stop.", "system": "AI-based intelligent CCTV for railway crossings (supplier not named)", "model_version": null, "developer": "Not named", "deployer": "Ministry of Land, Infrastructure and Transport (South Korea), planned", "location": null, "domain": "Railway safety", "segment": "Level-crossing obstacle detection", "benefit_type": "Increased Product Safety", "taxonomy_note": "Pilot announcement only; the type names the crossing-accident prevention aimed at.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No outcome is documented." }, { "group": "organizational", "depth": null, "reason": "No outcome is documented." }, { "group": "personal", "depth": null, "reason": "No outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "Planned system; the sources describe the intended function and rollout sequence only." }, "evidence": [ { "kind": "news report", "citation": "최미랑 (11 Feb 2026). 철도건널목에 차량 갇히면 기관사에게 정보 전송···인공지능 CCTV 도입. 경향신문.", "title": "철도건널목에 차량 갇히면 기관사에게 정보 전송···인공지능 CCTV 도입", "url": "https://www.khan.co.kr/article/202602111540011", "date": "2026-02-11", "written_by": "independent", "quote": "국토부에 따르면 최근 5년간 철도건널목에서 발생한 36건의 사고로 14명이 숨지고 7명이 다쳤다." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-02-11-4404: South Korea Deploys AI CCTV to Prevent Railway Crossing Accidents (labelled AI hazard).", "title": "South Korea Deploys AI CCTV to Prevent Railway Crossing Accidents", "url": "https://oecd.ai/en/incidents/2026-02-11-4404", "date": "2026-02-11", "written_by": "independent", "quote": "This initiative aims to reduce frequent accidents caused by driver negligence, with nationwide rollout planned after pilot installations." } ], "replication": { "produced_by": [ "A national accident-prevention plan following fatal crossing accidents", "Pilot sites chosen where accidents occurred the previous year" ], "must_hold": [ "Pilot results support rollout", "Alerts reach drivers early enough to stop" ], "echoes": [ { "date": "2026-06-24", "setting": "Odakyu's AI crossing image analysis linked to train braking in Japan (ITmedia)", "model_version": null, "outcome": "recurred", "source": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html" } ] }, "paired_incident": null, "headline": "AI crossing cameras to alert train drivers at Nonsan and Boseong", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The sources report the announcement of 11 February 2026. No subsequent installation or results from the Nonsan or Boseong pilots are established.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "South Korea", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Ministry_of_Land,_Infrastructure_and_Transport_(South_Korea)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and a registry entry. 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It was to take effect from March 2026. It includes an AI-based intelligent closed-circuit television (CCTV) system, to be installed in railway protection zones nationwide. The system immediately detects a vehicle or pedestrian trapped inside a crossing. It then transmits the information to the driver of an approaching train. Pilot installations were planned within the first quarter at Nonsan in Chungnam and at Boseong, where accidents occurred in 2025. Installation at the 543 national crossings would follow in sequence, depending on the results. The plan also adds fines of up to 70,000 won, after a six-month grace period. They apply to vehicles that fail to stop or that enter while barriers operate. The ministry cited 36 crossing accidents over five years with 14 deaths and 7 injuries, 27 of them due to driver carelessness. No developer is named and no results exist. The OECD AI Incidents Monitor classified the announcement as an AI hazard rather than an incident.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No outcome is documented." }, { "group": "organizational", "reason": "No outcome is documented." }, { "group": "personal", "reason": "No outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A national accident-prevention plan following fatal crossing accidents", "Pilot sites chosen where accidents occurred the previous year" ], "must_hold": [ "Pilot results support rollout", "Alerts reach drivers early enough to stop" ], "echoes": [ { "date": "2026-06-24", "setting": "Odakyu's AI crossing image analysis linked to train braking in Japan (ITmedia)", "outcome": "recurred", "source": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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It was to take effect from March 2026. It includes an AI-based intelligent closed-circuit television (CCTV) system, to be installed in railway protection zones nationwide. The system immediately detects a vehicle or pedestrian trapped inside a crossing. It then transmits the information to the driver of an approaching train. Pilot installations were planned within the first quarter at Nonsan in Chungnam and at Boseong, where accidents occurred in 2025. Installation at the 543 national crossings would follow in sequence, depending on the results. The plan also adds fines of up to 70,000 won, after a six-month grace period. They apply to vehicles that fail to stop or that enter while barriers operate. The ministry cited 36 crossing accidents over five years with 14 deaths and 7 injuries, 27 of them due to driver carelessness. No developer is named and no results exist. The OECD AI Incidents Monitor classified the announcement as an AI hazard rather than an incident." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI-based intelligent CCTV for railway crossings (supplier not named)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Korea's transport ministry announces AI CCTV to alert train drivers to vehicles or pedestrians trapped at crossings, piloting in Nonsan and Boseong before 543 national crossings", "headline": "AI crossing cameras to alert train drivers at Nonsan and Boseong" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3fdbb43dd8967548064bb14a8359a4b0a4bc13dae589dd9ae57a508914e866a9" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Kyunghyang Shinmun's 최미랑 reported on 11 Feb 2026 that the Ministry of Land, Infrastructure and Transport had drawn up a comprehensive railway-crossing accident-prevention plan. It was to take effect from March 2026. It includes an AI-based intelligent closed-circuit television (CCTV) system, to be installed in railway protection zones nationwide. The system immediately detects a vehicle or pedestrian trapped inside a crossing. It then transmits the information to the driver of an approaching train. Pilot installations were planned within the first quarter at Nonsan in Chungnam and at Boseong, where accidents occurred in 2025. Installation at the 543 national crossings would follow in sequence, depending on the results. The plan also adds fines of up to 70,000 won, after a six-month grace period. They apply to vehicles that fail to stop or that enter while barriers operate. The ministry cited 36 crossing accidents over five years with 14 deaths and 7 injuries, 27 of them due to driver carelessness. No developer is named and no results exist. 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The provincial council had begun them on the CV-600 road, in the area of Simat de la Valldigna and Benifairó de la Valldigna. The intelligent signaling system is designed to detect wild boar near the carriageway and automatically activate luminous warning signs. The Valencian road-safety company Metalesa carried out the work, with civil works by Grupo Bertolín. The system combines cameras with computer vision and automatic detection algorithms that identify animals passing. It activates dynamic luminous signs only when a real risk exists, and it is powered by photovoltaic energy. Council president Vicent Mompó visited the site with roads deputy Reme Mazzolari. He said that after some weeks the council would evaluate the results. If the system is effective, the council would extend the model to the most sensitive stretches of the provincial network. No detection counts or accident figures are given. The OECD AI Incidents Monitor lists the pilot as an aggregate benefit.", "category": "general benefit", "unexpected": false, "purpose": "The system is built to detect wild boar near the road and warn drivers only when animals are present.", "system": "Metalesa camera and computer-vision wild-boar detection with dynamic luminous warning signs (solar-powered)", "model_version": null, "developer": "Metalesa (civil works by Grupo Bertolín)", "deployer": "Diputació de València", "location": "Simat de la Valldigna, Spain", "domain": "Road safety / wildlife-vehicle collision prevention", "segment": "Wildlife-vehicle collision prevention", "benefit_type": "Increased Product Safety", "taxonomy_note": "A driver-warning pilot with no data; the type names the collision-avoidance feature.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No detection, speed or collision outcome is documented." }, { "group": "organizational", "depth": null, "reason": "Evaluation was to follow after some weeks; none is reported." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The detection algorithms trigger the signs; no accuracy, trigger counts or driver-behavior data are reported." }, "evidence": [ { "kind": "news report", "citation": "Europa Press (12 Feb 2026). Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas.", "title": "Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas", "url": "https://web.archive.org/web/2026/https://www.europapress.es/comunitat-valenciana/noticia-diputacio-valencia-ensaya-sistema-inteligente-detecta-jabalies-activa-senales-luminosas-20260212143809.html", "date": "2026-02-12", "written_by": "independent", "quote": "La Diputació de València ha iniciado en la carretera CV-600 las pruebas piloto de un sistema de señalización inteligente diseñado para detectar la presencia de jabalíes" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-02-12-aa5d: AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents.", "title": "AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents", "url": "https://oecd.ai/en/incidents/2026-02-12-aa5d", "date": "2026-02-12", "written_by": "independent", "quote": "Using cameras and detection algorithms, the system identifies wild boars and automatically alerts drivers with illuminated signals" } ], "replication": { "produced_by": [ "A road stretch with frequent wildlife crossings", "Camera detection tied to dynamic signs powered by solar panels", "A road authority committed to evaluating before extending" ], "must_hold": [ "Detection works at night when boar move", "Drivers slow in response to the lights" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured (reported results)", "model_version": null, "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] }, "paired_incident": null, "headline": "Metalesa AI pilot lights wild-boar warning signs on the CV-600", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The February 2026 coverage in COPE and El Debate describes the launch. No evaluation result or extension of the CV-600 pilot is established.", "quote": null, "url": null }, "value": null, "developer_country": "Spain", "deployer_country": "Spain", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.metalesa.com/; https://es.wikipedia.org/wiki/Diputación_Provincial_de_Valencia", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0256", "catalog_version": "1.0.0", "source_fingerprint": "661dae141deadffbc52fa016833f7611b9801fdcf1f47c37aa971dc2eb8358ef", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0256-source-0001", "AIBD-0256-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Metalesa (civil works by Grupo Bertolín)", "deployer": "Diputació de València" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The detection algorithms trigger the signs; no accuracy, trigger counts or driver-behavior data are reported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No detection, speed or collision outcome is documented." }, { "group": "organizational", "reason": "Evaluation was to follow after some weeks; none is reported." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", 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The provincial council had begun them on the CV-600 road, in the area of Simat de la Valldigna and Benifairó de la Valldigna. The intelligent signaling system is designed to detect wild boar near the carriageway and automatically activate luminous warning signs. The Valencian road-safety company Metalesa carried out the work, with civil works by Grupo Bertolín. The system combines cameras with computer vision and automatic detection algorithms that identify animals passing. It activates dynamic luminous signs only when a real risk exists, and it is powered by photovoltaic energy. Council president Vicent Mompó visited the site with roads deputy Reme Mazzolari. He said that after some weeks the council would evaluate the results. If the system is effective, the council would extend the model to the most sensitive stretches of the provincial network. No detection counts or accident figures are given. 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Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas.", "title": "Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas", "url": "https://web.archive.org/web/2026/https://www.europapress.es/comunitat-valenciana/noticia-diputacio-valencia-ensaya-sistema-inteligente-detecta-jabalies-activa-senales-luminosas-20260212143809.html", "date": "2026-02-12", "written_by": "independent", "quote": "La Diputació de València ha iniciado en la carretera CV-600 las pruebas piloto de un sistema de señalización inteligente diseñado para detectar la presencia de jabalíes" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-02-12-aa5d: AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents.", "title": "AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents", "url": "https://oecd.ai/en/incidents/2026-02-12-aa5d", "date": "2026-02-12", "written_by": "independent", "quote": "Using cameras and detection algorithms, the system identifies wild boars and automatically alerts drivers with illuminated signals" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0256-source-0001", "AIBD-0256-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Europa Press (12 Feb 2026). Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas.", "title": "Diputació de València ensaya un sistema inteligente que detecta jabalíes y activa señales luminosas", "url": "https://web.archive.org/web/2026/https://www.europapress.es/comunitat-valenciana/noticia-diputacio-valencia-ensaya-sistema-inteligente-detecta-jabalies-activa-senales-luminosas-20260212143809.html", "date": "2026-02-12", "written_by": "independent", "quote": "La Diputació de València ha iniciado en la carretera CV-600 las pruebas piloto de un sistema de señalización inteligente diseñado para detectar la presencia de jabalíes" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-02-12-aa5d: AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents.", "title": "AI-Powered System Piloted in Valencia to Prevent Wild Boar Road Accidents", "url": "https://oecd.ai/en/incidents/2026-02-12-aa5d", "date": "2026-02-12", "written_by": "independent", "quote": "Using cameras and detection algorithms, the system identifies wild boars and automatically alerts drivers with illuminated signals" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Europa Press (12 Feb 2026): a solar-powered system combining cameras, computer vision and detection algorithms lights warning signs only when animals are present; the provincial council will evalua...", "account": "Europa Press reported on 12 Feb 2026, from a statement by the Diputació de València, on a set of pilot tests. The provincial council had begun them on the CV-600 road, in the area of Simat de la Valldigna and Benifairó de la Valldigna. The intelligent signaling system is designed to detect wild boar near the carriageway and automatically activate luminous warning signs. The Valencian road-safety company Metalesa carried out the work, with civil works by Grupo Bertolín. The system combines cameras with computer vision and automatic detection algorithms that identify animals passing. It activates dynamic luminous signs only when a real risk exists, and it is powered by photovoltaic energy. Council president Vicent Mompó visited the site with roads deputy Reme Mazzolari. He said that after some weeks the council would evaluate the results. If the system is effective, the council would extend the model to the most sensitive stretches of the provincial network. No detection counts or accident figures are given. The OECD AI Incidents Monitor lists the pilot as an aggregate benefit." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Metalesa camera and computer-vision wild-boar detection with dynamic luminous warning signs (solar-powered)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Metalesa (civil works by Grupo Bertolín)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Diputació de València pilots Metalesa's camera-and-AI wild-boar detection with dynamic warning lights on the CV-600 at Simat de la Valldigna", "headline": "Metalesa AI pilot lights wild-boar warning signs on the CV-600" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "661dae141deadffbc52fa016833f7611b9801fdcf1f47c37aa971dc2eb8358ef" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Europa Press reported on 12 Feb 2026, from a statement by the Diputació de València, on a set of pilot tests. The provincial council had begun them on the CV-600 road, in the area of Simat de la Valldigna and Benifairó de la Valldigna. The intelligent signaling system is designed to detect wild boar near the carriageway and automatically activate luminous warning signs. The Valencian road-safety company Metalesa carried out the work, with civil works by Grupo Bertolín. The system combines cameras with computer vision and automatic detection algorithms that identify animals passing. It activates dynamic luminous signs only when a real risk exists, and it is powered by photovoltaic energy. Council president Vicent Mompó visited the site with roads deputy Reme Mazzolari. He said that after some weeks the council would evaluate the results. If the system is effective, the council would extend the model to the most sensitive stretches of the provincial network. No detection counts or accident figures are given. The OECD AI Incidents Monitor lists the pilot as an aggregate benefit.", "replication": { "produced_by": [ "A road stretch with frequent wildlife crossings", "Camera detection tied to dynamic signs powered by solar panels", "A road authority committed to evaluating before extending" ], "must_hold": [ "Detection works at night when boar move", "Drivers slow in response to the lights" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot (VTTI/VDOT): 3 mph speed reduction, collisions not measured (reported results)", "outcome": "unknown", "source": "https://techxplore.com/news/2026-10-real-driver-animal-collisions.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0102", "title": "TrailGuard AI cameras trigger arrest of 39 armed poachers in Similipal Tiger Reserve", "summary": "AI trail cameras detected armed intruders on 18 February 2026; STR Field Director reports 39 surrendered, nine guns seized, case registered.", "date_observed": "2026-02-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Similipal Tiger Reserve in Mayurbhanj district, Odisha, runs a network of about 220 TrailGuard AI trail cameras. The cameras classify humans, animals and vehicles and send images to a control room. Late on Wednesday 18 February 2026 the cameras detected a group of armed intruders entering the reserve. Field Director Prakash Chand Gogineni said the real-time alerts mobilized the Similipal South Division, three ranges and three Special Tiger Protection Force units. After about 24 hours of combing, at least 39 poachers surrendered. Nine guns, gunpowder and more than 20 bows and arrows were recovered. A case was registered at Jenabil Wildlife Range. Later detections on 11 April, around 24 July and 23 September 2026 led to arrests. Courts refused bail to the July and September groups. The camera count varies by source. The Field Director gave “around 220” in February 2026 and The Hans India “over 220” in July 2026. The Times of India in April 2026 reported 50 AI cameras in use, up from an initial 10, with 300 planned.", "category": "harm prevented", "unexpected": false, "purpose": "Detect human intruders and poachers entering the reserve in near real time so rangers can intercept them before wildlife is killed.", "system": "TrailGuard AI camera network (about 220 units) with embedded human/animal/vehicle classification", "model_version": null, "developer": null, "deployer": "Similipal Tiger Reserve, Odisha Forest Department (Similipal South Division, Special Tiger Protection Force, Similipal Wildlife Intelligence Network)", "location": "Similipal Tiger Reserve, Mayurbhanj, India", "domain": "Conservation and biodiversity", "segment": "Anti-poaching enforcement", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-02-20-fae6" }, "ratings": [ { "group": "personal", "depth": null, "reason": "Not assessed: no specific injury to rangers avoided is documented. The reports describe arrests and seizures." }, { "group": "organizational", "depth": 2, "reason": "The reserve's Field Director states the detection and 24-hour operation averted a major poaching incident. It yielded nine guns and more than 20 bows and arrows." }, { "group": "societal", "depth": 3, "reason": "Armed groups were intercepted inside a tiger reserve more than once. Nine guns and more than 20 bows and arrows were seized. That is material to the reserve's wildlife." } ], "ai_role": { "status": "assessed", "statement": "The AI cameras' real-time detection of the armed group is the stated trigger for the mobilization. That operation ended in surrender and seizure. The park authority's statement is the Field Director's on-record account, quoted by The New Indian Express and the Times of India. The court remands are reported in the press by PTI, Hans India and Ommcom. The cited account lacks corroboration from an available official press note or court order. The account rests on press-quoted forest-department statements." }, "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). 39 persons arrested as AI cameras foil major poaching bid in Similipal.", "title": "39 persons arrested as AI cameras foil major poaching bid in Similipal", "url": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal", "date": "2026-02-20", "written_by": "independent", "quote": "AI-enabled surveillance cameras detected a group of armed intruders entering the sanctuary late on Wednesday night." }, { "kind": "news report", "citation": "The Times of India (2026). AI camera footage helps nab 5 armed poachers in Similipal.", "title": "AI camera footage helps nab 5 armed poachers in Similipal", "url": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms", "date": "2026-04-12", "written_by": "independent", "quote": "The accused were taken into custody after the raid and were later produced before the court" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park.", "title": "AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park", "url": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "date": "2026-09-24", "written_by": "independent", "quote": "The poachers were sent to jail custody after their bail petition was rejected by a local court on Wednesday" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps nab four poachers in Similipal Tiger Reserve.", "title": "AI-enabled camera helps nab four poachers in Similipal Tiger Reserve", "url": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/", "date": "2026-07-24", "written_by": "independent", "quote": "remanded to judicial custody after their bail pleas were rejected" }, { "kind": "news report", "citation": "Sambad English (2026). Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary.", "title": "Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary in Odisha's Mayurbhanj, hunting bid foiled", "url": "https://sambadenglish.com/latest-news/four-poachers-arrested-for-illegal-entry-into-similipal-wildlife-sanctuary-in-odishas-mayurbhanj-hunting-bid-foiled-12193080", "date": "2026-07-24", "written_by": "independent", "quote": "the suspects were detected by AI-enabled TrailGuard cameras installed inside the protected forest" }, { "kind": "news report", "citation": "The Hans India (2026). AI camera helps nab four poachers in Similipal.", "title": "AI camera helps nab four poachers in Similipal", "url": "https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "date": "2026-07-27", "written_by": "independent", "quote": "a case has been registered against the accused at the Podadiha Wildlife Range" }, { "kind": "news report", "citation": "Ommcom News (2025). AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary.", "title": "AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary", "url": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/", "date": "2025-05-09", "written_by": "independent", "quote": "forwarded to the Chief Judicial Magistrate (CJM) court in Baripada and have been sent to judicial custody after their bail was rejected" } ], "replication": { "produced_by": [ "Dense camera coverage of entry trails (about 220 units)", "On-device classification that transmits only human detections", "A staffed control room and armed response units able to deploy within hours", "Prosecution follow-through under the Arms Act and wildlife law" ], "must_hold": [ "Cameras remain concealed and powered", "Alerts reach field teams in near real time", "Response teams can reach remote detection points", "Courts continue to accept camera evidence" ], "echoes": [ { "date": "2025-05-09", "setting": "Three poachers tracked via TrailGuard photographs, Baripada CJM court", "model_version": null, "outcome": "recurred", "source": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/" }, { "date": "2026-04-11", "setting": "Five armed poachers arrested after AI camera capture and house raid, Katuria village", "model_version": null, "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms" }, { "date": "2026-07-24", "setting": "Four poachers apprehended before any wildlife harmed, Podadiha range", "model_version": null, "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/" }, { "date": "2026-09-23", "setting": "Two armed poachers detected separately and jailed after bail refused", "model_version": null, "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "severity": null, "group": "societal", "basis": "AI anti-poaching cameras at Ezemvelo KZN Wildlife missed poachers who killed four rhinos; TrailGuard AI cameras perform the same task at Similipal." }, "headline": "TrailGuard AI alerts lead to arrest of 39 poachers in Similipal", "metric": "at least 39 poachers surrendered", "comparator": null, "later": { "status": "persisted", "date": "2026-09-24", "note": "The camera network kept producing arrests after February 2026, with armed poachers detected and jailed in April, July and September 2026, and the reserve ran over 220 cameras by mid-2026 with expansion planned.", "quote": "The poachers were sent to jail custody after their bail petition was rejected by a local court on Wednesday, the forest officials said, adding that they were detected by a secret AI camera deployed inside Similipal.", "url": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" }, "value": null, "developer_country": null, "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Set developer to null because none of the seven cited sources names RESOLVE or any maker of the TrailGuard cameras, limited the bail refusals to the July and September 2026 groups because the Times of India report on the April arrests says only that the accused were produced before the court, and added the Times of India's lower camera count (50 in use, up from 10, with 300 planned) beside the Field Director's “around 220”.", "source": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal; https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms; https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Similipal_National_Park", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0102", "catalog_version": "1.0.0", "source_fingerprint": "f2fa74ac6313c0122d14f5e42a6b8291016292e413e3cd4aa0f3079b3de0bd75", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0102-source-0001", "AIBD-0102-source-0002", "AIBD-0102-source-0003", "AIBD-0102-source-0004", "AIBD-0102-source-0005", "AIBD-0102-source-0006", "AIBD-0102-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Similipal Tiger Reserve, Odisha Forest Department (Similipal South Division, Special Tiger Protection Force, Similipal Wildlife Intelligence Network)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI cameras' real-time detection of the armed group is the stated trigger for the mobilization. That operation ended in surrender and seizure. The park authority's statement is the Field Director's on-record account, quoted by The New Indian Express and the Times of India. The court remands are reported in the press by PTI, Hans India and Ommcom. The cited account lacks corroboration from an available official press note or court order. The account rests on press-quoted forest-department statements." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The AI cameras' real-time detection of the armed group is the stated trigger for the mobilization. That operation ended in surrender and seizure. The park authority's statement is the Field Director's on-record account, quoted by The New Indian Express and the Times of India. The court remands are reported in the press by PTI, Hans India and Ommcom. The cited account lacks corroboration from an available official press note or court order. The account rests on press-quoted forest-department statements." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Not assessed: no specific injury to rangers avoided is documented. The reports describe arrests and seizures." }, { "group": "organizational", "depth": 2, "reason": "The reserve's Field Director states the detection and 24-hour operation averted a major poaching incident. It yielded nine guns and more than 20 bows and arrows." }, { "group": "societal", "depth": 3, "reason": "Armed groups were intercepted inside a tiger reserve more than once. Nine guns and more than 20 bows and arrows were seized. That is material to the reserve's wildlife." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: seven independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Not assessed: no specific injury to rangers avoided is documented. The reports describe arrests and seizures." }, { "group": "organizational", "depth": 2, "reason": "The reserve's Field Director states the detection and 24-hour operation averted a major poaching incident. It yielded nine guns and more than 20 bows and arrows." }, { "group": "societal", "depth": 3, "reason": "Armed groups were intercepted inside a tiger reserve more than once. Nine guns and more than 20 bows and arrows were seized. That is material to the reserve's wildlife." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Not assessed: no specific injury to rangers avoided is documented. The reports describe arrests and seizures." }, { "group": "organizational", "depth": 2, "reason": "The reserve's Field Director states the detection and 24-hour operation averted a major poaching incident. It yielded nine guns and more than 20 bows and arrows." }, { "group": "societal", "depth": 3, "reason": "Armed groups were intercepted inside a tiger reserve more than once. Nine guns and more than 20 bows and arrows were seized. That is material to the reserve's wildlife." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "AI anti-poaching cameras at Ezemvelo KZN Wildlife missed poachers who killed four rhinos; TrailGuard AI cameras perform the same task at Similipal.", "links": [ { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "group": "societal", "basis": "AI anti-poaching cameras at Ezemvelo KZN Wildlife missed poachers who killed four rhinos; TrailGuard AI cameras perform the same task at Similipal.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "at least 39 poachers surrendered", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-02-20-fae6" }, "paired_incident": { "database": "AI Incident Database", "identifier": "219", "title": "Poachers Evaded AI Cameras and Killed Four Rhinos", "url": "https://incidentdatabase.ai/cite/219", "group": "societal", "basis": "AI anti-poaching cameras at Ezemvelo KZN Wildlife missed poachers who killed four rhinos; TrailGuard AI cameras perform the same task at Similipal." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids", "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-09-24", "note": "The camera network kept producing arrests after February 2026, with armed poachers detected and jailed in April, July and September 2026, and the reserve ran over 220 cameras by mid-2026 with expansion planned.", "quote": "The poachers were sent to jail custody after their bail petition was rejected by a local court on Wednesday, the forest officials said, adding that they were detected by a secret AI camera deployed inside Similipal.", "url": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0102" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Similipal Tiger Reserve in Mayurbhanj district, Odisha, runs a network of about 220 TrailGuard AI trail cameras. The cameras classify humans, animals and vehicles and send images to a control room. Late on Wednesday 18 February 2026 the cameras detected a group of armed intruders entering the reserve. Field Director Prakash Chand Gogineni said the real-time alerts mobilized the Similipal South Division, three ranges and three Special Tiger Protection Force units. After about 24 hours of combing, at least 39 poachers surrendered. Nine guns, gunpowder and more than 20 bows and arrows were recovered. A case was registered at Jenabil Wildlife Range. Later detections on 11 April, around 24 July and 23 September 2026 led to arrests. Courts refused bail to the July and September groups. The camera count varies by source. The Field Director gave “around 220” in February 2026 and The Hans India “over 220” in July 2026. The Times of India in April 2026 reported 50 AI cameras in use, up from an initial 10, with 300 planned.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Not assessed: no specific injury to rangers avoided is documented. The reports describe arrests and seizures." }, { "group": "organizational", "depth": 2, "reason": "The reserve's Field Director states the detection and 24-hour operation averted a major poaching incident. It yielded nine guns and more than 20 bows and arrows." }, { "group": "societal", "depth": 3, "reason": "Armed groups were intercepted inside a tiger reserve more than once. Nine guns and more than 20 bows and arrows were seized. That is material to the reserve's wildlife." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect human intruders and poachers entering the reserve in near real time so rangers can intercept them before wildlife is killed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Similipal Tiger Reserve, Mayurbhanj, India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect human intruders and poachers entering the reserve in near real time so rangers can intercept them before wildlife is killed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-02-18", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Set developer to null because none of the seven cited sources names RESOLVE or any maker of the TrailGuard cameras, limited the bail refusals to the July and September 2026 groups because the Times of India report on the April arrests says only that the accused were produced before the court, and added the Times of India's lower camera count (50 in use, up from 10, with 300 planned) beside the Field Director's “around 220”.", "source": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal; https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms; https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Similipal_National_Park", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Dense camera coverage of entry trails (about 220 units)", "On-device classification that transmits only human detections", "A staffed control room and armed response units able to deploy within hours", "Prosecution follow-through under the Arms Act and wildlife law" ], "must_hold": [ "Cameras remain concealed and powered", "Alerts reach field teams in near real time", "Response teams can reach remote detection points", "Courts continue to accept camera evidence" ], "echoes": [ { "date": "2025-05-09", "setting": "Three poachers tracked via TrailGuard photographs, Baripada CJM court", "outcome": "recurred", "source": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/" }, { "date": "2026-04-11", "setting": "Five armed poachers arrested after AI camera capture and house raid, Katuria village", "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms" }, { "date": "2026-07-24", "setting": "Four poachers apprehended before any wildlife harmed, Podadiha range", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/" }, { "date": "2026-09-23", "setting": "Two armed poachers detected separately and jailed after bail refused", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Dense camera coverage of entry trails (about 220 units)", "On-device classification that transmits only human detections", "A staffed control room and armed response units able to deploy within hours", "Prosecution follow-through under the Arms Act and wildlife law" ], "must_hold": [ "Cameras remain concealed and powered", "Alerts reach field teams in near real time", "Response teams can reach remote detection points", "Courts continue to accept camera evidence" ], "echoes": [ { "date": "2025-05-09", "setting": "Three poachers tracked via TrailGuard photographs, Baripada CJM court", "outcome": "recurred", "source": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/" }, { "date": "2026-04-11", "setting": "Five armed poachers arrested after AI camera capture and house raid, Katuria village", "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms" }, { "date": "2026-07-24", "setting": "Four poachers apprehended before any wildlife harmed, Podadiha range", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/" }, { "date": "2026-09-23", "setting": "Two armed poachers detected separately and jailed after bail refused", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 219 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/219", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Set developer to null because none of the seven cited sources names RESOLVE or any maker of the TrailGuard cameras, limited the bail refusals to the July and September 2026 groups because the Times of India report on the April arrests says only that the accused were produced before the court, and added the Times of India's lower camera count (50 in use, up from 10, with 300 planned) beside the Field Director's “around 220”.", "source": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal; https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms; https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Similipal_National_Park", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Conservation and biodiversity", "segment": "Anti-poaching enforcement" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). 39 persons arrested as AI cameras foil major poaching bid in Similipal.", "title": "39 persons arrested as AI cameras foil major poaching bid in Similipal", "url": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal", "date": "2026-02-20", "written_by": "independent", "quote": "AI-enabled surveillance cameras detected a group of armed intruders entering the sanctuary late on Wednesday night." }, { "kind": "news report", "citation": "The Times of India (2026). AI camera footage helps nab 5 armed poachers in Similipal.", "title": "AI camera footage helps nab 5 armed poachers in Similipal", "url": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms", "date": "2026-04-12", "written_by": "independent", "quote": "The accused were taken into custody after the raid and were later produced before the court" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park.", "title": "AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park", "url": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "date": "2026-09-24", "written_by": "independent", "quote": "The poachers were sent to jail custody after their bail petition was rejected by a local court on Wednesday" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps nab four poachers in Similipal Tiger Reserve.", "title": "AI-enabled camera helps nab four poachers in Similipal Tiger Reserve", "url": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/", "date": "2026-07-24", "written_by": "independent", "quote": "remanded to judicial custody after their bail pleas were rejected" }, { "kind": "news report", "citation": "Sambad English (2026). Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary.", "title": "Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary in Odisha's Mayurbhanj, hunting bid foiled", "url": "https://sambadenglish.com/latest-news/four-poachers-arrested-for-illegal-entry-into-similipal-wildlife-sanctuary-in-odishas-mayurbhanj-hunting-bid-foiled-12193080", "date": "2026-07-24", "written_by": "independent", "quote": "the suspects were detected by AI-enabled TrailGuard cameras installed inside the protected forest" }, { "kind": "news report", "citation": "The Hans India (2026). AI camera helps nab four poachers in Similipal.", "title": "AI camera helps nab four poachers in Similipal", "url": "https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "date": "2026-07-27", "written_by": "independent", "quote": "a case has been registered against the accused at the Podadiha Wildlife Range" }, { "kind": "news report", "citation": "Ommcom News (2025). AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary.", "title": "AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary", "url": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/", "date": "2025-05-09", "written_by": "independent", "quote": "forwarded to the Chief Judicial Magistrate (CJM) court in Baripada and have been sent to judicial custody after their bail was rejected" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0102-source-0001", "AIBD-0102-source-0002", "AIBD-0102-source-0003", "AIBD-0102-source-0004", "AIBD-0102-source-0005", "AIBD-0102-source-0006", "AIBD-0102-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "The New Indian Express (2026). 39 persons arrested as AI cameras foil major poaching bid in Similipal.", "title": "39 persons arrested as AI cameras foil major poaching bid in Similipal", "url": "https://www.newindianexpress.com/states/odisha/2026/Feb/20/39-persons-arrested-as-ai-cameras-foil-major-poaching-bid-in-similipal", "date": "2026-02-20", "written_by": "independent", "quote": "AI-enabled surveillance cameras detected a group of armed intruders entering the sanctuary late on Wednesday night." }, { "kind": "news report", "citation": "The Times of India (2026). AI camera footage helps nab 5 armed poachers in Similipal.", "title": "AI camera footage helps nab 5 armed poachers in Similipal", "url": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms", "date": "2026-04-12", "written_by": "independent", "quote": "The accused were taken into custody after the raid and were later produced before the court" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park.", "title": "AI-enabled camera helps Forest dept to nab two poachers in Similipal National Park", "url": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/", "date": "2026-09-24", "written_by": "independent", "quote": "The poachers were sent to jail custody after their bail petition was rejected by a local court on Wednesday" }, { "kind": "news report", "citation": "PTI via ThePrint (2026). AI-enabled camera helps nab four poachers in Similipal Tiger Reserve.", "title": "AI-enabled camera helps nab four poachers in Similipal Tiger Reserve", "url": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/", "date": "2026-07-24", "written_by": "independent", "quote": "remanded to judicial custody after their bail pleas were rejected" }, { "kind": "news report", "citation": "Sambad English (2026). Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary.", "title": "Four poachers arrested for illegal entry into Similipal Wildlife Sanctuary in Odisha's Mayurbhanj, hunting bid foiled", "url": "https://sambadenglish.com/latest-news/four-poachers-arrested-for-illegal-entry-into-similipal-wildlife-sanctuary-in-odishas-mayurbhanj-hunting-bid-foiled-12193080", "date": "2026-07-24", "written_by": "independent", "quote": "the suspects were detected by AI-enabled TrailGuard cameras installed inside the protected forest" }, { "kind": "news report", "citation": "The Hans India (2026). AI camera helps nab four poachers in Similipal.", "title": "AI camera helps nab four poachers in Similipal", "url": "https://www.thehansindia.com/news/national/ai-camera-helps-nab-four-poachers-in-similipal-1101741", "date": "2026-07-27", "written_by": "independent", "quote": "a case has been registered against the accused at the Podadiha Wildlife Range" }, { "kind": "news report", "citation": "Ommcom News (2025). AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary.", "title": "AI TrailGuard cameras help nab three poachers in Similipal Wildlife Sanctuary", "url": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/", "date": "2025-05-09", "written_by": "independent", "quote": "forwarded to the Chief Judicial Magistrate (CJM) court in Baripada and have been sent to judicial custody after their bail was rejected" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI trail cameras detected armed intruders on 18 February 2026; STR Field Director reports 39 surrendered, nine guns seized, case registered.", "account": "Similipal Tiger Reserve in Mayurbhanj district, Odisha, runs a network of about 220 TrailGuard AI trail cameras. The cameras classify humans, animals and vehicles and send images to a control room. Late on Wednesday 18 February 2026 the cameras detected a group of armed intruders entering the reserve. Field Director Prakash Chand Gogineni said the real-time alerts mobilized the Similipal South Division, three ranges and three Special Tiger Protection Force units. After about 24 hours of combing, at least 39 poachers surrendered. Nine guns, gunpowder and more than 20 bows and arrows were recovered. A case was registered at Jenabil Wildlife Range. Later detections on 11 April, around 24 July and 23 September 2026 led to arrests. Courts refused bail to the July and September groups. The camera count varies by source. The Field Director gave “around 220” in February 2026 and The Hans India “over 220” in July 2026. The Times of India in April 2026 reported 50 AI cameras in use, up from an initial 10, with 300 planned." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "TrailGuard AI camera network (about 220 units) with embedded human/animal/vehicle classification" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TrailGuard AI cameras trigger arrest of 39 armed poachers in Similipal Tiger Reserve", "headline": "TrailGuard AI alerts lead to arrest of 39 poachers in Similipal" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f2fa74ac6313c0122d14f5e42a6b8291016292e413e3cd4aa0f3079b3de0bd75" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Similipal Tiger Reserve in Mayurbhanj district, Odisha, runs a network of about 220 TrailGuard AI trail cameras. The cameras classify humans, animals and vehicles and send images to a control room. Late on Wednesday 18 February 2026 the cameras detected a group of armed intruders entering the reserve. Field Director Prakash Chand Gogineni said the real-time alerts mobilized the Similipal South Division, three ranges and three Special Tiger Protection Force units. After about 24 hours of combing, at least 39 poachers surrendered. Nine guns, gunpowder and more than 20 bows and arrows were recovered. A case was registered at Jenabil Wildlife Range. Later detections on 11 April, around 24 July and 23 September 2026 led to arrests. Courts refused bail to the July and September groups. The camera count varies by source. The Field Director gave “around 220” in February 2026 and The Hans India “over 220” in July 2026. The Times of India in April 2026 reported 50 AI cameras in use, up from an initial 10, with 300 planned.", "replication": { "produced_by": [ "Dense camera coverage of entry trails (about 220 units)", "On-device classification that transmits only human detections", "A staffed control room and armed response units able to deploy within hours", "Prosecution follow-through under the Arms Act and wildlife law" ], "must_hold": [ "Cameras remain concealed and powered", "Alerts reach field teams in near real time", "Response teams can reach remote detection points", "Courts continue to accept camera evidence" ], "echoes": [ { "date": "2025-05-09", "setting": "Three poachers tracked via TrailGuard photographs, Baripada CJM court", "outcome": "recurred", "source": "https://ommcomnews.com/odisha-news/ai-trailguard-cameras-help-nab-three-poachers-in-similipal-wildlife-sanctuary/" }, { "date": "2026-04-11", "setting": "Five armed poachers arrested after AI camera capture and house raid, Katuria village", "outcome": "recurred", "source": "https://timesofindia.indiatimes.com/city/bhubaneswar/ai-camera-footage-helps-nab-5-armed-poachers-in-similipal/articleshow/130197981.cms" }, { "date": "2026-07-24", "setting": "Four poachers apprehended before any wildlife harmed, Podadiha range", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-nab-four-poachers-in-similipal-tiger-reserve/2996083/" }, { "date": "2026-09-23", "setting": "Two armed poachers detected separately and jailed after bail refused", "outcome": "recurred", "source": "https://theprint.in/india/ai-enabled-camera-helps-forest-dept-to-nab-two-poachers-in-similipal-national-park/3052132/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0157", "title": "Rishi Vohra's Tesla Cybertruck on FSD (Supervised) may have detected that he had passed out on a freeway, slowed, put on its hazards and pulled onto the shoulder, then driven him to the ER (18 February 2026)", "summary": "Rishi Vohra says FSD pulled his Cybertruck onto a freeway shoulder after he passed out, 18 February 2026; Musk replied, no data published.", "date_observed": "2026-02-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In an X post of 19 February 2026, Rishi Vohra wrote that he passed out while driving on 18 February. He was on a freeway in his Tesla Cybertruck, mid-call with his wife. He had passed out after a severe allergic reaction, following a 17-hour unintentional fast and medicine. Full Self-Driving (Supervised) was engaged, he wrote. Its driver monitoring system detected his loss of consciousness. The truck slowed, put on hazards and pulled onto the shoulder without a crash. His wife used Life360 to send emergency services, who reached him in five minutes. The car drove him to an emergency room, where he was stabilized overnight and discharged on 19 February. Musk replied “Glad you're ok!”. No vehicle data or official confirmation has been published.", "category": "protective response", "unexpected": false, "purpose": "Tesla sells Full Self-Driving (Supervised) as driver assistance that still requires driver supervision, as Storyboard18 notes. Its cabin driver-monitoring system watches the driver. Vohra credits that monitoring with detecting his loss of consciousness. He credits the system with slowing, putting on hazards and pulling onto the shoulder. Keeping the car out of a crash is what the system is built to do. Tesla has not described whether the stop was a designed unresponsive-driver fallback. The later drive to the emergency room used the system's ordinary point-to-point driving.", "system": "Tesla Full Self-Driving (Supervised) with cabin driver monitoring, on a Tesla Cybertruck as described by the driver and Teslarati", "model_version": "Not reported; Vohra wrote only that Full Self-Driving was engaged, and Teslarati calls it FSD Supervised on a Cybertruck", "developer": "Tesla", "deployer": null, "location": null, "domain": "Road vehicle crash avoidance", "segment": "Automotive", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-02-20-66a3" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "By his account Vohra was unconscious at freeway speed and the truck stopped on the shoulder without hitting anything. It then took him to an emergency room, where he was stabilized overnight. He and the Indian outlets call it life-saving. The only source is his post. No vehicle data, police, emergency-service or hospital record has been published. The freeway, FSD version and hospital are unnamed." } ], "ai_role": { "status": "unassessed", "statement": "Everything known about what the system did comes from Vohra's post. FSD (Supervised) was engaged, and the driver monitoring system registered that he had lost consciousness. The truck slowed, put on its hazards and pulled onto the shoulder. After responders had attended to him, it drove him to the emergency room. The post carries a video that The American Bazaar describes as showing emergency services responding, not the pull-over itself. Tesla has published no vehicle data or statement. Its account replied with a heart and Elon Musk wrote “Glad you're ok!”. Those replies acknowledge the outcome, not the mechanism. No police, emergency-service or hospital record, freeway location or FSD version has been published." }, "evidence": [ { "kind": "other", "citation": "Vohra, R. (2026). Post on X, @rishivohra, 19 February 2026 (17:38 UTC), status 2024539159269167410; video and photo attached.", "title": "My Tesla literally saved my life yesterday", "url": "https://x.com/rishivohra/status/2024539159269167410", "date": "2026-02-19", "written_by": "beneficiary", "quote": "My Tesla literally saved my life yesterday. What started as a normal drive turned terrifying fast." }, { "kind": "news report", "citation": "Alvarez, S. (2026). Tesla Cybertruck owner credits FSD for saving life after freeway medical emergency. Teslarati (enthusiast site), 20 February 2026.", "title": "Tesla Cybertruck owner credits FSD for saving life after freeway medical emergency", "url": "https://www.teslarati.com/tesla-cybertruck-fsd-saving-life-freeway-medical-emergency/", "date": "2026-02-20", "written_by": "independent", "quote": "It detected I lost consciousness (thanks to the driver monitoring system), immediately slowed, activated hazards, and safely pulled over to the shoulder." }, { "kind": "news report", "citation": "Chouhan, M. S. (2026). Elon Musk responds after Indian-origin man says Tesla drove him to ER when he fainted mid-drive. Hindustan Times, 20 February 2026.", "title": "Elon Musk responds after Indian-origin man says Tesla drove him to ER when he fainted mid-drive", "url": "https://www.hindustantimes.com/trending/elon-musk-reacts-after-man-claims-tesla-saved-his-life-during-freeway-medical-emergency-life-saving-tech-101771574831376.html", "date": "2026-02-20", "written_by": "independent", "quote": "A Tesla owner has claimed that the company’s autonomous driving technology helped prevent a potentially fatal accident after he lost consciousness behind the wheel during a medical emergency." }, { "kind": "news report", "citation": "Storyboard18 (2026). Indian-origin Tesla owner says car prevented crash after he passed out, Musk says 'Glad You're Ok!'. Storyboard18, 20 February 2026.", "title": "Indian-origin Tesla owner says car prevented crash after he passed out, Musk says ‘Glad You’re Ok!’", "url": "https://www.storyboard18.com/trending/indian-origin-tesla-owner-says-car-prevented-crash-after-he-passed-out-musk-says-glad-youre-ok-90258.htm", "date": "2026-02-20", "written_by": "independent", "quote": "While Tesla’s Full Self-Driving system still requires driver supervision and remains under regulatory scrutiny in several regions" }, { "kind": "news report", "citation": "AB Wire (2026). Elon Musk responds to Tesla saving a person's life during accident. The American Bazaar, 20 February 2026 (reproduces the full text of the post).", "title": "Elon Musk responds to Tesla saving a person’s life during accident", "url": "https://americanbazaaronline.com/2026/02/20/elon-musk-responds-to-tesla-saving-a-persons-life-during-accident-475581/", "date": "2026-02-20", "written_by": "independent", "quote": "The user also posted a video of emergency services responding to the accident." }, { "kind": "press release", "citation": "Musk, E. (2026). Reply on X, @elonmusk, 19 February 2026 (18:26 UTC), status 2024551075576189357.", "title": "Glad you’re ok!", "url": "https://x.com/elonmusk/status/2024551075576189357", "date": "2026-02-19", "written_by": "makers", "quote": "Glad you’re ok! ❤️" } ], "replication": { "produced_by": [ "A Tesla Cybertruck with Full Self-Driving (Supervised) engaged on a freeway, by Vohra's account", "A cabin driver-monitoring system that, on his account, registered his loss of consciousness. The truck then slowed, put on its hazards and pulled onto the shoulder", "A wife on the phone who used Life360 to send emergency services to him within five minutes. Responders attended to him before he had the car continue to the emergency room" ], "must_hold": [ "FSD (Supervised) requires driver supervision, per Storyboard18. An unconscious driver is outside its intended operating condition. Whatever stopped the truck was a fallback, not a substitute for an attentive driver", "The account is Vohra's alone. No Tesla vehicle data, police or emergency-service record, hospital statement, freeway location, FSD version or footage of the pull-over has been published. The replies from Elon Musk and Tesla's account acknowledge the outcome without confirming the mechanism", "Vohra chose to have the car take him to the emergency room after responders had reached him. Emergency services, not the car, were the documented first response" ], "echoes": [] }, "paired_incident": null, "headline": "Tesla FSD may have pulled over after Rishi Vohra passed out", "metric": null, "comparator": { "against": "a manually driven vehicle whose driver loses consciousness", "before": "would have likely crashed or caused a pileup", "after": "immediately slowed, activated hazards, and safely pulled over to the shoulder", "basis": "assumed", "quote": "A vehicle that is manually driven would have likely crashed or caused a pileup if its driver lost consciousness in the middle of the freeway, after all.", "url": "https://www.teslarati.com/tesla-cybertruck-fsd-saving-life-freeway-medical-emergency/" }, "later": { "status": "unknown", "date": null, "note": "No vehicle data, Tesla confirmation or later development was found after the February 2026 reports.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. Date set to 18 February 2026, the day before Vohra's post (“yesterday”), rather than the Monitor's 20 February 2026 report date.", "source": "https://oecd.ai/en/incidents/2026-02-20-66a3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.teslarati.com/tesla-cybertruck-fsd-saving-life-freeway-medical-emergency/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports, the makers' press release and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0157", "catalog_version": "1.0.0", "source_fingerprint": "b229eb9a17df496e65561be64cfbb0dbeedb176c955564d224818697d9727315", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0157-source-0001", "AIBD-0157-source-0002", "AIBD-0157-source-0003", "AIBD-0157-source-0004", "AIBD-0157-source-0005", "AIBD-0157-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "display": { "answer": "Vohra reported that his Cybertruck detected his loss of consciousness, slowed, activated its hazard lights, and pulled over while Full Self-Driving was engaged. He said that it later drove him to an emergency department.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "unassessed", "statement": "Everything known about what the system did comes from Vohra's post. FSD (Supervised) was engaged, and the driver monitoring system registered that he had lost consciousness. The truck slowed, put on its hazards and pulled onto the shoulder. After responders had attended to him, it drove him to the emergency room. The post carries a video that The American Bazaar describes as showing emergency services responding, not the pull-over itself. Tesla has published no vehicle data or statement. Its account replied with a heart and Elon Musk wrote “Glad you're ok!”. Those replies acknowledge the outcome, not the mechanism. No police, emergency-service or hospital record, freeway location or FSD version has been published." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By his account Vohra was unconscious at freeway speed and the truck stopped on the shoulder without hitting anything. It then took him to an emergency room, where he was stabilized overnight. He and the Indian outlets call it life-saving. The only source is his post. No vehicle data, police, emergency-service or hospital record has been published. The freeway, FSD version and hospital are unnamed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports, the makers' press release and the beneficiary's other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By his account Vohra was unconscious at freeway speed and the truck stopped on the shoulder without hitting anything. It then took him to an emergency room, where he was stabilized overnight. He and the Indian outlets call it life-saving. The only source is his post. No vehicle data, police, emergency-service or hospital record has been published. The freeway, FSD version and hospital are unnamed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By his account Vohra was unconscious at freeway speed and the truck stopped on the shoulder without hitting anything. It then took him to an emergency room, where he was stabilized overnight. He and the Indian outlets call it life-saving. The only source is his post. No vehicle data, police, emergency-service or hospital record has been published. The freeway, FSD version and hospital are unnamed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", 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He was on a freeway in his Tesla Cybertruck, mid-call with his wife. He had passed out after a severe allergic reaction, following a 17-hour unintentional fast and medicine. Full Self-Driving (Supervised) was engaged, he wrote. Its driver monitoring system detected his loss of consciousness. The truck slowed, put on hazards and pulled onto the shoulder without a crash. His wife used Life360 to send emergency services, who reached him in five minutes. The car drove him to an emergency room, where he was stabilized overnight and discharged on 19 February. Musk replied “Glad you're ok!”. No vehicle data or official confirmation has been published.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "By his account Vohra was unconscious at freeway speed and the truck stopped on the shoulder without hitting anything. It then took him to an emergency room, where he was stabilized overnight. He and the Indian outlets call it life-saving. The only source is his post. No vehicle data, police, emergency-service or hospital record has been published. The freeway, FSD version and hospital are unnamed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Tesla sells Full Self-Driving (Supervised) as driver assistance that still requires driver supervision, as Storyboard18 notes. Its cabin driver-monitoring system watches the driver. Vohra credits that monitoring with detecting his loss of consciousness. He credits the system with slowing, putting on hazards and pulling onto the shoulder. Keeping the car out of a crash is what the system is built to do. Tesla has not described whether the stop was a designed unresponsive-driver fallback. 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Storyboard18, 20 February 2026.", "title": "Indian-origin Tesla owner says car prevented crash after he passed out, Musk says ‘Glad You’re Ok!’", "url": "https://www.storyboard18.com/trending/indian-origin-tesla-owner-says-car-prevented-crash-after-he-passed-out-musk-says-glad-youre-ok-90258.htm", "date": "2026-02-20", "written_by": "independent", "quote": "While Tesla’s Full Self-Driving system still requires driver supervision and remains under regulatory scrutiny in several regions" }, { "kind": "news report", "citation": "AB Wire (2026). Elon Musk responds to Tesla saving a person's life during accident. The American Bazaar, 20 February 2026 (reproduces the full text of the post).", "title": "Elon Musk responds to Tesla saving a person’s life during accident", "url": "https://americanbazaaronline.com/2026/02/20/elon-musk-responds-to-tesla-saving-a-persons-life-during-accident-475581/", "date": "2026-02-20", "written_by": "independent", "quote": "The user also posted a video of emergency services responding to the accident." }, { "kind": "press release", "citation": "Musk, E. (2026). Reply on X, @elonmusk, 19 February 2026 (18:26 UTC), status 2024551075576189357.", "title": "Glad you’re ok!", "url": "https://x.com/elonmusk/status/2024551075576189357", "date": "2026-02-19", "written_by": "makers", "quote": "Glad you’re ok! ❤️" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Rishi Vohra says FSD pulled his Cybertruck onto a freeway shoulder after he passed out, 18 February 2026; Musk replied, no data published.", "account": "In an X post of 19 February 2026, Rishi Vohra wrote that he passed out while driving on 18 February. He was on a freeway in his Tesla Cybertruck, mid-call with his wife. He had passed out after a severe allergic reaction, following a 17-hour unintentional fast and medicine. Full Self-Driving (Supervised) was engaged, he wrote. Its driver monitoring system detected his loss of consciousness. The truck slowed, put on hazards and pulled onto the shoulder without a crash. His wife used Life360 to send emergency services, who reached him in five minutes. The car drove him to an emergency room, where he was stabilized overnight and discharged on 19 February. Musk replied “Glad you're ok!”. No vehicle data or official confirmation has been published." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "Vohra reported that the system detected his unresponsiveness and pulled the vehicle onto the shoulder." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Vohra reported that Full Self-Driving was engaged. Teslarati identified the vehicle as a Cybertruck." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not reported; Vohra wrote only that Full Self-Driving was engaged, and Teslarati calls it FSD Supervised on a Cybertruck" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Full Self-Driving (Supervised) with cabin driver monitoring, on a Tesla Cybertruck as described by the driver and Teslarati" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rishi Vohra's Tesla Cybertruck on FSD (Supervised) may have detected that he had passed out on a freeway, slowed, put on its hazards and pulled onto the shoulder, then driven him to the ER (18 February 2026)", "headline": "Tesla FSD may have pulled over after Rishi Vohra passed out" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b229eb9a17df496e65561be64cfbb0dbeedb176c955564d224818697d9727315" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In an X post of 19 February 2026, Rishi Vohra wrote that he passed out while driving on 18 February. He was on a freeway in his Tesla Cybertruck, mid-call with his wife. He had passed out after a severe allergic reaction, following a 17-hour unintentional fast and medicine. Full Self-Driving (Supervised) was engaged, he wrote. Its driver monitoring system detected his loss of consciousness. The truck slowed, put on hazards and pulled onto the shoulder without a crash. His wife used Life360 to send emergency services, who reached him in five minutes. The car drove him to an emergency room, where he was stabilized overnight and discharged on 19 February. Musk replied “Glad you're ok!”. No vehicle data or official confirmation has been published.", "replication": { "produced_by": [ "A Tesla Cybertruck with Full Self-Driving (Supervised) engaged on a freeway, by Vohra's account", "A cabin driver-monitoring system that, on his account, registered his loss of consciousness. The truck then slowed, put on its hazards and pulled onto the shoulder", "A wife on the phone who used Life360 to send emergency services to him within five minutes. Responders attended to him before he had the car continue to the emergency room" ], "must_hold": [ "FSD (Supervised) requires driver supervision, per Storyboard18. An unconscious driver is outside its intended operating condition. Whatever stopped the truck was a fallback, not a substitute for an attentive driver", "The account is Vohra's alone. No Tesla vehicle data, police or emergency-service record, hospital statement, freeway location, FSD version or footage of the pull-over has been published. The replies from Elon Musk and Tesla's account acknowledge the outcome without confirming the mechanism", "Vohra chose to have the car take him to the emergency room after responders had reached him. Emergency services, not the car, were the documented first response" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0302", "title": "Apple Watch Crash Detection calls 911 for Andi Burns, 19, trapped upside down in her pickup in the Little Miami River; Clermont County crews pull her out with bruises only", "summary": "On 22 February 2026 near Batavia, Ohio, a 19-year-old's truck flipped into the Little Miami River; Clermont County officials say her Apple Watch called 911 by Crash Detection and crews freed her.", "date_observed": "2026-02-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Andi Burns, 19, was driving home from work on State Route 222 in Batavia Township, Clermont County, Ohio, on 22 February 2026. The Ohio State Highway Patrol accident report cited by ABC News says she lost control on black ice. She hit a tree and went off an embankment into the Little Miami River. WLWT says the truck dropped down a 15-foot ravine and flipped. ABC News (4 March 2026) reports that “According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature”. Body-camera footage released by the Clermont County Sheriff's Office shows a dispatcher keeping her on the line. Central Joint Fire-EMS District firefighters and sheriff's deputies smashed a window and pulled her out. First-year firefighter Tommy Jetter was first into the water. Burns had found a pocket of air of about four inches at the floorboard. The accident report says she walked away with bruises. Burns told WKRC (11 March 2026) that there was also “a crash detection on the Live 360 that my mom had on her phone”. She said it called the police and her family, so a second crash-detection service may have placed calls. WLWT and ABC attribute the 911 call to the Apple Watch.", "category": "protective response", "unexpected": false, "purpose": "Crash Detection is built to recognize a severe car crash from sensor data. It then calls emergency services with the device's location if the wearer does not respond. This call was that purpose.", "system": "Apple Watch Crash Detection", "model_version": null, "developer": "Apple", "deployer": null, "location": "Batavia Township, Clermont County, Ohio, United States", "domain": "Emergency response / road traffic injury", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Rescuers and Burns describe a submerged cab with four to six inches of air. Firefighter Jetter called her survival “very, very, very lucky”. The call brought crews at night to a river crash. Whether anyone else would have called is not documented, and the sources are news reports." }, { "group": "organizational", "depth": 1, "reason": "Clermont County dispatch received the automated call with a location and stayed on the line. The sheriff's office released the body-camera video. No agency statement on timing or resources is among the sources." } ], "ai_role": { "status": "assessed", "statement": "ABC News, citing Clermont County officials, and WLWT say the Apple Watch's Crash Detection placed the 911 call. Apple's support page says the feature detects severe crashes from on-device sensor data. It calls automatically after a countdown if the wearer does not respond. Burns also told WKRC that a Life360 crash-detection service on her mother's phone called police and family. The watch may not have been the only alert. Only news reports are among the sources, and no dispatch log or agency statement is on record." }, "evidence": [ { "kind": "news report", "citation": "ABC News / Good Morning America (2026). 19-year-old rescued from car sinking in freezing water speaks out. 4 March 2026.", "title": "19-year-old rescued from car sinking in freezing water speaks out", "url": "https://abcnews.com/GMA/News/19-year-pulled-sinking-car-details-rescue-responders/story?id=130747244", "date": "2026-03-04", "written_by": "independent", "quote": "According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature." }, { "kind": "news report", "citation": "WLWT News 5 (2026). 19-year-old pulled from near-drowning truck crash in Little Miami River. Updated 26 February 2026.", "title": "19-year-old pulled from near-drowning truck crash in Little Miami River", "url": "https://www.wlwt.com/article/miami-river-body-camera-video-rescue-car-truck/70526120", "date": "2026-02-26", "written_by": "independent", "quote": "Her Apple Watch crash detection called 911." }, { "kind": "news report", "citation": "Clements A (2026). Woman thanks rescuers who saved her from crash into Clermont County river. WKRC Local 12, 11 March 2026.", "title": "Woman thanks rescuers who saved her from crash into Clermont County river", "url": "https://web.archive.org/web/20260311210830/https://local12.com/news/local/woman-thanks-rescuers-who-saved-her-from-crash-into-clermont-county-creek-andi-burns-ice-little-miami-river-apple-watch-thomas-jetter-first-responders", "date": "2026-03-11", "written_by": "independent", "quote": "I had my Apple Watch on that day, and there was a crash detection on the Live 360 that my mom had on her phone. It called the police." }, { "kind": "press release", "citation": "Apple Support. Use Crash Detection on iPhone or Apple Watch to call for help in an accident (article 104959).", "title": "Use Crash Detection on iPhone or Apple Watch to call for help in an accident", "url": "https://support.apple.com/en-us/104959", "date": null, "written_by": "makers", "quote": "If you're unable to respond, your device automatically calls emergency services after a 30-second countdown." } ], "replication": { "produced_by": [ "A supported Apple Watch (Series 8 or later, SE 2nd generation, Ultra) with Crash Detection on and a cellular or Wi-Fi path to emergency services", "A severe crash (rollover into water) with the wearer unable to reach a phone", "A dispatcher able to act on the automated call and location" ], "must_hold": [ "The on-device crash classifier recognizes the impact as a severe car crash", "The wearer does not dismiss the alert within the countdown", "Responders can reach the transmitted location in time" ], "echoes": [ { "date": "2024-12-16", "setting": "Easthampton, Massachusetts: Brent Hill, 55, blacked out while driving and landed upside down in a neighbor's pool; emergency services spoke to him through the watch and arrived within minutes (Western Mass News, 16 January 2025)", "model_version": null, "outcome": "recurred", "source": "https://www.westernmassnews.com/2025/01/16/easthampton-man-credits-apple-watch-helping-save-his-life/" } ] }, "paired_incident": null, "headline": "Apple Watch Crash Detection calls 911 for Andi Burns in a river", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-03-11", "note": "WKRC reported on 11 March 2026 that Burns was alive and well and had thanked the Clermont County responders; ABC News (4 March) said the accident report recorded only bruises.", "quote": "A local woman is alive and well after she's rescued from frigid waters by first responders.", "url": "https://web.archive.org/web/20260311210830/https://local12.com/news/local/woman-thanks-rescuers-who-saved-her-from-crash-into-clermont-county-creek-andi-burns-ice-little-miami-river-apple-watch-thomas-jetter-first-responders" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://web.archive.org/web/20260311210830/https://local12.com/news/local/woman-thanks-rescuers-who-saved-her-from-crash-into-clermont-county-creek-andi-burns-ice-little-miami-river-apple-watch-thomas-jetter-first-responders", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0302", "catalog_version": "1.0.0", "source_fingerprint": "ddecf428306c8ef0d7ef7c11420d47a6b43501cd38e569c2e39070264c7d9294", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0302-source-0001", "AIBD-0302-source-0002", "AIBD-0302-source-0003", "AIBD-0302-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "ABC News, citing Clermont County officials, and WLWT say the Apple Watch's Crash Detection placed the 911 call. Apple's support page says the feature detects severe crashes from on-device sensor data. It calls automatically after a countdown if the wearer does not respond. Burns also told WKRC that a Life360 crash-detection service on her mother's phone called police and family. The watch may not have been the only alert. Only news reports are among the sources, and no dispatch log or agency statement is on record." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "ABC News, citing Clermont County officials, and WLWT say the Apple Watch's Crash Detection placed the 911 call. Apple's support page says the feature detects severe crashes from on-device sensor data. It calls automatically after a countdown if the wearer does not respond. Burns also told WKRC that a Life360 crash-detection service on her mother's phone called police and family. The watch may not have been the only alert. Only news reports are among the sources, and no dispatch log or agency statement is on record." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rescuers and Burns describe a submerged cab with four to six inches of air. Firefighter Jetter called her survival “very, very, very lucky”. The call brought crews at night to a river crash. Whether anyone else would have called is not documented, and the sources are news reports." }, { "group": "organizational", "depth": 1, "reason": "Clermont County dispatch received the automated call with a location and stayed on the line. The sheriff's office released the body-camera video. No agency statement on timing or resources is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rescuers and Burns describe a submerged cab with four to six inches of air. Firefighter Jetter called her survival “very, very, very lucky”. The call brought crews at night to a river crash. Whether anyone else would have called is not documented, and the sources are news reports." }, { "group": "organizational", "depth": 1, "reason": "Clermont County dispatch received the automated call with a location and stayed on the line. The sheriff's office released the body-camera video. No agency statement on timing or resources is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rescuers and Burns describe a submerged cab with four to six inches of air. Firefighter Jetter called her survival “very, very, very lucky”. The call brought crews at night to a river crash. Whether anyone else would have called is not documented, and the sources are news reports." }, { "group": "organizational", "depth": 1, "reason": "Clermont County dispatch received the automated call with a location and stayed on the line. The sheriff's office released the body-camera video. 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The Ohio State Highway Patrol accident report cited by ABC News says she lost control on black ice. She hit a tree and went off an embankment into the Little Miami River. WLWT says the truck dropped down a 15-foot ravine and flipped. ABC News (4 March 2026) reports that “According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature”. Body-camera footage released by the Clermont County Sheriff's Office shows a dispatcher keeping her on the line. Central Joint Fire-EMS District firefighters and sheriff's deputies smashed a window and pulled her out. First-year firefighter Tommy Jetter was first into the water. Burns had found a pocket of air of about four inches at the floorboard. The accident report says she walked away with bruises. Burns told WKRC (11 March 2026) that there was also “a crash detection on the Live 360 that my mom had on her phone”. She said it called the police and her family, so a second crash-detection service may have placed calls. WLWT and ABC attribute the 911 call to the Apple Watch.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Rescuers and Burns describe a submerged cab with four to six inches of air. Firefighter Jetter called her survival “very, very, very lucky”. The call brought crews at night to a river crash. Whether anyone else would have called is not documented, and the sources are news reports." }, { "group": "organizational", "depth": 1, "reason": "Clermont County dispatch received the automated call with a location and stayed on the line. The sheriff's office released the body-camera video. No agency statement on timing or resources is among the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Crash Detection is built to recognize a severe car crash from sensor data. It then calls emergency services with the device's location if the wearer does not respond. 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facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A supported Apple Watch (Series 8 or later, SE 2nd generation, Ultra) with Crash Detection on and a cellular or Wi-Fi path to emergency services", "A severe crash (rollover into water) with the wearer unable to reach a phone", "A dispatcher able to act on the automated call and location" ], "must_hold": [ "The on-device crash classifier recognizes the impact as a severe car crash", "The wearer does not dismiss the alert within the countdown", "Responders can reach the transmitted location in time" ], "echoes": [ { "date": "2024-12-16", "setting": "Easthampton, Massachusetts: Brent Hill, 55, blacked out while driving and landed upside down in a neighbor's pool; 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Updated 26 February 2026.", "title": "19-year-old pulled from near-drowning truck crash in Little Miami River", "url": "https://www.wlwt.com/article/miami-river-body-camera-video-rescue-car-truck/70526120", "date": "2026-02-26", "written_by": "independent", "quote": "Her Apple Watch crash detection called 911." }, { "kind": "news report", "citation": "Clements A (2026). Woman thanks rescuers who saved her from crash into Clermont County river. WKRC Local 12, 11 March 2026.", "title": "Woman thanks rescuers who saved her from crash into Clermont County river", "url": "https://web.archive.org/web/20260311210830/https://local12.com/news/local/woman-thanks-rescuers-who-saved-her-from-crash-into-clermont-county-creek-andi-burns-ice-little-miami-river-apple-watch-thomas-jetter-first-responders", "date": "2026-03-11", "written_by": "independent", "quote": "I had my Apple Watch on that day, and there was a crash detection on the Live 360 that my mom had on her phone. It called the police." }, { "kind": "press release", "citation": "Apple Support. Use Crash Detection on iPhone or Apple Watch to call for help in an accident (article 104959).", "title": "Use Crash Detection on iPhone or Apple Watch to call for help in an accident", "url": "https://support.apple.com/en-us/104959", "written_by": "makers", "quote": "If you're unable to respond, your device automatically calls emergency services after a 30-second countdown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0302-source-0001", "AIBD-0302-source-0002", "AIBD-0302-source-0003", "AIBD-0302-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "ABC News / Good Morning America (2026). 19-year-old rescued from car sinking in freezing water speaks out. 4 March 2026.", "title": "19-year-old rescued from car sinking in freezing water speaks out", "url": "https://abcnews.com/GMA/News/19-year-pulled-sinking-car-details-rescue-responders/story?id=130747244", "date": "2026-03-04", "written_by": "independent", "quote": "According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature." }, { "kind": "news report", "citation": "WLWT News 5 (2026). 19-year-old pulled from near-drowning truck crash in Little Miami River. Updated 26 February 2026.", "title": "19-year-old pulled from near-drowning truck crash in Little Miami River", "url": "https://www.wlwt.com/article/miami-river-body-camera-video-rescue-car-truck/70526120", "date": "2026-02-26", "written_by": "independent", "quote": "Her Apple Watch crash detection called 911." }, { "kind": "news report", "citation": "Clements A (2026). Woman thanks rescuers who saved her from crash into Clermont County river. WKRC Local 12, 11 March 2026.", "title": "Woman thanks rescuers who saved her from crash into Clermont County river", "url": "https://web.archive.org/web/20260311210830/https://local12.com/news/local/woman-thanks-rescuers-who-saved-her-from-crash-into-clermont-county-creek-andi-burns-ice-little-miami-river-apple-watch-thomas-jetter-first-responders", "date": "2026-03-11", "written_by": "independent", "quote": "I had my Apple Watch on that day, and there was a crash detection on the Live 360 that my mom had on her phone. It called the police." }, { "kind": "press release", "citation": "Apple Support. Use Crash Detection on iPhone or Apple Watch to call for help in an accident (article 104959).", "title": "Use Crash Detection on iPhone or Apple Watch to call for help in an accident", "url": "https://support.apple.com/en-us/104959", "written_by": "makers", "quote": "If you're unable to respond, your device automatically calls emergency services after a 30-second countdown." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "On 22 February 2026 near Batavia, Ohio, a 19-year-old's truck flipped into the Little Miami River; Clermont County officials say her Apple Watch called 911 by Crash Detection and crews freed her.", "account": "Andi Burns, 19, was driving home from work on State Route 222 in Batavia Township, Clermont County, Ohio, on 22 February 2026. The Ohio State Highway Patrol accident report cited by ABC News says she lost control on black ice. She hit a tree and went off an embankment into the Little Miami River. WLWT says the truck dropped down a 15-foot ravine and flipped. ABC News (4 March 2026) reports that “According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature”. Body-camera footage released by the Clermont County Sheriff's Office shows a dispatcher keeping her on the line. Central Joint Fire-EMS District firefighters and sheriff's deputies smashed a window and pulled her out. First-year firefighter Tommy Jetter was first into the water. Burns had found a pocket of air of about four inches at the floorboard. The accident report says she walked away with bruises. Burns told WKRC (11 March 2026) that there was also “a crash detection on the Live 360 that my mom had on her phone”. She said it called the police and her family, so a second crash-detection service may have placed calls. 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The Ohio State Highway Patrol accident report cited by ABC News says she lost control on black ice. She hit a tree and went off an embankment into the Little Miami River. WLWT says the truck dropped down a 15-foot ravine and flipped. ABC News (4 March 2026) reports that “According to Clermont County officials, Burns was wearing an Apple Watch that automatically called 911 using its crash detection feature”. Body-camera footage released by the Clermont County Sheriff's Office shows a dispatcher keeping her on the line. Central Joint Fire-EMS District firefighters and sheriff's deputies smashed a window and pulled her out. First-year firefighter Tommy Jetter was first into the water. Burns had found a pocket of air of about four inches at the floorboard. The accident report says she walked away with bruises. Burns told WKRC (11 March 2026) that there was also “a crash detection on the Live 360 that my mom had on her phone”. She said it called the police and her family, so a second crash-detection service may have placed calls. WLWT and ABC attribute the 911 call to the Apple Watch.", "replication": { "produced_by": [ "A supported Apple Watch (Series 8 or later, SE 2nd generation, Ultra) with Crash Detection on and a cellular or Wi-Fi path to emergency services", "A severe crash (rollover into water) with the wearer unable to reach a phone", "A dispatcher able to act on the automated call and location" ], "must_hold": [ "The on-device crash classifier recognizes the impact as a severe car crash", "The wearer does not dismiss the alert within the countdown", "Responders can reach the transmitted location in time" ], "echoes": [ { "date": "2024-12-16", "setting": "Easthampton, Massachusetts: Brent Hill, 55, blacked out while driving and landed upside down in a neighbor's pool; emergency services spoke to him through the watch and arrived within minutes (Western Mass News, 16 January 2025)", "outcome": "recurred", "source": "https://www.westernmassnews.com/2025/01/16/easthampton-man-credits-apple-watch-helping-save-his-life/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0046", "title": "RFdiffusion-designed scaffolds let an unaffiliated group solve four small-protein cryo-EM structures", "summary": "A Shandong University team used RFdiffusion and ProteinMPNN scaffolds in a trimbody fiducial to solve four small-protein structures at 2.29 to 2.62 angstroms.", "date_observed": "2026-02-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "RFdiffusion is a generative model of protein backbones from the University of Washington Institute for Protein Design. It was published in Nature on 11 July 2023 with experimental validation. That validation included a 2.9 angstrom cryo-EM structure of a designed binder-haemagglutinin complex. The structure matched the computational design model to 0.63 angstrom r.m.s.d. On 24 February 2026 an unaffiliated group at Shandong University and collaborating institutes reported in Nature Communications. They used RFdiffusion and ProteinMPNN to design rigid helical-bundle and TAIL domains for a trimbody fiducial. They then determined atomic-resolution cryo-EM structures of four small proteins that are normally intractable. Human Galectin10 came out at 2.62 angstroms and Aequorea coerulescens GFP at 2.29 angstroms. The Nectin4 IgV domain came out at 2.43 angstroms and Escherichia coli LacY at 2.50 angstroms.", "category": "benefit created", "unexpected": false, "purpose": "Generate de novo protein backbones to order, here to build rigid scaffolds that hold a small target protein still for cryo-electron microscopy.", "system": "RFdiffusion (generative protein backbone diffusion model) with ProteinMPNN sequence design", "model_version": "RFdiffusion", "developer": "University of Washington Institute for Protein Design (Baker lab)", "deployer": "Shandong University and collaborating institutes", "location": "Jinan, China", "domain": "Structural biology / de novo protein design", "segment": null, "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The deploying group obtained a reusable fiducial. It yielded four structures between 2.29 and 2.62 angstroms, for proteins that are otherwise difficult targets for cryo-EM." }, { "group": "societal", "depth": 1, "reason": "A methodological advance for structural biology with no identified downstream beneficiaries reported in the source." } ], "ai_role": { "status": "assessed", "statement": "RFdiffusion and ProteinMPNN produced the de novo scaffold domains that make the assembly rigid. The deploying authors are not the tool's developers. They validated the designs experimentally by determining cryo-EM structures at atomic resolution. The designs originated with the deploying group, which used the publicly released model." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Watson JL, Juergens D, Bennett NR, et al. (2023). De novo design of protein structure and function with RFdiffusion. Nature.", "title": "De novo design of protein structure and function with RFdiffusion", "url": "https://www.nature.com/articles/s41586-023-06415-8", "date": "2023-07-11", "written_by": "makers", "quote": "a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design" }, { "kind": "peer-reviewed study", "citation": "Song J, et al. (2026). Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins. Nat Commun.", "title": "Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins", "url": "https://europepmc.org/article/PMC/PMC13043659", "date": "2026-02-24", "written_by": "deployer", "quote": "The de novo 3-helix bundle (H3) and TAIL domains, engineered via RFdiffusion and ProteinMPNN, stabilize the interactions between Nbs and the scaffold" } ], "replication": { "produced_by": [ "Publicly released RFdiffusion and ProteinMPNN models", "A nanobody against each target and a rigid trimbody scaffold design", "Cryo-EM data collection and processing by the deploying group" ], "must_hold": [ "Publicly released RFdiffusion and ProteinMPNN weights", "A nanobody against the target protein", "Cryo-EM data collection and processing capability" ], "echoes": [] }, "paired_incident": null, "headline": "RFdiffusion scaffolds help solve four small-protein structures", "metric": "four small-protein structures at 2.29 to 2.62 angstroms", "comparator": { "against": "earlier DARPin-containing cage fiducials for small proteins", "before": "determined the structure of the cargo protein (GFP) at a local resolution of 3.8 Å but failed to provide a reliable atomic interpretation", "after": "Aequorea coerulescens GFP (2.29 Å)", "basis": "measured", "quote": "The earlier version of the DARPin-containing cage, T33-21, determined the structure of the cargo protein (GFP) at a local resolution of 3.8 Å but failed to provide a reliable atomic interpretation due to the flexibility of the single-helix linker between DARPin and scaffold.", "url": "https://europepmc.org/article/PMC/PMC13043659" }, "later": { "status": "unknown", "date": null, "note": "No later development found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Replaced the conflated cryo-EM figure in the account with the paper's own two numbers, a 2.9 angstrom map of the designed binder-haemagglutinin complex and a 0.63 angstrom r.m.s.d. to the design model, because the record had presented 0.63 angstroms as a map resolution.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10468394/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/article/PMC/PMC13043659", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.ipd.uw.edu/contact/; https://en.wikipedia.org/wiki/Shandong_University", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' peer-reviewed study and the deployer's peer-reviewed study. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0046", "catalog_version": "1.0.0", "source_fingerprint": "73274245993280a620b4d80fd36be8f2f11cf593827d16f3c4faa7aef8e7893c", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0046-source-0001", "AIBD-0046-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "University of Washington Institute for Protein Design (Baker lab)", "deployer": "Shandong University and collaborating institutes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "RFdiffusion and ProteinMPNN produced the de novo scaffold domains that make the assembly rigid. 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(2023). De novo design of protein structure and function with RFdiffusion. Nature.", "title": "De novo design of protein structure and function with RFdiffusion", "url": "https://www.nature.com/articles/s41586-023-06415-8", "date": "2023-07-11", "written_by": "makers", "quote": "a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design" }, { "kind": "peer-reviewed study", "citation": "Song J, et al. (2026). Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins. Nat Commun.", "title": "Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins", "url": "https://europepmc.org/article/PMC/PMC13043659", "date": "2026-02-24", "written_by": "deployer", "quote": "The de novo 3-helix bundle (H3) and TAIL domains, engineered via RFdiffusion and ProteinMPNN, stabilize the interactions between Nbs and the scaffold" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0046-source-0001", "AIBD-0046-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Watson JL, Juergens D, Bennett NR, et al. (2023). De novo design of protein structure and function with RFdiffusion. Nature.", "title": "De novo design of protein structure and function with RFdiffusion", "url": "https://www.nature.com/articles/s41586-023-06415-8", "date": "2023-07-11", "written_by": "makers", "quote": "a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design" }, { "kind": "peer-reviewed study", "citation": "Song J, et al. (2026). Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins. Nat Commun.", "title": "Trimbody with rigid AI-designed scaffolds enables atomic-resolution cryo-EM structure determination of small proteins", "url": "https://europepmc.org/article/PMC/PMC13043659", "date": "2026-02-24", "written_by": "deployer", "quote": "The de novo 3-helix bundle (H3) and TAIL domains, engineered via RFdiffusion and ProteinMPNN, stabilize the interactions between Nbs and the scaffold" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Shandong University team used RFdiffusion and ProteinMPNN scaffolds in a trimbody fiducial to solve four small-protein structures at 2.29 to 2.62 angstroms.", "account": "RFdiffusion is a generative model of protein backbones from the University of Washington Institute for Protein Design. It was published in Nature on 11 July 2023 with experimental validation. That validation included a 2.9 angstrom cryo-EM structure of a designed binder-haemagglutinin complex. The structure matched the computational design model to 0.63 angstrom r.m.s.d. On 24 February 2026 an unaffiliated group at Shandong University and collaborating institutes reported in Nature Communications. They used RFdiffusion and ProteinMPNN to design rigid helical-bundle and TAIL domains for a trimbody fiducial. They then determined atomic-resolution cryo-EM structures of four small proteins that are normally intractable. Human Galectin10 came out at 2.62 angstroms and Aequorea coerulescens GFP at 2.29 angstroms. The Nectin4 IgV domain came out at 2.43 angstroms and Escherichia coli LacY at 2.50 angstroms." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "RFdiffusion generated protein backbones, and ProteinMPNN generated amino-acid sequences." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "RFdiffusion designs protein backbones, and ProteinMPNN designs their amino-acid sequences." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "RFdiffusion" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "RFdiffusion (generative protein backbone diffusion model) with ProteinMPNN sequence design" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "University of Washington Institute for Protein Design (Baker lab)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "RFdiffusion-designed scaffolds let an unaffiliated group solve four small-protein cryo-EM structures", "headline": "RFdiffusion scaffolds help solve four small-protein structures" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "73274245993280a620b4d80fd36be8f2f11cf593827d16f3c4faa7aef8e7893c" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "RFdiffusion is a generative model of protein backbones from the University of Washington Institute for Protein Design. It was published in Nature on 11 July 2023 with experimental validation. That validation included a 2.9 angstrom cryo-EM structure of a designed binder-haemagglutinin complex. The structure matched the computational design model to 0.63 angstrom r.m.s.d. On 24 February 2026 an unaffiliated group at Shandong University and collaborating institutes reported in Nature Communications. They used RFdiffusion and ProteinMPNN to design rigid helical-bundle and TAIL domains for a trimbody fiducial. They then determined atomic-resolution cryo-EM structures of four small proteins that are normally intractable. Human Galectin10 came out at 2.62 angstroms and Aequorea coerulescens GFP at 2.29 angstroms. The Nectin4 IgV domain came out at 2.43 angstroms and Escherichia coli LacY at 2.50 angstroms.", "replication": { "produced_by": [ "Publicly released RFdiffusion and ProteinMPNN models", "A nanobody against each target and a rigid trimbody scaffold design", "Cryo-EM data collection and processing by the deploying group" ], "must_hold": [ "Publicly released RFdiffusion and ProteinMPNN weights", "A nanobody against the target protein", "Cryo-EM data collection and processing capability" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0327", "title": "Israel's Iron Beam laser may have made its first combat interception, of a Hezbollah drone, in footage of 2 March 2026", "summary": "Ynet and JPost (2 March 2026) call the video unconfirmed; Times of Israel (27 Mar, 30 June 2026) quotes officials that Iron Beam “has not yet been declared operational”. No cited source calls it AI.", "date_observed": "2026-03-02", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry says that Israel “deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages”. It separately bundles a Hankyoreh item (dated 10 October 2023) on Hamas rockets penetrating Iron Dome. The Iron Beam claim rests on social-media footage from Monday 2 March 2026, not 28 February. Ynet (Yair Kraus) reports that the footage “appeared to show the first operational use” of the system. It was delivered to the Israeli Air Force in late December 2025. Hezbollah fired rockets and drones from Lebanon after the killing of Iran's Supreme Leader, with one drone intercepted near Shlomi. The Jerusalem Post (Seth Frantzman, 2 March 2026) says that the circulated video “did not show lasers intercepting rockets”. TimesNow (2 March 2026) says that whether this was Iron Beam's first combat use “awaits official confirmation”. Army Recognition (3 March 2026) says that officials “have not formally confirmed the specific engagements” and that no authoritative combat log names the system. The Conversation (4 March 2026) calls the reports unconfirmed. Moneycontrol (3 March 2026) sources its “first-ever use” to an “Israel War Room” social-media video. The Times of Israel reports the Defense Ministry's handover of the first operational system on 28 December 2025, after tests against rockets, mortars and drones. Times of Israel/AFP (16 March 2026) reports that the IDF “has so far refused to comment on its use during the ongoing war”. Times of Israel (Stav Levaton, 27 March 2026) reports that “military officials said it has not yet been declared operational within the IDF”. Times of Israel (Emanuel Fabian, 30 June 2026) reports that the one deployed system “has seen limited use and has not yet been declared operational within the IDF”. A senior officer called its coverage partial. The only confirmed laser combat use is aggregate and earlier. A lower-powered, shorter-range variant shot down some 35 drones from Lebanon in 2024 (Times of Israel/AFP). The Ministry of Defense announced it in May 2025 (JPost). The MoD said that no Iron Beam components were involved (Wikipedia). No cited source describes Iron Beam as an AI system. The only AI mention found is Rafael's CEO framing machine learning as a future capability (Breaking Defense, 22 October 2025). That piece is not among the sources. Metro, Economic Times, MoneyControl's second item, Hankyoreh and others among the Monitor's 20 listed sources are syndications or explainers.", "category": "harm prevented", "unexpected": false, "purpose": "Iron Beam is a high-energy laser built to intercept rockets, mortars and drones at short range. It is a low-cost complement to Iron Dome, David's Sling and Arrow. Interception of Hezbollah projectiles is its stated purpose.", "system": "Iron Beam ('Or Eitan') 100 kW-class high-energy laser air-defense system by Rafael Advanced Defense Systems, with beam director and electro-optical targeting; the Monitor calls it 'AI-enabled', which no cited source supports", "model_version": null, "developer": "Rafael Advanced Defense Systems with the Israel Ministry of Defense (Lockheed Martin collaboration for the US market, per Wikipedia)", "deployer": "Israeli Air Force air-defense array; first operational system delivered 28 December 2025", "location": "Northern Israel near the Lebanese border (Shlomi area reported), Israel", "domain": "Defense: air defense", "segment": "Directed-energy interception of rockets, mortars and drones", "benefit_type": "Reduced Violence", "taxonomy_note": "An intercepted drone or rockets are read as a physically harmful incident averted; no defense type exists.", "registry_ids": { "oecd_aim": "2026-02-28-d62f" }, "ratings": [ { "group": "societal", "depth": null, "reason": "Ynet reports that one drone was intercepted and no injuries occurred in the 2 March 2026 launches. No official source attributes any interception to Iron Beam." }, { "group": "organizational", "depth": null, "reason": "The IDF has not confirmed use. Officials told Times of Israel that the one deployed system had limited use and partial coverage. It had no operational declaration as of June 2026." } ], "ai_role": { "status": "unassessed", "statement": "No cited source describes Iron Beam as an AI or machine-learning system. Those sources are Ynet, JPost, Army Recognition, TimesNow, The Conversation and Moneycontrol. They also include Times of Israel 28 December 2025, 16 Mar, 27 Mar and 30 June 2026, and Wikipedia. They describe a high-power laser with a beam director and electro-optical targeting. The Monitor's “AI-enabled” label is its own. Rafael's CEO described machine learning as a future capability (Breaking Defense, 22 October 2025). The IDF has not confirmed the engagement itself, so neither an AI role nor a contribution can be assessed." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2026-02-28-d62f, 'AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense' (AI-generated summary).", "title": "AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense", "url": "https://oecd.ai/en/incidents/2026-02-28-d62f", "date": "2026-02-28", "written_by": "independent", "quote": "Israel deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages" }, { "kind": "news report", "citation": "Ynetnews (Yair Kraus), 2 March 2026, 'Video appears to show first combat use of Israel's Iron Beam laser defense system'.", "title": "Video appears to show first combat use of Israel’s Iron Beam laser defense system", "url": "https://www.ynetnews.com/article/h13axdmfwx", "date": "2026-03-02", "written_by": "independent", "quote": "Footage circulating on social media early Monday appeared to show the first operational use of the new Iron Beam laser air defense system" }, { "kind": "news report", "citation": "The Jerusalem Post (Seth J. Frantzman), 2 March 2026, 'Israel's Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis'.", "title": "Israel’s Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis", "url": "https://www.jpost.com/israel-news/defense-news/article-888515", "date": "2026-03-02", "written_by": "independent", "quote": "The video did not show lasers intercepting rockets, but the mass interest in the new technology is clear." }, { "kind": "news report", "citation": "Army Recognition, 3 March 2026, 'Israel's Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon'.", "title": "Israel’s Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon", "url": "https://www.armyrecognition.com/news/army-news/2026/israels-iron-beam-laser-linked-to-first-combat-intercepts-of-hezbollah-rockets-in-lebanon", "date": "2026-03-03", "written_by": "independent", "quote": "Israeli authorities have not released an authoritative combat log explicitly naming the system." }, { "kind": "news report", "citation": "Times Now, 2 March 2026, 'Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far'.", "title": "Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far", "url": "https://www.timesnownews.com/world/middle-east/did-israel-debut-their-iron-beam-defence-system-to-intercept-missiles-fired-by-hezbollah-what-we-know-so-far-article-153731169", "date": "2026-03-02", "written_by": "independent", "quote": "Whether this constitutes Iron Beam’s definitive first combat use awaits official confirmation." }, { "kind": "news report", "citation": "The Conversation, 4 March 2026, 'Israel's 'Iron Beam': why laser weapons are no longer science fiction'.", "title": "Israel’s ‘Iron Beam’: why laser weapons are no longer science fiction", "url": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "date": "2026-03-04", "written_by": "independent", "quote": "While the reports are unconfirmed, video circulating on social media appears to show rockets being destroyed within moments of launching without visible intervention" }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton and Emanuel Fabian), 28 December 2025, 'Defense Ministry hands IDF first combat-ready Iron Beam laser interception system'.", "title": "Defense Ministry hands IDF first combat-ready Iron Beam laser interception system", "url": "https://www.timesofisrael.com/defense-ministry-hands-idf-first-combat-ready-iron-beam-laser-interception-system/", "date": "2025-12-28", "written_by": "independent", "quote": "has successfully intercepted rockets, mortar shells and drones during extensive testing" }, { "kind": "news report", "citation": "The Times of Israel / AFP, 16 March 2026, 'Surge in drone attacks sharpens focus on laser defense'.", "title": "Surge in drone attacks sharpens focus on laser defense", "url": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/", "date": "2026-03-16", "written_by": "independent", "quote": "The IDF received the system in December, but has so far refused to comment on its use during the ongoing war with Iran and its Lebanese terror proxy Hezbollah." }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton), 27 March 2026, 'Cheap and elusive drones put incessant pressure on Israel's evolving air defenses'.", "title": "Cheap and elusive drones put incessant pressure on Israel’s evolving air defenses", "url": "https://www.timesofisrael.com/cheap-and-elusive-drones-put-incessant-pressure-on-israels-evolving-air-defenses/", "date": "2026-03-27", "written_by": "independent", "quote": "While the Defense Ministry said the system became operational in late 2025, military officials said it has not yet been declared operational within the IDF." }, { "kind": "news report", "citation": "The Times of Israel (Emanuel Fabian), 30 June 2026, 'Iron Dome air defenses upgraded, 'incorporating lessons learned' from Iran war'.", "title": "Iron Dome air defenses upgraded, ‘incorporating lessons learned’ from Iran war", "url": "https://www.timesofisrael.com/iron-dome-air-defenses-upgraded-incorporating-lessons-learned-from-iran-war/", "date": "2026-06-30", "written_by": "independent", "quote": "But while the military has deployed one Iron Beam system, it has seen limited use and has not yet been declared operational within the IDF." }, { "kind": "other", "citation": "Wikipedia, 'Iron Beam', accessed 20 October 2026 (on Rafael's 28 May 2025 announcement of 2024 laser interceptions).", "title": "Iron Beam", "url": "https://en.wikipedia.org/wiki/Iron_Beam", "date": null, "written_by": "independent", "quote": "MOD said that no Iron Beam components were involved" }, { "kind": "news report", "citation": "Hankyoreh (English edition), 10 October 2023, '$600 rockets shatter Israel's Iron Dome - will Seoul's skies be safe?' (the Monitor's bundled Iron Dome item; it predates and does not concern Iron Beam).", "title": "$600 rockets shatter Israel’s Iron Dome – will Seoul’s skies be safe?", "url": "https://english.hani.co.kr/arti/english_edition/e_international/1111552.html", "date": "2023-10-10", "written_by": "independent", "quote": "Many of the rockets fired by Hamas penetrated Israel’s low-altitude air defense system, known as the Iron Dome, and struck Israel." } ], "replication": { "produced_by": [ "A ground-based high-energy laser that holds its beam on a short-range target within line of sight until it is destroyed. JPost describes the terrain, weather and dwell-time limits", "Integration into the Israeli Air Force's layered air-defense array as a complement to Iron Dome" ], "must_hold": [ "IDF confirmation that Iron Beam, not Iron Dome, other interceptors or counter-UAS effects, made the 2 March 2026 interception", "Line of sight and clear weather. A senior officer said in May 2026 that the system's coverage is partial and that at least 14 batteries are sought" ], "echoes": [ { "date": null, "setting": "2024 conflict with Hezbollah, northern Israel: a lower-powered, shorter-range laser variant shot down some 35 drones (Times of Israel/AFP), announced by the Ministry of Defense in May 2025 (JPost); the MoD said no Iron Beam components were involved (Wikipedia)", "model_version": "lower-powered variant (Lite Beam or Iron Beam-M, per Wikipedia's account of Israeli media)", "outcome": "recurred", "source": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/" } ] }, "paired_incident": null, "headline": "Iron Beam may have made its first combat interception", "metric": "one drone intercepted near Shlomi", "comparator": { "against": "Iron Dome interceptor missiles", "before": "A single Iron Dome interceptor missile costs about US$50,000", "after": "each shot cost around $US3.50, and more recent estimates suggest the cost may now have fallen as low as US$2.50 per shot", "basis": "assumed", "quote": "A single Iron Dome interceptor missile costs about US$50,000 – which means the costs add up quickly when defending against large or frequent attacks. Firing the Iron Beam laser costs a lot less. In 2022, Israel’s then prime minister Naftali Bennett said each shot cost around $US3.50, and more recent estimates suggest the cost may now have fallen as low as US$2.50 per shot.", "url": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390" }, "later": null, "value": null, "developer_country": "Israel", "deployer_country": "Israel", "unrated_because": "the IDF has not confirmed use, and no source calls it AI", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the IDF has not confirmed use, and no source calls it AI.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Israeli_Air_Defense_Command", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: ten independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0327", "catalog_version": "1.0.0", "source_fingerprint": "cd4d27d77be41530edf2699ac8a2ccef212aaef7026277623e8af020144da5b5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0327-source-0001", "AIBD-0327-source-0002", "AIBD-0327-source-0003", "AIBD-0327-source-0004", "AIBD-0327-source-0005", "AIBD-0327-source-0006", "AIBD-0327-source-0007", "AIBD-0327-source-0008", "AIBD-0327-source-0009", "AIBD-0327-source-0010", "AIBD-0327-source-0011", "AIBD-0327-source-0012" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Rafael Advanced Defense Systems with the Israel Ministry of Defense (Lockheed Martin collaboration for the US market, per Wikipedia)", "deployer": "Israeli Air Force air-defense array; first operational system delivered 28 December 2025" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "unassessed", "statement": "No cited source describes Iron Beam as an AI or machine-learning system. Those sources are Ynet, JPost, Army Recognition, TimesNow, The Conversation and Moneycontrol. They also include Times of Israel 28 December 2025, 16 Mar, 27 Mar and 30 June 2026, and Wikipedia. They describe a high-power laser with a beam director and electro-optical targeting. The Monitor's “AI-enabled” label is its own. Rafael's CEO described machine learning as a future capability (Breaking Defense, 22 October 2025). The IDF has not confirmed the engagement itself, so neither an AI role nor a contribution can be assessed." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: ten independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Ynet reports that one drone was intercepted and no injuries occurred in the 2 March 2026 launches. No official source attributes any interception to Iron Beam." }, { "group": "organizational", "reason": "The IDF has not confirmed use. Officials told Times of Israel that the one deployed system had limited use and partial coverage. It had no operational declaration as of June 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Ynet reports that one drone was intercepted and no injuries occurred in the 2 March 2026 launches. No official source attributes any interception to Iron Beam." }, { "group": "organizational", "reason": "The IDF has not confirmed use. Officials told Times of Israel that the one deployed system had limited use and partial coverage. It had no operational declaration as of June 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "one drone intercepted near Shlomi", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-02-28-d62f" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0327" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence", "taxonomy_note": "An intercepted drone or rockets are read as a physically harmful incident averted; no defense type exists." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry says that Israel “deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages”. It separately bundles a Hankyoreh item (dated 10 October 2023) on Hamas rockets penetrating Iron Dome. The Iron Beam claim rests on social-media footage from Monday 2 March 2026, not 28 February. Ynet (Yair Kraus) reports that the footage “appeared to show the first operational use” of the system. It was delivered to the Israeli Air Force in late December 2025. Hezbollah fired rockets and drones from Lebanon after the killing of Iran's Supreme Leader, with one drone intercepted near Shlomi. The Jerusalem Post (Seth Frantzman, 2 March 2026) says that the circulated video “did not show lasers intercepting rockets”. TimesNow (2 March 2026) says that whether this was Iron Beam's first combat use “awaits official confirmation”. Army Recognition (3 March 2026) says that officials “have not formally confirmed the specific engagements” and that no authoritative combat log names the system. The Conversation (4 March 2026) calls the reports unconfirmed. Moneycontrol (3 March 2026) sources its “first-ever use” to an “Israel War Room” social-media video. The Times of Israel reports the Defense Ministry's handover of the first operational system on 28 December 2025, after tests against rockets, mortars and drones. Times of Israel/AFP (16 March 2026) reports that the IDF “has so far refused to comment on its use during the ongoing war”. Times of Israel (Stav Levaton, 27 March 2026) reports that “military officials said it has not yet been declared operational within the IDF”. Times of Israel (Emanuel Fabian, 30 June 2026) reports that the one deployed system “has seen limited use and has not yet been declared operational within the IDF”. A senior officer called its coverage partial. The only confirmed laser combat use is aggregate and earlier. A lower-powered, shorter-range variant shot down some 35 drones from Lebanon in 2024 (Times of Israel/AFP). The Ministry of Defense announced it in May 2025 (JPost). The MoD said that no Iron Beam components were involved (Wikipedia). No cited source describes Iron Beam as an AI system. The only AI mention found is Rafael's CEO framing machine learning as a future capability (Breaking Defense, 22 October 2025). That piece is not among the sources. Metro, Economic Times, MoneyControl's second item, Hankyoreh and others among the Monitor's 20 listed sources are syndications or explainers.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "Ynet reports that one drone was intercepted and no injuries occurred in the 2 March 2026 launches. No official source attributes any interception to Iron Beam." }, { "group": "organizational", "reason": "The IDF has not confirmed use. Officials told Times of Israel that the one deployed system had limited use and partial coverage. It had no operational declaration as of June 2026." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Iron Beam is a high-energy laser built to intercept rockets, mortars and drones at short range. It is a low-cost complement to Iron Dome, David's Sling and Arrow. Interception of Hezbollah projectiles is its stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Northern Israel near the Lebanese border (Shlomi area reported), Israel", "developer_country": "Israel", "deployer_country": "Israel" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Iron Beam is a high-energy laser built to intercept rockets, mortars and drones at short range. It is a low-cost complement to Iron Dome, David's Sling and Arrow. Interception of Hezbollah projectiles is its stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-02", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the IDF has not confirmed use, and no source calls it AI.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Israeli_Air_Defense_Command", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A ground-based high-energy laser that holds its beam on a short-range target within line of sight until it is destroyed. JPost describes the terrain, weather and dwell-time limits", "Integration into the Israeli Air Force's layered air-defense array as a complement to Iron Dome" ], "must_hold": [ "IDF confirmation that Iron Beam, not Iron Dome, other interceptors or counter-UAS effects, made the 2 March 2026 interception", "Line of sight and clear weather. A senior officer said in May 2026 that the system's coverage is partial and that at least 14 batteries are sought" ], "echoes": [ { "setting": "2024 conflict with Hezbollah, northern Israel: a lower-powered, shorter-range laser variant shot down some 35 drones (Times of Israel/AFP), announced by the Ministry of Defense in May 2025 (JPost); the MoD said no Iron Beam components were involved (Wikipedia)", "model_version": "lower-powered variant (Lite Beam or Iron Beam-M, per Wikipedia's account of Israeli media)", "outcome": "recurred", "source": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A ground-based high-energy laser that holds its beam on a short-range target within line of sight until it is destroyed. JPost describes the terrain, weather and dwell-time limits", "Integration into the Israeli Air Force's layered air-defense array as a complement to Iron Dome" ], "must_hold": [ "IDF confirmation that Iron Beam, not Iron Dome, other interceptors or counter-UAS effects, made the 2 March 2026 interception", "Line of sight and clear weather. A senior officer said in May 2026 that the system's coverage is partial and that at least 14 batteries are sought" ], "echoes": [ { "setting": "2024 conflict with Hezbollah, northern Israel: a lower-powered, shorter-range laser variant shot down some 35 drones (Times of Israel/AFP), announced by the Ministry of Defense in May 2025 (JPost); the MoD said no Iron Beam components were involved (Wikipedia)", "model_version": "lower-powered variant (Lite Beam or Iron Beam-M, per Wikipedia's account of Israeli media)", "outcome": "recurred", "source": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: the IDF has not confirmed use, and no source calls it AI.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Rafael_Advanced_Defense_Systems; https://en.wikipedia.org/wiki/Israeli_Air_Defense_Command", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Defense: air defense", "segment": "Directed-energy interception of rockets, mortars and drones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2026-02-28-d62f, 'AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense' (AI-generated summary).", "title": "AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense", "url": "https://oecd.ai/en/incidents/2026-02-28-d62f", "date": "2026-02-28", "written_by": "independent", "quote": "Israel deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages" }, { "kind": "news report", "citation": "Ynetnews (Yair Kraus), 2 March 2026, 'Video appears to show first combat use of Israel's Iron Beam laser defense system'.", "title": "Video appears to show first combat use of Israel’s Iron Beam laser defense system", "url": "https://www.ynetnews.com/article/h13axdmfwx", "date": "2026-03-02", "written_by": "independent", "quote": "Footage circulating on social media early Monday appeared to show the first operational use of the new Iron Beam laser air defense system" }, { "kind": "news report", "citation": "The Jerusalem Post (Seth J. Frantzman), 2 March 2026, 'Israel's Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis'.", "title": "Israel’s Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis", "url": "https://www.jpost.com/israel-news/defense-news/article-888515", "date": "2026-03-02", "written_by": "independent", "quote": "The video did not show lasers intercepting rockets, but the mass interest in the new technology is clear." }, { "kind": "news report", "citation": "Army Recognition, 3 March 2026, 'Israel's Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon'.", "title": "Israel’s Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon", "url": "https://www.armyrecognition.com/news/army-news/2026/israels-iron-beam-laser-linked-to-first-combat-intercepts-of-hezbollah-rockets-in-lebanon", "date": "2026-03-03", "written_by": "independent", "quote": "Israeli authorities have not released an authoritative combat log explicitly naming the system." }, { "kind": "news report", "citation": "Times Now, 2 March 2026, 'Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far'.", "title": "Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far", "url": "https://www.timesnownews.com/world/middle-east/did-israel-debut-their-iron-beam-defence-system-to-intercept-missiles-fired-by-hezbollah-what-we-know-so-far-article-153731169", "date": "2026-03-02", "written_by": "independent", "quote": "Whether this constitutes Iron Beam’s definitive first combat use awaits official confirmation." }, { "kind": "news report", "citation": "The Conversation, 4 March 2026, 'Israel's 'Iron Beam': why laser weapons are no longer science fiction'.", "title": "Israel’s ‘Iron Beam’: why laser weapons are no longer science fiction", "url": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "date": "2026-03-04", "written_by": "independent", "quote": "While the reports are unconfirmed, video circulating on social media appears to show rockets being destroyed within moments of launching without visible intervention" }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton and Emanuel Fabian), 28 December 2025, 'Defense Ministry hands IDF first combat-ready Iron Beam laser interception system'.", "title": "Defense Ministry hands IDF first combat-ready Iron Beam laser interception system", "url": "https://www.timesofisrael.com/defense-ministry-hands-idf-first-combat-ready-iron-beam-laser-interception-system/", "date": "2025-12-28", "written_by": "independent", "quote": "has successfully intercepted rockets, mortar shells and drones during extensive testing" }, { "kind": "news report", "citation": "The Times of Israel / AFP, 16 March 2026, 'Surge in drone attacks sharpens focus on laser defense'.", "title": "Surge in drone attacks sharpens focus on laser defense", "url": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/", "date": "2026-03-16", "written_by": "independent", "quote": "The IDF received the system in December, but has so far refused to comment on its use during the ongoing war with Iran and its Lebanese terror proxy Hezbollah." }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton), 27 March 2026, 'Cheap and elusive drones put incessant pressure on Israel's evolving air defenses'.", "title": "Cheap and elusive drones put incessant pressure on Israel’s evolving air defenses", "url": "https://www.timesofisrael.com/cheap-and-elusive-drones-put-incessant-pressure-on-israels-evolving-air-defenses/", "date": "2026-03-27", "written_by": "independent", "quote": "While the Defense Ministry said the system became operational in late 2025, military officials said it has not yet been declared operational within the IDF." }, { "kind": "news report", "citation": "The Times of Israel (Emanuel Fabian), 30 June 2026, 'Iron Dome air defenses upgraded, 'incorporating lessons learned' from Iran war'.", "title": "Iron Dome air defenses upgraded, ‘incorporating lessons learned’ from Iran war", "url": "https://www.timesofisrael.com/iron-dome-air-defenses-upgraded-incorporating-lessons-learned-from-iran-war/", "date": "2026-06-30", "written_by": "independent", "quote": "But while the military has deployed one Iron Beam system, it has seen limited use and has not yet been declared operational within the IDF." }, { "kind": "other", "citation": "Wikipedia, 'Iron Beam', accessed 20 October 2026 (on Rafael's 28 May 2025 announcement of 2024 laser interceptions).", "title": "Iron Beam", "url": "https://en.wikipedia.org/wiki/Iron_Beam", "written_by": "independent", "quote": "MOD said that no Iron Beam components were involved" }, { "kind": "news report", "citation": "Hankyoreh (English edition), 10 October 2023, '$600 rockets shatter Israel's Iron Dome - will Seoul's skies be safe?' (the Monitor's bundled Iron Dome item; it predates and does not concern Iron Beam).", "title": "$600 rockets shatter Israel’s Iron Dome – will Seoul’s skies be safe?", "url": "https://english.hani.co.kr/arti/english_edition/e_international/1111552.html", "date": "2023-10-10", "written_by": "independent", "quote": "Many of the rockets fired by Hamas penetrated Israel’s low-altitude air defense system, known as the Iron Dome, and struck Israel." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0327-source-0001", "AIBD-0327-source-0002", "AIBD-0327-source-0003", "AIBD-0327-source-0004", "AIBD-0327-source-0005", "AIBD-0327-source-0006", "AIBD-0327-source-0007", "AIBD-0327-source-0008", "AIBD-0327-source-0009", "AIBD-0327-source-0010", "AIBD-0327-source-0011", "AIBD-0327-source-0012" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2026-02-28-d62f, 'AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense' (AI-generated summary).", "title": "AI-Enabled Iron Beam and Iron Dome Systems Deployed in Israeli Defense", "url": "https://oecd.ai/en/incidents/2026-02-28-d62f", "date": "2026-02-28", "written_by": "independent", "quote": "Israel deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages" }, { "kind": "news report", "citation": "Ynetnews (Yair Kraus), 2 March 2026, 'Video appears to show first combat use of Israel's Iron Beam laser defense system'.", "title": "Video appears to show first combat use of Israel’s Iron Beam laser defense system", "url": "https://www.ynetnews.com/article/h13axdmfwx", "date": "2026-03-02", "written_by": "independent", "quote": "Footage circulating on social media early Monday appeared to show the first operational use of the new Iron Beam laser air defense system" }, { "kind": "news report", "citation": "The Jerusalem Post (Seth J. Frantzman), 2 March 2026, 'Israel's Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis'.", "title": "Israel’s Iron Beam laser: What can it do, and was it used against missiles from Lebanon? - analysis", "url": "https://www.jpost.com/israel-news/defense-news/article-888515", "date": "2026-03-02", "written_by": "independent", "quote": "The video did not show lasers intercepting rockets, but the mass interest in the new technology is clear." }, { "kind": "news report", "citation": "Army Recognition, 3 March 2026, 'Israel's Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon'.", "title": "Israel’s Iron Beam Laser Linked to First Combat Intercepts of Hezbollah Rockets in Lebanon", "url": "https://www.armyrecognition.com/news/army-news/2026/israels-iron-beam-laser-linked-to-first-combat-intercepts-of-hezbollah-rockets-in-lebanon", "date": "2026-03-03", "written_by": "independent", "quote": "Israeli authorities have not released an authoritative combat log explicitly naming the system." }, { "kind": "news report", "citation": "Times Now, 2 March 2026, 'Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far'.", "title": "Did Israel Debut Their Iron Beam Defence System to Intercept Missiles Fired by Hezbollah? What We Know So Far", "url": "https://www.timesnownews.com/world/middle-east/did-israel-debut-their-iron-beam-defence-system-to-intercept-missiles-fired-by-hezbollah-what-we-know-so-far-article-153731169", "date": "2026-03-02", "written_by": "independent", "quote": "Whether this constitutes Iron Beam’s definitive first combat use awaits official confirmation." }, { "kind": "news report", "citation": "The Conversation, 4 March 2026, 'Israel's 'Iron Beam': why laser weapons are no longer science fiction'.", "title": "Israel’s ‘Iron Beam’: why laser weapons are no longer science fiction", "url": "http://theconversation.com/israels-iron-beam-why-laser-weapons-are-no-longer-science-fiction-277390", "date": "2026-03-04", "written_by": "independent", "quote": "While the reports are unconfirmed, video circulating on social media appears to show rockets being destroyed within moments of launching without visible intervention" }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton and Emanuel Fabian), 28 December 2025, 'Defense Ministry hands IDF first combat-ready Iron Beam laser interception system'.", "title": "Defense Ministry hands IDF first combat-ready Iron Beam laser interception system", "url": "https://www.timesofisrael.com/defense-ministry-hands-idf-first-combat-ready-iron-beam-laser-interception-system/", "date": "2025-12-28", "written_by": "independent", "quote": "has successfully intercepted rockets, mortar shells and drones during extensive testing" }, { "kind": "news report", "citation": "The Times of Israel / AFP, 16 March 2026, 'Surge in drone attacks sharpens focus on laser defense'.", "title": "Surge in drone attacks sharpens focus on laser defense", "url": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/", "date": "2026-03-16", "written_by": "independent", "quote": "The IDF received the system in December, but has so far refused to comment on its use during the ongoing war with Iran and its Lebanese terror proxy Hezbollah." }, { "kind": "news report", "citation": "The Times of Israel (Stav Levaton), 27 March 2026, 'Cheap and elusive drones put incessant pressure on Israel's evolving air defenses'.", "title": "Cheap and elusive drones put incessant pressure on Israel’s evolving air defenses", "url": "https://www.timesofisrael.com/cheap-and-elusive-drones-put-incessant-pressure-on-israels-evolving-air-defenses/", "date": "2026-03-27", "written_by": "independent", "quote": "While the Defense Ministry said the system became operational in late 2025, military officials said it has not yet been declared operational within the IDF." }, { "kind": "news report", "citation": "The Times of Israel (Emanuel Fabian), 30 June 2026, 'Iron Dome air defenses upgraded, 'incorporating lessons learned' from Iran war'.", "title": "Iron Dome air defenses upgraded, ‘incorporating lessons learned’ from Iran war", "url": "https://www.timesofisrael.com/iron-dome-air-defenses-upgraded-incorporating-lessons-learned-from-iran-war/", "date": "2026-06-30", "written_by": "independent", "quote": "But while the military has deployed one Iron Beam system, it has seen limited use and has not yet been declared operational within the IDF." }, { "kind": "other", "citation": "Wikipedia, 'Iron Beam', accessed 20 October 2026 (on Rafael's 28 May 2025 announcement of 2024 laser interceptions).", "title": "Iron Beam", "url": "https://en.wikipedia.org/wiki/Iron_Beam", "written_by": "independent", "quote": "MOD said that no Iron Beam components were involved" }, { "kind": "news report", "citation": "Hankyoreh (English edition), 10 October 2023, '$600 rockets shatter Israel's Iron Dome - will Seoul's skies be safe?' (the Monitor's bundled Iron Dome item; it predates and does not concern Iron Beam).", "title": "$600 rockets shatter Israel’s Iron Dome – will Seoul’s skies be safe?", "url": "https://english.hani.co.kr/arti/english_edition/e_international/1111552.html", "date": "2023-10-10", "written_by": "independent", "quote": "Many of the rockets fired by Hamas penetrated Israel’s low-altitude air defense system, known as the Iron Dome, and struck Israel." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Ynet and JPost (2 March 2026) call the video unconfirmed; Times of Israel (27 Mar, 30 June 2026) quotes officials that Iron Beam “has not yet been declared operational”. No cited source calls it AI.", "account": "The OECD AI Incidents entry says that Israel “deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages”. It separately bundles a Hankyoreh item (dated 10 October 2023) on Hamas rockets penetrating Iron Dome. The Iron Beam claim rests on social-media footage from Monday 2 March 2026, not 28 February. Ynet (Yair Kraus) reports that the footage “appeared to show the first operational use” of the system. It was delivered to the Israeli Air Force in late December 2025. Hezbollah fired rockets and drones from Lebanon after the killing of Iran's Supreme Leader, with one drone intercepted near Shlomi. The Jerusalem Post (Seth Frantzman, 2 March 2026) says that the circulated video “did not show lasers intercepting rockets”. TimesNow (2 March 2026) says that whether this was Iron Beam's first combat use “awaits official confirmation”. Army Recognition (3 March 2026) says that officials “have not formally confirmed the specific engagements” and that no authoritative combat log names the system. The Conversation (4 March 2026) calls the reports unconfirmed. Moneycontrol (3 March 2026) sources its “first-ever use” to an “Israel War Room” social-media video. The Times of Israel reports the Defense Ministry's handover of the first operational system on 28 December 2025, after tests against rockets, mortars and drones. Times of Israel/AFP (16 March 2026) reports that the IDF “has so far refused to comment on its use during the ongoing war”. Times of Israel (Stav Levaton, 27 March 2026) reports that “military officials said it has not yet been declared operational within the IDF”. Times of Israel (Emanuel Fabian, 30 June 2026) reports that the one deployed system “has seen limited use and has not yet been declared operational within the IDF”. A senior officer called its coverage partial. The only confirmed laser combat use is aggregate and earlier. A lower-powered, shorter-range variant shot down some 35 drones from Lebanon in 2024 (Times of Israel/AFP). The Ministry of Defense announced it in May 2025 (JPost). The MoD said that no Iron Beam components were involved (Wikipedia). No cited source describes Iron Beam as an AI system. The only AI mention found is Rafael's CEO framing machine learning as a future capability (Breaking Defense, 22 October 2025). That piece is not among the sources. Metro, Economic Times, MoneyControl's second item, Hankyoreh and others among the Monitor's 20 listed sources are syndications or explainers." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Iron Beam ('Or Eitan') 100 kW-class high-energy laser air-defense system by Rafael Advanced Defense Systems, with beam director and electro-optical targeting; the Monitor calls it 'AI-enabled', which no cited source supports" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rafael Advanced Defense Systems with the Israel Ministry of Defense (Lockheed Martin collaboration for the US market, per Wikipedia)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Israel's Iron Beam laser may have made its first combat interception, of a Hezbollah drone, in footage of 2 March 2026", "headline": "Iron Beam may have made its first combat interception" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cd4d27d77be41530edf2699ac8a2ccef212aaef7026277623e8af020144da5b5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry says that Israel “deployed its AI-powered Iron Beam laser defense system for the first time in combat to intercept Hezbollah missile barrages”. It separately bundles a Hankyoreh item (dated 10 October 2023) on Hamas rockets penetrating Iron Dome. The Iron Beam claim rests on social-media footage from Monday 2 March 2026, not 28 February. Ynet (Yair Kraus) reports that the footage “appeared to show the first operational use” of the system. It was delivered to the Israeli Air Force in late December 2025. Hezbollah fired rockets and drones from Lebanon after the killing of Iran's Supreme Leader, with one drone intercepted near Shlomi. The Jerusalem Post (Seth Frantzman, 2 March 2026) says that the circulated video “did not show lasers intercepting rockets”. TimesNow (2 March 2026) says that whether this was Iron Beam's first combat use “awaits official confirmation”. Army Recognition (3 March 2026) says that officials “have not formally confirmed the specific engagements” and that no authoritative combat log names the system. The Conversation (4 March 2026) calls the reports unconfirmed. Moneycontrol (3 March 2026) sources its “first-ever use” to an “Israel War Room” social-media video. The Times of Israel reports the Defense Ministry's handover of the first operational system on 28 December 2025, after tests against rockets, mortars and drones. Times of Israel/AFP (16 March 2026) reports that the IDF “has so far refused to comment on its use during the ongoing war”. Times of Israel (Stav Levaton, 27 March 2026) reports that “military officials said it has not yet been declared operational within the IDF”. Times of Israel (Emanuel Fabian, 30 June 2026) reports that the one deployed system “has seen limited use and has not yet been declared operational within the IDF”. A senior officer called its coverage partial. The only confirmed laser combat use is aggregate and earlier. A lower-powered, shorter-range variant shot down some 35 drones from Lebanon in 2024 (Times of Israel/AFP). The Ministry of Defense announced it in May 2025 (JPost). The MoD said that no Iron Beam components were involved (Wikipedia). No cited source describes Iron Beam as an AI system. The only AI mention found is Rafael's CEO framing machine learning as a future capability (Breaking Defense, 22 October 2025). That piece is not among the sources. Metro, Economic Times, MoneyControl's second item, Hankyoreh and others among the Monitor's 20 listed sources are syndications or explainers.", "replication": { "produced_by": [ "A ground-based high-energy laser that holds its beam on a short-range target within line of sight until it is destroyed. JPost describes the terrain, weather and dwell-time limits", "Integration into the Israeli Air Force's layered air-defense array as a complement to Iron Dome" ], "must_hold": [ "IDF confirmation that Iron Beam, not Iron Dome, other interceptors or counter-UAS effects, made the 2 March 2026 interception", "Line of sight and clear weather. A senior officer said in May 2026 that the system's coverage is partial and that at least 14 batteries are sought" ], "echoes": [ { "setting": "2024 conflict with Hezbollah, northern Israel: a lower-powered, shorter-range laser variant shot down some 35 drones (Times of Israel/AFP), announced by the Ministry of Defense in May 2025 (JPost); the MoD said no Iron Beam components were involved (Wikipedia)", "model_version": "lower-powered variant (Lite Beam or Iron Beam-M, per Wikipedia's account of Israeli media)", "outcome": "recurred", "source": "https://www.timesofisrael.com/surge-in-drone-attacks-sharpens-focus-on-laser-defense/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0206", "title": "Wiz Research's AI-augmented reverse engineering of GitHub's closed-source git binaries, with Claude Code and IDA MCP, finds a critical push-option injection giving remote code execution on GitHub.com and GitHub Enterprise Server; GitHub reproduces it in 40 minutes, patches github.com by 7:00 pm UTC on 4 March 2026 and finds no exploitation", "summary": "Wiz's AI-aided reverse engineering found a critical GitHub RCE (CVE-2026–3854); github.com was patched the same day, no exploitation found.", "date_observed": "2026-03-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 4 March 2026 Wiz Research reported a critical remote code execution (RCE) flaw to GitHub, later CVE-2026–3854. It sat in GitHub's internal git infrastructure. Git push options were not sanitized before being written into internal headers. Any authenticated user could therefore run arbitrary commands on GitHub's servers with a single git push. Wiz says AI-augmented tooling made the research feasible, particularly automated reverse engineering of GitHub's compiled binaries with IDA MCP. The Register reports that the team used Claude Code and went from idea to working exploit in under 48 hours. GitHub reproduced the bug within 40 minutes and deployed a fix to github.com at 7:00 pm UTC that day. It released GitHub Enterprise Server (GHES) patches from 10 March, and found no exploitation.", "category": "benefit created", "unexpected": false, "purpose": "Claude Code is Anthropic's agentic coding tool, built to read a codebase, edit files, run commands and connect to external tools over MCP. Wiz used it, with IDA MCP, to automate reverse engineering of GitHub's compiled binaries. Analyzing code for flaws is within that general purpose. The benefit was an application of what the tool was built to do rather than a departure from it.", "system": "AI-augmented reverse-engineering tooling used by Wiz Research: Claude Code (named by The Register and WebProNews) with IDA MCP for automated reverse engineering of GitHub's compiled binaries (named by Wiz), applied to GitHub.com's backend and GitHub Enterprise Server 3.19.1", "model_version": "Not named in the cited sources. Wiz's write-up credits 'AI-augmented tooling, particularly automated reverse engineering using IDA MCP' and does not name Claude. The Register and WebProNews name Claude Code.", "developer": "Anthropic (Claude Code); the maker of IDA MCP is not named in the sources", "deployer": "Wiz Research (Sagi Tzadik, Nir Ohfeld, Ronen Shustin, Hillai Ben-Sasson, Yuval Avrahami, Noam Malron)", "location": null, "domain": "Cybersecurity: vulnerability research and software supply chain", "segment": "Bug bounty research: AI-assisted reverse engineering of closed-source server binaries", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-04-28-f5d8" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "GitHub closed a critical remote code execution hole in its git push pipeline within hours of the report. The fix reached github.com at 7:00 pm UTC on 4 March 2026. GitHub also shipped patches for six GitHub Enterprise Server release lines. Wiz earned what GitHub calls one of the highest rewards in the history of its Bug Bounty program. The loss avoided is hypothetical. GitHub's forensic investigation found that no other account had triggered the code path. No customer data was accessed, modified or exfiltrated. The benefit is an exposure closed rather than a demonstrated loss prevented." } ], "ai_role": { "status": "assessed", "statement": "The AI's documented contribution is speed of analysis, on the researchers' own account. Wiz writes that AI-augmented reverse-engineering tooling, particularly IDA MCP, let it rapidly analyze GitHub's compiled binaries and reconstruct internal protocols. Wiz says that speed would not have been feasible manually. Sagi Tzadik told Dark Reading that with AI tools it took under 48 hours from idea to working exploit. The Register adds that the team used Claude Code “to take a lot of the legwork out of the process”. The hypothesis, the exploit, the report and the fix were human work. Six named Wiz researchers confirmed RCE on GHES 3.19.1 and wrote what GitHub called a thorough report. GitHub's security and engineering teams reproduced the bug within 40 minutes and deployed the fix. GitHub's own post, the CVE record and the GHES release notes describe a Bug Bounty report without mentioning AI. The AI-assistance claim therefore rests on Wiz and on outlets quoting Wiz. Wiz's write-up, in the text as read, names IDA MCP and not Claude." }, "evidence": [ { "kind": "report", "citation": "Wales A / GitHub (2026). Securing the git push pipeline: Responding to a critical remote code execution vulnerability. The GitHub Blog, 28 April 2026 (updated 29 April 2026).", "title": "Securing the git push pipeline: Responding to a critical remote code execution vulnerability", "url": "https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "date": "2026-04-28", "written_by": "beneficiary", "quote": "our engineering team developed and deployed a fix to github.com at 7:00 p.m. UTC that same day" }, { "kind": "other", "citation": "GitHub (CNA) (2026). CVE-2026-3854. CVE Program record, published 10 March 2026.", "title": "CVE-2026-3854", "url": "https://cveawg.mitre.org/api/cve/CVE-2026-3854", "date": "2026-03-10", "written_by": "beneficiary", "quote": "allowed an attacker with push access to a repository to achieve remote code execution on the instance" }, { "kind": "other", "citation": "GitHub (2026). GitHub Enterprise Server 3.14 release notes, 3.14.25, 12 March 2026. GitHub Docs.", "title": "GitHub Enterprise Server 3.14 release notes (3.14.25)", "url": "https://docs.github.com/en/enterprise-server@3.14/admin/release-notes", "date": "2026-03-12", "written_by": "beneficiary", "quote": "GitHub has requested CVE ID CVE-2026-3854 for this vulnerability, which was reported via the GitHub Bug Bounty program." }, { "kind": "press release", "citation": "Tzadik S, Ohfeld N, Shustin R, Ben-Sasson H, Avrahami Y, Malron N / Wiz Research (2026). Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854). Wiz Blog, 28 April 2026.", "title": "Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854)", "url": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854", "date": "2026-04-28", "written_by": "deployer", "quote": "This research was made possible by AI-augmented reverse engineering tooling, particularly IDA MCP, which allowed us to rapidly analyze GitHub's compiled binaries" }, { "kind": "news report", "citation": "Jones C / The Register (2026). GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash. The Register, 29 April 2026.", "title": "GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash", "url": "https://www.theregister.com/2026/04/29/github_woah_a_genuinely_helpful/", "date": "2026-04-29", "written_by": "independent", "quote": "They used Claude Code to take a lot of the legwork out of the process" }, { "kind": "news report", "citation": "Warren T / The Verge (2026). GitHub rushed to fix a critical vulnerability in less than six hours. The Verge, 29 April 2026.", "title": "GitHub rushed to fix a critical vulnerability in less than six hours", "url": "https://www.theverge.com/news/920295/github-remote-code-execution-vulnerability-fix", "date": "2026-04-29", "written_by": "independent", "quote": "A critical remote code execution vulnerability was discovered using an AI model and patched within hours." }, { "kind": "news report", "citation": "Culafi A / Dark Reading (2026). Reverse Engineering With AI Unearths High-Severity GitHub Bug. Dark Reading, 29 April 2026.", "title": "Reverse Engineering With AI Unearths High-Severity GitHub Bug", "url": "https://www.darkreading.com/application-security/reverse-engineering-ai-unearths-high-severity-github-bug", "date": "2026-04-29", "written_by": "independent", "quote": "With the help of AI tools, it took less than 48 hours to go from idea to a working exploit" }, { "kind": "news report", "citation": "Ritchie D / WebProNews (2026). Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty. WebProNews, 30 April 2026.", "title": "Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty", "url": "https://www.webpronews.com/wizs-ai-powered-strike-how-claude-cracked-githubs-git-fortress-for-a-fat-bounty/", "date": "2026-04-30", "written_by": "independent", "quote": "They leaned on Claude Code, Anthropic's agentic coding tool, for the heavy lifting." }, { "kind": "press release", "citation": "Anthropic (2026). Claude Code overview. Claude Code documentation.", "title": "Overview", "url": "https://code.claude.com/docs/en/overview", "date": null, "written_by": "makers", "quote": "Claude Code is an agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools." } ], "replication": { "produced_by": [ "A closed-source target that researchers could obtain and disassemble. GitHub's backend git services also ship as GitHub Enterprise Server binaries. Those binaries gave automated reverse engineering something to work on, and GHES 3.19.1 gave a place to confirm the exploit.", "AI-augmented tooling for reverse engineering: IDA MCP (per Wiz) driven by Claude Code (per The Register). It reconstructed internal protocols and traced where user input could influence server behavior across the pipeline.", "Experienced vulnerability researchers: six named Wiz authors formed the hypothesis and built and confirmed a working exploit. They wrote what GitHub called a thorough report that clearly demonstrated the impact.", "A beneficiary with a Bug Bounty intake and an on-call security team. GitHub reproduced the bug within 40 minutes of the report. It deployed a fix to github.com at 7:00 pm UTC the same day." ], "must_hold": [ "AI output has to be confirmed by exploit, not trusted. Wiz confirmed RCE on a GHES 3.19.1 instance before reporting. That is why GitHub could validate the report in 40 minutes.", "The receiving organization must be able to patch its own service and ship fixes to self-hosted customers. GHES customers stayed exposed until they upgraded to the patched versions released from 10 March 2026.", "Disclosure must wait for the patches, here from 4 March to 28 April 2026. No exploitation had occurred, so the benefit is an exposure closed, not a loss recovered." ], "echoes": [] }, "paired_incident": null, "headline": "Wiz finds a critical GitHub RCE with Claude Code and IDA MCP", "metric": "went from idea to working exploit in under 48 hours", "comparator": { "against": "manual reverse engineering of GitHub's compiled binaries without AI tooling", "before": "an impractical amount of time and manual effort (Wiz); months' worth of manual analysis, per The Register's account of Wiz", "after": "from idea to working exploit in less than 48 hours", "basis": "assumed", "quote": "However, extracting and auditing the sheer volume of compiled blackbox binaries that run this pipeline historically required an impractical amount of time and manual effort. But this is Round 2, and the landscape has shifted. By leveraging AI-augmented tooling-particularly automated reverse engineering using IDA MCP-we were able to do what was previously too costly.", "url": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854" }, "later": { "status": "persisted", "date": "2026-04-28", "note": "GitHub's 28 April 2026 disclosure confirmed the same-day fix, patches for all supported GitHub Enterprise Server releases, and a forensic investigation that found no exploitation beyond the researchers' own testing.", "quote": "In less than two hours we had validated the finding, deployed a fix to github.com, and begun a forensic investigation that concluded there was no exploitation.", "url": "https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 4 March 2026, the day Wiz reported the flaw and GitHub fixed github.com (GitHub's post: root cause identified at 5:45 pm UTC, fix deployed at 7:00 pm UTC; Wiz and The Verge say within six hours of the report; GitHub's standfirst says under two hours); the Monitor's 28 April 2026 is the public-disclosure date. Filed as benefit created or restored: the AI-assisted discovery produced a concrete fix for an identifiable organization, and the harm avoided is hypothetical because GitHub's forensic investigation found no exploitation. The AI tool is named differently by the sources: The Register (byline Connor Jones on the page as first read) and WebProNews say Claude Code, and WebProNews names Anthropic; Wiz's own write-up credits “AI-augmented tooling, particularly automated reverse engineering using IDA MCP”, and a search of its text as read found no occurrence of “Claude” or “Anthropic”, so the record names Claude Code on The Register's authority and IDA MCP on Wiz's. No Claude model is named anywhere. Severity: the CVE record (CNA GitHub) gives CVSS 4.0 8.7; The Register reports an 8.8 rating from NIST. GHES patch dates: Wiz's timeline says 10 March 2026, the 3.14.25 release notes are dated 12 March 2026. The Wiz post is marked as written by the makers because it is the discoverer's own account of its tooling, although Wiz is not the AI vendor; GitHub's post is the beneficiary's statement and is not flagged. Anthropic's Claude Code overview is cited only for what the product is. The Monitor lists The Register's headline as “Wiz hands GitHub AI-aided bug report that isn't total slop”; the page as read carries the longer headline used in the citation. The Verge and Dark Reading refused direct fetches and were read through the r.jina.ai text proxy; NVD's page did not render; WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged, so the CVE record's reference list was used to locate the Wiz and GitHub posts.", "source": "https://oecd.ai/en/incidents/2026-04-28-f5d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854; https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Wiz_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports, the makers' press release, the deployer's press release, the beneficiary's report and two other sources from the beneficiary. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0206", "catalog_version": "1.0.0", "source_fingerprint": "7f34bca5fb89430f7594439f89d31ee3a5bdf590dac0a26ae25031315a985960", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0206-source-0001", "AIBD-0206-source-0002", "AIBD-0206-source-0003", "AIBD-0206-source-0004", "AIBD-0206-source-0005", "AIBD-0206-source-0006", "AIBD-0206-source-0007", "AIBD-0206-source-0008", "AIBD-0206-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Anthropic (Claude Code); the maker of IDA MCP is not named in the sources", "deployer": "Wiz Research (Sagi Tzadik, Nir Ohfeld, Ronen Shustin, Hillai Ben-Sasson, Yuval Avrahami, Noam Malron)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI's documented contribution is speed of analysis, on the researchers' own account. Wiz writes that AI-augmented reverse-engineering tooling, particularly IDA MCP, let it rapidly analyze GitHub's compiled binaries and reconstruct internal protocols. Wiz says that speed would not have been feasible manually. Sagi Tzadik told Dark Reading that with AI tools it took under 48 hours from idea to working exploit. The Register adds that the team used Claude Code “to take a lot of the legwork out of the process”. The hypothesis, the exploit, the report and the fix were human work. Six named Wiz researchers confirmed RCE on GHES 3.19.1 and wrote what GitHub called a thorough report. GitHub's security and engineering teams reproduced the bug within 40 minutes and deployed the fix. GitHub's own post, the CVE record and the GHES release notes describe a Bug Bounty report without mentioning AI. The AI-assistance claim therefore rests on Wiz and on outlets quoting Wiz. Wiz's write-up, in the text as read, names IDA MCP and not Claude." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Wiz researchers used AI tools to analyze GitHub’s compiled software and reconstruct its internal protocols. They reported that the tools accelerated the work and that they produced a working exploit in under 48 hours.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI's documented contribution is speed of analysis, on the researchers' own account. Wiz writes that AI-augmented reverse-engineering tooling, particularly IDA MCP, let it rapidly analyze GitHub's compiled binaries and reconstruct internal protocols. Wiz says that speed would not have been feasible manually. Sagi Tzadik told Dark Reading that with AI tools it took under 48 hours from idea to working exploit. The Register adds that the team used Claude Code “to take a lot of the legwork out of the process”. The hypothesis, the exploit, the report and the fix were human work. Six named Wiz researchers confirmed RCE on GHES 3.19.1 and wrote what GitHub called a thorough report. GitHub's security and engineering teams reproduced the bug within 40 minutes and deployed the fix. GitHub's own post, the CVE record and the GHES release notes describe a Bug Bounty report without mentioning AI. The AI-assistance claim therefore rests on Wiz and on outlets quoting Wiz. Wiz's write-up, in the text as read, names IDA MCP and not Claude." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "GitHub closed a critical remote code execution hole in its git push pipeline within hours of the report. The fix reached github.com at 7:00 pm UTC on 4 March 2026. GitHub also shipped patches for six GitHub Enterprise Server release lines. Wiz earned what GitHub calls one of the highest rewards in the history of its Bug Bounty program. The loss avoided is hypothetical. GitHub's forensic investigation found that no other account had triggered the code path. No customer data was accessed, modified or exfiltrated. The benefit is an exposure closed rather than a demonstrated loss prevented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: four independent news reports, the makers' press release, the deployer's press release, the beneficiary's report and two other sources from the beneficiary. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "GitHub closed a critical remote code execution hole in its git push pipeline within hours of the report. The fix reached github.com at 7:00 pm UTC on 4 March 2026. GitHub also shipped patches for six GitHub Enterprise Server release lines. Wiz earned what GitHub calls one of the highest rewards in the history of its Bug Bounty program. The loss avoided is hypothetical. GitHub's forensic investigation found that no other account had triggered the code path. No customer data was accessed, modified or exfiltrated. The benefit is an exposure closed rather than a demonstrated loss prevented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GitHub closed the vulnerability within hours and patched six Enterprise Server release lines. Its investigation found that no other account had triggered the affected code path and that no customer data had been accessed, changed, or removed. The benefit is a corrected exposure, with no measured loss avoided." } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "GitHub closed a critical remote code execution hole in its git push pipeline within hours of the report. The fix reached github.com at 7:00 pm UTC on 4 March 2026. GitHub also shipped patches for six GitHub Enterprise Server release lines. Wiz earned what GitHub calls one of the highest rewards in the history of its Bug Bounty program. The loss avoided is hypothetical. GitHub's forensic investigation found that no other account had triggered the code path. No customer data was accessed, modified or exfiltrated. The benefit is an exposure closed rather than a demonstrated loss prevented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Wiz reports less than 48 hours from the initial idea to a working exploit. Its comparison with months of manual analysis is an estimate, without a measured control." } }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "Time from the initial idea to a working exploit, time to verify the report, and time to deploy a fix." } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The account of AI assistance comes from Wiz and interviews with its researchers. Wiz names IDA MCP; The Register and WebProNews name Claude Code. GitHub independently confirmed and fixed the vulnerability but did not describe AI’s contribution.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-04-28-f5d8" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-04-28", "note": "GitHub's 28 April 2026 disclosure confirmed the same-day fix, patches for all supported GitHub Enterprise Server releases, and a forensic investigation that found no exploitation beyond the researchers' own testing.", "quote": "In less than two hours we had validated the finding, deployed a fix to github.com, and begun a forensic investigation that concluded there was no exploitation.", "url": "https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GitHub fixed github.com on 4 March 2026 and released Enterprise Server patches from 10 March. Public disclosure followed on 28 April, with an investigation that found no exploitation beyond the researchers’ testing." } }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Wiz researchers developed and tested the exploit. GitHub’s security and engineering teams reproduced the vulnerability and deployed the fix." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0206" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "GitHub and organizations using GitHub Enterprise Server." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GitHub and organizations using GitHub Enterprise Server." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 4 March 2026 Wiz Research reported a critical remote code execution (RCE) flaw to GitHub, later CVE-2026–3854. It sat in GitHub's internal git infrastructure. Git push options were not sanitized before being written into internal headers. Any authenticated user could therefore run arbitrary commands on GitHub's servers with a single git push. Wiz says AI-augmented tooling made the research feasible, particularly automated reverse engineering of GitHub's compiled binaries with IDA MCP. The Register reports that the team used Claude Code and went from idea to working exploit in under 48 hours. GitHub reproduced the bug within 40 minutes and deployed a fix to github.com at 7:00 pm UTC that day. It released GitHub Enterprise Server (GHES) patches from 10 March, and found no exploitation.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "GitHub fixed a vulnerability that allowed remote code execution after Wiz researchers reported it." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "GitHub closed a critical remote code execution hole in its git push pipeline within hours of the report. The fix reached github.com at 7:00 pm UTC on 4 March 2026. GitHub also shipped patches for six GitHub Enterprise Server release lines. Wiz earned what GitHub calls one of the highest rewards in the history of its Bug Bounty program. The loss avoided is hypothetical. GitHub's forensic investigation found that no other account had triggered the code path. No customer data was accessed, modified or exfiltrated. The benefit is an exposure closed rather than a demonstrated loss prevented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Claude Code is Anthropic's agentic coding tool, built to read a codebase, edit files, run commands and connect to external tools over MCP. Wiz used it, with IDA MCP, to automate reverse engineering of GitHub's compiled binaries. Analyzing code for flaws is within that general purpose. The benefit was an application of what the tool was built to do rather than a departure from it." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Claude Code is Anthropic's agentic coding tool, built to read a codebase, edit files, run commands and connect to external tools over MCP. Wiz used it, with IDA MCP, to automate reverse engineering of GitHub's compiled binaries. Analyzing code for flaws is within that general purpose. The benefit was an application of what the tool was built to do rather than a departure from it." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-04", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 4 March 2026, the day Wiz reported the flaw and GitHub fixed github.com (GitHub's post: root cause identified at 5:45 pm UTC, fix deployed at 7:00 pm UTC; Wiz and The Verge say within six hours of the report; GitHub's standfirst says under two hours); the Monitor's 28 April 2026 is the public-disclosure date. Filed as benefit created or restored: the AI-assisted discovery produced a concrete fix for an identifiable organization, and the harm avoided is hypothetical because GitHub's forensic investigation found no exploitation. The AI tool is named differently by the sources: The Register (byline Connor Jones on the page as first read) and WebProNews say Claude Code, and WebProNews names Anthropic; Wiz's own write-up credits “AI-augmented tooling, particularly automated reverse engineering using IDA MCP”, and a search of its text as read found no occurrence of “Claude” or “Anthropic”, so the record names Claude Code on The Register's authority and IDA MCP on Wiz's. No Claude model is named anywhere. Severity: the CVE record (CNA GitHub) gives CVSS 4.0 8.7; The Register reports an 8.8 rating from NIST. GHES patch dates: Wiz's timeline says 10 March 2026, the 3.14.25 release notes are dated 12 March 2026. The Wiz post is marked as written by the makers because it is the discoverer's own account of its tooling, although Wiz is not the AI vendor; GitHub's post is the beneficiary's statement and is not flagged. Anthropic's Claude Code overview is cited only for what the product is. The Monitor lists The Register's headline as “Wiz hands GitHub AI-aided bug report that isn't total slop”; the page as read carries the longer headline used in the citation. The Verge and Dark Reading refused direct fetches and were read through the r.jina.ai text proxy; NVD's page did not render; WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged, so the CVE record's reference list was used to locate the Wiz and GitHub posts.", "source": "https://oecd.ai/en/incidents/2026-04-28-f5d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854; https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Wiz_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A closed-source target that researchers could obtain and disassemble. GitHub's backend git services also ship as GitHub Enterprise Server binaries. Those binaries gave automated reverse engineering something to work on, and GHES 3.19.1 gave a place to confirm the exploit.", "AI-augmented tooling for reverse engineering: IDA MCP (per Wiz) driven by Claude Code (per The Register). It reconstructed internal protocols and traced where user input could influence server behavior across the pipeline.", "Experienced vulnerability researchers: six named Wiz authors formed the hypothesis and built and confirmed a working exploit. They wrote what GitHub called a thorough report that clearly demonstrated the impact.", "A beneficiary with a Bug Bounty intake and an on-call security team. GitHub reproduced the bug within 40 minutes of the report. It deployed a fix to github.com at 7:00 pm UTC the same day." ], "must_hold": [ "AI output has to be confirmed by exploit, not trusted. Wiz confirmed RCE on a GHES 3.19.1 instance before reporting. That is why GitHub could validate the report in 40 minutes.", "The receiving organization must be able to patch its own service and ship fixes to self-hosted customers. GHES customers stayed exposed until they upgraded to the patched versions released from 10 March 2026.", "Disclosure must wait for the patches, here from 4 March to 28 April 2026. No exploitation had occurred, so the benefit is an exposure closed, not a loss recovered." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Researchers need access to the compiled software and an environment for testing the suspected flaw. They must establish that the exploit works, report it privately, and allow time for patches. Self-hosted customers need to install the patched release." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources. the date observed is 4 March 2026, the day Wiz reported the flaw and GitHub fixed github.com (GitHub's post: root cause identified at 5:45 pm UTC, fix deployed at 7:00 pm UTC; Wiz and The Verge say within six hours of the report; GitHub's standfirst says under two hours); the Monitor's 28 April 2026 is the public-disclosure date. Filed as benefit created or restored: the AI-assisted discovery produced a concrete fix for an identifiable organization, and the harm avoided is hypothetical because GitHub's forensic investigation found no exploitation. The AI tool is named differently by the sources: The Register (byline Connor Jones on the page as first read) and WebProNews say Claude Code, and WebProNews names Anthropic; Wiz's own write-up credits “AI-augmented tooling, particularly automated reverse engineering using IDA MCP”, and a search of its text as read found no occurrence of “Claude” or “Anthropic”, so the record names Claude Code on The Register's authority and IDA MCP on Wiz's. No Claude model is named anywhere. Severity: the CVE record (CNA GitHub) gives CVSS 4.0 8.7; The Register reports an 8.8 rating from NIST. GHES patch dates: Wiz's timeline says 10 March 2026, the 3.14.25 release notes are dated 12 March 2026. The Wiz post is marked as written by the makers because it is the discoverer's own account of its tooling, although Wiz is not the AI vendor; GitHub's post is the beneficiary's statement and is not flagged. Anthropic's Claude Code overview is cited only for what the product is. The Monitor lists The Register's headline as “Wiz hands GitHub AI-aided bug report that isn't total slop”; the page as read carries the longer headline used in the citation. The Verge and Dark Reading refused direct fetches and were read through the r.jina.ai text proxy; NVD's page did not render; WebSearch was exhausted and Brave and DuckDuckGo rate-limited or challenged, so the CVE record's reference list was used to locate the Wiz and GitHub posts.", "source": "https://oecd.ai/en/incidents/2026-04-28-f5d8", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854; https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Wiz_(company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Cybersecurity: vulnerability research and software supply chain", "segment": "Bug bounty research: AI-assisted reverse engineering of closed-source server binaries" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Wales A / GitHub (2026). Securing the git push pipeline: Responding to a critical remote code execution vulnerability. The GitHub Blog, 28 April 2026 (updated 29 April 2026).", "title": "Securing the git push pipeline: Responding to a critical remote code execution vulnerability", "url": "https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "date": "2026-04-28", "written_by": "beneficiary", "quote": "our engineering team developed and deployed a fix to github.com at 7:00 p.m. UTC that same day" }, { "kind": "other", "citation": "GitHub (CNA) (2026). CVE-2026-3854. CVE Program record, published 10 March 2026.", "title": "CVE-2026-3854", "url": "https://cveawg.mitre.org/api/cve/CVE-2026-3854", "date": "2026-03-10", "written_by": "beneficiary", "quote": "allowed an attacker with push access to a repository to achieve remote code execution on the instance" }, { "kind": "other", "citation": "GitHub (2026). GitHub Enterprise Server 3.14 release notes, 3.14.25, 12 March 2026. GitHub Docs.", "title": "GitHub Enterprise Server 3.14 release notes (3.14.25)", "url": "https://docs.github.com/en/enterprise-server@3.14/admin/release-notes", "date": "2026-03-12", "written_by": "beneficiary", "quote": "GitHub has requested CVE ID CVE-2026-3854 for this vulnerability, which was reported via the GitHub Bug Bounty program." }, { "kind": "press release", "citation": "Tzadik S, Ohfeld N, Shustin R, Ben-Sasson H, Avrahami Y, Malron N / Wiz Research (2026). Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854). Wiz Blog, 28 April 2026.", "title": "Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854)", "url": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854", "date": "2026-04-28", "written_by": "deployer", "quote": "This research was made possible by AI-augmented reverse engineering tooling, particularly IDA MCP, which allowed us to rapidly analyze GitHub's compiled binaries" }, { "kind": "news report", "citation": "Jones C / The Register (2026). GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash. The Register, 29 April 2026.", "title": "GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash", "url": "https://www.theregister.com/2026/04/29/github_woah_a_genuinely_helpful/", "date": "2026-04-29", "written_by": "independent", "quote": "They used Claude Code to take a lot of the legwork out of the process" }, { "kind": "news report", "citation": "Warren T / The Verge (2026). GitHub rushed to fix a critical vulnerability in less than six hours. The Verge, 29 April 2026.", "title": "GitHub rushed to fix a critical vulnerability in less than six hours", "url": "https://www.theverge.com/news/920295/github-remote-code-execution-vulnerability-fix", "date": "2026-04-29", "written_by": "independent", "quote": "A critical remote code execution vulnerability was discovered using an AI model and patched within hours." }, { "kind": "news report", "citation": "Culafi A / Dark Reading (2026). Reverse Engineering With AI Unearths High-Severity GitHub Bug. Dark Reading, 29 April 2026.", "title": "Reverse Engineering With AI Unearths High-Severity GitHub Bug", "url": "https://www.darkreading.com/application-security/reverse-engineering-ai-unearths-high-severity-github-bug", "date": "2026-04-29", "written_by": "independent", "quote": "With the help of AI tools, it took less than 48 hours to go from idea to a working exploit" }, { "kind": "news report", "citation": "Ritchie D / WebProNews (2026). Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty. WebProNews, 30 April 2026.", "title": "Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty", "url": "https://www.webpronews.com/wizs-ai-powered-strike-how-claude-cracked-githubs-git-fortress-for-a-fat-bounty/", "date": "2026-04-30", "written_by": "independent", "quote": "They leaned on Claude Code, Anthropic's agentic coding tool, for the heavy lifting." }, { "kind": "press release", "citation": "Anthropic (2026). Claude Code overview. Claude Code documentation.", "title": "Overview", "url": "https://code.claude.com/docs/en/overview", "written_by": "makers", "quote": "Claude Code is an agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0206-source-0001", "AIBD-0206-source-0002", "AIBD-0206-source-0003", "AIBD-0206-source-0004", "AIBD-0206-source-0005", "AIBD-0206-source-0006", "AIBD-0206-source-0007", "AIBD-0206-source-0008", "AIBD-0206-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Wales A / GitHub (2026). Securing the git push pipeline: Responding to a critical remote code execution vulnerability. The GitHub Blog, 28 April 2026 (updated 29 April 2026).", "title": "Securing the git push pipeline: Responding to a critical remote code execution vulnerability", "url": "https://github.blog/security/securing-the-git-push-pipeline-responding-to-a-critical-remote-code-execution-vulnerability/", "date": "2026-04-28", "written_by": "beneficiary", "quote": "our engineering team developed and deployed a fix to github.com at 7:00 p.m. UTC that same day" }, { "kind": "other", "citation": "GitHub (CNA) (2026). CVE-2026-3854. CVE Program record, published 10 March 2026.", "title": "CVE-2026-3854", "url": "https://cveawg.mitre.org/api/cve/CVE-2026-3854", "date": "2026-03-10", "written_by": "beneficiary", "quote": "allowed an attacker with push access to a repository to achieve remote code execution on the instance" }, { "kind": "other", "citation": "GitHub (2026). GitHub Enterprise Server 3.14 release notes, 3.14.25, 12 March 2026. GitHub Docs.", "title": "GitHub Enterprise Server 3.14 release notes (3.14.25)", "url": "https://docs.github.com/en/enterprise-server@3.14/admin/release-notes", "date": "2026-03-12", "written_by": "beneficiary", "quote": "GitHub has requested CVE ID CVE-2026-3854 for this vulnerability, which was reported via the GitHub Bug Bounty program." }, { "kind": "press release", "citation": "Tzadik S, Ohfeld N, Shustin R, Ben-Sasson H, Avrahami Y, Malron N / Wiz Research (2026). Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854). Wiz Blog, 28 April 2026.", "title": "Securing GitHub: Wiz Research uncovers Remote Code Execution in GitHub.com and GitHub Enterprise Server (CVE-2026-3854)", "url": "https://www.wiz.io/blog/github-rce-vulnerability-cve-2026-3854", "date": "2026-04-28", "written_by": "deployer", "quote": "This research was made possible by AI-augmented reverse engineering tooling, particularly IDA MCP, which allowed us to rapidly analyze GitHub's compiled binaries" }, { "kind": "news report", "citation": "Jones C / The Register (2026). GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash. The Register, 29 April 2026.", "title": "GitHub: Zounds, a genuinely helpful AI-assisted bug report that isn't total slop! Here, Wiz, take this wad of cash", "url": "https://www.theregister.com/2026/04/29/github_woah_a_genuinely_helpful/", "date": "2026-04-29", "written_by": "independent", "quote": "They used Claude Code to take a lot of the legwork out of the process" }, { "kind": "news report", "citation": "Warren T / The Verge (2026). GitHub rushed to fix a critical vulnerability in less than six hours. The Verge, 29 April 2026.", "title": "GitHub rushed to fix a critical vulnerability in less than six hours", "url": "https://www.theverge.com/news/920295/github-remote-code-execution-vulnerability-fix", "date": "2026-04-29", "written_by": "independent", "quote": "A critical remote code execution vulnerability was discovered using an AI model and patched within hours." }, { "kind": "news report", "citation": "Culafi A / Dark Reading (2026). Reverse Engineering With AI Unearths High-Severity GitHub Bug. Dark Reading, 29 April 2026.", "title": "Reverse Engineering With AI Unearths High-Severity GitHub Bug", "url": "https://www.darkreading.com/application-security/reverse-engineering-ai-unearths-high-severity-github-bug", "date": "2026-04-29", "written_by": "independent", "quote": "With the help of AI tools, it took less than 48 hours to go from idea to a working exploit" }, { "kind": "news report", "citation": "Ritchie D / WebProNews (2026). Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty. WebProNews, 30 April 2026.", "title": "Wiz's AI-Powered Strike: How Claude Cracked GitHub's Git Fortress for a Fat Bounty", "url": "https://www.webpronews.com/wizs-ai-powered-strike-how-claude-cracked-githubs-git-fortress-for-a-fat-bounty/", "date": "2026-04-30", "written_by": "independent", "quote": "They leaned on Claude Code, Anthropic's agentic coding tool, for the heavy lifting." }, { "kind": "press release", "citation": "Anthropic (2026). Claude Code overview. Claude Code documentation.", "title": "Overview", "url": "https://code.claude.com/docs/en/overview", "written_by": "makers", "quote": "Claude Code is an agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Wiz's AI-aided reverse engineering found a critical GitHub RCE (CVE-2026–3854); github.com was patched the same day, no exploitation found.", "account": "On 4 March 2026 Wiz Research reported a critical remote code execution (RCE) flaw to GitHub, later CVE-2026–3854. It sat in GitHub's internal git infrastructure. Git push options were not sanitized before being written into internal headers. Any authenticated user could therefore run arbitrary commands on GitHub's servers with a single git push. Wiz says AI-augmented tooling made the research feasible, particularly automated reverse engineering of GitHub's compiled binaries with IDA MCP. The Register reports that the team used Claude Code and went from idea to working exploit in under 48 hours. GitHub reproduced the bug within 40 minutes and deployed a fix to github.com at 7:00 pm UTC that day. It released GitHub Enterprise Server (GHES) patches from 10 March, and found no exploitation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The tools analyzed compiled binaries and helped researchers reconstruct internal protocols." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Wiz used IDA MCP to analyze GitHub’s compiled binaries. The Register identified Claude Code as the tool through which researchers performed some of that work." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Wiz used IDA MCP to analyze GitHub’s compiled binaries. The Register identified Claude Code as the tool through which researchers performed some of that work.", "editor_note": "Wiz’s original report names IDA MCP but not Claude Code. The latter identification comes from The Register’s reporting (references 4 and 5)." } }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The tools analyzed compiled binaries and helped researchers reconstruct internal protocols." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Not named in the cited sources. Wiz's write-up credits 'AI-augmented tooling, particularly automated reverse engineering using IDA MCP' and does not name Claude. The Register and WebProNews name Claude Code." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI-augmented reverse-engineering tooling used by Wiz Research: Claude Code (named by The Register and WebProNews) with IDA MCP for automated reverse engineering of GitHub's compiled binaries (named by Wiz), applied to GitHub.com's backend and GitHub Enterprise Server 3.19.1" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Anthropic (Claude Code); the maker of IDA MCP is not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Wiz Research's AI-augmented reverse engineering of GitHub's closed-source git binaries, with Claude Code and IDA MCP, finds a critical push-option injection giving remote code execution on GitHub.com and GitHub Enterprise Server; GitHub reproduces it in 40 minutes, patches github.com by 7:00 pm UTC on 4 March 2026 and finds no exploitation", "headline": "Wiz finds a critical GitHub RCE with Claude Code and IDA MCP" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7f34bca5fb89430f7594439f89d31ee3a5bdf590dac0a26ae25031315a985960" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 4 March 2026 Wiz Research reported a critical remote code execution (RCE) flaw to GitHub, later CVE-2026–3854. It sat in GitHub's internal git infrastructure. Git push options were not sanitized before being written into internal headers. Any authenticated user could therefore run arbitrary commands on GitHub's servers with a single git push. Wiz says AI-augmented tooling made the research feasible, particularly automated reverse engineering of GitHub's compiled binaries with IDA MCP. The Register reports that the team used Claude Code and went from idea to working exploit in under 48 hours. GitHub reproduced the bug within 40 minutes and deployed a fix to github.com at 7:00 pm UTC that day. It released GitHub Enterprise Server (GHES) patches from 10 March, and found no exploitation.", "replication": { "produced_by": [ "A closed-source target that researchers could obtain and disassemble. GitHub's backend git services also ship as GitHub Enterprise Server binaries. Those binaries gave automated reverse engineering something to work on, and GHES 3.19.1 gave a place to confirm the exploit.", "AI-augmented tooling for reverse engineering: IDA MCP (per Wiz) driven by Claude Code (per The Register). It reconstructed internal protocols and traced where user input could influence server behavior across the pipeline.", "Experienced vulnerability researchers: six named Wiz authors formed the hypothesis and built and confirmed a working exploit. They wrote what GitHub called a thorough report that clearly demonstrated the impact.", "A beneficiary with a Bug Bounty intake and an on-call security team. GitHub reproduced the bug within 40 minutes of the report. It deployed a fix to github.com at 7:00 pm UTC the same day." ], "must_hold": [ "AI output has to be confirmed by exploit, not trusted. Wiz confirmed RCE on a GHES 3.19.1 instance before reporting. That is why GitHub could validate the report in 40 minutes.", "The receiving organization must be able to patch its own service and ship fixes to self-hosted customers. GHES customers stayed exposed until they upgraded to the patched versions released from 10 March 2026.", "Disclosure must wait for the patches, here from 4 March to 28 April 2026. No exploitation had occurred, so the benefit is an exposure closed, not a loss recovered." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Wiz researchers obtained GitHub’s compiled software that also shipped with Enterprise Server. They used AI tools to examine it and developed an exploit that they confirmed on version 3.19.1. Their report showed that remote code execution was possible. GitHub reproduced the issue within 40 minutes and fixed github.com that evening." } } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 0, "record_mapped": 35, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0269", "title": "EchoNext ECG flag finds severe aortic stenosis in an asymptomatic 84-year-old; TAVR after hip-fracture surgery", "summary": "At Columbia/NewYork-Presbyterian, EchoNext flagged a pre-operative ECG (score 0.6094), triggering an EHR advisory; echo showed LVEF 40% and severe aortic stenosis; cardiac anesthesia, surgery, TAVR.", "date_observed": "2026-03-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Tat et al. (JACC: Case Reports, 4 March 2026) describe an 84-year-old woman with hypertension. She was admitted after a fall with a left femur fracture. Her electrocardiogram (ECG) was analyzed by EchoNext, a deep-learning model for structural heart disease developed at Columbia. The score was 0.6094; the model's high-risk cutoff is 0.6. The score triggered an electronic health record (EHR) advisory. Transthoracic echocardiography showed an ejection fraction of 40% and severe aortic stenosis. The valve area was 0.6 cm2, peak velocity 3.9 m/s and mean gradient 34 mm Hg. Cardiology recommended cardiac anesthesia for the orthopedic operation. The patient then underwent transcatheter aortic valve replacement (TAVR), on day 8. The authors call it the first report of an AI-ECG algorithm detecting undiagnosed severe aortic stenosis that led to TAVR. EchoNext's development paper (Poterucha et al., Nature, July 2025) reports training on more than 1 million ECG and imaging records. It reports that 73% of patients flagged high-risk in prospective evaluation had newly diagnosed disease. All authors are the Columbia developers. Dr Elias reports research support including from Edwards.", "category": "benefit created", "unexpected": false, "purpose": "Screen ECGs for unrecognised structural heart disease and alert clinicians through the electronic health record", "system": "EchoNext deep-learning ECG model integrated into the electronic health record", "model_version": "second-generation EchoNext model", "developer": "Columbia University (Poterucha, Elias and colleagues)", "deployer": "Columbia University Irving Medical Center / NewYork-Presbyterian", "location": "New York, New York, USA", "domain": "Health; cardiology", "segment": "Hospital patients with an ECG and no known structural heart disease", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Severe aortic stenosis found before non-cardiac surgery, changing perioperative management and leading to TAVR." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome reported for this case." }, { "group": "societal", "depth": null, "reason": "Single case." } ], "ai_role": { "status": "assessed", "statement": "The EHR advisory from EchoNext prompted the echocardiogram in an asymptomatic patient, according to the developers' own case report. The evidence is developer-authored: the case report and the Nature development paper, with disclosed industry research support. No independent account was found." }, "evidence": [ { "kind": "case report", "citation": "Tat E, Oliver FR, Malta P, Castillo M, Poterucha TJ, Elias P. JACC Case Rep 31(14):107184 (2026)", "title": "Artificial Intelligence-Enabled Electrocardiographic Detection of Severe Aortic Stenosis Leading to Transcatheter Aortic Valve Replacement", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13080615/", "date": "2026-03-04", "written_by": "makers", "quote": "To our knowledge, this is the first report of an artificial intelligence-enabled ECG algorithm detecting undiagnosed severe AS that led to transcatheter aortic valve replacement." }, { "kind": "peer-reviewed study", "citation": "Poterucha TJ, Jing L, Ricart RP, et al. Nature (2025)", "title": "Detecting structural heart disease from electrocardiograms using AI", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/", "date": "2025-07-16", "written_by": "makers", "quote": "we introduce a deep learning model, EchoNext, trained on more than 1 million heart rhythm and imaging records across a large and diverse health system" }, { "kind": "press release", "citation": "NewYork-Presbyterian (23 Jun 2026). 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "EchoNext scoring of a routine ECG", "EHR-integrated advisory to the primary team", "Cardiology consultation and echocardiography" ], "must_hold": [ "Model deployed with alerts in the health record", "Clinicians act on the advisory before surgery" ], "echoes": [ { "date": "2025-07-16", "setting": "Prospective evaluation in the development paper: 73% of patients flagged high-risk had newly diagnosed disease", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/; https://www.nyp.org/news/ai-tool-developed-at-newyork-presbyterian-and-columbia-to-detect-hidden-heart-disease-receives-fda-approval; https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Columbia_University; https://en.wikipedia.org/wiki/Columbia_University_Irving_Medical_Center", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Health; cardiology", "segment": "Hospital patients with an ECG and no known structural heart disease" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Tat E, Oliver FR, Malta P, Castillo M, Poterucha TJ, Elias P. JACC Case Rep 31(14):107184 (2026)", "title": "Artificial Intelligence-Enabled Electrocardiographic Detection of Severe Aortic Stenosis Leading to Transcatheter Aortic Valve Replacement", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13080615/", "date": "2026-03-04", "written_by": "makers", "quote": "To our knowledge, this is the first report of an artificial intelligence-enabled ECG algorithm detecting undiagnosed severe AS that led to transcatheter aortic valve replacement." }, { "kind": "peer-reviewed study", "citation": "Poterucha TJ, Jing L, Ricart RP, et al. Nature (2025)", "title": "Detecting structural heart disease from electrocardiograms using AI", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/", "date": "2025-07-16", "written_by": "makers", "quote": "we introduce a deep learning model, EchoNext, trained on more than 1 million heart rhythm and imaging records across a large and diverse health system" }, { "kind": "press release", "citation": "NewYork-Presbyterian (23 Jun 2026). AI Tool Developed at NewYork-Presbyterian and Columbia to Detect Hidden Heart Disease Receives FDA Approval.", "title": "AI Tool Developed at NewYork-Presbyterian and Columbia to Detect Hidden Heart Disease Receives FDA Approval", "url": "https://www.nyp.org/news/ai-tool-developed-at-newyork-presbyterian-and-columbia-to-detect-hidden-heart-disease-receives-fda-approval", "date": "2026-06-23", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0269-source-0001", "AIBD-0269-source-0002", "AIBD-0269-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Tat E, Oliver FR, Malta P, Castillo M, Poterucha TJ, Elias P. JACC Case Rep 31(14):107184 (2026)", "title": "Artificial Intelligence-Enabled Electrocardiographic Detection of Severe Aortic Stenosis Leading to Transcatheter Aortic Valve Replacement", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13080615/", "date": "2026-03-04", "written_by": "makers", "quote": "To our knowledge, this is the first report of an artificial intelligence-enabled ECG algorithm detecting undiagnosed severe AS that led to transcatheter aortic valve replacement." }, { "kind": "peer-reviewed study", "citation": "Poterucha TJ, Jing L, Ricart RP, et al. Nature (2025)", "title": "Detecting structural heart disease from electrocardiograms using AI", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/", "date": "2025-07-16", "written_by": "makers", "quote": "we introduce a deep learning model, EchoNext, trained on more than 1 million heart rhythm and imaging records across a large and diverse health system" }, { "kind": "press release", "citation": "NewYork-Presbyterian (23 Jun 2026). AI Tool Developed at NewYork-Presbyterian and Columbia to Detect Hidden Heart Disease Receives FDA Approval.", "title": "AI Tool Developed at NewYork-Presbyterian and Columbia to Detect Hidden Heart Disease Receives FDA Approval", "url": "https://www.nyp.org/news/ai-tool-developed-at-newyork-presbyterian-and-columbia-to-detect-hidden-heart-disease-receives-fda-approval", "date": "2026-06-23", "written_by": "makers" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At Columbia/NewYork-Presbyterian, EchoNext flagged a pre-operative ECG (score 0.6094), triggering an EHR advisory; echo showed LVEF 40% and severe aortic stenosis; cardiac anesthesia, surgery, TAVR.", "account": "Tat et al. (JACC: Case Reports, 4 March 2026) describe an 84-year-old woman with hypertension. She was admitted after a fall with a left femur fracture. Her electrocardiogram (ECG) was analyzed by EchoNext, a deep-learning model for structural heart disease developed at Columbia. The score was 0.6094; the model's high-risk cutoff is 0.6. The score triggered an electronic health record (EHR) advisory. Transthoracic echocardiography showed an ejection fraction of 40% and severe aortic stenosis. The valve area was 0.6 cm2, peak velocity 3.9 m/s and mean gradient 34 mm Hg. Cardiology recommended cardiac anesthesia for the orthopedic operation. The patient then underwent transcatheter aortic valve replacement (TAVR), on day 8. The authors call it the first report of an AI-ECG algorithm detecting undiagnosed severe aortic stenosis that led to TAVR. EchoNext's development paper (Poterucha et al., Nature, July 2025) reports training on more than 1 million ECG and imaging records. It reports that 73% of patients flagged high-risk in prospective evaluation had newly diagnosed disease. All authors are the Columbia developers. Dr Elias reports research support including from Edwards." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "EchoNext analyzed an ECG and prompted further assessment for structural heart disease." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The second-generation EchoNext model." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "second-generation EchoNext model" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The second generation of EchoNext.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "EchoNext deep-learning ECG model integrated into the electronic health record" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Columbia University (Poterucha, Elias and colleagues)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "EchoNext ECG flag finds severe aortic stenosis in an asymptomatic 84-year-old; TAVR after hip-fracture surgery", "headline": "EchoNext ECG flag finds severe aortic stenosis, leads to TAVR" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ded723cc3c3b65962632c70b0673f5cffda0c064d6cc9a402c53108b5cfbc366" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Tat et al. (JACC: Case Reports, 4 March 2026) describe an 84-year-old woman with hypertension. She was admitted after a fall with a left femur fracture. Her electrocardiogram (ECG) was analyzed by EchoNext, a deep-learning model for structural heart disease developed at Columbia. The score was 0.6094; the model's high-risk cutoff is 0.6. The score triggered an electronic health record (EHR) advisory. Transthoracic echocardiography showed an ejection fraction of 40% and severe aortic stenosis. The valve area was 0.6 cm2, peak velocity 3.9 m/s and mean gradient 34 mm Hg. Cardiology recommended cardiac anesthesia for the orthopedic operation. The patient then underwent transcatheter aortic valve replacement (TAVR), on day 8. The authors call it the first report of an AI-ECG algorithm detecting undiagnosed severe aortic stenosis that led to TAVR. EchoNext's development paper (Poterucha et al., Nature, July 2025) reports training on more than 1 million ECG and imaging records. It reports that 73% of patients flagged high-risk in prospective evaluation had newly diagnosed disease. All authors are the Columbia developers. Dr Elias reports research support including from Edwards.", "replication": { "produced_by": [ "EchoNext scoring of a routine ECG", "EHR-integrated advisory to the primary team", "Cardiology consultation and echocardiography" ], "must_hold": [ "Model deployed with alerts in the health record", "Clinicians act on the advisory before surgery" ], "echoes": [ { "date": "2025-07-16", "setting": "Prospective evaluation in the development paper: 73% of patients flagged high-risk had newly diagnosed disease", "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12328201/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0202", "title": "Gyeonggi ARES AI pig-weighing pilot cuts shipping age 5.6 days and lifts income per head 18% on six farms", "summary": "2025 provincial pilot on six farms in Anseong, Pocheon and Yeoju: AI non-contact weighing cut shipping age 182.3 to 176.7 days, lifted 1+ grade share 35.3 to 37.7% and income per head 18%.", "date_observed": "2026-03-06", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Gyeonggi-do Agricultural Research and Extension Services announced the results of its 2025 livestock AI pilot on 6 March 2026. The Fact reported it with a Suwon dateline, and Joongboo Ilbo on 8 March. A fattening-pig shipping selection system uses AI to measure pigs' weight without contact and advise the optimal shipping date. It was introduced on six farms in Anseong, Pocheon and Yeoju. Shipping age fell from 182.3 to 176.7 days, a drop of 5.6 days. The share shipped at grade 1+ rose from 35.3% to 37.7%, up 2.4 percentage points. Income per head rose from 100,000 to 118,000 won, up 18%. A sow farrowing management system using ICT equipment for real-time monitoring was introduced on Pocheon farms. It cut the sow accident rate from 3.1% to 2.7%; those accidents are mastitis, fever, loss of appetite and crushing of piglets. Piglets shipped per sow per year rose from 18.3 to 19.2, up 4.9%. Real-time alerts reduced the need to stay in the barn. Lee Jun-bae, head of the agency's technology dissemination division, said the results confirmed AI as a way to raise productivity and income. The agency plans to extend the weighing system to Yeoncheon in 2026. The vendor of the systems is not named. The pilot is listed in the OECD AI Incidents Monitor.", "category": "benefit created", "unexpected": false, "purpose": "Measure fattening pigs' weight without contact using AI and advise the optimal shipping date. Monitor sows in real time around farrowing.", "system": "Fattening-pig shipping selection system (AI non-contact weighing) and sow farrowing management system (ICT monitoring)", "model_version": null, "developer": "Not named in the sources", "deployer": "Gyeonggi-do Agricultural Research and Extension Services with six pig farms in Anseong, Pocheon and Yeoju (weighing) and Pocheon farms (sow system)", "location": "Anseong, Pocheon and Yeoju, South Korea", "domain": "Livestock production", "segment": "Swine finishing and farrowing", "benefit_type": "Increased Product Revenue", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "On six farms, shipping age fell from 182.3 to 176.7 days and the grade 1+ share rose from 35.3% to 37.7%. Income per head rose from 100,000 to 118,000 won, up 18%. On Pocheon farms, sow accidents fell from 3.1% to 2.7% and piglets per sow per year rose from 18.3 to 19.2. These are the agency's own before-and-after figures." }, { "group": "personal", "depth": null, "reason": "Reduced need for farmers to stay in the barn is mentioned but not measured." } ], "ai_role": { "status": "assessed", "statement": "The AI's contribution is the weight estimate and shipping-date advice. The production gains are the agency's uncontrolled before-and-after comparisons. The deployer is a public body that reports its own pilot. The developer is not named. Two independent newspapers carried the release with a named official." }, "evidence": [ { "kind": "news report", "citation": "이승호. AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\". 더팩트 (The Fact), 6 March 2026.", "title": "AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\"", "url": "https://news.tf.co.kr/read/national/2299220.htm", "date": "2026-03-06", "written_by": "independent", "quote": "이 결과 출하일령이 182.3일에서 176.7일로 5.6일 줄었다." }, { "kind": "news report", "citation": "신연경. 도농기원, AI 기술로 경기지역 농가서 스마트축산 실현. 중부일보 (Joongboo Ilbo), 8 March 2026.", "title": "도농기원, AI 기술로 경기지역 농가서 스마트축산 실현", "url": "https://www.joongboo.com/news/articleView.html?idxno=363719065", "date": "2026-03-08", "written_by": "independent", "quote": "두당 소득은 1두 10만 원에서 11만8천 원으로 18% 증가했다." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province. Record 2026-03-05-1ac3.", "title": "AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province", "url": "https://oecd.ai/en/incidents/2026-03-05-1ac3", "date": "2026-03-05", "written_by": "independent", "quote": "These systems reduced birthing accidents and increased both productivity and farmer income, demonstrating AI's positive impact on livestock management in South Korea's Gyeonggi Province." } ], "replication": { "produced_by": [ "A provincial extension pilot funded in 2025", "Six commercial pig farms adopting non-contact AI weighing", "A grading system that pays a premium for grade 1+ pigs" ], "must_hold": [ "Farm staff acting on the shipping-date advice", "Real-time alerts reaching farmers from the sow system" ], "echoes": [ { "date": "2026-03-08", "setting": "Yeoncheon, Gyeonggi: planned 2026 extension of the weighing system targeting a higher grade 1+ rate", "model_version": "same system", "outcome": "unknown", "source": "Joongboo Ilbo, 8 March 2026" } ] }, "paired_incident": null, "headline": "Gyeonggi AI pig-weighing pilot lifts income per head 18%", "metric": "income per head rose from 100,000 to 118,000 won (18%)", "comparator": { "against": "the same six farms before the AI shipping selection system was introduced (2025 pilot)", "before": "출하일령 182.3일; 1+등급 출하율 35.3%; 두당 소득 10만 원", "after": "출하일령 176.7일 (5.6일 단축); 1+등급 출하율 37.7% (2.4%p 증가); 두당 소득 11만 8000원 (18% 증가)", "basis": "measured", "quote": "출하일령이 182.3일에서 176.7일로 5.6일 줄었다. 또 1+등급 출하율은 35.3%에서 37.7%으로 2.4%p 증가하고, 두당 소득이 10만 원에서 11만 8000원으로 18% 늘었다.", "url": "https://news.tf.co.kr/read/national/2299220.htm" }, "later": { "status": "unknown", "date": null, "note": "The agency announced a plan to run the weighing system in Yeoncheon in 2026, but no report of that rollout or its results was found.", "quote": null, "url": null }, "value": { "amount": "11만 8000원", "what": "income per pig shipped with the AI shipping selection system, up from 10만 원 (100,000 won) per head, an 18% increase", "who": "the six pilot pig farms in Anseong, Pocheon and Yeoju", "estimate": false, "quote": "출하일령이 182.3일에서 176.7일로 5.6일 줄었다. 또 1+등급 출하율은 35.3%에서 37.7%으로 2.4%p 증가하고, 두당 소득이 10만 원에서 11만 8000원으로 18% 늘었다.", "url": "https://news.tf.co.kr/read/national/2299220.htm" }, "developer_country": null, "deployer_country": "South Korea", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://news.tf.co.kr/read/national/2299220.htm; https://news.tf.co.kr/read/national/2299220.htm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://ko.wikipedia.org/wiki/%EA%B2%BD%EA%B8%B0%EB%8F%84%EB%86%8D%EC%97%85%EA%B8%B0%EC%88%A0%EC%9B%90", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. 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These are the agency's own before-and-after figures." }, { "group": "personal", "reason": "Reduced need for farmers to stay in the barn is mentioned but not measured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "On six farms, shipping age fell from 182.3 to 176.7 days and the grade 1+ share rose from 35.3% to 37.7%. Income per head rose from 100,000 to 118,000 won, up 18%. On Pocheon farms, sow accidents fell from 3.1% to 2.7% and piglets per sow per year rose from 18.3 to 19.2. 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external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Gyeonggi-do Agricultural Research and Extension Services announced the results of its 2025 livestock AI pilot on 6 March 2026. The Fact reported it with a Suwon dateline, and Joongboo Ilbo on 8 March. A fattening-pig shipping selection system uses AI to measure pigs' weight without contact and advise the optimal shipping date. It was introduced on six farms in Anseong, Pocheon and Yeoju. Shipping age fell from 182.3 to 176.7 days, a drop of 5.6 days. The share shipped at grade 1+ rose from 35.3% to 37.7%, up 2.4 percentage points. Income per head rose from 100,000 to 118,000 won, up 18%. A sow farrowing management system using ICT equipment for real-time monitoring was introduced on Pocheon farms. It cut the sow accident rate from 3.1% to 2.7%; those accidents are mastitis, fever, loss of appetite and crushing of piglets. Piglets shipped per sow per year rose from 18.3 to 19.2, up 4.9%. Real-time alerts reduced the need to stay in the barn. Lee Jun-bae, head of the agency's technology dissemination division, said the results confirmed AI as a way to raise productivity and income. The agency plans to extend the weighing system to Yeoncheon in 2026. The vendor of the systems is not named. The pilot is listed in the OECD AI Incidents Monitor.", "benefit_type": "Increased Product Revenue" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "On six farms, shipping age fell from 182.3 to 176.7 days and the grade 1+ share rose from 35.3% to 37.7%. Income per head rose from 100,000 to 118,000 won, up 18%. On Pocheon farms, sow accidents fell from 3.1% to 2.7% and piglets per sow per year rose from 18.3 to 19.2. These are the agency's own before-and-after figures." }, { "group": "personal", "reason": "Reduced need for farmers to stay in the barn is mentioned but not measured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Measure fattening pigs' weight without contact using AI and advise the optimal shipping date. Monitor sows in real time around farrowing." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Anseong, Pocheon and Yeoju, South Korea", "deployer_country": "South Korea" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Measure fattening pigs' weight without contact using AI and advise the optimal shipping date. Monitor sows in real time around farrowing." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-06", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Revenue under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://news.tf.co.kr/read/national/2299220.htm; 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external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Livestock production", "segment": "Swine finishing and farrowing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "이승호. AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\". 더팩트 (The Fact), 6 March 2026.", "title": "AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\"", "url": "https://news.tf.co.kr/read/national/2299220.htm", "date": "2026-03-06", "written_by": "independent", "quote": "이 결과 출하일령이 182.3일에서 176.7일로 5.6일 줄었다." }, { "kind": "news report", "citation": "신연경. 도농기원, AI 기술로 경기지역 농가서 스마트축산 실현. 중부일보 (Joongboo Ilbo), 8 March 2026.", "title": "도농기원, AI 기술로 경기지역 농가서 스마트축산 실현", "url": "https://www.joongboo.com/news/articleView.html?idxno=363719065", "date": "2026-03-08", "written_by": "independent", "quote": "두당 소득은 1두 10만 원에서 11만8천 원으로 18% 증가했다." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province. Record 2026-03-05-1ac3.", "title": "AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province", "url": "https://oecd.ai/en/incidents/2026-03-05-1ac3", "date": "2026-03-05", "written_by": "independent", "quote": "These systems reduced birthing accidents and increased both productivity and farmer income, demonstrating AI's positive impact on livestock management in South Korea's Gyeonggi Province." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0202-source-0001", "AIBD-0202-source-0002", "AIBD-0202-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "이승호. AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\". 더팩트 (The Fact), 6 March 2026.", "title": "AI와 ICT로 돼지 키운다…경기도농기원 \"출하 소득↑ 분만 사고↓\"", "url": "https://news.tf.co.kr/read/national/2299220.htm", "date": "2026-03-06", "written_by": "independent", "quote": "이 결과 출하일령이 182.3일에서 176.7일로 5.6일 줄었다." }, { "kind": "news report", "citation": "신연경. 도농기원, AI 기술로 경기지역 농가서 스마트축산 실현. 중부일보 (Joongboo Ilbo), 8 March 2026.", "title": "도농기원, AI 기술로 경기지역 농가서 스마트축산 실현", "url": "https://www.joongboo.com/news/articleView.html?idxno=363719065", "date": "2026-03-08", "written_by": "independent", "quote": "두당 소득은 1두 10만 원에서 11만8천 원으로 18% 증가했다." }, { "kind": "registry label", "citation": "OECD.AI AI Incidents and Hazards Monitor. AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province. Record 2026-03-05-1ac3.", "title": "AI Systems Reduce Livestock Accidents and Boost Farmer Income in Gyeonggi Province", "url": "https://oecd.ai/en/incidents/2026-03-05-1ac3", "date": "2026-03-05", "written_by": "independent", "quote": "These systems reduced birthing accidents and increased both productivity and farmer income, demonstrating AI's positive impact on livestock management in South Korea's Gyeonggi Province." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "2025 provincial pilot on six farms in Anseong, Pocheon and Yeoju: AI non-contact weighing cut shipping age 182.3 to 176.7 days, lifted 1+ grade share 35.3 to 37.7% and income per head 18%.", "account": "Gyeonggi-do Agricultural Research and Extension Services announced the results of its 2025 livestock AI pilot on 6 March 2026. The Fact reported it with a Suwon dateline, and Joongboo Ilbo on 8 March. A fattening-pig shipping selection system uses AI to measure pigs' weight without contact and advise the optimal shipping date. It was introduced on six farms in Anseong, Pocheon and Yeoju. Shipping age fell from 182.3 to 176.7 days, a drop of 5.6 days. The share shipped at grade 1+ rose from 35.3% to 37.7%, up 2.4 percentage points. Income per head rose from 100,000 to 118,000 won, up 18%. A sow farrowing management system using ICT equipment for real-time monitoring was introduced on Pocheon farms. It cut the sow accident rate from 3.1% to 2.7%; those accidents are mastitis, fever, loss of appetite and crushing of piglets. Piglets shipped per sow per year rose from 18.3 to 19.2, up 4.9%. Real-time alerts reduced the need to stay in the barn. Lee Jun-bae, head of the agency's technology dissemination division, said the results confirmed AI as a way to raise productivity and income. The agency plans to extend the weighing system to Yeoncheon in 2026. The vendor of the systems is not named. The pilot is listed in the OECD AI Incidents Monitor." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fattening-pig shipping selection system (AI non-contact weighing) and sow farrowing management system (ICT monitoring)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not named in the sources" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Gyeonggi ARES AI pig-weighing pilot cuts shipping age 5.6 days and lifts income per head 18% on six farms", "headline": "Gyeonggi AI pig-weighing pilot lifts income per head 18%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "12d95b8f75b460405f62c3229035e3bf716a895661fd05da72c067575be6d068" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Gyeonggi-do Agricultural Research and Extension Services announced the results of its 2025 livestock AI pilot on 6 March 2026. The Fact reported it with a Suwon dateline, and Joongboo Ilbo on 8 March. A fattening-pig shipping selection system uses AI to measure pigs' weight without contact and advise the optimal shipping date. It was introduced on six farms in Anseong, Pocheon and Yeoju. Shipping age fell from 182.3 to 176.7 days, a drop of 5.6 days. The share shipped at grade 1+ rose from 35.3% to 37.7%, up 2.4 percentage points. Income per head rose from 100,000 to 118,000 won, up 18%. A sow farrowing management system using ICT equipment for real-time monitoring was introduced on Pocheon farms. It cut the sow accident rate from 3.1% to 2.7%; those accidents are mastitis, fever, loss of appetite and crushing of piglets. Piglets shipped per sow per year rose from 18.3 to 19.2, up 4.9%. Real-time alerts reduced the need to stay in the barn. Lee Jun-bae, head of the agency's technology dissemination division, said the results confirmed AI as a way to raise productivity and income. The agency plans to extend the weighing system to Yeoncheon in 2026. The vendor of the systems is not named. The pilot is listed in the OECD AI Incidents Monitor.", "replication": { "produced_by": [ "A provincial extension pilot funded in 2025", "Six commercial pig farms adopting non-contact AI weighing", "A grading system that pays a premium for grade 1+ pigs" ], "must_hold": [ "Farm staff acting on the shipping-date advice", "Real-time alerts reaching farmers from the sow system" ], "echoes": [ { "date": "2026-03-08", "setting": "Yeoncheon, Gyeonggi: planned 2026 extension of the weighing system targeting a higher grade 1+ rate", "model_version": "same system", "outcome": "unknown", "source": "Joongboo Ilbo, 8 March 2026" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0553", "title": "Leeds City Council and Xylo: transforming planning with AI", "summary": "Leeds reports over 40% more applications processed per officer, less research time, and improved officer wellbeing during its Xylo pilot.", "date_observed": "2026-03-12", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-013", "account": "Leeds and Xylo developed a workspace that helps planning officers research applications and prepare material for human review. The council reports that its pilot began with eight officers and later expanded to 20. Officer interviews and usage data reportedly showed over 40% more householder and minor applications processed monthly per officer, less research work, and improved wellbeing. Xylo cofounder Habs Isabelle Kim had reported a 40% increase against a control group on March 12, 2026. Neither account provides the throughput denominator, group assignment, baseline totals, or analysis needed to assess that comparison. The reported accuracy improvement concerns officers’ judgments of their work, rather than an independently measured change in decision accuracy. Xylo’s separate March 11 account describes six officers and 33 pre-applications using Patch. That sample cannot automatically be treated as the denominator for the Core throughput result. The council’s earlier technical disclosure names the language models and requires officers to review the generated material. These are original accounts from the council and supplier, without an independent evaluation of the reported benefit.", "category": "general benefit", "unexpected": false, "purpose": "Help planning officers find and process relevant information while retaining professional judgment.", "system": "Xylo Core AI planning workspace", "model_version": "The November 27, 2025 council disclosure lists gpt-5-2025-08-07, gemini-2.5-pro, and claude-sonnet-4@20250514. Versions used for individual reported results are unspecified.", "developer": "Xylo", "deployer": "Leeds City Council", "location": "United Kingdom", "domain": "Planning administration", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Reported application throughput rises by over 40%, supporting a measurable service-capability gain." }, { "group": "personal", "depth": 2, "reason": "All surveyed officers reportedly experienced improved stress and energy levels, alongside less research work. These are reported wellbeing/work-capability improvements without a demonstrated lasting change." } ], "ai_role": { "status": "assessed", "statement": "The council describes retrieval of relevant planning material and API calls to language models that generate suggestions and draft text for officer review. Its November 2025 disclosure identifies GPT-5, Gemini 2.5 Pro, and Claude Sonnet 4. The models do not determine planning merits. Reported changes in work and wellbeing come from project-side interviews and usage data. A supplier-reported control group lacks sufficient published methods to establish an independent causal comparison." }, "evidence": [ { "kind": "report", "citation": "Leeds City Council and Xylo, published by the Local Government Association. Leeds City Council and Xylo: transforming planning with AI. 2026-05-08. Sections “The collaborative process,” “Successes and results,” and “Risk identification and mitigation.” Original project account with pilot participation and outcome figures; no underlying evaluation dataset or independent assessment.", "title": "Leeds City Council and Xylo: transforming planning with AI", "url": "https://www.local.gov.uk/case-studies/leeds-city-council-and-xylo-transforming-planning-ai", "date": "2026-05-08", "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Habs Isabelle Kim, Xylo cofounder. Leeds planning pilot: 40% more applications than the control group. 2026-03-12. Original supplier account of results presented alongside Leeds planning officer Benedict Barnett. Page metadata gives March 12, 2026, 11:05:31 UTC. Adds the control-group claim and earlier chronology, without disclosing methods.", "title": "Leeds planning pilot: 40% more applications than the control group", "url": "https://www.linkedin.com/posts/habin-isa_our-pilot-officers-processed-40-more-planning-activity-7437816039079489537-z4dP", "date": "2026-03-12", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Leeds City Council and Xylo. Leeds City Council: Xylo Core. 2025-11-27. Algorithmic Transparency Recording Standard, §§2.1, 3.2–3.3, 4.1–4.2, and 5.1–5.2. Original council/supplier disclosure of system design, named model versions, human review, and risks. Publication on GOV.UK is not independent regulatory confirmation of the outcomes.", "title": "Leeds City Council: Xylo Core", "url": "https://www.gov.uk/algorithmic-transparency-records/leeds-city-council-xylo-core", "date": "2025-11-27", "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Xylo. 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Contents not reviewed." } ], "limitations": [ "The disclosed versions are a November 2025 snapshot, not a version log for individual outcome measurements.", "The ATRS entry is a deployer/supplier submission, not a regulator’s evaluation of the benefit.", "The LGA mentions an opportunities report, privacy/AI white paper, DPIA, and responsible-AI assessment; complete underlying files were not provided in the reviewed pages.", "Generic model cards and planning-policy input datasets linked by the ATRS entry document components and inputs; they do not independently establish the local pilot results." ], "source_ref": "AIBD-0553-source-0003" }, { "claim": "Sample distinction for pre-application results", "source_chain": [ { "url": "https://www.linkedin.com/posts/buildxylo_using-xylo-cut-down-the-time-i-spent-on-activity-7437461682311925760-Oc3w", "locator": "Main post: Patch, six officers, 33 pre-applications; datePublished metadata", "role": "Original supplier account of a related but separately described pilot", "access_status": "Full relevant text reviewed", "published_on": "2026-03-11" } ], "limitations": [ "The relationship between this sample and the LGA outcome percentages is not specified. Do not use the six-officer sample as a known Core throughput denominator.", "The current post is marked edited; the text at original publication is not independently archived." ], "source_ref": "AIBD-0553-source-0004" } ], "limitations": [ "No independent evaluation or publicly inspectable underlying outcome dataset was found.", "The technical overview requires Google Drive access; complete internal assessments, pilot calculations, and outcome denominators remain unavailable." ], "chronology_source": { "url": "https://www.linkedin.com/posts/habin-isa_our-pilot-officers-processed-40-more-planning-activity-7437816039079489537-z4dP", "title": "Leeds planning pilot: 40% more applications than the control group", "date": "2026-03-12", "timestamp": "2026-03-12T11:05:31.637Z", "basis": "Original post metadata; first verified report of the central throughput claim." } } }, "provenance": { "kind": "source_review", "basis": "Traced the original project reports, corrected publication chronology to March 12, 2026, identified disclosed model versions, and distinguished pilot participation from unpublished outcome denominators.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0553-source-0001", "AIBD-0553-source-0002", "AIBD-0553-source-0003", "AIBD-0553-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The council’s account has no independent evaluation or public dataset of outcomes. The technical overview, complete internal assessments, and pilot calculations were inaccessible.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Leeds reports over 40% more applications processed per officer, less research time, and improved officer wellbeing during its Xylo pilot.", "account": "Leeds and Xylo developed a workspace that helps planning officers research applications and prepare material for human review. The council reports that its pilot began with eight officers and later expanded to 20. Officer interviews and usage data reportedly showed over 40% more householder and minor applications processed monthly per officer, less research work, and improved wellbeing. Xylo cofounder Habs Isabelle Kim had reported a 40% increase against a control group on March 12, 2026. Neither account provides the throughput denominator, group assignment, baseline totals, or analysis needed to assess that comparison. The reported accuracy improvement concerns officers’ judgments of their work, rather than an independently measured change in decision accuracy. Xylo’s separate March 11 account describes six officers and 33 pre-applications using Patch. That sample cannot automatically be treated as the denominator for the Core throughput result. The council’s earlier technical disclosure names the language models and requires officers to review the generated material. These are original accounts from the council and supplier, without an independent evaluation of the reported benefit." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. 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No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The council’s November 2025 disclosure listed gpt-5-2025-08-07, gemini-2.5-pro, and claude-sonnet-4@20250514." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "The council listed GPT-5, Gemini 2.5 Pro, and Claude Sonnet 4." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The council listed GPT-5, Gemini 2.5 Pro, and Claude Sonnet 4.", "editor_note": "The council’s disclosure dated 27 November 2025 lists these models. It does not identify which model produced each reported result." } }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "The November 27, 2025 council disclosure lists gpt-5-2025-08-07, gemini-2.5-pro, and claude-sonnet-4@20250514. Versions used for individual reported results are unspecified." } }, "provenance": { "kind": "source_review", "basis": "Council/supplier ATRS disclosure, November 27, 2025, §§4.2.1–4.2.2. Per-result model versions remain unspecified.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0553-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The council’s disclosure of 27 November 2025 lists gpt-5-2025-08-07, gemini-2.5-pro, and claude-sonnet-4@20250514. It does not connect individual results to one of those releases.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Xylo Core AI planning workspace" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Xylo" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Leeds City Council and Xylo: transforming planning with AI", "headline": "Leeds reports more planning applications processed with Xylo" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "547cdd694349861b4afbe0dddffb6a16bd6730437c4352c4ed41516726b28719" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Leeds and Xylo developed a workspace that helps planning officers research applications and prepare material for human review. The council reports that its pilot began with eight officers and later expanded to 20. Officer interviews and usage data reportedly showed over 40% more householder and minor applications processed monthly per officer, less research work, and improved wellbeing. Xylo cofounder Habs Isabelle Kim had reported a 40% increase against a control group on March 12, 2026. Neither account provides the throughput denominator, group assignment, baseline totals, or analysis needed to assess that comparison. The reported accuracy improvement concerns officers’ judgments of their work, rather than an independently measured change in decision accuracy. Xylo’s separate March 11 account describes six officers and 33 pre-applications using Patch. That sample cannot automatically be treated as the denominator for the Core throughput result. The council’s earlier technical disclosure names the language models and requires officers to review the generated material. These are original accounts from the council and supplier, without an independent evaluation of the reported benefit.", "replication": { "produced_by": [ "Leeds and Xylo co-designed and tested the workspace over more than six months.", "The reported pilot focused on time, work quality, and officer wellbeing." ], "must_hold": [ "Local planning policies and application material are available and kept current for retrieval.", "Planning officers review generated suggestions against the original material and retain responsibility for decisions.", "Integration limits, officer training, and the time required for review affect the achievable gains." ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0553-source-0001", "AIBD-0553-source-0002", "AIBD-0553-source-0003", "AIBD-0553-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 5, "record_mapped": 30, "not_assessed": 56, "complete": false, "by_state": { "value_present": 35, "not_reported": 0, "unresolved": 0, "not_assessed": 56, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0158", "title": "Paul Conyngham uses ChatGPT and AlphaFold to choose targets for a personalized mRNA vaccine that UNSW made for his dog Rosie's mast cell cancer; her largest tumor halved", "summary": "AI-chosen targets, a UNSW-made mRNA vaccine and a checkpoint inhibitor halved Rosie's largest tumor by early 2026; partial, not a cure.", "date_observed": "2026-03-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Paul Conyngham, a Sydney machine-learning engineer, used ChatGPT to plan treatment for his dog Rosie. Rosie is an eight-year-old Staffy-Shar Pei cross with mast cell cancer diagnosed in 2024. He used AlphaFold to model mutated proteins from tumor sequencing he paid $3,000 for at UNSW's Ramaciotti Centre for Genomics. He chose neoantigen targets and confirmed them “again using AI”. Pall Thordarson's UNSW RNA Institute made the mRNA vaccine in under two months. Rachel Allavena of the University of Queensland injected it at Gatton in December 2025, with a checkpoint inhibitor, and gave a booster in February 2026. The tennis-ball-sized tumor on Rosie's hock halved, and she was chasing rabbits by late January 2026. Some tumors did not respond. By August 2026 the cancer had returned after a later surgery.", "category": "benefit created", "unexpected": false, "purpose": "ChatGPT is a general-purpose assistant and AlphaFold a protein-structure predictor. Conyngham used the first to plan and navigate the veterinary and genomic work. He used the second to model mutated proteins as candidate targets. Both are uses within what each tool was built to do. Neither was built to treat Rosie. The vaccine was designed by Conyngham, made by UNSW and given by a veterinary school. The therapeutic response is a downstream use of the tools rather than their product purpose.", "system": "ChatGPT (OpenAI) and AlphaFold (Google DeepMind), with Grok (xAI) reported for the final mRNA construct, used with Conyngham's own analysis to select tumor neoantigen targets for a personalized mRNA vaccine", "model_version": null, "developer": "OpenAI (ChatGPT); Google DeepMind (AlphaFold); xAI (Grok)", "deployer": "Paul Conyngham (owner), with UNSW's Ramaciotti Centre for Genomics (sequencing), the UNSW RNA Institute (vaccine manufacture) and the University of Queensland School of Veterinary Science, Gatton (administration)", "location": "Sydney, Australia", "domain": "Veterinary oncology / personalized mRNA vaccine design", "segment": "Companion animal with mast cell cancer", "benefit_type": "Improved Physical Health", "taxonomy_note": "The patient is a dog; Trustible's health type is written for people.", "registry_ids": { "oecd_aim": "2026-03-15-f424" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Rosie was given months to live after surgery and chemotherapy. Her largest tumor halved and she regained mobility by late January 2026. Per ABC on 22 June 2026, she was still running and playing. The response was partial and confounded by a checkpoint inhibitor, and her cancer later returned." }, { "group": "organizational", "depth": 1, "reason": "UNSW's RNA Institute and Ramaciotti Center got what Thordarson called the first personalized cancer vaccine designed for a dog. They describe the case as a milestone. Conyngham's spin-out GAMGEE raised a $4 million seed round in August 2026 on the strength of it." } ], "ai_role": { "status": "assessed", "statement": "The AI tools worked at the design stage. ChatGPT suggested immunotherapy, pointed Conyngham to UNSW's genomics center and helped him plan the analysis. AlphaFold modeled mutated proteins. He says he “confirmed, again using AI, that those targets were good cancer candidates”. Humans sequenced the genome (Martin Smith), made the mRNA and nanoparticles (Pall Thordarson) and injected it (Rachel Allavena). A checkpoint inhibitor was given at the same time. UNSW says “We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine”. The AI's share of the outcome therefore cannot be isolated. It is a single uncontrolled case, and no outcome data have been published outside interviews and statements." }, "evidence": [ { "kind": "press release", "citation": "Melville, T. / UNSW Sydney (2026). Meet the man who designed a cancer vaccine for his dog. UNSW Newsroom, 17 March 2026.", "title": "Meet the man who designed a cancer vaccine for his dog", "url": "https://news.unsw.edu.au/en/meet-the-man-who-designed-a-cancer-vaccine-for-his-dog", "date": "2026-03-17", "written_by": "deployer", "quote": "We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine." }, { "kind": "news report", "citation": "Ma, J. / Fortune (2026). A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog. Fortune, 15 March 2026.", "title": "A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog", "url": "https://fortune.com/2026/03/15/australian-tech-entrepreneur-ai-cancer-vaccine-dog-rosie-unsw-mrna/", "date": "2026-03-15", "written_by": "independent", "quote": "Rosie got her first injection of the cancer treatment this past December, then received a booster in February." }, { "kind": "news report", "citation": "Bita, N. / The Australian, republished by Stockhead (2026). Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog. Stockhead, 18 March 2026.", "title": "Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog", "url": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/", "date": "2026-03-18", "written_by": "independent", "quote": "Mr Conyngham drove 10 hours with Rosie for her first injection in December, followed by a booster shot last month and another due next week." }, { "kind": "other", "citation": "Stebbing, J. / The Conversation (2026). A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution. The Conversation, 20 March 2026 (academic commentary).", "title": "A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution", "url": "https://theconversation.com/a-man-used-ai-to-help-make-a-cancer-vaccine-for-his-dog-an-oncologist-urges-caution-278735", "date": "2026-03-20", "written_by": "independent", "quote": "several tumours shrank markedly, her overall tumour burden fell, and her energy and behaviour improved" }, { "kind": "news report", "citation": "Roberts, R. / The Scientist (2026). ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer. The Scientist, online 16 March 2026, June 2026 issue.", "title": "ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer", "url": "https://www.the-scientist.com/chatgpt-and-alphafold-help-design-personalized-vaccine-for-dog-with-cancer-74227", "date": "2026-03-16", "written_by": "independent", "quote": "it is difficult to disentangle which of the treatments had the greatest effect." }, { "kind": "news report", "citation": "AFP via Phys.org (2026). One man, his dog, and ChatGPT: Australia's AI vaccine saga. Phys.org, 30 March 2026.", "title": "One man, his dog, and ChatGPT: Australia's AI vaccine saga", "url": "https://phys.org/news/2026-03-dog-chatgpt-australia-ai-vaccine.html", "date": "2026-03-30", "written_by": "independent", "quote": "This was not a clinical trial by any means" }, { "kind": "news report", "citation": "Kim, S. / Newsweek (2026). Owner With No Medical Background Invents Cure for Dog's Terminal Cancer. Newsweek, 16 March 2026.", "title": "Owner With No Medical Background Invents Cure for Dog's Terminal Cancer", "url": "https://www.newsweek.com/owner-no-medical-background-invents-cure-dogs-terminal-cancer-11684882", "date": "2026-03-16", "written_by": "independent", "quote": "And, toward the end of January, she was jumping over a fence to chase a rabbit." }, { "kind": "news report", "citation": "Bailey, R. / Reason (2026). Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer. Reason, 19 March 2026.", "title": "Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer", "url": "https://reason.com/2026/03/19/man-successfully-designs-mrna-vaccine-to-treat-his-dogs-cancer/", "date": "2026-03-19", "written_by": "independent", "quote": "If we can do this for a dog, why aren't we rolling this out to all humans with cancer?" }, { "kind": "news report", "citation": "Davis, M. / ABC News (2026). AI designs cancer vaccine for dog but scientists says red tape a barrier for human care. ABC News, 22 June 2026.", "title": "AI designs cancer vaccine for dog but scientists says red tape a barrier for human care", "url": "https://www.abc.net.au/news/2026-06-22/australian-dog-cancer-treated-via-mrna-vaccine-and-ai/106692668", "date": "2026-06-22", "written_by": "independent", "quote": "AI did not cure Rosie's cancer, nor did it create or administer the vaccine" }, { "kind": "news report", "citation": "Palmer, A. / Medical Daily (2026). Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million. Medical Daily, 18 August 2026.", "title": "Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million", "url": "https://www.medicaldaily.com/rosie-dog-ai-mrna-cancer-vaccine-gamgee-launch-477500", "date": "2026-08-18", "written_by": "independent", "quote": "Rosie entered remission, but her cancer returned following a later surgery." }, { "kind": "press release", "citation": "GAMGEE via GlobeNewswire (2026). One Dog's Legacy Becomes GAMGEE. GlobeNewswire press release, Sydney, 17 August 2026, as carried by Yahoo Finance.", "title": "One Dog's Legacy Becomes GAMGEE", "url": "https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "date": "2026-08-17", "written_by": "deployer", "quote": "While her story may have ended, her legacy lives on in the work that followed." } ], "replication": { "produced_by": [ "Whole-genome sequencing of tumor and healthy tissue, about 150 billion DNA letters for $3,000, from which neoantigen targets could be chosen with AI help.", "An academic RNA facility, the UNSW RNA Institute, willing to make a custom mRNA vaccine from an owner-designed sequence in under two months.", "A veterinary school with ethics cover and an immunotherapy specialist to administer it, after about three months of ethics paperwork.", "An owner with 17 years of machine-learning experience able to run the process, pay for it and drive ten hours for each dose." ], "must_hold": [ "The response cannot be credited to the vaccine alone. A checkpoint inhibitor was given at the same time, and UNSW says the split is unknown.", "One uncontrolled animal. Mast cell tumors behave unpredictably, and some of Rosie's tumors did not respond.", "The benefit was time, not cure. The cancer returned after a later surgery, and the company founded on the case wrote in August 2026 that her story may have ended." ], "echoes": [] }, "paired_incident": null, "headline": "ChatGPT and AlphaFold pick vaccine targets; dog's tumor halves", "metric": "halved Rosie's largest tumor by early 2026", "comparator": { "against": "veterinary chemotherapy and surgery given before the vaccine", "before": "slowed but failed to shrink the tumours", "after": "the tennis ball-sized tumour on Rosie’s hock has shrunk in half", "basis": "assumed", "quote": "Heartbroken when his fur-baby was diagnosed with a deadly mast cell cancer in 2024, Mr ­Conyngham threw thousands of dollars at veterinary chemotherapy and surgery, which slowed but failed to shrink the tumours. Now, after treatment with a custom mRNA cancer vaccine over the Christmas break, the tennis ball-sized tumour on Rosie’s hock has shrunk in half, in a recovery that has astounded researchers at the cutting-edge of human cancer treatments.", "url": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/" }, "later": { "status": "reversed", "date": "2026-08-17", "note": "The GAMGEE launch release of 17 August 2026 says Rosie's cancer returned after a later surgery and writes of her in the past tense.", "quote": "Rosie entered remission, but her cancer returned following a later surgery.", "url": "https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and eleven sources on file: UNSW's newsroom story of 17 March 2026, The Australian's report by Natasha Bita as republished by Stockhead, Fortune, The Conversation (Justin Stebbing, Anglia Ruskin University), The Scientist, AFP via Phys.org, Newsweek, Reason, ABC News of 22 June 2026, Medical Daily of 18 August 2026 and GAMGEE's GlobeNewswire release, marked written by the makers because the company was founded by Conyngham on this case. Kept at benefit created or restored: a therapeutic response for one identifiable animal and her owner, not a prevented specified harm; the Monitor labels it an incident with harm type health impact. Dates: the first injection was in December 2025 and the booster in February 2026 per The Australian (“last month” in a piece dated 18 March) and Fortune; Medical Daily says “the following month”; no source gives a day, so, as for AIBD-0052, the Monitor's date, which is Fortune's report date, is used. Outcome figures differ by speaker: Allavena “probably halved” for the hock tumor; Conyngham “about 75 percent of the cancer” on Today; UNSW “partial response”. A checkpoint inhibitor was given with the vaccine (UNSW, The Scientist, AFP), which is why the system's part says the split is unknown. WinBuzzer's “December 2024” is contradicted by every other source and not used. The Australian (the original of 13 March and a 26 June 2026 piece whose headline in a Google News feed reads “Rescue dog dies after owner's pioneering AI cancer fight”), The Verge, news.com.au, Daily Mail and NY Post could not be read; the death is therefore not asserted in the account, which records the relapse reported by Medical Daily and GAMGEE. The WebSearch budget was exhausted, so sources were found through the Monitor's link list and Google and Bing news feeds.", "source": "https://oecd.ai/en/incidents/2026-03-15-f424", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/; https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: eight independent news reports, one other independent source and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0158", "catalog_version": "1.0.0", "source_fingerprint": "1a21cd2cdf56ace508c40de6d3b87e3a17d0d57899f0cfcce9bb7c49722ccd36", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0158-source-0001", "AIBD-0158-source-0002", "AIBD-0158-source-0003", "AIBD-0158-source-0004", "AIBD-0158-source-0005", "AIBD-0158-source-0006", "AIBD-0158-source-0007", "AIBD-0158-source-0008", "AIBD-0158-source-0009", "AIBD-0158-source-0010", "AIBD-0158-source-0011" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI (ChatGPT); Google DeepMind (AlphaFold); xAI (Grok)", "deployer": "Paul Conyngham (owner), with UNSW's Ramaciotti Centre for Genomics (sequencing), the UNSW RNA Institute (vaccine manufacture) and the University of Queensland School of Veterinary Science, Gatton (administration)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI tools worked at the design stage. ChatGPT suggested immunotherapy, pointed Conyngham to UNSW's genomics center and helped him plan the analysis. AlphaFold modeled mutated proteins. He says he “confirmed, again using AI, that those targets were good cancer candidates”. Humans sequenced the genome (Martin Smith), made the mRNA and nanoparticles (Pall Thordarson) and injected it (Rachel Allavena). A checkpoint inhibitor was given at the same time. UNSW says “We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine”. The AI's share of the outcome therefore cannot be isolated. It is a single uncontrolled case, and no outcome data have been published outside interviews and statements." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Conyngham used ChatGPT to plan the investigation and AlphaFold to model mutated proteins when selecting targets for a personalized cancer vaccine for his dog. Grok was also reported as assisting with the final mRNA construct.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The AI tools worked at the design stage. ChatGPT suggested immunotherapy, pointed Conyngham to UNSW's genomics center and helped him plan the analysis. AlphaFold modeled mutated proteins. He says he “confirmed, again using AI, that those targets were good cancer candidates”. Humans sequenced the genome (Martin Smith), made the mRNA and nanoparticles (Pall Thordarson) and injected it (Rachel Allavena). A checkpoint inhibitor was given at the same time. UNSW says “We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine”. The AI's share of the outcome therefore cannot be isolated. It is a single uncontrolled case, and no outcome data have been published outside interviews and statements." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Rosie was given months to live after surgery and chemotherapy. Her largest tumor halved and she regained mobility by late January 2026. Per ABC on 22 June 2026, she was still running and playing. The response was partial and confounded by a checkpoint inhibitor, and her cancer later returned." }, { "group": "organizational", "depth": 1, "reason": "UNSW's RNA Institute and Ramaciotti Center got what Thordarson called the first personalized cancer vaccine designed for a dog. They describe the case as a milestone. Conyngham's spin-out GAMGEE raised a $4 million seed round in August 2026 on the strength of it." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: eight independent news reports, one other independent source and two press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Rosie was given months to live after surgery and chemotherapy. Her largest tumor halved and she regained mobility by late January 2026. Per ABC on 22 June 2026, she was still running and playing. The response was partial and confounded by a checkpoint inhibitor, and her cancer later returned." }, { "group": "organizational", "depth": 1, "reason": "UNSW's RNA Institute and Ramaciotti Center got what Thordarson called the first personalized cancer vaccine designed for a dog. They describe the case as a milestone. Conyngham's spin-out GAMGEE raised a $4 million seed round in August 2026 on the strength of it." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Rosie was given months to live after surgery and chemotherapy. Her largest tumor halved and she regained mobility by late January 2026. Per ABC on 22 June 2026, she was still running and playing. The response was partial and confounded by a checkpoint inhibitor, and her cancer later returned." }, { "group": "organizational", "depth": 1, "reason": "UNSW's RNA Institute and Ramaciotti Center got what Thordarson called the first personalized cancer vaccine designed for a dog. They describe the case as a milestone. Conyngham's spin-out GAMGEE raised a $4 million seed round in August 2026 on the strength of it." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "halved Rosie's largest tumor by early 2026", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "The dog received a checkpoint inhibitor alongside the vaccine. UNSW said that the contribution of each treatment was unknown. The uncontrolled account does not isolate AI’s contribution, and the reported results come from interviews and statements.", "editor_note": "" } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-03-15-f424" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "reversed", "date": "2026-08-17", "note": "The GAMGEE launch release of 17 August 2026 says Rosie's cancer returned after a later surgery and writes of her in the past tense.", "quote": "Rosie entered remission, but her cancer returned following a later surgery.", "url": "https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Researchers sequenced the tumor and manufactured the vaccine. A veterinarian administered the treatment." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0158" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The patient is a dog; Trustible's health type is written for people." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Paul Conyngham, a Sydney machine-learning engineer, used ChatGPT to plan treatment for his dog Rosie. Rosie is an eight-year-old Staffy-Shar Pei cross with mast cell cancer diagnosed in 2024. He used AlphaFold to model mutated proteins from tumor sequencing he paid $3,000 for at UNSW's Ramaciotti Centre for Genomics. He chose neoantigen targets and confirmed them “again using AI”. Pall Thordarson's UNSW RNA Institute made the mRNA vaccine in under two months. Rachel Allavena of the University of Queensland injected it at Gatton in December 2025, with a checkpoint inhibitor, and gave a booster in February 2026. The tennis-ball-sized tumor on Rosie's hock halved, and she was chasing rabbits by late January 2026. Some tumors did not respond. By August 2026 the cancer had returned after a later surgery.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "Rosie was given months to live after surgery and chemotherapy. Her largest tumor halved and she regained mobility by late January 2026. Per ABC on 22 June 2026, she was still running and playing. The response was partial and confounded by a checkpoint inhibitor, and her cancer later returned." }, { "group": "organizational", "depth": 1, "reason": "UNSW's RNA Institute and Ramaciotti Center got what Thordarson called the first personalized cancer vaccine designed for a dog. They describe the case as a milestone. Conyngham's spin-out GAMGEE raised a $4 million seed round in August 2026 on the strength of it." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ChatGPT is a general-purpose assistant and AlphaFold a protein-structure predictor. Conyngham used the first to plan and navigate the veterinary and genomic work. He used the second to model mutated proteins as candidate targets. Both are uses within what each tool was built to do. Neither was built to treat Rosie. The vaccine was designed by Conyngham, made by UNSW and given by a veterinary school. The therapeutic response is a downstream use of the tools rather than their product purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Sydney, Australia", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose assistant and AlphaFold a protein-structure predictor. Conyngham used the first to plan and navigate the veterinary and genomic work. He used the second to model mutated proteins as candidate targets. Both are uses within what each tool was built to do. Neither was built to treat Rosie. The vaccine was designed by Conyngham, made by UNSW and given by a veterinary school. The therapeutic response is a downstream use of the tools rather than their product purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-15", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and eleven sources on file: UNSW's newsroom story of 17 March 2026, The Australian's report by Natasha Bita as republished by Stockhead, Fortune, The Conversation (Justin Stebbing, Anglia Ruskin University), The Scientist, AFP via Phys.org, Newsweek, Reason, ABC News of 22 June 2026, Medical Daily of 18 August 2026 and GAMGEE's GlobeNewswire release, marked written by the makers because the company was founded by Conyngham on this case. Kept at benefit created or restored: a therapeutic response for one identifiable animal and her owner, not a prevented specified harm; the Monitor labels it an incident with harm type health impact. Dates: the first injection was in December 2025 and the booster in February 2026 per The Australian (“last month” in a piece dated 18 March) and Fortune; Medical Daily says “the following month”; no source gives a day, so, as for AIBD-0052, the Monitor's date, which is Fortune's report date, is used. Outcome figures differ by speaker: Allavena “probably halved” for the hock tumor; Conyngham “about 75 percent of the cancer” on Today; UNSW “partial response”. A checkpoint inhibitor was given with the vaccine (UNSW, The Scientist, AFP), which is why the system's part says the split is unknown. WinBuzzer's “December 2024” is contradicted by every other source and not used. The Australian (the original of 13 March and a 26 June 2026 piece whose headline in a Google News feed reads “Rescue dog dies after owner's pioneering AI cancer fight”), The Verge, news.com.au, Daily Mail and NY Post could not be read; the death is therefore not asserted in the account, which records the relapse reported by Medical Daily and GAMGEE. The WebSearch budget was exhausted, so sources were found through the Monitor's link list and Google and Bing news feeds.", "source": "https://oecd.ai/en/incidents/2026-03-15-f424", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/; https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Whole-genome sequencing of tumor and healthy tissue, about 150 billion DNA letters for $3,000, from which neoantigen targets could be chosen with AI help.", "An academic RNA facility, the UNSW RNA Institute, willing to make a custom mRNA vaccine from an owner-designed sequence in under two months.", "A veterinary school with ethics cover and an immunotherapy specialist to administer it, after about three months of ethics paperwork.", "An owner with 17 years of machine-learning experience able to run the process, pay for it and drive ten hours for each dose." ], "must_hold": [ "The response cannot be credited to the vaccine alone. A checkpoint inhibitor was given at the same time, and UNSW says the split is unknown.", "One uncontrolled animal. Mast cell tumors behave unpredictably, and some of Rosie's tumors did not respond.", "The benefit was time, not cure. The cancer returned after a later surgery, and the company founded on the case wrote in August 2026 that her story may have ended." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and eleven sources on file: UNSW's newsroom story of 17 March 2026, The Australian's report by Natasha Bita as republished by Stockhead, Fortune, The Conversation (Justin Stebbing, Anglia Ruskin University), The Scientist, AFP via Phys.org, Newsweek, Reason, ABC News of 22 June 2026, Medical Daily of 18 August 2026 and GAMGEE's GlobeNewswire release, marked written by the makers because the company was founded by Conyngham on this case. Kept at benefit created or restored: a therapeutic response for one identifiable animal and her owner, not a prevented specified harm; the Monitor labels it an incident with harm type health impact. Dates: the first injection was in December 2025 and the booster in February 2026 per The Australian (“last month” in a piece dated 18 March) and Fortune; Medical Daily says “the following month”; no source gives a day, so, as for AIBD-0052, the Monitor's date, which is Fortune's report date, is used. Outcome figures differ by speaker: Allavena “probably halved” for the hock tumor; Conyngham “about 75 percent of the cancer” on Today; UNSW “partial response”. A checkpoint inhibitor was given with the vaccine (UNSW, The Scientist, AFP), which is why the system's part says the split is unknown. WinBuzzer's “December 2024” is contradicted by every other source and not used. The Australian (the original of 13 March and a 26 June 2026 piece whose headline in a Google News feed reads “Rescue dog dies after owner's pioneering AI cancer fight”), The Verge, news.com.au, Daily Mail and NY Post could not be read; the death is therefore not asserted in the account, which records the relapse reported by Medical Daily and GAMGEE. The WebSearch budget was exhausted, so sources were found through the Monitor's link list and Google and Bing news feeds.", "source": "https://oecd.ai/en/incidents/2026-03-15-f424", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/; https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Veterinary oncology / personalized mRNA vaccine design", "segment": "Companion animal with mast cell cancer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Melville, T. / UNSW Sydney (2026). Meet the man who designed a cancer vaccine for his dog. UNSW Newsroom, 17 March 2026.", "title": "Meet the man who designed a cancer vaccine for his dog", "url": "https://news.unsw.edu.au/en/meet-the-man-who-designed-a-cancer-vaccine-for-his-dog", "date": "2026-03-17", "written_by": "deployer", "quote": "We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine." }, { "kind": "news report", "citation": "Ma, J. / Fortune (2026). A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog. Fortune, 15 March 2026.", "title": "A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog", "url": "https://fortune.com/2026/03/15/australian-tech-entrepreneur-ai-cancer-vaccine-dog-rosie-unsw-mrna/", "date": "2026-03-15", "written_by": "independent", "quote": "Rosie got her first injection of the cancer treatment this past December, then received a booster in February." }, { "kind": "news report", "citation": "Bita, N. / The Australian, republished by Stockhead (2026). Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog. Stockhead, 18 March 2026.", "title": "Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog", "url": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/", "date": "2026-03-18", "written_by": "independent", "quote": "Mr Conyngham drove 10 hours with Rosie for her first injection in December, followed by a booster shot last month and another due next week." }, { "kind": "other", "citation": "Stebbing, J. / The Conversation (2026). A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution. The Conversation, 20 March 2026 (academic commentary).", "title": "A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution", "url": "https://theconversation.com/a-man-used-ai-to-help-make-a-cancer-vaccine-for-his-dog-an-oncologist-urges-caution-278735", "date": "2026-03-20", "written_by": "independent", "quote": "several tumours shrank markedly, her overall tumour burden fell, and her energy and behaviour improved" }, { "kind": "news report", "citation": "Roberts, R. / The Scientist (2026). ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer. The Scientist, online 16 March 2026, June 2026 issue.", "title": "ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer", "url": "https://www.the-scientist.com/chatgpt-and-alphafold-help-design-personalized-vaccine-for-dog-with-cancer-74227", "date": "2026-03-16", "written_by": "independent", "quote": "it is difficult to disentangle which of the treatments had the greatest effect." }, { "kind": "news report", "citation": "AFP via Phys.org (2026). One man, his dog, and ChatGPT: Australia's AI vaccine saga. Phys.org, 30 March 2026.", "title": "One man, his dog, and ChatGPT: Australia's AI vaccine saga", "url": "https://phys.org/news/2026-03-dog-chatgpt-australia-ai-vaccine.html", "date": "2026-03-30", "written_by": "independent", "quote": "This was not a clinical trial by any means" }, { "kind": "news report", "citation": "Kim, S. / Newsweek (2026). Owner With No Medical Background Invents Cure for Dog's Terminal Cancer. Newsweek, 16 March 2026.", "title": "Owner With No Medical Background Invents Cure for Dog's Terminal Cancer", "url": "https://www.newsweek.com/owner-no-medical-background-invents-cure-dogs-terminal-cancer-11684882", "date": "2026-03-16", "written_by": "independent", "quote": "And, toward the end of January, she was jumping over a fence to chase a rabbit." }, { "kind": "news report", "citation": "Bailey, R. / Reason (2026). Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer. Reason, 19 March 2026.", "title": "Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer", "url": "https://reason.com/2026/03/19/man-successfully-designs-mrna-vaccine-to-treat-his-dogs-cancer/", "date": "2026-03-19", "written_by": "independent", "quote": "If we can do this for a dog, why aren't we rolling this out to all humans with cancer?" }, { "kind": "news report", "citation": "Davis, M. / ABC News (2026). AI designs cancer vaccine for dog but scientists says red tape a barrier for human care. ABC News, 22 June 2026.", "title": "AI designs cancer vaccine for dog but scientists says red tape a barrier for human care", "url": "https://www.abc.net.au/news/2026-06-22/australian-dog-cancer-treated-via-mrna-vaccine-and-ai/106692668", "date": "2026-06-22", "written_by": "independent", "quote": "AI did not cure Rosie's cancer, nor did it create or administer the vaccine" }, { "kind": "news report", "citation": "Palmer, A. / Medical Daily (2026). Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million. Medical Daily, 18 August 2026.", "title": "Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million", "url": "https://www.medicaldaily.com/rosie-dog-ai-mrna-cancer-vaccine-gamgee-launch-477500", "date": "2026-08-18", "written_by": "independent", "quote": "Rosie entered remission, but her cancer returned following a later surgery." }, { "kind": "press release", "citation": "GAMGEE via GlobeNewswire (2026). One Dog's Legacy Becomes GAMGEE. GlobeNewswire press release, Sydney, 17 August 2026, as carried by Yahoo Finance.", "title": "One Dog's Legacy Becomes GAMGEE", "url": "https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "date": "2026-08-17", "written_by": "deployer", "quote": "While her story may have ended, her legacy lives on in the work that followed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0158-source-0001", "AIBD-0158-source-0002", "AIBD-0158-source-0003", "AIBD-0158-source-0004", "AIBD-0158-source-0005", "AIBD-0158-source-0006", "AIBD-0158-source-0007", "AIBD-0158-source-0008", "AIBD-0158-source-0009", "AIBD-0158-source-0010", "AIBD-0158-source-0011" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Melville, T. / UNSW Sydney (2026). Meet the man who designed a cancer vaccine for his dog. UNSW Newsroom, 17 March 2026.", "title": "Meet the man who designed a cancer vaccine for his dog", "url": "https://news.unsw.edu.au/en/meet-the-man-who-designed-a-cancer-vaccine-for-his-dog", "date": "2026-03-17", "written_by": "deployer", "quote": "We don't know how much of the response came from the checkpoint inhibitor and how much from the mRNA vaccine." }, { "kind": "news report", "citation": "Ma, J. / Fortune (2026). A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog. Fortune, 15 March 2026.", "title": "A tech entrepreneur used AI to help create the first-ever bespoke cancer vaccine for a dog", "url": "https://fortune.com/2026/03/15/australian-tech-entrepreneur-ai-cancer-vaccine-dog-rosie-unsw-mrna/", "date": "2026-03-15", "written_by": "independent", "quote": "Rosie got her first injection of the cancer treatment this past December, then received a booster in February." }, { "kind": "news report", "citation": "Bita, N. / The Australian, republished by Stockhead (2026). Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog. Stockhead, 18 March 2026.", "title": "Tech boss uses AI and ChatGPT to create cancer vaccine for his dying dog", "url": "https://stockhead.com.au/tech/tech-boss-uses-ai-and-chatgpt-to-create-cancer-vaccine-for-his-dying-dog/", "date": "2026-03-18", "written_by": "independent", "quote": "Mr Conyngham drove 10 hours with Rosie for her first injection in December, followed by a booster shot last month and another due next week." }, { "kind": "other", "citation": "Stebbing, J. / The Conversation (2026). A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution. The Conversation, 20 March 2026 (academic commentary).", "title": "A man used AI to help make a cancer vaccine for his dog – an oncologist urges caution", "url": "https://theconversation.com/a-man-used-ai-to-help-make-a-cancer-vaccine-for-his-dog-an-oncologist-urges-caution-278735", "date": "2026-03-20", "written_by": "independent", "quote": "several tumours shrank markedly, her overall tumour burden fell, and her energy and behaviour improved" }, { "kind": "news report", "citation": "Roberts, R. / The Scientist (2026). ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer. The Scientist, online 16 March 2026, June 2026 issue.", "title": "ChatGPT and AlphaFold Help Design Personalized Vaccine for Dog with Cancer", "url": "https://www.the-scientist.com/chatgpt-and-alphafold-help-design-personalized-vaccine-for-dog-with-cancer-74227", "date": "2026-03-16", "written_by": "independent", "quote": "it is difficult to disentangle which of the treatments had the greatest effect." }, { "kind": "news report", "citation": "AFP via Phys.org (2026). One man, his dog, and ChatGPT: Australia's AI vaccine saga. Phys.org, 30 March 2026.", "title": "One man, his dog, and ChatGPT: Australia's AI vaccine saga", "url": "https://phys.org/news/2026-03-dog-chatgpt-australia-ai-vaccine.html", "date": "2026-03-30", "written_by": "independent", "quote": "This was not a clinical trial by any means" }, { "kind": "news report", "citation": "Kim, S. / Newsweek (2026). Owner With No Medical Background Invents Cure for Dog's Terminal Cancer. Newsweek, 16 March 2026.", "title": "Owner With No Medical Background Invents Cure for Dog's Terminal Cancer", "url": "https://www.newsweek.com/owner-no-medical-background-invents-cure-dogs-terminal-cancer-11684882", "date": "2026-03-16", "written_by": "independent", "quote": "And, toward the end of January, she was jumping over a fence to chase a rabbit." }, { "kind": "news report", "citation": "Bailey, R. / Reason (2026). Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer. Reason, 19 March 2026.", "title": "Man Successfully Designs mRNA Vaccine To Treat His Dog's Cancer", "url": "https://reason.com/2026/03/19/man-successfully-designs-mrna-vaccine-to-treat-his-dogs-cancer/", "date": "2026-03-19", "written_by": "independent", "quote": "If we can do this for a dog, why aren't we rolling this out to all humans with cancer?" }, { "kind": "news report", "citation": "Davis, M. / ABC News (2026). AI designs cancer vaccine for dog but scientists says red tape a barrier for human care. ABC News, 22 June 2026.", "title": "AI designs cancer vaccine for dog but scientists says red tape a barrier for human care", "url": "https://www.abc.net.au/news/2026-06-22/australian-dog-cancer-treated-via-mrna-vaccine-and-ai/106692668", "date": "2026-06-22", "written_by": "independent", "quote": "AI did not cure Rosie's cancer, nor did it create or administer the vaccine" }, { "kind": "news report", "citation": "Palmer, A. / Medical Daily (2026). Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million. Medical Daily, 18 August 2026.", "title": "Rosie's Cancer Came Back After Her AI-Designed Vaccine, and Her Owner Just Raised $4 Million", "url": "https://www.medicaldaily.com/rosie-dog-ai-mrna-cancer-vaccine-gamgee-launch-477500", "date": "2026-08-18", "written_by": "independent", "quote": "Rosie entered remission, but her cancer returned following a later surgery." }, { "kind": "press release", "citation": "GAMGEE via GlobeNewswire (2026). One Dog's Legacy Becomes GAMGEE. GlobeNewswire press release, Sydney, 17 August 2026, as carried by Yahoo Finance.", "title": "One Dog's Legacy Becomes GAMGEE", "url": "https://finance.yahoo.com/healthcare/articles/one-dogs-legacy-becomes-gamgee-190000768.html", "date": "2026-08-17", "written_by": "deployer", "quote": "While her story may have ended, her legacy lives on in the work that followed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI-chosen targets, a UNSW-made mRNA vaccine and a checkpoint inhibitor halved Rosie's largest tumor by early 2026; partial, not a cure.", "account": "Paul Conyngham, a Sydney machine-learning engineer, used ChatGPT to plan treatment for his dog Rosie. Rosie is an eight-year-old Staffy-Shar Pei cross with mast cell cancer diagnosed in 2024. He used AlphaFold to model mutated proteins from tumor sequencing he paid $3,000 for at UNSW's Ramaciotti Centre for Genomics. He chose neoantigen targets and confirmed them “again using AI”. Pall Thordarson's UNSW RNA Institute made the mRNA vaccine in under two months. Rachel Allavena of the University of Queensland injected it at Gatton in December 2025, with a checkpoint inhibitor, and gave a booster in February 2026. The tennis-ball-sized tumor on Rosie's hock halved, and she was chasing rabbits by late January 2026. Some tumors did not respond. By August 2026 the cancer had returned after a later surgery." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (OpenAI) and AlphaFold (Google DeepMind), with Grok (xAI) reported for the final mRNA construct, used with Conyngham's own analysis to select tumor neoantigen targets for a personalized mRNA vaccine" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI (ChatGPT); Google DeepMind (AlphaFold); xAI (Grok)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Paul Conyngham uses ChatGPT and AlphaFold to choose targets for a personalized mRNA vaccine that UNSW made for his dog Rosie's mast cell cancer; her largest tumor halved", "headline": "ChatGPT and AlphaFold pick vaccine targets; dog's tumor halves" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1a21cd2cdf56ace508c40de6d3b87e3a17d0d57899f0cfcce9bb7c49722ccd36" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Paul Conyngham, a Sydney machine-learning engineer, used ChatGPT to plan treatment for his dog Rosie. Rosie is an eight-year-old Staffy-Shar Pei cross with mast cell cancer diagnosed in 2024. He used AlphaFold to model mutated proteins from tumor sequencing he paid $3,000 for at UNSW's Ramaciotti Centre for Genomics. He chose neoantigen targets and confirmed them “again using AI”. Pall Thordarson's UNSW RNA Institute made the mRNA vaccine in under two months. Rachel Allavena of the University of Queensland injected it at Gatton in December 2025, with a checkpoint inhibitor, and gave a booster in February 2026. The tennis-ball-sized tumor on Rosie's hock halved, and she was chasing rabbits by late January 2026. Some tumors did not respond. By August 2026 the cancer had returned after a later surgery.", "replication": { "produced_by": [ "Whole-genome sequencing of tumor and healthy tissue, about 150 billion DNA letters for $3,000, from which neoantigen targets could be chosen with AI help.", "An academic RNA facility, the UNSW RNA Institute, willing to make a custom mRNA vaccine from an owner-designed sequence in under two months.", "A veterinary school with ethics cover and an immunotherapy specialist to administer it, after about three months of ethics paperwork.", "An owner with 17 years of machine-learning experience able to run the process, pay for it and drive ten hours for each dose." ], "must_hold": [ "The response cannot be credited to the vaccine alone. A checkpoint inhibitor was given at the same time, and UNSW says the split is unknown.", "One uncontrolled animal. Mast cell tumors behave unpredictably, and some of Rosie's tumors did not respond.", "The benefit was time, not cure. The cancer returned after a later surgery, and the company founded on the case wrote in August 2026 that her story may have ended." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0204", "title": "BrainGate participants T17 (ALS) and T18 (spinal cord injury) type on a two-handed QWERTY keyboard through an intracortical neuroprosthesis, reaching 22 words per minute at 1.6% word error", "summary": "Two BrainGate2 participants typed by attempted finger movement at up to 22 wpm, 1.6% word error, in at-home research sessions (Mar 2026).", "date_observed": "2026-03-16", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "T17 and T18 took part in the BrainGate2 pilot trial (NCT00912041). T17 is a 33-year-old man with ALS, tetraplegia, anarthria and ventilator dependence. T18 is a 48-year-old man with a C4 ASIA A spinal cord injury about 18 months before enrollment. Each received six 64-electrode Utah arrays in precentral gyrus. A five-layer gated recurrent unit decoder with a 5-gram language model turned attempted finger movements into QWERTY keystrokes. It needed as few as 30 calibration sentences. Research sessions took place at each participant's place of residence, on trial days 44 to 144. T18 reached 110 characters (22 words) per minute with a 1.6% word error rate. T17 reached 47 characters per minute. Both typed sentences of their own choosing. The work was published in Nature Neuroscience, 16 March 2026.", "category": "benefit created", "unexpected": false, "purpose": "The typing neuroprosthesis was built to restore communication for people with paralysis. It decodes attempted finger movements into keystrokes. The typing the two participants achieved is exactly that purpose.", "system": "BrainGate2 intracortical typing neuroprosthesis: six 64-electrode Utah arrays (Blackrock Microsystems) per participant, a five-layer gated recurrent unit decoder trained with connectionist temporal classification loss, and a 5-gram language model implemented as a Kaldi weighted finite-state transducer", "model_version": null, "developer": "BrainGate consortium and Neurorecovery, Brown University and VA Providence Healthcare System, with Stanford University and UC Davis co-authors", "deployer": "BrainGate consortium (BrainGate2 pilot clinical trial; sponsor-investigator Leigh R. Hochberg; FDA Investigational Device Exemption G090003), with research sessions at the participants' residences", "location": null, "domain": "Neurotechnology / assistive communication", "segment": "People with tetraplegia from ALS or cervical spinal cord injury", "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-03-16-f051" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Two identifiable participants typed sentences of their own choosing at up to 22 words per minute. One of them has anarthria and only eye movement left. The typing happened only in research sessions. The paper lists independent use as future work, so the gain is material rather than life-changing." }, { "group": "societal", "depth": 1, "reason": "The authors report higher throughput than current state-of-the-art hand-motor iBCI decoding. UCSF's Edward Chang, who is not on the paper, called it among the fastest motor-cortex typing BCIs yet. There were two participants and no population effect." } ], "ai_role": { "status": "assessed", "statement": "The decoder is the component that makes typing possible. It is a recurrent neural network of five gated recurrent unit layers with 512 units each. It was trained with CTC loss on 20 ms bins of threshold crossings and spike-band power. It maps attempted finger movements to characters, and a 5-gram language model corrects them. Without it the arrays only record. The error rate figures are word error rates after the language model. Performance figures come from the developers' own peer-reviewed paper. The paper declares that the MGH Translational Research Center has research support agreements with several BCI companies, for which L.R.H. provides consultative input." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Jude, J. J., Levi-Aharoni, H., Acosta, A. J., et al. (2026). Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis. Nature Neuroscience 29, 2613–2622, online 16 March 2026.", "title": "Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis", "url": "https://www.nature.com/articles/s41593-026-02218-y", "date": "2026-03-16", "written_by": "makers", "quote": "Typing speed is user-regulated, reaching 110 characters per minute, resulting in 22 words per minute with a word error rate of 1.6%." }, { "kind": "peer-reviewed study", "citation": "Jude, J. J., et al. (2026). Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis. Open-access full text, Europe PMC PMC13633126 (PMID 41840138).", "title": "Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis (Europe PMC full text)", "url": "https://europepmc.org/article/PMC/PMC13633126", "date": "2026-03-16", "written_by": "makers", "quote": "All research sessions were performed at each participant's place of residence." }, { "kind": "press release", "citation": "Mass General Brigham (2026). Investigational Brain Implant Restores High-Speed Communication. Press release as reproduced by Neuroscience News, 16 March 2026.", "title": "Investigational Brain Implant Restores High-Speed Communication", "url": "https://neurosciencenews.com/brain-computer-interface-typing-paralysis-30325/", "date": "2026-03-16", "written_by": "makers", "quote": "Both participants used the device from the comfort of their own place of residence, demonstrating the potential for translation and at-home use in the future." }, { "kind": "press release", "citation": "Brown University (2026). Brain computer interface enables rapid communication for two people with paralysis. Release as reproduced by Medical Xpress, 16 March 2026.", "title": "Brain computer interface enables rapid communication for two people with paralysis", "url": "https://medicalxpress.com/news/2026-03-brain-interface-enables-rapid-communication.html", "date": "2026-03-16", "written_by": "makers", "quote": "BCIs are on track to become an important new alternative to what's currently offered." }, { "kind": "news report", "citation": "Lewis, T. / Scientific American (2026). Brain implant allows people who are paralyzed to type using their thoughts at speed of texting. Scientific American, 16 March 2026.", "title": "Brain implant allows people who are paralyzed to type using their thoughts at speed of texting", "url": "https://www.scientificamerican.com/article/brain-implant-allows-people-who-are-paralyzed-to-type-using-their-thoughts/", "date": "2026-03-16", "written_by": "independent", "quote": "At about 22 words per minute, this is among the fastest motor-cortex typing BCIs yet" }, { "kind": "news report", "citation": "Horak, M. / ALS News Today (2026). Brain implant decodes finger moves so paralyzed patients can type. ALS News Today, 18 March 2026.", "title": "Brain implant decodes finger moves so paralyzed patients can type", "url": "https://alsnewstoday.com/news/brain-implant-decodes-finger-moves-paralyzed-patients-type/", "date": "2026-03-18", "written_by": "independent", "quote": "For many people with paralysis, when losing use of both the hands and the muscles of speech, communication can become difficult or impossible." }, { "kind": "news report", "citation": "Europa Press / Infosalus (2026). Una neuroprótesis experimental permite a personas con parálisis escribir con la mente como si usaran un teclado. Infosalus, 17 March 2026.", "title": "Una neuroprótesis experimental permite a personas con parálisis escribir con la mente como si usaran un teclado", "url": "https://www.infosalus.com/salud-investigacion/noticia-neuroprotesis-experimental-permite-personas-paralisis-escribir-mente-si-usaran-teclado-20260317071649.html", "date": "2026-03-17", "written_by": "independent", "quote": "Para muchas personas con parálisis, al perder el uso de las manos y los músculos del habla, la comunicación puede volverse difícil o imposible." }, { "kind": "other", "citation": "ClinicalTrials.gov (n.d.). BrainGate2: Feasibility Study of an Intracortical Neural Interface System for Persons With Tetraplegia. NCT00912041, sponsor Leigh R. Hochberg, MD, PhD.", "title": "BrainGate2: Feasibility Study of an Intracortical Neural Interface System for Persons With Tetraplegia", "url": "https://clinicaltrials.gov/study/NCT00912041", "date": null, "written_by": "makers", "quote": "BrainGate2: Feasibility Study of an Intracortical Neural Interface System for Persons With Tetraplegia" } ], "replication": { "produced_by": [ "Six 64-electrode Utah arrays per participant placed in precentral gyrus after fMRI-guided parcellation, giving hand-motor electrodes for both hands.", "A recurrent neural network decoder trained with CTC loss on attempted finger movements, recalibrated from as few as 30 sentences, plus a 5-gram language model.", "A keyboard setup the participants already knew. Neither was a touch typist, and both learned the layout over sessions.", "A pilot-trial infrastructure that brings research staff and equipment to the participant's residence." ], "must_hold": [ "Use was confined to research sessions. The paper describes independent use through online decoder training as future work.", "Performance differed by participant. T18 reached 22 words per minute with word error below 7% across blocks. T17 reached 47 characters per minute with word error mostly below 15%.", "Invasive surgery is required. The device is investigational under an FDA investigational device exemption. The paper reports no clinical-trial safety outcomes." ], "echoes": [] }, "paired_incident": null, "headline": "BrainGate2 neuroprosthesis lets a paralyzed man type 22 wpm", "metric": "T18 reached 110 characters (22 words) per minute with a 1.6% word error rate", "comparator": { "against": "the previous state-of-the-art hand-motor iBCI (handwriting decoding) and able-bodied smartphone typing", "before": "the previous state-of-the-art method, 20 characters per minute slower (90 characters per minute, about 18 words per minute, per Scientific American); able-bodied smartphone typing of 27.3 words per minute for T18's age group", "after": "110 characters per minute (22 words per minute) at a 1.6% word error rate", "basis": "measured", "quote": "To our knowledge, this system provides the fastest iBCI communication method reported to date based on decoding from hand motor cortex; participant T18 used this system to communicate at 110 characters per minute, which is 20 characters per minute faster than the previous state-of-the-art method", "url": "https://www.nature.com/articles/s41593-026-02218-y" }, "later": { "status": "unknown", "date": null, "note": "No development after the 16 March 2026 publication was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry, the Nature Neuroscience paper (read in full through the Europe PMC open-access copy, PMC13633126), the Mass General Brigham release as reproduced by Neuroscience News, the Brown University release as reproduced by Medical Xpress, Scientific American, ALS News Today, Europa Press via Infosalus (one of the Monitor's seven Spanish-language sources) and the ClinicalTrials.gov entry via its API. Kept at benefit created or restored following AIBD-0005, AIBD-0051 and AIBD-0052, which file single- and two-participant BCI trial demonstrations as created benefits for identifiable people; the paper is not an aggregate study, but it reports research-session performance only and states that it “does not report any clinical trial-related outcomes”, which the the taxonomy note records. The paper dates sessions only as trial days relative to surgery (T17 days 56–144, T18 days 44–107), so the online publication date, which is also the Monitor's date, is used. Participant ages and diagnoses come from the paper's Methods; the Boston Globe's STAT republication was read but its extraction swapped the participants' diagnoses, so it is not cited. La Razón and LaSexta from the Monitor's list and nature.com without a cookie-bypass could not be read. The WebSearch budget was exhausted, so sources were found through Google and Bing news feeds and the Crossref and Europe PMC APIs.", "source": "https://oecd.ai/en/incidents/2026-03-16-f051", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.nature.com/articles/s41593-026-02218-y", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/BrainGate; https://clinicaltrials.gov/api/v2/studies/NCT00912041", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to BrainGate consortium.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to BrainGate consortium.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, two peer-reviewed studies from the makers, two press releases from the makers and the makers' other. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0204", "catalog_version": "1.0.0", "source_fingerprint": "b3c6dcf2900e727d7ae98e772a7e80bc7b7f9bcfb1b8192a37cd48bd309d9e56", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0204-source-0001", "AIBD-0204-source-0002", "AIBD-0204-source-0003", "AIBD-0204-source-0004", "AIBD-0204-source-0005", "AIBD-0204-source-0006", "AIBD-0204-source-0007", "AIBD-0204-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "BrainGate consortium and Neurorecovery, Brown University and VA Providence Healthcare System, with Stanford University and UC Davis co-authors", "deployer": "BrainGate consortium (BrainGate2 pilot clinical trial; sponsor-investigator Leigh R. 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Kept at benefit created or restored following AIBD-0005, AIBD-0051 and AIBD-0052, which file single- and two-participant BCI trial demonstrations as created benefits for identifiable people; the paper is not an aggregate study, but it reports research-session performance only and states that it “does not report any clinical trial-related outcomes”, which the the taxonomy note records. The paper dates sessions only as trial days relative to surgery (T17 days 56–144, T18 days 44–107), so the online publication date, which is also the Monitor's date, is used. Participant ages and diagnoses come from the paper's Methods; the Boston Globe's STAT republication was read but its extraction swapped the participants' diagnoses, so it is not cited. La Razón and LaSexta from the Monitor's list and nature.com without a cookie-bypass could not be read. 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The WebSearch budget was exhausted, so sources were found through Google and Bing news feeds and the Crossref and Europe PMC APIs.", "source": "https://oecd.ai/en/incidents/2026-03-16-f051", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.nature.com/articles/s41593-026-02218-y", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/BrainGate; https://clinicaltrials.gov/api/v2/studies/NCT00912041", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to BrainGate consortium.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to BrainGate consortium.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Neurotechnology / assistive communication", "segment": "People with tetraplegia from ALS or cervical spinal cord injury" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "peer-reviewed study", "citation": "Jude, J. 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ALS News Today, 18 March 2026.", "title": "Brain implant decodes finger moves so paralyzed patients can type", "url": "https://alsnewstoday.com/news/brain-implant-decodes-finger-moves-paralyzed-patients-type/", "date": "2026-03-18", "written_by": "independent", "quote": "For many people with paralysis, when losing use of both the hands and the muscles of speech, communication can become difficult or impossible." }, { "kind": "news report", "citation": "Europa Press / Infosalus (2026). Una neuroprótesis experimental permite a personas con parálisis escribir con la mente como si usaran un teclado. 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Infosalus, 17 March 2026.", "title": "Una neuroprótesis experimental permite a personas con parálisis escribir con la mente como si usaran un teclado", "url": "https://www.infosalus.com/salud-investigacion/noticia-neuroprotesis-experimental-permite-personas-paralisis-escribir-mente-si-usaran-teclado-20260317071649.html", "date": "2026-03-17", "written_by": "independent", "quote": "Para muchas personas con parálisis, al perder el uso de las manos y los músculos del habla, la comunicación puede volverse difícil o imposible." }, { "kind": "other", "citation": "ClinicalTrials.gov (n.d.). BrainGate2: Feasibility Study of an Intracortical Neural Interface System for Persons With Tetraplegia. NCT00912041, sponsor Leigh R. 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T17 is a 33-year-old man with ALS, tetraplegia, anarthria and ventilator dependence. T18 is a 48-year-old man with a C4 ASIA A spinal cord injury about 18 months before enrollment. Each received six 64-electrode Utah arrays in precentral gyrus. A five-layer gated recurrent unit decoder with a 5-gram language model turned attempted finger movements into QWERTY keystrokes. It needed as few as 30 calibration sentences. Research sessions took place at each participant's place of residence, on trial days 44 to 144. T18 reached 110 characters (22 words) per minute with a 1.6% word error rate. T17 reached 47 characters per minute. Both typed sentences of their own choosing. The work was published in Nature Neuroscience, 16 March 2026." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "BrainGate2 intracortical typing neuroprosthesis: six 64-electrode Utah arrays (Blackrock Microsystems) per participant, a five-layer gated recurrent unit decoder trained with connectionist temporal classification loss, and a 5-gram language model implemented as a Kaldi weighted finite-state transducer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "BrainGate consortium and Neurorecovery, Brown University and VA Providence Healthcare System, with Stanford University and UC Davis co-authors" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "BrainGate participants T17 (ALS) and T18 (spinal cord injury) type on a two-handed QWERTY keyboard through an intracortical neuroprosthesis, reaching 22 words per minute at 1.6% word error", "headline": "BrainGate2 neuroprosthesis lets a paralyzed man type 22 wpm" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "b3c6dcf2900e727d7ae98e772a7e80bc7b7f9bcfb1b8192a37cd48bd309d9e56" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "T17 and T18 took part in the BrainGate2 pilot trial (NCT00912041). T17 is a 33-year-old man with ALS, tetraplegia, anarthria and ventilator dependence. T18 is a 48-year-old man with a C4 ASIA A spinal cord injury about 18 months before enrollment. Each received six 64-electrode Utah arrays in precentral gyrus. A five-layer gated recurrent unit decoder with a 5-gram language model turned attempted finger movements into QWERTY keystrokes. It needed as few as 30 calibration sentences. Research sessions took place at each participant's place of residence, on trial days 44 to 144. T18 reached 110 characters (22 words) per minute with a 1.6% word error rate. T17 reached 47 characters per minute. Both typed sentences of their own choosing. The work was published in Nature Neuroscience, 16 March 2026.", "replication": { "produced_by": [ "Six 64-electrode Utah arrays per participant placed in precentral gyrus after fMRI-guided parcellation, giving hand-motor electrodes for both hands.", "A recurrent neural network decoder trained with CTC loss on attempted finger movements, recalibrated from as few as 30 sentences, plus a 5-gram language model.", "A keyboard setup the participants already knew. Neither was a touch typist, and both learned the layout over sessions.", "A pilot-trial infrastructure that brings research staff and equipment to the participant's residence." ], "must_hold": [ "Use was confined to research sessions. The paper describes independent use through online decoder training as future work.", "Performance differed by participant. T18 reached 22 words per minute with word error below 7% across blocks. T17 reached 47 characters per minute with word error mostly below 15%.", "Invasive surgery is required. The device is investigational under an FDA investigational device exemption. The paper reports no clinical-trial safety outcomes." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0584", "title": "SpeciesNet supports ecological estimates similar to expert analysis for shared species, with important omissions", "summary": "Researchers used MegaDetector and SpeciesNet to produce ecological estimates similar to expert analysis for many species, while some species were missed or misclassified.", "date_observed": "2026-03-17", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "Thornton, Morris, and colleagues compared ecological occupancy models derived from automated SpeciesNet identifications with models derived from expert identifications. The study used 638 cameras in Washington, 263 in Montana, and 326 in Guatemala. MegaDetector 5a located animals, and SpeciesNet classified the crops, with regional species lists, taxonomic adjustments, and sequence processing. Across six AI configurations, mean absolute differences in occupancy probabilities were 0.04-0.05 in Washington, 0.05-0.07 in Montana, and 0.03-0.06 in Guatemala. These comparisons cover species present in both datasets; they are not image-accuracy percentages. Some individual species differed substantially, with a maximum difference of 0.40 in Montana. All 94 mountain-goat detections in Montana were classified as domestic goats and omitted from the AI occupancy models. Montana's expert workflow already used MegaDetector for initial sorting. The study demonstrates automated ecological analysis with broadly similar results for shared species, while preserving a need for human review in some research tasks. It does not measure net labor savings, changed management decisions, or wildlife outcomes. Google developer Dan Morris coauthored the study. The author summary was first dated March 17, 2026; the full paper appeared on May 6.", "category": "general benefit", "unexpected": false, "purpose": "SpeciesNet identifies wildlife in images. The study tested whether automated identifications could support ecological occupancy models without routine human verification of each image.", "system": "MegaDetector and SpeciesNet", "model_version": "MegaDetector 5a; SpeciesNet checkpoint not reported", "developer": "Google and MegaDetector contributors", "deployer": "Washington State University and collaborating wildlife research teams", "location": "Washington and Montana, United States; Maya Biosphere Reserve, Guatemala", "domain": "Environment and conservation", "segment": "Ecological occupancy modeling from camera images", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": "The observed result is useful ecological modeling with automated species identifications. Faster research and conservation improvements are not measured outcomes in this study.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The study demonstrates an automated analytical capability with broadly similar occupancy estimates for shared species. Rare-species omissions and setting-specific differences limit its use." }, { "group": "societal", "depth": null, "reason": "No changed conservation decision or wildlife outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "MegaDetector located animals and SpeciesNet supplied identifications for ecological models. Researchers configured and analyzed the workflow. The comparison tests analytical usefulness, not a measured improvement in conservation outcomes or net labor time." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Thornton D, Morris D, King T, Perera-Romero L, Anderson A, Garcia-Anleu R, Fitkin S, Vynne C. Identification of camera trap images by artificial intelligence and human experts produces similar multi-species occupancy models. Journal of Applied Ecology 63(5):e70370. First published May 6, 2026. doi:10.1111/1365-2664.70370.", "title": "Identification of camera trap images by artificial intelligence and human experts produces similar multi-species occupancy models", "url": "https://doi.org/10.1111/1365-2664.70370", "date": "2026-05-06", "written_by": "makers", "quote": null }, { "kind": "dataset", "citation": "Archived code and data accompanying the Thornton et al. occupancy study. Zenodo record 19560799, version 1.0.1, April 13, 2026.", "title": "Code and data for the SpeciesNet occupancy comparison, version 1.0.1", "url": "https://zenodo.org/records/19560799", "date": "2026-04-13", "written_by": "makers", "quote": null, "supports_benefit": false } ], "replication": { "produced_by": [ "Camera datasets from Washington (2016-2017), Montana (2018-2021), and Guatemala (2018-2019).", "MegaDetector 5a detections at confidence 0.15 or above, SpeciesNet classifications, regional filters, and six processing configurations.", "Comparison of ecological models fitted to AI and expert identifications of the same images." ], "must_hold": [ "The system must retain the species that matter to the intended ecological question.", "The exact SpeciesNet checkpoint and processing settings must be recoverable.", "Regional input data and analysis scripts must be available, with appropriate protections for sensitive wildlife locations." ], "echoes": [] }, "paired_incident": null, "headline": "SpeciesNet supports ecological estimates with some species missed", "metric": "Mean occupancy differences of 0.03-0.07 across study areas", "comparator": { "against": "Ecological models fitted to expert identifications of the same images; Montana experts already used MegaDetector for initial sorting.", "before": "Expert-based estimates of species occupancy and species-environment relationships.", "after": "Mean absolute occupancy-probability differences of 0.04-0.05 in Washington, 0.05-0.07 in Montana, and 0.03-0.06 in Guatemala for shared species.", "basis": "measured", "quote": "We found that for most species of mammal, AI based models were remarkably similar to expert-based models", "url": "https://doi.org/10.1111/1365-2664.70370" }, "later": { "status": "unknown", "date": null, "note": "Subsequent deployment, correction of the reported errors, and changes to conservation decisions have not been established by this source review.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-25", "change": "Added the original comparative study, its methods and limitations, source lineage, and unresolved follow-up questions.", "source": "https://doi.org/10.1111/1365-2664.70370", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study and the makers' dataset. 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Referenced Montana and Guatemala inputs are absent. The public Washington image subset has a different denominator. The complete supplement was inaccessible." } }, "evaluations[].setting_sample": { "state": "value_present", "value": { "kind": "structured", "data": { "Washington": { "cameras": 638, "images_approx": 1800000, "collection_years": "2016-2017" }, "Montana": { "cameras": 263, "images_approx": 1700000, "collection_years": "2018-2021" }, "Guatemala": { "cameras": 326, "images_approx": 280000, "collection_years": "2018-2019" } } }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Washington: 638 cameras and about 1.8 million images. Montana: 263 cameras and about 1.7 million images. Guatemala: 326 cameras and about 280,000 images." } }, "evaluations[].uncertainty_limitations": { "state": "value_present", "value": { "kind": "text", "text": "Comparisons of model estimates cover shared species. Rare-species omissions remain outside those comparisons. Regional filtering and sequence processing affect results. Montana's expert workflow already used AI. The exact SpeciesNet checkpoint, some regional inputs, and the complete supplement were unavailable in this review." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "external_references[]": { "state": "value_present", "value": { "kind": "structured", "data": { "study_doi": "10.1111/1365-2664.70370", "archive_version_1_0_1": "https://zenodo.org/records/19560799", "archive_version_1_0_0": "https://zenodo.org/records/19073128", "public_washington_subset": "https://lila.science/datasets/wsu-lynx/" } }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The study DOI is 10.1111/1365-2664.70370. The record links both archive versions and the public Washington image subset." } }, "follow_up[]": { "state": "not_assessed", "reason": "Post-study adoption and conservation decisions require follow-up.", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Researchers supplied regional filters and taxonomic adjustments and assessed the statistical output. Expert identifications provided the comparator. The authors recommend human review for some rare-species and biodiversity tasks." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0584" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "infrastructure_dependencies[]": { "state": "value_present", "value": { "kind": "text", "text": "Camera datasets, MegaDetector, SpeciesNet, regional species information, and statistical analysis in R were required. A complete historical SpeciesNet checkpoint and all regional data inputs are not preserved in the inspected archive." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "The participating ecological research teams. Benefits to monitoring organizations and conservation managers are prospective unless subsequent use is documented." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].beneficiary_count": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original study and its stated data availability.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not count people who benefited. Cameras, images, species, and detection events are study units.", "review_state": "reviewed", "coverage": "complete" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "text", "text": "Improved Knowledge Discovery" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "text", "text": "Thornton, Morris, and colleagues compared ecological occupancy models derived from automated SpeciesNet identifications with models derived from expert identifications. The study used 638 cameras in Washington, 263 in Montana, and 326 in Guatemala. MegaDetector 5a located animals, and SpeciesNet classified the crops, with regional species lists, taxonomic adjustments, and sequence processing. Across six AI configurations, mean absolute differences in occupancy probabilities were 0.04-0.05 in Washington, 0.05-0.07 in Montana, and 0.03-0.06 in Guatemala. These comparisons cover species present in both datasets; they are not image-accuracy percentages. Some individual species differed substantially, with a maximum difference of 0.40 in Montana. All 94 mountain-goat detections in Montana were classified as domestic goats and omitted from the AI occupancy models. Montana's expert workflow already used MegaDetector for initial sorting. The study demonstrates automated ecological analysis with broadly similar results for shared species, while preserving a need for human review in some research tasks. It does not measure net labor savings, changed management decisions, or wildlife outcomes. Google developer Dan Morris coauthored the study. The author summary was first dated March 17, 2026; the full paper appeared on May 6." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].distribution": { "state": "value_present", "value": { "kind": "text", "text": "Agreement varied by region and species. Shared-species comparisons do not cover species missing from the AI datasets. Rare or difficult species may require human review." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].duration": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Reviewed the original study and its stated data availability.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "reason": "The study does not establish how long the benefit persisted after the evaluation.", "review_state": "reviewed", "coverage": "complete" }, "outcomes[].id": { "state": "value_present", "value": { "kind": "text", "text": "AIBD-0584-outcome-research" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "text", "text": "Participating research organizations. Wider conservation benefits remain unmeasured." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "text", "text": "Reported research result with explicit limitations." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].tradeoffs": { "state": "value_present", "value": { "kind": "text", "text": "Broad agreement coexisted with substantial errors for some species. All 94 Montana mountain-goat detections were labeled domestic goats and omitted from AI occupancy models. Some species appeared falsely in AI outputs." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "text", "text": "The result concerns the intended use of AI to support wildlife-image analysis." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "places[]": { "state": "value_present", "value": { "kind": "structured", "data": { "case_jurisdictions": [ "United States", "Guatemala" ], "developer_jurisdictions": [ "United States" ], "study_places": [ "Washington, United States", "Glacier National Park, Montana, United States", "Maya Biosphere Reserve, Guatemala" ], "location_label": "Study locations" } }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Washington and Montana in the United States, and the Maya Biosphere Reserve in Guatemala." } }, "purpose": { "state": "value_present", "value": { "kind": "text", "text": "SpeciesNet identifies wildlife in images. The study tested whether automated identifications could support ecological occupancy models without routine human verification of each image." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "record_dates": { "state": "value_present", "value": { "kind": "structured", "data": { "image_collection": { "Washington": "2016-2017", "Montana": "2018-2021", "Guatemala": "2018-2019" }, "first_dated_public_account": "2026-03-17", "code_release_1_0_0": "2026-03-17", "code_and_data_release_1_0_1": "2026-04-13", "full_paper_publication": "2026-05-06", "author_summary_modified": "2026-05-07", "case_date": "2026-03-17", "case_date_basis": "Earliest dated author account of this work. The original March text was not recovered; the current summary was modified in May.", "last_reviewed": "2026-10-25" } }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002", "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "https://zenodo.org/records/19073128" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Images were collected in 2016-2021 across the three regions. An author account was first dated March 17, 2026; the full study appeared May 6. The original March text was not recovered." } }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "text", "text": "The system must retain the species that matter to the intended ecological question. The exact SpeciesNet checkpoint and processing settings must be recoverable. Regional input data and analysis scripts must be available, with appropriate protections for sensitive wildlife locations." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "revision_history[]": { "state": "value_present", "value": { "kind": "structured", "data": { "revisions": [ { "date": "2026-10-25", "change": "Added the original comparative study, its methods and limitations, source lineage, and unresolved follow-up questions.", "source": "https://doi.org/10.1111/1365-2664.70370", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Recorded the initial source review and addition.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The record and its source assessment were added on October 25, 2026." } }, "sector": { "state": "value_present", "value": { "kind": "text", "text": "Environment and conservation" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "paper": "Version of record, May 6, 2026.", "archive_version": "1.0.1", "archive_date": "2026-04-13", "zip_md5": "2171ba86c5e91025ea6f12fe4c757e2d", "earlier_archive": "https://zenodo.org/records/19073128", "summary_original_text": "Not recovered; the current author summary was modified May 7, 2026.", "supplement": { "url": "https://besjournals.onlinelibrary.wiley.com/doi/suppl/10.1111/1365-2664.70370/supinfo/jpe70370-sup-0001-Supinfo.docx", "status": "Full DOCX inaccessible after 403 and retrieval failures. Description and captions only." }, "missing_archive_inputs": "Montana and Guatemala CSV inputs referenced by the archived scripts." } }, "provenance": { "kind": "source_review", "basis": "Preserved version history and actual access limits.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002", "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "https://zenodo.org/records/19073128", "https://besjournals.onlinelibrary.wiley.com/doi/suppl/10.1111/1365-2664.70370/supinfo/jpe70370-sup-0001-Supinfo.docx" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The full paper and archive version 1.0.1 were inspected. Some regional inputs are absent, and the full supplementary document could not be retrieved." } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "source_ref": "AIBD-0584-source-0001", "citation": "Thornton D, Morris D, King T, Perera-Romero L, Anderson A, Garcia-Anleu R, Fitkin S, Vynne C. Identification of camera trap images by artificial intelligence and human experts produces similar multi-species occupancy models. Journal of Applied Ecology 63(5):e70370. First published May 6, 2026. doi:10.1111/1365-2664.70370.", "url": "https://doi.org/10.1111/1365-2664.70370" }, { "source_ref": "AIBD-0584-source-0002", "citation": "Archived code and data accompanying the Thornton et al. occupancy study. 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Zenodo version 1.0.1 supplies the inspected scripts and partial data." } }, "sources[].id": { "state": "value_present", "value": { "kind": "structured", "data": { "identifiers": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ] } }, "provenance": { "kind": "curatorial", "basis": "Assigned stable source references for the retained evidence.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Two retained sources have stable identifiers beneath this record." } }, "sources[].language": { "state": "value_present", "value": { "kind": "text", "text": "The retained sources are in English." }, "provenance": { "kind": "source_review", "basis": "Inspected the retained sources.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "The original peer-reviewed study includes Dan Morris, a Google employee and contributor to SpeciesNet. It is research with developer participation. The code-and-data archive belongs to the same work and is not independent confirmation." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0584-source-0001", "retained_source_order": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "origins": [ { "url": "https://doi.org/10.1111/1365-2664.70370", "source_refs": [ "AIBD-0584-source-0001" ], "display_name": "Journal of Applied Ecology", "contribution": "Original study design, regional comparisons, species omissions, and developer disclosure.", "locator": "Sections 2.1-2.6; Table 1; sections 3.1 and 4; Author Contributions; Conflict of Interest; Data Availability.", "relationship": "Original comparative study with Google developer participation." }, { "url": "https://zenodo.org/records/19560799", "source_refs": [ "AIBD-0584-source-0002" ], "display_name": "Zenodo", "contribution": "Versioned scripts and partial regional data, allowing inspection of reproducibility limits.", "locator": "Version 1.0.1 metadata and ZIP file inventory; Montana_MSOM.R and Guatemala_MSOM.R input references.", "relationship": "Code and data for the same study, without independent confirmation of its result." } ], "chronology_source": { "url": "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "title": "Review of camera trap images by artificial intelligence produce accurate models for rapid decision making", "date": "2026-03-17", "qualification": "Publication metadata is March 17 and modification metadata is May 7, 2026. The original March text was not recovered." }, "version_relationships": [ { "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002" ], "relationship": "The article and archive belong to one evaluation. The archive adds reproducibility information, not another benefit observation." }, { "url": "https://zenodo.org/records/19073128", "relationship": "Version 1.0.0, March 17, 2026, contained code only. Version 1.0.1 added data on April 13." }, { "url": "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "relationship": "The author summary is another presentation of the same work and establishes earlier public chronology." } ], "metadata_sources": [ { "url": "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "title": "Author plain-language summary", "date": "2026-03-17" } ], "review_scope": "Original paper, archive metadata and file inventory, analysis inputs, author-summary chronology, and public image-subset metadata inspected. The complete supplement and absent regional inputs were not inspected." } }, "provenance": { "kind": "source_review", "basis": "Traced the reported result to the original paper and separated its supporting materials, versions, and earlier public account.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001", "AIBD-0584-source-0002", "https://appliedecologistsblog.com/2026/03/17/review-of-camera-trap-images-by-artificial-intelligence-produce-accurate-models-for-rapid-decision-making/", "https://zenodo.org/records/19073128", "https://lila.science/datasets/wsu-lynx/" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The paper supplies the comparative results. Its archive and author summary belong to the same work and do not provide independent confirmation." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used MegaDetector and SpeciesNet to produce ecological estimates similar to expert analysis for many species, while some species were missed or misclassified." }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].autonomy_permissions": { "state": "value_present", "value": { "kind": "text", "text": "The evaluated AI workflow did not require routine human review of each image. Researchers designed the processing and ecological analysis. No automated conservation action is documented." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector located animals. SpeciesNet classified image crops. Statistical occupancy models estimated ecological relationships from the resulting labels." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector 5a detections at confidence 0.15 or above were passed to SpeciesNet. Researchers applied regional species lists, taxonomic adjustments, sequence smoothing, and six combinations of classification thresholds and sequence cleaning. The SpeciesNet checkpoint is unspecified." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "Camera photographs became animal crops and species identifications, which researchers used to estimate occupancy and relationships with environmental variables." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector and SpeciesNet." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; versioned archive and source chronology where specified.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector 5a; SpeciesNet checkpoint not reported" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "text", "text": "MegaDetector and SpeciesNet" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Google and MegaDetector contributors" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "text", "text": "SpeciesNet supports ecological estimates similar to expert analysis for shared species, with important omissions" }, "provenance": { "kind": "source_review", "basis": "Original study, methods, results, and discussion.", "record_fields": [], "source_refs": [ "AIBD-0584-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete" }, "version": { "state": "value_present", "value": { "kind": "structured", "data": { "fingerprint": "da3108e5efcd3c734b00857ce3ef966562d8e04a55f77e431b215a408193dc5c" } }, "provenance": { "kind": "derivation", "basis": "SHA-256 of the normalized record.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The record has a content fingerprint that changes when its source data change." } }, "workflow": { "state": "value_present", "value": { "kind": "text", "text": "Researchers processed images with MegaDetector and SpeciesNet, prepared six AI datasets, fitted occupancy models, and compared those models with models based on expert identifications." }, "provenance": { "kind": "source_review", "basis": "Thornton et al., sections 2.1-2.6, Table 1, sections 3.1 and 4, author contributions and disclosure; 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The Spokesman-Review syndicated the report. Lime Vision is a system of cameras and AI software developed in-house to detect sidewalk riding. It emits audible alerts that repeat until the scooter leaves the sidewalk or the trip ends. Lime would fit it to about 3,500 vehicles, half its Seattle fleet, by 1 June 2026, and to the whole fleet by year's end. New and retrofitted scooters were to arrive from mid-April. Parker Dawson, Lime's regional government relations lead, said the technology had been tested in Seattle in recent months. He said Seattle would get it before any other city, and that it coaches riders rather than slowing the scooter. He would not say why the scooters do not slow down on sidewalks as they do under geofencing at Seattle Center. Jon Scholes of the Downtown Seattle Association called sidewalk riding a safety issue. Lime shares data with a Seattle Department of Transportation (SDOT) dashboard. The article gives no sidewalk-riding or complaint figures before or after deployment.", "category": "general benefit", "unexpected": false, "purpose": "Lime Vision was built to detect sidewalk riding and deter it through audible alerts.", "system": "Lime Vision (on-scooter cameras with AI sidewalk-riding detection and audible alerts)", "model_version": null, "developer": "Lime", "deployer": "Lime (Seattle shared-scooter fleet)", "location": "Seattle, United States", "domain": "Micromobility safety", "segment": "Shared e-scooters / pedestrian conflict", "benefit_type": "Increased Product Safety", "taxonomy_note": "Launch only; sidewalk-riding alerts are a safety feature with no outcome yet.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No outcome is documented; the article describes a rollout." }, { "group": "organizational", "depth": null, "reason": "No outcome for Lime or SDOT is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The article describes the intended function. No detection counts, accuracy or behavioral results are reported, and Lime declined to share many details." }, "evidence": [ { "kind": "news report", "citation": "Deshais N (20 Mar 2026). AI to warn Seattle Lime scooters to stay off sidewalks. The Seattle Times, syndicated by The Spokesman-Review.", "title": "AI to warn Seattle Lime scooters to stay off sidewalks", "url": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/", "date": "2026-03-20", "written_by": "independent", "quote": "Lime Vision will be installed on half the scooter fleet, about 3,500 vehicles, by June 1 and all of the fleet by year’s end." } ], "replication": { "produced_by": [ "Camera-equipped scooters with on-device sidewalk classification", "Audible alerts that persist until the rider leaves the sidewalk", "A city where sidewalk riding is barred and where the operator shares data with the transport department" ], "must_hold": [ "Classification works on Seattle's mixed sidewalk and parking-corral layout", "Riders respond to alerts rather than ignoring them" ], "echoes": [ { "date": "2024-11-20", "setting": "Randomized test of a camera-based feedback system on 100 Spin scooters in Santa Monica: 22% less sidewalk time with feedback on", "model_version": null, "outcome": "recurred", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters" } ] }, "paired_incident": null, "headline": "Lime fits Lime Vision sidewalk alerts to 3,500 Seattle scooters", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No source after the 20 March 2026 report was available to confirm whether the 1 June 2026 rollout target was met.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Lime_(transportation_company); https://en.wikipedia.org/wiki/Lime_(transportation_company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0244", "catalog_version": "1.0.0", "source_fingerprint": "a9835942fb96ce11f875e2b3f44731968a00455f9f099bc66858ec77f6a21d66", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0244-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Lime", "deployer": "Lime (Seattle shared-scooter fleet)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The article describes the intended function. 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], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No outcome is documented; the article describes a rollout." }, { "group": "organizational", "reason": "No outcome for Lime or SDOT is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": 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"not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "Launch only; sidewalk-riding alerts are a safety feature with no outcome yet." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nicholas Deshais of The Seattle Times reported on 20 March 2026 that Lime would fit “Lime Vision” to its Seattle scooters. The Spokesman-Review syndicated the report. Lime Vision is a system of cameras and AI software developed in-house to detect sidewalk riding. It emits audible alerts that repeat until the scooter leaves the sidewalk or the trip ends. Lime would fit it to about 3,500 vehicles, half its Seattle fleet, by 1 June 2026, and to the whole fleet by year's end. New and retrofitted scooters were to arrive from mid-April. Parker Dawson, Lime's regional government relations lead, said the technology had been tested in Seattle in recent months. He said Seattle would get it before any other city, and that it coaches riders rather than slowing the scooter. He would not say why the scooters do not slow down on sidewalks as they do under geofencing at Seattle Center. Jon Scholes of the Downtown Seattle Association called sidewalk riding a safety issue. Lime shares data with a Seattle Department of Transportation (SDOT) dashboard. The article gives no sidewalk-riding or complaint figures before or after deployment.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No outcome is documented; the article describes a rollout." }, { "group": "organizational", "reason": "No outcome for Lime or SDOT is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Lime Vision was built to detect sidewalk riding and deter it through audible alerts." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Seattle, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Lime Vision was built to detect sidewalk riding and deter it through audible alerts." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Lime_(transportation_company); https://en.wikipedia.org/wiki/Lime_(transportation_company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-equipped scooters with on-device sidewalk classification", "Audible alerts that persist until the rider leaves the sidewalk", "A city where sidewalk riding is barred and where the operator shares data with the transport department" ], "must_hold": [ "Classification works on Seattle's mixed sidewalk and parking-corral layout", "Riders respond to alerts rather than ignoring them" ], "echoes": [ { "date": "2024-11-20", "setting": "Randomized test of a camera-based feedback system on 100 Spin scooters in Santa Monica: 22% less sidewalk time with feedback on", "outcome": "recurred", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Camera-equipped scooters with on-device sidewalk classification", "Audible alerts that persist until the rider leaves the sidewalk", "A city where sidewalk riding is barred and where the operator shares data with the transport department" ], "must_hold": [ "Classification works on Seattle's mixed sidewalk and parking-corral layout", "Riders respond to alerts rather than ignoring them" ], "echoes": [ { "date": "2024-11-20", "setting": "Randomized test of a camera-based feedback system on 100 Spin scooters in Santa Monica: 22% less sidewalk time with feedback on", "outcome": "recurred", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Lime_(transportation_company); https://en.wikipedia.org/wiki/Lime_(transportation_company)", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Micromobility safety", "segment": "Shared e-scooters / pedestrian conflict" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Deshais N (20 Mar 2026). AI to warn Seattle Lime scooters to stay off sidewalks. The Seattle Times, syndicated by The Spokesman-Review.", "title": "AI to warn Seattle Lime scooters to stay off sidewalks", "url": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/", "date": "2026-03-20", "written_by": "independent", "quote": "Lime Vision will be installed on half the scooter fleet, about 3,500 vehicles, by June 1 and all of the fleet by year’s end." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0244-source-0001" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Deshais N (20 Mar 2026). AI to warn Seattle Lime scooters to stay off sidewalks. The Seattle Times, syndicated by The Spokesman-Review.", "title": "AI to warn Seattle Lime scooters to stay off sidewalks", "url": "https://www.spokesman.com/stories/2026/mar/20/ai-to-warn-seattle-lime-scooters-to-stay-off-sidew/", "date": "2026-03-20", "written_by": "independent", "quote": "Lime Vision will be installed on half the scooter fleet, about 3,500 vehicles, by June 1 and all of the fleet by year’s end." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Seattle Times (20 March 2026): Lime Vision uses cameras and AI to detect sidewalk riding and emit repeating audible alerts; 3,500 scooters by 1 June 2026, whole fleet by year-end; no outcome data yet.", "account": "Nicholas Deshais of The Seattle Times reported on 20 March 2026 that Lime would fit “Lime Vision” to its Seattle scooters. The Spokesman-Review syndicated the report. Lime Vision is a system of cameras and AI software developed in-house to detect sidewalk riding. It emits audible alerts that repeat until the scooter leaves the sidewalk or the trip ends. Lime would fit it to about 3,500 vehicles, half its Seattle fleet, by 1 June 2026, and to the whole fleet by year's end. New and retrofitted scooters were to arrive from mid-April. Parker Dawson, Lime's regional government relations lead, said the technology had been tested in Seattle in recent months. He said Seattle would get it before any other city, and that it coaches riders rather than slowing the scooter. He would not say why the scooters do not slow down on sidewalks as they do under geofencing at Seattle Center. Jon Scholes of the Downtown Seattle Association called sidewalk riding a safety issue. Lime shares data with a Seattle Department of Transportation (SDOT) dashboard. The article gives no sidewalk-riding or complaint figures before or after deployment." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Lime Vision (on-scooter cameras with AI sidewalk-riding detection and audible alerts)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Lime" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Lime rolls out its in-house “Lime Vision” camera AI that chirps at sidewalk riders to half of its 7,000-scooter Seattle fleet by 1 June 2026", "headline": "Lime fits Lime Vision sidewalk alerts to 3,500 Seattle scooters" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "a9835942fb96ce11f875e2b3f44731968a00455f9f099bc66858ec77f6a21d66" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Nicholas Deshais of The Seattle Times reported on 20 March 2026 that Lime would fit “Lime Vision” to its Seattle scooters. The Spokesman-Review syndicated the report. Lime Vision is a system of cameras and AI software developed in-house to detect sidewalk riding. It emits audible alerts that repeat until the scooter leaves the sidewalk or the trip ends. Lime would fit it to about 3,500 vehicles, half its Seattle fleet, by 1 June 2026, and to the whole fleet by year's end. New and retrofitted scooters were to arrive from mid-April. Parker Dawson, Lime's regional government relations lead, said the technology had been tested in Seattle in recent months. He said Seattle would get it before any other city, and that it coaches riders rather than slowing the scooter. He would not say why the scooters do not slow down on sidewalks as they do under geofencing at Seattle Center. Jon Scholes of the Downtown Seattle Association called sidewalk riding a safety issue. Lime shares data with a Seattle Department of Transportation (SDOT) dashboard. The article gives no sidewalk-riding or complaint figures before or after deployment.", "replication": { "produced_by": [ "Camera-equipped scooters with on-device sidewalk classification", "Audible alerts that persist until the rider leaves the sidewalk", "A city where sidewalk riding is barred and where the operator shares data with the transport department" ], "must_hold": [ "Classification works on Seattle's mixed sidewalk and parking-corral layout", "Riders respond to alerts rather than ignoring them" ], "echoes": [ { "date": "2024-11-20", "setting": "Randomized test of a camera-based feedback system on 100 Spin scooters in Santa Monica: 22% less sidewalk time with feedback on", "outcome": "recurred", "source": "https://findingspress.org/article/125892-ai-driven-feedback-systems-reduce-sidewalk-riding-on-shared-e-scooters" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0312", "title": "AI smoke-detection camera installed for Arizona Public Service spots early signs of the March 2026 Diamond Fire in Coconino National Forest; crews hold it under 7 acres", "summary": "AP: an APS AI camera detected smoke on a March 2026 afternoon and crews contained the Diamond Fire before 7 acres; the Arizona Daily Sun's account of 26 March 2026 gives the timeline but no camera.", "date_observed": "2026-03-26", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Associated Press reported on 4 May 2026 that artificial intelligence detected something resembling smoke on a camera feed from Arizona's Coconino National Forest. The report is by Dorany Pineda and Brittany Peterson, on record in the KPBS and Courthouse News republications. The detection came on a March afternoon. One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs. The fire came to be known as the Diamond Fire. Firefighters raced to the scene and contained it before it grew past 7 acres (2.8 hectares). AP says APS has nearly 40 active AI smoke-detection cameras and plans 71 by summer's end. APS meteorologist Cindy Kobold says the technology notifies the utility about 45 minutes faster on average than the first 911 call. Pano AI, launched in 2020 and charging around $50,000 a year per camera, counts APS among its customers. It says it detected 725 wildfires in the US last year. AP does not state outright which company made the camera that spotted the Diamond Fire. The Arizona Daily Sun (staff report, 26 March 2026) reports that a small fire later named the Diamond Fire began shortly after 2 p.m. on Thursday. It started just north of Lake Mary Road, about three miles south-east of Lake Mary Road and Beulah Boulevard. That is south of Pine Canyon Golf Club and east of Flagstaff Pulliam Airport. It reached seven acres by 3:16 p.m. according to WatchDuty. Its forward progress was stopped at 3:37 p.m., about 80 minutes after the first report, and it was 100% contained at 6:09 p.m. The Daily Sun does not mention a camera, the Coconino National Forest or who made the first report. The two accounts are matched by the fire's name, month and size. No official incident record naming the camera was found; InciWeb's “Diamond Fire” is a June 2023 Scottsdale fire. The Daily Sun reported the fire that Thursday.", "category": "protective response", "unexpected": false, "purpose": "Built to detect smoke on camera feeds and notify the utility and fire agencies earlier than 911 calls. This detection was that purpose.", "system": "AI smoke-detection camera installed for Arizona Public Service (AP lists APS among Pano AI's customers; the Diamond Fire camera's maker is not stated outright)", "model_version": null, "developer": "Pano AI, by implication of AP's customer list; not stated for this camera", "deployer": "Arizona Public Service", "location": "Coconino National Forest near Flagstaff, Arizona, United States", "domain": "Wildfire detection and response", "segment": "Electric utility wildfire mitigation", "benefit_type": "Reduced Risk", "taxonomy_note": "Fire spread averted is read as reduced potential for harm; Trustible's description stresses legal harm.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire near Flagstaff was held to 7 acres, with forward progress stopped about 80 minutes after the first report, per the Daily Sun. AP, in a single report, attributes early detection to the APS camera." }, { "group": "organizational", "depth": null, "reason": "APS's own gain for this fire is not documented, whether protection of its lines or earlier dispatch. Its meteorologist gives only an average 45-minute lead over 911 calls across fires." } ], "ai_role": { "status": "assessed", "statement": "AP reports that the camera's AI detected something resembling smoke and spotted early signs of the fire. It does not say whether the alert was the first report or what the fire agencies did with it. The Daily Sun's timeline does not mention the camera: first report, 7 acres by 3:16 p.m., progress stopped 3:37 p.m., contained 6:09 p.m. The attribution to AI rests on one news report, and the camera's maker is implied rather than stated. No official record naming the camera was found." }, "evidence": [ { "kind": "news report", "citation": "Pineda D, Peterson B (2026). States across the wildfire-prone Western US are using AI for early detection. Associated Press, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://apnews.com/article/ai-wildfire-detection-cameras-194656fe63ea89dbc4661eaf8b79f6bb", "date": "2026-05-04", "written_by": "independent", "quote": "One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs of what came to be known as the Diamond Fire." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by KPBS, 5 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.kpbs.org/news/science-technology/2026/05/05/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection", "date": "2026-05-05", "written_by": "independent", "quote": "Firefighters raced to the scene and contained the blaze before it grew past 7 acres (2.8 hectares)." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by Courthouse News Service, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/", "date": "2026-05-04", "written_by": "independent", "quote": "Cindy Kobold, an Arizona Public Service meteorologist, said the technology notifies them about 45 minutes faster on average than the first 911 call." }, { "kind": "news report", "citation": "Daily Sun staff (2026). Seven-acre fire fully contained south of Flagstaff on Thursday afternoon. Arizona Daily Sun, 26 March 2026 (the article does not mention a camera).", "title": "Seven-acre fire fully contained south of Flagstaff on Thursday afternoon", "url": "https://azdailysun.com/news/local/seven-acre-fire-fully-contained-south-of-flagstaff-on-thursday-afternoon/article_585bebfe-c17c-4872-a37d-7e08195a39d7.html", "date": "2026-03-26", "written_by": "independent", "quote": "Forward progress on the fire was stopped at 3:37 p.m., about 80 minutes after the first report of the fire, and reached 100% containment at 6:09 p.m." } ], "replication": { "produced_by": [ "An AI smoke-detection camera network installed for a utility covering national-forest land near Flagstaff", "Human review of the AI detection, then notification to the utility and fire agencies. AP says human intervention keeps false positives low", "Crews able to reach a small fire on a March afternoon within about 80 minutes of the first report" ], "must_hold": [ "The camera has line of sight to the ignition and the detection reaches a responding agency before the fire grows", "Fire weather and fuels that allow containment at a few acres. The sources give no conditions for this fire" ], "echoes": [ { "date": "2024-06-16", "setting": "Pano AI cameras on Xcel and CORE Electric towers spot the Bear Creek Fire in Douglas County, Colorado; held to three acres (AIBD-0161)", "model_version": null, "outcome": "recurred", "source": "AIBD-0161" }, { "date": "2024-07-09", "setting": "Xcel-funded Pano AI camera catches the Wellington fire near Breckenridge, Colorado; crews hold it to one-eighth of an acre (AIBD-0162)", "model_version": null, "outcome": "recurred", "source": "AIBD-0162" }, { "date": null, "setting": "Pano AI's own claim, relayed by AP, that its technology detected 725 wildfires in the US in the previous year; no outcomes given", "model_version": null, "outcome": "unknown", "source": "Associated Press, 4 May 2026" } ] }, "paired_incident": null, "headline": "APS AI camera spots Diamond Fire; crews hold it under 7 acres", "metric": "contained it before it grew past 7 acres (2.8 hectares)", "comparator": { "against": "the first 911 call reporting a fire", "before": "the first 911 call", "after": "about 45 minutes faster on average than the first 911 call", "basis": "assumed", "quote": "Cindy Kobold, an Arizona Public Service meteorologist, said the technology notifies them about 45 minutes faster on average than the first 911 call.", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" }, "later": { "status": "scaled", "date": "2026-05-04", "note": "Seven weeks after the fire, AP reported that APS had nearly 40 active AI smoke-detection cameras and planned to have 71 by the end of summer 2026.", "quote": "Arizona Public Service has nearly 40 active AI smoke-detection cameras and plans to have 71 by summer’s end, and the state’s fire agency has deployed seven of its own.", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/; https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.pbs.org/newshour/show/how-satellites-and-ai-cameras-are-detecting-wildfires-before-they-get-out-of-control; https://en.wikipedia.org/wiki/Arizona_Public_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0312", "catalog_version": "1.0.0", "source_fingerprint": "c81aed4312d5a518f38cb56ae8aac7ef5e300608c8f387fa0b37d080e2be4538", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0312-source-0001", "AIBD-0312-source-0002", "AIBD-0312-source-0003", "AIBD-0312-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Pano AI, by implication of AP's customer list; not stated for this camera", "deployer": "Arizona Public Service" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AP reports that the camera's AI detected something resembling smoke and spotted early signs of the fire. It does not say whether the alert was the first report or what the fire agencies did with it. The Daily Sun's timeline does not mention the camera: first report, 7 acres by 3:16 p.m., progress stopped 3:37 p.m., contained 6:09 p.m. The attribution to AI rests on one news report, and the camera's maker is implied rather than stated. No official record naming the camera was found." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "AP reports that the camera's AI detected something resembling smoke and spotted early signs of the fire. 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has deployed seven of its own.", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0312" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": 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The report is by Dorany Pineda and Brittany Peterson, on record in the KPBS and Courthouse News republications. The detection came on a March afternoon. One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs. The fire came to be known as the Diamond Fire. Firefighters raced to the scene and contained it before it grew past 7 acres (2.8 hectares). AP says APS has nearly 40 active AI smoke-detection cameras and plans 71 by summer's end. APS meteorologist Cindy Kobold says the technology notifies the utility about 45 minutes faster on average than the first 911 call. Pano AI, launched in 2020 and charging around $50,000 a year per camera, counts APS among its customers. It says it detected 725 wildfires in the US last year. AP does not state outright which company made the camera that spotted the Diamond Fire. The Arizona Daily Sun (staff report, 26 March 2026) reports that a small fire later named the Diamond Fire began shortly after 2 p.m. on Thursday. It started just north of Lake Mary Road, about three miles south-east of Lake Mary Road and Beulah Boulevard. That is south of Pine Canyon Golf Club and east of Flagstaff Pulliam Airport. It reached seven acres by 3:16 p.m. according to WatchDuty. Its forward progress was stopped at 3:37 p.m., about 80 minutes after the first report, and it was 100% contained at 6:09 p.m. The Daily Sun does not mention a camera, the Coconino National Forest or who made the first report. The two accounts are matched by the fire's name, month and size. No official incident record naming the camera was found; InciWeb's “Diamond Fire” is a June 2023 Scottsdale fire. The Daily Sun reported the fire that Thursday.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "A fire near Flagstaff was held to 7 acres, with forward progress stopped about 80 minutes after the first report, per the Daily Sun. AP, in a single report, attributes early detection to the APS camera." }, { "group": "organizational", "reason": "APS's own gain for this fire is not documented, whether protection of its lines or earlier dispatch. Its meteorologist gives only an average 45-minute lead over 911 calls across fires." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to detect smoke on camera feeds and notify the utility and fire agencies earlier than 911 calls. This detection was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Coconino National Forest near Flagstaff, Arizona, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to detect smoke on camera feeds and notify the utility and fire agencies earlier than 911 calls. This detection was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-26", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/; https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.pbs.org/newshour/show/how-satellites-and-ai-cameras-are-detecting-wildfires-before-they-get-out-of-control; https://en.wikipedia.org/wiki/Arizona_Public_Service", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An AI smoke-detection camera network installed for a utility covering national-forest land near Flagstaff", "Human review of the AI detection, then notification to the utility and fire agencies. AP says human intervention keeps false positives low", "Crews able to reach a small fire on a March afternoon within about 80 minutes of the first report" ], "must_hold": [ "The camera has line of sight to the ignition and the detection reaches a responding agency before the fire grows", "Fire weather and fuels that allow containment at a few acres. The sources give no conditions for this fire" ], "echoes": [ { "date": "2024-06-16", "setting": "Pano AI cameras on Xcel and CORE Electric towers spot the Bear Creek Fire in Douglas County, Colorado; held to three acres (AIBD-0161)", "outcome": "recurred", "source": "AIBD-0161" }, { "date": "2024-07-09", "setting": "Xcel-funded Pano AI camera catches the Wellington fire near Breckenridge, Colorado; crews hold it to one-eighth of an acre (AIBD-0162)", "outcome": "recurred", "source": "AIBD-0162" }, { "setting": "Pano AI's own claim, relayed by AP, that its technology detected 725 wildfires in the US in the previous year; no outcomes given", "outcome": "unknown", "source": "Associated Press, 4 May 2026" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An AI smoke-detection camera network installed for a utility covering national-forest land near Flagstaff", "Human review of the AI detection, then notification to the utility and fire agencies. 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States across the wildfire-prone Western US are using AI for early detection. Associated Press, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://apnews.com/article/ai-wildfire-detection-cameras-194656fe63ea89dbc4661eaf8b79f6bb", "date": "2026-05-04", "written_by": "independent", "quote": "One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs of what came to be known as the Diamond Fire." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by KPBS, 5 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.kpbs.org/news/science-technology/2026/05/05/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection", "date": "2026-05-05", "written_by": "independent", "quote": "Firefighters raced to the scene and contained the blaze before it grew past 7 acres (2.8 hectares)." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by Courthouse News Service, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/", "date": "2026-05-04", "written_by": "independent", "quote": "Cindy Kobold, an Arizona Public Service meteorologist, said the technology notifies them about 45 minutes faster on average than the first 911 call." }, { "kind": "news report", "citation": "Daily Sun staff (2026). Seven-acre fire fully contained south of Flagstaff on Thursday afternoon. Arizona Daily Sun, 26 March 2026 (the article does not mention a camera).", "title": "Seven-acre fire fully contained south of Flagstaff on Thursday afternoon", "url": "https://azdailysun.com/news/local/seven-acre-fire-fully-contained-south-of-flagstaff-on-thursday-afternoon/article_585bebfe-c17c-4872-a37d-7e08195a39d7.html", "date": "2026-03-26", "written_by": "independent", "quote": "Forward progress on the fire was stopped at 3:37 p.m., about 80 minutes after the first report of the fire, and reached 100% containment at 6:09 p.m." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0312-source-0001", "AIBD-0312-source-0002", "AIBD-0312-source-0003", "AIBD-0312-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Pineda D, Peterson B (2026). States across the wildfire-prone Western US are using AI for early detection. Associated Press, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://apnews.com/article/ai-wildfire-detection-cameras-194656fe63ea89dbc4661eaf8b79f6bb", "date": "2026-05-04", "written_by": "independent", "quote": "One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs of what came to be known as the Diamond Fire." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by KPBS, 5 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.kpbs.org/news/science-technology/2026/05/05/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection", "date": "2026-05-05", "written_by": "independent", "quote": "Firefighters raced to the scene and contained the blaze before it grew past 7 acres (2.8 hectares)." }, { "kind": "news report", "citation": "Pineda D, Peterson B (2026). The same AP report as republished by Courthouse News Service, 4 May 2026.", "title": "States across the wildfire-prone Western US are using AI for early detection", "url": "https://www.courthousenews.com/states-across-the-wildfire-prone-western-us-are-using-ai-for-early-detection/", "date": "2026-05-04", "written_by": "independent", "quote": "Cindy Kobold, an Arizona Public Service meteorologist, said the technology notifies them about 45 minutes faster on average than the first 911 call." }, { "kind": "news report", "citation": "Daily Sun staff (2026). Seven-acre fire fully contained south of Flagstaff on Thursday afternoon. Arizona Daily Sun, 26 March 2026 (the article does not mention a camera).", "title": "Seven-acre fire fully contained south of Flagstaff on Thursday afternoon", "url": "https://azdailysun.com/news/local/seven-acre-fire-fully-contained-south-of-flagstaff-on-thursday-afternoon/article_585bebfe-c17c-4872-a37d-7e08195a39d7.html", "date": "2026-03-26", "written_by": "independent", "quote": "Forward progress on the fire was stopped at 3:37 p.m., about 80 minutes after the first report of the fire, and reached 100% containment at 6:09 p.m." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AP: an APS AI camera detected smoke on a March 2026 afternoon and crews contained the Diamond Fire before 7 acres; the Arizona Daily Sun's account of 26 March 2026 gives the timeline but no camera.", "account": "The Associated Press reported on 4 May 2026 that artificial intelligence detected something resembling smoke on a camera feed from Arizona's Coconino National Forest. The report is by Dorany Pineda and Brittany Peterson, on record in the KPBS and Courthouse News republications. The detection came on a March afternoon. One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs. The fire came to be known as the Diamond Fire. Firefighters raced to the scene and contained it before it grew past 7 acres (2.8 hectares). AP says APS has nearly 40 active AI smoke-detection cameras and plans 71 by summer's end. APS meteorologist Cindy Kobold says the technology notifies the utility about 45 minutes faster on average than the first 911 call. Pano AI, launched in 2020 and charging around $50,000 a year per camera, counts APS among its customers. It says it detected 725 wildfires in the US last year. AP does not state outright which company made the camera that spotted the Diamond Fire. The Arizona Daily Sun (staff report, 26 March 2026) reports that a small fire later named the Diamond Fire began shortly after 2 p.m. on Thursday. It started just north of Lake Mary Road, about three miles south-east of Lake Mary Road and Beulah Boulevard. That is south of Pine Canyon Golf Club and east of Flagstaff Pulliam Airport. It reached seven acres by 3:16 p.m. according to WatchDuty. Its forward progress was stopped at 3:37 p.m., about 80 minutes after the first report, and it was 100% contained at 6:09 p.m. The Daily Sun does not mention a camera, the Coconino National Forest or who made the first report. The two accounts are matched by the fire's name, month and size. No official incident record naming the camera was found; InciWeb's “Diamond Fire” is a June 2023 Scottsdale fire. The Daily Sun reported the fire that Thursday." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI smoke-detection camera installed for Arizona Public Service (AP lists APS among Pano AI's customers; the Diamond Fire camera's maker is not stated outright)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Pano AI, by implication of AP's customer list; not stated for this camera" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI smoke-detection camera installed for Arizona Public Service spots early signs of the March 2026 Diamond Fire in Coconino National Forest; crews hold it under 7 acres", "headline": "APS AI camera spots Diamond Fire; crews hold it under 7 acres" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c81aed4312d5a518f38cb56ae8aac7ef5e300608c8f387fa0b37d080e2be4538" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Associated Press reported on 4 May 2026 that artificial intelligence detected something resembling smoke on a camera feed from Arizona's Coconino National Forest. The report is by Dorany Pineda and Brittany Peterson, on record in the KPBS and Courthouse News republications. The detection came on a March afternoon. One of dozens of AI cameras installed for the utility Arizona Public Service had spotted early signs. The fire came to be known as the Diamond Fire. Firefighters raced to the scene and contained it before it grew past 7 acres (2.8 hectares). AP says APS has nearly 40 active AI smoke-detection cameras and plans 71 by summer's end. APS meteorologist Cindy Kobold says the technology notifies the utility about 45 minutes faster on average than the first 911 call. Pano AI, launched in 2020 and charging around $50,000 a year per camera, counts APS among its customers. It says it detected 725 wildfires in the US last year. AP does not state outright which company made the camera that spotted the Diamond Fire. The Arizona Daily Sun (staff report, 26 March 2026) reports that a small fire later named the Diamond Fire began shortly after 2 p.m. on Thursday. It started just north of Lake Mary Road, about three miles south-east of Lake Mary Road and Beulah Boulevard. That is south of Pine Canyon Golf Club and east of Flagstaff Pulliam Airport. It reached seven acres by 3:16 p.m. according to WatchDuty. Its forward progress was stopped at 3:37 p.m., about 80 minutes after the first report, and it was 100% contained at 6:09 p.m. The Daily Sun does not mention a camera, the Coconino National Forest or who made the first report. The two accounts are matched by the fire's name, month and size. No official incident record naming the camera was found; InciWeb's “Diamond Fire” is a June 2023 Scottsdale fire. The Daily Sun reported the fire that Thursday.", "replication": { "produced_by": [ "An AI smoke-detection camera network installed for a utility covering national-forest land near Flagstaff", "Human review of the AI detection, then notification to the utility and fire agencies. AP says human intervention keeps false positives low", "Crews able to reach a small fire on a March afternoon within about 80 minutes of the first report" ], "must_hold": [ "The camera has line of sight to the ignition and the detection reaches a responding agency before the fire grows", "Fire weather and fuels that allow containment at a few acres. The sources give no conditions for this fire" ], "echoes": [ { "date": "2024-06-16", "setting": "Pano AI cameras on Xcel and CORE Electric towers spot the Bear Creek Fire in Douglas County, Colorado; held to three acres (AIBD-0161)", "outcome": "recurred", "source": "AIBD-0161" }, { "date": "2024-07-09", "setting": "Xcel-funded Pano AI camera catches the Wellington fire near Breckenridge, Colorado; crews hold it to one-eighth of an acre (AIBD-0162)", "outcome": "recurred", "source": "AIBD-0162" }, { "setting": "Pano AI's own claim, relayed by AP, that its technology detected 725 wildfires in the US in the previous year; no outcomes given", "outcome": "unknown", "source": "Associated Press, 4 May 2026" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0159", "title": "Meta flags a Raebareli 18-year-old's Instagram suicide post at 8:58 pm; Uttar Pradesh Police reach him within 12 minutes after he took rat poison, and he is treated and stable", "summary": "29 March 2026: Meta alert at 8:58 pm; Raebareli police reached an 18-year-old in 12 minutes after rat poison; hospital treatment, stable", "date_observed": "2026-03-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 29 March 2026 an 18-year-old class 12 student from Raebareli, Uttar Pradesh, texted his girlfriend “Alvida” after a breakup. He lived within the Mill Area police station limits. He also posted a suicide video on Instagram with rat poison and messages of intent. At about 8:58 pm Meta flagged the content and emailed an alert to the Social Media Center at Uttar Pradesh Police headquarters. The center traced his mobile number and location and alerted Raebareli police. A police team reached his home within 12 minutes and found him in severe distress, with an empty rat-poison packet nearby. Police and family took him to a nearby hospital, where he was treated. On 1 April 2026 police said he was stable.", "category": "harm prevented", "unexpected": false, "purpose": "Meta's detection and review system is built to find posts and live videos that indicate suicide or self-injury risk. It routes them to trained reviewers and, in imminent cases, contacts local authorities. The Uttar Pradesh Police Social Media Center exists to act on those alerts. This rescue is that purpose.", "system": "Meta's suicide and self-injury detection and review pipeline on Instagram, with email alerts to the Uttar Pradesh Police Social Media Center at DGP headquarters", "model_version": null, "developer": "Meta Platforms", "deployer": "Meta Platforms with the Uttar Pradesh Police Social Media Center (Decode: Uttar Pradesh has been part of Meta's suicide-prevention program since 2022)", "location": "Raebareli, India", "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police", "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health.", "registry_ids": { "oecd_aim": "2026-04-01-6e56" }, "ratings": [ { "group": "personal", "depth": 4, "reason": "An 18-year-old who had taken rat poison was reached within 12 minutes of Meta's 8:58 pm alert. He was treated in hospital and reported stable. Officials said even a slight delay could have been fatal. No clinician is quoted and the rodenticide is not identified. The life-saving reading rests on the police account." } ], "ai_role": { "status": "assessed", "statement": "Police say Meta flagged the Instagram post at about 8:58 pm on 29 March and emailed the Uttar Pradesh Police Social Media Center. No source says whether Meta's classifier or a user report started the review. Decode reports that UP alerts arise from “artificial intelligence systems or user reports” reviewed by Meta staff. Everything after the email was human work. The center traced the phone number and location. Raebareli police reached the home in 12 minutes on the DGP's instructions, and a hospital treated him." }, "evidence": [ { "kind": "news report", "citation": "TNN (2026). Cops save 18-yr-old from suicide after Meta alert. The Times of India, Lucknow.", "title": "Cops save 18-yr-old from suicide after Meta alert", "url": "https://timesofindia.indiatimes.com/city/lucknow/cops-save-18-yr-old-from-suicide-after-meta-alert/articleshow/129935943.cms", "date": "2026-04-01", "written_by": "independent", "quote": "At around 8:58pm, Meta flagged the content and sent an alert via email to the social media centre at the UP police headquarters." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert. Telangana Today.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://telanganatoday.com/teens-life-saved-in-12-minutes-up-police-act-swiftly-after-social-media-suicide-alert", "date": "2026-04-01", "written_by": "independent", "quote": "The information was received by the police through Meta. Action was taken within minutes, and he was saved." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: Raebareli police act swiftly after social media suicide alert. IANS Live.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://ianslive.in/teens-life-saved-in-12-minutes-raebareli-police-act-swiftly-after-social-media-suicide-alert--20260401091324", "date": "2026-04-01", "written_by": "independent", "quote": "a video related to suicide was posted on Instagram, triggering an alert through the Meta Alert System at the police headquarters" }, { "kind": "news report", "citation": "Mathrubhumi English (2026). 'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen.", "title": "'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen", "url": "https://english.mathrubhumi.com/news/good-news/up-police-rescue-teen-social-media-alert-ar7x14gi", "date": "2026-04-01", "written_by": "independent", "quote": "police in Raebareli saved an 18-year-old youth after a distressing Instagram post triggered an automated alert through Meta's monitoring system" }, { "kind": "news report", "citation": "Srivastava, S. (2026). Meta Flagged A Suicide Post. Police Had Minutes To Save The Man. Decode (BOOM).", "title": "Meta Flagged A Suicide Post. Police Had Minutes To Save The Man", "url": "https://www.decodeinternet.in/decode/meta-sent-suicide-alert-uttar-pradesh-police-had-minutes-to-save-30394", "date": "2026-01-06", "written_by": "independent", "quote": "flagged—by artificial intelligence systems or user reports—as potentially indicating self-harm are reviewed by Meta and, in high-risk cases, shared with law enforcement partners" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it’s determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "press release", "citation": "Rosen, G. (2017). Getting Our Community Help in Real Time. Meta Newsroom.", "title": "Getting Our Community Help in Real Time", "url": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/", "date": "2017-11-27", "written_by": "makers", "quote": "Using pattern recognition to detect posts or live videos where someone might be expressing thoughts of suicide" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta. The Hans India, 10 June 2026.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "An Instagram post with rat poison and messages of intent, after a breakup. Meta's detection and review system flagged it as a suicide risk at about 8:58 pm on 29 March 2026", "A standing arrangement, in place since 2022 per Decode, under which Meta emails such alerts to the Uttar Pradesh Police Social Media Center. The center traces the account's phone number and location and forwards them to district police", "A Raebareli police team able to reach the Mill Area address within 12 minutes and take him to a nearby hospital with his family" ], "must_hold": [ "The post is flagged and reviewed while the person can still be treated. Here the alert came at about 8:58 pm and police arrived within 12 minutes", "The account leads to a phone number and a reachable address. Decode reports that UP police usually receive a phone number and trace the SIM and live location", "Officers and a hospital are available at once. Officials said even a slight delay could have been fatal" ], "echoes": [] }, "paired_incident": null, "headline": "Meta flags a suicide post; Raebareli police arrive in 12 minutes", "metric": "A police team reached his home within 12 minutes", "comparator": { "against": "reports escalated without Meta's pattern-recognition acceleration", "before": "escalation speed of other reports", "after": "escalated to local authorities twice as quickly as other reports", "basis": "measured", "quote": "We also use pattern recognition to help accelerate the most concerning reports. We’ve found these accelerated reports— that we have signaled require immediate attention—are escalated to local authorities twice as quickly as other reports.", "url": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/" }, "later": { "status": "persisted", "date": "2026-06-10", "note": "A further Meta alert on 7 June 2026 led Meerut police to reach a 25-year-old within eight minutes of a suicide post and get him to hospital.", "quote": "A 25-year-old man’s life was saved after Meerut Police acted on a suicide alert received from Meta following an Instagram post, reaching him within eight minutes and getting him admitted to a hospital, officials have said.", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-01-6e56", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/; https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0159", "catalog_version": "1.0.0", "source_fingerprint": "24892167a8185c5d54ff449ed7c0697ebac643babb4fe7e28ef0fa4aa89df921", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0159-source-0001", "AIBD-0159-source-0002", "AIBD-0159-source-0003", "AIBD-0159-source-0004", "AIBD-0159-source-0005", "AIBD-0159-source-0006", "AIBD-0159-source-0007", "AIBD-0159-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Meta Platforms", "deployer": "Meta Platforms with the Uttar Pradesh Police Social Media Center (Decode: Uttar Pradesh has been part of Meta's suicide-prevention program since 2022)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Police say Meta flagged the Instagram post at about 8:58 pm on 29 March and emailed the Uttar Pradesh Police Social Media Center. No source says whether Meta's classifier or a user report started the review. Decode reports that UP alerts arise from “artificial intelligence systems or user reports” reviewed by Meta staff. Everything after the email was human work. The center traced the phone number and location. Raebareli police reached the home in 12 minutes on the DGP's instructions, and a hospital treated him." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "Police say Meta flagged the Instagram post at about 8:58 pm on 29 March and emailed the Uttar Pradesh Police Social Media Center. No source says whether Meta's classifier or a user report started the review. Decode reports that UP alerts arise from “artificial intelligence systems or user reports” reviewed by Meta staff. Everything after the email was human work. The center traced the phone number and location. Raebareli police reached the home in 12 minutes on the DGP's instructions, and a hospital treated him." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "An 18-year-old who had taken rat poison was reached within 12 minutes of Meta's 8:58 pm alert. He was treated in hospital and reported stable. Officials said even a slight delay could have been fatal. No clinician is quoted and the rodenticide is not identified. The life-saving reading rests on the police account." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "An 18-year-old who had taken rat poison was reached within 12 minutes of Meta's 8:58 pm alert. He was treated in hospital and reported stable. Officials said even a slight delay could have been fatal. No clinician is quoted and the rodenticide is not identified. The life-saving reading rests on the police account." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "An 18-year-old who had taken rat poison was reached within 12 minutes of Meta's 8:58 pm alert. He was treated in hospital and reported stable. Officials said even a slight delay could have been fatal. No clinician is quoted and the rodenticide is not identified. The life-saving reading rests on the police account." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "A police team reached his home within 12 minutes", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-04-01-6e56" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-06-10", "note": "A further Meta alert on 7 June 2026 led Meerut police to reach a 25-year-old within eight minutes of a suicide post and get him to hospital.", "quote": "A 25-year-old man’s life was saved after Meerut Police acted on a suicide alert received from Meta following an Instagram post, reaching him within eight minutes and getting him admitted to a hospital, officials have said.", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0159" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 29 March 2026 an 18-year-old class 12 student from Raebareli, Uttar Pradesh, texted his girlfriend “Alvida” after a breakup. He lived within the Mill Area police station limits. He also posted a suicide video on Instagram with rat poison and messages of intent. At about 8:58 pm Meta flagged the content and emailed an alert to the Social Media Center at Uttar Pradesh Police headquarters. The center traced his mobile number and location and alerted Raebareli police. A police team reached his home within 12 minutes and found him in severe distress, with an empty rat-poison packet nearby. Police and family took him to a nearby hospital, where he was treated. On 1 April 2026 police said he was stable.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "An 18-year-old who had taken rat poison was reached within 12 minutes of Meta's 8:58 pm alert. He was treated in hospital and reported stable. Officials said even a slight delay could have been fatal. No clinician is quoted and the rodenticide is not identified. The life-saving reading rests on the police account." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Meta's detection and review system is built to find posts and live videos that indicate suicide or self-injury risk. It routes them to trained reviewers and, in imminent cases, contacts local authorities. The Uttar Pradesh Police Social Media Center exists to act on those alerts. This rescue is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Raebareli, India", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Meta's detection and review system is built to find posts and live videos that indicate suicide or self-injury risk. It routes them to trained reviewers and, in imminent cases, contacts local authorities. The Uttar Pradesh Police Social Media Center exists to act on those alerts. This rescue is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-03-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-01-6e56", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/; https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "An Instagram post with rat poison and messages of intent, after a breakup. Meta's detection and review system flagged it as a suicide risk at about 8:58 pm on 29 March 2026", "A standing arrangement, in place since 2022 per Decode, under which Meta emails such alerts to the Uttar Pradesh Police Social Media Center. The center traces the account's phone number and location and forwards them to district police", "A Raebareli police team able to reach the Mill Area address within 12 minutes and take him to a nearby hospital with his family" ], "must_hold": [ "The post is flagged and reviewed while the person can still be treated. Here the alert came at about 8:58 pm and police arrived within 12 minutes", "The account leads to a phone number and a reachable address. Decode reports that UP police usually receive a phone number and trace the SIM and live location", "Officers and a hospital are available at once. Officials said even a slight delay could have been fatal" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-01-6e56", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/; https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "TNN (2026). Cops save 18-yr-old from suicide after Meta alert. The Times of India, Lucknow.", "title": "Cops save 18-yr-old from suicide after Meta alert", "url": "https://timesofindia.indiatimes.com/city/lucknow/cops-save-18-yr-old-from-suicide-after-meta-alert/articleshow/129935943.cms", "date": "2026-04-01", "written_by": "independent", "quote": "At around 8:58pm, Meta flagged the content and sent an alert via email to the social media centre at the UP police headquarters." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert. Telangana Today.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://telanganatoday.com/teens-life-saved-in-12-minutes-up-police-act-swiftly-after-social-media-suicide-alert", "date": "2026-04-01", "written_by": "independent", "quote": "The information was received by the police through Meta. Action was taken within minutes, and he was saved." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: Raebareli police act swiftly after social media suicide alert. IANS Live.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://ianslive.in/teens-life-saved-in-12-minutes-raebareli-police-act-swiftly-after-social-media-suicide-alert--20260401091324", "date": "2026-04-01", "written_by": "independent", "quote": "a video related to suicide was posted on Instagram, triggering an alert through the Meta Alert System at the police headquarters" }, { "kind": "news report", "citation": "Mathrubhumi English (2026). 'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen.", "title": "'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen", "url": "https://english.mathrubhumi.com/news/good-news/up-police-rescue-teen-social-media-alert-ar7x14gi", "date": "2026-04-01", "written_by": "independent", "quote": "police in Raebareli saved an 18-year-old youth after a distressing Instagram post triggered an automated alert through Meta's monitoring system" }, { "kind": "news report", "citation": "Srivastava, S. (2026). Meta Flagged A Suicide Post. Police Had Minutes To Save The Man. Decode (BOOM).", "title": "Meta Flagged A Suicide Post. Police Had Minutes To Save The Man", "url": "https://www.decodeinternet.in/decode/meta-sent-suicide-alert-uttar-pradesh-police-had-minutes-to-save-30394", "date": "2026-01-06", "written_by": "independent", "quote": "flagged—by artificial intelligence systems or user reports—as potentially indicating self-harm are reviewed by Meta and, in high-risk cases, shared with law enforcement partners" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it’s determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "press release", "citation": "Rosen, G. (2017). Getting Our Community Help in Real Time. Meta Newsroom.", "title": "Getting Our Community Help in Real Time", "url": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/", "date": "2017-11-27", "written_by": "makers", "quote": "Using pattern recognition to detect posts or live videos where someone might be expressing thoughts of suicide" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta. The Hans India, 10 June 2026.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0159-source-0001", "AIBD-0159-source-0002", "AIBD-0159-source-0003", "AIBD-0159-source-0004", "AIBD-0159-source-0005", "AIBD-0159-source-0006", "AIBD-0159-source-0007", "AIBD-0159-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "TNN (2026). Cops save 18-yr-old from suicide after Meta alert. The Times of India, Lucknow.", "title": "Cops save 18-yr-old from suicide after Meta alert", "url": "https://timesofindia.indiatimes.com/city/lucknow/cops-save-18-yr-old-from-suicide-after-meta-alert/articleshow/129935943.cms", "date": "2026-04-01", "written_by": "independent", "quote": "At around 8:58pm, Meta flagged the content and sent an alert via email to the social media centre at the UP police headquarters." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert. Telangana Today.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://telanganatoday.com/teens-life-saved-in-12-minutes-up-police-act-swiftly-after-social-media-suicide-alert", "date": "2026-04-01", "written_by": "independent", "quote": "The information was received by the police through Meta. Action was taken within minutes, and he was saved." }, { "kind": "news report", "citation": "IANS (2026). Teen's life saved in 12 minutes: Raebareli police act swiftly after social media suicide alert. IANS Live.", "title": "Teen's life saved in 12 minutes: UP Police act swiftly after social media suicide alert", "url": "https://ianslive.in/teens-life-saved-in-12-minutes-raebareli-police-act-swiftly-after-social-media-suicide-alert--20260401091324", "date": "2026-04-01", "written_by": "independent", "quote": "a video related to suicide was posted on Instagram, triggering an alert through the Meta Alert System at the police headquarters" }, { "kind": "news report", "citation": "Mathrubhumi English (2026). 'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen.", "title": "'Alvida' text, poison post, and a 12-min race against death: How UP police saved a teen", "url": "https://english.mathrubhumi.com/news/good-news/up-police-rescue-teen-social-media-alert-ar7x14gi", "date": "2026-04-01", "written_by": "independent", "quote": "police in Raebareli saved an 18-year-old youth after a distressing Instagram post triggered an automated alert through Meta's monitoring system" }, { "kind": "news report", "citation": "Srivastava, S. (2026). Meta Flagged A Suicide Post. Police Had Minutes To Save The Man. Decode (BOOM).", "title": "Meta Flagged A Suicide Post. Police Had Minutes To Save The Man", "url": "https://www.decodeinternet.in/decode/meta-sent-suicide-alert-uttar-pradesh-police-had-minutes-to-save-30394", "date": "2026-01-06", "written_by": "independent", "quote": "flagged—by artificial intelligence systems or user reports—as potentially indicating self-harm are reviewed by Meta and, in high-risk cases, shared with law enforcement partners" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it’s determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "press release", "citation": "Rosen, G. (2017). Getting Our Community Help in Real Time. Meta Newsroom.", "title": "Getting Our Community Help in Real Time", "url": "https://about.fb.com/news/2017/11/getting-our-community-help-in-real-time/", "date": "2017-11-27", "written_by": "makers", "quote": "Using pattern recognition to detect posts or live videos where someone might be expressing thoughts of suicide" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta. The Hans India, 10 June 2026.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "29 March 2026: Meta alert at 8:58 pm; Raebareli police reached an 18-year-old in 12 minutes after rat poison; hospital treatment, stable", "account": "On 29 March 2026 an 18-year-old class 12 student from Raebareli, Uttar Pradesh, texted his girlfriend “Alvida” after a breakup. He lived within the Mill Area police station limits. He also posted a suicide video on Instagram with rat poison and messages of intent. At about 8:58 pm Meta flagged the content and emailed an alert to the Social Media Center at Uttar Pradesh Police headquarters. The center traced his mobile number and location and alerted Raebareli police. A police team reached his home within 12 minutes and found him in severe distress, with an empty rat-poison packet nearby. Police and family took him to a nearby hospital, where he was treated. On 1 April 2026 police said he was stable." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Meta's suicide and self-injury detection and review pipeline on Instagram, with email alerts to the Uttar Pradesh Police Social Media Center at DGP headquarters" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meta Platforms" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Meta flags a Raebareli 18-year-old's Instagram suicide post at 8:58 pm; Uttar Pradesh Police reach him within 12 minutes after he took rat poison, and he is treated and stable", "headline": "Meta flags a suicide post; Raebareli police arrive in 12 minutes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "24892167a8185c5d54ff449ed7c0697ebac643babb4fe7e28ef0fa4aa89df921" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 29 March 2026 an 18-year-old class 12 student from Raebareli, Uttar Pradesh, texted his girlfriend “Alvida” after a breakup. He lived within the Mill Area police station limits. He also posted a suicide video on Instagram with rat poison and messages of intent. At about 8:58 pm Meta flagged the content and emailed an alert to the Social Media Center at Uttar Pradesh Police headquarters. The center traced his mobile number and location and alerted Raebareli police. A police team reached his home within 12 minutes and found him in severe distress, with an empty rat-poison packet nearby. Police and family took him to a nearby hospital, where he was treated. On 1 April 2026 police said he was stable.", "replication": { "produced_by": [ "An Instagram post with rat poison and messages of intent, after a breakup. Meta's detection and review system flagged it as a suicide risk at about 8:58 pm on 29 March 2026", "A standing arrangement, in place since 2022 per Decode, under which Meta emails such alerts to the Uttar Pradesh Police Social Media Center. The center traces the account's phone number and location and forwards them to district police", "A Raebareli police team able to reach the Mill Area address within 12 minutes and take him to a nearby hospital with his family" ], "must_hold": [ "The post is flagged and reviewed while the person can still be treated. Here the alert came at about 8:58 pm and police arrived within 12 minutes", "The account leads to a phone number and a reachable address. Decode reports that UP police usually receive a phone number and trace the SIM and live location", "Officers and a hospital are available at once. Officials said even a slight delay could have been fatal" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0089", "title": "NHC's 2025 season verification: Google DeepMind ensemble mean outperformed official short-range Atlantic track forecasts in NHC's first operational use of AI models", "summary": "NHC's 2025 verification: Google DeepMind ensemble mean beat official Atlantic track forecasts at 12–72 h; first AI models in NHC operations.", "date_observed": "2026-03-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The National Hurricane Center's Forecast Verification Report for the 2025 season is dated 30 March 2026. It states that 2025 marked the first time NHC incorporated AI-based models into real-time operations. In the Atlantic track comparison, the Google DeepMind ensemble mean (GDMI) slightly outperformed the official forecast at lead times from 12 to 72 h. Official forecasts outperformed the consensus aids TVCA, HCCA and FSSE. In the eastern North Pacific, GDMI performed considerably better than every other individual model. It beat the official forecast and all consensus aids at 48–120 h. For intensity it was the top individual model from 12 to 48 h. GDMI was not available early in the season, so the first storms are excluded from these comparisons.", "category": "general benefit", "unexpected": false, "purpose": "Experimental AI tropical cyclone forecast model providing ensemble track and intensity guidance to NHC forecasters.", "system": "Google DeepMind AI hurricane forecast model, ensemble mean designated GDMI in NHC guidance", "model_version": null, "developer": "DeepMind", "deployer": "NOAA National Hurricane Center", "location": "Miami, United States", "domain": "Weather forecasting / tropical cyclones", "segment": "Public-sector meteorological service", "benefit_type": "Improved Task Accuracy", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Aggregate verification statistics, no discrete event." }, { "group": "organizational", "depth": null, "reason": "Aggregate verification statistics, no discrete event." }, { "group": "societal", "depth": null, "reason": "Aggregate verification statistics, no discrete event." } ], "ai_role": { "status": "assessed", "statement": "NHC's own homogeneous verification isolates GDMI's track and intensity performance against official forecasts, consensus aids and other models. The sample excludes early-season storms, when GDMI was unavailable." }, "evidence": [ { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, Section 1 (Introduction), p. 7. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (AI models statement)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "The 2025 season marked the first time that NHC incorporated AI-based models into real-time operations." }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, Atlantic track verification. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (Atlantic track)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "there was one model, the Google DeepMind ensemble mean (GDMI), that slightly outperformed NHC at the shorter lead times from 12 to 72 h" }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, eastern North Pacific track verification. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (eastern North Pacific track)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "GDMI performed considerably better than all of the other individual models and beat the official forecast and all of the consensus aids at 48-120 h." }, { "kind": "press release", "citation": "National Weather Service (n.d.). AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC Science Operation Officer Wallace Hogsett. 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NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (Atlantic track)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "there was one model, the Google DeepMind ensemble mean (GDMI), that slightly outperformed NHC at the shorter lead times from 12 to 72 h" }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, eastern North Pacific track verification. 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P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, Section 1 (Introduction), p. 7. NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (AI models statement)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "The 2025 season marked the first time that NHC incorporated AI-based models into real-time operations." }, { "kind": "report", "citation": "Cangialosi, J. P., Martinez, J., Reinhart, B., Papin, P. (2026). National Hurricane Center Forecast Verification Report: 2025 Hurricane Season, Atlantic track verification. 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NOAA/NHC, 30 March 2026.", "title": "NHC Forecast Verification Report, 2025 Hurricane Season (eastern North Pacific track)", "url": "https://www.nhc.noaa.gov/verification/pdfs/Verification_2025.pdf", "date": "2026-03-30", "written_by": "deployer", "quote": "GDMI performed considerably better than all of the other individual models and beat the official forecast and all of the consensus aids at 48-120 h." }, { "kind": "press release", "citation": "National Weather Service (n.d.). AI in Hurricane Forecasting at the National Hurricane Center: A Q&A with NHC Science Operation Officer Wallace Hogsett. 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It states that 2025 marked the first time NHC incorporated AI-based models into real-time operations. In the Atlantic track comparison, the Google DeepMind ensemble mean (GDMI) slightly outperformed the official forecast at lead times from 12 to 72 h. Official forecasts outperformed the consensus aids TVCA, HCCA and FSSE. In the eastern North Pacific, GDMI performed considerably better than every other individual model. It beat the official forecast and all consensus aids at 48–120 h. For intensity it was the top individual model from 12 to 48 h. GDMI was not available early in the season, so the first storms are excluded from these comparisons." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Google DeepMind AI hurricane forecast model, ensemble mean designated GDMI in NHC guidance" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeepMind" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "NHC's 2025 season verification: Google DeepMind ensemble mean outperformed official short-range Atlantic track forecasts in NHC's first operational use of AI models", "headline": "DeepMind's GDMI beats NHC Atlantic track forecasts at 12–72 h" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3d3a6d9a0d417e10c3ead3fee6a12f9ab36de4ba91189cd5339324317199cc25" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The National Hurricane Center's Forecast Verification Report for the 2025 season is dated 30 March 2026. It states that 2025 marked the first time NHC incorporated AI-based models into real-time operations. In the Atlantic track comparison, the Google DeepMind ensemble mean (GDMI) slightly outperformed the official forecast at lead times from 12 to 72 h. Official forecasts outperformed the consensus aids TVCA, HCCA and FSSE. In the eastern North Pacific, GDMI performed considerably better than every other individual model. It beat the official forecast and all consensus aids at 48–120 h. For intensity it was the top individual model from 12 to 48 h. GDMI was not available early in the season, so the first storms are excluded from these comparisons.", "replication": { "produced_by": [ "Real-time availability of the Google DeepMind ensemble to NHC for most of the 2025 season", "NHC's standard homogeneous verification procedure applied to early-model versions of the guidance" ], "must_hold": [ "Consistent timely delivery of the AI guidance (NHC notes some AI systems were not consistently available)", "Results from one season. NHC's Science Operations Officer says it takes a long time to fully evaluate new models" ], "echoes": [ { "date": "2024-09-08", "setting": "Independent CIRA evaluation of earlier open-source AI models (GraphCast-operational, Pangu-Weather, FourCastNet) on May-November 2023 cyclones: track errors comparable to best operational models", "model_version": "GraphCast-operational, Pangu-Weather, FourCastNet v1/v2-small", "outcome": "recurred", "source": "https://arxiv.org/abs/2409.06735" }, { "date": "2025-10-23", "setting": "Hurricane Melissa: NHC blended GDMI into official track and intensity forecasts", "outcome": "recurred", "source": "https://www.nhc.noaa.gov/archive/2025/al13/al132025.discus.010.shtml" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 0, "record_mapped": 30, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0343", "title": "After a UNEP MARS alert, operators repair a failed ball valve that released 175 t of methane in one week at the Aerial oil and gas field, Alberta, a week after detection (April 2026)", "summary": "Trade press relaying UNEP's August 2026 snapshot: a 175 t/week methane plume at Alberta's Aerial field in April 2026 was traced to a failed ball valve on pigging equipment and repaired within a week.", "date_observed": "2026-04-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Chemical Engineer reported on 4 September 2026 on UNEP's monthly snapshot of the biggest satellite-detected methane plumes recorded in August. UNEP confirmed that operators had plugged a source at the Aerial oil and gas field in southeastern Alberta, Canada. The source had released 175 t of methane (4,900 tCO2e) in a single week in April 2026. The cause was a failed ball valve connected to pigging equipment. Operators completed the repair one week after the plume was first detected. The repair followed an alert issued under UNEP's Methane Alert and Response System (MARS). The article states that UNEP does not name suspected or known operators. It states that since 2023 MARS has sent over 3,500 alerts but confirmed just 43 mitigation cases. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments. It couples that with scientific expertise and advanced AI models to notify governments and companies. The August 2026 UNEP snapshot itself is not among the sources; UNEP's snapshot page now carries the September 2026 update, which does not mention Canada. UNEP's press pages were not available and are not among the sources. The case rests on one trade-press report relaying UNEP.", "category": "benefit created", "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators mitigate them. This case was that purpose.", "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation", "model_version": null, "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed operators at the Aerial oil and gas field (repair)", "location": "Aerial oil and gas field, southeastern Alberta, Canada", "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas production; intergovernmental observatory", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 2, "reason": "The operator found and fixed a failed valve releasing 175 t of methane a week, within one week of detection. The operator is unnamed, and no cost or further detail is reported." }, { "group": "societal", "depth": 1, "reason": "A single confirmed case among about 43 since 2023, against more than 3,500 alerts. A one-week 4,900 tCO2e release was stopped." } ], "ai_role": { "status": "assessed", "statement": "The report credits the repair to a MARS alert and UNEP's confirmation. Only UNEP's general page describes MARS detection and analysis as using satellites with advanced AI models. The AI contribution to this specific alert is not isolated. One news item relaying the system operator's snapshot documents the event, and the snapshot itself is not among the sources." }, "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). Canada plugs 'major source' of methane emissions from oil and gas field leak. The Chemical Engineer, 4 Sep 2026.", "title": "Canada plugs 'major source' of methane emissions from oil and gas field leak", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Operators completed the repair work one week after the methane plume was first detected" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emission estimate.", "title": "Canada plugs 'major source' of methane emissions (emission estimate)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "175 t of methane (4,900 tCO2e) in a single week in April" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, cause of the leak.", "title": "Canada plugs 'major source' of methane emissions (cause)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "a failed ball valve connected to some pigging equipment" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, programme totals.", "title": "Canada plugs 'major source' of methane emissions (MARS totals)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Since 2023, MARS has sent over 3,500 alerts to operators of sites releasing methane plumes, but has confirmed just 43 mitigation cases." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "date": null, "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ], "replication": { "produced_by": [ "Satellite detection of a large plume at a producing field", "A MARS alert reaching operators able to inspect equipment within days", "A discrete equipment failure (ball valve on pigging equipment) that a repair could end" ], "must_hold": [ "Responsive operators or a national focal point. UNEP's snapshot says most mitigation occurs where focal points direct information", "Clear-sky satellite coverage to detect and later confirm cessation", "Independent confirmation beyond UNEP's own snapshot, which is not among the sources" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped by rerouting gas after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "model_version": null, "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091): MARS notification followed by repair", "model_version": null, "outcome": "recurred", "source": "AIBD-0091" } ] }, "paired_incident": null, "headline": "UNEP MARS alert leads to Alberta methane leak repair in a week", "metric": "released 175 t of methane (4,900 tCO2e) in a single week", "comparator": { "against": "the leak before repair", "before": "175 t of methane (4,900 tCO2e) in a single week in April", "after": "Operators completed the repair work one week after the methane plume was first detected.", "basis": "measured", "quote": "In its monthly snapshot of the biggest methane plumes recorded by satellites in August, the UNEP confirmed operators had plugged a source of methane that emitted 175 t of methane (4,900 tCO2e) in a single week in April.", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" }, "later": { "status": "unknown", "date": null, "note": "Nothing dated after the 4 September 2026 article was found; UNEP's September 2026 snapshot does not mention Canada.", "quote": null, "url": null }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0343", "catalog_version": "1.0.0", "source_fingerprint": "0ef391e4175d499d06ad640f10c507dee33241c2b451a8983764232aa2f2583e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0343-source-0001", "AIBD-0343-source-0002", "AIBD-0343-source-0003", "AIBD-0343-source-0004", "AIBD-0343-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); unnamed operators at the Aerial oil and gas field (repair)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The report credits the repair to a MARS alert and UNEP's confirmation. Only UNEP's general page describes MARS detection and analysis as using satellites with advanced AI models. The AI contribution to this specific alert is not isolated. One news item relaying the system operator's snapshot documents the event, and the snapshot itself is not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The report credits the repair to a MARS alert and UNEP's confirmation. Only UNEP's general page describes MARS detection and analysis as using satellites with advanced AI models. The AI contribution to this specific alert is not isolated. One news item relaying the system operator's snapshot documents the event, and the snapshot itself is not among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 2, "reason": "The operator found and fixed a failed valve releasing 175 t of methane a week, within one week of detection. The operator is unnamed, and no cost or further detail is reported." }, { "group": "societal", "depth": 1, "reason": "A single confirmed case among about 43 since 2023, against more than 3,500 alerts. A one-week 4,900 tCO2e release was stopped." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 2, "reason": "The operator found and fixed a failed valve releasing 175 t of methane a week, within one week of detection. 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"review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "released 175 t of methane (4,900 tCO2e) in a single week", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "Nothing dated after the 4 September 2026 article was found; UNEP's September 2026 snapshot does not mention Canada." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0343" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Chemical Engineer reported on 4 September 2026 on UNEP's monthly snapshot of the biggest satellite-detected methane plumes recorded in August. UNEP confirmed that operators had plugged a source at the Aerial oil and gas field in southeastern Alberta, Canada. The source had released 175 t of methane (4,900 tCO2e) in a single week in April 2026. The cause was a failed ball valve connected to pigging equipment. Operators completed the repair one week after the plume was first detected. The repair followed an alert issued under UNEP's Methane Alert and Response System (MARS). The article states that UNEP does not name suspected or known operators. It states that since 2023 MARS has sent over 3,500 alerts but confirmed just 43 mitigation cases. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments. It couples that with scientific expertise and advanced AI models to notify governments and companies. The August 2026 UNEP snapshot itself is not among the sources; UNEP's snapshot page now carries the September 2026 update, which does not mention Canada. UNEP's press pages were not available and are not among the sources. The case rests on one trade-press report relaying UNEP.", "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 2, "reason": "The operator found and fixed a failed valve releasing 175 t of methane a week, within one week of detection. The operator is unnamed, and no cost or further detail is reported." }, { "group": "societal", "depth": 1, "reason": "A single confirmed case among about 43 since 2023, against more than 3,500 alerts. A one-week 4,900 tCO2e release was stopped." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators mitigate them. This case was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Aerial oil and gas field, southeastern Alberta, Canada", "developer_country": "France", "deployer_country": "France" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Satellite-based detection and notification of large methane plumes so that operators mitigate them. This case was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-04-01", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Satellite detection of a large plume at a producing field", "A MARS alert reaching operators able to inspect equipment within days", "A discrete equipment failure (ball valve on pigging equipment) that a repair could end" ], "must_hold": [ "Responsive operators or a national focal point. UNEP's snapshot says most mitigation occurs where focal points direct information", "Clear-sky satellite coverage to detect and later confirm cessation", "Independent confirmation beyond UNEP's own snapshot, which is not among the sources" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped by rerouting gas after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091): MARS notification followed by repair", "outcome": "recurred", "source": "AIBD-0091" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Satellite detection of a large plume at a producing field", "A MARS alert reaching operators able to inspect equipment within days", "A discrete equipment failure (ball valve on pigging equipment) that a repair could end" ], "must_hold": [ "Responsive operators or a national focal point. UNEP's snapshot says most mitigation occurs where focal points direct information", "Clear-sky satellite coverage to detect and later confirm cessation", "Independent confirmation beyond UNEP's own snapshot, which is not among the sources" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped by rerouting gas after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091): MARS notification followed by repair", "outcome": "recurred", "source": "AIBD-0091" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas production; intergovernmental observatory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). Canada plugs 'major source' of methane emissions from oil and gas field leak. The Chemical Engineer, 4 Sep 2026.", "title": "Canada plugs 'major source' of methane emissions from oil and gas field leak", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Operators completed the repair work one week after the methane plume was first detected" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emission estimate.", "title": "Canada plugs 'major source' of methane emissions (emission estimate)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "175 t of methane (4,900 tCO2e) in a single week in April" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, cause of the leak.", "title": "Canada plugs 'major source' of methane emissions (cause)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "a failed ball valve connected to some pigging equipment" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, programme totals.", "title": "Canada plugs 'major source' of methane emissions (MARS totals)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Since 2023, MARS has sent over 3,500 alerts to operators of sites releasing methane plumes, but has confirmed just 43 mitigation cases." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0343-source-0001", "AIBD-0343-source-0002", "AIBD-0343-source-0003", "AIBD-0343-source-0004", "AIBD-0343-source-0005" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). Canada plugs 'major source' of methane emissions from oil and gas field leak. The Chemical Engineer, 4 Sep 2026.", "title": "Canada plugs 'major source' of methane emissions from oil and gas field leak", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Operators completed the repair work one week after the methane plume was first detected" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emission estimate.", "title": "Canada plugs 'major source' of methane emissions (emission estimate)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "175 t of methane (4,900 tCO2e) in a single week in April" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, cause of the leak.", "title": "Canada plugs 'major source' of methane emissions (cause)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "a failed ball valve connected to some pigging equipment" }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, programme totals.", "title": "Canada plugs 'major source' of methane emissions (MARS totals)", "url": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/", "date": "2026-09-04", "written_by": "independent", "quote": "Since 2023, MARS has sent over 3,500 alerts to operators of sites releasing methane plumes, but has confirmed just 43 mitigation cases." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Trade press relaying UNEP's August 2026 snapshot: a 175 t/week methane plume at Alberta's Aerial field in April 2026 was traced to a failed ball valve on pigging equipment and repaired within a week.", "account": "The Chemical Engineer reported on 4 September 2026 on UNEP's monthly snapshot of the biggest satellite-detected methane plumes recorded in August. UNEP confirmed that operators had plugged a source at the Aerial oil and gas field in southeastern Alberta, Canada. The source had released 175 t of methane (4,900 tCO2e) in a single week in April 2026. The cause was a failed ball valve connected to pigging equipment. Operators completed the repair one week after the plume was first detected. The repair followed an alert issued under UNEP's Methane Alert and Response System (MARS). The article states that UNEP does not name suspected or known operators. It states that since 2023 MARS has sent over 3,500 alerts but confirmed just 43 mitigation cases. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments. It couples that with scientific expertise and advanced AI models to notify governments and companies. The August 2026 UNEP snapshot itself is not among the sources; UNEP's snapshot page now carries the September 2026 update, which does not mention Canada. UNEP's press pages were not available and are not among the sources. The case rests on one trade-press report relaying UNEP." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UNEP International Methane Emissions Observatory (IMEO)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "After a UNEP MARS alert, operators repair a failed ball valve that released 175 t of methane in one week at the Aerial oil and gas field, Alberta, a week after detection (April 2026)", "headline": "UNEP MARS alert leads to Alberta methane leak repair in a week" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0ef391e4175d499d06ad640f10c507dee33241c2b451a8983764232aa2f2583e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Chemical Engineer reported on 4 September 2026 on UNEP's monthly snapshot of the biggest satellite-detected methane plumes recorded in August. UNEP confirmed that operators had plugged a source at the Aerial oil and gas field in southeastern Alberta, Canada. The source had released 175 t of methane (4,900 tCO2e) in a single week in April 2026. The cause was a failed ball valve connected to pigging equipment. Operators completed the repair one week after the plume was first detected. The repair followed an alert issued under UNEP's Methane Alert and Response System (MARS). The article states that UNEP does not name suspected or known operators. It states that since 2023 MARS has sent over 3,500 alerts but confirmed just 43 mitigation cases. UNEP's MARS page states that IMEO uses data from more than 30 satellite instruments. It couples that with scientific expertise and advanced AI models to notify governments and companies. The August 2026 UNEP snapshot itself is not among the sources; UNEP's snapshot page now carries the September 2026 update, which does not mention Canada. UNEP's press pages were not available and are not among the sources. The case rests on one trade-press report relaying UNEP.", "replication": { "produced_by": [ "Satellite detection of a large plume at a producing field", "A MARS alert reaching operators able to inspect equipment within days", "A discrete equipment failure (ball valve on pigging equipment) that a repair could end" ], "must_hold": [ "Responsive operators or a national focal point. UNEP's snapshot says most mitigation occurs where focal points direct information", "Clear-sky satellite coverage to detect and later confirm cessation", "Independent confirmation beyond UNEP's own snapshot, which is not among the sources" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped by rerouting gas after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091): MARS notification followed by repair", "outcome": "recurred", "source": "AIBD-0091" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0328", "title": "A CIA tool called “Ghost Murmur”, pairing quantum magnetometry with AI, may have located downed F-15E officer “Dude 44 Bravo” in Iran before his 4 April 2026 rescue", "summary": "The rescue is documented. The claim that Ghost Murmur located the airman rests on two anonymous sources and a subsequent presidential remark; its technical capability remains unverified.", "date_observed": "2026-04-04", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The April 6 White House briefing documents the rescue of the downed F-15E weapons systems officer in Iran. The official transcript also describes watching his suspected position with a camera from 40 miles away. That distance concerns the camera, not an established heartbeat-detection range. On April 7, the New York Post reported that two anonymous sources attributed the officer's location to a CIA tool called Ghost Murmur. They described quantum magnetic sensing combined with AI that separates a heartbeat signal from background noise, and attributed its development to Lockheed Martin's Skunk Works. Lockheed Martin declined to comment. In an April 8 telephone interview with the Post, President Trump called the tool important to the rescue, but supplied no technical explanation. The Post and Scientific American separately interviewed physicists who questioned the described capability. The official briefing does not name Ghost Murmur or establish an AI contribution. No public measurements or inspectable technical account establish that the claimed system located the officer.", "category": "harm prevented", "unexpected": false, "purpose": "Per the Post's sources, it is a tool built to find a human heartbeat at distance. The uses are intelligence collection and personnel recovery, and it was tested on Black Hawk helicopters. Its stated purpose is exactly the use claimed.", "system": "'Ghost Murmur': long-range quantum (nitrogen-vacancy diamond) magnetometry paired with AI software that isolates heartbeat signatures from background noise, as described by the NY Post's anonymous sources", "model_version": null, "developer": "Lockheed Martin Skunk Works, per two NY Post sources; the company declined to comment", "deployer": "US Central Intelligence Agency, per the NY Post; the CIA and White House named no tool", "location": "Mountains of southern Iran", "domain": "Defense and intelligence: combat search and rescue", "segment": "Remote personnel-location sensing", "benefit_type": "Improved Physical Health", "taxonomy_note": "A combat rescue is read as a health outcome because no rescue or defense type exists.", "registry_ids": { "oecd_aim": "2026-04-08-d905" }, "ratings": [ { "group": "personal", "depth": 5, "reason": "The weapons systems officer was found alive on 4 April 2026 and brought out with no US casualties, per Ratcliffe and Trump. Whether Ghost Murmur produced the find rests on the Post's anonymous sources and Trump's “very important”. Physicists dispute the described mechanism, and a beacon and a long-range camera were also in play." }, { "group": "organizational", "depth": null, "reason": "No source quantifies the tool's contribution to the search beyond Trump's remark. The mission also used human assets, deception, a camera at 40 miles and the airman's beacon." } ], "ai_role": { "status": "unassessed", "statement": "The Post's anonymous sources describe AI that isolates a heartbeat signal from sensor noise. No public technical evidence establishes that this system located the airman. The official account confirms the rescue and camera observation, while the later presidential remark does not establish the sensing method." }, "evidence": [ { "kind": "news report", "citation": "Steven Nelson, New York Post. 'Ghost Murmur,' a never-used secret tool, deployed to find lost airman in Iran in daring mission. 2026-04-07. Original reporting based on two anonymous sources.", "title": "'Ghost Murmur,' a never-used secret tool, deployed to find lost airman in Iran in daring mission", "url": "https://nypost.com/2026/04/07/us-news/ghost-murmur-a-never-used-secret-tool-deployed-to-find-lost-airman-in-iran-in-daring-mission/", "date": "2026-04-07", "written_by": "independent", "quote": null }, { "kind": "report", "citation": "White House; Daily Compilation of Presidential Documents. Remarks on the Rescue of United States Military Personnel in Iran and an Exchange With Reporters. 2026-04-06. DCPD-202600233, pp. 1–2 and 7. Official account of the rescue and long-range camera observation.", "title": "Remarks on the Rescue of United States Military Personnel in Iran and an Exchange With Reporters", "url": "https://www.govinfo.gov/content/pkg/DCPD-202600233/pdf/DCPD-202600233.pdf", "date": "2026-04-06", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Steven Nelson, New York Post. Trump confirms CIA 'Ghost Murmur' tool was ‘very important’ to find airman in Iran — as experts debate how it works. 2026-04-08. Adds a direct telephone interview with President Trump and interviews with physicists.", "title": "Trump confirms CIA 'Ghost Murmur' tool was ‘very important’ to find airman in Iran — as experts debate how it works", "url": "https://nypost.com/2026/04/08/us-news/trump-confirms-cia-ghost-murmur-tool-was-very-important-to-find-airman-in-iran-as-experts-debate-how-it-works/", "date": "2026-04-08", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Deni Ellis Béchard, Scientific American. Is the ‘Ghost Murmur’ quantum device possible? Scientists are skeptical. 2026-04-08. Adds original expert interviews challenging the publicly described sensing mechanism.", "title": "Is the ‘Ghost Murmur’ quantum device possible? Scientists are skeptical", "url": "https://www.scientificamerican.com/article/what-is-the-quantum-ghost-murmur-purportedly-used-in-iran-scientists/", "date": "2026-04-08", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A rescue operation that involved personnel, aircraft, intelligence, and camera observation", "An alleged AI-assisted sensing contribution whose specifications and performance are not public" ], "must_hold": [ "Public evidence of the sensing method and its role in locating the officer would be needed before identifying reproducible conditions for an AI benefit" ], "echoes": [] }, "paired_incident": null, "headline": "*Ghost Murmur* may have found downed F-15E officer", "metric": "one rescued airman; the claimed AI contribution remains unverified", "comparator": null, "later": { "status": "challenged", "date": "2026-04-08", "note": "Physicists interviewed by the Post and Scientific American disputed the public technical description. Their criticism does not establish that the rescue claim was formally reversed or withdrawn.", "quote": null, "url": "https://www.scientificamerican.com/article/what-is-the-quantum-ghost-murmur-purportedly-used-in-iran-scientists/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": [ "White House, April 6, 2026, DCPD-202600233, pp. 1–2 and 7. https://www.govinfo.gov/content/pkg/DCPD-202600233/pdf/DCPD-202600233.pdf", "Steven Nelson, New York Post, April 7 and 8, 2026. https://nypost.com/2026/04/07/us-news/ghost-murmur-a-never-used-secret-tool-deployed-to-find-lost-airman-in-iran-in-daring-mission/ https://nypost.com/2026/04/08/us-news/trump-confirms-cia-ghost-murmur-tool-was-very-important-to-find-airman-in-iran-as-experts-debate-how-it-works/", "Deni Ellis Béchard, Scientific American, April 8, 2026, original expert interviews. https://www.scientificamerican.com/article/what-is-the-quantum-ghost-murmur-purportedly-used-in-iran-scientists/" ], "brief": "The April 6 White House briefing documents the rescue of a downed American airman in Iran.[1] The claim that an AI-assisted quantum sensor located him comes from two anonymous sources in the New York Post. President Trump subsequently told the Post that the tool was important, without explaining how it worked.[2] Physicists interviewed by the Post and Scientific American questioned the described capability.[3] The rescue is established; the contribution attributed to Ghost Murmur remains unverified.", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Brief from Peter added.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Brief from Peter rewritten to say why the case matters now.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Sidenotes added to the brief.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.military.com/feature/2026/04/18/ghost-murmur-heartbeat-tracking-tech-has-experts-questioning-laws-of-physics.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Skunk_Works; https://www.cia.gov/legacy/headquarters/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced the incident-monitor summary with original reporting, separated camera distance from heartbeat claims, and corrected the unsupported reversal label.", "source": "https://nypost.com/2026/04/07/us-news/ghost-murmur-a-never-used-secret-tool-deployed-to-find-lost-airman-in-iran-in-daring-mission/", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and the deployer's report. 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Adds original expert interviews challenging the publicly described sensing mechanism." } ], "excluded_republications": [ { "url": "https://oecd.ai/en/incidents/2026-04-08-d905", "title": "CIA Uses AI System 'Ghost Murmur' to Rescue Downed Pilot in Iran", "published_on": "2026-04-08", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0001" }, { "url": "https://www.airandspaceforces.com/dude-44-rescue-massive-operation-iran-save-downed-airmen/", "title": "Inside the Massive Operation to Save Two Downed Airmen In Iran", "published_on": "2026-04-06", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0004" }, { "url": "https://www.military.com/feature/2026/04/18/ghost-murmur-heartbeat-tracking-tech-has-experts-questioning-laws-of-physics.html", "title": "Ghost Murmur: The Heartbeat-Tracking Tech That Has Experts Questioning the Laws of Physics", "published_on": "2026-04-18", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0006" }, { "url": "https://www.ynetnews.com/tech-and-digital/article/bywkzwhh11e", "title": "CIA's experimental ‘Ghost Murmur’ device reportedly helped locate downed pilot in Iran", "published_on": "2026-04-09", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0007" }, { "url": "https://thequantuminsider.com/2026/04/08/did-a-quantum-sensor-help-rescuers-find-a-downed-american-pilot/", "title": "Did a Quantum Sensor Help Rescuers Find a Downed American Pilot?", "published_on": "2026-04-08", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0008" }, { "url": "https://www.diariopanorama.com/noticia/548513/ghost-murmur-ciencia-o-ficcion-inedita-tecnologia-habria-usado-cia-para-rescate-iran", "title": "Ghost Murmur: ¿Ciencia o ficción?, la inédita tecnología que habría usado la CIA para el rescate en Irán", "published_on": "2026-04-10", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0328-source-0009" } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0328-source-0001", "retained_source_order": [ "AIBD-0328-source-0001", "AIBD-0328-source-0002", "AIBD-0328-source-0003", "AIBD-0328-source-0004" ], "ordering_basis": "The source that directly supports the central case leads. Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Alleged Ghost Murmur mechanism and role", "source_chain": [ { "url": "https://nypost.com/2026/04/07/us-news/ghost-murmur-a-never-used-secret-tool-deployed-to-find-lost-airman-in-iran-in-daring-mission/", "locator": "Body: two sources close to the breakthrough; Lockheed Martin response", "role": "Original anonymous-source reporting", "access_status": "Full relevant text reviewed", "published_on": "2026-04-07" } ], "limitations": [ "Anonymous sources; no technical measurements or inspectable device evidence" ], "source_ref": "AIBD-0328-source-0001" }, { "claim": "Rescue and camera observation", "source_chain": [ { "url": "https://www.govinfo.gov/content/pkg/DCPD-202600233/pdf/DCPD-202600233.pdf", "locator": "pp. 1–2 and 7", "role": "Original official briefing transcript", "access_status": "Full relevant text reviewed", "published_on": "2026-04-06" } ], "limitations": [ "The transcript does not name Ghost Murmur; the 40-mile statement concerns a camera", "Ratcliffe’s remarks are abridged in this official transcript; the full April 6 briefing transcript is archived at https://rollcall.com/factbase/trump/transcript/donald-trump-press-conference-briefing-room-april-6-2026/" ], "source_ref": "AIBD-0328-source-0002" }, { "claim": "Presidential remark and independent technical criticism", "source_chain": [ { "url": "https://nypost.com/2026/04/08/us-news/trump-confirms-cia-ghost-murmur-tool-was-very-important-to-find-airman-in-iran-as-experts-debate-how-it-works/", "locator": "Trump telephone interview and named physicist interviews", "role": "Original interviews", "access_status": "Full relevant text reviewed", "published_on": "2026-04-08" }, { "url": "https://www.scientificamerican.com/article/what-is-the-quantum-ghost-murmur-purportedly-used-in-iran-scientists/", "locator": "Interviews with John Wikswo, Chad Orzel, and Bradley Roth", "role": "Independent scrutiny of the public description", "access_status": "Indexed article text reviewed; direct publisher access was restricted" } ], "limitations": [ "Criticism of the public account is not an independent test of the actual classified device" ], "source_ref": "AIBD-0328-source-0003" } ], "limitations": [ "No independent evaluation of the alleged device", "Military.com full text could not be re-opened; it is not used for retained claims" ] } }, "provenance": { "kind": "source_review", "basis": "Replaced the incident-monitor summary with original reporting, separated camera distance from heartbeat claims, and corrected the unsupported reversal label.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0328-source-0001", "AIBD-0328-source-0002", "AIBD-0328-source-0003", "AIBD-0328-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The rescue is documented. The alleged device has no independent evaluation, and physicists dispute its described mechanism.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The rescue is documented. The claim that Ghost Murmur located the airman rests on two anonymous sources and a subsequent presidential remark; its technical capability remains unverified.", "account": "The April 6 White House briefing documents the rescue of the downed F-15E weapons systems officer in Iran. The official transcript also describes watching his suspected position with a camera from 40 miles away. That distance concerns the camera, not an established heartbeat-detection range. On April 7, the New York Post reported that two anonymous sources attributed the officer's location to a CIA tool called Ghost Murmur. They described quantum magnetic sensing combined with AI that separates a heartbeat signal from background noise, and attributed its development to Lockheed Martin's Skunk Works. Lockheed Martin declined to comment. In an April 8 telephone interview with the Post, President Trump called the tool important to the rescue, but supplied no technical explanation. The Post and Scientific American separately interviewed physicists who questioned the described capability. The official briefing does not name Ghost Murmur or establish an AI contribution. No public measurements or inspectable technical account establish that the claimed system located the officer." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0328-source-0001", "AIBD-0328-source-0002", "AIBD-0328-source-0003", "AIBD-0328-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "'Ghost Murmur': long-range quantum (nitrogen-vacancy diamond) magnetometry paired with AI software that isolates heartbeat signatures from background noise, as described by the NY Post's anonymous sources" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Lockheed Martin Skunk Works, per two NY Post sources; the company declined to comment" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "A CIA tool called “Ghost Murmur”, pairing quantum magnetometry with AI, may have located downed F-15E officer “Dude 44 Bravo” in Iran before his 4 April 2026 rescue", "headline": "*Ghost Murmur* may have found downed F-15E officer" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4678006907444b0cd74c0e1b28a900499156578134b32a7632876f04ae852846" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The April 6 White House briefing documents the rescue of the downed F-15E weapons systems officer in Iran. The official transcript also describes watching his suspected position with a camera from 40 miles away. That distance concerns the camera, not an established heartbeat-detection range. On April 7, the New York Post reported that two anonymous sources attributed the officer's location to a CIA tool called Ghost Murmur. They described quantum magnetic sensing combined with AI that separates a heartbeat signal from background noise, and attributed its development to Lockheed Martin's Skunk Works. Lockheed Martin declined to comment. In an April 8 telephone interview with the Post, President Trump called the tool important to the rescue, but supplied no technical explanation. The Post and Scientific American separately interviewed physicists who questioned the described capability. The official briefing does not name Ghost Murmur or establish an AI contribution. No public measurements or inspectable technical account establish that the claimed system located the officer.", "replication": { "produced_by": [ "A rescue operation that involved personnel, aircraft, intelligence, and camera observation", "An alleged AI-assisted sensing contribution whose specifications and performance are not public" ], "must_hold": [ "Public evidence of the sensing method and its role in locating the officer would be needed before identifying reproducible conditions for an AI benefit" ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0328-source-0001", "AIBD-0328-source-0002", "AIBD-0328-source-0003", "AIBD-0328-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 4, "record_mapped": 26, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0255", "title": "LNER's on-train AIVR camera AI flags a minor track fault near Retford a week after a driver-reported defect cost 10,000 delay minutes; overnight repair, zero delay minutes", "summary": "New Civil Engineer (6 Jul 2026) quoting LNER's 9 Apr 2026 announcement: after a January 2026 Cambridgeshire defect caused over 10,000 delay minutes, One Big Circle's AIVR identified a developing fa...", "date_observed": "2026-04-09", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "New Civil Engineer's Tom Pashby reported on 6 Jul 2026. His story was about the system flagging a snake as a track defect on 3 July. LNER runs the Pantograph Damage Assessment System (PANDAS) and One Big Circle's Automated Intelligent Video Review (AIVR) on a number of its trains. They assess overhead line equipment and track and report potential damage to Network Rail. The article reproduces LNER's 9 April 2026 announcement. In January 2026 a train driver in Cambridgeshire reported a track defect. It caused over 10,000 delay minutes, multiple cancellations and a full day of disruption. A week later the AIVR system identified a minor fault near Retford with the potential to become a larger issue. Engineers carried out an overnight repair with no delay to passengers and zero delay minutes. An LNER spokesperson said the information is fed back to Network Rail to target areas for attention. A Network Rail spokesperson said the snake would be raised automatically as standard practice. Network Rail's own 2022 story describes AIVR as a phone-sized front-of-train device applying machine learning to video of more than 20,000 miles of track. The exact day of the Retford detection is not given. LNER's announcement itself and later Southeastern and South Western Railway AIVR releases are not among the sources.", "category": "benefit created", "unexpected": false, "purpose": "AIVR is built to capture and analyze front-of-train video with machine learning. The aim is to find and fix track and lineside defects before they cause disruption.", "system": "Automated Intelligent Video Review (AIVR) front-of-train camera system with machine-learning analysis", "model_version": null, "developer": "One Big Circle", "deployer": "LNER (on-train cameras), with findings passed to Network Rail", "location": "Retford, United Kingdom", "domain": "Railway safety", "segment": "Track inspection / defect detection", "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "An overnight planned repair with zero delay minutes. The comparison is a defect the same month that cost over 10,000 delay minutes and a day of disruption." }, { "group": "societal", "depth": 1, "reason": "Passengers were spared delay from this fault. The scale of avoided disruption is not quantified." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "AIVR's analysis raised the fault report that Network Rail engineers acted on. No human had reported it. Whether the minor fault would have escalated is LNER's claim. Detection rates and false-positive rates are not published." }, "evidence": [ { "kind": "news report", "citation": "Pashby T (6 Jul 2026). AI system on LNER train misidentifies snake as track defect. New Civil Engineer.", "title": "AI system on LNER train misidentifies snake as track defect", "url": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/", "date": "2026-07-06", "written_by": "independent", "quote": "a week later, the AIVR system identified a minor fault which had the potential to turn into a larger issue near Retford." }, { "kind": "press release", "citation": "Network Rail (31 Oct 2022). Future Rail – how machine learning is improving your journeys.", "title": "Future Rail – how machine learning is improving your journeys", "url": "https://www.networkrail.co.uk/stories/future-rail-how-machine-learning-is-improving-your-journeys/", "date": "2022-10-31", "written_by": "deployer", "quote": "Automated Intelligent Video Review (AIVR) – developed by Bristol-based tech company One Big Circle – gathers a wide range of data from high-definition video around the railway." } ], "replication": { "produced_by": [ "Front-of-train cameras on scheduled passenger services covering the same track daily", "Machine-learning review that raises possible defects to the infrastructure manager", "A maintenance organization able to schedule overnight possessions" ], "must_hold": [ "Engineers triage AI reports promptly", "False positives (such as the snake) do not swamp the reporting channel", "The fault is visible from a train-mounted camera" ], "echoes": [ { "date": "2026-07-03", "setting": "The same AIVR system on an LNER train raised a snake crossing the line as a potential rail defect; Network Rail said raising it automatically was standard practice", "model_version": null, "outcome": "did not recur", "source": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/" } ] }, "paired_incident": null, "headline": "LNER AIVR flags a Retford track fault; overnight fix, zero delay", "metric": "an overnight repair with no delay to passengers and zero delay minutes", "comparator": { "against": "a track defect reported by a train driver a week earlier (January 2026, Cambridgeshire)", "before": "over 10,000 delay minutes, multiple cancellations, and led to a full day of disruption for customers", "after": "an overnight repair, with no delay to passengers, and zero delay minutes caused", "basis": "measured", "quote": "In January 2026, a track defect was reported by a train driver in Cambridgeshire which caused over 10,000 delay minutes, multiple cancellations, and led to a full day of disruption for customers. However, a week later, the AIVR system identified a minor fault which had the potential to turn into a larger issue near Retford. The report allowed engineers to carry out an overnight repair, with no delay to passengers, and zero delay minutes caused.", "url": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/" }, "later": { "status": "persisted", "date": "2026-07-06", "note": "The system was still running on LNER trains in July 2026, when it raised a snake crossing the line as a potential track defect; Network Rail said raising it automatically was standard practice.", "quote": "An artificial intelligence-powered system on an LNER (London North Eastern Railway) train designed to inform LNER and Network Rail about issues on the railway, misidentified a snake as a track defect.", "url": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/; https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.onebigcircle.co.uk/contact; https://en.wikipedia.org/wiki/London_North_Eastern_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0255", "catalog_version": "1.0.0", "source_fingerprint": "c075807381a97cbf07f267ea4cf5da92a2d06c318e0f1c74a67f9a0915908db7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0255-source-0001", "AIBD-0255-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "One Big Circle", "deployer": "LNER (on-train cameras), with findings passed to Network Rail" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AIVR's analysis raised the fault report that Network Rail engineers acted on. 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Future Rail – how machine learning is improving your journeys.", "title": "Future Rail – how machine learning is improving your journeys", "url": "https://www.networkrail.co.uk/stories/future-rail-how-machine-learning-is-improving-your-journeys/", "date": "2022-10-31", "written_by": "deployer", "quote": "Automated Intelligent Video Review (AIVR) – developed by Bristol-based tech company One Big Circle – gathers a wide range of data from high-definition video around the railway." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0255-source-0001", "AIBD-0255-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Pashby T (6 Jul 2026). 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Future Rail – how machine learning is improving your journeys.", "title": "Future Rail – how machine learning is improving your journeys", "url": "https://www.networkrail.co.uk/stories/future-rail-how-machine-learning-is-improving-your-journeys/", "date": "2022-10-31", "written_by": "deployer", "quote": "Automated Intelligent Video Review (AIVR) – developed by Bristol-based tech company One Big Circle – gathers a wide range of data from high-definition video around the railway." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "New Civil Engineer (6 Jul 2026) quoting LNER's 9 Apr 2026 announcement: after a January 2026 Cambridgeshire defect caused over 10,000 delay minutes, One Big Circle's AIVR identified a developing fa...", "account": "New Civil Engineer's Tom Pashby reported on 6 Jul 2026. His story was about the system flagging a snake as a track defect on 3 July. LNER runs the Pantograph Damage Assessment System (PANDAS) and One Big Circle's Automated Intelligent Video Review (AIVR) on a number of its trains. They assess overhead line equipment and track and report potential damage to Network Rail. The article reproduces LNER's 9 April 2026 announcement. In January 2026 a train driver in Cambridgeshire reported a track defect. It caused over 10,000 delay minutes, multiple cancellations and a full day of disruption. A week later the AIVR system identified a minor fault near Retford with the potential to become a larger issue. Engineers carried out an overnight repair with no delay to passengers and zero delay minutes. An LNER spokesperson said the information is fed back to Network Rail to target areas for attention. A Network Rail spokesperson said the snake would be raised automatically as standard practice. Network Rail's own 2022 story describes AIVR as a phone-sized front-of-train device applying machine learning to video of more than 20,000 miles of track. The exact day of the Retford detection is not given. 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His story was about the system flagging a snake as a track defect on 3 July. LNER runs the Pantograph Damage Assessment System (PANDAS) and One Big Circle's Automated Intelligent Video Review (AIVR) on a number of its trains. They assess overhead line equipment and track and report potential damage to Network Rail. The article reproduces LNER's 9 April 2026 announcement. In January 2026 a train driver in Cambridgeshire reported a track defect. It caused over 10,000 delay minutes, multiple cancellations and a full day of disruption. A week later the AIVR system identified a minor fault near Retford with the potential to become a larger issue. Engineers carried out an overnight repair with no delay to passengers and zero delay minutes. An LNER spokesperson said the information is fed back to Network Rail to target areas for attention. A Network Rail spokesperson said the snake would be raised automatically as standard practice. Network Rail's own 2022 story describes AIVR as a phone-sized front-of-train device applying machine learning to video of more than 20,000 miles of track. The exact day of the Retford detection is not given. LNER's announcement itself and later Southeastern and South Western Railway AIVR releases are not among the sources.", "replication": { "produced_by": [ "Front-of-train cameras on scheduled passenger services covering the same track daily", "Machine-learning review that raises possible defects to the infrastructure manager", "A maintenance organization able to schedule overnight possessions" ], "must_hold": [ "Engineers triage AI reports promptly", "False positives (such as the snake) do not swamp the reporting channel", "The fault is visible from a train-mounted camera" ], "echoes": [ { "date": "2026-07-03", "setting": "The same AIVR system on an LNER train raised a snake crossing the line as a potential rail defect; Network Rail said raising it automatically was standard practice", "outcome": "did not recur", "source": "https://www.newcivilengineer.com/latest/ai-system-on-lner-train-misidentifies-snake-as-track-defect-06-07-2026/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0235", "title": "Metropolitan Police announces exploration of AI to grade and triage child sexual abuse imagery to find unknown victims faster", "summary": "On 13 April 2026 the Met said it is exploring AI to grade and triage child sexual abuse imagery, testing with multiple companies, to flag unknown victims faster; no deployment or outcome yet.", "date_observed": "2026-04-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Metropolitan Police Service announced that it is exploring the use of artificial intelligence to support rapid grading and triage of child sexual abuse imagery. Material possibly relating to unknown victims could then be flagged for prioritized safeguarding. The force also wants to reduce officers' manual review of distressing material. It said it is in conversations with multiple companies and testing how this could work. It described a separate tool that reviews 641,000 messages in 35 minutes, and a £10 million investment in victim interview suites. It cited more than 5,400 child sexual abuse offenses investigated in the past year and over 1,300 children safeguarded. Deputy Commissioner Matt Jukes said speed matters for safeguarding and that human judgment and oversight would remain central. The OECD AI Incidents Monitor records it as an “AI hazard”, noting the use is under consideration and not implemented.", "category": "general benefit", "unexpected": false, "purpose": "Rapidly analyze seized imagery to grade it in categories A to C. Flag content possibly showing previously unknown victims. 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external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "On 13 April 2026 the Met said it is exploring AI to grade and triage child sexual abuse imagery, testing with multiple companies, to flag unknown victims faster; no deployment or outcome yet.", "account": "The Metropolitan Police Service announced that it is exploring the use of artificial intelligence to support rapid grading and triage of child sexual abuse imagery. Material possibly relating to unknown victims could then be flagged for prioritized safeguarding. The force also wants to reduce officers' manual review of distressing material. It said it is in conversations with multiple companies and testing how this could work. It described a separate tool that reviews 641,000 messages in 35 minutes, and a £10 million investment in victim interview suites. It cited more than 5,400 child sexual abuse offenses investigated in the past year and over 1,300 children safeguarded. Deputy Commissioner Matt Jukes said speed matters for safeguarding and that human judgment and oversight would remain central. The OECD AI Incidents Monitor records it as an “AI hazard”, noting the use is under consideration and not implemented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Unnamed AI grading and triage tools under evaluation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Multiple companies, not named" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Metropolitan Police announces exploration of AI to grade and triage child sexual abuse imagery to find unknown victims faster", "headline": "AI triage of abuse imagery under test to find victims faster" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d4b32d6bc90833c02f1ff5d0f72b7480ab0603ee0dd8f08319a0e38588e63293" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Metropolitan Police Service announced that it is exploring the use of artificial intelligence to support rapid grading and triage of child sexual abuse imagery. Material possibly relating to unknown victims could then be flagged for prioritized safeguarding. The force also wants to reduce officers' manual review of distressing material. It said it is in conversations with multiple companies and testing how this could work. It described a separate tool that reviews 641,000 messages in 35 minutes, and a £10 million investment in victim interview suites. It cited more than 5,400 child sexual abuse offenses investigated in the past year and over 1,300 children safeguarded. Deputy Commissioner Matt Jukes said speed matters for safeguarding and that human judgment and oversight would remain central. The OECD AI Incidents Monitor records it as an “AI hazard”, noting the use is under consideration and not implemented.", "replication": { "produced_by": [ "Large volumes of seized imagery awaiting manual grading", "Vendor classifiers for severity grading and known-versus-unknown victim flagging" ], "must_hold": [ "Legal and ethical frameworks for processing the material", "Human decision-making retained", "Evaluation showing acceptable error rates" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0374", "title": "Ukrainian ground robots and drones may have taken a Russian position with no infantry and no Ukrainian losses; the location, date, unit and prisoner count are undisclosed", "summary": "Zelenskyy (13 April 2026): an enemy position was taken “exclusively by unmanned platforms” with no infantry and no losses, per Politico and Business Insider; no location, date or verification.", "date_observed": "2026-04-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "President Volodymyr Zelenskyy gave an Arms Makers' Day address on Monday 13 April 2026. “For the first time in the history of this war, an enemy position was taken exclusively by unmanned platforms — ground systems and drones,” he said. He added that “the occupiers surrendered, and the operation was carried out without infantry and without losses on our side” (Politico, Business Insider, Censor.NET). He said ground robotic systems performed more than 22,000 missions on Ukraine's front line in the first three months of 2026. He named Ratel, TerMIT, Ardal, Rys, Zmiy, Protector and Volia. Newsweek says he did not say where the advance took place. No outlet gives a date, unit or prisoner count. Ars Technica says the claim is not independently verified and may refer to a 3rd Separate Assault Brigade action in Kharkiv Oblast last year. Politico calls the robots “currently piloted by humans from a safe distance”.", "category": "benefit created", "unexpected": false, "purpose": "Ukrainian unmanned ground vehicles and drones are built to carry out front-line missions in place of soldiers. Those missions include assaults, logistics and evacuation. Taking a position without exposing infantry is that purpose.", "system": "Ukrainian unmanned ground vehicles (Ratel, TerMIT, Ardal, Rys, Zmiy, Protector and Volia, as named by Zelenskyy) operating with aerial drones", "model_version": null, "developer": "Ukrainian makers of the named systems (Ratel, TerMIT, Ardal, Rys, Zmiy, Protector, Volia)", "deployer": "Ukrainian Defense Forces", "location": "Ukraine", "domain": "Defense: ground robotic systems in assault operations", "segment": "Unmanned ground vehicles and drones in combat", "benefit_type": "Reduced Risk", "taxonomy_note": "A combat action with no friendly losses is read as reduced potential for harm; no defense type exists.", "registry_ids": { "oecd_aim": "2026-04-13-ec31" }, "ratings": [ { "group": "organizational", "depth": null, "reason": "The capture, the surrender and the absence of losses rest solely on the President's statement. Newsweek says no location was given. Ars Technica and The Debrief say the claim is not independently verified, so the outcome is not established." } ], "ai_role": { "status": "unassessed", "statement": "No source describes an AI function in this operation. Politico says the ground robotic systems are “currently piloted by humans from a safe distance”. Jacob Parakilas of RAND Europe writes in The Conversation that they are “mostly still remotely operated”. He says autonomy is limited to tasks such as highlighting identified enemy positions. The Debrief says it is unclear how much remote human control was involved at each stage. Politico separately notes a January 2026 case in which a DevDroid robot “equipped with artificial intelligence elements” took three prisoners, a different event." }, "evidence": [ { "kind": "news report", "citation": "Melkozerova V (2026). Robots captured Russian army positions for first time in history, Zelenskyy says. POLITICO Europe, 14 April 2026.", "title": "Robots captured Russian army positions for first time in history, Zelenskyy says", "url": "https://www.politico.eu/article/volodymyr-zelenskyy-robotic-systems-russia-army-positions-ukraine/", "date": "2026-04-14", "written_by": "independent", "quote": "The Ukrainian army has been scaling up the use of ground robotic systems, currently piloted by humans from a safe distance, to perform different assault operations" }, { "kind": "news report", "citation": "Business Insider (2026). Ukraine said it captured a Russian position using only ground robots and drones, no infantry, for the first time. Business Insider, 14 April 2026.", "title": "Ukraine said it captured a Russian position using only ground robots and drones, no infantry, for the first time", "url": "https://www.businessinsider.com/ukraine-russia-position-taken-without-using-troops-just-robots-drones-2026-4", "date": "2026-04-14", "written_by": "independent", "quote": "Ukraine said it forced Russian soldiers to surrender and captured their position using only aerial drones and ground robots, no infantry, in a first for the war." }, { "kind": "news report", "citation": "Censor.NET (2026). Defense Forces capture enemy position for first time without infantry, using UGVs and drones, Zelenskyy says. Censor.NET, 13 April 2026.", "title": "Defense Forces capture enemy position for first time without infantry, using UGVs and drones, Zelenskyy says", "url": "https://censor.net/en/news/3610314/ukraine-s-defense-forces-seize-position-using-only-robots-and-drones", "date": "2026-04-13", "written_by": "independent", "quote": "The occupiers surrendered, and this operation was carried out without the involvement of infantry and without any losses on our side." }, { "kind": "news report", "citation": "Ars Technica (2026). Ukraine's military robot surge aims to offset drone risks to humans. Ars Technica, 14 April 2026.", "title": "Ukraine's military robot surge aims to offset drone risks to humans", "url": "https://arstechnica.com/ai/2026/04/ukraines-military-robot-surge-aims-to-offset-drone-risks-to-humans/", "date": "2026-04-14", "written_by": "independent", "quote": "The claim by Zelenskyy has not been independently verified but was accompanied by a promotional video" }, { "kind": "news report", "citation": "Robinson M, Cook E (2026). Putin's Troops Surrender Position to Robots for First Time: Zelensky. Newsweek, 14 April 2026.", "title": "Putin's Troops Surrender Position to Robots for First Time: Zelensky", "url": "https://www.newsweek.com/russia-ukraine-war-latest-putin-troops-surrender-military-robot-first-time-11825010", "date": "2026-04-14", "written_by": "independent", "quote": "The Ukrainian leader did not say where the advance took place." }, { "kind": "news report", "citation": "McMillan T (2026). Ukraine Says It Captured a Russian Position Using Only Unmanned Systems—A Glimpse of Future Warfare. The Debrief, 14 April 2026.", "title": "Ukraine Says It Captured a Russian Position Using Only Unmanned Systems—A Glimpse of Future Warfare", "url": "https://thedebrief.org/ukraine-says-it-captured-a-russian-position-using-only-unmanned-systems-a-glimpse-of-future-warfare/", "date": "2026-04-14", "written_by": "independent", "quote": "The claim has not yet been fully independently verified." }, { "kind": "other", "citation": "Parakilas J (2026). Robots just captured a Russian position in Ukraine – but don't worry about real-life Terminators just yet. The Conversation (analysis by a RAND Europe research leader), 17 April 2026.", "title": "Robots just captured a Russian position in Ukraine – but don't worry about real-life Terminators just yet", "url": "https://theconversation.com/robots-just-captured-a-russian-position-in-ukraine-but-dont-worry-about-real-life-terminators-just-yet-280959", "date": "2026-04-17", "written_by": "independent", "quote": "they are mostly still remotely operated, which means the operator must maintain a constant control link with the vehicle" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2026). Ukrainian AI Robots Capture Enemy Position Without Infantry. OECD.AI, 13 April 2026.", "title": "Ukrainian AI Robots Capture Enemy Position Without Infantry", "url": "https://oecd.ai/en/incidents/2026-04-13-ec31", "date": "2026-04-13", "written_by": "independent", "quote": "Ukrainian defense forces used unmanned ground robotic complexes and drones, powered by AI, to autonomously capture a Russian enemy position." } ], "replication": { "produced_by": [ "Ground robots and aerial drones available in numbers after a rapid rise in missions in early 2026", "Operators controlling the vehicles from a distance over radio, fiber or satellite links", "A Russian position whose defenders chose to surrender rather than fight the machines" ], "must_hold": [ "Control links survive electronic warfare and terrain", "Robots reach the position. Ars Technica cites a 38th Marine Brigade officer saying evacuation robots failed to reach positions in four of five cases", "Defenders are willing to surrender to unmanned systems" ], "echoes": [] }, "paired_incident": null, "headline": "Ukrainian robots and drones may have taken a Russian position alone", "metric": "more than 22,000 missions on Ukraine's front line", "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Ukraine", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-13-ec31", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Armed_Forces_of_Ukraine", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: six independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0374", "catalog_version": "1.0.0", "source_fingerprint": "f398651d3ee73cd9026c0ecbecc0d5f8d8b0481aced3c989bff304ddc13305e7", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0374-source-0001", "AIBD-0374-source-0002", "AIBD-0374-source-0003", "AIBD-0374-source-0004", "AIBD-0374-source-0005", "AIBD-0374-source-0006", "AIBD-0374-source-0007", "AIBD-0374-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Ukrainian makers of the named systems (Ratel, TerMIT, Ardal, Rys, Zmiy, Protector, Volia)", "deployer": "Ukrainian Defense Forces" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "unassessed", "statement": "No source describes an AI function in this operation. Politico says the ground robotic systems are “currently piloted by humans from a safe distance”. Jacob Parakilas of RAND Europe writes in The Conversation that they are “mostly still remotely operated”. He says autonomy is limited to tasks such as highlighting identified enemy positions. The Debrief says it is unclear how much remote human control was involved at each stage. Politico separately notes a January 2026 case in which a DevDroid robot “equipped with artificial intelligence elements” took three prisoners, a different event." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: six independent news reports, a registry entry and one other independent source. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The capture, the surrender and the absence of losses rest solely on the President's statement. Newsweek says no location was given. Ars Technica and The Debrief say the claim is not independently verified, so the outcome is not established." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The capture, the surrender and the absence of losses rest solely on the President's statement. Newsweek says no location was given. 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Ukraine Says It Captured a Russian Position Using Only Unmanned Systems—A Glimpse of Future Warfare. The Debrief, 14 April 2026.", "title": "Ukraine Says It Captured a Russian Position Using Only Unmanned Systems—A Glimpse of Future Warfare", "url": "https://thedebrief.org/ukraine-says-it-captured-a-russian-position-using-only-unmanned-systems-a-glimpse-of-future-warfare/", "date": "2026-04-14", "written_by": "independent", "quote": "The claim has not yet been fully independently verified." }, { "kind": "other", "citation": "Parakilas J (2026). Robots just captured a Russian position in Ukraine – but don't worry about real-life Terminators just yet. 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The Conversation (analysis by a RAND Europe research leader), 17 April 2026.", "title": "Robots just captured a Russian position in Ukraine – but don't worry about real-life Terminators just yet", "url": "https://theconversation.com/robots-just-captured-a-russian-position-in-ukraine-but-dont-worry-about-real-life-terminators-just-yet-280959", "date": "2026-04-17", "written_by": "independent", "quote": "they are mostly still remotely operated, which means the operator must maintain a constant control link with the vehicle" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2026). Ukrainian AI Robots Capture Enemy Position Without Infantry. OECD.AI, 13 April 2026.", "title": "Ukrainian AI Robots Capture Enemy Position Without Infantry", "url": "https://oecd.ai/en/incidents/2026-04-13-ec31", "date": "2026-04-13", "written_by": "independent", "quote": "Ukrainian defense forces used unmanned ground robotic complexes and drones, powered by AI, to autonomously capture a Russian enemy position." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Zelenskyy (13 April 2026): an enemy position was taken “exclusively by unmanned platforms” with no infantry and no losses, per Politico and Business Insider; no location, date or verification.", "account": "President Volodymyr Zelenskyy gave an Arms Makers' Day address on Monday 13 April 2026. “For the first time in the history of this war, an enemy position was taken exclusively by unmanned platforms — ground systems and drones,” he said. He added that “the occupiers surrendered, and the operation was carried out without infantry and without losses on our side” (Politico, Business Insider, Censor.NET). He said ground robotic systems performed more than 22,000 missions on Ukraine's front line in the first three months of 2026. He named Ratel, TerMIT, Ardal, Rys, Zmiy, Protector and Volia. Newsweek says he did not say where the advance took place. No outlet gives a date, unit or prisoner count. Ars Technica says the claim is not independently verified and may refer to a 3rd Separate Assault Brigade action in Kharkiv Oblast last year. Politico calls the robots “currently piloted by humans from a safe distance”." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Ukrainian unmanned ground vehicles (Ratel, TerMIT, Ardal, Rys, Zmiy, Protector and Volia, as named by Zelenskyy) operating with aerial drones" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Ukrainian makers of the named systems (Ratel, TerMIT, Ardal, Rys, Zmiy, Protector, Volia)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Ukrainian ground robots and drones may have taken a Russian position with no infantry and no Ukrainian losses; the location, date, unit and prisoner count are undisclosed", "headline": "Ukrainian robots and drones may have taken a Russian position alone" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f398651d3ee73cd9026c0ecbecc0d5f8d8b0481aced3c989bff304ddc13305e7" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "President Volodymyr Zelenskyy gave an Arms Makers' Day address on Monday 13 April 2026. “For the first time in the history of this war, an enemy position was taken exclusively by unmanned platforms — ground systems and drones,” he said. He added that “the occupiers surrendered, and the operation was carried out without infantry and without losses on our side” (Politico, Business Insider, Censor.NET). He said ground robotic systems performed more than 22,000 missions on Ukraine's front line in the first three months of 2026. He named Ratel, TerMIT, Ardal, Rys, Zmiy, Protector and Volia. Newsweek says he did not say where the advance took place. No outlet gives a date, unit or prisoner count. Ars Technica says the claim is not independently verified and may refer to a 3rd Separate Assault Brigade action in Kharkiv Oblast last year. Politico calls the robots “currently piloted by humans from a safe distance”.", "replication": { "produced_by": [ "Ground robots and aerial drones available in numbers after a rapid rise in missions in early 2026", "Operators controlling the vehicles from a distance over radio, fiber or satellite links", "A Russian position whose defenders chose to surrender rather than fight the machines" ], "must_hold": [ "Control links survive electronic warfare and terrain", "Robots reach the position. Ars Technica cites a 38th Marine Brigade officer saying evacuation robots failed to reach positions in four of five cases", "Defenders are willing to surrender to unmanned systems" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0251", "title": "Orca AI's watchkeeping may have cut high-severity close encounters 52% across 139 container ships in its first year", "summary": "Riviera and Hellenic Shipping News (16 Apr 2026): the P&I club and Orca AI analyzed 10.8 million nautical miles; high-severity close encounters fell from 2.7 to 1.3 per vessel-month between months ...", "date_observed": "2026-04-15", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Trade reports published on 15 and 16 Apr 2026 describe a study by the protection and indemnity insurer NorthStandard with Orca AI. The reports are MarineLink, Riviera Maritime Media's Martyn Wingrove, and Hellenic Shipping News reproducing Orca AI's release. The study covered a globally operating cohort of 139 container vessels fitted with Orca AI's navigation platform. Across more than 10.8 million nautical miles, it compared the first three months after installation with months 10 to 12. It reported a 52% reduction in high-severity close encounters, with 22% within the first six months. The reduction was 36% in the North and Baltic Seas and 18% in the seas around China and Japan. Encounters were defined by closest point of approach, time to closest point of approach, COLREGs interactions and traffic density. Orca AI's report page states that such encounters declined from 2.7 per vessel per month early after implementation to 1.3 by months 10 to 12. NorthStandard's head of loss prevention Colin Gillespie and Orca AI's chief executive Yarden Gross are quoted. The design is a before-and-after comparison on the same vessels with no control fleet, and the report is hosted by the vendor.", "category": "general benefit", "unexpected": false, "purpose": "Orca AI's platform is built to give bridge teams AI-assisted situational awareness and earlier detection of risky targets.", "system": "Orca AI navigation platform (digital watchkeeper modules and software)", "model_version": "Orca AI SeaPod digital watchkeeper", "developer": "Orca AI", "deployer": "Operators of 139 container vessels insured with NorthStandard", "location": null, "domain": "Maritime safety", "segment": "Commercial shipping / navigational decision support", "benefit_type": "Increased Product Safety", "taxonomy_note": "The metric is close encounters rather than collisions.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Aggregate change in a proxy metric; no collision, claim or cost outcome is documented." }, { "group": "societal", "depth": null, "reason": "No outcome beyond the proxy metric is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "The platform's detections feed bridge decisions. The reported reduction compares the same vessels early and late in their first year. Crew familiarization, seasonality and route changes are not separated from the system's effect." }, "evidence": [ { "kind": "news report", "citation": "Wingrove M (16 Apr 2026). NorthStandard study demonstrates benefits of AI navigation support. Riviera Maritime Media.", "title": "NorthStandard study demonstrates benefits of AI navigation support", "url": "https://www.rivieramm.com/news-content-hub/news-content-hub/northstandard-study-demonstrates-benefits-of-ai-navigation-support-88473", "date": "2026-04-16", "written_by": "independent", "quote": "NorthStandard P&I club undertook a 12-month study with Orca AI, using its AI navigation services for a cohort of 139 container vessels." }, { "kind": "press release", "citation": "Hellenic Shipping News (16 Apr 2026). Joint Orca AI-NorthStandard study highlights strong impact of AI on navigational safety (source credited as Orca AI).", "title": "Joint Orca AI-NorthStandard study highlights strong impact of AI on navigational safety", "url": "https://www.hellenicshippingnews.com/joint-orca-ai-northstandard-study-highlights-strong-impact-of-ai-on-navigational-safety/", "date": "2026-04-16", "written_by": "makers", "quote": "What we’re seeing through our work with Orca AI, and now reinforced by this study, is that improved situational awareness and earlier risk detection can materially reduce close-quarters situations." }, { "kind": "news report", "citation": "MarineLink / Maritime Activity Reports (15 Apr 2026). Study From Orca AI, NorthStandard Highlights Role of AI on Navigational Safety.", "title": "Study From Orca AI, NorthStandard Highlights Role of AI on Navigational Safety", "url": "https://www.marinelink.com/news/study-orca-ai-northstandard-highlights-538079", "date": "2026-04-15", "written_by": "independent", "quote": "The study examined more than 10.8 million nautical miles of voyages, comparing the initial system adaptation period (first three months after installation) with the stabilized usage phase (months 10–12)." }, { "kind": "press release", "citation": "Orca AI (2026). Orca AI and NorthStandard Safety Report (report landing page).", "title": "Orca AI and NorthStandard Safety Report", "url": "https://www.orca-ai.io/reports/safetyreport/", "date": null, "written_by": "makers", "quote": "High-severity close encounters declined from 2.7 per vessel per month in the early post-implementation phase to 1.3 by months 10–12 - a 52% reduction." }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-04-15-b7a4: AI Navigation System Reduces Maritime Near Misses by 52%.", "title": "AI Navigation System Reduces Maritime Near Misses by 52%", "url": "https://oecd.ai/en/incidents/2026-04-15-b7a4", "date": "2026-04-15", "written_by": "independent", "quote": "deploying Orca AI's navigation platform on 139 container vessels led to a 52% reduction in high-severity close encounters over 12 months" }, { "kind": "report", "citation": "Orca AI and NorthStandard (Mar 2026). Orca AI and NorthStandard Safety Report: Orca AI's impact on navigational safety.", "title": "Orca AI and NorthStandard Safety Report", "url": "https://d3cpegos94401u.cloudfront.net/publications/documents/orca-ai-&-northstandard-safety-report---final.pdf", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Fleet-wide installation of a sensor-and-software watchkeeping platform", "Twelve months of anonymized operational data per vessel", "An insurer willing to analyze member-fleet data" ], "must_hold": [ "Crews keep using the system after the adaptation phase", "The close-encounter definition stays constant across the comparison", "Routes and traffic density are comparable between periods" ], "echoes": [ { "date": "2020-04-15", "setting": "Shore-side AI collision-risk prediction at the Tokyo Wan VTS Center: warnings about two minutes earlier in simulated tasks (Maritime Executive)", "model_version": null, "outcome": "unknown", "source": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers" } ] }, "paired_incident": null, "headline": "Orca AI may have cut high-severity close encounters by 52%", "metric": "high-severity close encounters fell from 2.7 to 1.3 per vessel-month", "comparator": { "against": "the same vessels' first three months after installation (early post-implementation phase), no control fleet", "before": "2.7 per vessel per month in the early post-implementation phase", "after": "1.3 by months 10–12 - a 52% reduction", "basis": "measured", "quote": "High-severity close encounters declined from 2.7 per vessel per month in the early post-implementation phase to 1.3 by months 10–12 - a 52% reduction.", "url": "https://www.orca-ai.io/reports/safetyreport/" }, "later": { "status": "unknown", "date": null, "note": "No development after the report of 15 April 2026 is established. The vendor's October 2025 post predates it.", "quote": null, "url": null }, "value": null, "developer_country": "United Kingdom", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the model version from the cited sources.", "source": "https://www.orca-ai.io/reports/safetyreport/; https://d3cpegos94401u.cloudfront.net/publications/documents/orca-ai-&-northstandard-safety-report---final.pdf", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.orca-ai.io/contact", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, a registry entry, the makers' report and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0251", "catalog_version": "1.0.0", "source_fingerprint": "3e2ae9be39315bbb7ce89e6cf4892315109aaf1fac6e2d44cfac2c982c9674f6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0251-source-0001", "AIBD-0251-source-0002", "AIBD-0251-source-0003", "AIBD-0251-source-0004", "AIBD-0251-source-0005", "AIBD-0251-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Orca AI", "deployer": "Operators of 139 container vessels insured with NorthStandard" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The platform's detections feed bridge decisions. The reported reduction compares the same vessels early and late in their first year. Crew familiarization, seasonality and route changes are not separated from the system's effect." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The platform's detections feed bridge decisions. The reported reduction compares the same vessels early and late in their first year. Crew familiarization, seasonality and route changes are not separated from the system's effect." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, a registry entry, the makers' report and two press releases from the makers. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Aggregate change in a proxy metric; no collision, claim or cost outcome is documented." }, { "group": "societal", "reason": "No outcome beyond the proxy metric is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Aggregate change in a proxy metric; no collision, claim or cost outcome is documented." }, { "group": "societal", "reason": "No outcome beyond the proxy metric is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": 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Study From Orca AI, NorthStandard Highlights Role of AI on Navigational Safety.", "title": "Study From Orca AI, NorthStandard Highlights Role of AI on Navigational Safety", "url": "https://www.marinelink.com/news/study-orca-ai-northstandard-highlights-538079", "date": "2026-04-15", "written_by": "independent", "quote": "The study examined more than 10.8 million nautical miles of voyages, comparing the initial system adaptation period (first three months after installation) with the stabilized usage phase (months 10–12)." }, { "kind": "press release", "citation": "Orca AI (2026). 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The design is a before-and-after comparison on the same vessels with no control fleet, and the report is hosted by the vendor." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The platform detected navigational hazards for the ship’s crew to assess." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The vessel used Orca AI’s SeaPod system." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Orca AI SeaPod digital watchkeeper" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Orca AI navigation platform (digital watchkeeper modules and software)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Orca AI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Orca AI's watchkeeping may have cut high-severity close encounters 52% across 139 container ships in its first year", "headline": "Orca AI may have cut high-severity close encounters by 52%" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3e2ae9be39315bbb7ce89e6cf4892315109aaf1fac6e2d44cfac2c982c9674f6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Trade reports published on 15 and 16 Apr 2026 describe a study by the protection and indemnity insurer NorthStandard with Orca AI. The reports are MarineLink, Riviera Maritime Media's Martyn Wingrove, and Hellenic Shipping News reproducing Orca AI's release. The study covered a globally operating cohort of 139 container vessels fitted with Orca AI's navigation platform. Across more than 10.8 million nautical miles, it compared the first three months after installation with months 10 to 12. It reported a 52% reduction in high-severity close encounters, with 22% within the first six months. The reduction was 36% in the North and Baltic Seas and 18% in the seas around China and Japan. Encounters were defined by closest point of approach, time to closest point of approach, COLREGs interactions and traffic density. Orca AI's report page states that such encounters declined from 2.7 per vessel per month early after implementation to 1.3 by months 10 to 12. NorthStandard's head of loss prevention Colin Gillespie and Orca AI's chief executive Yarden Gross are quoted. The design is a before-and-after comparison on the same vessels with no control fleet, and the report is hosted by the vendor.", "replication": { "produced_by": [ "Fleet-wide installation of a sensor-and-software watchkeeping platform", "Twelve months of anonymized operational data per vessel", "An insurer willing to analyze member-fleet data" ], "must_hold": [ "Crews keep using the system after the adaptation phase", "The close-encounter definition stays constant across the comparison", "Routes and traffic density are comparable between periods" ], "echoes": [ { "date": "2020-04-15", "setting": "Shore-side AI collision-risk prediction at the Tokyo Wan VTS Center: warnings about two minutes earlier in simulated tasks (Maritime Executive)", "outcome": "unknown", "source": "https://www.maritime-executive.com/article/ai-system-tested-by-tokyo-bay-vessel-traffic-controllers" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0205", "title": "Southern Water's sewer-monitor anomaly model flagged a forming fatberg in Rowner, Gosport, and a crew cleared it before any overflow into the River Alver", "summary": "Southern Water's AI sewer monitors flagged a forming fatberg in Rowner, Gosport; a crew cleared it before any overflow into the River Alver.", "date_observed": "2026-04-22", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Southern Water runs around 34,000 sewer level monitors with machine learning. Its proactive operations control manager Daniel McElhinney says the system learns the normal behavior of sewers. He says it can tell a forming blockage from daily rushes or rain. Shortly before 22 April 2026 the sensors detected an abnormal flow in Rowner, Gosport, and alerted the control room. A crew jetted the sewer and found a fatberg of wet wipes and other unflushable items. The company said that, left unchecked, the sewer could have overflowed from a manhole into a surface water drain leading to the River Alver. The case was reported on 22 April 2026. A second flagged blockage at Warlands Lane, Shalfleet, Isle of Wight, was reported on 23 April.", "category": "protective response", "unexpected": false, "purpose": "The monitors and the anomaly model were installed to spot blockages and leaks forming in sewers. Crews can then clear them before they cause pollution or flooding. This case was that intended use.", "system": "Southern Water's AI-enabled digital sewer system: a network of around 34,000 sewer level monitors in blockage hotspots with machine learning that learns normal sewer behavior and flags a forming blockage", "model_version": null, "developer": null, "deployer": "Southern Water", "location": "Gosport, United Kingdom", "domain": "Wastewater networks / pollution prevention", "segment": "Regulated water and wastewater utility", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "A sewage overflow averted is pollution prevented, which Trustible's description does not name.", "registry_ids": { "oecd_aim": "2026-04-22-7047" }, "ratings": [ { "group": "societal", "depth": 2, "reason": "The company says a sewage overflow into the River Alver was averted. The Andover Advertiser says the river is home to herons, water voles and kingfishers. The counterfactual is asserted rather than shown, and no pollution occurred. This is a specific avoided harm of unmeasured size." }, { "group": "organizational", "depth": 1, "reason": "Southern Water cleared one blockage before it became a pollution incident or a customer flooding. The company says blocked sewers are the leading cause of its pollution incidents. This is one of the more than 4,000 interventions it reports in a year." } ], "ai_role": { "status": "assessed", "statement": "The level monitors detected an abnormal flow at Rowner. The machine-learning model raised the alert to the control room; by the company's account it distinguishes a forming blockage from daily rushes and rainfall. The jetting crew found and removed the fatberg. The articles are built on a Southern Water statement and a single quoted manager. They do not name the developer of the model and give no sensor data. No independent party confirmed that an overflow was imminent." }, "evidence": [ { "kind": "news report", "citation": "Southern Daily Echo (2026). Fatberg found in Gosport removed before causing damage. dailyecho.co.uk, 23 April 2026; reproduces a Southern Water statement.", "title": "Fatberg found in Gosport removed before causing damage", "url": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/", "date": "2026-04-23", "written_by": "independent", "quote": "Southern Water prevented sewage pollution of the River Alver in Gosport with the help of its AI-enabled digital sewer system and rapid action from its teams." }, { "kind": "news report", "citation": "Andover Advertiser (2026). Southern Water using AI to prevent pollution incidents. andoveradvertiser.co.uk, 25 April 2026; reproduces a Southern Water statement.", "title": "Southern Water using AI to prevent pollution incidents", "url": "https://www.andoveradvertiser.co.uk/news/26046397.southern-water-using-ai-prevent-pollution-incidents/", "date": "2026-04-25", "written_by": "independent", "quote": "Southern Water's AI technology detected a fatberg forming in Rowner, Gosport, before it could pollute the River Alver last week." }, { "kind": "news report", "citation": "Island Echo (2026). AI sewer tech prevents fatberg from polluting chalk stream in Calbourne. islandecho.co.uk, 23 April 2026; the second flagged blockage, with the same Southern Water quote.", "title": "AI sewer tech prevents fatberg from polluting chalk stream in Calbourne", "url": "https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "date": "2026-04-23", "written_by": "independent", "quote": "The issue at Warlands Lane, Shalfleet was identified using Southern Water's network of around 34,000 sewer level monitors, which continuously track flows and detect unusual activity" } ], "replication": { "produced_by": [ "Level monitors in sewer blockage hotspots feeding a model that has learned the sewer's normal flow pattern and flags deviations from it", "A staffed control room that receives the alert and can dispatch a jetting crew quickly" ], "must_hold": [ "The flagged anomaly is a forming blockage rather than rain or a daily peak, which the company says the model distinguishes but for which no accuracy figures are given", "A crew reaches the site before the sewer surcharges; the articles do not say how long that took here", "The overflow route the company describes (manhole to surface water drain to river) exists as stated; it is the company's own account" ], "echoes": [] }, "paired_incident": null, "headline": "Southern Water's sewer monitors flag a fatberg before overflow", "metric": null, "comparator": { "against": "the previous reactive practice of attending blockages after a flooding or pollution event", "before": "turning up after the event to clean up and commiserate with devastated customers", "after": "spotting hundreds of potential blockages before it is too late", "basis": "assumed", "quote": "\"Instead of turning up after the event to clean up and commiserate with devastated customers we're spotting hundreds of potential blockages before it's too late.\"", "url": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/" }, "later": { "status": "persisted", "date": "2026-04-23", "note": "The next day the same monitor network flagged a second forming fatberg at Warlands Lane, Shalfleet, on the Isle of Wight, which crews cleared before it reached the Caul Bourne chalk stream.", "quote": "The issue at Warlands Lane, Shalfleet was identified using Southern Water’s network of around 34,000 sewer level monitors, which continuously track flows and detect unusual activity that may indicate a blockage or leak. As the fatberg began to form, sensors alerted the control room, prompting a swift response.", "url": "https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/" }, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-22-7047", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/; https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Southern_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0205", "catalog_version": "1.0.0", "source_fingerprint": "d37052488798e332c79e45b266c0729c2f981e8be35ae9795e110e247cccd2d6", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0205-source-0001", "AIBD-0205-source-0002", "AIBD-0205-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Southern Water" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The level monitors detected an abnormal flow at Rowner. The machine-learning model raised the alert to the control room; by the company's account it distinguishes a forming blockage from daily rushes and rainfall. The jetting crew found and removed the fatberg. The articles are built on a Southern Water statement and a single quoted manager. They do not name the developer of the model and give no sensor data. No independent party confirmed that an overflow was imminent." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The level monitors detected an abnormal flow at Rowner. The machine-learning model raised the alert to the control room; by the company's account it distinguishes a forming blockage from daily rushes and rainfall. The jetting crew found and removed the fatberg. The articles are built on a Southern Water statement and a single quoted manager. They do not name the developer of the model and give no sensor data. No independent party confirmed that an overflow was imminent." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The company says a sewage overflow into the River Alver was averted. The Andover Advertiser says the river is home to herons, water voles and kingfishers. The counterfactual is asserted rather than shown, and no pollution occurred. This is a specific avoided harm of unmeasured size." }, { "group": "organizational", "depth": 1, "reason": "Southern Water cleared one blockage before it became a pollution incident or a customer flooding. The company says blocked sewers are the leading cause of its pollution incidents. This is one of the more than 4,000 interventions it reports in a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The company says a sewage overflow into the River Alver was averted. The Andover Advertiser says the river is home to herons, water voles and kingfishers. The counterfactual is asserted rather than shown, and no pollution occurred. This is a specific avoided harm of unmeasured size." }, { "group": "organizational", "depth": 1, "reason": "Southern Water cleared one blockage before it became a pollution incident or a customer flooding. The company says blocked sewers are the leading cause of its pollution incidents. This is one of the more than 4,000 interventions it reports in a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The company says a sewage overflow into the River Alver was averted. The Andover Advertiser says the river is home to herons, water voles and kingfishers. The counterfactual is asserted rather than shown, and no pollution occurred. This is a specific avoided harm of unmeasured size." }, { "group": "organizational", "depth": 1, "reason": "Southern Water cleared one blockage before it became a pollution incident or a customer flooding. The company says blocked sewers are the leading cause of its pollution incidents. This is one of the more than 4,000 interventions it reports in a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-04-22-7047" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-04-23", "note": "The next day the same monitor network flagged a second forming fatberg at Warlands Lane, Shalfleet, on the Isle of Wight, which crews cleared before it reached the Caul Bourne chalk stream.", "quote": "The issue at Warlands Lane, Shalfleet was identified using Southern Water’s network of around 34,000 sewer level monitors, which continuously track flows and detect unusual activity that may indicate a blockage or leak. As the fatberg began to form, sensors alerted the control room, prompting a swift response.", "url": "https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0205" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "A sewage overflow averted is pollution prevented, which Trustible's description does not name." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Southern Water runs around 34,000 sewer level monitors with machine learning. Its proactive operations control manager Daniel McElhinney says the system learns the normal behavior of sewers. He says it can tell a forming blockage from daily rushes or rain. Shortly before 22 April 2026 the sensors detected an abnormal flow in Rowner, Gosport, and alerted the control room. A crew jetted the sewer and found a fatberg of wet wipes and other unflushable items. The company said that, left unchecked, the sewer could have overflowed from a manhole into a surface water drain leading to the River Alver. The case was reported on 22 April 2026. A second flagged blockage at Warlands Lane, Shalfleet, Isle of Wight, was reported on 23 April.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "depth": 2, "reason": "The company says a sewage overflow into the River Alver was averted. The Andover Advertiser says the river is home to herons, water voles and kingfishers. The counterfactual is asserted rather than shown, and no pollution occurred. This is a specific avoided harm of unmeasured size." }, { "group": "organizational", "depth": 1, "reason": "Southern Water cleared one blockage before it became a pollution incident or a customer flooding. The company says blocked sewers are the leading cause of its pollution incidents. This is one of the more than 4,000 interventions it reports in a year." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The monitors and the anomaly model were installed to spot blockages and leaks forming in sewers. Crews can then clear them before they cause pollution or flooding. This case was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Gosport, United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The monitors and the anomaly model were installed to spot blockages and leaks forming in sewers. Crews can then clear them before they cause pollution or flooding. This case was that intended use." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-04-22", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-22-7047", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/; https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Southern_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Level monitors in sewer blockage hotspots feeding a model that has learned the sewer's normal flow pattern and flags deviations from it", "A staffed control room that receives the alert and can dispatch a jetting crew quickly" ], "must_hold": [ "The flagged anomaly is a forming blockage rather than rain or a daily peak, which the company says the model distinguishes but for which no accuracy figures are given", "A crew reaches the site before the sewer surcharges; the articles do not say how long that took here", "The overflow route the company describes (manhole to surface water drain to river) exists as stated; it is the company's own account" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-04-22-7047", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/; https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Southern_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Wastewater networks / pollution prevention", "segment": "Regulated water and wastewater utility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Southern Daily Echo (2026). Fatberg found in Gosport removed before causing damage. dailyecho.co.uk, 23 April 2026; reproduces a Southern Water statement.", "title": "Fatberg found in Gosport removed before causing damage", "url": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/", "date": "2026-04-23", "written_by": "independent", "quote": "Southern Water prevented sewage pollution of the River Alver in Gosport with the help of its AI-enabled digital sewer system and rapid action from its teams." }, { "kind": "news report", "citation": "Andover Advertiser (2026). Southern Water using AI to prevent pollution incidents. andoveradvertiser.co.uk, 25 April 2026; reproduces a Southern Water statement.", "title": "Southern Water using AI to prevent pollution incidents", "url": "https://www.andoveradvertiser.co.uk/news/26046397.southern-water-using-ai-prevent-pollution-incidents/", "date": "2026-04-25", "written_by": "independent", "quote": "Southern Water's AI technology detected a fatberg forming in Rowner, Gosport, before it could pollute the River Alver last week." }, { "kind": "news report", "citation": "Island Echo (2026). AI sewer tech prevents fatberg from polluting chalk stream in Calbourne. islandecho.co.uk, 23 April 2026; the second flagged blockage, with the same Southern Water quote.", "title": "AI sewer tech prevents fatberg from polluting chalk stream in Calbourne", "url": "https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "date": "2026-04-23", "written_by": "independent", "quote": "The issue at Warlands Lane, Shalfleet was identified using Southern Water's network of around 34,000 sewer level monitors, which continuously track flows and detect unusual activity" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0205-source-0001", "AIBD-0205-source-0002", "AIBD-0205-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Southern Daily Echo (2026). Fatberg found in Gosport removed before causing damage. dailyecho.co.uk, 23 April 2026; reproduces a Southern Water statement.", "title": "Fatberg found in Gosport removed before causing damage", "url": "https://www.dailyecho.co.uk/news/26045031.fatberg-found-gosport-removed-causing-damage/", "date": "2026-04-23", "written_by": "independent", "quote": "Southern Water prevented sewage pollution of the River Alver in Gosport with the help of its AI-enabled digital sewer system and rapid action from its teams." }, { "kind": "news report", "citation": "Andover Advertiser (2026). Southern Water using AI to prevent pollution incidents. andoveradvertiser.co.uk, 25 April 2026; reproduces a Southern Water statement.", "title": "Southern Water using AI to prevent pollution incidents", "url": "https://www.andoveradvertiser.co.uk/news/26046397.southern-water-using-ai-prevent-pollution-incidents/", "date": "2026-04-25", "written_by": "independent", "quote": "Southern Water's AI technology detected a fatberg forming in Rowner, Gosport, before it could pollute the River Alver last week." }, { "kind": "news report", "citation": "Island Echo (2026). AI sewer tech prevents fatberg from polluting chalk stream in Calbourne. islandecho.co.uk, 23 April 2026; the second flagged blockage, with the same Southern Water quote.", "title": "AI sewer tech prevents fatberg from polluting chalk stream in Calbourne", "url": "https://www.islandecho.co.uk/ai-sewer-tech-prevents-fatberg-from-polluting-chalk-stream-in-calbourne/", "date": "2026-04-23", "written_by": "independent", "quote": "The issue at Warlands Lane, Shalfleet was identified using Southern Water's network of around 34,000 sewer level monitors, which continuously track flows and detect unusual activity" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Southern Water's AI sewer monitors flagged a forming fatberg in Rowner, Gosport; a crew cleared it before any overflow into the River Alver.", "account": "Southern Water runs around 34,000 sewer level monitors with machine learning. Its proactive operations control manager Daniel McElhinney says the system learns the normal behavior of sewers. He says it can tell a forming blockage from daily rushes or rain. Shortly before 22 April 2026 the sensors detected an abnormal flow in Rowner, Gosport, and alerted the control room. A crew jetted the sewer and found a fatberg of wet wipes and other unflushable items. The company said that, left unchecked, the sewer could have overflowed from a manhole into a surface water drain leading to the River Alver. The case was reported on 22 April 2026. A second flagged blockage at Warlands Lane, Shalfleet, Isle of Wight, was reported on 23 April." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Southern Water's AI-enabled digital sewer system: a network of around 34,000 sewer level monitors in blockage hotspots with machine learning that learns normal sewer behavior and flags a forming blockage" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Southern Water's sewer-monitor anomaly model flagged a forming fatberg in Rowner, Gosport, and a crew cleared it before any overflow into the River Alver", "headline": "Southern Water's sewer monitors flag a fatberg before overflow" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "d37052488798e332c79e45b266c0729c2f981e8be35ae9795e110e247cccd2d6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Southern Water runs around 34,000 sewer level monitors with machine learning. Its proactive operations control manager Daniel McElhinney says the system learns the normal behavior of sewers. He says it can tell a forming blockage from daily rushes or rain. Shortly before 22 April 2026 the sensors detected an abnormal flow in Rowner, Gosport, and alerted the control room. A crew jetted the sewer and found a fatberg of wet wipes and other unflushable items. The company said that, left unchecked, the sewer could have overflowed from a manhole into a surface water drain leading to the River Alver. The case was reported on 22 April 2026. A second flagged blockage at Warlands Lane, Shalfleet, Isle of Wight, was reported on 23 April.", "replication": { "produced_by": [ "Level monitors in sewer blockage hotspots feeding a model that has learned the sewer's normal flow pattern and flags deviations from it", "A staffed control room that receives the alert and can dispatch a jetting crew quickly" ], "must_hold": [ "The flagged anomaly is a forming blockage rather than rain or a daily peak, which the company says the model distinguishes but for which no accuracy figures are given", "A crew reaches the site before the sewer surcharges; the articles do not say how long that took here", "The overflow route the company describes (manhole to surface water drain to river) exists as stated; it is the company's own account" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0245", "title": "Tesla on Autopilot stops on the I-75 shoulder at Sarasota with a drunk driver asleep; Florida police charge the 37-year-old with DUI", "summary": "Ouest-France (3 May 2026, citing ABC 7): around 2 a.m. on 24 Apr 2026 police found a 37-year-old woman unconscious in her stopped Tesla on Interstate 75; blood alcohol over twice the limit; charged...", "date_observed": "2026-04-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Alexandre Chauvel reported in Ouest-France on 3 May 2026, relaying the Sarasota station ABC 7, on a car stopped on Interstate 75. Officers were alerted at about 2 a.m. on Friday 24 April 2026 to a car on the emergency lane at Sarasota, Florida. They found a 37-year-old woman unconscious at the wheel of a Tesla. Local police, quoted without naming the agency or officer, said she should not have been driving. They said her blood alcohol was more than twice the legal limit. They said she had assumed the Tesla would bring her home safely on Autopilot. The article explains that cabin sensors check that the driver is looking ahead and warn them. If the driver does not reopen their eyes after the first warning, the vehicle stops. She was arrested and is being prosecuted for driving under the influence. The Tesla model is not stated. Neither a police report nor the ABC 7 story is among the sources. The OECD AI Incidents Monitor lists the event as a protective response with French-language sources.", "category": "protective response", "unexpected": false, "purpose": "Autopilot's driver-attention monitoring is built to warn an inattentive driver. It brings the car to a stop if the driver does not respond. It is not designed to drive an impaired person home.", "system": "Tesla Autopilot with cabin driver-attention monitoring (model not stated)", "model_version": null, "developer": "Tesla", "deployer": "Private owner", "location": "Sarasota, United States", "domain": "Road vehicle crash avoidance", "segment": "Consumer driver assistance / driver monitoring", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "An unconscious, intoxicated driver came to a stop without a crash. The sources document no injury and no collision avoided." }, { "group": "societal", "depth": 1, "reason": "Other road users were exposed to a stationary car on the shoulder rather than a moving one. No incident with them is documented." }, { "group": "organizational", "depth": null, "reason": "No organizational outcome is documented." } ], "ai_role": { "status": "assessed", "statement": "Per the report, the attention-monitoring logic issued warnings and then stopped the vehicle on the emergency lane. The agency, the vehicle data and the duration of the stop are not given. The police framed the episode as misuse rather than a rescue." }, "evidence": [ { "kind": "news report", "citation": "Chauvel A (3 May 2026). Ivre, elle s'endort dans sa Tesla en mode Autopilot : la voiture s'arrête sur l'autoroute. 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external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Tesla,_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; 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Ivre, elle s'endort dans sa Tesla en mode Autopilot : la voiture s'arrête sur l'autoroute. Ouest-France.", "title": "Ivre, elle s’endort dans sa Tesla en mode Autopilot : la voiture s’arrête sur l’autoroute", "url": "https://web.archive.org/web/2026/https://www.ouest-france.fr/societe/faits-divers/ivre-elle-sendort-dans-sa-tesla-en-mode-autopilot-la-voiture-sarrete-sur-lautoroute-8519ae64-42eb-11f1-8492-0dabd481308d", "date": "2026-05-03", "written_by": "independent", "quote": "Malheureusement, son alcoolémie était plus de deux fois supérieure à la limite légale et elle a supposé que la Tesla la ramènerait chez elle en toute sécurité" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-05-03-516b: Intoxicated Driver Relies on Tesla Autopilot, Car Stops on Florida Highway.", "title": "Intoxicated Driver Relies on Tesla Autopilot, Car Stops on Florida Highway", "url": "https://oecd.ai/en/incidents/2026-05-03-516b", "date": "2026-05-03", "written_by": "independent", "quote": "She fell asleep, and the AI system eventually stopped the car on the highway after detecting her unresponsiveness." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0245-source-0001", "AIBD-0245-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Chauvel A (3 May 2026). Ivre, elle s'endort dans sa Tesla en mode Autopilot : la voiture s'arrête sur l'autoroute. Ouest-France.", "title": "Ivre, elle s’endort dans sa Tesla en mode Autopilot : la voiture s’arrête sur l’autoroute", "url": "https://web.archive.org/web/2026/https://www.ouest-france.fr/societe/faits-divers/ivre-elle-sendort-dans-sa-tesla-en-mode-autopilot-la-voiture-sarrete-sur-lautoroute-8519ae64-42eb-11f1-8492-0dabd481308d", "date": "2026-05-03", "written_by": "independent", "quote": "Malheureusement, son alcoolémie était plus de deux fois supérieure à la limite légale et elle a supposé que la Tesla la ramènerait chez elle en toute sécurité" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-05-03-516b: Intoxicated Driver Relies on Tesla Autopilot, Car Stops on Florida Highway.", "title": "Intoxicated Driver Relies on Tesla Autopilot, Car Stops on Florida Highway", "url": "https://oecd.ai/en/incidents/2026-05-03-516b", "date": "2026-05-03", "written_by": "independent", "quote": "She fell asleep, and the AI system eventually stopped the car on the highway after detecting her unresponsiveness." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Ouest-France (3 May 2026, citing ABC 7): around 2 a.m. on 24 Apr 2026 police found a 37-year-old woman unconscious in her stopped Tesla on Interstate 75; blood alcohol over twice the limit; charged...", "account": "Alexandre Chauvel reported in Ouest-France on 3 May 2026, relaying the Sarasota station ABC 7, on a car stopped on Interstate 75. Officers were alerted at about 2 a.m. on Friday 24 April 2026 to a car on the emergency lane at Sarasota, Florida. They found a 37-year-old woman unconscious at the wheel of a Tesla. Local police, quoted without naming the agency or officer, said she should not have been driving. They said her blood alcohol was more than twice the legal limit. They said she had assumed the Tesla would bring her home safely on Autopilot. The article explains that cabin sensors check that the driver is looking ahead and warn them. If the driver does not reopen their eyes after the first warning, the vehicle stops. She was arrested and is being prosecuted for driving under the influence. The Tesla model is not stated. Neither a police report nor the ABC 7 story is among the sources. The OECD AI Incidents Monitor lists the event as a protective response with French-language sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Tesla Autopilot with cabin driver-attention monitoring (model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Tesla" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Tesla on Autopilot stops on the I-75 shoulder at Sarasota with a drunk driver asleep; Florida police charge the 37-year-old with DUI", "headline": "Tesla Autopilot stops on I-75 shoulder; drunk driver charged" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5dc89dc014bbf9b98920f5a4e5698ac635aadd66e26fc9e1c06e961514fcfed6" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Alexandre Chauvel reported in Ouest-France on 3 May 2026, relaying the Sarasota station ABC 7, on a car stopped on Interstate 75. Officers were alerted at about 2 a.m. on Friday 24 April 2026 to a car on the emergency lane at Sarasota, Florida. They found a 37-year-old woman unconscious at the wheel of a Tesla. Local police, quoted without naming the agency or officer, said she should not have been driving. They said her blood alcohol was more than twice the legal limit. They said she had assumed the Tesla would bring her home safely on Autopilot. The article explains that cabin sensors check that the driver is looking ahead and warn them. If the driver does not reopen their eyes after the first warning, the vehicle stops. She was arrested and is being prosecuted for driving under the influence. The Tesla model is not stated. Neither a police report nor the ABC 7 story is among the sources. The OECD AI Incidents Monitor lists the event as a protective response with French-language sources.", "replication": { "produced_by": [ "Autopilot engaged by an impaired driver on a limited-access highway", "Cabin camera attention monitoring with escalating warnings", "A stop-in-lane or shoulder-stop fallback when warnings go unanswered" ], "must_hold": [ "The driver does not respond to warnings", "The road has a shoulder or lane where a stopped car is not struck", "Police attend before another vehicle collides with the stationary car" ], "echoes": [ { "date": "2026-02-19", "setting": "Cybertruck owner Rishi Vohra says FSD's driver monitoring detected his blackout on a freeway and pulled the truck onto the shoulder (owner's account via Teslarati)", "outcome": "recurred", "source": "https://www.teslarati.com/tesla-cybertruck-fsd-saving-life-freeway-medical-emergency/" }, { "date": "2025-06-01", "setting": "NIO World Model emergency pull-over stopped a sleeping owner's car at 110 km/h on a rainy highway in China and placed an SOS call (owner's video reposted by NIO's founder)", "outcome": "recurred", "source": "https://news.mydrivers.com/1/1051/1051320.htm" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0348", "title": "Amazon Mining Watch's convolutional-network detector maps gold-mining scars basin-wide; 496,000 ha of protected and Indigenous lands affected 2018–2025, with no documented enforcement action", "summary": "AI mining detector (Earth Genome, Amazon Conservation, Pulitzer Center) maps mining scars basin-wide; 496,000 ha in protected areas 2018–2025 reported Apr 2026; no attributable enforcement event.", "date_observed": "2026-04-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection.", "category": "general benefit", "unexpected": false, "purpose": "Automated detection and mapping of artisanal gold-mining scars in satellite imagery. The users are journalists, researchers, civil society and policymakers. The mapping is the intended use.", "system": "Amazon Mining Watch gold-mine detector (ensemble of convolutional neural networks on Sentinel-2 imagery)", "model_version": "48px_v4.10b-18d-20g-21a-22bc-ensemble (July 2026 production model, per the repository README)", "developer": "Earth Genome (model), with Amazon Conservation Association and the Pulitzer Center's Rainforest Investigations Network", "deployer": "Amazon Mining Watch partnership (public web platform)", "location": "Amazon basin (Brazil, Peru, Guyana, Venezuela and other basin countries)", "domain": "Environmental monitoring: illegal gold mining in tropical forest", "segment": "Non-profit remote-sensing platform for journalism and conservation", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary documented." }, { "group": "organizational", "depth": null, "reason": "Journalists and non-governmental organizations (NGOs) use the maps, but no organization's decision is documented as changed by a detection." }, { "group": "societal", "depth": null, "reason": "Basin-wide statistics exist, but no enforcement or policy outcome is attributed to the tool in a cited source." } ], "ai_role": { "status": "assessed", "statement": "The AI system produces the maps and area statistics themselves. The makers' repository describes an ensemble of convolutional neural networks on Sentinel-2 patches, with reported holdout specificity 0.976 and sensitivity 0.991. Mongabay independently describes the platform as training AI algorithms to recognize mining scars. No cited source links a detection to an enforcement action. Mongabay remarks that the platform is useful for cross-border work, citing 2025 Brazil-Colombia operations on the Pure River. It does not state that those operations used its detections. MAAP's Operation Mercury analysis, by the same maker, used satellite imagery without machine learning." }, "evidence": [ { "kind": "news report", "citation": "Malleret, C. (2026). AI tool tracks spread of illegal gold mining in Amazon protected areas. Mongabay, 24 April 2026.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "496,000 hectares (1.2 million acres) of Indigenous territories and protected areas were affected by mining between 2018 and 2025." }, { "kind": "news report", "citation": "Malleret, C. (2026). Same article, method sentence.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas (method)", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "Amazon Mining Watch trains artificial intelligence algorithms to recognize mining scars in satellite images." }, { "kind": "press release", "citation": "Amazon Mining Watch (n.d.). About. amazonminingwatch.org.", "title": "Amazon Mining Watch: About", "url": "https://amazonminingwatch.org/en/about", "date": null, "written_by": "makers", "quote": "Amazon Mining Watch is a collaborative platform developed through a partnership between the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association, and Earth Genome." }, { "kind": "other", "citation": "Earth Genome (2026). Gold Mine Detector, README (August 2026 updates and Methodology). GitHub repository earthrise-media/mining-detector.", "title": "Gold Mine Detector README (Methodology)", "url": "https://github.com/earthrise-media/mining-detector", "date": null, "written_by": "makers", "quote": "The mine detector is an ensemble of convolutional neural networks trained to discriminate mines from other terrain using hand-labeled examples in Sentinel-2 L1C imagery." }, { "kind": "other", "citation": "Earth Genome (2026). Same README, Persistence section, evaluation of cumulative 2024 detections.", "title": "Gold Mine Detector README (Persistence)", "url": "https://github.com/earthrise-media/mining-detector", "date": null, "written_by": "makers", "quote": "Venezuela holdout: specificity 0.976, sensitivity 0.991" }, { "kind": "report", "citation": "Finer, M. et al. (2019). MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury. Monitoring of the Andean Amazon Project, Amazon Conservation, 4 August 2019 (no mention of machine learning or AI).", "title": "MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury", "url": "https://www.maapprogram.org/lapampa_opermercury/", "date": "2019-08-04", "written_by": "makers", "quote": "The gold mining deforestation decreased 92% between 2018 (900 hectares) and 2019 (67 hectares)" } ], "replication": { "produced_by": [ "Free Sentinel-2 imagery composited on Google Earth Engine", "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists", "Ensemble CNN detector run over the whole basin yearly and quarterly", "Public release of detections and code for journalists and NGOs" ], "must_hold": [ "Cloud-free composites over the period monitored", "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds", "Continued labeling and corroboration across years to limit false detections", "A user, agency or newsroom willing to act on detections, which no cited source documents" ], "echoes": [ { "date": "2019-08-04", "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI", "model_version": null, "outcome": "unknown", "source": "https://www.maapprogram.org/lapampa_opermercury/" }, { "date": "2026-04-24", "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)", "model_version": null, "outcome": "recurred", "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/" } ] }, "paired_incident": null, "headline": "Amazon Mining Watch maps 496,000 ha of mining in protected areas", "metric": "496,000 hectares affected between 2018 and 2025", "comparator": { "against": "hand-labeled Sentinel-2 patches (Venezuela geographic holdout)", "before": null, "after": "specificity 0.976, sensitivity 0.991", "basis": "measured", "quote": "For 2024, the last period with confirmed detections at time of writing, the cumulative detections return the following scores with respect to the evaluation locations used above: Venezuela holdout: specificity 0.976, sensitivity 0.991", "url": "https://github.com/earthrise-media/mining-detector" }, "later": { "status": "persisted", "date": "2026-08-01", "note": "Earth Genome published a full rebuild of the Amazon Mining Watch models and data in August 2026, continuing the platform after the April 2026 report.", "quote": "In August 2026 we published a full rebuild of Amazon Mining Watch models and data, to improve model sensitivity and to account for monitoring conditions on shorter time intervals (especially, increased cloud cover).", "url": "https://github.com/earthrise-media/mining-detector" }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://github.com/earthrise-media/mining-detector", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://projects.propublica.org/nonprofits/organizations/472935807", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' report, the makers' press release and the makers' other. 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MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. 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facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Free Sentinel-2 imagery composited on Google Earth Engine", "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists", "Ensemble CNN detector run over the whole basin yearly and quarterly", "Public release of detections and code for journalists and NGOs" ], "must_hold": [ "Cloud-free composites over the period monitored", "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds", "Continued labeling and corroboration across years to limit false detections", "A user, agency or newsroom willing to act on detections, which no cited source documents" ], "echoes": [ { "date": "2019-08-04", "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI", "outcome": "unknown", "source": "https://www.maapprogram.org/lapampa_opermercury/" }, { "date": "2026-04-24", "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)", "outcome": "recurred", "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Free Sentinel-2 imagery composited on Google Earth Engine", "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists", "Ensemble CNN detector run over the whole basin yearly and quarterly", "Public release of detections and code for journalists and NGOs" ], "must_hold": [ "Cloud-free composites over the period monitored", "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds", "Continued labeling and corroboration across years to limit false detections", "A user, agency or newsroom willing to act on detections, which no cited source documents" ], "echoes": [ { "date": "2019-08-04", "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI", "outcome": "unknown", "source": "https://www.maapprogram.org/lapampa_opermercury/" }, { "date": "2026-04-24", "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)", "outcome": "recurred", "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://github.com/earthrise-media/mining-detector", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Knowledge Discovery under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://projects.propublica.org/nonprofits/organizations/472935807", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Environmental monitoring: illegal gold mining in tropical forest", "segment": "Non-profit remote-sensing platform for journalism and conservation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Malleret, C. (2026). AI tool tracks spread of illegal gold mining in Amazon protected areas. Mongabay, 24 April 2026.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "496,000 hectares (1.2 million acres) of Indigenous territories and protected areas were affected by mining between 2018 and 2025." }, { "kind": "news report", "citation": "Malleret, C. (2026). Same article, method sentence.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas (method)", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "Amazon Mining Watch trains artificial intelligence algorithms to recognize mining scars in satellite images." }, { "kind": "press release", "citation": "Amazon Mining Watch (n.d.). About. amazonminingwatch.org.", "title": "Amazon Mining Watch: About", "url": "https://amazonminingwatch.org/en/about", "written_by": "makers", "quote": "Amazon Mining Watch is a collaborative platform developed through a partnership between the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association, and Earth Genome." }, { "kind": "other", "citation": "Earth Genome (2026). Gold Mine Detector, README (August 2026 updates and Methodology). GitHub repository earthrise-media/mining-detector.", "title": "Gold Mine Detector README (Methodology)", "url": "https://github.com/earthrise-media/mining-detector", "written_by": "makers", "quote": "The mine detector is an ensemble of convolutional neural networks trained to discriminate mines from other terrain using hand-labeled examples in Sentinel-2 L1C imagery." }, { "kind": "other", "citation": "Earth Genome (2026). Same README, Persistence section, evaluation of cumulative 2024 detections.", "title": "Gold Mine Detector README (Persistence)", "url": "https://github.com/earthrise-media/mining-detector", "written_by": "makers", "quote": "Venezuela holdout: specificity 0.976, sensitivity 0.991" }, { "kind": "report", "citation": "Finer, M. et al. (2019). MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury. Monitoring of the Andean Amazon Project, Amazon Conservation, 4 August 2019 (no mention of machine learning or AI).", "title": "MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury", "url": "https://www.maapprogram.org/lapampa_opermercury/", "date": "2019-08-04", "written_by": "makers", "quote": "The gold mining deforestation decreased 92% between 2018 (900 hectares) and 2019 (67 hectares)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0348-source-0001", "AIBD-0348-source-0002", "AIBD-0348-source-0003", "AIBD-0348-source-0004", "AIBD-0348-source-0005", "AIBD-0348-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Malleret, C. (2026). AI tool tracks spread of illegal gold mining in Amazon protected areas. Mongabay, 24 April 2026.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "496,000 hectares (1.2 million acres) of Indigenous territories and protected areas were affected by mining between 2018 and 2025." }, { "kind": "news report", "citation": "Malleret, C. (2026). Same article, method sentence.", "title": "AI tool tracks spread of illegal gold mining in Amazon protected areas (method)", "url": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/", "date": "2026-04-24", "written_by": "independent", "quote": "Amazon Mining Watch trains artificial intelligence algorithms to recognize mining scars in satellite images." }, { "kind": "press release", "citation": "Amazon Mining Watch (n.d.). About. amazonminingwatch.org.", "title": "Amazon Mining Watch: About", "url": "https://amazonminingwatch.org/en/about", "written_by": "makers", "quote": "Amazon Mining Watch is a collaborative platform developed through a partnership between the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association, and Earth Genome." }, { "kind": "other", "citation": "Earth Genome (2026). Gold Mine Detector, README (August 2026 updates and Methodology). GitHub repository earthrise-media/mining-detector.", "title": "Gold Mine Detector README (Methodology)", "url": "https://github.com/earthrise-media/mining-detector", "written_by": "makers", "quote": "The mine detector is an ensemble of convolutional neural networks trained to discriminate mines from other terrain using hand-labeled examples in Sentinel-2 L1C imagery." }, { "kind": "other", "citation": "Earth Genome (2026). Same README, Persistence section, evaluation of cumulative 2024 detections.", "title": "Gold Mine Detector README (Persistence)", "url": "https://github.com/earthrise-media/mining-detector", "written_by": "makers", "quote": "Venezuela holdout: specificity 0.976, sensitivity 0.991" }, { "kind": "report", "citation": "Finer, M. et al. (2019). MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury. Monitoring of the Andean Amazon Project, Amazon Conservation, 4 August 2019 (no mention of machine learning or AI).", "title": "MAAP #104: Major Reduction in Illegal Gold Mining from Peru's Operation Mercury", "url": "https://www.maapprogram.org/lapampa_opermercury/", "date": "2019-08-04", "written_by": "makers", "quote": "The gold mining deforestation decreased 92% between 2018 (900 hectares) and 2019 (67 hectares)" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AI mining detector (Earth Genome, Amazon Conservation, Pulitzer Center) maps mining scars basin-wide; 496,000 ha in protected areas 2018–2025 reported Apr 2026; no attributable enforcement event.", "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The models detected mining activity in satellite images and calculated its extent." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The repository identified the July 2026 production model as 48px_v4.10b-18d-20g-21a-22bc-ensemble." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "48px_v4.10b-18d-20g-21a-22bc-ensemble (July 2026 production model, per the repository README)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "48px_v4.10b-18d-20g-21a-22bc-ensemble.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Amazon Mining Watch gold-mine detector (ensemble of convolutional neural networks on Sentinel-2 imagery)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Earth Genome (model), with Amazon Conservation Association and the Pulitzer Center's Rainforest Investigations Network" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Amazon Mining Watch's convolutional-network detector maps gold-mining scars basin-wide; 496,000 ha of protected and Indigenous lands affected 2018–2025, with no documented enforcement action", "headline": "Amazon Mining Watch maps 496,000 ha of mining in protected areas" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "65329a090a51f990f3856c3ff0e717fac09db0cac334467ef2bdf8968a426135" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Amazon Mining Watch is a public platform built by the Pulitzer Center's Rainforest Investigations Network, Amazon Conservation Association and Earth Genome. In its own words, it leverages artificial intelligence to map the impact of gold mining. Its code repository describes the detector as an ensemble of convolutional neural networks (CNNs) trained on hand-labeled Sentinel-2 patches. The detector is run over the 8.2 million km2 Amazon basin, with detections recomputed yearly for 2018–2025 and quarterly from 2025. The repository reports specificity 0.976 and sensitivity 0.991 on a Venezuelan geographic holdout for the cumulative 2024 detections. Mongabay reported on 24 April 2026, on the platform's quarterly report. That report found about 6,000 hectares of mining deforestation in protected areas and Indigenous territories in the last three months of 2025. It found 496,000 hectares affected between 2018 and 2025. The enforcement operations on record are documented by the same tool maker without any AI role. MAAP #104 (4 August 2019) attributes a 92% fall in gold-mining deforestation at La Pampa to Peru's Operation Mercury of February 2019. That analysis used satellite imagery (ESA, Maxar, Sentinel-1) with no mention of machine learning. No cited source documents an enforcement action taken on an Amazon Mining Watch detection.", "replication": { "produced_by": [ "Free Sentinel-2 imagery composited on Google Earth Engine", "Hand-labeled training set of 23,463 patches built from earlier human surveys with journalists", "Ensemble CNN detector run over the whole basin yearly and quarterly", "Public release of detections and code for journalists and NGOs" ], "must_hold": [ "Cloud-free composites over the period monitored", "Mining scars visually distinct from sandbars, braided rivers and aquaculture ponds", "Continued labeling and corroboration across years to limit false detections", "A user, agency or newsroom willing to act on detections, which no cited source documents" ], "echoes": [ { "date": "2019-08-04", "setting": "MAAP #104, La Pampa, Peru: 92% drop in mining deforestation after Operation Mercury, analyzed from satellite imagery without AI", "outcome": "unknown", "source": "https://www.maapprogram.org/lapampa_opermercury/" }, { "date": "2026-04-24", "setting": "Quarterly “Panorama” report, Q4 2025: about 6,000 ha of mining deforestation in protected areas and Indigenous territories (Mongabay)", "outcome": "recurred", "source": "https://news.mongabay.com/2026/04/ai-tool-tracks-spread-of-illegal-gold-mining-in-amazon-protected-areas/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0075", "title": "GPT-5.5 Pro solves Erdős problem #38; solution human-checked, Lean-formalized and recorded as solved on erdosproblems.com", "summary": "GPT-5.5 Pro solved Erdős problem #38; human-checked 26 April 2026, Lean-formalized by Aristotle 1 May, recorded as solved on erdosproblems.com", "date_observed": "2026-04-25", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Erdős problem #38 is an open question in additive number theory. It asks for a set B that is not an additive basis yet raises the Schnirelmann density of every set A. OpenAI's GPT-5.5 Pro solved it. On 25 April 2026 a user (gebyjaff) posted the model's solution on the erdosproblems.com forum, with a PDF cleanup by Liam Price. On 26 April forum commenter Nat Sothanaphan reported that a standard check found no issues in the write-up. On 1 May the Aristotle system autoformalized the argument in Lean, which Sothanaphan confirmed matches the paper. Site maintainer Thomas Bloom added an alternative sketch on 2 May 2026. The problem page now records the positive solution by GPT 5.5 Pro. Terence Tao's wiki lists it as an AI-standalone full solution.", "category": "benefit created", "unexpected": false, "purpose": "General-purpose reasoning model prompted to solve an open research problem", "system": "GPT-5.5 Pro, with Aristotle used for Lean autoformalisation", "model_version": "GPT-5.5 Pro", "developer": "OpenAI (GPT-5.5 Pro); Aristotle (developer not named in the cited sources)", "deployer": "Individual user (gebyjaff) posting on erdosproblems.com", "location": null, "domain": "Mathematics", "segment": "Research mathematics (additive number theory)", "benefit_type": "Improved Knowledge Discovery", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "Small: one more entry resolved in the erdosproblems.com project, accepted by its maintainer" }, { "group": "societal", "depth": 1, "reason": "Small: a single open problem settled. The problem page records the solution, and Tao's wiki catalogs it among many AI contributions" } ], "ai_role": { "status": "assessed", "statement": "The model produced the proof after a human prompt. Humans cleaned up the write-up and checked it, and the maintainer accepted it. A separate AI system (Aristotle) produced the Lean formalization that a human confirmed matches the paper. Tao's wiki classifies the case as AI standalone with non-significant human involvement. The attribution of GPT-5.5 Pro to OpenAI rests on the chatgpt.com share link in gebyjaff's forum post. No cited source names OpenAI in prose. The cited sources do not name Aristotle's developer." }, "evidence": [ { "kind": "other", "citation": "Bloom, T. (ed.) (2026). Erdős Problem #38. erdosproblems.com.", "title": "Erdős Problem #38", "url": "https://www.erdosproblems.com/38", "date": "2026-05-02", "written_by": "independent", "quote": "A positive solution was given by GPT 5.5 Pro (prompted by gebyjaff) in the comments; in fact a sparse random set B has this property" }, { "kind": "other", "citation": "erdosproblems.com forum (2026). Thread for problem 38. erdosproblems.com.", "title": "Forum thread: Problem 38", "url": "https://www.erdosproblems.com/forum/thread/38", "date": "2026-04-26", "written_by": "independent", "quote": "Standard check found no issues in the writeup" }, { "kind": "other", "citation": "Tao, T. et al. (2026). AI contributions to Erdős problems. 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ZeroEyes gun detection technology had detected an individual in black pointing a gun on the bottom level. Camera footage showed Tyler Farmer, 19, brandishing a loaded firearm at four other people. Officers found a Glock 19 handgun, stolen from Miller County, Georgia, in his waistband. He was charged with possessing a firearm on school property, unlawful carry, improper display of a firearm and grand theft of a firearm. He bonded out on Sunday. The Tallahassee Democrat, citing court records, says police responded to a “ZeroEyes camera notification” and that Farmer is not an FSU student. ZeroEyes layers over existing cameras and routes human-verified detections to police.", "category": "protective response", "unexpected": false, "purpose": "Detect visible firearms in existing security-camera feeds, verify with human analysts and alert police within seconds to reduce response times to potential shootings.", "system": "ZeroEyes AI gun detection", "model_version": null, "developer": "ZeroEyes", "deployer": "Florida State University Police Department", "location": "Tallahassee, United States", "domain": "Public safety / weapons detection", "segment": "Education", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "societal", "depth": 2, "reason": "An armed man waving a loaded, stolen handgun at bystanders was arrested and the weapon recovered, per court documents reported by WCTV." }, { "group": "personal", "depth": null, "reason": "The four bystanders are not identified and no source documents what the arrest prevented for them." } ], "ai_role": { "status": "assessed", "statement": "Court documents (as reported) attribute the police response to a ZeroEyes camera notification. 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https://police.fsu.edu/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public safety / weapons detection", "segment": "Education" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Caroline Christensen, WCTV, 4 May 2026 (citing court documents)", "title": "Court documents: 19-year-old arrested after brandishing gun in FSU parking garage early Saturday morning", "url": "https://www.wctv.tv/2026/05/04/court-documents-19-year-old-arrested-after-brandishing-weapon-fsu-parking-garage-early-saturday-morning/", "date": "2026-05-04", "written_by": "independent", "quote": "Tyler Farmer is charged with possessing a firearm on school property, unlawful carry, improper display of a firearm and grand theft of a firearm, court documents say." }, { "kind": "news report", "citation": "Arianna Otero, Tallahassee Democrat, 5 May 2026 (citing court records)", "title": "New AI gun detection tool leads to arrest at FSU parking garage", "url": "https://www.tallahassee.com/story/news/local/2026/05/05/ai-tool-identifying-firearm-leads-to-arrest-of-fsu-student/89946929007/", "date": "2026-05-05", "written_by": "independent", "quote": "led to the arrest of a teen after he was caught brandishing a gun at an Florida State University campus parking garage, police said." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0226-source-0001", "AIBD-0226-source-0002" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Caroline Christensen, WCTV, 4 May 2026 (citing court documents)", "title": "Court documents: 19-year-old arrested after brandishing gun in FSU parking garage early Saturday morning", "url": "https://www.wctv.tv/2026/05/04/court-documents-19-year-old-arrested-after-brandishing-weapon-fsu-parking-garage-early-saturday-morning/", "date": "2026-05-04", "written_by": "independent", "quote": "Tyler Farmer is charged with possessing a firearm on school property, unlawful carry, improper display of a firearm and grand theft of a firearm, court documents say." }, { "kind": "news report", "citation": "Arianna Otero, Tallahassee Democrat, 5 May 2026 (citing court records)", "title": "New AI gun detection tool leads to arrest at FSU parking garage", "url": "https://www.tallahassee.com/story/news/local/2026/05/05/ai-tool-identifying-firearm-leads-to-arrest-of-fsu-student/89946929007/", "date": "2026-05-05", "written_by": "independent", "quote": "led to the arrest of a teen after he was caught brandishing a gun at an Florida State University campus parking garage, police said." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "At about 2:30 a.m. on 2 May 2026 ZeroEyes flagged a man pointing a gun in FSU's St. Augustine garage; officers found a stolen Glock 19 on Tyler Farmer and charged him, per court documents.", "account": "According to arrest papers cited by WCTV, Florida State University police responded to the St. Augustine parking garage at about 2:30 a.m. on Saturday 2 May 2026. ZeroEyes gun detection technology had detected an individual in black pointing a gun on the bottom level. Camera footage showed Tyler Farmer, 19, brandishing a loaded firearm at four other people. Officers found a Glock 19 handgun, stolen from Miller County, Georgia, in his waistband. He was charged with possessing a firearm on school property, unlawful carry, improper display of a firearm and grand theft of a firearm. He bonded out on Sunday. The Tallahassee Democrat, citing court records, says police responded to a “ZeroEyes camera notification” and that Farmer is not an FSU student. ZeroEyes layers over existing cameras and routes human-verified detections to police." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ZeroEyes AI gun detection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ZeroEyes" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ZeroEyes camera alert sends FSU police to a man pointing a stolen Glock at bystanders; arrested on four charges", "headline": "ZeroEyes alert sends FSU police to a man pointing a stolen Glock" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7fad5474a387556d45b9263837e3e6d278b86523681e910cc04197cbf55cbb7d" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "According to arrest papers cited by WCTV, Florida State University police responded to the St. Augustine parking garage at about 2:30 a.m. on Saturday 2 May 2026. ZeroEyes gun detection technology had detected an individual in black pointing a gun on the bottom level. Camera footage showed Tyler Farmer, 19, brandishing a loaded firearm at four other people. Officers found a Glock 19 handgun, stolen from Miller County, Georgia, in his waistband. He was charged with possessing a firearm on school property, unlawful carry, improper display of a firearm and grand theft of a firearm. He bonded out on Sunday. The Tallahassee Democrat, citing court records, says police responded to a “ZeroEyes camera notification” and that Farmer is not an FSU student. ZeroEyes layers over existing cameras and routes human-verified detections to police.", "replication": { "produced_by": [ "A firearm visibly brandished within view of a connected security camera", "Human verification at the vendor's operations center before dispatch", "Campus police able to reach the location while the person was still present" ], "must_hold": [ "Camera coverage and image quality sufficient for the detector", "The weapon must be visible (concealed guns are not detected)", "A staffed verification center and a responsive police unit" ], "echoes": [ { "date": "2023-11-30", "setting": "Hobbs, New Mexico: parking lot of Del Norte Pool, suspects detained and one charged", "outcome": "recurred", "source": "https://www.govtech.com/public-safety/ai-gun-detection-system-leads-to-charges-in-new-mexico" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0340", "title": "Origin Tech's AI satellite leak detection may have found over 800 leaks in an 18-week Thames Water trial, saving an estimated 8.7 million liters a day", "summary": "18-week Origin Orbit trial on Thames Water's network: over 800 leaks found, est. 8.7 million liters a day saved (utility figures); 13-month contract followed, target 100 million liters a day.", "date_observed": "2026-05-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Thames Water trialed Origin Orbit, the satellite leak-detection product of North East England start-up Origin Tech Ltd (founded 2019). The company and the utility describe it as using AI on satellite data to flag suspected underground leaks within a 30-meter search radius. Origin's co-founder John Marsden told the BBC the satellites pass over Swindon roughly every six days. He said they produce points on a map for Thames Water crews. Thames Water's statements say an 18-week trial found over 800 leaks across the network. They were reported by the BBC (20 May 2026) and reproduced in trade press. It saved an estimated 8.7 million liters of water a day, with several leaks running at more than 10 liters per second. On the strength of the trial, Thames Water signed a 13-month contract, launched in March 2026 per the utility's release. It deploys 20 specialist teams expected to find about 25 leaks a week each, and aims to cut leakage by 100 million liters a day. That makes it the first water company to integrate Origin Orbit into business-as-usual leakage operations. Origin Tech's own site adds a 2026 claim that Origin Orbit identified over 5,000 leaks (73.45 ML/d) across its customers. All figures originate with the utility and the vendor, and no regulator or independent measurement is among the sources. The trial dates are not given. Smart Water Magazine reported the result on 5 May 2026. Cambridgeshire County Council's AI inspection contract (April 2026) and Hertfordshire's ARRES robot (January 2024) have no outcomes on record. They are not among the sources.", "category": "benefit created", "unexpected": false, "purpose": "Built to pinpoint non-visible underground leaks from satellite data so that crews can find and fix them. The leaks found in the trial are that purpose.", "system": "Origin Orbit (Origin Tech satellite leak detection applying AI to satellite data to flag suspected leaks within a 30-meter search radius)", "model_version": "Origin Orbit®", "developer": "Origin Tech Ltd (North East England)", "deployer": "Thames Water (leakage operations; 20 Origin specialist teams under the 2026 contract)", "location": "Thames Water supply area, England (BBC report centered on Swindon, Wiltshire)", "domain": "Water utilities: leakage detection", "segment": "Private regulated water company", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": "Water lost to leaks is read under Trustible's “water consumption”; the saving is the utility's figure.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual customer outcome is documented. The BBC notes most of these leaks are never seen by customers." }, { "group": "organizational", "depth": 2, "reason": "Material to the utility's leakage operations by its own account. Over 800 leaks were found and an estimated 8.7 million liters a day saved in one trial. A 13-month business-as-usual contract followed. The estimate is the utility's own and unverified." }, { "group": "societal", "depth": 1, "reason": "Water was conserved for the public supply. Per the Environment Agency figure cited by the BBC, about 19% of UK water is lost to leakage. The scale claimed is modest and unverified." } ], "ai_role": { "status": "assessed", "statement": "Only the vendor and the utility describe the AI role. The BBC caption says the AI-generated satellite technology detects moisture and movement in the ground, and Origin Tech describes AI-driven satellite insights. The system outputs suspected-leak points that Thames Water crews then locate and repair with conventional methods. The 800-leak and 8.7 million liters a day figures are Thames Water's estimates relayed by the BBC. They are reproduced in the utility's press release (Water Magazine) and trade press. Origin Tech's site adds vendor claims. No independent verification is among the sources." }, "evidence": [ { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026.", "title": "Thames Water using AI technology to find leaks in Swindon", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "During a previous trial, 800 leaks across Thames Water's network were found." }, { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026 (savings estimate attributed to the company).", "title": "Thames Water using AI technology to find leaks in Swindon (savings estimate)", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "The company said this helped to save an estimated 8.7 million litres of water per day, enough to fill more than three Olympic-sized swimming pools." }, { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026 (image caption describing the technology).", "title": "Thames Water using AI technology to find leaks in Swindon (technology description)", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "The AI-generated satellite technology detects moisture and movement in the ground" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Press release reproduced by Water Magazine, 29 May 2026 (source credited as Thames Water).", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day/", "date": "2026-05-29", "written_by": "deployer", "quote": "During a previous 18-week trial, Origin Orbit® was able to find over 800 leaks across Thames Water's network, helping to save an estimated 8.7 million litres of water per day." }, { "kind": "news report", "citation": "Tempest, O. (2026). Thames Water signs AI satellite deal to plug 100 million litres of daily leaks. Smart Water Magazine, 5 May 2026 (no verbatim quote taken).", "title": "Thames Water signs AI satellite deal to plug 100 million litres of daily leaks", "url": "https://smartwatermagazine.com/news/thames-water/thames-water-signs-ai-satellite-deal-plug-100-million-litres-daily-leaks", "date": "2026-05-05", "written_by": "independent", "quote": null }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech in Partnership with Thames Water. Origin news, 29 May 2026.", "title": "Origin Tech in Partnership with Thames Water", "url": "https://www.origintech.co.uk/origin-news/origin-tech-in-partnership-with-thames-water", "date": "2026-05-29", "written_by": "makers", "quote": "By combining AI-driven satellite insights with operational expertise, Origin Tech is enabling faster, more precise detection of previously invisible leaks." }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech Featured in BBC News and BBC Wiltshire Radio. Origin news, 20 May 2026.", "title": "Origin Tech Featured in BBC News and BBC Wiltshire Radio", "url": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio", "date": "2026-05-20", "written_by": "makers", "quote": "Origin Orbit® has been able to identify over 5K leaks, which is over 73.45 ML/d of leakage" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Newsroom, 1 May 2026.", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "date": "2026-05-01", "written_by": "deployer", "quote": null }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South-East drought pressure intensifies. Newsroom, 24 August 2026.", "title": "Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South‑East drought pressure intensifies", "url": "https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies", "date": "2026-08-24", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Satellite passes about every six days over the network, processed into suspected-leak points within a 30-meter radius", "An 18-week trial in which Thames Water crews investigated the points with conventional ground methods", "A network with a large share of non-visible underground leaks (92% of Origin Orbit finds are non-visible, per the vendor)" ], "must_hold": [ "Satellite revisit frequency and ground conditions that allow moisture and movement to be detected", "Crew capacity to investigate points (20 teams at about 25 leaks a week each under the contract)", "Repair follow-through so that found leaks become saved water", "The utility's method for estimating liters saved per leak, which no independent source has checked" ], "echoes": [ { "date": "2026-05-29", "setting": "13-month business-as-usual contract launched March 2026 with 20 specialist teams, targeting 100 million liters a day; no result reported yet", "model_version": null, "outcome": "unknown", "source": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-liters-of-water-per-day/" }, { "date": "2026-05-20", "setting": "Origin Tech's 2026 claim across its customers: over 5,000 leaks identified, 73.45 ML/d (vendor statement, unverified)", "model_version": null, "outcome": "unknown", "source": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio" } ] }, "paired_incident": null, "headline": "Origin Orbit trial may have found over 800 Thames Water leaks", "metric": "over 800 leaks across the network, saving an estimated 8.7 million liters of water a day", "comparator": { "against": "a person detecting leaks unassisted on the ground (the vendor co-founder's claim)", "before": "a person working unassisted on the ground", "after": "at least five times quicker", "basis": "assumed", "quote": "Marsden said the technology is \"at least five times quicker\" at detecting \"invisible leaks that are really difficult to find\" than a person working unassisted on the ground.", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo" }, "later": { "status": "scaled", "date": "2026-08-24", "note": "After the trial Thames Water took Origin Orbit into a 13-month business-as-usual contract (launched March 2026, 20 teams) and by August 2026 described the satellite detection as part of its drought-response leak hunting, without reporting post-trial leak counts.", "quote": "Thames Water also uses an AI-driven leak detection solution that uses satellite data to identify leaks. The utility company partners with Origin Orbit to detect anomalies in the ground that indicate underground water leaks.", "url": "https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies" }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo; https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies; https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/12359793; https://en.wikipedia.org/wiki/Thames_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, two press releases from the makers and three press releases from the deployer. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0340", "catalog_version": "1.0.0", "source_fingerprint": "7d1b2c1ddb627a3cb73bdc8b7e842b73fac11086faf02670ed739acb1100f910", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0340-source-0001", "AIBD-0340-source-0002", "AIBD-0340-source-0003", "AIBD-0340-source-0004", "AIBD-0340-source-0005", "AIBD-0340-source-0006", "AIBD-0340-source-0007", "AIBD-0340-source-0008", "AIBD-0340-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Origin Tech Ltd (North East England)", "deployer": "Thames Water (leakage operations; 20 Origin specialist teams under the 2026 contract)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Only the vendor and the utility describe the AI role. The BBC caption says the AI-generated satellite technology detects moisture and movement in the ground, and Origin Tech describes AI-driven satellite insights. The system outputs suspected-leak points that Thames Water crews then locate and repair with conventional methods. The 800-leak and 8.7 million liters a day figures are Thames Water's estimates relayed by the BBC. They are reproduced in the utility's press release (Water Magazine) and trade press. Origin Tech's site adds vendor claims. No independent verification is among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "Only the vendor and the utility describe the AI role. The BBC caption says the AI-generated satellite technology detects moisture and movement in the ground, and Origin Tech describes AI-driven satellite insights. The system outputs suspected-leak points that Thames Water crews then locate and repair with conventional methods. The 800-leak and 8.7 million liters a day figures are Thames Water's estimates relayed by the BBC. They are reproduced in the utility's press release (Water Magazine) and trade press. Origin Tech's site adds vendor claims. No independent verification is among the sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual customer outcome is documented. The BBC notes most of these leaks are never seen by customers." }, { "group": "organizational", "depth": 2, "reason": "Material to the utility's leakage operations by its own account. Over 800 leaks were found and an estimated 8.7 million liters a day saved in one trial. A 13-month business-as-usual contract followed. The estimate is the utility's own and unverified." }, { "group": "societal", "depth": 1, "reason": "Water was conserved for the public supply. Per the Environment Agency figure cited by the BBC, about 19% of UK water is lost to leakage. The scale claimed is modest and unverified." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports, two press releases from the makers and three press releases from the deployer. 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an AI-driven leak detection solution that uses satellite data to identify leaks. The utility company partners with Origin Orbit to detect anomalies in the ground that indicate underground water leaks.", "url": "https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0340" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": "Water lost to leaks is read under Trustible's “water consumption”; the saving is the utility's figure." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Thames Water trialed Origin Orbit, the satellite leak-detection product of North East England start-up Origin Tech Ltd (founded 2019). The company and the utility describe it as using AI on satellite data to flag suspected underground leaks within a 30-meter search radius. Origin's co-founder John Marsden told the BBC the satellites pass over Swindon roughly every six days. He said they produce points on a map for Thames Water crews. Thames Water's statements say an 18-week trial found over 800 leaks across the network. They were reported by the BBC (20 May 2026) and reproduced in trade press. It saved an estimated 8.7 million liters of water a day, with several leaks running at more than 10 liters per second. On the strength of the trial, Thames Water signed a 13-month contract, launched in March 2026 per the utility's release. It deploys 20 specialist teams expected to find about 25 leaks a week each, and aims to cut leakage by 100 million liters a day. That makes it the first water company to integrate Origin Orbit into business-as-usual leakage operations. Origin Tech's own site adds a 2026 claim that Origin Orbit identified over 5,000 leaks (73.45 ML/d) across its customers. All figures originate with the utility and the vendor, and no regulator or independent measurement is among the sources. The trial dates are not given. Smart Water Magazine reported the result on 5 May 2026. Cambridgeshire County Council's AI inspection contract (April 2026) and Hertfordshire's ARRES robot (January 2024) have no outcomes on record. They are not among the sources.", "benefit_type": "Reduced Carbon Emissions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual customer outcome is documented. The BBC notes most of these leaks are never seen by customers." }, { "group": "organizational", "depth": 2, "reason": "Material to the utility's leakage operations by its own account. Over 800 leaks were found and an estimated 8.7 million liters a day saved in one trial. A 13-month business-as-usual contract followed. The estimate is the utility's own and unverified." }, { "group": "societal", "depth": 1, "reason": "Water was conserved for the public supply. Per the Environment Agency figure cited by the BBC, about 19% of UK water is lost to leakage. The scale claimed is modest and unverified." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Built to pinpoint non-visible underground leaks from satellite data so that crews can find and fix them. The leaks found in the trial are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Thames Water supply area, England (BBC report centered on Swindon, Wiltshire)", "developer_country": "United Kingdom", "deployer_country": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Built to pinpoint non-visible underground leaks from satellite data so that crews can find and fix them. The leaks found in the trial are that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-05-05", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo; https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies; https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/12359793; https://en.wikipedia.org/wiki/Thames_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; 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no result reported yet", "outcome": "unknown", "source": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-liters-of-water-per-day/" }, { "date": "2026-05-20", "setting": "Origin Tech's 2026 claim across its customers: over 5,000 leaks identified, 73.45 ML/d (vendor statement, unverified)", "outcome": "unknown", "source": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Satellite passes about every six days over the network, processed into suspected-leak points within a 30-meter radius", "An 18-week trial in which Thames Water crews investigated the points with conventional ground methods", "A network with a large share of non-visible underground leaks (92% of Origin Orbit finds are non-visible, per the vendor)" ], "must_hold": [ "Satellite revisit frequency and ground conditions that allow moisture and movement to be detected", "Crew capacity to investigate points (20 teams at about 25 leaks a week each under the contract)", "Repair follow-through so that found leaks become saved water", "The utility's method for estimating liters saved per leak, which no independent source has checked" ], "echoes": [ { "date": "2026-05-29", "setting": "13-month business-as-usual contract launched March 2026 with 20 specialist teams, targeting 100 million liters a day; no result reported yet", "outcome": "unknown", "source": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-liters-of-water-per-day/" }, { "date": "2026-05-20", "setting": "Origin Tech's 2026 claim across its customers: over 5,000 leaks identified, 73.45 ML/d (vendor statement, unverified)", "outcome": "unknown", "source": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since, the model version from the cited sources.", "source": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo; https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies; https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/12359793; https://en.wikipedia.org/wiki/Thames_Water", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; 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Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026 (image caption describing the technology).", "title": "Thames Water using AI technology to find leaks in Swindon (technology description)", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "The AI-generated satellite technology detects moisture and movement in the ground" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Press release reproduced by Water Magazine, 29 May 2026 (source credited as Thames Water).", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day/", "date": "2026-05-29", "written_by": "deployer", "quote": "During a previous 18-week trial, Origin Orbit® was able to find over 800 leaks across Thames Water's network, helping to save an estimated 8.7 million litres of water per day." }, { "kind": "news report", "citation": "Tempest, O. (2026). Thames Water signs AI satellite deal to plug 100 million litres of daily leaks. Smart Water Magazine, 5 May 2026 (no verbatim quote taken).", "title": "Thames Water signs AI satellite deal to plug 100 million litres of daily leaks", "url": "https://smartwatermagazine.com/news/thames-water/thames-water-signs-ai-satellite-deal-plug-100-million-litres-daily-leaks", "date": "2026-05-05", "written_by": "independent" }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech in Partnership with Thames Water. Origin news, 29 May 2026.", "title": "Origin Tech in Partnership with Thames Water", "url": "https://www.origintech.co.uk/origin-news/origin-tech-in-partnership-with-thames-water", "date": "2026-05-29", "written_by": "makers", "quote": "By combining AI-driven satellite insights with operational expertise, Origin Tech is enabling faster, more precise detection of previously invisible leaks." }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech Featured in BBC News and BBC Wiltshire Radio. Origin news, 20 May 2026.", "title": "Origin Tech Featured in BBC News and BBC Wiltshire Radio", "url": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio", "date": "2026-05-20", "written_by": "makers", "quote": "Origin Orbit® has been able to identify over 5K leaks, which is over 73.45 ML/d of leakage" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Newsroom, 1 May 2026.", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "date": "2026-05-01", "written_by": "deployer" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South-East drought pressure intensifies. Newsroom, 24 August 2026.", "title": "Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South‑East drought pressure intensifies", "url": "https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies", "date": "2026-08-24", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0340-source-0001", "AIBD-0340-source-0002", "AIBD-0340-source-0003", "AIBD-0340-source-0004", "AIBD-0340-source-0005", "AIBD-0340-source-0006", "AIBD-0340-source-0007", "AIBD-0340-source-0008", "AIBD-0340-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026.", "title": "Thames Water using AI technology to find leaks in Swindon", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "During a previous trial, 800 leaks across Thames Water's network were found." }, { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026 (savings estimate attributed to the company).", "title": "Thames Water using AI technology to find leaks in Swindon (savings estimate)", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "The company said this helped to save an estimated 8.7 million litres of water per day, enough to fill more than three Olympic-sized swimming pools." }, { "kind": "news report", "citation": "Rattley, H. and Jewers, N. (2026). Thames Water using AI technology to find leaks in Swindon. BBC News, 20 May 2026 (image caption describing the technology).", "title": "Thames Water using AI technology to find leaks in Swindon (technology description)", "url": "https://www.bbc.co.uk/news/articles/cr5pzmyr5jeo", "date": "2026-05-20", "written_by": "independent", "quote": "The AI-generated satellite technology detects moisture and movement in the ground" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Press release reproduced by Water Magazine, 29 May 2026 (source credited as Thames Water).", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day/", "date": "2026-05-29", "written_by": "deployer", "quote": "During a previous 18-week trial, Origin Orbit® was able to find over 800 leaks across Thames Water's network, helping to save an estimated 8.7 million litres of water per day." }, { "kind": "news report", "citation": "Tempest, O. (2026). Thames Water signs AI satellite deal to plug 100 million litres of daily leaks. Smart Water Magazine, 5 May 2026 (no verbatim quote taken).", "title": "Thames Water signs AI satellite deal to plug 100 million litres of daily leaks", "url": "https://smartwatermagazine.com/news/thames-water/thames-water-signs-ai-satellite-deal-plug-100-million-litres-daily-leaks", "date": "2026-05-05", "written_by": "independent" }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech in Partnership with Thames Water. Origin news, 29 May 2026.", "title": "Origin Tech in Partnership with Thames Water", "url": "https://www.origintech.co.uk/origin-news/origin-tech-in-partnership-with-thames-water", "date": "2026-05-29", "written_by": "makers", "quote": "By combining AI-driven satellite insights with operational expertise, Origin Tech is enabling faster, more precise detection of previously invisible leaks." }, { "kind": "press release", "citation": "Origin Tech (2026). Origin Tech Featured in BBC News and BBC Wiltshire Radio. Origin news, 20 May 2026.", "title": "Origin Tech Featured in BBC News and BBC Wiltshire Radio", "url": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio", "date": "2026-05-20", "written_by": "makers", "quote": "Origin Orbit® has been able to identify over 5K leaks, which is over 73.45 ML/d of leakage" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day. Newsroom, 1 May 2026.", "title": "Thames Water signs landmark leak detection contract with Origin Tech to save over 100 million litres of water per day", "url": "https://www.thameswater.co.uk/news/2026/apr/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-litres-of-water-per-day", "date": "2026-05-01", "written_by": "deployer" }, { "kind": "press release", "citation": "Thames Water (2026). Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South-East drought pressure intensifies. Newsroom, 24 August 2026.", "title": "Thames Water uses satellites, AI and thousands of acoustic sensors to hunt down leaks as South‑East drought pressure intensifies", "url": "https://www.thameswater.co.uk/news/2026/aug/thames-water-uses-satellites-ai-and-thousands-of-acoustic-sensors-to-hunt-down-leaks-as-south-east-drought-pressure-intensifies", "date": "2026-08-24", "written_by": "deployer" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "18-week Origin Orbit trial on Thames Water's network: over 800 leaks found, est. 8.7 million liters a day saved (utility figures); 13-month contract followed, target 100 million liters a day.", "account": "Thames Water trialed Origin Orbit, the satellite leak-detection product of North East England start-up Origin Tech Ltd (founded 2019). The company and the utility describe it as using AI on satellite data to flag suspected underground leaks within a 30-meter search radius. Origin's co-founder John Marsden told the BBC the satellites pass over Swindon roughly every six days. He said they produce points on a map for Thames Water crews. Thames Water's statements say an 18-week trial found over 800 leaks across the network. They were reported by the BBC (20 May 2026) and reproduced in trade press. It saved an estimated 8.7 million liters of water a day, with several leaks running at more than 10 liters per second. On the strength of the trial, Thames Water signed a 13-month contract, launched in March 2026 per the utility's release. It deploys 20 specialist teams expected to find about 25 leaks a week each, and aims to cut leakage by 100 million liters a day. That makes it the first water company to integrate Origin Orbit into business-as-usual leakage operations. Origin Tech's own site adds a 2026 claim that Origin Orbit identified over 5,000 leaks (73.45 ML/d) across its customers. All figures originate with the utility and the vendor, and no regulator or independent measurement is among the sources. The trial dates are not given. Smart Water Magazine reported the result on 5 May 2026. Cambridgeshire County Council's AI inspection contract (April 2026) and Hertfordshire's ARRES robot (January 2024) have no outcomes on record. They are not among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The software analyzed satellite data to identify possible water leaks." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used Origin Orbit." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Origin Orbit®" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Origin Orbit (Origin Tech satellite leak detection applying AI to satellite data to flag suspected leaks within a 30-meter search radius)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Origin Tech Ltd (North East England)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Origin Tech's AI satellite leak detection may have found over 800 leaks in an 18-week Thames Water trial, saving an estimated 8.7 million liters a day", "headline": "Origin Orbit trial may have found over 800 Thames Water leaks" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7d1b2c1ddb627a3cb73bdc8b7e842b73fac11086faf02670ed739acb1100f910" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Thames Water trialed Origin Orbit, the satellite leak-detection product of North East England start-up Origin Tech Ltd (founded 2019). The company and the utility describe it as using AI on satellite data to flag suspected underground leaks within a 30-meter search radius. Origin's co-founder John Marsden told the BBC the satellites pass over Swindon roughly every six days. He said they produce points on a map for Thames Water crews. Thames Water's statements say an 18-week trial found over 800 leaks across the network. They were reported by the BBC (20 May 2026) and reproduced in trade press. It saved an estimated 8.7 million liters of water a day, with several leaks running at more than 10 liters per second. On the strength of the trial, Thames Water signed a 13-month contract, launched in March 2026 per the utility's release. It deploys 20 specialist teams expected to find about 25 leaks a week each, and aims to cut leakage by 100 million liters a day. That makes it the first water company to integrate Origin Orbit into business-as-usual leakage operations. Origin Tech's own site adds a 2026 claim that Origin Orbit identified over 5,000 leaks (73.45 ML/d) across its customers. All figures originate with the utility and the vendor, and no regulator or independent measurement is among the sources. The trial dates are not given. Smart Water Magazine reported the result on 5 May 2026. Cambridgeshire County Council's AI inspection contract (April 2026) and Hertfordshire's ARRES robot (January 2024) have no outcomes on record. They are not among the sources.", "replication": { "produced_by": [ "Satellite passes about every six days over the network, processed into suspected-leak points within a 30-meter radius", "An 18-week trial in which Thames Water crews investigated the points with conventional ground methods", "A network with a large share of non-visible underground leaks (92% of Origin Orbit finds are non-visible, per the vendor)" ], "must_hold": [ "Satellite revisit frequency and ground conditions that allow moisture and movement to be detected", "Crew capacity to investigate points (20 teams at about 25 leaks a week each under the contract)", "Repair follow-through so that found leaks become saved water", "The utility's method for estimating liters saved per leak, which no independent source has checked" ], "echoes": [ { "date": "2026-05-29", "setting": "13-month business-as-usual contract launched March 2026 with 20 specialist teams, targeting 100 million liters a day; no result reported yet", "outcome": "unknown", "source": "https://watermagazine.co.uk/2026/05/29/thames-water-signs-landmark-leak-detection-contract-with-origin-tech-to-save-over-100-million-liters-of-water-per-day/" }, { "date": "2026-05-20", "setting": "Origin Tech's 2026 claim across its customers: over 5,000 leaks identified, 73.45 ML/d (vendor statement, unverified)", "outcome": "unknown", "source": "https://www.origintech.co.uk/origin-news/origin-tech-featured-in-bbc-news-and-bbc-wiltshire-radio" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 0, "record_mapped": 32, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0344", "title": "After UNEP MARS alerts, operators divert gas from an Iraqi flare that had released about 1.7m tCO2e since 2023; the source may be in the Zubair field near Basra", "summary": "The Chemical Engineer (5 May 2026), relaying UNEP: the largest source mitigated in 2026 was an Iraqi flare, 1.7m tCO2e since 2023, apparently in the Zubair field; Eni did not confirm closure.", "date_observed": "2026-05-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Chemical Engineer reported on 5 May 2026, relaying UNEP's Methane Alert and Response System (MARS) figures. MARS had curbed 41 methane super-emitters since launching in 2023. Six significant sources had stopped emitting in 2026 following MARS alerts, including three in Turkmenistan and one each in Libya, Iraq and Kazakhstan. The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility. The flare had released an estimated 1.7m tCO2e since 2023. The source appears to have been at a facility in the Zubair oil and gas field near Basra. The article reports that the operator Eni acknowledged running a leak detection and repair campaign at Zubair. Eni did not confirm closure of the specific source. The article says MARS uses data from 35 satellite instruments to identify large plumes and alert operators. UNEP's MARS page adds that IMEO couples satellite data with scientific expertise and advanced AI models. No date for the mitigation is given beyond 2026. UNEP's press releases were not available, and no UNEP case document for this source is on record.", "category": "benefit created", "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators mitigate them. This case was that purpose.", "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation", "model_version": null, "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); facility operators in Iraq (gas diversion); the article names Eni as operator of the Zubair field", "location": "Zubair oil and gas field near Basra, Iraq (location reported as apparent, not confirmed)", "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas production; intergovernmental observatory", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 1, "reason": "Operators are reported to have diverted gas to a newer facility. The operator did not confirm the specific closure, and no operational detail or cost is documented." }, { "group": "societal", "depth": 2, "reason": "Reported as the largest source mitigated in 2026, after an estimated 1.7m tCO2e released since 2023. It is still one case among about 41 confirmed, and unconfirmed by the operator." } ], "ai_role": { "status": "assessed", "statement": "The trade press credits the mitigation to MARS alerts. Only UNEP's general page describes MARS as satellite-based with advanced AI models, so the AI contribution to this detection is not isolated. A single news item relaying the system operator documents the case. The named field operator declined to confirm closure of the specific source." }, "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emissions estimate.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Iraq flare emissions)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The flare had released an estimated 1.7m tCO2e since 2023." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, location and operator response (Eni acknowledged a campaign at Zubair but did not confirm closure of the specific source).", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Zubair)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The source appears to have been at a facility in the Zubair oil and gas field near Basra." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "date": null, "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ], "replication": { "produced_by": [ "Satellite detection of a persistent flare plume emitting since 2023", "MARS alerts to operators with a newer facility able to take the diverted gas", "UNEP confirmation through later satellite observation (as described for MARS cases generally)" ], "must_hold": [ "Operator capacity and willingness to re-route gas rather than flare it", "Satellite coverage to confirm cessation", "Operator or government confirmation, absent here (Eni did not confirm the specific closure)" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "model_version": null, "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection (trade press relaying UNEP)", "model_version": null, "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091)", "model_version": null, "outcome": "recurred", "source": "AIBD-0091" } ] }, "paired_incident": null, "headline": "UNEP MARS alerts lead operators to divert gas from Iraqi flare", "metric": "the flare had released an estimated 1.7m tCO2e since 2023", "comparator": { "against": "the flare before gas was diverted", "before": "an estimated 1.7m tCO2e since 2023", "after": "operators diverted gas production to a newer facility", "basis": "measured", "quote": "The largest source mitigated this year was a flare in Iraq, where operators diverted gas production to a newer facility. The flare had released an estimated 1.7m tCO2e since 2023.", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/" }, "later": { "status": "unknown", "date": null, "note": "Eni did not confirm closing the specific source and nothing dated after the 5 May 2026 article was found in the cited sources; the September 2026 UNEP snapshot lists no Iraqi source among its top 50.", "quote": null, "url": null }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0344", "catalog_version": "1.0.0", "source_fingerprint": "5f1b2e0372d74c8235c8410853ea5a5f5eca7ae7023e04fed53a297c8d67ad9b", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0344-source-0001", "AIBD-0344-source-0002", "AIBD-0344-source-0003", "AIBD-0344-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); facility operators in Iraq (gas diversion); the article names Eni as operator of the Zubair field" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The trade press credits the mitigation to MARS alerts. Only UNEP's general page describes MARS as satellite-based with advanced AI models, so the AI contribution to this detection is not isolated. A single news item relaying the system operator documents the case. The named field operator declined to confirm closure of the specific source." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The trade press credits the mitigation to MARS alerts. Only UNEP's general page describes MARS as satellite-based with advanced AI models, so the AI contribution to this detection is not isolated. A single news item relaying the system operator documents the case. The named field operator declined to confirm closure of the specific source." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 1, "reason": "Operators are reported to have diverted gas to a newer facility. The operator did not confirm the specific closure, and no operational detail or cost is documented." }, { "group": "societal", "depth": 2, "reason": "Reported as the largest source mitigated in 2026, after an estimated 1.7m tCO2e released since 2023. It is still one case among about 41 confirmed, and unconfirmed by the operator." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 1, "reason": "Operators are reported to have diverted gas to a newer facility. The operator did not confirm the specific closure, and no operational detail or cost is documented." }, { "group": "societal", "depth": 2, "reason": "Reported as the largest source mitigated in 2026, after an estimated 1.7m tCO2e released since 2023. It is still one case among about 41 confirmed, and unconfirmed by the operator." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual beneficiary is identified." }, { "group": "organizational", "depth": 1, "reason": "Operators are reported to have diverted gas to a newer facility. The operator did not confirm the specific closure, and no operational detail or cost is documented." }, { "group": "societal", "depth": 2, "reason": "Reported as the largest source mitigated in 2026, after an estimated 1.7m tCO2e released since 2023. It is still one case among about 41 confirmed, and unconfirmed by the operator." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": 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It is still one case among about 41 confirmed, and unconfirmed by the operator." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that operators mitigate them. 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https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas production; intergovernmental observatory" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emissions estimate.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Iraq flare emissions)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The flare had released an estimated 1.7m tCO2e since 2023." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, location and operator response (Eni acknowledged a campaign at Zubair but did not confirm closure of the specific source).", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Zubair)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The source appears to have been at a facility in the Zubair oil and gas field near Basra." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0344-source-0001", "AIBD-0344-source-0002", "AIBD-0344-source-0003", "AIBD-0344-source-0004" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Baker, S. (2026). UN satellite programme curbs more than 40 methane 'super-emitters' since 2023. The Chemical Engineer, 5 May 2026.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' since 2023", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, emissions estimate.", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Iraq flare emissions)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The flare had released an estimated 1.7m tCO2e since 2023." }, { "kind": "news report", "citation": "Baker, S. (2026). Same article, location and operator response (Eni acknowledged a campaign at Zubair but did not confirm closure of the specific source).", "title": "UN satellite programme curbs more than 40 methane 'super-emitters' (Zubair)", "url": "https://www.thechemicalengineer.com/news/un-satellite-programme-curbs-more-than-40-methane-super-emitters-since-2023/", "date": "2026-05-05", "written_by": "independent", "quote": "The source appears to have been at a facility in the Zubair oil and gas field near Basra." }, { "kind": "press release", "citation": "UNEP (n.d.). Methane Alert and Response System (MARS). UNEP topics page.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/topics/energy/methane/methane-alert-and-response-system-mars", "written_by": "makers", "quote": "Using data from more than 30 satellite instruments, coupled with scientific expertise and advanced AI models, IMEO notifies governments and companies of emissions" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "The Chemical Engineer (5 May 2026), relaying UNEP: the largest source mitigated in 2026 was an Iraqi flare, 1.7m tCO2e since 2023, apparently in the Zubair field; Eni did not confirm closure.", "account": "The Chemical Engineer reported on 5 May 2026, relaying UNEP's Methane Alert and Response System (MARS) figures. MARS had curbed 41 methane super-emitters since launching in 2023. Six significant sources had stopped emitting in 2026 following MARS alerts, including three in Turkmenistan and one each in Libya, Iraq and Kazakhstan. The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility. The flare had released an estimated 1.7m tCO2e since 2023. The source appears to have been at a facility in the Zubair oil and gas field near Basra. The article reports that the operator Eni acknowledged running a leak detection and repair campaign at Zubair. Eni did not confirm closure of the specific source. The article says MARS uses data from 35 satellite instruments to identify large plumes and alert operators. UNEP's MARS page adds that IMEO couples satellite data with scientific expertise and advanced AI models. No date for the mitigation is given beyond 2026. UNEP's press releases were not available, and no UNEP case document for this source is on record." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UNEP International Methane Emissions Observatory (IMEO)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "After UNEP MARS alerts, operators divert gas from an Iraqi flare that had released about 1.7m tCO2e since 2023; the source may be in the Zubair field near Basra", "headline": "UNEP MARS alerts lead operators to divert gas from Iraqi flare" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "5f1b2e0372d74c8235c8410853ea5a5f5eca7ae7023e04fed53a297c8d67ad9b" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Chemical Engineer reported on 5 May 2026, relaying UNEP's Methane Alert and Response System (MARS) figures. MARS had curbed 41 methane super-emitters since launching in 2023. Six significant sources had stopped emitting in 2026 following MARS alerts, including three in Turkmenistan and one each in Libya, Iraq and Kazakhstan. The largest source mitigated this year was a flare in Iraq, where operators diverted gas to a newer facility. The flare had released an estimated 1.7m tCO2e since 2023. The source appears to have been at a facility in the Zubair oil and gas field near Basra. The article reports that the operator Eni acknowledged running a leak detection and repair campaign at Zubair. Eni did not confirm closure of the specific source. The article says MARS uses data from 35 satellite instruments to identify large plumes and alert operators. UNEP's MARS page adds that IMEO couples satellite data with scientific expertise and advanced AI models. No date for the mitigation is given beyond 2026. UNEP's press releases were not available, and no UNEP case document for this source is on record.", "replication": { "produced_by": [ "Satellite detection of a persistent flare plume emitting since 2023", "MARS alerts to operators with a newer facility able to take the diverted gas", "UNEP confirmation through later satellite observation (as described for MARS cases generally)" ], "must_hold": [ "Operator capacity and willingness to re-route gas rather than flare it", "Satellite coverage to confirm cessation", "Operator or government confirmation, absent here (Eni did not confirm the specific closure)" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: pipeline leak stopped after a MARS notification (UNEP case document); emissions observed again by 21 May 2026", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" }, { "date": "2026-04-01", "setting": "Aerial field, Alberta, Canada: ball-valve repair one week after detection (trade press relaying UNEP)", "outcome": "recurred", "source": "https://www.thechemicalengineer.com/news/canada-plugs-major-source-of-methane-emissions-from-oil-and-gas-field-leak/" }, { "date": "2024-01-01", "setting": "Hassi Messaoud, Algeria (existing record AIBD-0091)", "outcome": "recurred", "source": "AIBD-0091" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0554", "title": "Milton Keynes City Council and Valon: streamlining planning with AI", "summary": "Milton Keynes reports faster validation and decisions during its Valon pilot, with receipt-to-validation time falling from 15.8 to 7.6 days.", "date_observed": "2026-05-05", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-017", "account": "Milton Keynes piloted Valon for planning work from October to December 2025. The council reports that officers validated applications 60–80% faster. Its analysis of the planning register put average receipt-to-validation time at 15.8 days before and 7.6 days during the pilot, and validation-to-decision time at 53.1 and 43.2 days. The estimated 1,360 officer hours per year is an extrapolation from an assumed 80% saving. Valon’s own account describes major-application checks falling from about 65 to 10 minutes and non-major checks from 15 to 5 minutes. It reports 7.7 days for early-November validation turnaround and a separate 18% decision-time difference against a non-pilot group. The two accounts do not publish the underlying timesheets, selected application records, sample sizes, or rules for constructing the comparisons. These are reported efficiency gains, with uncertainty about how much AI caused. The council purchased a one-year license after the pilot and reports continued use.", "category": "general benefit", "unexpected": false, "purpose": "Support planning officers from application validation through decision-making.", "system": "Valon AI planning platform", "model_version": null, "developer": "Valon", "deployer": "Milton Keynes City Council", "location": "United Kingdom", "domain": "Planning administration", "segment": null, "benefit_type": "Improved Organizational Efficiency", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council and developer report shorter validation and decision-processing times. The underlying samples and comparison methods are not published, so the gain remains a first-party estimate." }, { "group": "personal", "depth": 1, "reason": "Officers report less processing work, and the council reports shorter waits for applicants. No improvement in decision quality or realized housing delivery is demonstrated." } ], "ai_role": { "status": "assessed", "statement": "The council used Valon to read and check planning documents and present information for officer review. The council and developer describe shorter processing times, but provide no reproducible analysis that isolates AI from case mix, staffing, or other workflow changes. Planning decisions remain officers’ responsibility." }, "evidence": [ { "kind": "report", "citation": "Milton Keynes City Council, “Milton Keynes City Council and Valon: streamlining planning with AI,” Local Government Association, May 8, 2026, “Impact,” “Key takeaways,” and “What’s next.”", "title": "Milton Keynes City Council and Valon: streamlining planning with AI", "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "date": "2026-05-08", "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Valon, “Innovation at the Centre: How Milton Keynes’ Planning Team Transformed with AI,” undated, “Impact at a Glance,” “From Hour-Long Checks to Minutes,” and “Department-Wide Velocity.”", "title": "Innovation at the Centre: How Milton Keynes’ Planning Team Transformed with AI", "url": "https://www.valon-ai.com/case-studies/milton-keynes", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A nominated council pilot group using Valon on live planning applications from October to December 2025", "Document retrieval from the public planning register, officer training, and regular feedback to the developer" ], "must_hold": [ "Officers must review the information that the system supplies and retain responsibility for planning decisions", "The system must reflect the authority’s validation requirements and have access to the necessary application documents", "Comparable timings and case characteristics are needed to determine whether similar savings recur" ], "echoes": [] }, "paired_incident": null, "headline": "Milton Keynes reports faster planning validation with Valon", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-05-08", "note": "The council reports that it purchased a one-year license after the pilot and that officers continue using Valon. Integration with Arcus is being scoped, and rollout to all planning officers remains an ambition.", "quote": null, "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "source": "https://www.miltonkeynes.co.uk/your-world/milton-keynes-council-slashes-planning-wait-times-by-a-fifth-using-ai-8499059", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' report and the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0554", "catalog_version": "1.0.0", "source_fingerprint": "cc59f0d66336edc1f31ed894bc68b3ef5a97a21a4f842c9857b62036dc64db03", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Valon", "deployer": "Milton Keynes City Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The council used Valon to read and check planning documents and present information for officer review. The council and developer describe shorter processing times, but provide no reproducible analysis that isolates AI from case mix, staffing, or other workflow changes. Planning decisions remain officers’ responsibility." } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Valon read planning documents, checked them, and presented information to officers. The council and developer report faster processing but do not isolate AI from differences in applications, staffing, or workflow. Officers retained responsibility for decisions.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The council used Valon to read and check planning documents and present information for officer review. The council and developer describe shorter processing times, but provide no reproducible analysis that isolates AI from case mix, staffing, or other workflow changes. Planning decisions remain officers’ responsibility." } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council and developer report shorter validation and decision-processing times. The underlying samples and comparison methods are not published, so the gain remains a first-party estimate." }, { "group": "personal", "depth": 1, "reason": "Officers report less processing work, and the council reports shorter waits for applicants. No improvement in decision quality or realized housing delivery is demonstrated." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' report and the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from the council and developer accounts. Additional first-party detail does not supply independent verification.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council and developer report shorter validation and decision-processing times. The underlying samples and comparison methods are not published, so the gain remains a first-party estimate." }, { "group": "personal", "depth": 1, "reason": "Officers report less processing work, and the council reports shorter waits for applicants. No improvement in decision quality or realized housing delivery is demonstrated." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The council and developer report shorter processing times and less work for officers. They publish no underlying sample or comparison method, and the sources establish no improvement in decision quality or completed housing.", "editor_note": "" } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The council and developer report shorter validation and decision-processing times. The underlying samples and comparison methods are not published, so the gain remains a first-party estimate." }, { "group": "personal", "depth": 1, "reason": "Officers report less processing work, and the council reports shorter waits for applicants. No improvement in decision quality or realized housing delivery is demonstrated." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-017" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-05-08", "note": "The council reports that it purchased a one-year license after the pilot and that officers continue using Valon. Integration with Arcus is being scoped, and rollout to all planning officers remains an ambition.", "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai" } } }, "provenance": { "kind": "source_review", "basis": "The council’s “What’s next” section reports a one-year license and continued officer use; expanded integration and full rollout remain future plans.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0554-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0554" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Milton Keynes piloted Valon for planning work from October to December 2025. 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The council purchased a one-year license after the pilot and reports continued use.", "benefit_type": "Improved Organizational Efficiency" } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. 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The underlying samples and comparison methods are not published, so the gain remains a first-party estimate." }, { "group": "personal", "depth": 1, "reason": "Officers report less processing work, and the council reports shorter waits for applicants. No improvement in decision quality or realized housing delivery is demonstrated." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. 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The pilot period is October–December 2025, but the sources do not establish an exact date for the measured result.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002", "https://www.miltonkeynes.co.uk/your-world/milton-keynes-council-slashes-planning-wait-times-by-a-fifth-using-ai-8499059" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A nominated council pilot group using Valon on live planning applications from October to December 2025", "Document retrieval from the public planning register, officer training, and regular feedback to the developer" ], "must_hold": [ "Officers must review the information that the system supplies and retain responsibility for planning decisions", "The system must reflect the authority’s validation requirements and have access to the necessary application documents", "Comparable timings and case characteristics are needed to determine whether similar savings recur" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. 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Its timesheet and register analysis are summarized but not released." }, { "source_refs": [ "AIBD-0554-source-0002" ], "url": "https://www.valon-ai.com/case-studies/milton-keynes", "relationship": "Original developer account adds task-level timings and more specific, incompletely described comparisons." } ], "lead_source_ref": "AIBD-0554-source-0001", "retained_source_order": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "ordering_basis": "The council account directly supports the case and leads. The developer account adds measurement detail and discrepancies. Earliest publicity supplies a separate chronology source without replacing the primary lead.", "chronology_source": { "url": "https://www.miltonkeynes.co.uk/your-world/milton-keynes-council-slashes-planning-wait-times-by-a-fifth-using-ai-8499059", "title": "Milton Keynes Council slashes planning wait times by a fifth using AI", "date": "2026-05-05", "published_on": "2026-05-05", "basis": "Earliest dated publication of these pilot results verified in this review. Joshua Parker contributor article, published at 10:46 BST. It establishes chronology, not an independently reproduced result." }, "claim_lineage": [ { "claim": "The council reports receipt-to-validation times of 15.8 and 7.6 days and validation-to-decision times of 53.1 and 43.2 days.", "source_ref": "AIBD-0554-source-0001", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "locator": "“Impact,” first paragraph; “Key takeaways,” “Evaluations”", "role": "Council’s summary of its own register analysis and officer timesheets" } ], "method": { "pilot_period": "October–December 2025", "receipt_to_validation_days": { "before": 15.8, "during": 7.6 }, "validation_to_decision_days": { "before": 53.1, "during": 43.2 }, "underlying_material": "Public planning-register records and council timesheets, identified but not linked or supplied as an analysis dataset" }, "limitations": [ "No application identifiers, cohort sizes, case-mix controls, selection rules, or analysis code are supplied.", "The public register is named without a link to the selected records or frozen extract. The full analysis cannot be reconstructed from the article alone." ] }, { "claim": "The estimated 1,360 officer hours available annually is extrapolated from an estimated 80% validation-time saving.", "source_ref": "AIBD-0554-source-0001", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "locator": "“Impact,” first paragraph, final sentence", "role": "Council annual extrapolation" } ], "method": { "estimated_annual_hours": 1360, "assumed_validation_saving_percent": 80 }, "limitations": [ "This is not an observed full-year saving, cash saving, or increase in completed housing.", "The article does not provide the annual workload or baseline-hours calculation." ] }, { "claim": "The developer reports active validation time falling from 65 to 10 minutes for major cases and from 15 to 5 minutes for non-major cases.", "source_ref": "AIBD-0554-source-0002", "source_chain": [ { "url": "https://www.valon-ai.com/case-studies/milton-keynes", "locator": "“From Hour-Long Checks to Minutes” and “Validation Time per Case (Minutes)” chart", "role": "Developer’s original account of the same council pilot" } ], "method": { "major_minutes": { "before": 65, "after": 10 }, "nonmajor_minutes": { "before": 15, "after": 5 } }, "limitations": [ "No sample counts, task-timing records, or independent verification accompany these figures.", "Active officer time is different from elapsed receipt-to-validation time." ] }, { "claim": "The developer gives 7.7 days for early-November turnaround and an 18% difference in decision time against a non-pilot control group.", "source_ref": "AIBD-0554-source-0002", "source_chain": [ { "url": "https://www.valon-ai.com/case-studies/milton-keynes", "locator": "“Impact at a Glance” and “Department-Wide Velocity,” including the early-October/early-November comparison", "role": "Developer’s description of comparison periods and comparator" } ], "method": { "early_october_days": 15.8, "early_november_days": 7.7, "reported_decision_time_difference_percent": 18 }, "limitations": [ "The developer’s 7.7 differs from the LGA account’s 7.6; the sources do not explain whether the difference reflects rounding or a different window.", "The claimed non-pilot control group is not defined, and comparability is not demonstrated.", "An 18% difference is not interchangeable with the separate promotional claim of 18 days saved." ] }, { "claim": "The council obtained a one-year license and continued using Valon after the pilot.", "source_ref": "AIBD-0554-source-0001", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "locator": "“What’s next,” first two sentences", "role": "Deployer follow-up account" } ], "method": {}, "limitations": [ "No procurement document is linked. Arcus integration is being scoped, and full rollout remains a future objective." ] } ], "excluded_republications": [ { "url": "https://www.miltonkeynes.co.uk/your-world/milton-keynes-council-slashes-planning-wait-times-by-a-fifth-using-ai-8499059", "relationship": "Earlier contributor publicity repeats pilot figures and quotes the vendor CEO without providing independent evaluation or underlying records. Retained separately for chronology." }, { "url": "https://www.cityam.com/councils-turn-to-ai-to-boost-housebuilding/", "relationship": "Later original reporting attributes the eight-day improvement to the council and adds broader housing-policy interviews. It supplies no new evidence about the Milton Keynes pilot’s measured effect. Generic policy context is not counted as AI-result corroboration." } ], "independent_evaluations_of_reported_results": 0, "limitations": [ "The council and developer accounts are original but interested-party sources. Neither independently validates AI-caused improvements.", "Neither retained page links the underlying timesheets, selected register extract, evaluation protocol, statistical analysis, appendices, or supplementary results. Those underlying materials were not inspected.", "The 60–80% reported saving in officer time, the 80% assumption for annual hours, elapsed processing times, and the 18% control comparison describe different measures and are not combined.", "The developer’s 7.7-day figure and the council account’s 7.6-day figure remain distinct; no unsupported reconciliation is introduced.", "No source demonstrates that faster processing produced more homes or better planning decisions." ], "access_audit": [ { "url": "https://www.local.gov.uk/case-studies/milton-keynes-city-council-and-valon-streamlining-planning-ai", "access": "Complete original council case-study text read, including all five sections and publication date. No linked supporting analysis or supplement appears in the article." }, { "url": "https://www.valon-ai.com/case-studies/milton-keynes", "access": "Complete developer case-study text, chart text, and source HTML read. No publication-date metadata or supporting dataset was present." }, { "url": "https://www.miltonkeynes.co.uk/your-world/milton-keynes-council-slashes-planning-wait-times-by-a-fifth-using-ai-8499059", "access": "Complete contributor article read, including date, byline, time-saving figures, and CEO quotation." }, { "url": "https://www.cityam.com/councils-turn-to-ai-to-boost-housebuilding/", "access": "Complete May 18 City AM article read. It attributes the eight-day result to the council and adds industry context, not an independent pilot evaluation." } ], "scope": "Complete lineage and access review of the retained written accounts. The unavailable underlying timesheets, register extracts, and evaluation methods are explicitly unresolved." } }, "provenance": { "kind": "source_review", "basis": "Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The council and developer report the results but publish no underlying timesheets or analysis. Their measures of officer time and elapsed processing time differ. The developer reports 7.7 days and the council 7.6 days, without explaining the difference.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Milton Keynes reports faster validation and decisions during its Valon pilot, with receipt-to-validation time falling from 15.8 to 7.6 days.", "account": "Milton Keynes piloted Valon for planning work from October to December 2025. The council reports that officers validated applications 60–80% faster. Its analysis of the planning register put average receipt-to-validation time at 15.8 days before and 7.6 days during the pilot, and validation-to-decision time at 53.1 and 43.2 days. The estimated 1,360 officer hours per year is an extrapolation from an assumed 80% saving. Valon’s own account describes major-application checks falling from about 65 to 10 minutes and non-major checks from 15 to 5 minutes. It reports 7.7 days for early-November validation turnaround and a separate 18% decision-time difference against a non-pilot group. The two accounts do not publish the underlying timesheets, selected application records, sample sizes, or rules for constructing the comparisons. These are reported efficiency gains, with uncertainty about how much AI caused. The council purchased a one-year license after the pilot and reports continued use." } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Valon AI planning platform" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Valon" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Milton Keynes City Council and Valon: streamlining planning with AI", "headline": "Milton Keynes reports faster planning validation with Valon" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cc59f0d66336edc1f31ed894bc68b3ef5a97a21a4f842c9857b62036dc64db03" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the reviewed case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Milton Keynes piloted Valon for planning work from October to December 2025. The council reports that officers validated applications 60–80% faster. Its analysis of the planning register put average receipt-to-validation time at 15.8 days before and 7.6 days during the pilot, and validation-to-decision time at 53.1 and 43.2 days. The estimated 1,360 officer hours per year is an extrapolation from an assumed 80% saving. Valon’s own account describes major-application checks falling from about 65 to 10 minutes and non-major checks from 15 to 5 minutes. It reports 7.7 days for early-November validation turnaround and a separate 18% decision-time difference against a non-pilot group. The two accounts do not publish the underlying timesheets, selected application records, sample sizes, or rules for constructing the comparisons. These are reported efficiency gains, with uncertainty about how much AI caused. The council purchased a one-year license after the pilot and reports continued use.", "replication": { "produced_by": [ "A nominated council pilot group using Valon on live planning applications from October to December 2025", "Document retrieval from the public planning register, officer training, and regular feedback to the developer" ], "must_hold": [ "Officers must review the information that the system supplies and retain responsibility for planning decisions", "The system must reflect the authority’s validation requirements and have access to the necessary application documents", "Comparable timings and case characteristics are needed to determine whether similar savings recur" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated mapped fields following the original-source review. Traced the council’s figures to its original LGA account and the developer’s more detailed account. Distinguished observed timings from annual extrapolation, preserved differences between the reported comparisons, and corrected the earliest verified publication to May 5, 2026.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0554-source-0001", "AIBD-0554-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A group of council officers used Valon on live planning applications from October to December 2025. The system retrieved documents from the public planning register. Officers received training and gave feedback to the developer.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 18, "record_mapped": 15, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0544", "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "summary": "Bradford reports that Annie handles about 50 conversations weekly, with 20% outside office hours and 74% user satisfaction.", "date_observed": "2026-05-08", "date_basis": "source publication", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-003", "account": "Bradford reports that its Annie adult-social-care assistant answers questions on the web and WhatsApp, including outside contact-center hours and in multiple languages. Since its October 2025 launch, the council reports about 50 conversations weekly, 20% outside office hours, and 74% satisfaction from follow-up feedback. The public account does not give the feedback denominator, response rate, or underlying conversation logs. Contact-center staff also use Annie to find resources. The council reports that human monitoring of conversations helped identify people who needed food or electricity and led to food parcels, without publishing case counts or individual outcomes. Equivalence to one full-time adviser is the council’s estimate, without a published calculation or demonstrated staffing reduction. A planned 20% shift of information queries to Annie is a target. These are original claims from the deploying council, without independent outcome evaluation.", "category": "general benefit", "unexpected": false, "purpose": "Provide accessible adult-social-care information, advice, and signposting through a digital assistant.", "system": "Annie, Bradford’s AIDA adult-social-care digital assistant on the web and WhatsApp", "model_version": null, "developer": "Bullet AI, with council co-production facilitated by CC2i", "deployer": "Bradford Council", "location": "United Kingdom", "domain": "Adult social care and public information", "segment": null, "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": 2, "reason": "A functioning multilingual, 24/7 advice channel handles roughly 50 conversations weekly. This is a reported service-capability gain." }, { "group": "personal", "depth": 2, "reason": "Residents use the service outside office hours and in several languages. Improved health and completed care provision are unmeasured." } ], "ai_role": { "status": "assessed", "statement": "Annie retrieves and combines information from trusted service resources, asks clarifying questions, and supports multilingual conversations. The reported access and usage gains are attributed to the assistant, while improved care outcomes are not established." }, "evidence": [ { "kind": "report", "citation": "Bradford Council project account, published by the Local Government Association. Bradford Council: Supporting the ASC front door with AI digital assistants. 2026-05-08. Sections “How does it work?,” “Safeguarding, governance and risk,” and “Impact.” Original deployment, usage, and feedback account. Underlying dashboard logs, feedback data, and staffing-equivalence calculations are not published.", "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "date": "2026-05-08", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Bradford co-produced the AIDA approach with Norfolk and West Northamptonshire councils, CC2i, and Bullet AI.", "The Bradford assistant uses trusted service information and operates through web and WhatsApp channels." ], "must_hold": [ "The council curates approved service information and keeps that information current.", "Staff monitor conversations and handle complex queries, with a mechanism to retrieve the preceding conversation.", "Accessible web and messaging channels, appropriate language support, and available local services are needed for the reported access benefit." ], "echoes": [] }, "paired_incident": null, "headline": "Bradford adds multilingual, out-of-hours social-care advice", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0544", "catalog_version": "1.0.0", "source_fingerprint": "4b8dc86c4dff45f104d81051c6f9ba65ee3228ecdd930f61865f16cca53ee9d8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0544-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Bullet AI, with council co-production facilitated by CC2i", "deployer": "Bradford Council" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Annie retrieves and combines information from trusted service resources, asks clarifying questions, and supports multilingual conversations. The reported access and usage gains are attributed to the assistant, while improved care outcomes are not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "Annie retrieves and combines information from trusted service resources, asks clarifying questions, and supports multilingual conversations. 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This is a reported service-capability gain." }, { "group": "personal", "depth": 2, "reason": "Residents use the service outside office hours and in several languages. Improved health and completed care provision are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "A functioning multilingual, 24/7 advice channel handles roughly 50 conversations weekly. This is a reported service-capability gain." }, { "group": "personal", "depth": 2, "reason": "Residents use the service outside office hours and in several languages. Improved health and completed care provision are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "A functioning multilingual, 24/7 advice channel handles roughly 50 conversations weekly. This is a reported service-capability gain." }, { "group": "personal", "depth": 2, "reason": "Residents use the service outside office hours and in several languages. Improved health and completed care provision are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-003" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0544" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Bradford reports that its Annie adult-social-care assistant answers questions on the web and WhatsApp, including outside contact-center hours and in multiple languages. Since its October 2025 launch, the council reports about 50 conversations weekly, 20% outside office hours, and 74% satisfaction from follow-up feedback. The public account does not give the feedback denominator, response rate, or underlying conversation logs. Contact-center staff also use Annie to find resources. The council reports that human monitoring of conversations helped identify people who needed food or electricity and led to food parcels, without publishing case counts or individual outcomes. Equivalence to one full-time adviser is the council’s estimate, without a published calculation or demonstrated staffing reduction. A planned 20% shift of information queries to Annie is a target. These are original claims from the deploying council, without independent outcome evaluation.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "A functioning multilingual, 24/7 advice channel handles roughly 50 conversations weekly. This is a reported service-capability gain." }, { "group": "personal", "depth": 2, "reason": "Residents use the service outside office hours and in several languages. Improved health and completed care provision are unmeasured." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "reported" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Provide accessible adult-social-care information, advice, and signposting through a digital assistant." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Provide accessible adult-social-care information, advice, and signposting through a digital assistant." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-05-08", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Bradford co-produced the AIDA approach with Norfolk and West Northamptonshire councils, CC2i, and Bullet AI.", "The Bradford assistant uses trusted service information and operates through web and WhatsApp channels." ], "must_hold": [ "The council curates approved service information and keeps that information current.", "Staff monitor conversations and handle complex queries, with a mechanism to retrieve the preceding conversation.", "Accessible web and messaging channels, appropriate language support, and available local services are needed for the reported access benefit." ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "source": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Adult social care and public information" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Bradford Council project account, published by the Local Government Association. Bradford Council: Supporting the ASC front door with AI digital assistants. 2026-05-08. Sections “How does it work?,” “Safeguarding, governance and risk,” and “Impact.” Original deployment, usage, and feedback account. Underlying dashboard logs, feedback data, and staffing-equivalence calculations are not published.", "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "date": "2026-05-08", "written_by": "deployer" } ] } }, "provenance": { "kind": "source_review", "basis": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0544-source-0001" ], "role": "Active evidence sources in reviewed order" }, "provenance": { "kind": "curatorial", "basis": "Assigned to the retained evidence in the dated source review.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Bradford Council project account, published by the Local Government Association. Bradford Council: Supporting the ASC front door with AI digital assistants. 2026-05-08. Sections “How does it work?,” “Safeguarding, governance and risk,” and “Impact.” Original deployment, usage, and feedback account. Underlying dashboard logs, feedback data, and staffing-equivalence calculations are not published.", "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "date": "2026-05-08", "written_by": "deployer" } ] } }, "provenance": { "kind": "source_review", "basis": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0544-source-0001" ], "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "published_on": "2026-05-08", "relationship": "deployer", "citation": "Bradford Council project account, published by the Local Government Association. Bradford Council: Supporting the ASC front door with AI digital assistants. 2026-05-08. Sections “How does it work?,” “Safeguarding, governance and risk,” and “Impact.” Original deployment, usage, and feedback account. Underlying dashboard logs, feedback data, and staffing-equivalence calculations are not published." } ], "excluded_republications": [], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0544-source-0001", "retained_source_order": [ "AIBD-0544-source-0001" ], "ordering_basis": "The original council/project account directly supports the central reported benefit. Additional sources are retained only for the specific earlier claim, technical disclosure, or sample distinction recorded in claim_lineage.", "claim_lineage": [ { "claim": "Usage, out-of-hours access, satisfaction, and staffing-equivalence estimate", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "locator": "Impact, first paragraph and concluding paragraphs", "role": "Original council account of dashboard use and proactive feedback", "access_status": "Full relevant text reviewed", "published_on": "2026-05-08" } ], "limitations": [ "Dashboard records and feedback responses are not public; the denominator, response rate, and exact measurement period are unspecified.", "The one-adviser equivalence has no published calculation and is not demonstrated staffing savings. The 20% channel-shift figure is a future target." ], "source_ref": "AIBD-0544-source-0001" }, { "claim": "AI contribution, language support, and human follow-up", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "locator": "How does it work?; Safeguarding, governance and risk", "role": "Original deployment description and monitoring account", "access_status": "Full relevant text reviewed", "published_on": "2026-05-08" } ], "limitations": [ "No model name or version is disclosed.", "The report that monitoring led to food parcels has no published case count or case-level evidence.", "The DPIA, penetration-test report, and Cyber Security & IG pack are not attached; the pack is offered on request and was not inspected." ], "source_ref": "AIBD-0544-source-0001" }, { "claim": "October 2025 launch and public availability", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/bradford-council-supporting-asc-front-door-ai-digital-assistants", "locator": "Impact: launch in October 2025", "role": "Original retrospective council account", "access_status": "Full relevant text reviewed", "published_on": "2026-05-08" }, { "url": "https://bradford.connecttosupport.org/media/dyjfthie/provider-bulletin-edition-283.pdf", "locator": "p. 2, ANNIE notice and embedded press-release link", "role": "Earlier original council provider bulletin", "access_status": "Full PDF notice and link annotation reviewed", "published_on": "2025-10-30" }, { "url": "https://news.bradford.gov.uk/press-releases/ea5c7566-e78e-4d0c-b107-c32750399d1f/bradford-council-launches-digital-advisor-for-adult-social-care", "locator": "Council launch announcement linked from provider bulletin", "role": "Underlying original council release", "access_status": "Page shell and title were accessible, but the dynamic article body was not retrieved." } ], "limitations": [ "The earlier bulletin establishes launch availability, not the later 50-conversation, 20%-out-of-hours, or 74%-satisfaction results. It does not justify dating those results to October 2025." ], "source_ref": "AIBD-0544-source-0001" } ], "limitations": [ "Underlying usage/feedback data and the calculation of adviser equivalence remain unpublished.", "The original launch release’s body and the on-request governance documents were not available for review." ] } }, "provenance": { "kind": "source_review", "basis": "Read the original council account and traced the earlier launch notice. Kept May 8, 2026 for the usage results and made the unpublished feedback denominator and staffing calculation explicit.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The underlying usage and feedback data are unpublished, as is the calculation of adviser equivalence. The original launch release and governance documents were inaccessible.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Bradford reports that Annie handles about 50 conversations weekly, with 20% outside office hours and 74% user satisfaction.", "account": "Bradford reports that its Annie adult-social-care assistant answers questions on the web and WhatsApp, including outside contact-center hours and in multiple languages. Since its October 2025 launch, the council reports about 50 conversations weekly, 20% outside office hours, and 74% satisfaction from follow-up feedback. The public account does not give the feedback denominator, response rate, or underlying conversation logs. Contact-center staff also use Annie to find resources. The council reports that human monitoring of conversations helped identify people who needed food or electricity and led to food parcels, without publishing case counts or individual outcomes. Equivalence to one full-time adviser is the council’s estimate, without a published calculation or demonstrated staffing reduction. A planned 20% shift of information queries to Annie is a target. These are original claims from the deploying council, without independent outcome evaluation." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Annie, Bradford’s AIDA adult-social-care digital assistant on the web and WhatsApp" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Bullet AI, with council co-production facilitated by CC2i" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Bradford Council: Supporting the ASC front door with AI digital assistants", "headline": "Bradford adds multilingual, out-of-hours social-care advice" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "4b8dc86c4dff45f104d81051c6f9ba65ee3228ecdd930f61865f16cca53ee9d8" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Bradford reports that its Annie adult-social-care assistant answers questions on the web and WhatsApp, including outside contact-center hours and in multiple languages. Since its October 2025 launch, the council reports about 50 conversations weekly, 20% outside office hours, and 74% satisfaction from follow-up feedback. The public account does not give the feedback denominator, response rate, or underlying conversation logs. Contact-center staff also use Annie to find resources. The council reports that human monitoring of conversations helped identify people who needed food or electricity and led to food parcels, without publishing case counts or individual outcomes. Equivalence to one full-time adviser is the council’s estimate, without a published calculation or demonstrated staffing reduction. A planned 20% shift of information queries to Annie is a target. These are original claims from the deploying council, without independent outcome evaluation.", "replication": { "produced_by": [ "Bradford co-produced the AIDA approach with Norfolk and West Northamptonshire councils, CC2i, and Bullet AI.", "The Bradford assistant uses trusted service information and operates through web and WhatsApp channels." ], "must_hold": [ "The council curates approved service information and keeps that information current.", "Staff monitor conversations and handle complex queries, with a mechanism to retrieve the preceding conversation.", "Accessible web and messaging channels, appropriate language support, and available local services are needed for the reported access benefit." ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0544-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 4, "record_mapped": 27, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0559", "title": "OSCAR: Orchestrated Service & Citizen AI Router", "summary": "Peterborough and Datnexa are developing OSCAR to connect council services. The council reports that OSCAR Workforce is live, but has not supplied measured results.", "date_observed": "2026-05-13", "date_basis": "source publication", "date_precision": "day", "benefit_status": "mixed", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-023", "account": "Peterborough’s May 13, 2026 LGA case study describes OSCAR as a proof of concept for connecting council assistants through a shared service interface. Datnexa identifies itself as the development partner and describes AI that interprets requests and routes them to specialist services. On October 21, the council reported that OSCAR Workforce was live and helped staff find emails and documents and query data faster. It did not publish timings, user counts, or a comparative evaluation. The resident-facing accessibility benefits remain intended. A separate council contract identifies Datnexa as the supplier for Workforce design and scoping. That contract establishes procurement, not a measured benefit.", "category": "general benefit", "unexpected": false, "purpose": "Connect service-specific assistants through a shared, governed digital front door.", "system": "OSCAR, the Orchestrated Service & Citizen AI Router, and OSCAR Workforce", "model_version": null, "developer": "Datnexa and Peterborough City Council", "deployer": "Peterborough City Council", "location": "United Kingdom", "domain": "Local-government service orchestration", "segment": null, "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "The council reports that OSCAR Workforce helps staff find information and query data faster, but supplies no measured comparison or independently evaluated organizational result." }, { "group": "personal", "depth": null, "reason": "The resident-facing system is intended to simplify access to council services. The retained sources supply no measured resident outcome." } ], "ai_role": { "status": "unassessed", "statement": "OSCAR is intended to interpret requests, route them among specialist agents, and apply common controls. Datnexa states that the system will not independently diagnose, decide eligibility, or make safeguarding judgments. The council reports internal Workforce use, but no source supplies a model version, task-level test results, or an independent assessment of the AI contribution." }, "evidence": [ { "kind": "report", "citation": "Peterborough City Council project account, “OSCAR — Orchestrated Service & Citizen AI Router,” Local Government Association, May 13, 2026, “The solution” and “Strategic Roadmap: Scaling OSCAR.”", "title": "OSCAR — Orchestrated Service & Citizen AI Router", "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "date": "2026-05-13", "written_by": "deployer", "quote": null }, { "kind": "press release", "citation": "Peterborough City Council, “Council staff member heralded as one of the country’s top AI leaders,” October 21, 2026, paragraph beginning “The council’s OSCAR workforce tool…”", "title": "Council staff member heralded as one of the country's top AI leaders", "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "date": "2026-10-21", "written_by": "deployer", "quote": null }, { "kind": "press release", "citation": "Datnexa HQ, “OSCAR: Building an AI front door with, not just for, local government,” July 9, 2026, “What OSCAR actually is” and “Built with governance from day one.”", "title": "OSCAR: Building an AI front door with, not just for, local government", "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "date": "2026-07-09", "written_by": "makers", "quote": null }, { "kind": "other", "citation": "Peterborough City Council, contract register, “Oscar Workforce AI Assistant,” reference DN827472; award dated October 5, 2026, description and awarded supplier fields. Publication date not stated.", "title": "Oscar Workforce AI Assistant", "url": "https://procontract.due-north.com/ContractsRegister/ViewContractDetails?contractId=3fafb2cc-33a1-f111-813c-005056b64545", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "The framework is designed for web, WhatsApp, and voice channels and for connection to existing services.", "The reported design includes centralized permissions, redaction, guardrails, and audit logging." ], "must_hold": [ "Specialist services and information sources must be available for the routing system to use", "Human staff must retain responsibility for the decisions that the system is not authorized to make", "Access controls and records of system actions must work in the deployment, rather than merely being described in the design" ], "echoes": [] }, "paired_incident": null, "headline": "Peterborough develops OSCAR to connect council AI services", "metric": null, "comparator": null, "later": { "status": "scaled", "date": "2026-10-21", "note": "Peterborough reports that the internal OSCAR Workforce tool is live. No rollout date, usage count, or measured time saving is supplied, and resident-facing benefits remain unverified.", "quote": null, "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders" }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "source": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' press release, the deployer's report, the deployer's press release and the deployer's other. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0559", "catalog_version": "1.0.0", "source_fingerprint": "93564829de6b05bff61f6216bddc47315b330fd21a5cefd8e73ca7ab7111ed40", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Datnexa and Peterborough City Council", "deployer": "Peterborough City Council" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "developer", "deployer" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Datnexa and Peterborough City Council developed the system. The council operates it.", "editor_note": "" } }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "OSCAR is intended to interpret requests, route them among specialist agents, and apply common controls. Datnexa states that the system will not independently diagnose, decide eligibility, or make safeguarding judgments. The council reports internal Workforce use, but no source supplies a model version, task-level test results, or an independent assessment of the AI contribution." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the makers' press release, the deployer's report, the deployer's press release and the deployer's other. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from retained evidence under the existing display rule. All retained accounts concern the developer, deployer, or buyer; additional sources do not create independent verification.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The council reports that OSCAR Workforce helps staff find information and query data faster, but supplies no measured comparison or independently evaluated organizational result." }, { "group": "personal", "reason": "The resident-facing system is intended to simplify access to council services. The retained sources supply no measured resident outcome." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The council reports that OSCAR Workforce helps staff retrieve information and query data faster, without a measured comparison. Easier access for residents remains an intended benefit.", "editor_note": "" } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported and intended benefits" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The council reports that OSCAR Workforce helps staff find information and query data faster, but supplies no measured comparison or independently evaluated organizational result." }, { "group": "personal", "reason": "The resident-facing system is intended to simplify access to council services. The retained sources supply no measured resident outcome." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "source_collection": "LGA AI case-study bank", "source_entry": "LGA-023" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "source_collection", "source_entry" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "scaled", "date": "2026-10-21", "note": "Peterborough reports that the internal OSCAR Workforce tool is live. No rollout date, usage count, or measured time saving is supplied, and resident-facing benefits remain unverified.", "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders" } } }, "provenance": { "kind": "source_review", "basis": "The council’s October 21 announcement reports that OSCAR Workforce is now live. This is a first-party rollout claim, not an independent evaluation.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0559-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0559" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Peterborough’s May 13, 2026 LGA case study describes OSCAR as a proof of concept for connecting council assistants through a shared service interface. Datnexa identifies itself as the development partner and describes AI that interprets requests and routes them to specialist services. On October 21, the council reported that OSCAR Workforce was live and helped staff find emails and documents and query data faster. It did not publish timings, user counts, or a comparative evaluation. The resident-facing accessibility benefits remain intended. A separate council contract identifies Datnexa as the supplier for Workforce design and scoping. That contract establishes procurement, not a measured benefit.", "benefit_type": "Improved Accessibility" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "The council reports that OSCAR Workforce helps staff find information and query data faster, but supplies no measured comparison or independently evaluated organizational result." }, { "group": "personal", "reason": "The resident-facing system is intended to simplify access to council services. The retained sources supply no measured resident outcome." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].status": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_status": "mixed" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "benefit_status" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Connect service-specific assistants through a shared, governed digital front door." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "United Kingdom" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Connect service-specific assistants through a shared, governed digital front door." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-05-13", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "source": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "May 13, 2026 is the LGA account’s publication date. Datnexa’s source HTML identifies July 9, 2026 in datePublished and dateModified, despite the search index’s misleading relative age. October 21 is the council follow-up publication, not a replacement for the original chronology. The Workforce contract’s award date is not its publication date.", "record_fields": [ "date_observed", "date_basis", "date_precision", "revisions" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The framework is designed for web, WhatsApp, and voice channels and for connection to existing services.", "The reported design includes centralized permissions, redaction, guardrails, and audit logging." ], "must_hold": [ "Specialist services and information sources must be available for the routing system to use", "Human staff must retain responsibility for the decisions that the system is not authorized to make", "Access controls and records of system actions must work in the deployment, rather than merely being described in the design" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "source": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Local-government service orchestration" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "access": "complete case-study text read through web retrieval; direct curl returned a browser challenge" }, { "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "access": "complete original council article read" }, { "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "access": "complete developer article and its source HTML metadata read", "version": "datePublished 2026-07-09T09:34:54.000Z" }, { "url": "https://procontract.due-north.com/ContractsRegister/ViewContractDetails?contractId=3fafb2cc-33a1-f111-813c-005056b64545", "access": "complete public contract entry read, including description, supplier, dates, amounts, and no-attachments statement" }, { "url": "https://www.youtube.com/watch?v=vd19C_1O0GI", "access": "fetch throttled; video not watched" } ] } }, "provenance": { "kind": "source_review", "basis": "Recorded inspected written versions and the inaccessible linked video.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The LGA account, council announcement, developer article, and public contract entry are available. The contract contains no attachments. The developer’s video was inaccessible.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Peterborough City Council project account, “OSCAR — Orchestrated Service & Citizen AI Router,” Local Government Association, May 13, 2026, “The solution” and “Strategic Roadmap: Scaling OSCAR.”", "title": "OSCAR — Orchestrated Service & Citizen AI Router", "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "date": "2026-05-13", "written_by": "deployer" }, { "kind": "press release", "citation": "Peterborough City Council, “Council staff member heralded as one of the country’s top AI leaders,” October 21, 2026, paragraph beginning “The council’s OSCAR workforce tool…”", "title": "Council staff member heralded as one of the country's top AI leaders", "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "date": "2026-10-21", "written_by": "deployer" }, { "kind": "press release", "citation": "Datnexa HQ, “OSCAR: Building an AI front door with, not just for, local government,” July 9, 2026, “What OSCAR actually is” and “Built with governance from day one.”", "title": "OSCAR: Building an AI front door with, not just for, local government", "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "date": "2026-07-09", "written_by": "makers" }, { "kind": "other", "citation": "Peterborough City Council, contract register, “Oscar Workforce AI Assistant,” reference DN827472; award dated October 5, 2026, description and awarded supplier fields. 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Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0559-source-0001" ], "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "published_on": "2026-05-13", "relationship": "Original council/project case account hosted by LGA. It gives the architecture and proof-of-concept roadmap, without an independent evaluation." }, { "source_refs": [ "AIBD-0559-source-0002" ], "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "published_on": "2026-10-21", "relationship": "Original council announcement adds reported live Workforce use and examples of staff tasks. This is a deployer claim, without quantified results." }, { "source_refs": [ "AIBD-0559-source-0003" ], "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "published_on": "2026-07-09", "relationship": "Original developer explanation identifies the development partnership, routing workflow, and intended limits on autonomous decisions." }, { "source_refs": [ "AIBD-0559-source-0004" ], "url": "https://procontract.due-north.com/ContractsRegister/ViewContractDetails?contractId=3fafb2cc-33a1-f111-813c-005056b64545", "relationship": "The council’s public procurement record independently establishes its supplier and scoping contract. Buyer documentation does not evaluate the tool’s benefit." } ], "excluded_republications": [ { "url": "https://www.datnexa.com/post/the-oscar-reviews-are-in", "relationship": "Read in full. The developer characterizes the LGA entry as validation, but supplies no evaluation. It repeats the LGA architecture and is not separate corroboration." }, { "url": "https://www.datnexa.com/oscarlocalgovai", "relationship": "Read in full. The current product page reiterates the intended routing architecture and links back to the same LGA case study, without measured results." } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0559-source-0001", "retained_source_order": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "ordering_basis": "The original council case account leads. The next sources add a later deployment claim, identified development partnership and decision boundaries, and procurement evidence. All remain distinct from independent outcome verification.", "claim_lineage": [ { "claim": "OSCAR was a proof of concept for a shared resident-facing service interface in May 2026.", "source_ref": "AIBD-0559-source-0001", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "locator": "“The solution” and “Strategic Roadmap: Scaling OSCAR,” especially the opening roadmap paragraph", "role": "Original council/project account" } ], "method": { "stage": "proof of concept" }, "limitations": [ "Architectural and governance claims are descriptions, not demonstrated reliability or accessibility results." ] }, { "claim": "Datnexa is the development partner, and describes interpretation, routing, and human decision boundaries.", "source_ref": "AIBD-0559-source-0003", "source_chain": [ { "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "locator": "Opening partnership paragraph, “What OSCAR actually is,” and “Built with governance from day one”", "role": "Developer’s own account" } ], "method": {}, "limitations": [ "No named foundation model, model version, source code, test protocol, or measured effect is supplied." ] }, { "claim": "OSCAR Workforce was live and reportedly helped staff find emails/documents and query data faster by October 21.", "source_ref": "AIBD-0559-source-0002", "source_chain": [ { "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "locator": "Paragraph beginning “The council’s OSCAR workforce tool is also now live”", "role": "Original deployer follow-up" } ], "method": { "reported_tasks": [ "finding emails", "finding documents", "querying data" ] }, "limitations": [ "No rollout date, timing study, usage denominator, user sample, or independent comparison is supplied.", "Document translation and PDF editing/redaction are described as future functions." ] }, { "claim": "Peterborough awarded Datnexa £21,250 for OSCAR Workforce design and scoping.", "source_ref": "AIBD-0559-source-0004", "source_chain": [ { "url": "https://procontract.due-north.com/ContractsRegister/ViewContractDetails?contractId=3fafb2cc-33a1-f111-813c-005056b64545", "locator": "Description; reference DN827472; awarded date; awarded value; awarded supplier", "role": "Original buyer procurement record" } ], "method": { "award_date": "2026-10-05", "awarded_value_gbp": 21250, "estimated_total_value_gbp": 25500 }, "limitations": [ "This is procurement expenditure, not value created or a realized saving.", "The record lists a 2027 end date alongside a two-month contract period. That inconsistency is not silently reconciled.", "The scoping description and subsequent live-tool announcement do not establish which component or version was delivered under this contract." ] } ], "limitations": [ "The LGA case study has no linked experiment, results dataset, footnotes, appendices, or supplementary evidence for its projected benefits.", "The original LGA account, developer explanation, and later council announcement are interested-party sources. None independently evaluates resident or staff outcomes.", "The developer’s embedded YouTube video at https://www.youtube.com/watch?v=vd19C_1O0GI could not be fetched and was not watched. No claim relies on its unseen content.", "The contract supplies no public attachments. Its date inconsistency and relationship to the live Workforce release remain unresolved.", "Benefits reported for Hey Geraldine, Bridgit, or other Peterborough tools are not transferred to OSCAR." ], "access_audit": [ { "url": "https://www.local.gov.uk/case-studies/oscar-orchestrated-service-citizen-ai-router", "access": "complete case-study text read through web retrieval; direct curl returned a browser challenge" }, { "url": "https://www.peterborough.gov.uk/engagement-hub/council-staff-member-heralded-as-one-of-the-countrys-top-ai-leaders", "access": "complete original council article read" }, { "url": "https://www.datnexa.com/post/oscar-building-an-ai-front-door-with-not-just-for-local-government", "access": "complete developer article and its source HTML metadata read", "version": "datePublished 2026-07-09T09:34:54.000Z" }, { "url": "https://procontract.due-north.com/ContractsRegister/ViewContractDetails?contractId=3fafb2cc-33a1-f111-813c-005056b64545", "access": "complete public contract entry read, including description, supplier, dates, amounts, and no-attachments statement" }, { "url": "https://www.youtube.com/watch?v=vd19C_1O0GI", "access": "fetch throttled; video not watched" } ], "scope": "Complete review of retained-source lineage and documented access. Unavailable video content and unavailable evaluation data are not represented as inspected." } }, "provenance": { "kind": "source_review", "basis": "Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The council and developer describe OSCAR without publishing an evaluation of staff or resident outcomes. The developer’s video was inaccessible. The contract’s date and connection to OSCAR Workforce remain unresolved.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Peterborough and Datnexa are developing OSCAR to connect council services. The council reports that OSCAR Workforce is live, but has not supplied measured results.", "account": "Peterborough’s May 13, 2026 LGA case study describes OSCAR as a proof of concept for connecting council assistants through a shared service interface. Datnexa identifies itself as the development partner and describes AI that interprets requests and routes them to specialist services. On October 21, the council reported that OSCAR Workforce was live and helped staff find emails and documents and query data faster. It did not publish timings, user counts, or a comparative evaluation. The resident-facing accessibility benefits remain intended. A separate council contract identifies Datnexa as the supplier for Workforce design and scoping. That contract establishes procurement, not a measured benefit." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "OSCAR, the Orchestrated Service & Citizen AI Router, and OSCAR Workforce" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "OSCAR and OSCAR Workforce", "editor_note": "" } }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Datnexa and Peterborough City Council" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OSCAR: Orchestrated Service & Citizen AI Router", "headline": "Peterborough develops OSCAR to connect council AI services" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "93564829de6b05bff61f6216bddc47315b330fd21a5cefd8e73ca7ab7111ed40" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the reviewed case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Peterborough’s May 13, 2026 LGA case study describes OSCAR as a proof of concept for connecting council assistants through a shared service interface. Datnexa identifies itself as the development partner and describes AI that interprets requests and routes them to specialist services. On October 21, the council reported that OSCAR Workforce was live and helped staff find emails and documents and query data faster. It did not publish timings, user counts, or a comparative evaluation. The resident-facing accessibility benefits remain intended. A separate council contract identifies Datnexa as the supplier for Workforce design and scoping. That contract establishes procurement, not a measured benefit.", "replication": { "produced_by": [ "The framework is designed for web, WhatsApp, and voice channels and for connection to existing services.", "The reported design includes centralized permissions, redaction, guardrails, and audit logging." ], "must_hold": [ "Specialist services and information sources must be available for the routing system to use", "Human staff must retain responsibility for the decisions that the system is not authorized to make", "Access controls and records of system actions must work in the deployment, rather than merely being described in the design" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the original-source review. Traced the LGA account to additional original developer, council, and procurement records. Identified Datnexa and the council’s reported Workforce rollout, while distinguishing intended resident benefits and unmeasured efficiency claims.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0559-source-0001", "AIBD-0559-source-0002", "AIBD-0559-source-0003", "AIBD-0559-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "OSCAR is designed to receive requests through the web, WhatsApp, and voice and route them to council services. The design includes permissions, redaction, safeguards, and logs of system actions.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 20, "record_mapped": 11, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0257", "title": "Greece's transport ministry presents an AI system to transcribe stationmaster-driver GSM-R dialogues in real time and check them against protocols", "summary": "In a SKAI interview, Greece’s transport minister described AI transcription of GSM-R conversations and checks against railway communication protocols; no measured safety result was given.", "date_observed": "2026-05-18", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In a SKAI interview reported on May 18, 2026, Deputy Minister of Transport Konstantinos Kyranakis described an AI system that transcribes GSM-R communications between stationmasters and train drivers. He said that it would identify departures from railway communication protocols so that the control center could intervene. He said that the system had been presented the previous Saturday. 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Human specialists verify them before alerts reach mariners. IEEE Spectrum adds an early detection count and the developer’s explanation of why human review remains necessary. Bay Nature independently observed the Coast Guard workflow. Neither report independently estimates the system’s effect on whale survival." }, "evidence": [ { "kind": "press release", "citation": "Sonia Fernandez, “New AI system uses cameras and thermal sensors to steer ships clear of gray whales in the San Francisco Bay,” UC Santa Barbara, May 19, 2026.", "title": "New AI system uses cameras and thermal sensors to steer ships clear of gray whales in the San Francisco Bay", "url": "https://news.ucsb.edu/2026/022586/new-ai-system-uses-cameras-and-thermal-sensors-steer-ships-clear-gray-whales-san", "date": "2026-05-19", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Katherine Bourzac, “Thermal Cameras and AI Help Ships Steer Clear of Gray Whales,” IEEE Spectrum, May 26, 2026; reporting at the May 19 launch and interviews with the project team.", "title": "Thermal Cameras and AI Help Ships Steer Clear of Gray Whales", "url": "https://spectrum.ieee.org/whales-ai-thermal-camera-tracking", "date": "2026-05-26", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Tanvi Dutta Gupta, “Saving the Whales Just Got a Little Easier,” Bay Nature, July 2, 2026; June visit to the Coast Guard’s Vessel Traffic Service and interviews with operators and an outside whale-protection specialist.", "title": "Saving the Whales Just Got a Little Easier", "url": "https://baynature.org/2026/07/02/science-nature/urban-nature/saving-the-whales-just-got-a-little-easier/", "date": "2026-07-02", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A fixed vantage point over a whale-vessel overlap hotspot", "Thermal cameras able to see blows at several nautical miles", "Human review of each AI detection before alerting", "A Vessel Traffic Service willing to relay alerts by radio" ], "must_hold": [ "Whales continue to enter the bay in the detection footprint", "Mariners and ferry operators act on posted detections", "Funding sustains camera nodes and specialist review" ], "echoes": [ { "date": "2023-12-27", "setting": "Acoustic LFDCS detection by a WHOI/NOAA glider triggering a voluntary Right Whale Slow Zone east of Portland, Maine (AIBD-0036)", "model_version": null, "outcome": "recurred", "source": "https://content.govdelivery.com/accounts/USNOAAFISHERIES/bulletins/3824b02" } ] }, "paired_incident": null, "headline": "WhaleSpotter thermal AI starts whale alerts in San Francisco Bay", "metric": null, "comparator": null, "later": { "status": "unknown", "date": "2026-07-02", "note": "Bay Nature reported that the ferry camera had been installed and that Vessel Traffic Service operators were using Whale Safe. No comparative strike outcome was reported.", "quote": null, "url": "https://baynature.org/2026/07/02/science-nature/urban-nature/saving-the-whales-just-got-a-little-easier/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://spectrum.ieee.org/whales-ai-thermal-camera-tracking", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.whalespotter.com/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced the May 21 UC republication with UCSB’s May 19 original. 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Replaced the May 21 UC republication with UCSB’s May 19 original. 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The 6,600 count is a project-reported detection count, not a count of unique animals or prevented strikes." }, { "source_refs": [ "AIBD-0252-source-0003" ], "url": "https://baynature.org/2026/07/02/science-nature/urban-nature/saving-the-whales-just-got-a-little-easier/", "title": "Saving the Whales Just Got a Little Easier", "published_on": "2026-07-02", "relationship": "Bay Nature adds a separate reporting visit to Vessel Traffic Service, later deployment details, and an outside specialist’s caution that captains must act on alerts." } ], "excluded_republications": [ { "url": "https://www.universityofcalifornia.edu/news/new-ai-system-uses-cameras-and-thermal-sensors-steer-ships-clear-gray-whales-san-francisco-bay", "citation": "Fernandez S (21 May 2026). New AI system uses cameras and thermal sensors to steer ships clear of gray whales in the San Francisco Bay. UC Santa Barbara / University of California News.", "relationship": "The UC network page republishes UCSB; OECD is a discovery label. Mongabay did not supply a verified additional contribution beyond the retained accounts in this review. The live Whale Safe zero-count snapshot does not measure effectiveness." }, { "url": "https://news.mongabay.com/2026/06/pilot-project-in-san-francisco-bay-aims-to-help-ships-avoid-gray-whales/", "citation": "Brown D (4 Jun 2026). Pilot project in San Francisco Bay aims to help ships avoid gray whales. Mongabay.", "relationship": "The UC network page republishes UCSB; OECD is a discovery label. Mongabay did not supply a verified additional contribution beyond the retained accounts in this review. The live Whale Safe zero-count snapshot does not measure effectiveness." }, { "url": "https://whalesafe.com/", "citation": "Whale Safe (Benioff Ocean Science Laboratory), homepage San Francisco Bay data card as viewed 20 Oct 2026.", "relationship": "The UC network page republishes UCSB; OECD is a discovery label. Mongabay did not supply a verified additional contribution beyond the retained accounts in this review. The live Whale Safe zero-count snapshot does not measure effectiveness." }, { "url": "https://oecd.ai/en/incidents/2026-05-20-8989", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-05-20-8989: AI System Deployed to Prevent Whale-Ship Collisions in San Francisco Bay.", "relationship": "The UC network page republishes UCSB; OECD is a discovery label. Mongabay did not supply a verified additional contribution beyond the retained accounts in this review. The live Whale Safe zero-count snapshot does not measure effectiveness." } ], "lead_source_ref": "AIBD-0252-source-0001", "retained_source_order": [ "AIBD-0252-source-0001", "AIBD-0252-source-0002", "AIBD-0252-source-0003" ], "ordering_basis": "The first source directly supports the reported benefit or is the closest accessible original account. Each additional source has a distinct evidentiary contribution described in its relationship. Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "The Angel Island system combines thermal AI detection, human confirmation, Whale Safe mapping, and Coast Guard radio warnings.", "source_ref": "AIBD-0252-source-0001", "source_chain": [ { "url": "https://news.ucsb.edu/2026/022586/new-ai-system-uses-cameras-and-thermal-sensors-steer-ships-clear-gray-whales-san", "locator": "“Tracking hungry gray whales,” paragraphs 1–4; installation and ferry paragraphs", "role": "UCSB is the original institutional publisher and a project participant, not an independent evaluator." } ], "locator": "“Tracking hungry gray whales,” paragraphs 1–4; installation and ferry paragraphs", "method": {}, "limitations": [ "The release’s predicted life-saving effect is not a measured result." ] }, { "claim": "The system logged 6,600 detections by the May 19 launch after about a week and a half of operation.", "source_ref": "AIBD-0252-source-0002", "source_chain": [ { "url": "https://spectrum.ieee.org/whales-ai-thermal-camera-tracking", "locator": "“AI Thermal Cameras Detect Whale Spouts,” paragraph beginning “The San Francisco Bay system…”", "role": "IEEE Spectrum’s reporter attended the launch and interviewed participants. The 6,600 count is a project-reported detection count, not a count of unique animals or prevented strikes." } ], "locator": "“AI Thermal Cameras Detect Whale Spouts,” paragraph beginning “The San Francisco Bay system…”", "method": { "unit": "detections", "window": "about a week and a half to May 19, 2026" }, "limitations": [ "Repeated sightings may concern only a few whales.", "The underlying detection log is not supplied." ] }, { "claim": "Vessel Traffic Service was using the display and radio warnings; a second camera was installed on Lyra.", "source_ref": "AIBD-0252-source-0003", "source_chain": [ { "url": "https://baynature.org/2026/07/02/science-nature/urban-nature/saving-the-whales-just-got-a-little-easier/", "locator": "Opening VTS visit and paragraphs beginning “With funding…” and “Silber…”", "role": "Bay Nature adds a separate reporting visit to Vessel Traffic Service, later deployment details, and an outside specialist’s caution that captains must act on alerts." } ], "locator": "Opening VTS visit and paragraphs beginning “With funding…” and “Silber…”", "method": {}, "limitations": [ "Operational reporting is not a controlled evaluation of strikes or whale mortality." ] } ], "limitations": [ "No independently evaluated reduction in strikes is reported.", "The 2020 infrared-camera study cited by IEEE was identified at https://www.sciencedirect.com/science/article/pii/S0025326X20301442 but its publisher returned 403. Its false-positive findings are not substituted for performance of this installation.", "Whale Safe’s one-day zero count is a volatile display snapshot, not a finding of no benefit." ], "access_audit": [ { "url": "https://news.ucsb.edu/2026/022586/new-ai-system-uses-cameras-and-thermal-sensors-steer-ships-clear-gray-whales-san", "access": "full HTML and original printable PDF read", "alternate": "https://news.ucsb.edu/print/pdf/node/22586" }, { "url": "https://spectrum.ieee.org/whales-ai-thermal-camera-tracking", "access": "full article read" }, { "url": "https://baynature.org/2026/07/02/science-nature/urban-nature/saving-the-whales-just-got-a-little-easier/", "access": "full article read" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified.", "contextual_comparisons": [ { "url": "https://spectrum.ieee.org/whales-ai-thermal-camera-tracking", "locator": "AI Thermal Cameras Detect Whale Spouts, paragraph beginning “WhaleSpotter’s systems are already in use”.", "finding": "IEEE Spectrum attributes a general 90% reduction in ship-strike risk to WhaleSpotter, without a supporting study or calculation. It is not a measured comparison for the San Francisco Bay installation.", "use": "Context only; no case-specific comparison established." } ] } }, "provenance": { "kind": "source_review", "basis": "Replaced the May 21 UC republication with UCSB’s May 19 original. Preserved independent deployment reporting and corrected the assertion that no detection counts or operational use had been published. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0252-source-0001", "AIBD-0252-source-0002", "AIBD-0252-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Independent reporting documents installation and Coast Guard use. It gives no measured reduction in whale strikes. An earlier infrared-camera study was identified but inaccessible, so its results are not attributed to this installation.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "WhaleSpotter’s thermal AI and human review feed whale alerts to San Francisco Bay mariners; independent reporters documented deployment and Coast Guard use, without a measured decline in strikes.", "account": "UC Santa Barbara announced the San Francisco Bay WhaleSpotter system on May 19, 2026. Its first thermal camera was on Angel Island. AI flags whale heat signatures, a marine-mammal specialist checks them, and confirmed detections appear on Whale Safe for mariners and the Coast Guard’s Vessel Traffic Service. IEEE Spectrum attended the launch and reported that the system had logged 6,600 detections in about a week and a half. These were repeated detections, not 6,600 individual whales. Bay Nature later visited the traffic service and described its dedicated Whale Safe screen, near-daily detections, radio guidance to captains, and a second camera on the ferry Lyra. That reporting establishes operational use. The sources do not measure a reduction in strikes or link a particular alert to a documented avoided collision." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced the May 21 UC republication with UCSB’s May 19 original. Preserved independent deployment reporting and corrected the assertion that no detection counts or operational use had been published.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0252-source-0001", "AIBD-0252-source-0002", "AIBD-0252-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "WhaleSpotter detected whales in thermal images, and human reviewers passed alerts to mariners. Independent reporters documented Coast Guard use but no measured decline in strikes.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "FLIR thermal cameras with WhaleSpotter AI detection, human verification and Whale Safe alert mapping" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "WhaleSpotter (detection AI) with UC Santa Barbara's Benioff Ocean Science Laboratory" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "WhaleSpotter thermal-camera AI on a Coast Guard station at Angel Island starts alerting San Francisco Bay mariners and the Vessel Traffic Service to gray whales", "headline": "WhaleSpotter thermal AI starts whale alerts in San Francisco Bay" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "0a0a7b9f5b7bad1645389fcfc496542a26e17132d5f83b0e7ae88060827b1f96" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "UC Santa Barbara announced the San Francisco Bay WhaleSpotter system on May 19, 2026. Its first thermal camera was on Angel Island. AI flags whale heat signatures, a marine-mammal specialist checks them, and confirmed detections appear on Whale Safe for mariners and the Coast Guard’s Vessel Traffic Service. IEEE Spectrum attended the launch and reported that the system had logged 6,600 detections in about a week and a half. These were repeated detections, not 6,600 individual whales. Bay Nature later visited the traffic service and described its dedicated Whale Safe screen, near-daily detections, radio guidance to captains, and a second camera on the ferry Lyra. That reporting establishes operational use. The sources do not measure a reduction in strikes or link a particular alert to a documented avoided collision.", "replication": { "produced_by": [ "A fixed vantage point over a whale-vessel overlap hotspot", "Thermal cameras able to see blows at several nautical miles", "Human review of each AI detection before alerting", "A Vessel Traffic Service willing to relay alerts by radio" ], "must_hold": [ "Whales continue to enter the bay in the detection footprint", "Mariners and ferry operators act on posted detections", "Funding sustains camera nodes and specialist review" ], "echoes": [ { "date": "2023-12-27", "setting": "Acoustic LFDCS detection by a WHOI/NOAA glider triggering a voluntary Right Whale Slow Zone east of Portland, Maine (AIBD-0036)", "outcome": "recurred", "source": "https://content.govdelivery.com/accounts/USNOAAFISHERIES/bulletins/3824b02" } ] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced the May 21 UC republication with UCSB’s May 19 original. Preserved independent deployment reporting and corrected the assertion that no detection counts or operational use had been published.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0252-source-0001", "AIBD-0252-source-0002", "AIBD-0252-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Thermal cameras observed an area used by whales and vessels. People reviewed each AI detection before Vessel Traffic Service operators relayed alerts by radio.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 15, "record_mapped": 14, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0300", "title": "Apple Watch Series 11 breathing-disturbance notifications send a 79-year-old to his cardiologist; morning watch ECGs show AF after “elevated” nights and CPAP starts without polysomnography", "summary": "Fukuoka case (Cureus, 26 May 2026): sleep-apnoea notifications prompted consultation; watch ECGs showed AF only after “elevated” breathing-disturbance nights; CPAP under way, no polysomnography.", "date_observed": "2026-05-26", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Maruyama (Haradoi Hospital, Fukuoka), Hieda and Fukata reported a case in Cureus on 26 May 2026. The consultation is undated. The patient is a 79-year-old Japanese man with hypertension, dyslipidemia, type 2 diabetes and symptomatic paroxysmal atrial fibrillation (AF). A 12-lead electrocardiogram (ECG) had documented it a decade earlier. After retirement no paroxysms were documented by ambulatory or standard ECG, and pulsed-field ablation was deferred. Some months after he began wearing an Apple Watch Series 11 paired with an iPhone 15 Pro, he consulted the authors. He asked about notifications of nocturnal “respiratory disturbance”. He activated the watch ECG every morning and evening. AF paroxysms were detected repeatedly on mornings after nights the watch rated breathing disturbance “elevated”. They were not detected after “not elevated” nights, and they terminated by evening. He is undergoing CPAP therapy, and pulsed-field ablation will be considered depending on its effect on the paroxysms. No polysomnography was performed. The authors state that watch-detected breathing disturbance is not equivalent to the apnea-hypopnea index. They state that the watch ECG cannot fully substitute for conventional ECG, and that the notification algorithm “was reportedly developed using advanced machine learning”. The Food and Drug Administration (FDA) cleared Apple's Sleep Apnea Notification Feature under 510(k) K240929 on 13 September 2024. Apple's 510(k) submission says that it uses a deep learning algorithm on Apple Watch accelerometer data, analyzed in 30-day windows. It was trained on over 11,000 nights with polysomnography or home sleep-test reference. No treatment outcome is reported.", "category": "benefit created", "unexpected": false, "purpose": "The notification feature is built to identify patterns of breathing disturbance suggestive of moderate-to-severe sleep apnea and tell the user. The ECG app is built to record and classify single-lead rhythm. Both were used as designed.", "system": "Apple Watch Sleep Apnea Notification Feature (breathing-disturbance notifications) and the ECG app", "model_version": "Apple Watch Series 11 with iPhone 15 Pro", "developer": "Apple", "deployer": null, "location": "Fukuoka, Japan", "domain": "Healthcare (cardiology; sleep medicine)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 1, "reason": "A man whose AF was thought quiescent learned that paroxysms recur after disturbed-breathing nights, and he started CPAP. No confirmed sleep-apnea diagnosis and no treatment effect are reported." } ], "ai_role": { "status": "assessed", "statement": "The notification feature's deep-learning model, described in Apple's submission to FDA, flagged elevated breathing disturbance and brought the patient to the clinic. His own morning ECG recordings, read by the authors, showed the AF paroxysms. The paper does not state separately what the ECG app's classifier reported. Clinicians chose CPAP and deferred ablation. The treating authors report the clinical episode. Apple supplies the technical description and validation in its 510(k) summary. FDA's clearance is a separate regulatory decision and does not verify this patient's benefit." }, "evidence": [ { "kind": "case report", "citation": "Maruyama T, Hieda M, Fukata M (2026). Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report. Cureus 18(5):e109701 (PMC13301138). Case Presentation, Figure 2, Discussion, and references 12–14.", "title": "Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "date": "2026-05-26", "written_by": "independent", "quote": "the smartwatch repeatedly detected AF paroxysms the following morning, only after the smartwatch had issued a breathing-disturbance notification during sleep." }, { "kind": "regulatory document", "citation": "Apple Inc. (2024). Sleep Apnea Notification Feature: 510(k) Summary, K240929, device description and performance testing, pp. 2 and 5–7, filed with the FDA. File includes FDA's September 13, 2024 substantial-equivalence letter.", "title": "510(k) Summary K240929: Sleep Apnea Notification Feature (SANF)", "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf", "date": "2024-09-13", "written_by": "makers", "quote": "SANF includes a deep learning algorithm to identify breathing disturbances using accelerometer sensor data from Apple Watch." } ], "replication": { "produced_by": [ "Nightly watch wear with the sleep-apnea notification feature active, plus the owner's habit of recording a watch ECG every morning and evening", "A known history of paroxysmal AF that made the morning traces interpretable to his cardiologists", "Access to a clinic willing to act on watch data (CPAP started without polysomnography)" ], "must_hold": [ "The user completes onboarding and wears the watch during sleep, since the feature evaluates 30-day windows opportunistically", "Clinicians confirm with conventional ECG and polysomnography, which the authors say the watch cannot replace and which was not done here" ], "echoes": [] }, "paired_incident": null, "headline": "Apple Watch breathing alerts send a 79-year-old to CPAP therapy", "metric": null, "comparator": { "against": "ambulatory monitoring and standard 12-lead ECG, which had documented no paroxysms since his retirement", "before": "AF paroxysms were not documented by ambulatory monitoring or standard ECG", "after": "AF paroxysms were detected repeatedly in the morning after notification of nocturnal “elevated” breathing disturbance, but not in the morning after nights when breathing disturbance was “not elevated”", "basis": "measured", "quote": "AF paroxysms were not documented by ambulatory monitoring or standard ECG (Figure 1B), and we deferred pulsed-field ablation for his AF paroxysms.", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/" }, "later": { "status": "unknown", "date": null, "note": "The May 2026 report says CPAP therapy is under way and ablation will depend on its effect; no later outcome was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Apple_Inc.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated three excerpts of the clinical report and two excerpts of the 510(k) file into two sources. Followed the case's technical references to Apple's original white paper and submission. Corrected the prose to identify that the FDA-hosted technical summary was written by Apple. Preserved that CPAP began but no treatment outcome or polysomnographic confirmation was reported.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report and the makers' regulatory document. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0300", "catalog_version": "1.0.0", "source_fingerprint": "3c00ba05fd9e3361ace72306c00b7428276417fec489bdf1bb70cf22ba9853cd", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The notification feature's deep-learning model, described in Apple's submission to FDA, flagged elevated breathing disturbance and brought the patient to the clinic. His own morning ECG recordings, read by the authors, showed the AF paroxysms. The paper does not state separately what the ECG app's classifier reported. Clinicians chose CPAP and deferred ablation. The treating authors report the clinical episode. Apple supplies the technical description and validation in its 510(k) summary. FDA's clearance is a separate regulatory decision and does not verify this patient's benefit." } } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Sleep-apnea notifications prompted the patient to seek care. Clinicians interpreted his morning ECG recordings and chose CPAP treatment. The report does not separately identify an ECG classifier’s contribution or provide a treatment outcome.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The notification feature's deep-learning model, described in Apple's submission to FDA, flagged elevated breathing disturbance and brought the patient to the clinic. His own morning ECG recordings, read by the authors, showed the AF paroxysms. The paper does not state separately what the ECG app's classifier reported. Clinicians chose CPAP and deferred ablation. The treating authors report the clinical episode. Apple supplies the technical description and validation in its 510(k) summary. 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"value_present", "value": { "kind": "record_fields", "fields": { "account": "Maruyama (Haradoi Hospital, Fukuoka), Hieda and Fukata reported a case in Cureus on 26 May 2026. The consultation is undated. The patient is a 79-year-old Japanese man with hypertension, dyslipidemia, type 2 diabetes and symptomatic paroxysmal atrial fibrillation (AF). A 12-lead electrocardiogram (ECG) had documented it a decade earlier. After retirement no paroxysms were documented by ambulatory or standard ECG, and pulsed-field ablation was deferred. Some months after he began wearing an Apple Watch Series 11 paired with an iPhone 15 Pro, he consulted the authors. He asked about notifications of nocturnal “respiratory disturbance”. He activated the watch ECG every morning and evening. AF paroxysms were detected repeatedly on mornings after nights the watch rated breathing disturbance “elevated”. They were not detected after “not elevated” nights, and they terminated by evening. He is undergoing CPAP therapy, and pulsed-field ablation will be considered depending on its effect on the paroxysms. No polysomnography was performed. The authors state that watch-detected breathing disturbance is not equivalent to the apnea-hypopnea index. They state that the watch ECG cannot fully substitute for conventional ECG, and that the notification algorithm “was reportedly developed using advanced machine learning”. The Food and Drug Administration (FDA) cleared Apple's Sleep Apnea Notification Feature under 510(k) K240929 on 13 September 2024. Apple's 510(k) submission says that it uses a deep learning algorithm on Apple Watch accelerometer data, analyzed in 30-day windows. It was trained on over 11,000 nights with polysomnography or home sleep-test reference. No treatment outcome is reported.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. 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No confirmed sleep-apnea diagnosis and no treatment effect are reported." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The notification feature is built to identify patterns of breathing disturbance suggestive of moderate-to-severe sleep apnea and tell the user. The ECG app is built to record and classify single-lead rhythm. Both were used as designed." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Fukuoka, Japan", "developer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The notification feature is built to identify patterns of breathing disturbance suggestive of moderate-to-severe sleep apnea and tell the user. 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Nightly breathing-disturbance ratings differ from the feature’s 30-day notification. Apple’s underlying training and validation records are not public.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Maruyama T, Hieda M, Fukata M (2026). Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report. Cureus 18(5):e109701 (PMC13301138). Case Presentation, Figure 2, Discussion, and references 12–14.", "title": "Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "date": "2026-05-26", "written_by": "independent", "quote": "the smartwatch repeatedly detected AF paroxysms the following morning, only after the smartwatch had issued a breathing-disturbance notification during sleep." }, { "kind": "regulatory document", "citation": "Apple Inc. (2024). Sleep Apnea Notification Feature: 510(k) Summary, K240929, device description and performance testing, pp. 2 and 5–7, filed with the FDA. 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Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report. Cureus 18(5):e109701 (PMC13301138). Case Presentation, Figure 2, Discussion, and references 12–14.", "title": "Smartwatch-Detected Atrial Fibrillation on the Morning After a Nocturnal Sleep-Disordered Breathing Notification: A Case Report", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "date": "2026-05-26", "written_by": "independent", "quote": "the smartwatch repeatedly detected AF paroxysms the following morning, only after the smartwatch had issued a breathing-disturbance notification during sleep." }, { "kind": "regulatory document", "citation": "Apple Inc. (2024). Sleep Apnea Notification Feature: 510(k) Summary, K240929, device description and performance testing, pp. 2 and 5–7, filed with the FDA. File includes FDA's September 13, 2024 substantial-equivalence letter.", "title": "510(k) Summary K240929: Sleep Apnea Notification Feature (SANF)", "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf", "date": "2024-09-13", "written_by": "makers", "quote": "SANF includes a deep learning algorithm to identify breathing disturbances using accelerometer sensor data from Apple Watch." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "lead_source_ref": "AIBD-0300-source-0001", "retained_source_order": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "origins": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "contribution": "Original clinical narrative, ECGs and breathing-disturbance chart document consultation and management.", "locator": "Case Presentation; Figure 2; Discussion; references 12–14.", "relationship": "Treating clinical authors report the episode and declare no relevant support or financial relationships.", "source_refs": [ "AIBD-0300-source-0001" ] }, { "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf", "contribution": "Manufacturer specifies the deep-learning model, training and 30-day notification rule; FDA letter establishes clearance.", "locator": "FDA letter pp. 1–3; Apple summary pp. 2 and 5–7.", "relationship": "Mixed file: FDA's decision plus Apple's technical submission. The technical claims are maker-authored.", "source_refs": [ "AIBD-0300-source-0002" ] } ], "claim_chains": [ { "claim": "Patient episode and management", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "Case Presentation and Figure 2" ], "finding": "The clinical authors interpreted the ECGs and chose CPAP. No CPAP response is reported, and no polysomnography confirmed sleep apnea." }, { "claim": "Machine learning and detection method", "path": [ "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "References 12–14", "https://www.apple.com/health/pdf/sleep-apnea/Sleep_Apnea_Notifications_on_Apple_Watch_September_2024.pdf", "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf" ], "finding": "The original white paper and 510(k) summary describe Apple's own development and validation. The paper's references 12 and 13 resolve to the same Apple white paper, not two independent sources." }, { "claim": "Regulatory status", "path": [ "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf", "September 13, 2024 FDA substantial-equivalence letter" ], "finding": "Clearance concerns the product and intended use; it is not confirmation of this clinical outcome." } ], "limitations": [ "The article does not show whether the watch ECG classifier, rather than clinical reading, identified each AF episode.", "No polysomnography, controlled counterfactual, or treatment response is reported.", "Nightly breathing-disturbance categories and the feature's 30-day sleep-apnea notification are related but distinct outputs.", "Apple's underlying training and validation records were not publicly available for independent reproduction." ], "excluded_or_consolidated_sources": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "reason": "Duplicate excerpt of the retained clinical report or technical submission." }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13301138/", "reason": "Duplicate excerpt of the retained clinical report or technical submission." }, { "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240929.pdf", "reason": "Duplicate excerpt of the retained clinical report or technical submission." } ], "review_scope": "Traced the claims in this case through accessible original publications and relevant embedded references, tables, appendices, corrections, and supplements. The stated access limits remain unresolved." } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Treating clinicians report the consultation and ECG findings. Apple’s FDA submission describes the notification algorithm and its validation. FDA’s clearance is a regulatory decision, not confirmation of this patient’s benefit.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Fukuoka case (Cureus, 26 May 2026): sleep-apnoea notifications prompted consultation; watch ECGs showed AF only after “elevated” breathing-disturbance nights; CPAP under way, no polysomnography.", "account": "Maruyama (Haradoi Hospital, Fukuoka), Hieda and Fukata reported a case in Cureus on 26 May 2026. The consultation is undated. The patient is a 79-year-old Japanese man with hypertension, dyslipidemia, type 2 diabetes and symptomatic paroxysmal atrial fibrillation (AF). A 12-lead electrocardiogram (ECG) had documented it a decade earlier. After retirement no paroxysms were documented by ambulatory or standard ECG, and pulsed-field ablation was deferred. Some months after he began wearing an Apple Watch Series 11 paired with an iPhone 15 Pro, he consulted the authors. He asked about notifications of nocturnal “respiratory disturbance”. He activated the watch ECG every morning and evening. AF paroxysms were detected repeatedly on mornings after nights the watch rated breathing disturbance “elevated”. They were not detected after “not elevated” nights, and they terminated by evening. He is undergoing CPAP therapy, and pulsed-field ablation will be considered depending on its effect on the paroxysms. No polysomnography was performed. The authors state that watch-detected breathing disturbance is not equivalent to the apnea-hypopnea index. They state that the watch ECG cannot fully substitute for conventional ECG, and that the notification algorithm “was reportedly developed using advanced machine learning”. The Food and Drug Administration (FDA) cleared Apple's Sleep Apnea Notification Feature under 510(k) K240929 on 13 September 2024. Apple's 510(k) submission says that it uses a deep learning algorithm on Apple Watch accelerometer data, analyzed in 30-day windows. It was trained on over 11,000 nights with polysomnography or home sleep-test reference. No treatment outcome is reported." } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Apple Watch sleep-apnea notifications prompted a consultation. Clinicians found atrial fibrillation in morning ECG recordings after nights with elevated breathing disturbances and began CPAP treatment, without a confirmatory sleep study.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model detected elevated breathing disturbance and generated a notification." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant used an Apple Watch Series 11 with an iPhone 15 Pro." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Apple Watch Series 11 with iPhone 15 Pro" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Apple Watch Sleep Apnea Notification Feature (breathing-disturbance notifications) and the ECG app" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Apple" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Apple Watch Series 11 breathing-disturbance notifications send a 79-year-old to his cardiologist; morning watch ECGs show AF after “elevated” nights and CPAP starts without polysomnography", "headline": "Apple Watch breathing alerts send a 79-year-old to CPAP therapy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "3c00ba05fd9e3361ace72306c00b7428276417fec489bdf1bb70cf22ba9853cd" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Updated the fingerprint after this targeted source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Maruyama (Haradoi Hospital, Fukuoka), Hieda and Fukata reported a case in Cureus on 26 May 2026. The consultation is undated. The patient is a 79-year-old Japanese man with hypertension, dyslipidemia, type 2 diabetes and symptomatic paroxysmal atrial fibrillation (AF). A 12-lead electrocardiogram (ECG) had documented it a decade earlier. After retirement no paroxysms were documented by ambulatory or standard ECG, and pulsed-field ablation was deferred. Some months after he began wearing an Apple Watch Series 11 paired with an iPhone 15 Pro, he consulted the authors. He asked about notifications of nocturnal “respiratory disturbance”. He activated the watch ECG every morning and evening. AF paroxysms were detected repeatedly on mornings after nights the watch rated breathing disturbance “elevated”. They were not detected after “not elevated” nights, and they terminated by evening. He is undergoing CPAP therapy, and pulsed-field ablation will be considered depending on its effect on the paroxysms. No polysomnography was performed. The authors state that watch-detected breathing disturbance is not equivalent to the apnea-hypopnea index. They state that the watch ECG cannot fully substitute for conventional ECG, and that the notification algorithm “was reportedly developed using advanced machine learning”. The Food and Drug Administration (FDA) cleared Apple's Sleep Apnea Notification Feature under 510(k) K240929 on 13 September 2024. Apple's 510(k) submission says that it uses a deep learning algorithm on Apple Watch accelerometer data, analyzed in 30-day windows. It was trained on over 11,000 nights with polysomnography or home sleep-test reference. No treatment outcome is reported.", "replication": { "produced_by": [ "Nightly watch wear with the sleep-apnea notification feature active, plus the owner's habit of recording a watch ECG every morning and evening", "A known history of paroxysmal AF that made the morning traces interpretable to his cardiologists", "Access to a clinic willing to act on watch data (CPAP started without polysomnography)" ], "must_hold": [ "The user completes onboarding and wears the watch during sleep, since the feature evaluates 30-day windows opportunistically", "Clinicians confirm with conventional ECG and polysomnography, which the authors say the watch cannot replace and which was not done here" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0300-source-0001", "AIBD-0300-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 11, "record_mapped": 22, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0260", "title": "OpenAI refers Darren Zhou’s threats to the FBI; local police investigate and he pleads guilty to stalking and threat charges", "summary": "An OpenAI disclosure brought Darren Zhou’s threats to police attention; he pleaded guilty to stalking and threat charges and received probation, GPS monitoring, and contact and weapons restrictions.", "date_observed": "2026-05-29", "date_basis": "event", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Court reporting describes an OpenAI emergency disclosure that reached the Palm Beach County Sheriff’s Office through the FBI after Darren Zhou wrote threats against his ex-girlfriend in ChatGPT. Deputies compared those messages with anonymous threats that she had preserved. The sheriff’s booking entry lists May 29, 2026 as his arrest date. BocaNewsNow reports that he pleaded guilty on August 13 to written threats, aggravated stalking, and unlawful use of a two-way communication device. Adjudication was withheld, with eight years of probation, two years of GPS monitoring, and restrictions on contact and weapons. The accessible reporting cites court documents but does not reproduce the complete affidavit or plea order. It supports a police intervention and court restrictions, rather than proof that an attack would otherwise have occurred.", "category": "protective response", "unexpected": false, "purpose": "OpenAI says that when it detects users planning to harm others, it routes the conversations to a small team trained on its usage policies. It says that if human reviewers find an imminent threat of serious physical harm to others, it may refer the case to law enforcement. This referral is that designed use. ChatGPT itself is a general-purpose assistant, which Zhou used to rehearse his plans.", "system": "ChatGPT (OpenAI), with OpenAI's automated detection and human review pipeline for users planning to harm others", "model_version": null, "developer": "OpenAI", "deployer": "OpenAI", "location": "South Palm Beach, United States", "domain": "Public safety - stalking and threat investigation", "segment": "Consumer chatbot trust-and-safety referral to law enforcement", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-08-15-e71a" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The reported referral led to investigation, arrest, and court restrictions that protected the threatened person. The accessible report describes probation, GPS monitoring, and contact and weapons restrictions. The underlying affidavit and plea order were not directly accessible in this review, and prevention of a future attack remains a counterfactual claim." } ], "ai_role": { "status": "assessed", "statement": "The reporting identifies an OpenAI disclosure as the route that brought Zhou’s messages to police attention. OpenAI’s general policy describes detection followed by human review before possible referral to law enforcement. That policy does not document the exact classifier, trigger, reviewer decisions, or ChatGPT replies in this case." }, "evidence": [ { "kind": "news report", "citation": "Colton A (2026). Man Flagged by ChatGPT Pleads Guilty in Stalking Case. BocaNewsNow.com, 27 August 2026; cites court records.", "title": "Man Flagged by ChatGPT Pleads Guilty in Stalking Case", "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "date": "2026-08-27", "written_by": "independent", "quote": null }, { "kind": "other", "citation": "Palm Beach County Sheriff's Office (2026). Booking Blotter, record for ZHOU, DARREN SHIDA, booking number 2026014226, arresting agency 01-PBSO. Retrieved 20 October 2026 by searching the blotter for last name Zhou between 20 May and 5 June 2026; the search form returns results without a stable record URL. The page rejected access during the October 24 source audit; the earlier record identification is preserved without a fresh verification claim.", "title": "Palm Beach County Sheriff's Office - Booking Blotter", "url": "https://www3.pbso.org/blotter/", "date": "2026-05-29", "written_by": "independent", "quote": null }, { "kind": "news report", "citation": "Moolten S (2026). Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex. South Florida Sun Sentinel, 14 August 2026; cites the PBSO probable cause affidavit and the State Attorney's Office.", "title": "Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex", "url": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "date": "2026-08-14", "written_by": "independent", "quote": null }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. OpenAI blog; Hoodline dates the policy to August 2025.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "date": null, "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ], "replication": { "produced_by": [ "A reported OpenAI emergency disclosure of threatening messages to the FBI", "Referral to local police and comparison with messages that the threatened person had preserved", "Investigation and court restrictions following a guilty plea" ], "must_hold": [ "A disclosure must reach an agency able to investigate", "Investigators must establish identity and assess the threat using supporting evidence", "A general detection-and-review policy does not establish the details of a particular referral", "Arrest and court restrictions do not prove that an attack would otherwise have occurred" ], "echoes": [] }, "paired_incident": null, "headline": "OpenAI refers Darren Zhou's threats to the FBI; he pleads guilty", "metric": "arrest on May 29, 2026; guilty plea on August 13", "comparator": null, "later": { "status": "litigated", "date": "2026-08-13", "note": "Zhou pleaded guilty on 13 August 2026 to written threats to kill, aggravated stalking and misuse of a two-way device, with adjudication withheld and eight years of probation.", "quote": null, "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-08-15-e71a", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "source": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports, one other independent source and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0260", "catalog_version": "1.0.0", "source_fingerprint": "1305768f24ac19a795ee53d018884bb83754966afae529eb2e6116f1de72b313", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The reporting identifies an OpenAI disclosure as the route that brought Zhou’s messages to police attention. OpenAI’s general policy describes detection followed by human review before possible referral to law enforcement. That policy does not document the exact classifier, trigger, reviewer decisions, or ChatGPT replies in this case." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Reporting identifies OpenAI’s disclosure as the route through which police learned of the threats. OpenAI’s general policy describes automated detection followed by human review, but the sources do not identify the classifier or review process used here.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The reporting identifies an OpenAI disclosure as the route that brought Zhou’s messages to police attention. OpenAI’s general policy describes detection followed by human review before possible referral to law enforcement. That policy does not document the exact classifier, trigger, reviewer decisions, or ChatGPT replies in this case." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. 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The police blotter and court portal rejected access, so the underlying filings were not inspected.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Colton A (2026). Man Flagged by ChatGPT Pleads Guilty in Stalking Case. BocaNewsNow.com, 27 August 2026; cites court records.", "title": "Man Flagged by ChatGPT Pleads Guilty in Stalking Case", "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "date": "2026-08-27", "written_by": "independent" }, { "kind": "other", "citation": "Palm Beach County Sheriff's Office (2026). Booking Blotter, record for ZHOU, DARREN SHIDA, booking number 2026014226, arresting agency 01-PBSO. Retrieved 20 October 2026 by searching the blotter for last name Zhou between 20 May and 5 June 2026; the search form returns results without a stable record URL. The page rejected access during the October 24 source audit; the earlier record identification is preserved without a fresh verification claim.", "title": "Palm Beach County Sheriff's Office - Booking Blotter", "url": "https://www3.pbso.org/blotter/", "date": "2026-05-29", "written_by": "independent" }, { "kind": "news report", "citation": "Moolten S (2026). Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex. South Florida Sun Sentinel, 14 August 2026; cites the PBSO probable cause affidavit and the State Attorney's Office.", "title": "Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex", "url": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "date": "2026-08-14", "written_by": "independent" }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. OpenAI blog; Hoodline dates the policy to August 2025.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "role": "Retained evidence entries in reviewed order for this fingerprinted record version" }, "provenance": { "kind": "source_review", "basis": "Assigned to the retained evidence entries after this source review.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Colton A (2026). Man Flagged by ChatGPT Pleads Guilty in Stalking Case. BocaNewsNow.com, 27 August 2026; cites court records.", "title": "Man Flagged by ChatGPT Pleads Guilty in Stalking Case", "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "date": "2026-08-27", "written_by": "independent" }, { "kind": "other", "citation": "Palm Beach County Sheriff's Office (2026). Booking Blotter, record for ZHOU, DARREN SHIDA, booking number 2026014226, arresting agency 01-PBSO. Retrieved 20 October 2026 by searching the blotter for last name Zhou between 20 May and 5 June 2026; the search form returns results without a stable record URL. The page rejected access during the October 24 source audit; the earlier record identification is preserved without a fresh verification claim.", "title": "Palm Beach County Sheriff's Office - Booking Blotter", "url": "https://www3.pbso.org/blotter/", "date": "2026-05-29", "written_by": "independent" }, { "kind": "news report", "citation": "Moolten S (2026). Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex. South Florida Sun Sentinel, 14 August 2026; cites the PBSO probable cause affidavit and the State Attorney's Office.", "title": "Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex", "url": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "date": "2026-08-14", "written_by": "independent" }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. OpenAI blog; Hoodline dates the policy to August 2025.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0260-source-0001" ], "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "title": "Man Flagged by ChatGPT Pleads Guilty in Stalking Case", "published_on": "2026-08-27", "relationship": "BocaNewsNow adds direct court reporting on the guilty plea and conditions. Its court documents are not linked or reproduced in full." }, { "source_refs": [ "AIBD-0260-source-0002" ], "url": "https://www3.pbso.org/blotter/", "title": "Palm Beach County Sheriff's Office - Booking Blotter", "published_on": "2026-05-29", "relationship": "The PBSO blotter is an official origin for the booking identity and date, previously recorded as checked October 20. It was inaccessible October 24 and is not freshly verified." }, { "source_refs": [ "AIBD-0260-source-0003" ], "url": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "title": "Ex-financial analyst sentenced to probation after telling ChatGPT about plans to rape and kill his ex", "published_on": "2026-08-14", "relationship": "The Sun Sentinel’s earlier local reporting is retained for its affidavit reporting and reported prosecutor/defense context. Its full text was inaccessible in this review." }, { "source_refs": [ "AIBD-0260-source-0004" ], "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "title": "Helping people when they need it most", "relationship": "OpenAI’s original policy explains the general human-review step. It does not verify this particular referral." } ], "excluded_republications": [ { "url": "https://www.wpbf.com/article/south-palm-beach-man-cyberstalking-ex-girlfriend-threats-chatgpt/73434967", "citation": "Laurent V (2026). Man accused of cyberstalking ex after alleged threats flagged through ChatGPT. WPBF 25 News, 14 August 2026 (updated 15 August); cites the arrest affidavit and court documents.", "relationship": "IBTimes and MediaNama relay reporting by other outlets. WPBF and Palm Beach Post supply overlapping case accounts whose additional evidentiary contribution could not be verified here. The retained Sun Sentinel source preserves potentially material prosecutor and defense context rather than discarding it as mere duplication." }, { "url": "https://www.palmbeachpost.com/story/news/crime/2026/08/14/openai-reported-florida-man-darren-zhou-chatgpt-murder-messages-fbi/91285875007/", "citation": "Phillips H (2026). ChatGPT reported South Palm Beach man's rape and murder threats to FBI. The Palm Beach Post, 14 August 2026 (updated 17 August).", "relationship": "IBTimes and MediaNama relay reporting by other outlets. WPBF and Palm Beach Post supply overlapping case accounts whose additional evidentiary contribution could not be verified here. The retained Sun Sentinel source preserves potentially material prosecutor and defense context rather than discarding it as mere duplication." }, { "url": "https://www.ibtimes.co.uk/florida-man-chatgpt-threats-fbi-probation-1814510", "citation": "Jaen R (2026). 'If I Can't Have Her, Nobody Can': ChatGPT Flags Florida Man's Chilling Threat to FBI. International Business Times UK, 17 August 2026.", "relationship": "IBTimes and MediaNama relay reporting by other outlets. WPBF and Palm Beach Post supply overlapping case accounts whose additional evidentiary contribution could not be verified here. The retained Sun Sentinel source preserves potentially material prosecutor and defense context rather than discarding it as mere duplication." }, { "url": "https://www.medianama.com/2026/08/223-openai-reports-chatgpt-murder-threats-to-fbi/", "citation": "Peter AM (2026). OpenAI Reports Florida Man's ChatGPT Murder Threats to FBI. MediaNama, 17 August 2026; draws on The Detroit News and court records.", "relationship": "IBTimes and MediaNama relay reporting by other outlets. WPBF and Palm Beach Post supply overlapping case accounts whose additional evidentiary contribution could not be verified here. The retained Sun Sentinel source preserves potentially material prosecutor and defense context rather than discarding it as mere duplication." } ], "lead_source_ref": "AIBD-0260-source-0001", "retained_source_order": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "ordering_basis": "The first source directly supports the reported benefit or is the closest accessible original account. Each additional source has a distinct evidentiary contribution described in its relationship. Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "An OpenAI emergency disclosure passed through the FBI to PBSO, which compared it with anonymous threatening texts.", "source_ref": "AIBD-0260-source-0001", "source_chain": [ { "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "locator": "BocaNewsNow paragraphs beginning “The case first surfaced…” and “A subsequent PBSO investigation…”", "role": "BocaNewsNow adds direct court reporting on the guilty plea and conditions. Its court documents are not linked or reproduced in full." } ], "locator": "BocaNewsNow paragraphs beginning “The case first surfaced…” and “A subsequent PBSO investigation…”", "method": {}, "limitations": [ "The underlying emergency disclosure and probable-cause affidavit were not directly inspected.", "Exact system triggers and model replies are not established." ] }, { "claim": "Zhou pleaded guilty August 13 and received probation, monitoring, and restrictions.", "source_ref": "AIBD-0260-source-0001", "source_chain": [ { "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "locator": "BocaNewsNow plea and sentencing paragraphs", "role": "BocaNewsNow adds direct court reporting on the guilty plea and conditions. Its court documents are not linked or reproduced in full." } ], "locator": "BocaNewsNow plea and sentencing paragraphs", "method": {}, "limitations": [ "The full plea agreement and order were not available from the article." ] }, { "claim": "The booking date is May 29, 2026.", "source_ref": "AIBD-0260-source-0002", "source_chain": [ { "url": "https://www3.pbso.org/blotter/", "locator": "PBSO booking 2026014226, previously recorded retrieval October 20, 2026", "role": "The PBSO blotter is an official origin for the booking identity and date, previously recorded as checked October 20. It was inaccessible October 24 and is not freshly verified." } ], "locator": "PBSO booking 2026014226, previously recorded retrieval October 20, 2026", "method": {}, "limitations": [ "The current access attempt was rejected. The old quotation contained non-source wording and has been removed rather than reconstructed." ] }, { "claim": "OpenAI’s policy routes detected threats through human reviewers before possible law-enforcement referral.", "source_ref": "AIBD-0260-source-0004", "source_chain": [ { "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "locator": "“Escalate risk of physical harm to others for human review”", "role": "OpenAI’s original policy explains the general human-review step. It does not verify this particular referral." } ], "locator": "“Escalate risk of physical harm to others for human review”", "method": {}, "limitations": [ "General policy is not a case-specific audit log." ] } ], "limitations": [ "PBSO’s blotter and the Palm Beach court portal rejected access. The affidavit, actual chats, emergency disclosure, and plea order were not directly read.", "Sun Sentinel, WPBF, and Palm Beach Post were inaccessible during this review. The audit does not claim that their complete texts were freshly read.", "The original booking quotation contained “specific harm prevented” inside statutory charge text, which is not credible source wording. It was removed.", "The earlier six-day timeline and detailed defense statements should not be elevated beyond the accessible evidence. The public account now avoids those unsupported specifics." ], "access_audit": [ { "url": "https://bocanewsnow.com/2026/08/27/man-flagged-by-chatgpt-pleads-guilty-in-stalking-case/", "access": "full original court-reporting article read" }, { "url": "https://www3.pbso.org/blotter/", "access": "request rejected; earlier October 20 record identification preserved" }, { "url": "https://www.sun-sentinel.com/2026/08/14/financial-analyst-sentenced-to-probation-after-telling-chatgpt-about-plans-to-rape-and-kill-his-ex/", "access": "full text inaccessible; earlier citation preserved for material legal context" }, { "url": "https://www.mypalmbeachclerk.com/records/court-records", "access": "403; underlying filings not retrieved" }, { "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "access": "full original policy article read" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified." } }, "provenance": { "kind": "source_review", "basis": "Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The accessible reporting describes the disclosure, arrest, and guilty plea. The affidavit, chats, emergency disclosure, and court order were inaccessible, so the account does not independently establish their full contents.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "An OpenAI disclosure brought Darren Zhou’s threats to police attention; he pleaded guilty to stalking and threat charges and received probation, GPS monitoring, and contact and weapons restrictions.", "account": "Court reporting describes an OpenAI emergency disclosure that reached the Palm Beach County Sheriff’s Office through the FBI after Darren Zhou wrote threats against his ex-girlfriend in ChatGPT. Deputies compared those messages with anonymous threats that she had preserved. The sheriff’s booking entry lists May 29, 2026 as his arrest date. BocaNewsNow reports that he pleaded guilty on August 13 to written threats, aggravated stalking, and unlawful use of a two-way communication device. Adjudication was withheld, with eight years of probation, two years of GPS monitoring, and restrictions on contact and weapons. The accessible reporting cites court documents but does not reproduce the complete affidavit or plea order. It supports a police intervention and court restrictions, rather than proof that an attack would otherwise have occurred." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "An OpenAI disclosure brought Darren Zhou’s threats to police attention. He pleaded guilty and received probation, GPS monitoring, and restrictions on contact and weapons.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT (OpenAI), with OpenAI's automated detection and human review pipeline for users planning to harm others" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OpenAI refers Darren Zhou’s threats to the FBI; local police investigate and he pleads guilty to stalking and threat charges", "headline": "OpenAI refers Darren Zhou's threats to the FBI; he pleads guilty" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "1305768f24ac19a795ee53d018884bb83754966afae529eb2e6116f1de72b313" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Court reporting describes an OpenAI emergency disclosure that reached the Palm Beach County Sheriff’s Office through the FBI after Darren Zhou wrote threats against his ex-girlfriend in ChatGPT. Deputies compared those messages with anonymous threats that she had preserved. The sheriff’s booking entry lists May 29, 2026 as his arrest date. BocaNewsNow reports that he pleaded guilty on August 13 to written threats, aggravated stalking, and unlawful use of a two-way communication device. Adjudication was withheld, with eight years of probation, two years of GPS monitoring, and restrictions on contact and weapons. The accessible reporting cites court documents but does not reproduce the complete affidavit or plea order. It supports a police intervention and court restrictions, rather than proof that an attack would otherwise have occurred.", "replication": { "produced_by": [ "A reported OpenAI emergency disclosure of threatening messages to the FBI", "Referral to local police and comparison with messages that the threatened person had preserved", "Investigation and court restrictions following a guilty plea" ], "must_hold": [ "A disclosure must reach an agency able to investigate", "Investigators must establish identity and assess the threat using supporting evidence", "A general detection-and-review policy does not establish the details of a particular referral", "Arrest and court restrictions do not prove that an attack would otherwise have occurred" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Removed a corrupted quotation from the booking entry and reduced eight sources to the original accessible court reporting, the previously identified official booking, material local reporting, and the provider’s original policy. The court documents remain an explicit access gap.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0260-source-0001", "AIBD-0260-source-0002", "AIBD-0260-source-0003", "AIBD-0260-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "OpenAI reportedly disclosed threatening messages to the FBI. Local police compared them with messages that the threatened person had preserved, investigated, and brought charges. A guilty plea led to court restrictions.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 19, "record_mapped": 12, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0234", "title": "Asilla's behavior-analysis AI at about 40 Japanese stations and buildings may have prompted two suicide interventions", "summary": "Asilla told Kyodo that camera alerts prompted guards to intervene in two apparent suicide risks. The facilities and dates were not identified, and the company is the sole source of those accounts.", "date_observed": "2026-06-01", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The two interventions are undated. Tokyo-based Asilla's system assesses the likelihood that a person will jump by analyzing behavior on security-camera footage. It looks for behavior such as pacing or lingering near a platform edge or rooftop. It alerts security guards and station staff, in some cases with loudspeaker warnings. In one case it detected a man loitering in a non-customer area of a commercial facility. A guard found him, and he later said he had intended to kill himself by jumping. In another, a child lingering near an upper-floor railing was found to have been writing a suicide note. Asilla says it trained the system since 2022 with around 200 facilities on about seven million pieces of footage. All details come from the company via Kyodo, and no operator, police or academic confirmation is among the sources. Asilla’s earlier product release identifies a jump-risk detection function in AI Security asilla version 2.4, using movement trajectories, position, and body-motion patterns. It does not identify the version used in these two interventions.", "category": "protective response", "unexpected": false, "purpose": "Detect behavior indicating suicide risk (and illness, immobility or violence) in security-camera footage and alert staff.", "system": "Asilla AI behavior-analysis system for security cameras", "model_version": null, "developer": "Asilla Inc.", "deployer": "About 40 railway stations and commercial buildings in Japan (operators not named)", "location": null, "domain": "Public safety / suicide prevention", "segment": "Transport and real estate", "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Two people in apparent crisis were reached by guards after alerts, per the developer; no independent account of either case." }, { "group": "organizational", "depth": null, "reason": "No operator-reported outcome or false-alert data in the sources." } ], "ai_role": { "status": "assessed", "statement": "Kyodo attributes both interventions to Asilla’s account. The company’s original product documentation supports the existence and intended mechanism of jump-risk alerts, but does not independently verify either intervention. 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Tokyo-based Asilla's system assesses the likelihood that a person will jump by analyzing behavior on security-camera footage. It looks for behavior such as pacing or lingering near a platform edge or rooftop. It alerts security guards and station staff, in some cases with loudspeaker warnings. In one case it detected a man loitering in a non-customer area of a commercial facility. A guard found him, and he later said he had intended to kill himself by jumping. In another, a child lingering near an upper-floor railing was found to have been writing a suicide note. Asilla says it trained the system since 2022 with around 200 facilities on about seven million pieces of footage. All details come from the company via Kyodo, and no operator, police or academic confirmation is among the sources. Asilla’s earlier product release identifies a jump-risk detection function in AI Security asilla version 2.4, using movement trajectories, position, and body-motion patterns. It does not identify the version used in these two interventions.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Asilla reported two interventions after camera alerts. It did not identify the facilities or dates.", "editor_note": "" } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two people in apparent crisis were reached by guards after alerts, per the developer; no independent account of either case." }, { "group": "organizational", "reason": "No operator-reported outcome or false-alert data in the sources." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect behavior indicating suicide risk (and illness, immobility or violence) in security-camera footage and alert staff." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect behavior indicating suicide risk (and illness, immobility or violence) in security-camera footage and alert staff." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-06-01", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.wantedly.com/companies/asilla", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "source": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "June 1, 2026 is the Kyodo report’s publication date. Neither intervention is dated. Revision history is preserved separately from case chronology.", "record_fields": [ "date_observed", "revisions", "date_basis", "date_precision" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Existing security cameras in areas with jump risk", "A behavior model trained on large volumes of site footage", "Guards or staff positioned to respond within minutes" ], "must_hold": [ "Staff presence to act on alerts", "Acceptable false-alert rates for operators", "Camera coverage of the risk zones" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.wantedly.com/companies/asilla", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "source": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. 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Chiba TV identifies its original distribution link, which is inaccessible. Asilla’s original product release is available.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kyodo News via The Straits Times, 1 Jun 2026", "title": "Japan stations, facilities use AI system to prevent suicide by jumping", "url": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "date": "2026-06-01", "written_by": "independent", "quote": "The man later said he had intended to kill himself by jumping, according to the company." }, { "kind": "press release", "citation": "Asilla, “アジラ、最先端のAI警備システム『AI Security asilla』をバージョンアップ。ver.2.4のリリースを開始！,” January 26, 2024, “飛び降り予兆検知機能.”", "title": "アジラ、最先端のAI警備システム『AI Security asilla』をバージョンアップ。ver.2.4のリリースを開始！", "url": "https://jp.asilla.com/post/version-2-4-20240126", "date": "2024-01-26", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "role": "Retained evidence entries in reviewed order for this fingerprinted record version" }, "provenance": { "kind": "source_review", "basis": "Assigned to the retained evidence entries after this source review.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Kyodo News via The Straits Times, 1 Jun 2026", "title": "Japan stations, facilities use AI system to prevent suicide by jumping", "url": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "date": "2026-06-01", "written_by": "independent", "quote": "The man later said he had intended to kill himself by jumping, according to the company." }, { "kind": "press release", "citation": "Asilla, “アジラ、最先端のAI警備システム『AI Security asilla』をバージョンアップ。ver.2.4のリリースを開始！,” January 26, 2024, “飛び降り予兆検知機能.”", "title": "アジラ、最先端のAI警備システム『AI Security asilla』をバージョンアップ。ver.2.4のリリースを開始！", "url": "https://jp.asilla.com/post/version-2-4-20240126", "date": "2024-01-26", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0234-source-0001" ], "url": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "title": "Japan stations, facilities use AI system to prevent suicide by jumping", "published_on": "2026-06-01", "relationship": "Kyodo’s report is original journalism carried by The Straits Times. The two intervention accounts are explicitly attributed to Asilla, not independently confirmed by the reporter." }, { "source_refs": [ "AIBD-0234-source-0002" ], "url": "https://jp.asilla.com/post/version-2-4-20240126", "title": "アジラ、最先端のAI警備システム『AI Security asilla』をバージョンアップ。ver.2.4のリリースを開始！", "published_on": "2024-01-26", "relationship": "Asilla’s January 2024 release identifies the product function and technical inputs. It is separate primary documentation of the mechanism, not corroboration of the two events." } ], "excluded_republications": [ { "url": "https://oecd.ai/en/incidents/2026-06-01-db16", "citation": "OECD AI Incidents Monitor, incident 2026-06-01-db16", "relationship": "The OECD entry repeats the reported interventions and adds no independent evidence." } ], "lead_source_ref": "AIBD-0234-source-0001", "retained_source_order": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "ordering_basis": "The first source directly supports the reported benefit or is the closest accessible original account. Each additional source has a distinct evidentiary contribution described in its relationship. Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "Asilla said that alerts prompted guards to reach two people who appeared to be at risk of jumping.", "source_ref": "AIBD-0234-source-0001", "source_chain": [ { "url": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "locator": "Two case paragraphs following the alert workflow", "role": "Kyodo’s report is original journalism carried by The Straits Times. The two intervention accounts are explicitly attributed to Asilla, not independently confirmed by the reporter." } ], "locator": "Two case paragraphs following the alert workflow", "method": {}, "limitations": [ "The developer is the sole identified origin of both cases.", "No facility, date, operator statement, or intervention log is given." ] }, { "claim": "AI Security asilla version 2.4 introduced jump-risk detection based on trajectories, position, and body movement.", "source_ref": "AIBD-0234-source-0002", "source_chain": [ { "url": "https://jp.asilla.com/post/version-2-4-20240126", "locator": "“飛び降り予兆検知機能”", "role": "Asilla’s January 2024 release identifies the product function and technical inputs. It is separate primary documentation of the mechanism, not corroboration of the two events." } ], "locator": "“飛び降り予兆検知機能”", "method": {}, "limitations": [ "The version deployed in the two 2026-reported cases is unspecified." ] } ], "limitations": [ "The original Kyodo distribution address was traced through Chiba TV to https://news.jp/i/1433984055470228190; that endpoint was inaccessible. The complete identified Kyodo syndication in The Straits Times was read.", "The company’s claim that lives were saved is not independent evidence of the counterfactual.", "A related Osaka report describes false alarms and response gaps, but cannot be matched to either anonymous case." ], "access_audit": [ { "url": "https://www.straitstimes.com/asia/east-asia/japan-stations-facilities-use-ai-system-to-prevent-suicide-by-jumping", "access": "complete identified Kyodo syndication read" }, { "url": "https://www.chiba-tv.com/plus/detail/amp/2026061691278", "access": "Kyodo attribution, date, and original distribution link read" }, { "url": "https://news.jp/i/1433984055470228190", "access": "inaccessible; not read" }, { "url": "https://jp.asilla.com/post/version-2-4-20240126", "access": "complete original product release read" } ], "related_material": [ { "url": "https://www.mlit.go.jp/toshi/tosiko/content/001892574.pdf", "title": "スマートシティ実装化支援事業 調査報告書", "author": "うめきた２期地区等スマートシティ形成協議会", "date": "March 2025", "locators": [ "pp. 26–31, AI camera deployment using asilla and icetana" ], "access": "relevant operational results and limitations read, not represented as a complete audit of all 46 pages", "finding": "Reports worker-related false alerts, difficulty responding promptly to detections, and the limitation of jump-risk criteria for immediate jumps.", "relationship": "A separate deployment and useful operational caution. It is not attributed to the two anonymous interventions and is not counted as corroboration." } ], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified." } }, "provenance": { "kind": "source_review", "basis": "Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Kyodo reports Asilla’s account of two interventions. The complete Straits Times republication is available, but the original distribution page is inaccessible. A separate Osaka report describes false alarms and gaps in response, without identifying either of these incidents.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Asilla told Kyodo that camera alerts prompted guards to intervene in two apparent suicide risks. The facilities and dates were not identified, and the company is the sole source of those accounts.", "account": "The two interventions are undated. Tokyo-based Asilla's system assesses the likelihood that a person will jump by analyzing behavior on security-camera footage. It looks for behavior such as pacing or lingering near a platform edge or rooftop. It alerts security guards and station staff, in some cases with loudspeaker warnings. In one case it detected a man loitering in a non-customer area of a commercial facility. A guard found him, and he later said he had intended to kill himself by jumping. In another, a child lingering near an upper-floor railing was found to have been writing a suicide note. Asilla says it trained the system since 2022 with around 200 facilities on about seven million pieces of footage. All details come from the company via Kyodo, and no operator, police or academic confirmation is among the sources. Asilla’s earlier product release identifies a jump-risk detection function in AI Security asilla version 2.4, using movement trajectories, position, and body-motion patterns. It does not identify the version used in these two interventions." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Asilla AI behavior-analysis system for security cameras" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Asilla Inc." } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Asilla's behavior-analysis AI at about 40 Japanese stations and buildings may have prompted two suicide interventions", "headline": "Asilla's camera AI may have prompted two suicide interventions" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f901188e7feedf658f44ab9f117672015b105d67cca14325d6cd760c68c7535e" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The two interventions are undated. Tokyo-based Asilla's system assesses the likelihood that a person will jump by analyzing behavior on security-camera footage. It looks for behavior such as pacing or lingering near a platform edge or rooftop. It alerts security guards and station staff, in some cases with loudspeaker warnings. In one case it detected a man loitering in a non-customer area of a commercial facility. A guard found him, and he later said he had intended to kill himself by jumping. In another, a child lingering near an upper-floor railing was found to have been writing a suicide note. Asilla says it trained the system since 2022 with around 200 facilities on about seven million pieces of footage. All details come from the company via Kyodo, and no operator, police or academic confirmation is among the sources. Asilla’s earlier product release identifies a jump-risk detection function in AI Security asilla version 2.4, using movement trajectories, position, and body-motion patterns. It does not identify the version used in these two interventions.", "replication": { "produced_by": [ "Existing security cameras in areas with jump risk", "A behavior model trained on large volumes of site footage", "Guards or staff positioned to respond within minutes" ], "must_hold": [ "Staff presence to act on alerts", "Acceptable false-alert rates for operators", "Camera coverage of the risk zones" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Kyodo’s original reporting through its identified syndication, added the developer’s actual product documentation, and removed OECD as corroboration.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0234-source-0001", "AIBD-0234-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The system analyzed security-camera footage for behavior that suggested a risk of jumping. Guards or other staff responded to its alerts.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 13, "record_mapped": 17, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0330", "title": "Qualcomm's Dragonwing IQ10-powered humanoid may have run a “safe-collapse” sequence to protect its surroundings when it fell during a Computex 2026 demo in Taipei", "summary": "Vendor statement via Creative Bloq (27 July 2026): “The safety systems worked as intended.” NDTV, Asianet and TechSpot describe a face-first or backward collapse; nobody is reported at risk.", "date_observed": "2026-06-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The OECD AI Incidents entry files the event as an AI hazard. A humanoid robot on Qualcomm's Dragonwing IQ10 AI platform collapsed on stage during a live demo at Computex 2026 in Taipei after a communication glitch. The entry says it “executed a safe shutdown sequence, preventing harm”. The protective claim is Qualcomm's alone. Creative Bloq (27 July 2026, updated with a Qualcomm statement) quotes the company: “Live demos involve risk. At Computex in Taipei, a brief communication glitch triggered a fault in the prototype humanoid and initiated a controlled shutdown. The robot performed its designed safe-collapse sequence, lowering itself to its knees to protect the environment around it. The safety systems worked as intended.” NDTV (30 Jul), NDTV Profit (30 Jul, via The Indian Express) and Deccan Chronicle (30 Jul, “according to a news report”) relay the same statement. So do Asianet (31 Jul) and TechSpot (31 Jul). Gadget Review (28 Jul) says that the explanation “has not been independently confirmed”. It says Qualcomm had issued no official public statement at its time of publication. No statement was found on Qualcomm's or Neura Robotics' newsrooms. Qualcomm's release page rendered empty here, and Neura's news page lists no such item. The independent descriptions of the footage do not match a controlled kneel. NDTV says the robot “tumbled face-first onto the stage”, Asianet “crashed face-first”, and Creative Bloq “a crashing heap of plastic and metal”. TechSpot says it “collapsed like it had been shot”, “folding backwards on itself like a gymnast”, and was “dropped onto the floor” while being carried off. No person or object is reported at risk, and no beneficiary is identifiable. TechSpot identifies the robot as Neura Robotics' 4NE1 Gen 3.5 on Qualcomm's Dragonwing IQ10 robotics reference design. That design is listed at up to 700 TOPS, 6–8 hours' runtime, 100 kg payload, 5 ft 9 in. Gadget Review instead places the 4NE1 Gen 3.5's debut in Munich and calls the Taipei unit “Qualcomm's Dragonwing IQ10 humanoid”. The outlets say the fall happened during Qualcomm's keynote presentation. The Computex schedule lists Cristiano Amon's keynote on 1 June 2026 at TaiNEX 2, and the show ran 2–5 June. The sources do not give the exact day of the keynote. The video surfaced on social media on 22 July 2026 (a post embedded by Deccan Chronicle) and spread from 27–30 July. The Monitor's 28 July date is the coverage date. Four of the Monitor's nine listed sources (Fox News, Newsweek, Global Times, Tech Times) do not mention the incident. TechSpot's embedded November 2025 post is the Moscow AIdol clip cited for comparison.", "category": "protective response", "unexpected": false, "purpose": "Qualcomm describes the “safe-collapse” sequence as designed behavior that lowers the robot to its knees to protect its surroundings after a fault. The Dragonwing IQ10 is a reference design for humanoid and industrial robots.", "system": "Prototype humanoid on Qualcomm's Dragonwing IQ10 Robotics Reference Design (up to 700 TOPS on-device AI); identified by TechSpot as Neura Robotics' 4NE1 Gen 3.5, which Gadget Review instead places at a Munich debut", "model_version": "Dragonwing IQ10 RRD prototype; 4NE1 Gen 3.5 per TechSpot", "developer": "Qualcomm (Dragonwing IQ10 platform); robot hardware attributed to Neura Robotics by TechSpot and Gadget Review", "deployer": "Qualcomm, at its Computex 2026 showcase in Taipei", "location": "Taipei, Taiwan (Computex 2026, TaiNEX 2)", "domain": "Robotics: humanoid robot demonstrations", "segment": "Safety fallback behavior in humanoid robots", "benefit_type": "Increased Product Safety", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-07-28-5a37" }, "ratings": [ { "group": "personal", "depth": null, "reason": "No person on stage is reported at risk from the fall. The only account of a protective kneel is Qualcomm's, contradicted by descriptions of a face-first crash." }, { "group": "organizational", "depth": null, "reason": "Qualcomm says that the incident “provided valuable real-world data”. No measure of damage avoided or reliability gained is given." } ], "ai_role": { "status": "assessed", "statement": "Qualcomm attributes the fault that caused the collapse to a communication glitch in the prototype. The claimed benefit is that the robot's safety software then executed a designed “safe-collapse” to its knees. That claim comes only from Qualcomm's statement to Creative Bloq, and no engineering account exists. NDTV, Asianet, TechSpot and Creative Bloq describe a face-first or backward fall followed by staff dropping the robot. Whether any safety routine ran, and whether it protected anything, is unsupported. The AI platform's role in the event is the malfunction itself." }, "evidence": [ { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, record 2026-07-28-5a37, 'Humanoid Robot Malfunctions and Collapses During Live AI Demo at Computex 2026' (AI-generated summary; filed as an AI hazard).", "title": "Humanoid Robot Malfunctions and Collapses During Live AI Demo at Computex 2026", "url": "https://oecd.ai/en/incidents/2026-07-28-5a37", "date": "2026-07-28", "written_by": "independent", "quote": "The robot executed a safe shutdown sequence, preventing harm, but the incident highlighted potential risks of AI system malfunctions." }, { "kind": "news report", "citation": "Creative Bloq, 27 July 2026 (updated to include a statement from Qualcomm), 'This video of an AI robot collapsing mid-presentation gets funnier every time I watch it'.", "title": "This video of an AI robot collapsing mid-presentation gets funnier every time I watch it", "url": "https://www.creativebloq.com/design/product-design/this-video-of-an-ai-robot-collapsing-mid-presentation-gets-funnier-every-time-i-watch-it", "date": "2026-07-27", "written_by": "independent", "quote": "The robot performed its designed ‘safe-collapse’ sequence, lowering itself to its knees to protect the environment around it. The safety systems worked as intended." }, { "kind": "news report", "citation": "NDTV (ed. Abhinav Singh), 30 July 2026, 'Watch: AI Humanoid Robot Collapses In Taiwan During Live Demo, Video Viral'.", "title": "Watch: AI Humanoid Robot Collapses In Taiwan During Live Demo, Video Viral", "url": "https://www.ndtv.com/offbeat/watch-ai-humanoid-robot-collapses-in-taiwan-during-live-demo-video-viral-11845190", "date": "2026-07-30", "written_by": "independent", "quote": "A humanoid robot in Taiwan tumbled face-first onto the stage, leaving the developers red-faced as the video of the incident went viral on social media." }, { "kind": "news report", "citation": "NDTV Profit (Shreya Sur), 30 July 2026, 'Humanoid Robot Running On Qualcomm AI Chip 'Dies' On Stage At Computex 2026'.", "title": "Humanoid Robot Running On Qualcomm AI Chip 'Dies' On Stage At Computex 2026", "url": "https://www.ndtvprofit.com/technology/humanoid-robot-running-on-qualcomm-ai-chip-dies-on-stage-at-computex-2026-11844305", "date": "2026-07-30", "written_by": "independent", "quote": "According to The Indian Express, Qualcomm later clarified that the incident was caused by a brief communication glitch that triggered a fault in the prototype." }, { "kind": "news report", "citation": "TechSpot, 31 July 2026, 'Qualcomm's humanoid robot demo went hilariously wrong when the machine just dropped dead on stage'.", "title": "Qualcomm's humanoid robot demo went hilariously wrong when the machine just dropped dead on stage", "url": "https://www.techspot.com/news/113313-qualcomm-powered-humanoid-robot-collapses-stage-like-shot.html", "date": "2026-07-31", "written_by": "independent", "quote": "It collapsed spectacularly, folding backwards on itself like a gymnast." }, { "kind": "news report", "citation": "Deccan Chronicle (DC Web Desk), 30 July 2026, 'Humanoid Robot Powered by Qualcomm Collapses on Stage at Computex 2026' (embeds a 22 July 2026 post of the video).", "title": "Humanoid Robot Powered by Qualcomm Collapses on Stage at Computex 2026", "url": "https://www.deccanchronicle.com/technology/humanoid-robot-powered-by-qualcomm-collapses-on-stage-at-computex-2026-1975284", "date": "2026-07-30", "written_by": "independent", "quote": "According to a news report, Qualcomm said the collapse was caused by a brief communication glitch that triggered a fault in the prototype." }, { "kind": "news report", "citation": "Asianet Newsable (Shweta Kumari), 31 July 2026, 'Taiwan: AI Humanoid Robot Crashes Face-First Onstage During Live Demo At Computex 2026 (WATCH)'.", "title": "Taiwan: AI Humanoid Robot Crashes Face-First Onstage During Live Demo At Computex 2026 (WATCH)", "url": "https://newsable.asianetnews.com/world/taiwan-ai-humanoid-robot-crashes-onstage-during-live-demo-at-computex-2026-articleshow-bcr0em1", "date": "2026-07-31", "written_by": "independent", "quote": "the machine dramatically crashed face-first onto the stage, leaving its developers scrambling" }, { "kind": "news report", "citation": "Gadget Review (Al Landes), 28 July 2026, 'A Humanoid Robot 'Dies' On Stage at Computex 2026, Gets Carried Off'.", "title": "A Humanoid Robot “Dies” On Stage at Computex 2026, Gets Carried Off", "url": "https://www.gadgetreview.com/a-humanoid-robot-dies-on-stage-at-computex-2026-gets-carried-off", "date": "2026-07-28", "written_by": "independent", "quote": "That explanation has not been independently confirmed — Qualcomm had not issued an official public statement on the incident at time of publication." }, { "kind": "other", "citation": "COMPUTEX Keynote & Forum 2026 programme (events.computextaipei.com.tw), accessed by the earlier verifier on 20 October 2026: Qualcomm CEO Cristiano Amon keynote on 1 June 2026 at TaiNEX 2.", "title": "COMPUTEX Keynote & Forum 2026", "url": "https://events.computextaipei.com.tw/en/", "date": null, "written_by": "independent", "quote": "Keynote June 1 - 3, 2026 TaiNEX 2 & TWTC, Taipei Taiwan" }, { "kind": "press release", "citation": "Neura Robotics, product page 'Humanoid Robot 4NE1 for Work and Life', accessed 20 October 2026 (current 4NE1 specifications; no Computex statement).", "title": "Humanoid Robot 4NE1 for Work and Life | NEURA Robotics", "url": "https://neura-robotics.com/products/4ne1", "date": null, "written_by": "makers", "quote": "4NE1 brings safe, intelligent automation to the real world – wherever humans are." } ], "replication": { "produced_by": [ "A controlled-shutdown routine triggered when a communication glitch caused a fault, in Qualcomm's account", "A prototype humanoid on the Dragonwing IQ10 reference design demonstrated on a stage" ], "must_hold": [ "Independent engineering evidence that the robot knelt rather than fell. The footage descriptions say it fell", "A person or object within reach that the behavior protected. None is reported" ], "echoes": [ { "date": null, "setting": "Moscow, Russia, November 2025: the AIdol humanoid fell face-first at its debut (TechSpot and NDTV cite it for comparison); its developer called it a “real-time training” session and no safe-collapse claim was made", "model_version": "AIdol (unrelated system)", "outcome": "unknown", "source": "https://www.techspot.com/news/113313-qualcomm-powered-humanoid-robot-collapses-stage-like-shot.html" } ] }, "paired_incident": null, "headline": "Qualcomm's humanoid may have collapsed safely at Computex", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "Nothing dated after the late-July 2026 coverage was found; Qualcomm's safe-collapse statement is the benefit claim itself, and Gadget Review noted it had not been independently confirmed.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": "only Qualcomm's account of a safe collapse, and nobody at risk", "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Left not rated: only Qualcomm's account of a safe collapse, and nobody at risk.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Qualcomm; https://en.wikipedia.org/wiki/Qualcomm", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports, a registry entry, one other independent source and the makers' press release. 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A humanoid robot on Qualcomm's Dragonwing IQ10 AI platform collapsed on stage during a live demo at Computex 2026 in Taipei after a communication glitch. The entry says it “executed a safe shutdown sequence, preventing harm”. The protective claim is Qualcomm's alone. Creative Bloq (27 July 2026, updated with a Qualcomm statement) quotes the company: “Live demos involve risk. At Computex in Taipei, a brief communication glitch triggered a fault in the prototype humanoid and initiated a controlled shutdown. The robot performed its designed safe-collapse sequence, lowering itself to its knees to protect the environment around it. The safety systems worked as intended.” NDTV (30 Jul), NDTV Profit (30 Jul, via The Indian Express) and Deccan Chronicle (30 Jul, “according to a news report”) relay the same statement. So do Asianet (31 Jul) and TechSpot (31 Jul). Gadget Review (28 Jul) says that the explanation “has not been independently confirmed”. It says Qualcomm had issued no official public statement at its time of publication. No statement was found on Qualcomm's or Neura Robotics' newsrooms. Qualcomm's release page rendered empty here, and Neura's news page lists no such item. The independent descriptions of the footage do not match a controlled kneel. NDTV says the robot “tumbled face-first onto the stage”, Asianet “crashed face-first”, and Creative Bloq “a crashing heap of plastic and metal”. TechSpot says it “collapsed like it had been shot”, “folding backwards on itself like a gymnast”, and was “dropped onto the floor” while being carried off. No person or object is reported at risk, and no beneficiary is identifiable. TechSpot identifies the robot as Neura Robotics' 4NE1 Gen 3.5 on Qualcomm's Dragonwing IQ10 robotics reference design. That design is listed at up to 700 TOPS, 6–8 hours' runtime, 100 kg payload, 5 ft 9 in. Gadget Review instead places the 4NE1 Gen 3.5's debut in Munich and calls the Taipei unit “Qualcomm's Dragonwing IQ10 humanoid”. The outlets say the fall happened during Qualcomm's keynote presentation. The Computex schedule lists Cristiano Amon's keynote on 1 June 2026 at TaiNEX 2, and the show ran 2–5 June. The sources do not give the exact day of the keynote. The video surfaced on social media on 22 July 2026 (a post embedded by Deccan Chronicle) and spread from 27–30 July. The Monitor's 28 July date is the coverage date. Four of the Monitor's nine listed sources (Fox News, Newsweek, Global Times, Tech Times) do not mention the incident. TechSpot's embedded November 2025 post is the Moscow AIdol clip cited for comparison.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No person on stage is reported at risk from the fall. The only account of a protective kneel is Qualcomm's, contradicted by descriptions of a face-first crash." }, { "group": "organizational", "reason": "Qualcomm says that the incident “provided valuable real-world data”. No measure of damage avoided or reliability gained is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Qualcomm describes the “safe-collapse” sequence as designed behavior that lowers the robot to its knees to protect its surroundings after a fault. The Dragonwing IQ10 is a reference design for humanoid and industrial robots." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Taipei, Taiwan (Computex 2026, TaiNEX 2)", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Qualcomm describes the “safe-collapse” sequence as designed behavior that lowers the robot to its knees to protect its surroundings after a fault. 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The footage descriptions say it fell", "A person or object within reach that the behavior protected. None is reported" ], "echoes": [ { "setting": "Moscow, Russia, November 2025: the AIdol humanoid fell face-first at its debut (TechSpot and NDTV cite it for comparison); its developer called it a “real-time training” session and no safe-collapse claim was made", "model_version": "AIdol (unrelated system)", "outcome": "unknown", "source": "https://www.techspot.com/news/113313-qualcomm-powered-humanoid-robot-collapses-stage-like-shot.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A controlled-shutdown routine triggered when a communication glitch caused a fault, in Qualcomm's account", "A prototype humanoid on the Dragonwing IQ10 reference design demonstrated on a stage" ], "must_hold": [ "Independent engineering evidence that the robot knelt rather than fell. 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no Computex statement).", "title": "Humanoid Robot 4NE1 for Work and Life | NEURA Robotics", "url": "https://neura-robotics.com/products/4ne1", "written_by": "makers", "quote": "4NE1 brings safe, intelligent automation to the real world – wherever humans are." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Vendor statement via Creative Bloq (27 July 2026): “The safety systems worked as intended.” NDTV, Asianet and TechSpot describe a face-first or backward collapse; nobody is reported at risk.", "account": "The OECD AI Incidents entry files the event as an AI hazard. A humanoid robot on Qualcomm's Dragonwing IQ10 AI platform collapsed on stage during a live demo at Computex 2026 in Taipei after a communication glitch. The entry says it “executed a safe shutdown sequence, preventing harm”. The protective claim is Qualcomm's alone. Creative Bloq (27 July 2026, updated with a Qualcomm statement) quotes the company: “Live demos involve risk. At Computex in Taipei, a brief communication glitch triggered a fault in the prototype humanoid and initiated a controlled shutdown. The robot performed its designed safe-collapse sequence, lowering itself to its knees to protect the environment around it. The safety systems worked as intended.” NDTV (30 Jul), NDTV Profit (30 Jul, via The Indian Express) and Deccan Chronicle (30 Jul, “according to a news report”) relay the same statement. So do Asianet (31 Jul) and TechSpot (31 Jul). Gadget Review (28 Jul) says that the explanation “has not been independently confirmed”. It says Qualcomm had issued no official public statement at its time of publication. No statement was found on Qualcomm's or Neura Robotics' newsrooms. Qualcomm's release page rendered empty here, and Neura's news page lists no such item. The independent descriptions of the footage do not match a controlled kneel. NDTV says the robot “tumbled face-first onto the stage”, Asianet “crashed face-first”, and Creative Bloq “a crashing heap of plastic and metal”. TechSpot says it “collapsed like it had been shot”, “folding backwards on itself like a gymnast”, and was “dropped onto the floor” while being carried off. No person or object is reported at risk, and no beneficiary is identifiable. TechSpot identifies the robot as Neura Robotics' 4NE1 Gen 3.5 on Qualcomm's Dragonwing IQ10 robotics reference design. That design is listed at up to 700 TOPS, 6–8 hours' runtime, 100 kg payload, 5 ft 9 in. Gadget Review instead places the 4NE1 Gen 3.5's debut in Munich and calls the Taipei unit “Qualcomm's Dragonwing IQ10 humanoid”. The outlets say the fall happened during Qualcomm's keynote presentation. The Computex schedule lists Cristiano Amon's keynote on 1 June 2026 at TaiNEX 2, and the show ran 2–5 June. The sources do not give the exact day of the keynote. The video surfaced on social media on 22 July 2026 (a post embedded by Deccan Chronicle) and spread from 27–30 July. The Monitor's 28 July date is the coverage date. Four of the Monitor's nine listed sources (Fox News, Newsweek, Global Times, Tech Times) do not mention the incident. TechSpot's embedded November 2025 post is the Moscow AIdol clip cited for comparison." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The prototype used Dragonwing IQ10 RRD. TechSpot identified the robot as 4NE1 Gen 3.5." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Dragonwing IQ10 RRD prototype; 4NE1 Gen 3.5 per TechSpot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Prototype humanoid on Qualcomm's Dragonwing IQ10 Robotics Reference Design (up to 700 TOPS on-device AI); identified by TechSpot as Neura Robotics' 4NE1 Gen 3.5, which Gadget Review instead places at a Munich debut" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Qualcomm (Dragonwing IQ10 platform); robot hardware attributed to Neura Robotics by TechSpot and Gadget Review" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Qualcomm's Dragonwing IQ10-powered humanoid may have run a “safe-collapse” sequence to protect its surroundings when it fell during a Computex 2026 demo in Taipei", "headline": "Qualcomm's humanoid may have collapsed safely at Computex" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "43b1c0ac3b6faf3c18cf0331e4190700350e8389cf0f15809b75ffa042feb2ea" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The OECD AI Incidents entry files the event as an AI hazard. A humanoid robot on Qualcomm's Dragonwing IQ10 AI platform collapsed on stage during a live demo at Computex 2026 in Taipei after a communication glitch. The entry says it “executed a safe shutdown sequence, preventing harm”. The protective claim is Qualcomm's alone. Creative Bloq (27 July 2026, updated with a Qualcomm statement) quotes the company: “Live demos involve risk. At Computex in Taipei, a brief communication glitch triggered a fault in the prototype humanoid and initiated a controlled shutdown. The robot performed its designed safe-collapse sequence, lowering itself to its knees to protect the environment around it. The safety systems worked as intended.” NDTV (30 Jul), NDTV Profit (30 Jul, via The Indian Express) and Deccan Chronicle (30 Jul, “according to a news report”) relay the same statement. So do Asianet (31 Jul) and TechSpot (31 Jul). Gadget Review (28 Jul) says that the explanation “has not been independently confirmed”. It says Qualcomm had issued no official public statement at its time of publication. No statement was found on Qualcomm's or Neura Robotics' newsrooms. Qualcomm's release page rendered empty here, and Neura's news page lists no such item. The independent descriptions of the footage do not match a controlled kneel. NDTV says the robot “tumbled face-first onto the stage”, Asianet “crashed face-first”, and Creative Bloq “a crashing heap of plastic and metal”. TechSpot says it “collapsed like it had been shot”, “folding backwards on itself like a gymnast”, and was “dropped onto the floor” while being carried off. No person or object is reported at risk, and no beneficiary is identifiable. TechSpot identifies the robot as Neura Robotics' 4NE1 Gen 3.5 on Qualcomm's Dragonwing IQ10 robotics reference design. That design is listed at up to 700 TOPS, 6–8 hours' runtime, 100 kg payload, 5 ft 9 in. Gadget Review instead places the 4NE1 Gen 3.5's debut in Munich and calls the Taipei unit “Qualcomm's Dragonwing IQ10 humanoid”. The outlets say the fall happened during Qualcomm's keynote presentation. The Computex schedule lists Cristiano Amon's keynote on 1 June 2026 at TaiNEX 2, and the show ran 2–5 June. The sources do not give the exact day of the keynote. The video surfaced on social media on 22 July 2026 (a post embedded by Deccan Chronicle) and spread from 27–30 July. The Monitor's 28 July date is the coverage date. Four of the Monitor's nine listed sources (Fox News, Newsweek, Global Times, Tech Times) do not mention the incident. TechSpot's embedded November 2025 post is the Moscow AIdol clip cited for comparison.", "replication": { "produced_by": [ "A controlled-shutdown routine triggered when a communication glitch caused a fault, in Qualcomm's account", "A prototype humanoid on the Dragonwing IQ10 reference design demonstrated on a stage" ], "must_hold": [ "Independent engineering evidence that the robot knelt rather than fell. The footage descriptions say it fell", "A person or object within reach that the behavior protected. None is reported" ], "echoes": [ { "setting": "Moscow, Russia, November 2025: the AIdol humanoid fell face-first at its debut (TechSpot and NDTV cite it for comparison); its developer called it a “real-time training” session and no safe-collapse claim was made", "model_version": "AIdol (unrelated system)", "outcome": "unknown", "source": "https://www.techspot.com/news/113313-qualcomm-powered-humanoid-robot-collapses-stage-like-shot.html" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0273", "title": "ForeSight-HF, a GPT-5 mini decision-support tool, scores two nursing-home heart-failure cases; patients managed independently", "summary": "Mount Sinai authors describe ForeSight-HF (GPT-5 mini on ProviderLoop) recommending diuresis for a warm/wet and de-escalation for a cold/dry nursing-home patient; both were managed independently.", "date_observed": "2026-06-03", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Glajchen and colleagues describe ForeSight-HF in JACC: Case Reports, published online on June 3, 2026. The tool uses GPT-5 mini to produce heart-failure assessments and treatment suggestions from nursing-facility notes. The paper presents two illustrative cases and explicitly states that its outputs did not guide clinical care. Both patients were managed independently of the system for four months. In the second case, the clinicians’ actual diuretic and medication decisions differed from the AI recommendations. Weekly physician review is part of the proposed workflow, not evidence that the model directed these patients’ treatment. ProviderLoop supplied the platform, and senior author Jeffrey Bander disclosed that he founded and owned it. The patients’ clinical outcomes cannot be attributed to the AI.", "category": "general benefit", "unexpected": false, "purpose": "Generate heart-failure risk scores and management recommendations from nursing-facility documentation", "system": "ForeSight-HF (large-language-model clinical decision support on the ProviderLoop platform)", "model_version": "OpenAI GPT-5 mini (accessed late 2025)", "developer": "ProviderLoop (New York) with Mount Sinai clinicians", "deployer": "Skilled nursing facilities served through the ProviderLoop platform (location not stated)", "location": "New York, New York, USA (authors)", "domain": "Health; post-acute cardiology", "segment": "Heart-failure patients in skilled nursing facilities", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "Recommendations that matched independent management are read as task performance; nothing changed for the patients.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Both patients were managed independently of the AI system; outcomes not attributable." }, { "group": "organizational", "depth": null, "reason": "No measured organizational effect; prospective validation is called for by the authors." }, { "group": "societal", "depth": null, "reason": "No attributable event." } ], "ai_role": { "status": "assessed", "statement": "The model generated illustrative recommendations for two selected cases. The authors expressly state that its outputs did not guide care. Case 2 describes differences between the recommendations and the treatment that clinicians actually provided. No prospective effect on treatment or health was tested." }, "evidence": [ { "kind": "case report", "citation": "Emma Glajchen et al., “AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities,” JACC: Case Reports 31, no. 29 (2026): 108561, https://doi.org/10.1016/j.jaccas.2026.108561; online June 3, 2026, “Intended Use” and the two case descriptions.", "title": "AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13420647/", "date": "2026-06-03", "written_by": "makers", "quote": "The patient remained at the SNF for the following 4 months, managed independently of the AI system." }, { "kind": "case report", "citation": "Glajchen et al., “AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities,” “Funding Support and Author Disclosures.” Same paper as the preceding quotation.", "title": "AI-Driven Heart Failure Decision Support in Skilled Nursing Facilities", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13420647/", "date": "2026-06-03", "written_by": "makers", "quote": "Dr Bander is the founder and holds an ownership interest in ProviderLoop, the platform on which ForeSight-HF was developed." } ], "replication": { "produced_by": [ "GPT-5 mini prompted with unstructured facility documentation", "A proposed workflow with physician review of the model output on ProviderLoop; the illustrated patients were managed independently of it" ], "must_hold": [ "Prospective validation showing recommendations change management and outcomes", "Independent evaluation outside the vendor's authorship" ], "echoes": [] }, "paired_incident": null, "headline": "ForeSight-HF scores two nursing-home heart-failure cases", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The two illustrative cases were managed independently of the system for four months, and the cited source reports no later deployment data, trial or follow-up.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the complete original JATS article, including both case histories, table, references, and disclosures. Clarified that the system did not guide clinical care.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13420647/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' case report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0273", "catalog_version": "1.0.0", "source_fingerprint": "eecc9714603d66432e6341865070fee877e0caae9bbb217ed586c16f287acb1a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0273-source-0001", "AIBD-0273-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "ProviderLoop (New York) with Mount Sinai clinicians", "deployer": "Skilled nursing facilities served through the ProviderLoop platform (location not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The model generated illustrative recommendations for two selected cases. The authors expressly state that its outputs did not guide care. Case 2 describes differences between the recommendations and the treatment that clinicians actually provided. No prospective effect on treatment or health was tested." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Read the complete original JATS article, including both case histories, table, references, and disclosures. Clarified that the system did not guide clinical care.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0273-source-0001", "AIBD-0273-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The authors used the model to generate recommendations for two selected patients and state that its outputs did not guide care. They did not test whether the recommendations improved treatment or health.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "assessed", "statement": "The model generated illustrative recommendations for two selected cases. The authors expressly state that its outputs did not guide care. Case 2 describes differences between the recommendations and the treatment that clinicians actually provided. No prospective effect on treatment or health was tested." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Read the complete original JATS article, including both case histories, table, references, and disclosures. Clarified that the system did not guide clinical care.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0273-source-0001", "AIBD-0273-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: the makers' case report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from the retained evidence using the existing display rule. Source originality is documented separately and does not imply independent verification.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Both patients were managed independently of the AI system; outcomes not attributable." }, { "group": "organizational", "reason": "No measured organizational effect; prospective validation is called for by the authors." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Both patients were managed independently of the AI system; outcomes not attributable." }, { "group": "organizational", "reason": "No measured organizational effect; prospective validation is called for by the authors." }, { "group": "societal", "reason": "No attributable event." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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Clinicians managed both patients without using those recommendations.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "value_present", "value": { "kind": "text", "text": "The model generated care recommendations for illustrative cases that the authors compared with actual treatment." }, "provenance": { "kind": "legacy_record", "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The authors accessed GPT-5 mini in late 2025." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "GPT-5 mini." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "OpenAI GPT-5 mini (accessed late 2025)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ForeSight-HF (large-language-model clinical decision support on the ProviderLoop platform)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "ProviderLoop (New York) with Mount Sinai clinicians" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "ForeSight-HF, a GPT-5 mini decision-support tool, scores two nursing-home heart-failure cases; patients managed independently", "headline": "ForeSight-HF scores two nursing-home heart-failure cases" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "eecc9714603d66432e6341865070fee877e0caae9bbb217ed586c16f287acb1a" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Glajchen and colleagues describe ForeSight-HF in JACC: Case Reports, published online on June 3, 2026. The tool uses GPT-5 mini to produce heart-failure assessments and treatment suggestions from nursing-facility notes. The paper presents two illustrative cases and explicitly states that its outputs did not guide clinical care. Both patients were managed independently of the system for four months. In the second case, the clinicians’ actual diuretic and medication decisions differed from the AI recommendations. Weekly physician review is part of the proposed workflow, not evidence that the model directed these patients’ treatment. ProviderLoop supplied the platform, and senior author Jeffrey Bander disclosed that he founded and owned it. The patients’ clinical outcomes cannot be attributed to the AI.", "replication": { "produced_by": [ "GPT-5 mini prompted with unstructured facility documentation", "A proposed workflow with physician review of the model output on ProviderLoop; the illustrated patients were managed independently of it" ], "must_hold": [ "Prospective validation showing recommendations change management and outcomes", "Independent evaluation outside the vendor's authorship" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Read the complete original JATS article, including both case histories, table, references, and disclosures. Clarified that the system did not guide clinical care.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0273-source-0001", "AIBD-0273-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The researchers supplied unstructured nursing-home documentation to GPT-5 mini through ProviderLoop. Their proposed workflow includes physician review, but the two illustrated patients received care independently of the model.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 33, "reviewed": 13, "record_mapped": 20, "not_assessed": 58, "complete": false, "by_state": { "value_present": 33, "not_reported": 0, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0208", "title": "IMIE intelligent retina restores partial vision to a blind woman at Xiangya Hospital", "summary": "Blind over a decade, a 61-year-old woman read E optotypes and walked indoors unaided after a 256-channel IMIE retinal implant in Changsha.", "date_observed": "2026-06-05", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 23 April 2026 Prof. Xu Huizhuo's team implanted the IMIE intelligent retina in a 61-year-old woman known as Auntie Chen. The team is at Xiangya Hospital, Central South University, Changsha. The implant is a 256-channel epiretinal array driven by camera glasses and an external video processor. She was diagnosed with retinitis pigmentosa at 40 and had been blind for over ten years. Mark Humayun advised in theater, and no serious complications occurred. On 5 June 2026 the hospital announced that after over a month of rehabilitation she could identify E optotypes (acuity 0.03, peak 0.1). She could also walk indoors and through doorways without an escort. She is the first subject of a Phase I trial. The team says she lacks full self-care ability and will be observed for a year.", "category": "benefit created", "unexpected": false, "purpose": "Built to restore partial sight to people blinded by photoreceptor degeneration by converting camera images into electrical stimulation of surviving retinal ganglion cells. The benefit recorded here is exactly that intended function.", "system": "IMIE intelligent retina (IMIE智能视网膜): 256-channel flexible epiretinal electrode array fixed on the macula, with camera glasses and an external video processing unit transmitting wirelessly to the implant", "model_version": "256-channel array; the device lineage is the IMIE 256 (Intelligent Micro Implant Eye, also called Theia α) reported in TVST 2021", "developer": "Xiangya Hospital (Prof. Xu Huizhuo's team, per 2026 reports, which name no company); the IMIE 256 was co-developed by Golden Eye Bionics LLC (Pasadena) and IntelliMicro Medical Co., Ltd. (Changsha) and manufactured by IntelliMicro, per Xu et al. 2021", "deployer": "Xiangya Hospital, Central South University (Ophthalmology Center), in a Phase I clinical trial led by Prof. Xu Huizhuo", "location": "Changsha, China", "domain": "Healthcare", "segment": "Ophthalmology; retinal neuroprosthetics (invasive brain-computer interface)", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-06-06-09a2" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable person, totally blind for more than ten years, regained enough vision to identify E optotypes (0.03, peak 0.1). She can walk indoors and through doorways without an escort. The hospital cautions that she does not yet have full self-care ability and needs long-term rehabilitation." } ], "ai_role": { "status": "assessed", "statement": "The system is the whole substitute visual pathway. Camera glasses capture the scene. An external processor converts each frame in real time into stimulation patterns across 256 electrodes. The implant stimulates surviving ganglion cells whose signals reach the visual cortex. The patient had no vision before, so the benefit is attributable to the system together with structured rehabilitation. The 2026 reports describe the conversion only as an algorithm inside an “intelligent” retina. The 2021 IMIE 256 paper describes a video processing unit with a per-electrode threshold map and 15 gray levels and no learned model. How much of that processing is AI in a machine-learning sense is not established by these sources." }, "evidence": [ { "kind": "news report", "citation": "Wang Haohao and Tan Lianlian, China Science Daily (2026). 全国首例！脑机接口智能视网膜让盲人看见字符 [China's first: brain-computer interface smart retina lets a blind person see characters]. ScienceNet, 8 June 2026.", "title": "全国首例！脑机接口智能视网膜让盲人看见字符", "url": "https://news.sciencenet.cn/htmlnews/2026/6/566108.shtm", "date": "2026-06-08", "written_by": "independent", "quote": "4月23日，陈阿姨在湘雅医院完成IMIE智能视网膜植入手术" }, { "kind": "news report", "citation": "Tang Lu, Zhou Shun and Xiang Ying, Huasheng Online / Hunan Daily (2026). 国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明 [Domestic IMIE intelligent retina trial achieves major breakthrough; totally blind patient regains light]. hunan.voc.com.cn, 7 June 2026.", "title": "国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明", "url": "https://hunan.voc.com.cn/news/202606/32846000.html", "date": "2026-06-07", "written_by": "independent", "quote": "目前该患者已可识别E字视力表字符，无需他人陪护即可独自在室内走动、穿门而行" }, { "kind": "news report", "citation": "Yangcheng Evening News (2026). 中国首例！盲人凭脑机接口复明成功，实现自主行走 [China's first: blind person regains sight via brain-computer interface and walks independently]. Xinkuaibao (xkb.com.cn), 6 June 2026.", "title": "中国首例！盲人凭脑机接口复明成功，实现自主行走", "url": "https://www.xkb.com.cn/articleDetail/499962", "date": "2026-06-06", "written_by": "independent", "quote": "6月5日，湖南湘雅医院宣布完成全国首例侵入式脑机接口视觉重建临床试验" }, { "kind": "news report", "citation": "Yan Shuo, 21st Century Business Herald (2026). 失明患者重见光明：脑机接口加速落地，行业迎来量产前夜 [Blind patient regains sight: brain-computer interfaces accelerate, industry on the eve of mass production]. 21jingji.com, 8 June 2026.", "title": "失明患者重见光明：脑机接口加速落地，行业迎来量产前夜", "url": "https://www.21jingji.com/article/20260608/herald/908d9a3949ada35c98e6b666d4b41bc0.html", "date": "2026-06-08", "written_by": "independent", "quote": "目前患者尚不具备完全生活自理能力，后续仍需接受长期康复训练" }, { "kind": "news report", "citation": "Kuai Technology (2026). 国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1 [China's first blind person regains sight via brain-computer interface; measured peak acuity reaches 0.1]. 3DMGame, 6 June 2026.", "title": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1", "url": "https://www.3dmgame.com/news/202606/3945762.html", "date": "2026-06-06", "written_by": "independent", "quote": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1" }, { "kind": "news report", "citation": "Red Net (2026). 盲人患者使用侵入式脑机接口复明 视觉功能初步重建 [Blind patient regains sight with invasive brain-computer interface; visual function preliminarily rebuilt]. China.com, 6 June 2026.", "title": "盲人患者使用侵入式脑机接口复明 视觉功能初步重建", "url": "https://news.china.com/socialgd/10000169/20260606/49533586.html", "date": "2026-06-06", "written_by": "independent", "quote": "科研团队自主研发的IMIE智能视网膜系统" }, { "kind": "news report", "citation": "Securities Times (2026). 脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道 [Brain-computer interfaces reshape blindness treatment; Meihao Medical joins the new track]. Phoenix Finance (ifeng.com), 8 June 2026.", "title": "脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道", "url": "https://finance.ifeng.com/c/8tmrCoDSlTF", "date": "2026-06-08", "written_by": "independent", "quote": "国产256通道柔性电极阵列" }, { "kind": "peer-reviewed study", "citation": "Xu H, Zhong X, Pang C, Zou J, Chen W, Wang X, Li S, Hu Y, Sagan DS, Weiss PT, Yao Y, Xiang J, Dayan MS, Humayun MS, Tai YC (2021). First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256). Translational Vision Science & Technology 10(10):14. doi:10.1167/tvst.10.10.14; PMID 34705041.", "title": "First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256)", "url": "https://doi.org/10.1167/tvst.10.10.14", "date": "2021-08-01", "written_by": "makers", "quote": "The IMIE 256 implants were implanted in the right eyes of five subjects with end-stage retinitis pigmentosa." } ], "replication": { "produced_by": [ "Surviving retinal ganglion cells and optic nerve in end-stage retinitis pigmentosa, so that epiretinal stimulation can reach the visual cortex", "A 256-channel flexible array fixed on the macula with 250-micrometer tacks and per-patient fitting of stimulation currents", "Camera glasses and an external processor converting live video into stimulation patterns in real time", "More than a month of structured visual rehabilitation after implantation", "A surgical team with prior IMIE 256 experience (five implants reported in TVST 2021) and on-site guidance from Mark Humayun" ], "must_hold": [ "The implant stays positioned on the macula without serious complications. The 2021 series saw one array movement and one hypotony", "Rehabilitation continues; the hospital's one-year observation period is still running", "The reported acuity (0.03, peak 0.1) is phosphene vision, not natural sight. The hospital says the patient lacks full self-care ability" ], "echoes": [] }, "paired_incident": null, "headline": "IMIE intelligent retina restores partial vision to a blind woman", "metric": "she could identify E optotypes (acuity 0.03, peak 0.1)", "comparator": { "against": "international retinal prostheses of the same type with 60 channels", "before": "60 channels (international products of the same kind)", "after": "256-channel flexible electrode array, with channel count and visual resolution reported as significantly superior", "basis": "assumed", "quote": "该系统搭载了我国首创的256通道柔性电极阵列，其通道数及视觉分辨能力均显著优于国际同类60通道产品", "url": "https://news.china.com/socialgd/10000169/20260606/49533586.html" }, "later": { "status": "unknown", "date": null, "note": "The June 2026 reports mention plans to expand the subject range and move toward registration review, but no later development was found.", "quote": null, "url": null }, "value": null, "developer_country": "China", "deployer_country": "China", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-06-09a2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://news.china.com/socialgd/10000169/20260606/49533586.html", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Xiangya_Hospital; https://en.wikipedia.org/wiki/Xiangya_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Xiangya Hospital.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: seven independent news reports and the makers' peer-reviewed study. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0208", "catalog_version": "1.0.0", "source_fingerprint": "59623807fb3992995825f6894b38d1ae0abf9b9a88377f9a9c6d6986fb81b420", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0208-source-0001", "AIBD-0208-source-0002", "AIBD-0208-source-0003", "AIBD-0208-source-0004", "AIBD-0208-source-0005", "AIBD-0208-source-0006", "AIBD-0208-source-0007", "AIBD-0208-source-0008" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Xiangya Hospital (Prof. Xu Huizhuo's team, per 2026 reports, which name no company); the IMIE 256 was co-developed by Golden Eye Bionics LLC (Pasadena) and IntelliMicro Medical Co., Ltd. (Changsha) and manufactured by IntelliMicro, per Xu et al. 2021", "deployer": "Xiangya Hospital, Central South University (Ophthalmology Center), in a Phase I clinical trial led by Prof. Xu Huizhuo" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The system is the whole substitute visual pathway. Camera glasses capture the scene. An external processor converts each frame in real time into stimulation patterns across 256 electrodes. The implant stimulates surviving ganglion cells whose signals reach the visual cortex. The patient had no vision before, so the benefit is attributable to the system together with structured rehabilitation. The 2026 reports describe the conversion only as an algorithm inside an “intelligent” retina. The 2021 IMIE 256 paper describes a video processing unit with a per-electrode threshold map and 15 gray levels and no learned model. How much of that processing is AI in a machine-learning sense is not established by these sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The IMIE system converted images from camera glasses into electrical stimulation through an implanted array. The patient also received rehabilitation to learn to use the resulting visual signals.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The system is the whole substitute visual pathway. Camera glasses capture the scene. An external processor converts each frame in real time into stimulation patterns across 256 electrodes. The implant stimulates surviving ganglion cells whose signals reach the visual cortex. The patient had no vision before, so the benefit is attributable to the system together with structured rehabilitation. The 2026 reports describe the conversion only as an algorithm inside an “intelligent” retina. The 2021 IMIE 256 paper describes a video processing unit with a per-electrode threshold map and 15 gray levels and no learned model. How much of that processing is AI in a machine-learning sense is not established by these sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable person, totally blind for more than ten years, regained enough vision to identify E optotypes (0.03, peak 0.1). She can walk indoors and through doorways without an escort. The hospital cautions that she does not yet have full self-care ability and needs long-term rehabilitation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: seven independent news reports and the makers' peer-reviewed study. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable person, totally blind for more than ten years, regained enough vision to identify E optotypes (0.03, peak 0.1). She can walk indoors and through doorways without an escort. The hospital cautions that she does not yet have full self-care ability and needs long-term rehabilitation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "One identifiable person, totally blind for more than ten years, regained enough vision to identify E optotypes (0.03, peak 0.1). She can walk indoors and through doorways without an escort. The hospital cautions that she does not yet have full self-care ability and needs long-term rehabilitation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { 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ScienceNet, 8 June 2026.", "title": "全国首例！脑机接口智能视网膜让盲人看见字符", "url": "https://news.sciencenet.cn/htmlnews/2026/6/566108.shtm", "date": "2026-06-08", "written_by": "independent", "quote": "4月23日，陈阿姨在湘雅医院完成IMIE智能视网膜植入手术" }, { "kind": "news report", "citation": "Tang Lu, Zhou Shun and Xiang Ying, Huasheng Online / Hunan Daily (2026). 国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明 [Domestic IMIE intelligent retina trial achieves major breakthrough; totally blind patient regains light]. hunan.voc.com.cn, 7 June 2026.", "title": "国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明", "url": "https://hunan.voc.com.cn/news/202606/32846000.html", "date": "2026-06-07", "written_by": "independent", "quote": "目前该患者已可识别E字视力表字符，无需他人陪护即可独自在室内走动、穿门而行" }, { "kind": "news report", "citation": "Yangcheng Evening News (2026). 中国首例！盲人凭脑机接口复明成功，实现自主行走 [China's first: blind person regains sight via brain-computer interface and walks independently]. Xinkuaibao (xkb.com.cn), 6 June 2026.", "title": "中国首例！盲人凭脑机接口复明成功，实现自主行走", "url": "https://www.xkb.com.cn/articleDetail/499962", "date": "2026-06-06", "written_by": "independent", "quote": "6月5日，湖南湘雅医院宣布完成全国首例侵入式脑机接口视觉重建临床试验" }, { "kind": "news report", "citation": "Yan Shuo, 21st Century Business Herald (2026). 失明患者重见光明：脑机接口加速落地，行业迎来量产前夜 [Blind patient regains sight: brain-computer interfaces accelerate, industry on the eve of mass production]. 21jingji.com, 8 June 2026.", "title": "失明患者重见光明：脑机接口加速落地，行业迎来量产前夜", "url": "https://www.21jingji.com/article/20260608/herald/908d9a3949ada35c98e6b666d4b41bc0.html", "date": "2026-06-08", "written_by": "independent", "quote": "目前患者尚不具备完全生活自理能力，后续仍需接受长期康复训练" }, { "kind": "news report", "citation": "Kuai Technology (2026). 国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1 [China's first blind person regains sight via brain-computer interface; measured peak acuity reaches 0.1]. 3DMGame, 6 June 2026.", "title": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1", "url": "https://www.3dmgame.com/news/202606/3945762.html", "date": "2026-06-06", "written_by": "independent", "quote": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1" }, { "kind": "news report", "citation": "Red Net (2026). 盲人患者使用侵入式脑机接口复明 视觉功能初步重建 [Blind patient regains sight with invasive brain-computer interface; visual function preliminarily rebuilt]. China.com, 6 June 2026.", "title": "盲人患者使用侵入式脑机接口复明 视觉功能初步重建", "url": "https://news.china.com/socialgd/10000169/20260606/49533586.html", "date": "2026-06-06", "written_by": "independent", "quote": "科研团队自主研发的IMIE智能视网膜系统" }, { "kind": "news report", "citation": "Securities Times (2026). 脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道 [Brain-computer interfaces reshape blindness treatment; Meihao Medical joins the new track]. Phoenix Finance (ifeng.com), 8 June 2026.", "title": "脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道", "url": "https://finance.ifeng.com/c/8tmrCoDSlTF", "date": "2026-06-08", "written_by": "independent", "quote": "国产256通道柔性电极阵列" }, { "kind": "peer-reviewed study", "citation": "Xu H, Zhong X, Pang C, Zou J, Chen W, Wang X, Li S, Hu Y, Sagan DS, Weiss PT, Yao Y, Xiang J, Dayan MS, Humayun MS, Tai YC (2021). First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256). Translational Vision Science & Technology 10(10):14. doi:10.1167/tvst.10.10.14; PMID 34705041.", "title": "First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256)", "url": "https://doi.org/10.1167/tvst.10.10.14", "date": "2021-08-01", "written_by": "makers", "quote": "The IMIE 256 implants were implanted in the right eyes of five subjects with end-stage retinitis pigmentosa." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0208-source-0001", "AIBD-0208-source-0002", "AIBD-0208-source-0003", "AIBD-0208-source-0004", "AIBD-0208-source-0005", "AIBD-0208-source-0006", "AIBD-0208-source-0007", "AIBD-0208-source-0008" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Wang Haohao and Tan Lianlian, China Science Daily (2026). 全国首例！脑机接口智能视网膜让盲人看见字符 [China's first: brain-computer interface smart retina lets a blind person see characters]. ScienceNet, 8 June 2026.", "title": "全国首例！脑机接口智能视网膜让盲人看见字符", "url": "https://news.sciencenet.cn/htmlnews/2026/6/566108.shtm", "date": "2026-06-08", "written_by": "independent", "quote": "4月23日，陈阿姨在湘雅医院完成IMIE智能视网膜植入手术" }, { "kind": "news report", "citation": "Tang Lu, Zhou Shun and Xiang Ying, Huasheng Online / Hunan Daily (2026). 国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明 [Domestic IMIE intelligent retina trial achieves major breakthrough; totally blind patient regains light]. hunan.voc.com.cn, 7 June 2026.", "title": "国产IMIE智能视网膜临床试验取得重大突破 全盲患者术后重获光明", "url": "https://hunan.voc.com.cn/news/202606/32846000.html", "date": "2026-06-07", "written_by": "independent", "quote": "目前该患者已可识别E字视力表字符，无需他人陪护即可独自在室内走动、穿门而行" }, { "kind": "news report", "citation": "Yangcheng Evening News (2026). 中国首例！盲人凭脑机接口复明成功，实现自主行走 [China's first: blind person regains sight via brain-computer interface and walks independently]. Xinkuaibao (xkb.com.cn), 6 June 2026.", "title": "中国首例！盲人凭脑机接口复明成功，实现自主行走", "url": "https://www.xkb.com.cn/articleDetail/499962", "date": "2026-06-06", "written_by": "independent", "quote": "6月5日，湖南湘雅医院宣布完成全国首例侵入式脑机接口视觉重建临床试验" }, { "kind": "news report", "citation": "Yan Shuo, 21st Century Business Herald (2026). 失明患者重见光明：脑机接口加速落地，行业迎来量产前夜 [Blind patient regains sight: brain-computer interfaces accelerate, industry on the eve of mass production]. 21jingji.com, 8 June 2026.", "title": "失明患者重见光明：脑机接口加速落地，行业迎来量产前夜", "url": "https://www.21jingji.com/article/20260608/herald/908d9a3949ada35c98e6b666d4b41bc0.html", "date": "2026-06-08", "written_by": "independent", "quote": "目前患者尚不具备完全生活自理能力，后续仍需接受长期康复训练" }, { "kind": "news report", "citation": "Kuai Technology (2026). 国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1 [China's first blind person regains sight via brain-computer interface; measured peak acuity reaches 0.1]. 3DMGame, 6 June 2026.", "title": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1", "url": "https://www.3dmgame.com/news/202606/3945762.html", "date": "2026-06-06", "written_by": "independent", "quote": "国内首例盲人凭脑机接口复明成功 实测视力峰值可达0.1" }, { "kind": "news report", "citation": "Red Net (2026). 盲人患者使用侵入式脑机接口复明 视觉功能初步重建 [Blind patient regains sight with invasive brain-computer interface; visual function preliminarily rebuilt]. China.com, 6 June 2026.", "title": "盲人患者使用侵入式脑机接口复明 视觉功能初步重建", "url": "https://news.china.com/socialgd/10000169/20260606/49533586.html", "date": "2026-06-06", "written_by": "independent", "quote": "科研团队自主研发的IMIE智能视网膜系统" }, { "kind": "news report", "citation": "Securities Times (2026). 脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道 [Brain-computer interfaces reshape blindness treatment; Meihao Medical joins the new track]. Phoenix Finance (ifeng.com), 8 June 2026.", "title": "脑机接口重塑失明治疗格局 美好医疗携手攻坚新赛道", "url": "https://finance.ifeng.com/c/8tmrCoDSlTF", "date": "2026-06-08", "written_by": "independent", "quote": "国产256通道柔性电极阵列" }, { "kind": "peer-reviewed study", "citation": "Xu H, Zhong X, Pang C, Zou J, Chen W, Wang X, Li S, Hu Y, Sagan DS, Weiss PT, Yao Y, Xiang J, Dayan MS, Humayun MS, Tai YC (2021). First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256). Translational Vision Science & Technology 10(10):14. doi:10.1167/tvst.10.10.14; PMID 34705041.", "title": "First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256)", "url": "https://doi.org/10.1167/tvst.10.10.14", "date": "2021-08-01", "written_by": "makers", "quote": "The IMIE 256 implants were implanted in the right eyes of five subjects with end-stage retinitis pigmentosa." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Blind over a decade, a 61-year-old woman read E optotypes and walked indoors unaided after a 256-channel IMIE retinal implant in Changsha.", "account": "On 23 April 2026 Prof. Xu Huizhuo's team implanted the IMIE intelligent retina in a 61-year-old woman known as Auntie Chen. The team is at Xiangya Hospital, Central South University, Changsha. The implant is a 256-channel epiretinal array driven by camera glasses and an external video processor. She was diagnosed with retinitis pigmentosa at 40 and had been blind for over ten years. Mark Humayun advised in theater, and no serious complications occurred. On 5 June 2026 the hospital announced that after over a month of rehabilitation she could identify E optotypes (acuity 0.03, peak 0.1). She could also walk indoors and through doorways without an escort. She is the first subject of a Phase I trial. The team says she lacks full self-care ability and will be observed for a year." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The participant’s retinal implant had 256 channels and followed the IMIE 256 device described in 2021." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "256-channel array; the device lineage is the IMIE 256 (Intelligent Micro Implant Eye, also called Theia α) reported in TVST 2021" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "IMIE intelligent retina (IMIE智能视网膜): 256-channel flexible epiretinal electrode array fixed on the macula, with camera glasses and an external video processing unit transmitting wirelessly to the implant" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Xiangya Hospital (Prof. Xu Huizhuo's team, per 2026 reports, which name no company); the IMIE 256 was co-developed by Golden Eye Bionics LLC (Pasadena) and IntelliMicro Medical Co., Ltd. (Changsha) and manufactured by IntelliMicro, per Xu et al. 2021" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "IMIE intelligent retina restores partial vision to a blind woman at Xiangya Hospital", "headline": "IMIE intelligent retina restores partial vision to a blind woman" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "59623807fb3992995825f6894b38d1ae0abf9b9a88377f9a9c6d6986fb81b420" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 23 April 2026 Prof. Xu Huizhuo's team implanted the IMIE intelligent retina in a 61-year-old woman known as Auntie Chen. The team is at Xiangya Hospital, Central South University, Changsha. The implant is a 256-channel epiretinal array driven by camera glasses and an external video processor. She was diagnosed with retinitis pigmentosa at 40 and had been blind for over ten years. Mark Humayun advised in theater, and no serious complications occurred. On 5 June 2026 the hospital announced that after over a month of rehabilitation she could identify E optotypes (acuity 0.03, peak 0.1). She could also walk indoors and through doorways without an escort. She is the first subject of a Phase I trial. The team says she lacks full self-care ability and will be observed for a year.", "replication": { "produced_by": [ "Surviving retinal ganglion cells and optic nerve in end-stage retinitis pigmentosa, so that epiretinal stimulation can reach the visual cortex", "A 256-channel flexible array fixed on the macula with 250-micrometer tacks and per-patient fitting of stimulation currents", "Camera glasses and an external processor converting live video into stimulation patterns in real time", "More than a month of structured visual rehabilitation after implantation", "A surgical team with prior IMIE 256 experience (five implants reported in TVST 2021) and on-site guidance from Mark Humayun" ], "must_hold": [ "The implant stays positioned on the macula without serious complications. The 2021 series saw one array movement and one hypotony", "Rehabilitation continues; the hospital's one-year observation period is still running", "The reported acuity (0.03, peak 0.1) is phosphene vision, not natural sight. The hospital says the patient lacks full self-care ability" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0280", "title": "AI-supported planning and skull-implant design in the separation of craniopagus twins Mercy and Goodness", "summary": "PureHealth/SKMC statement (5 June 2026) cites “AI-enhanced surgical planning”; XRlabs' own release claims AI-designed implants. The twins were separated in four operations and returned to Nigeria.", "date_observed": "2026-06-05", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "PureHealth reported on June 5, 2026 that surgeons at Sheikh Khalifa Medical City in Abu Dhabi had separated Nigerian twins Mercy and Goodness. More than 60 clinicians took part in four staged procedures, led by Noor ul Owase Jeelani of Gemini Untwined. The hospital credited AI-assisted planning, mixed reality, and custom titanium skull grafts. On June 19, XRlabs identified its implant-design platform and said that its model used infant head shapes to generate patient-specific implants from CT data. The company also described surgical rehearsal in a shared virtual environment and reported that the twins had returned home. These are accounts from the treating institution and technology supplier. They establish a claimed AI contribution to a successful surgical procedure, without measuring how much AI improved the result. The reports differ on age and timing, and do not provide an exact operation date.", "category": "benefit created", "unexpected": false, "purpose": "XRlabs says its platform is built to design patient-specific implants and plan operations in mixed reality. The hospital's “AI-enhanced surgical planning” is described only generically. Implant design for this separation was the vendor's stated purpose.", "system": "XRlabs 'Surgical Intelligence' platform for AI-designed skull implants (identified only by the vendor) and unnamed 'AI-enhanced surgical planning' (PureHealth statement)", "model_version": null, "developer": "XRlabs (implant design, per its own release); the hospital names no developer for the planning tools", "deployer": "PureHealth - SEHA Sheikh Khalifa Medical City, Abu Dhabi, with Gemini Untwined (Professor Noor Ul Owase Jeelani)", "location": "Abu Dhabi, United Arab Emirates", "domain": "Healthcare - pediatric neurosurgery and craniofacial surgery", "segment": "Craniopagus twin separation: surgical planning and patient-specific implants", "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's claimed part is surgical planning; the good recorded is the twins' separation.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "Two children joined at the head were separated, reconstructed and discharged home to Nigeria, per the hospital and press. The surgical team produced this outcome, and no source quantifies the AI's share of it." }, { "group": "organizational", "depth": null, "reason": "XRlabs claims that implant design took seconds, but supplies no measured comparison with manual design or independently verified planning-time saving." } ], "ai_role": { "status": "assessed", "statement": "The treating institution identifies AI-assisted planning, and XRlabs describes an AI model for patient-specific skull-implant design. Both participated in the procedure. Neither provides a comparison without AI or a clinical evaluation that separates the model’s contribution from the surgical team’s work." }, "evidence": [ { "kind": "press release", "citation": "Abu Dhabi Media Office / PureHealth (2026). PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi. 5 June 2026 (the hospital group's own statement).", "title": "PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi", "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "date": "2026-06-05", "written_by": "deployer", "quote": "mixed reality-guided implant design and AI-enhanced surgical planning" }, { "kind": "press release", "citation": "XRlabs, “XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation,” Business Wire, June 19, 2026; authorized distribution via Marketminute. Original release identifier 20260618045531.", "title": "XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation", "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "date": "2026-06-19", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A multidisciplinary surgical team performing four staged procedures", "CT-derived 3D models, mixed-reality rehearsal, and patient-specific skull implants", "Specialist coordination by Gemini Untwined and the treating hospital" ], "must_hold": [ "A surgical team able to act on AI-assisted plans and patient-specific implants", "Imaging of sufficient quality to model the twins' shared vasculature and skull", "The vendor's claims about the implant-design AI are not independently documented, so the AI's share cannot be assumed to transfer" ], "echoes": [] }, "paired_incident": null, "headline": "AI planning may have helped SKMC separate craniopagus twins", "metric": "successful separation in four staged procedures", "comparator": null, "later": { "status": "persisted", "date": "2026-06-19", "note": "XRlabs reported that the twins had recovered and returned home. The release gives no clinical follow-up interval or independent assessment of the AI contribution.", "quote": null, "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation" }, "value": null, "developer_country": null, "deployer_country": "United Arab Emirates", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria; https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheikh_Khalifa_Medical_City", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed an unsupported case-specific comparator and retained the general assertion and its limitations in source notes.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the makers' press release and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0280", "catalog_version": "1.0.0", "source_fingerprint": "7bc7f1b0f7c137ba75f7b7db2d94a31842ccc4a8c738a04796e32974baa7eeb8", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "XRlabs (implant design, per its own release); the hospital names no developer for the planning tools", "deployer": "PureHealth - SEHA Sheikh Khalifa Medical City, Abu Dhabi, with Gemini Untwined (Professor Noor Ul Owase Jeelani)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The treating institution identifies AI-assisted planning, and XRlabs describes an AI model for patient-specific skull-implant design. 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}, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "successful separation in four staged procedures", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "persisted", "date": "2026-06-19", "note": "XRlabs reported that the twins had recovered and returned home. The release gives no clinical follow-up interval or independent assessment of the AI contribution.", "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation" } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0280" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "The AI's claimed part is surgical planning; the good recorded is the twins' separation." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "PureHealth reported on June 5, 2026 that surgeons at Sheikh Khalifa Medical City in Abu Dhabi had separated Nigerian twins Mercy and Goodness. More than 60 clinicians took part in four staged procedures, led by Noor ul Owase Jeelani of Gemini Untwined. The hospital credited AI-assisted planning, mixed reality, and custom titanium skull grafts. On June 19, XRlabs identified its implant-design platform and said that its model used infant head shapes to generate patient-specific implants from CT data. The company also described surgical rehearsal in a shared virtual environment and reported that the twins had returned home. These are accounts from the treating institution and technology supplier. They establish a claimed AI contribution to a successful surgical procedure, without measuring how much AI improved the result. The reports differ on age and timing, and do not provide an exact operation date.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The twins were separated in four staged operations and returned home.", "editor_note": "" } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "Two children joined at the head were separated, reconstructed and discharged home to Nigeria, per the hospital and press. The surgical team produced this outcome, and no source quantifies the AI's share of it." }, { "group": "organizational", "reason": "XRlabs claims that implant design took seconds, but supplies no measured comparison with manual design or independently verified planning-time saving." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "XRlabs says its platform is built to design patient-specific implants and plan operations in mixed reality. The hospital's “AI-enhanced surgical planning” is described only generically. Implant design for this separation was the vendor's stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Abu Dhabi, United Arab Emirates", "deployer_country": "United Arab Emirates" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "XRlabs says its platform is built to design patient-specific implants and plan operations in mixed reality. The hospital's “AI-enhanced surgical planning” is described only generically. Implant design for this separation was the vendor's stated purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-06-05", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria; https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheikh_Khalifa_Medical_City", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed an unsupported case-specific comparator and retained the general assertion and its limitations in source notes.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "The original hospital statement claims the fastest recorded separation of vertically conjoined twins but supplies no duration or comparative series. The excluded Local12 article’s narrower “nine cases” assertion has not been traced to an inspectable original.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A multidisciplinary surgical team performing four staged procedures", "CT-derived 3D models, mixed-reality rehearsal, and patient-specific skull implants", "Specialist coordination by Gemini Untwined and the treating hospital" ], "must_hold": [ "A surgical team able to act on AI-assisted plans and patient-specific implants", "Imaging of sufficient quality to model the twins' shared vasculature and skull", "The vendor's claims about the implant-design AI are not independently documented, so the AI's share cannot be assumed to transfer" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "replication" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Specialists need imaging that shows the shared blood vessels and skull, together with the ability to use the plans and implants safely. The reported benefit does not establish how much the AI would contribute in another operation.", "editor_note": "" } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, what happened since from the cited sources.", "source": "https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria; https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Sheikh_Khalifa_Medical_City", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Removed an unsupported case-specific comparator and retained the general assertion and its limitations in source notes.", "source": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "The original hospital statement claims the fastest recorded separation of vertically conjoined twins but supplies no duration or comparative series. The excluded Local12 article’s narrower “nine cases” assertion has not been traced to an inspectable original.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare - pediatric neurosurgery and craniofacial surgery", "segment": "Craniopagus twin separation: surgical planning and patient-specific implants" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "access": "full original institutional release read" }, { "url": "https://www.businesswire.com/news/home/20260618045531/en/", "access": "direct original denied access" }, { "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "access": "full authorized Business Wire distribution read" }, { "url": "https://transcripts.cnn.com/show/cnc/date/2026-06-22/segment/02", "access": "relevant twins segment read" } ] } }, "provenance": { "kind": "source_review", "basis": "Recorded which versions were inspected and which origins or supplements could not be read.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital’s original release and an authorized Business Wire copy of XRlabs’ release are available. CNN’s transcript covers the same surgical account. The referenced BBC documentary was not inspected.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Abu Dhabi Media Office / PureHealth (2026). PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi. 5 June 2026 (the hospital group's own statement).", "title": "PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi", "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "date": "2026-06-05", "written_by": "deployer", "quote": "mixed reality-guided implant design and AI-enhanced surgical planning" }, { "kind": "press release", "citation": "XRlabs, “XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation,” Business Wire, June 19, 2026; authorized distribution via Marketminute. Original release identifier 20260618045531.", "title": "XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation", "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "date": "2026-06-19", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "role": "Retained evidence entries in reviewed order for this fingerprinted record version" }, "provenance": { "kind": "source_review", "basis": "Assigned to the retained evidence entries after this source review.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Abu Dhabi Media Office / PureHealth (2026). PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi. 5 June 2026 (the hospital group's own statement).", "title": "PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi", "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "date": "2026-06-05", "written_by": "deployer", "quote": "mixed reality-guided implant design and AI-enhanced surgical planning" }, { "kind": "press release", "citation": "XRlabs, “XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation,” Business Wire, June 19, 2026; authorized distribution via Marketminute. Original release identifier 20260618045531.", "title": "XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation", "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "date": "2026-06-19", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0280-source-0001" ], "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "title": "PureHealth performs GCC's first separation of craniopagus twins' procedure in Abu Dhabi", "published_on": "2026-06-05", "relationship": "PureHealth’s account was published by Abu Dhabi Media Office and is testimony from the treating institution." }, { "source_refs": [ "AIBD-0280-source-0002" ], "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "title": "XRlabs Achieves World First in AI-Designed Implants for Conjoined Twin Separation", "published_on": "2026-06-19", "relationship": "XRlabs’ Business Wire release provides the system-specific mechanism and later recovery statement. The readable Marketminute page is a distribution of that release, not a second report or independent verification." } ], "excluded_republications": [ { "url": "https://local12.com/news/nation-world/conjoined-twins-separated-virtual-reality-surgery-sheikh-khalifa-medical-city-abu-dhabi-craniopagus-nigeria", "citation": "CNN Newsource via WKRC Local 12 (2026). These twins had never seen each other's faces -- until a complex surgery separated them. 22 June 2026.", "relationship": "The National and Khaleej Times repeat the institutional announcement without additional AI evidence. CNN/WKRC summarizes the same procedure. Medical Product Outsourcing relays the XRlabs release, which is retained in its full authorized distribution." }, { "url": "https://www.thenationalnews.com/news/uae/2026/06/05/conjoined-twins-named-mercy-and-goodness-separated-after-abu-dhabi-surgery/", "citation": "The National (2026). Conjoined twins named Mercy and Goodness separated after Abu Dhabi surgery. 5 June 2026 (does not mention AI).", "relationship": "The National and Khaleej Times repeat the institutional announcement without additional AI evidence. CNN/WKRC summarizes the same procedure. Medical Product Outsourcing relays the XRlabs release, which is retained in its full authorized distribution." }, { "url": "https://www.khaleejtimes.com/uae/abu-dhabi-craniopagus-twins-separation-surgery", "citation": "Dajani H (2026). Video: Conjoined twins separated in 4 complex surgeries by Abu Dhabi hospital. Khaleej Times, 5 June 2026 (does not mention AI).", "relationship": "The National and Khaleej Times repeat the institutional announcement without additional AI evidence. CNN/WKRC summarizes the same procedure. Medical Product Outsourcing relays the XRlabs release, which is retained in its full authorized distribution." }, { "url": "https://www.mpo-mag.com/breaking-news/xrlabs-pioneers-ai-designed-implants-in-historic-conjoined-twin-separation/", "citation": "XRlabs (2026). XRlabs Pioneers AI-Designed Implants in Historic Conjoined Twin Separation. Business Wire press release, 19 June 2026, as carried by Medical Product Outsourcing (vendor's own account).", "relationship": "The National and Khaleej Times repeat the institutional announcement without additional AI evidence. CNN/WKRC summarizes the same procedure. Medical Product Outsourcing relays the XRlabs release, which is retained in its full authorized distribution." } ], "lead_source_ref": "AIBD-0280-source-0001", "retained_source_order": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "ordering_basis": "The first source directly supports the reported benefit or is the closest accessible original account. Each additional source has a distinct evidentiary contribution described in its relationship. Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "The twins were separated through four staged procedures with AI-assisted planning and custom titanium grafts.", "source_ref": "AIBD-0280-source-0001", "source_chain": [ { "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "locator": "Paragraphs beginning “Over six months,” “The seamless integration,” and “Coordinating with Gemini Untwined”", "role": "PureHealth’s account was published by Abu Dhabi Media Office and is testimony from the treating institution." } ], "locator": "Paragraphs beginning “Over six months,” “The seamless integration,” and “Coordinating with Gemini Untwined”", "method": {}, "limitations": [ "Institutional claims of greater safety and fastest separation lack a comparative clinical analysis." ] }, { "claim": "XRlabs supplied AI-designed skull implants using CT models and infant head-shape training data, and supported rehearsal.", "source_ref": "AIBD-0280-source-0002", "source_chain": [ { "url": "https://www.businesswire.com/news/home/20260618045531/en/", "role": "original Business Wire release, direct access denied" }, { "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "role": "authorized full-text distribution of the same release" } ], "locator": "Release paragraphs 1–6", "method": { "reported_training_domain": "similarly aged infant head shapes", "workflow": "CT-derived 3D models, mixed reality, implant design, surgical rehearsal" }, "limitations": [ "No model version, training cohort, accuracy evaluation, or clinical comparison is supplied." ] }, { "claim": "XRlabs reported that surgery took place in 2025 and that the twins had returned home.", "source_ref": "AIBD-0280-source-0002", "source_chain": [ { "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "locator": "Release paragraph 2", "role": "XRlabs’ Business Wire release provides the system-specific mechanism and later recovery statement. The readable Marketminute page is a distribution of that release, not a second report or independent verification." } ], "locator": "Release paragraph 2", "method": {}, "limitations": [ "The June 5 hospital release describes the twins as 15 months old and still recovering in the UAE. Later reports describe a different age/timeline. The exact operation date remains unresolved." ] } ], "limitations": [ "No clinical paper or patient-level operative record was linked in the two retained releases.", "The BBC documentary mentioned by XRlabs was not watched; it is a further lead, not inspected evidence.", "CNN’s June 22 broadcast transcript was located and read for the twins segment, but it summarizes the same surgical account and does not independently test the AI contribution.", "The exact ages and operation dates should not be inferred from inconsistent press descriptions." ], "access_audit": [ { "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "access": "full original institutional release read" }, { "url": "https://www.businesswire.com/news/home/20260618045531/en/", "access": "direct original denied access" }, { "url": "https://wqow.marketminute.com/article/bizwire-2026-6-19-xrlabs-achieves-world-first-in-ai-designed-implants-for-conjoined-twin-separation", "access": "full authorized Business Wire distribution read" }, { "url": "https://transcripts.cnn.com/show/cnc/date/2026-06-22/segment/02", "access": "relevant twins segment read" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified.", "contextual_comparisons": [ { "url": "https://www.mediaoffice.abudhabi/en/health/purehealth-performs-gccs-first-separation-of-craniopagus-twins-procedure-in-abu-dhabi/", "locator": "Final clinical paragraphs, following the description of AI-enhanced surgical planning.", "finding": "The original hospital statement claims the fastest recorded separation of vertically conjoined twins but supplies no duration or comparative series. The excluded Local12 article’s narrower “nine cases” assertion has not been traced to an inspectable original.", "use": "Context only; no case-specific comparison established." } ] } }, "provenance": { "kind": "source_review", "basis": "Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The hospital and XRlabs describe their own roles in the surgery. Their releases link no clinical paper or operative records. Other reporting repeats that account, and the BBC documentary was not inspected.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "PureHealth/SKMC statement (5 June 2026) cites “AI-enhanced surgical planning”; XRlabs' own release claims AI-designed implants. The twins were separated in four operations and returned to Nigeria.", "account": "PureHealth reported on June 5, 2026 that surgeons at Sheikh Khalifa Medical City in Abu Dhabi had separated Nigerian twins Mercy and Goodness. More than 60 clinicians took part in four staged procedures, led by Noor ul Owase Jeelani of Gemini Untwined. The hospital credited AI-assisted planning, mixed reality, and custom titanium skull grafts. On June 19, XRlabs identified its implant-design platform and said that its model used infant head shapes to generate patient-specific implants from CT data. The company also described surgical rehearsal in a shared virtual environment and reported that the twins had returned home. These are accounts from the treating institution and technology supplier. They establish a claimed AI contribution to a successful surgical procedure, without measuring how much AI improved the result. The reports differ on age and timing, and do not provide an exact operation date." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The hospital describes AI-assisted surgical planning, and XRlabs reports that it designed implants with AI. The twins were separated in four operations and returned to Nigeria.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "XRlabs 'Surgical Intelligence' platform for AI-designed skull implants (identified only by the vendor) and unnamed 'AI-enhanced surgical planning' (PureHealth statement)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "XRlabs (implant design, per its own release); the hospital names no developer for the planning tools" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-supported planning and skull-implant design in the separation of craniopagus twins Mercy and Goodness", "headline": "AI planning may have helped SKMC separate craniopagus twins" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7bc7f1b0f7c137ba75f7b7db2d94a31842ccc4a8c738a04796e32974baa7eeb8" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "PureHealth reported on June 5, 2026 that surgeons at Sheikh Khalifa Medical City in Abu Dhabi had separated Nigerian twins Mercy and Goodness. More than 60 clinicians took part in four staged procedures, led by Noor ul Owase Jeelani of Gemini Untwined. The hospital credited AI-assisted planning, mixed reality, and custom titanium skull grafts. On June 19, XRlabs identified its implant-design platform and said that its model used infant head shapes to generate patient-specific implants from CT data. The company also described surgical rehearsal in a shared virtual environment and reported that the twins had returned home. These are accounts from the treating institution and technology supplier. They establish a claimed AI contribution to a successful surgical procedure, without measuring how much AI improved the result. The reports differ on age and timing, and do not provide an exact operation date.", "replication": { "produced_by": [ "A multidisciplinary surgical team performing four staged procedures", "CT-derived 3D models, mixed-reality rehearsal, and patient-specific skull implants", "Specialist coordination by Gemini Untwined and the treating hospital" ], "must_hold": [ "A surgical team able to act on AI-assisted plans and patient-specific implants", "Imaging of sufficient quality to model the twins' shared vasculature and skull", "The vendor's claims about the implant-design AI are not independently documented, so the AI's share cannot be assumed to transfer" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Retained the original hospital account and recovered XRlabs’ full original release through authorized distribution. Removed intermediary summaries and avoided resolving conflicting age and operation timing by assumption.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0280-source-0001", "AIBD-0280-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Specialists used CT images to make three-dimensional models, rehearse the surgery in mixed reality, and design skull implants for the twins. Gemini Untwined and the hospital coordinated four staged procedures.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 30, "reviewed": 19, "record_mapped": 11, "not_assessed": 61, "complete": false, "by_state": { "value_present": 30, "not_reported": 0, "unresolved": 0, "not_assessed": 61, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0010", "title": "Meta self-harm alert routed to Uttar Pradesh Police leads to hospital treatment of a 25-year-old in Meerut within eight minutes", "summary": "7 June 2026: Meta alert at 6:53 pm; Meerut police reached a 25-year-old in 8 minutes, found him critical; hospital treatment, improved", "date_observed": "2026-06-07", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On 7 June 2026 a 25-year-old man from the Sardhana area of Meerut, Uttar Pradesh, posted an Instagram video. In it he appeared to drink a white liquid. Police said Meta sent a suicide alert about the post to the Social Media Center at Uttar Pradesh Police headquarters at 6:53 pm. The center alerted Meerut Police, and a Sardhana team reached his home within eight minutes. They found him in a critical condition with a bottle of suspected liquid nearby and took him to hospital, where his condition improved after treatment. He told police he was under stress following the end of a relationship. Police data cited by PTI credit such alerts with 3,011 lives saved statewide from 1 January 2023 to 31 May 2026.", "category": "harm prevented", "unexpected": false, "purpose": "Built to flag posts and live videos indicating suicide or self-harm risk for review and, in imminent cases, referral to emergency services. This benefit is that purpose.", "system": "Meta proactive self-harm detection on Instagram with alert routing to the Uttar Pradesh Police Social Media Center", "model_version": null, "developer": "Meta Platforms", "deployer": "Meta Platforms with the Uttar Pradesh Police Social Media Center (agreement signed March 2022)", "location": "Meerut, India", "domain": "Suicide prevention / online safety", "segment": "Social media platforms and police", "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health.", "registry_ids": { "oecd_aim": "2026-06-08-7d81" }, "ratings": [ { "group": "personal", "depth": 4, "reason": "Police found him in a critical condition after apparent ingestion, and he was treated in hospital within minutes of the alert. Police describe the outcome as a life saved." } ], "ai_role": { "status": "assessed", "statement": "Police sources say Meta sent the alert after the post. They do not state whether Meta's classifier or a user report flagged it. Meta's documentation and NPR describe the process as machine-learning detection with human review before contacting authorities. The record relies on that description and should be read with that caveat." }, "evidence": [ { "kind": "news report", "citation": "PTI (2026). When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post. Deccan Herald.", "title": "When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post", "url": "https://www.deccanherald.com/india/uttar-pradesh/when-every-minute-counts-uttar-pradesh-police-save-youth-attempting-suicide-in-8-minutes-after-meta-alert-over-instagram-post-4032393", "date": "2026-06-09", "written_by": "independent", "quote": "flags posts indicating possible self-harm and shares alerts with authorities" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent", "quote": "Police said Meta sent a suicide alert regarding the post to the Social Media Centre at the police headquarters at 6.53 pm." }, { "kind": "news report", "citation": "Kaste, M. (2018). Facebook Increasingly Reliant On A.I. To Predict Suicide Risk. NPR (transcript republished by North Country Public Radio).", "title": "Facebook Increasingly Reliant On A.I. To Predict Suicide Risk", "url": "https://www.northcountrypublicradio.org/news/npr/668408122/facebook-increasingly-reliant-on-a-i-to-predict-suicide-risk", "date": "2018-11-17", "written_by": "independent", "quote": "We also are able to use AI to coordinate a bunch of information on location to try to identify the location of that individual" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it's determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "news report", "citation": "PTI (2023). Facebook helps UP Police avert two suicides in a week in state. The Tribune.", "title": "Facebook helps UP Police avert two suicides in a week in state", "url": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp", "date": "2023-02-05", "written_by": "independent", "quote": "Meta Hqs USA immediately sends an alert to the social media centre of PHQ UP Police through phone and email" }, { "kind": "news report", "citation": "PTI (2021). Man saved by Delhi Police after Facebook alerts on self-harm video. The Tribune.", "title": "Man saved by Delhi Police after Facebook alerts on self-harm video", "url": "https://www.tribuneindia.com/news/delhi/man-saved-by-delhi-police-after-facebook-alerts-on-self-harm-video-263850/amp", "date": "2021-06-05", "written_by": "independent", "quote": "received a call alert from Facebook's US office about a suspicious self-harm live video being posted by a male Facebook user located in Delhi" } ], "replication": { "produced_by": [ "Platform detection and review that flags self-harm posts and contacts a police nodal center with account phone and location details", "Police nodal center with a standing arrangement to dispatch local officers immediately" ], "must_hold": [ "Account details resolve to a reachable address within minutes", "Local officers are available to respond immediately" ], "echoes": [ { "date": null, "setting": "Dwarka, Delhi (reported 5 June 2021): Delhi Police CyPAD received a Facebook alert at about 12:50 am on a self-harm live video; the man was found with heavy blood loss, taken to hospital and AIIMS Trauma Center, condition stable (PTI/The Tribune)", "model_version": null, "outcome": "recurred", "source": "https://www.tribuneindia.com/news/delhi/man-saved-by-delhi-police-after-facebook-alerts-on-self-harm-video-263850/amp" }, { "date": null, "setting": "Ambedkarnagar, Uttar Pradesh (late January 2023): Meta alert at 11:37 pm on a student's Instagram photos of pills; police arrived within 15 minutes and prevented the attempt (PTI/The Tribune, 5 February 2023)", "model_version": null, "outcome": "recurred", "source": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp" }, { "date": "2023-01-31", "setting": "Ghaziabad, Uttar Pradesh: Instagram live of a man preparing to hang himself; Inspector Anita Chauhan arrived within 13 minutes and prevented the attempt (PTI/The Tribune, 5 February 2023)", "model_version": null, "outcome": "recurred", "source": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp" }, { "date": null, "setting": "Upstate New York, from a Facebook promotional video described by NPR (17 November 2018): officers found a woman who had taken medication and got her to a local hospital", "model_version": null, "outcome": "recurred", "source": "https://www.northcountrypublicradio.org/news/npr/668408122/facebook-increasingly-reliant-on-a-i-to-predict-suicide-risk" } ] }, "paired_incident": { "database": "AI Incident Database", "identifier": "382", "title": "Instagram's Exposure of Harmful Content Allegedly Contributed to Teenage Girl's Suicide", "url": "https://incidentdatabase.ai/cite/382", "severity": null, "group": "personal", "basis": "Same developer and platform, Meta's Instagram, and the same at-risk user group: Instagram's recommendation of suicide and self-harm content was ruled to have contributed to Molly Russell's death, where the Meerut alert reached a user in time." }, "headline": "Meta self-harm alert gets Meerut police to a man in 8 minutes", "metric": "3,011 lives saved statewide from 1 January 2023 to 31 May 2026", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No development dated after the 7 June 2026 case was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 382 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/382", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; https://en.wikipedia.org/wiki/Meta_Platforms", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Meta Platforms.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0010", "catalog_version": "1.0.0", "source_fingerprint": "343d2f4067b78a2fb96d5b25eda3d840e5bf4035a99427db5e079f2fbcdc2624", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0010-source-0001", "AIBD-0010-source-0002", "AIBD-0010-source-0003", "AIBD-0010-source-0004", "AIBD-0010-source-0005", "AIBD-0010-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Meta Platforms", "deployer": "Meta Platforms with the Uttar Pradesh Police Social Media Center (agreement signed March 2022)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "Police sources say Meta sent the alert after the post. They do not state whether Meta's classifier or a user report flagged it. Meta's documentation and NPR describe the process as machine-learning detection with human review before contacting authorities. The record relies on that description and should be read with that caveat." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "Police sources say Meta sent the alert after the post. They do not state whether Meta's classifier or a user report flagged it. Meta's documentation and NPR describe the process as machine-learning detection with human review before contacting authorities. The record relies on that description and should be read with that caveat." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "Police found him in a critical condition after apparent ingestion, and he was treated in hospital within minutes of the alert. Police describe the outcome as a life saved." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "Police found him in a critical condition after apparent ingestion, and he was treated in hospital within minutes of the alert. Police describe the outcome as a life saved." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "Police found him in a critical condition after apparent ingestion, and he was treated in hospital within minutes of the alert. Police describe the outcome as a life saved." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "value_present", "value": { "kind": "structured", "data": { "answer": "Same developer and platform, Meta's Instagram, and the same at-risk user group: Instagram's recommendation of suicide and self-harm content was ruled to have contributed to Molly Russell's death, where the Meerut alert reached a user in time.", "links": [ { "database": "AI Incident Database", "identifier": "382", "title": "Instagram's Exposure of Harmful Content Allegedly Contributed to Teenage Girl's Suicide", "url": "https://incidentdatabase.ai/cite/382", "group": "personal", "basis": "Same developer and platform, Meta's Instagram, and the same at-risk user group: Instagram's recommendation of suicide and self-harm content was ruled to have contributed to Molly Russell's death, where the Meerut alert reached a user in time.", "relation": "comparable_harm" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Existing paired_incident classification; no new source review.", "record_fields": [ "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "3,011 lives saved statewide from 1 January 2023 to 31 May 2026", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-06-08-7d81" }, "paired_incident": { "database": "AI Incident Database", "identifier": "382", "title": "Instagram's Exposure of Harmful Content Allegedly Contributed to Teenage Girl's Suicide", "url": "https://incidentdatabase.ai/cite/382", "group": "personal", "basis": "Same developer and platform, Meta's Instagram, and the same at-risk user group: Instagram's recommendation of suicide and self-harm content was ruled to have contributed to Molly Russell's death, where the Meerut alert reached a user in time." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids", "paired_incident" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No development dated after the 7 June 2026 case was found in the cited sources." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0010" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Improved Physical Health", "taxonomy_note": "A suicide intervention; Trustible's only health type is physical health." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 7 June 2026 a 25-year-old man from the Sardhana area of Meerut, Uttar Pradesh, posted an Instagram video. In it he appeared to drink a white liquid. Police said Meta sent a suicide alert about the post to the Social Media Center at Uttar Pradesh Police headquarters at 6:53 pm. The center alerted Meerut Police, and a Sardhana team reached his home within eight minutes. They found him in a critical condition with a bottle of suspected liquid nearby and took him to hospital, where his condition improved after treatment. He told police he was under stress following the end of a relationship. Police data cited by PTI credit such alerts with 3,011 lives saved statewide from 1 January 2023 to 31 May 2026.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "Police found him in a critical condition after apparent ingestion, and he was treated in hospital within minutes of the alert. 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This benefit is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-06-07", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Paired with AI Incident Database incident 382 (high confidence); severity not given by the source.", "source": "https://incidentdatabase.ai/cite/382", "editor": "AIBD" }, { "date": "2026-10-20", "change": "Linked the OECD AI Incidents entry, which describes this event.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Meta_Platforms; 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When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post. Deccan Herald.", "title": "When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post", "url": "https://www.deccanherald.com/india/uttar-pradesh/when-every-minute-counts-uttar-pradesh-police-save-youth-attempting-suicide-in-8-minutes-after-meta-alert-over-instagram-post-4032393", "date": "2026-06-09", "written_by": "independent", "quote": "flags posts indicating possible self-harm and shares alerts with authorities" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent", "quote": "Police said Meta sent a suicide alert regarding the post to the Social Media Centre at the police headquarters at 6.53 pm." }, { "kind": "news report", "citation": "Kaste, M. (2018). Facebook Increasingly Reliant On A.I. To Predict Suicide Risk. NPR (transcript republished by North Country Public Radio).", "title": "Facebook Increasingly Reliant On A.I. To Predict Suicide Risk", "url": "https://www.northcountrypublicradio.org/news/npr/668408122/facebook-increasingly-reliant-on-a-i-to-predict-suicide-risk", "date": "2018-11-17", "written_by": "independent", "quote": "We also are able to use AI to coordinate a bunch of information on location to try to identify the location of that individual" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it's determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "news report", "citation": "PTI (2023). Facebook helps UP Police avert two suicides in a week in state. The Tribune.", "title": "Facebook helps UP Police avert two suicides in a week in state", "url": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp", "date": "2023-02-05", "written_by": "independent", "quote": "Meta Hqs USA immediately sends an alert to the social media centre of PHQ UP Police through phone and email" }, { "kind": "news report", "citation": "PTI (2021). Man saved by Delhi Police after Facebook alerts on self-harm video. The Tribune.", "title": "Man saved by Delhi Police after Facebook alerts on self-harm video", "url": "https://www.tribuneindia.com/news/delhi/man-saved-by-delhi-police-after-facebook-alerts-on-self-harm-video-263850/amp", "date": "2021-06-05", "written_by": "independent", "quote": "received a call alert from Facebook's US office about a suspicious self-harm live video being posted by a male Facebook user located in Delhi" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0010-source-0001", "AIBD-0010-source-0002", "AIBD-0010-source-0003", "AIBD-0010-source-0004", "AIBD-0010-source-0005", "AIBD-0010-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "PTI (2026). When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post. Deccan Herald.", "title": "When every minute counts: Uttar Pradesh Police save youth attempting suicide in 8 minutes after Meta alert over Instagram post", "url": "https://www.deccanherald.com/india/uttar-pradesh/when-every-minute-counts-uttar-pradesh-police-save-youth-attempting-suicide-in-8-minutes-after-meta-alert-over-instagram-post-4032393", "date": "2026-06-09", "written_by": "independent", "quote": "flags posts indicating possible self-harm and shares alerts with authorities" }, { "kind": "news report", "citation": "The Hans India (2026). Cops save man in 8 mins after suicide alert on Insta.", "title": "Cops save man in 8 mins after suicide alert on Insta", "url": "https://www.thehansindia.com/news/national/cops-save-man-in-8-mins-after-suicide-alert-on-insta-1084758", "date": "2026-06-10", "written_by": "independent", "quote": "Police said Meta sent a suicide alert regarding the post to the Social Media Centre at the police headquarters at 6.53 pm." }, { "kind": "news report", "citation": "Kaste, M. (2018). Facebook Increasingly Reliant On A.I. To Predict Suicide Risk. NPR (transcript republished by North Country Public Radio).", "title": "Facebook Increasingly Reliant On A.I. To Predict Suicide Risk", "url": "https://www.northcountrypublicradio.org/news/npr/668408122/facebook-increasingly-reliant-on-a-i-to-predict-suicide-risk", "date": "2018-11-17", "written_by": "independent", "quote": "We also are able to use AI to coordinate a bunch of information on location to try to identify the location of that individual" }, { "kind": "press release", "citation": "Card, C. (2018). How Facebook AI Helps Suicide Prevention. Meta Newsroom.", "title": "How Facebook AI Helps Suicide Prevention", "url": "https://about.fb.com/news/2018/09/inside-feed-suicide-prevention-and-ai/", "date": "2018-09-10", "written_by": "makers", "quote": "In serious cases, when it's determined that there may be imminent danger of self harm, Facebook may contact local authorities." }, { "kind": "news report", "citation": "PTI (2023). Facebook helps UP Police avert two suicides in a week in state. The Tribune.", "title": "Facebook helps UP Police avert two suicides in a week in state", "url": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp", "date": "2023-02-05", "written_by": "independent", "quote": "Meta Hqs USA immediately sends an alert to the social media centre of PHQ UP Police through phone and email" }, { "kind": "news report", "citation": "PTI (2021). Man saved by Delhi Police after Facebook alerts on self-harm video. The Tribune.", "title": "Man saved by Delhi Police after Facebook alerts on self-harm video", "url": "https://www.tribuneindia.com/news/delhi/man-saved-by-delhi-police-after-facebook-alerts-on-self-harm-video-263850/amp", "date": "2021-06-05", "written_by": "independent", "quote": "received a call alert from Facebook's US office about a suspicious self-harm live video being posted by a male Facebook user located in Delhi" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "7 June 2026: Meta alert at 6:53 pm; Meerut police reached a 25-year-old in 8 minutes, found him critical; hospital treatment, improved", "account": "On 7 June 2026 a 25-year-old man from the Sardhana area of Meerut, Uttar Pradesh, posted an Instagram video. In it he appeared to drink a white liquid. Police said Meta sent a suicide alert about the post to the Social Media Center at Uttar Pradesh Police headquarters at 6:53 pm. The center alerted Meerut Police, and a Sardhana team reached his home within eight minutes. They found him in a critical condition with a bottle of suspected liquid nearby and took him to hospital, where his condition improved after treatment. He told police he was under stress following the end of a relationship. Police data cited by PTI credit such alerts with 3,011 lives saved statewide from 1 January 2023 to 31 May 2026." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Meta proactive self-harm detection on Instagram with alert routing to the Uttar Pradesh Police Social Media Center" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meta Platforms" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Meta self-harm alert routed to Uttar Pradesh Police leads to hospital treatment of a 25-year-old in Meerut within eight minutes", "headline": "Meta self-harm alert gets Meerut police to a man in 8 minutes" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "343d2f4067b78a2fb96d5b25eda3d840e5bf4035a99427db5e079f2fbcdc2624" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On 7 June 2026 a 25-year-old man from the Sardhana area of Meerut, Uttar Pradesh, posted an Instagram video. In it he appeared to drink a white liquid. Police said Meta sent a suicide alert about the post to the Social Media Center at Uttar Pradesh Police headquarters at 6:53 pm. The center alerted Meerut Police, and a Sardhana team reached his home within eight minutes. They found him in a critical condition with a bottle of suspected liquid nearby and took him to hospital, where his condition improved after treatment. He told police he was under stress following the end of a relationship. Police data cited by PTI credit such alerts with 3,011 lives saved statewide from 1 January 2023 to 31 May 2026.", "replication": { "produced_by": [ "Platform detection and review that flags self-harm posts and contacts a police nodal center with account phone and location details", "Police nodal center with a standing arrangement to dispatch local officers immediately" ], "must_hold": [ "Account details resolve to a reachable address within minutes", "Local officers are available to respond immediately" ], "echoes": [ { "setting": "Dwarka, Delhi (reported 5 June 2021): Delhi Police CyPAD received a Facebook alert at about 12:50 am on a self-harm live video; the man was found with heavy blood loss, taken to hospital and AIIMS Trauma Center, condition stable (PTI/The Tribune)", "outcome": "recurred", "source": "https://www.tribuneindia.com/news/delhi/man-saved-by-delhi-police-after-facebook-alerts-on-self-harm-video-263850/amp" }, { "setting": "Ambedkarnagar, Uttar Pradesh (late January 2023): Meta alert at 11:37 pm on a student's Instagram photos of pills; police arrived within 15 minutes and prevented the attempt (PTI/The Tribune, 5 February 2023)", "outcome": "recurred", "source": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp" }, { "date": "2023-01-31", "setting": "Ghaziabad, Uttar Pradesh: Instagram live of a man preparing to hang himself; Inspector Anita Chauhan arrived within 13 minutes and prevented the attempt (PTI/The Tribune, 5 February 2023)", "outcome": "recurred", "source": "https://www.tribuneindia.com/news/nation/facebook-helps-up-police-avert-two-suicides-in-a-week-in-state-476915/amp" }, { "setting": "Upstate New York, from a Facebook promotional video described by NPR (17 November 2018): officers found a woman who had taken medication and got her to a local hospital", "outcome": "recurred", "source": "https://www.northcountrypublicradio.org/news/npr/668408122/facebook-increasingly-reliant-on-a-i-to-predict-suicide-risk" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 0, "record_mapped": 31, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0362", "title": "Rapiscan and Taronga/Macquarie CT algorithms detect shark fins, seahorses, and sea cucumbers at 86–96% in laboratory testing", "summary": "A vendor-affiliated CT study reported 86–96% detection of three marine-wildlife classes and 13% overall false alarms; testing used original scans and synthetic composites, with no customs outcome.", "date_observed": "2026-06-08", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Pirotta and colleagues tested AI detection of marine wildlife in three-dimensional X-ray scans. Their June 8, 2026 paper reports 298 scans from 68 specimens, including preserved specimens and fresh shark material. The researchers expanded the scans by inserting specimen images into baggage images. A 512-bag test set contained both original scans and these synthetic composites, drawn from the same specimen population. Table 3 reports detection rates of 95% for shark fins, 96% for seahorses, and 86% for sea cucumbers. The overall false-alarm rate was 13%; the class-specific rates were 2%, 9%, and 1%. Rapiscan supplied equipment and funded staff participation in analysis and writing. The paper demonstrates laboratory detection, with no reported operational seizure or customs evaluation.", "category": "general benefit", "unexpected": false, "purpose": "Automated detection of marine wildlife in CT scans of mail and luggage to support customs inspection; no operational evaluation is reported.", "system": "Rapiscan 3D X-ray CT marine-wildlife detection algorithms (3D convolutional neural networks with 3D Threat Image Projection)", "model_version": "Experimental 3D convolutional neural networks trained on CT scans and synthetic Threat Image Projection composites; no released model version reported", "developer": "Rapiscan Systems Ltd with Taronga Conservation Society Australia and Macquarie University", "deployer": "None; proof of concept with no customs authority deployment", "location": "Sydney, New South Wales, Australia (research setting)", "domain": "Wildlife trafficking detection at borders", "segment": "Security-screening vendor and conservation research partnership", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "Lab detection rates for trafficked wildlife are read as task performance; no seizure is documented.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome." }, { "group": "organizational", "depth": null, "reason": "The paper reports no operational customs evaluation or documented seizure using these algorithms." }, { "group": "societal", "depth": null, "reason": "Laboratory detection rates only." } ], "ai_role": { "status": "assessed", "statement": "AI classified objects in CT baggage scans. Most positive test bags used synthetically inserted specimens, and testing drew from the same specimen population. The paper is original research with disclosed Rapiscan involvement, not an independent deployment evaluation." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Pirotta, V., Meagher, P., Phan, H. T. H., Shen, K., Thompson, W., Dolman, B., Bending, Z., Smoothey, A. F., Hay, A., Rowe, C. E., Motamayor, A., Liddell, B., Allende, A., Allman, B. E., O'Brien, J. K. (2026). Marine wildlife trafficking: use of AI algorithms for the autodetection of shark fins, seahorses and sea cucumbers. Frontiers in Ocean Sustainability. doi:10.3389/focsu.2026.1776978; §§2–3, tables 1–3, data availability, and conflict-of-interest statement.", "title": "Marine wildlife trafficking: use of AI algorithms for the autodetection of shark fins, seahorses and sea cucumbers", "url": "https://www.frontiersin.org/journals/ocean-sustainability/articles/10.3389/focsu.2026.1776978/full", "date": "2026-06-08", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Rapiscan 3D X-ray CT scanners already used for security screening", "Preserved marine specimens and fresh shark material scanned with the Rapiscan RTT110", "Synthetic data expansion with 3D Threat Image Projection", "Vendor funding of the research" ], "must_hold": [ "Access to CT scanners at mail and airport screening points", "Algorithm performance on concealed, mixed consignments", "Customs authority adoption", "Legal basis for seizure on algorithm alerts" ], "echoes": [] }, "paired_incident": null, "headline": "Rapiscan CT algorithms detect marine wildlife at 86–96% in testing", "metric": "detection rates of 95% (shark fin), 96% (seahorse) and 86% (sea cucumber)", "comparator": { "against": "known scanned samples (ground truth), not human inspectors", "before": null, "after": "PD shark fin: 95%, seahorse: 96% and sea cucumber: 86%", "basis": "measured", "quote": "The performance of the detection algorithm across all marine species subclasses was high (Table 3, PD shark fin: 95%, seahorse: 96% and sea cucumber: 86%), with low false alarm rates (PFA shark fin: 2%, seahorse: 9% and sea cucumber: 1%).", "url": "https://www.frontiersin.org/articles/10.3389/focsu.2026.1776978/full" }, "later": { "status": "unknown", "date": null, "note": "The authors say implementation at the front lines is the next step; no customs trial or deployment of the algorithms is reported in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United Kingdom", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.frontiersin.org/articles/10.3389/focsu.2026.1776978/full", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://find-and-update.company-information.service.gov.uk/company/02755398", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.", "source": "https://www.frontiersin.org/journals/ocean-sustainability/articles/10.3389/focsu.2026.1776978/full", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study. 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No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The networks identified marine-wildlife specimens in CT images of baggage." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "text", "text": "Experimental three-dimensional convolutional neural networks." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Experimental 3D convolutional neural networks trained on CT scans and synthetic Threat Image Projection composites; no released model version reported" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0362-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The experimental convolutional networks have no published release identifier.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Rapiscan 3D X-ray CT marine-wildlife detection algorithms (3D convolutional neural networks with 3D Threat Image Projection)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Rapiscan Systems Ltd with Taronga Conservation Society Australia and Macquarie University" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Rapiscan and Taronga/Macquarie CT algorithms detect shark fins, seahorses, and sea cucumbers at 86–96% in laboratory testing", "headline": "Rapiscan CT algorithms detect marine wildlife at 86–96% in testing" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0362-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ad828aba7302318a8aca156c82e608f6c3552f81cfcd8ea5b33435163e9ee4d5" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Pirotta and colleagues tested AI detection of marine wildlife in three-dimensional X-ray scans. Their June 8, 2026 paper reports 298 scans from 68 specimens, including preserved specimens and fresh shark material. The researchers expanded the scans by inserting specimen images into baggage images. A 512-bag test set contained both original scans and these synthetic composites, drawn from the same specimen population. Table 3 reports detection rates of 95% for shark fins, 96% for seahorses, and 86% for sea cucumbers. The overall false-alarm rate was 13%; the class-specific rates were 2%, 9%, and 1%. Rapiscan supplied equipment and funded staff participation in analysis and writing. The paper demonstrates laboratory detection, with no reported operational seizure or customs evaluation.", "replication": { "produced_by": [ "Rapiscan 3D X-ray CT scanners already used for security screening", "Preserved marine specimens and fresh shark material scanned with the Rapiscan RTT110", "Synthetic data expansion with 3D Threat Image Projection", "Vendor funding of the research" ], "must_hold": [ "Access to CT scanners at mail and airport screening points", "Algorithm performance on concealed, mixed consignments", "Customs authority adoption", "Legal basis for seizure on algorithm alerts" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two derivative Conversation excerpts with the original study alone. Added synthetic-test composition, overall false alarms, fresh shark material, and funding qualifications.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0362-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Researchers scanned marine specimens with a Rapiscan RTT110. They inserted specimens digitally into other CT images to expand the training data and then tested the detection algorithms.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 20, "record_mapped": 14, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0209", "title": "Saronic Corsair sea drone picks up two Apache crew off Oman and carries them to a helicopter hoist", "summary": "A Navy Corsair sea drone picked up two Apache crew off Oman and carried them to a helicopter hoist; CENTCOM reported that both were rescued within about two hours.", "date_observed": "2026-06-09", "date_basis": "event", "date_precision": "day", "benefit_status": "reported", "source_collection": null, "source_entry": null, "account": "U.S. Central Command reported that two Army AH-64 Apache crew members were rescued at 7:33 p.m. Eastern time on June 8, 2026, or 3:33 a.m. on June 9 in Oman. That is the rescue time, not the time that the helicopter went down. CENTCOM said that recovery took approximately two hours and that both crew members were stable. In a direct interview with DefenseScoop, Capt. Tim Hawkins identified the vessel as a Saronic Corsair operated by the Navy’s Task Force 59. He said that it picked up the crew and carried them to another point on the water for a helicopter hoist. The official release said that the cause of the helicopter’s loss was under investigation. The sources do not identify which autonomous functions were used during the rescue.", "category": "protective response", "unexpected": true, "purpose": "The Corsair is an autonomous maritime platform that Task Force 59 had been fielding since late March 2026. In this case, the military used it to carry stranded crew members to a helicopter recovery point.", "system": "Saronic Corsair unmanned (autonomous) surface vessel operated by U.S. 5th Fleet's Task Force 59", "model_version": "Corsair; navigation-software version not reported", "developer": "Saronic Technologies (Texas)", "deployer": "U.S. Navy, 5th Fleet Task Force 59 (U.S. Naval Forces Central Command)", "location": "Off the coast of Oman, near the Strait of Hormuz", "domain": "Military search and rescue / personnel recovery at sea", "segment": "Government, security, and defense (naval unmanned surface vessels)", "benefit_type": "Improved Physical Health", "taxonomy_note": "An at-sea rescue of aircrew is read as a health outcome because no rescue type exists.", "registry_ids": { "oecd_aim": "2026-06-09-8f45" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "Two aviators were recovered from the water and transferred to a helicopter within approximately two hours, according to CENTCOM. Their condition was stable. The sources do not establish the counterfactual risk of death or whether another rescue asset could have reached them." }, { "group": "organizational", "depth": 2, "reason": "The military recovered two crew members using an unmanned vessel and a helicopter. The sources describe a successful operational recovery but do not isolate the AI’s contribution or quantify an organizational saving." } ], "ai_role": { "status": "unassessed", "statement": "Hawkins identified an unmanned Corsair as the recovery vessel. DefenseScoop describes the platform’s autonomous capabilities, but its suggestion that passive sensing helped locate the crew is an inference. The official sources do not identify the navigation mode, human supervision, or sensor contribution during this rescue. A crewed helicopter completed the recovery." }, "evidence": [ { "kind": "press release", "citation": "U.S. Central Command Public Affairs, “U.S. Army Crew Safely Rescued After Helicopter Lost at Sea,” June 9, 2026, DVIDS story 567214.", "title": "U.S. Army Crew Safely Rescued After Helicopter Lost at Sea", "url": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "date": "2026-06-09", "written_by": "deployer", "quote": "The Soldiers were safely rescued within approximately two hours and are in stable condition." }, { "kind": "news report", "citation": "Brandi Vincent, “Autonomous Corsair maritime drone rescues US military pilots after crash near Oman,” DefenseScoop, June 9, 2026; direct interview with CENTCOM spokesperson Capt. Tim Hawkins.", "title": "Autonomous Corsair maritime drone rescues US military pilots after crash near Oman", "url": "https://defensescoop.com/2026/06/09/autonomous-maritime-drone-rescues-apache-pilots-after-crash/", "date": "2026-06-09", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A Corsair already deployed with Task Force 59, which began fielding these vessels in late March 2026", "A vessel able to carry the crew to a location that a rescue helicopter could reach", "A crewed helicopter and coordinated military rescue effort" ], "must_hold": [ "The vessel must reach and carry the people safely", "The human and unmanned parts of the rescue must coordinate", "Navigation, sensing, and communications must be adequate for the conditions; their exact use here is not documented" ], "echoes": [] }, "paired_incident": null, "headline": "Saronic Corsair sea drone picks up two Apache crew off Oman", "metric": "both were rescued within approximately two hours", "comparator": null, "later": { "status": "unknown", "date": null, "note": "No development after the 9-10 June 2026 reports was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-09-8f45", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.saronic.com/careers; https://en.wikipedia.org/wiki/United_States_Navy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-23", "change": "Reviewed the occurrence date, day precision, and benefit status against ABC News and DefenseScoop. The reported time of June 8, 2026 at 7:33 p.m. EDT is June 9 in Oman. The rescue is a reported benefit. The AI contribution and depth ratings were not reassessed.", "source": "https://abcnews.com/Politics/unmanned-drone-boat-rescues-2-us-crew-members/story?id=133713326; https://defensescoop.com/2026/06/09/autonomous-maritime-drone-rescues-apache-pilots-after-crash/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "source": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0209", "catalog_version": "1.0.0", "source_fingerprint": "590f2c708df195209bc2591a071f233b3686c1830447724b39f9f4b64ba670e0", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Saronic Technologies (Texas)", "deployer": "U.S. Navy, 5th Fleet Task Force 59 (U.S. Naval Forces Central Command)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "unassessed", "statement": "Hawkins identified an unmanned Corsair as the recovery vessel. DefenseScoop describes the platform’s autonomous capabilities, but its suggestion that passive sensing helped locate the crew is an inference. The official sources do not identify the navigation mode, human supervision, or sensor contribution during this rescue. A crewed helicopter completed the recovery." } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two aviators were recovered from the water and transferred to a helicopter within approximately two hours, according to CENTCOM. Their condition was stable. The sources do not establish the counterfactual risk of death or whether another rescue asset could have reached them." }, { "group": "organizational", "depth": 2, "reason": "The military recovered two crew members using an unmanned vessel and a helicopter. The sources describe a successful operational recovery but do not isolate the AI’s contribution or quantify an organizational saving." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from the retained evidence using the existing display rule. Source originality is documented separately and does not imply independent verification.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two aviators were recovered from the water and transferred to a helicopter within approximately two hours, according to CENTCOM. Their condition was stable. The sources do not establish the counterfactual risk of death or whether another rescue asset could have reached them." }, { "group": "organizational", "depth": 2, "reason": "The military recovered two crew members using an unmanned vessel and a helicopter. The sources describe a successful operational recovery but do not isolate the AI’s contribution or quantify an organizational saving." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "CENTCOM reports that the two aviators reached safety within about two hours and were in stable condition. The rescue restored their safety and demonstrated an operational use of the vessel. The sources do not establish a risk of death or measure the AI’s separate contribution.", "editor_note": "" } }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two aviators were recovered from the water and transferred to a helicopter within approximately two hours, according to CENTCOM. Their condition was stable. The sources do not establish the counterfactual risk of death or whether another rescue asset could have reached them." }, { "group": "organizational", "depth": 2, "reason": "The military recovered two crew members using an unmanned vessel and a helicopter. The sources describe a successful operational recovery but do not isolate the AI’s contribution or quantify an organizational saving." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "both were rescued within approximately two hours", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-06-09-8f45" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "No development after the 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In this case, the military used it to carry stranded crew members to a helicopter recovery point." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. 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The Navy’s vessel identification and linked reporting are also available.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "U.S. Central Command Public Affairs, “U.S. Army Crew Safely Rescued After Helicopter Lost at Sea,” June 9, 2026, DVIDS story 567214.", "title": "U.S. Army Crew Safely Rescued After Helicopter Lost at Sea", "url": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "date": "2026-06-09", "written_by": "deployer", "quote": "The Soldiers were safely rescued within approximately two hours and are in stable condition." }, { "kind": "news report", "citation": "Brandi Vincent, “Autonomous Corsair maritime drone rescues US military pilots after crash near Oman,” DefenseScoop, June 9, 2026; direct interview with CENTCOM spokesperson Capt. 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Billion-Dollar USV Builder Saronic Scores Military Rescue Milestone Near Hormuz. gCaptain, 9 June 2026; quotes CENTCOM spokesman Capt. Tim Hawkins via Reuters and a Saronic statement.", "relationship": "ABC repeats the official timing; gCaptain and Daily Wire relay statements available through the originals; the generic Saronic homepage is not additional evidence. The Monitor’s previously quoted proximity statement is not needed to support the retained benefit and was not freshly verified." }, { "url": "https://www.csmonitor.com/USA/Military/2026/0610/navy-drones-apache-crew-rescue", "citation": "Mulrine Grobe A (2026). Troop rescue near Iran points to rising use of sea drones in combat. The Christian Science Monitor, 10 June 2026, 11:50 a.m. ET.", "relationship": "ABC repeats the official timing; gCaptain and Daily Wire relay statements available through the originals; the generic Saronic homepage is not additional evidence. The Monitor’s previously quoted proximity statement is not needed to support the retained benefit and was not freshly verified." }, { "url": "https://www.dailywire.com/news/the-robot-that-beat-iran-to-two-american-pilots", "citation": "Akiva K (2026). The Robot That Beat Iran To Two American Pilots. The Daily Wire, 9 June 2026; relays Capt. Tim Hawkins's remarks to the Wall Street Journal.", "relationship": "ABC repeats the official timing; gCaptain and Daily Wire relay statements available through the originals; the generic Saronic homepage is not additional evidence. The Monitor’s previously quoted proximity statement is not needed to support the retained benefit and was not freshly verified." }, { "url": "https://www.saronic.com/", "citation": "Saronic Technologies (2026). Corsair Rescues Downed Pilots in the Strait of Hormuz. 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Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "Both crew members were rescued at 7:33 p.m. ET on June 8 within approximately two hours, and were stable.", "source_ref": "AIBD-0209-source-0001", "source_chain": [ { "url": "https://www.centcom.mil/MEDIA/PUBLIC-RELEASES/Article/4511869/us-army-crew-safely-rescued-after-helicopter-lost-at-sea/", "role": "original command website, access denied" }, { "url": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "role": "same command’s full official distribution, read" } ], "locator": "Official release paragraphs 1–3", "method": {}, "limitations": [ "No crash time is supplied. The cause was under investigation." ] }, { "claim": "Task Force 59’s Saronic Corsair picked up the crew and carried them to a helicopter hoist.", "source_ref": "AIBD-0209-source-0002", "source_chain": [ { "url": "https://defensescoop.com/2026/06/09/autonomous-maritime-drone-rescues-apache-pilots-after-crash/", "locator": "Hawkins interview, opening and paragraphs 3–4", "role": "DefenseScoop contributes a direct interview with Capt. Tim Hawkins that identifies the Corsair and the transfer to a helicopter. It is original journalism, although the rescue details remain military testimony." } ], "locator": "Hawkins interview, opening and paragraphs 3–4", "method": {}, "limitations": [ "The source does not specify the autonomy mode or the exact contribution of AI." ] }, { "claim": "The local event date is June 9, 2026 in Oman.", "source_ref": "AIBD-0209-source-0001", "source_chain": [ { "url": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "locator": "Official rescue timestamp", "role": "CENTCOM Public Affairs supplies the original official rescue chronology and crew condition." } ], "locator": "Official rescue timestamp", "method": { "calculation": "7:33 p.m. EDT June 8 plus eight hours equals 3:33 a.m. Gulf Standard Time June 9" }, "limitations": [ "The conversion refers to the rescue, not the helicopter’s loss." ] } ], "limitations": [ "No mission log, operator account, sensor record, or independent evaluation establishes the AI’s particular role.", "Ars Technica links the original CENTCOM release and directly reproduces Hawkins’ platform identification, but that overlaps the retained sources.", "ABC and Christian Science Monitor pages were inaccessible in this review; no claim of fresh full-text review is made." ], "access_audit": [ { "url": "https://www.dvidshub.net/news/567214/us-army-crew-safely-rescued-after-helicopter-lost-sea", "access": "full official release read" }, { "url": "https://www.centcom.mil/MEDIA/PUBLIC-RELEASES/Article/4511869/us-army-crew-safely-rescued-after-helicopter-lost-at-sea/", "access": "403; official DVIDS copy read instead" }, { "url": "https://defensescoop.com/2026/06/09/autonomous-maritime-drone-rescues-apache-pilots-after-crash/", "access": "full article read" }, { "url": "https://arstechnica.com/gadgets/2026/06/us-military-claims-first-drone-boat-rescue-of-downed-helicopter-crew/", "access": "full article read and original-release link followed" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified." } }, "provenance": { "kind": "source_review", "basis": "Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "CENTCOM describes the rescue, and the Navy identifies the vessel. Mission logs, sensor records, and an operator account of the AI’s role are unavailable.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "A Navy Corsair sea drone picked up two Apache crew off Oman and carried them to a helicopter hoist; CENTCOM reported that both were rescued within about two hours.", "account": "U.S. Central Command reported that two Army AH-64 Apache crew members were rescued at 7:33 p.m. Eastern time on June 8, 2026, or 3:33 a.m. on June 9 in Oman. That is the rescue time, not the time that the helicopter went down. CENTCOM said that recovery took approximately two hours and that both crew members were stable. In a direct interview with DefenseScoop, Capt. Tim Hawkins identified the vessel as a Saronic Corsair operated by the Navy’s Task Force 59. He said that it picked up the crew and carried them to another point on the water for a helicopter hoist. The official release said that the cause of the helicopter’s loss was under investigation. The sources do not identify which autonomous functions were used during the rescue." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A Navy Corsair sea drone carried two Apache crew members off Oman to a helicopter recovery point. CENTCOM reported that both were rescued within about two hours.", "editor_note": "" } }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "The deployment used a Saronic Corsair vessel." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "Corsair; navigation-software version not reported" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The Corsair’s navigation software release is not disclosed.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Saronic Corsair unmanned (autonomous) surface vessel operated by U.S. 5th Fleet's Task Force 59" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Saronic Technologies (Texas)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Saronic Corsair sea drone picks up two Apache crew off Oman and carries them to a helicopter hoist", "headline": "Saronic Corsair sea drone picks up two Apache crew off Oman" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "590f2c708df195209bc2591a071f233b3686c1830447724b39f9f4b64ba670e0" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "U.S. Central Command reported that two Army AH-64 Apache crew members were rescued at 7:33 p.m. Eastern time on June 8, 2026, or 3:33 a.m. on June 9 in Oman. That is the rescue time, not the time that the helicopter went down. CENTCOM said that recovery took approximately two hours and that both crew members were stable. In a direct interview with DefenseScoop, Capt. Tim Hawkins identified the vessel as a Saronic Corsair operated by the Navy’s Task Force 59. He said that it picked up the crew and carried them to another point on the water for a helicopter hoist. The official release said that the cause of the helicopter’s loss was under investigation. The sources do not identify which autonomous functions were used during the rescue.", "replication": { "produced_by": [ "A Corsair already deployed with Task Force 59, which began fielding these vessels in late March 2026", "A vessel able to carry the crew to a location that a rescue helicopter could reach", "A crewed helicopter and coordinated military rescue effort" ], "must_hold": [ "The vessel must reach and carry the people safely", "The human and unmanned parts of the rescue must coordinate", "Navigation, sensing, and communications must be adequate for the conditions; their exact use here is not documented" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Recovered CENTCOM’s original release via its official DVIDS distribution. Corrected the rescue time previously described as the crash time and removed the unsupported statement that the helicopter was definitively shot down.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0209-source-0001", "AIBD-0209-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A Corsair vessel reached the crew and carried them to a point where a helicopter could recover them. Task Force 59 had begun fielding these vessels in late March 2026.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 34, "reviewed": 21, "record_mapped": 13, "not_assessed": 57, "complete": false, "by_state": { "value_present": 34, "not_reported": 0, "unresolved": 0, "not_assessed": 57, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0254", "title": "AI-powered DeterTech cameras may have cut trespass at Dingwall's canal level crossings from about five incidents a day in June 2025", "summary": "Network Rail reported fewer trespass incidents after installing DeterTech AI cameras at Dingwall, alongside signage and campaigns. It supplied no post-installation count and noted a renewed rise.", "date_observed": "2026-06-09", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Network Rail reported on June 9, 2026 that trespass had declined at Dingwall after it installed AI-powered DeterTech cameras. Monitoring in June 2025 had found an average of five incidents a day. The cameras detect people leaving the designated route, sound warnings, and send images to Network Rail and British Transport Police. Signage, safety campaigns, and minor site changes accompanied the installation. The release gives no post-installation count and says that incidents had begun rising again as the weather improved. It does not isolate the cameras’ effect or document an individual alert that prevented an accident.", "category": "general benefit", "unexpected": false, "purpose": "The cameras are built to detect people leaving the designated route, warn them and alert Network Rail and police in real time.", "system": "DeterTech AI-powered cameras with audio warnings and live image relay", "model_version": null, "developer": "DeterTech", "deployer": "Network Rail (Scotland's Railway) with British Transport Police", "location": "Dingwall, United Kingdom", "domain": "Railway safety", "segment": "Trespass and level-crossing misuse deterrence", "benefit_type": "Increased Product Safety", "taxonomy_note": "Fewer trespass incidents after detection and audio warnings are read as a safety mechanism working; trespass is also an offense.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "The release reports a reduction without numbers and notes incidents rising again." }, { "group": "organizational", "depth": null, "reason": "No quantified operational outcome is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The release credits the reduction to the cameras together with signage and campaigns. Detection counts, false alarms and responses are not reported. The cameras' AI is described only as detecting route departures." }, "evidence": [ { "kind": "press release", "citation": "Network Rail media centre (9 Jun 2026). AI cameras drive down Dingwall trespass but safety message remains. Scotland's Railway release.", "title": "AI cameras drive down Dingwall trespass but safety message remains", "url": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "date": "2026-06-09", "written_by": "deployer", "quote": "Data from June 2025 showed an average of five trespass incidents a day, with people using the bridge as a shortcut between Dingwall Canal North and South crossings." } ], "replication": { "produced_by": [ "A known trespass shortcut between two crossings with CCTV evidence from the prior year", "Cameras with on-site audio warnings and live relay to the infrastructure manager and police", "Concurrent signage and safety campaigns" ], "must_hold": [ "Warnings deter rather than being ignored", "Police and Network Rail respond to live images", "Seasonal and school-holiday increases are monitored" ], "echoes": [ { "date": "2026-06-09", "setting": "Network Rail level-crossing safety work at South Kessock, Cornton, Cleghorn and Logan's Road, Scotland; the sources do not say whether AI cameras are used at those sites", "model_version": null, "outcome": "unknown", "source": "Network Rail media center, 9 June 2026, https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains" } ] }, "paired_incident": null, "headline": "DeterTech AI cameras may have cut trespass at Dingwall", "metric": null, "comparator": { "against": "trespass recorded at the same crossings before the cameras (June 2025 monitoring)", "before": "an average of five trespass incidents a day", "after": "incidents have reduced (no figure given)", "basis": "assumed", "quote": "Following the introduction of AI-powered DeterTech cameras incidents have reduced.", "url": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains" }, "later": { "status": "unknown", "date": null, "note": "The June 9 release reports that incidents were beginning to rise again as the weather improved. No later measured trespass rate is established by the retained source.", "quote": null, "url": null }, "value": null, "developer_country": "United Kingdom", "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Merged a second write-up of the same announcement: added the BBC and Ross-shire Journal reports and the 2025 BBC background report.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Headline reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.detertech.com/contact-us/; https://en.wikipedia.org/wiki/Network_Rail", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Kept Network Rail’s original release and removed news summaries that do not establish an additional result. Preserved the concurrent interventions and rising-incidents qualification.", "source": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0254", "catalog_version": "1.0.0", "source_fingerprint": "e7ea0bbd38e4a22f80fa883118434d2753b94ab3837ef317b8810c598adb8ee5", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0254-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "DeterTech", "deployer": "Network Rail (Scotland's Railway) with British Transport Police" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The release credits the reduction to the cameras together with signage and campaigns. Detection counts, false alarms and responses are not reported. The cameras' AI is described only as detecting route departures." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Recomputed from the retained evidence using the existing display rule. Source originality is documented separately and does not imply independent verification.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The release reports a reduction without numbers and notes incidents rising again." }, { "group": "organizational", "reason": "No quantified operational outcome is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "The release reports a reduction without numbers and notes incidents rising again." }, { "group": "organizational", "reason": "No quantified operational outcome is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": 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"not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, 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Monitoring in June 2025 had found an average of five incidents a day. The cameras detect people leaving the designated route, sound warnings, and send images to Network Rail and British Transport Police. Signage, safety campaigns, and minor site changes accompanied the installation. The release gives no post-installation count and says that incidents had begun rising again as the weather improved. It does not isolate the cameras’ effect or document an individual alert that prevented an accident.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Network Rail’s original release and removed news summaries that do not establish an additional result. 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New AI cameras installed to deter railway trespassers in Dingwall. 10 June 2026.", "relationship": "The two 2026 news items relay the same announcement. The 2025 BBC background on the shortcut adds no separate evidence of the AI’s benefit, and the original release includes the relevant baseline." }, { "url": "https://www.ross-shirejournal.co.uk/news/ai-cameras-cut-dangerous-railway-trespass-in-dingwall-but-o-437183/", "citation": "Cameron L (2026). Dingwall railway trespassing incidents reduced by AI cameras installed by Network Rail and British Transport Police, but safety warnings continue. Ross-shire Journal, 9 June 2026.", "relationship": "The two 2026 news items relay the same announcement. The 2025 BBC background on the shortcut adds no separate evidence of the AI’s benefit, and the original release includes the relevant baseline." }, { "url": "https://www.bbc.com/news/articles/cwyq5q4dlp2o", "citation": "BBC News (2025). People using railway bridge as 'dangerous shortcut'. 2 July 2025 (background on the trespass problem).", "relationship": "The two 2026 news items relay the same announcement. The 2025 BBC background on the shortcut adds no separate evidence of the AI’s benefit, and the original release includes the relevant baseline." } ], "lead_source_ref": "AIBD-0254-source-0001", "retained_source_order": [ "AIBD-0254-source-0001" ], "ordering_basis": "The first source directly supports the reported benefit or is the closest accessible original account. Each additional source has a distinct evidentiary contribution described in its relationship. Documented inaccessible origins are not represented as having been read.", "claim_lineage": [ { "claim": "The baseline was five trespass incidents a day in June 2025, followed by an unspecified decline after cameras were introduced.", "source_ref": "AIBD-0254-source-0001", "source_chain": [ { "url": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "locator": "Dingwall baseline and camera paragraphs", "role": "Network Rail’s media release is the deployer’s original account. It includes remarks from Network Rail and British Transport Police, without releasing the underlying monitoring data." } ], "locator": "Dingwall baseline and camera paragraphs", "method": { "baseline_period": "June 2025", "baseline_rate": "five incidents per day on average", "post_installation_rate": "not supplied" }, "limitations": [ "Signage, campaigns, and minor improvements accompanied the cameras.", "The release also says that incidents were starting to rise again." ] }, { "claim": "DeterTech cameras issue audio warnings and send live images to Network Rail and BTP.", "source_ref": "AIBD-0254-source-0001", "source_chain": [ { "url": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "locator": "Paragraph beginning “The cameras can detect…”", "role": "Network Rail’s media release is the deployer’s original account. It includes remarks from Network Rail and British Transport Police, without releasing the underlying monitoring data." } ], "locator": "Paragraph beginning “The cameras can detect…”", "method": {}, "limitations": [ "No alert counts, false-alarm rates, or intervention records are supplied." ] } ], "limitations": [ "The release links no underlying monitoring dataset, evaluation, or supplement.", "The BBC and Ross-shire pages were not freshly accessible; the original release supports the retained claims without them." ], "access_audit": [ { "url": "https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains", "access": "complete original release read" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified." } }, "provenance": { "kind": "source_review", "basis": "Kept Network Rail’s original release and removed news summaries that do not establish an additional result. Preserved the concurrent interventions and rising-incidents qualification. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0254-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Network Rail’s original release supports the reported decline in trespassing. It links no monitoring data or evaluation and gives no count after installation.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Network Rail reported fewer trespass incidents after installing DeterTech AI cameras at Dingwall, alongside signage and campaigns. It supplied no post-installation count and noted a renewed rise.", "account": "Network Rail reported on June 9, 2026 that trespass had declined at Dingwall after it installed AI-powered DeterTech cameras. Monitoring in June 2025 had found an average of five incidents a day. The cameras detect people leaving the designated route, sound warnings, and send images to Network Rail and British Transport Police. Signage, safety campaigns, and minor site changes accompanied the installation. The release gives no post-installation count and says that incidents had begun rising again as the weather improved. It does not isolate the cameras’ effect or document an individual alert that prevented an accident." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Network Rail’s original release and removed news summaries that do not establish an additional result. Preserved the concurrent interventions and rising-incidents qualification.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0254-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "DeterTech AI-powered cameras with audio warnings and live image relay" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "DeterTech" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AI-powered DeterTech cameras may have cut trespass at Dingwall's canal level crossings from about five incidents a day in June 2025", "headline": "DeterTech AI cameras may have cut trespass at Dingwall" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "e7ea0bbd38e4a22f80fa883118434d2753b94ab3837ef317b8810c598adb8ee5" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Network Rail reported on June 9, 2026 that trespass had declined at Dingwall after it installed AI-powered DeterTech cameras. Monitoring in June 2025 had found an average of five incidents a day. The cameras detect people leaving the designated route, sound warnings, and send images to Network Rail and British Transport Police. Signage, safety campaigns, and minor site changes accompanied the installation. The release gives no post-installation count and says that incidents had begun rising again as the weather improved. It does not isolate the cameras’ effect or document an individual alert that prevented an accident.", "replication": { "produced_by": [ "A known trespass shortcut between two crossings with CCTV evidence from the prior year", "Cameras with on-site audio warnings and live relay to the infrastructure manager and police", "Concurrent signage and safety campaigns" ], "must_hold": [ "Warnings deter rather than being ignored", "Police and Network Rail respond to live images", "Seasonal and school-holiday increases are monitored" ], "echoes": [ { "date": "2026-06-09", "setting": "Network Rail level-crossing safety work at South Kessock, Cornton, Cleghorn and Logan's Road, Scotland; the sources do not say whether AI cameras are used at those sites", "outcome": "unknown", "source": "Network Rail media center, 9 June 2026, https://www.networkrailmediacentre.co.uk/news/ai-cameras-drive-down-dingwall-trespass-but-safety-message-remains" } ] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Kept Network Rail’s original release and removed news summaries that do not establish an additional result. Preserved the concurrent interventions and rising-incidents qualification.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0254-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "DeterTech cameras watched a known trespassing route and issued audio warnings. Alerts also reached Network Rail and police. Signage and safety campaigns ran alongside the cameras.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 11, "record_mapped": 18, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0375", "title": "Phú Thọ provincial police AI cameras put faces to all 18 teenagers found gathering with weapons to fight in Việt Trì within about 30 minutes; all were summoned and confessed", "summary": "Tuổi Trẻ (14 June 2026): on the night of 13 June Phú Thọ police saw a group preparing weapons to fight in Việt Trì; the AI camera system identified all 18 faces in about 30 minutes; all confessed.", "date_observed": "2026-06-13", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On the night of Saturday 13 June 2026, Phú Thọ provincial police detected a group of teenagers gathering in Việt Trì ward. Officers were monitoring and mining data from the camera system. The teenagers were preparing weapons and vehicles to fight and disturb public order, Tuổi Trẻ reported on 14 June. Within about 30 minutes the AI camera system of the provincial command center had accurately identified the faces of all 18 participants. They were aged 14 to 18. They came from Việt Trì, Vân Phú and Nông Trang wards and Phù Ninh and Bình Phú communes (Tuổi Trẻ, VietNamNet). Tiền Phong says the whole case was clarified in just over two hours. It says 17 of the 18 were pupils of schools including Vũ Thê Lang High School and Dữu Lâu Middle School. One had dropped out. It says the provincial police summoned all 18, and that at the police station they admitted the violations. No report says whether a fight took place.", "category": "protective response", "unexpected": false, "purpose": "The provincial AI camera system was installed to monitor traffic routes and key areas and detect violations for investigation and enforcement, per Tuổi Trẻ. Identifying people gathering with weapons is that purpose.", "system": "Phú Thọ provincial police AI camera system with facial recognition (provincial command and information center)", "model_version": null, "developer": null, "deployer": "Công an tỉnh Phú Thọ (Phú Thọ Provincial Police)", "location": "Việt Trì, Vietnam", "domain": "Policing / public order", "segment": "Public-space facial recognition of minors", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-06-14-ba55" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "Phú Thọ provincial police identified all 18 participants within about 30 minutes. The case was clarified in just over two hours, with all 18 summoned and confessing, per Tuổi Trẻ, VietNamNet and Tiền Phong." }, { "group": "societal", "depth": null, "reason": "Residents of Việt Trì were spared a street fight only if one was about to happen. The reports say the group was preparing weapons and vehicles, but they do not say whether a fight occurred or was interrupted." } ], "ai_role": { "status": "assessed", "statement": "The facial recognition of the provincial AI camera system supplied the identities. Tuổi Trẻ and VietNamNet say all 18 faces were accurately identified within about 30 minutes, after officers monitoring camera data had noticed the gathering. The summons, questioning and confessions were police work. The sources are three national outlets reporting the provincial police's own account, with no vendor, algorithm or accuracy figure given." }, "evidence": [ { "kind": "news report", "citation": "Chí Tuệ (2026). Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố. Tuổi Trẻ Online, 14 June 2026.", "title": "Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố", "url": "https://tuoitre.vn/tu-camera-ai-cong-an-chi-mat-30-phut-nhan-dien-18-thanh-thieu-nien-tu-tap-danh-nhau-tren-pho-20260614143550899.htm", "date": "2026-06-14", "written_by": "independent", "quote": "Chỉ sau khoảng 30 phút, toàn bộ 18 thanh, thiếu niên tham gia đã được hệ thống camera AI nhận diện chính xác khuôn mặt" }, { "kind": "news report", "citation": "Đức Hoàng (2026). 18 thanh thiếu niên gây rối bị camera AI ở Phú Thọ nhận diện sau 30 phút. VietNamNet, 14 June 2026.", "title": "18 thanh thiếu niên gây rối bị camera AI ở Phú Thọ nhận diện sau 30 phút", "url": "https://vietnamnet.vn/18-thanh-thieu-nien-gay-roi-bi-camera-ai-o-phu-tho-nhan-dien-sau-30-phut-2525799.html", "date": "2026-06-14", "written_by": "independent", "quote": "Chỉ sau khoảng 30 phút, toàn bộ các đối tượng tham gia đã được hệ thống nhận diện chính xác khuôn mặt" }, { "kind": "news report", "citation": "Viết Hà (2026). Camera AI 'tóm gọn' nhóm học sinh tụ tập mang theo hung khí. Tiền Phong, 14 June 2026.", "title": "Camera AI 'tóm gọn' nhóm học sinh tụ tập mang theo hung khí", "url": "https://tienphong.vn/camera-ai-tom-gon-nhom-hoc-sinh-tu-tap-mang-theo-hung-khi-post1851303.tpo", "date": "2026-06-14", "written_by": "independent", "quote": "Hệ thống camera giám sát ứng dụng trí tuệ nhân tạo đã nhanh chóng nhận diện các đối tượng, giúp công an làm rõ toàn bộ vụ việc" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2026). AI Surveillance Cameras Prevent Youth Gang Violence in Phú Thọ. OECD.AI, 14 June 2026.", "title": "AI Surveillance Cameras Prevent Youth Gang Violence in Phú Thọ", "url": "https://oecd.ai/en/incidents/2026-06-14-ba55", "date": "2026-06-14", "written_by": "independent", "quote": "AI-powered surveillance cameras enabled police to quickly identify and apprehend 18 teenagers preparing for a violent public disturbance" } ], "replication": { "produced_by": [ "A provincial camera network with facial recognition feeding the police command center", "Officers watching camera data at night who noticed the gathering", "Reference images that let the system put names to 14-to-18-year-olds", "Police able to summon the 18 and their families within hours" ], "must_hold": [ "Camera coverage of the gathering point with usable faces", "The subjects are enrolled in the reference database", "Police verification of each match before action" ], "echoes": [] }, "paired_incident": null, "headline": "AI cameras name 18 armed teenagers in Việt Trì within half an hour", "metric": "identified all 18 faces in about 30 minutes", "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "Vietnam", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-14-ba55", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://congan.phutho.gov.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0375", "catalog_version": "1.0.0", "source_fingerprint": "cbc3b4ff7f19e78060c6ad0dfbf0d0de7daffde4e0020f6cba8a81fa6f651c51", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0375-source-0001", "AIBD-0375-source-0002", "AIBD-0375-source-0003", "AIBD-0375-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Công an tỉnh Phú Thọ (Phú Thọ Provincial Police)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The facial recognition of the provincial AI camera system supplied the identities. Tuổi Trẻ and VietNamNet say all 18 faces were accurately identified within about 30 minutes, after officers monitoring camera data had noticed the gathering. The summons, questioning and confessions were police work. The sources are three national outlets reporting the provincial police's own account, with no vendor, algorithm or accuracy figure given." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The facial recognition of the provincial AI camera system supplied the identities. Tuổi Trẻ and VietNamNet say all 18 faces were accurately identified within about 30 minutes, after officers monitoring camera data had noticed the gathering. The summons, questioning and confessions were police work. The sources are three national outlets reporting the provincial police's own account, with no vendor, algorithm or accuracy figure given." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Phú Thọ provincial police identified all 18 participants within about 30 minutes. The case was clarified in just over two hours, with all 18 summoned and confessing, per Tuổi Trẻ, VietNamNet and Tiền Phong." }, { "group": "societal", "reason": "Residents of Việt Trì were spared a street fight only if one was about to happen. The reports say the group was preparing weapons and vehicles, but they do not say whether a fight occurred or was interrupted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Phú Thọ provincial police identified all 18 participants within about 30 minutes. The case was clarified in just over two hours, with all 18 summoned and confessing, per Tuổi Trẻ, VietNamNet and Tiền Phong." }, { "group": "societal", "reason": "Residents of Việt Trì were spared a street fight only if one was about to happen. The reports say the group was preparing weapons and vehicles, but they do not say whether a fight occurred or was interrupted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Phú Thọ provincial police identified all 18 participants within about 30 minutes. The case was clarified in just over two hours, with all 18 summoned and confessing, per Tuổi Trẻ, VietNamNet and Tiền Phong." }, { "group": "societal", "reason": "Residents of Việt Trì were spared a street fight only if one was about to happen. The reports say the group was preparing weapons and vehicles, but they do not say whether a fight occurred or was interrupted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "identified all 18 faces in about 30 minutes", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-06-14-ba55" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0375" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the night of Saturday 13 June 2026, Phú Thọ provincial police detected a group of teenagers gathering in Việt Trì ward. Officers were monitoring and mining data from the camera system. The teenagers were preparing weapons and vehicles to fight and disturb public order, Tuổi Trẻ reported on 14 June. Within about 30 minutes the AI camera system of the provincial command center had accurately identified the faces of all 18 participants. They were aged 14 to 18. They came from Việt Trì, Vân Phú and Nông Trang wards and Phù Ninh and Bình Phú communes (Tuổi Trẻ, VietNamNet). Tiền Phong says the whole case was clarified in just over two hours. It says 17 of the 18 were pupils of schools including Vũ Thê Lang High School and Dữu Lâu Middle School. One had dropped out. It says the provincial police summoned all 18, and that at the police station they admitted the violations. No report says whether a fight took place.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "Phú Thọ provincial police identified all 18 participants within about 30 minutes. The case was clarified in just over two hours, with all 18 summoned and confessing, per Tuổi Trẻ, VietNamNet and Tiền Phong." }, { "group": "societal", "reason": "Residents of Việt Trì were spared a street fight only if one was about to happen. The reports say the group was preparing weapons and vehicles, but they do not say whether a fight occurred or was interrupted." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The provincial AI camera system was installed to monitor traffic routes and key areas and detect violations for investigation and enforcement, per Tuổi Trẻ. Identifying people gathering with weapons is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Việt Trì, Vietnam", "deployer_country": "Vietnam" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "The provincial AI camera system was installed to monitor traffic routes and key areas and detect violations for investigation and enforcement, per Tuổi Trẻ. Identifying people gathering with weapons is that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-06-13", "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-14-ba55", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://congan.phutho.gov.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A provincial camera network with facial recognition feeding the police command center", "Officers watching camera data at night who noticed the gathering", "Reference images that let the system put names to 14-to-18-year-olds", "Police able to summon the 18 and their families within hours" ], "must_hold": [ "Camera coverage of the gathering point with usable faces", "The subjects are enrolled in the reference database", "Police verification of each match before action" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-14-ba55", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://congan.phutho.gov.vn/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Policing / public order", "segment": "Public-space facial recognition of minors" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Chí Tuệ (2026). Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố. Tuổi Trẻ Online, 14 June 2026.", "title": "Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố", "url": "https://tuoitre.vn/tu-camera-ai-cong-an-chi-mat-30-phut-nhan-dien-18-thanh-thieu-nien-tu-tap-danh-nhau-tren-pho-20260614143550899.htm", "date": "2026-06-14", "written_by": "independent", "quote": "Chỉ sau khoảng 30 phút, toàn bộ 18 thanh, thiếu niên tham gia đã được hệ thống camera AI nhận diện chính xác khuôn mặt" }, { "kind": "news report", "citation": "Đức Hoàng (2026). 18 thanh thiếu niên gây rối bị camera AI ở Phú Thọ nhận diện sau 30 phút. 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Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố. Tuổi Trẻ Online, 14 June 2026.", "title": "Từ camera AI, công an chỉ mất 30 phút nhận diện 18 thanh thiếu niên tụ tập đánh nhau trên phố", "url": "https://tuoitre.vn/tu-camera-ai-cong-an-chi-mat-30-phut-nhan-dien-18-thanh-thieu-nien-tu-tap-danh-nhau-tren-pho-20260614143550899.htm", "date": "2026-06-14", "written_by": "independent", "quote": "Chỉ sau khoảng 30 phút, toàn bộ 18 thanh, thiếu niên tham gia đã được hệ thống camera AI nhận diện chính xác khuôn mặt" }, { "kind": "news report", "citation": "Đức Hoàng (2026). 18 thanh thiếu niên gây rối bị camera AI ở Phú Thọ nhận diện sau 30 phút. 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AI Surveillance Cameras Prevent Youth Gang Violence in Phú Thọ. 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Officers were monitoring and mining data from the camera system. The teenagers were preparing weapons and vehicles to fight and disturb public order, Tuổi Trẻ reported on 14 June. Within about 30 minutes the AI camera system of the provincial command center had accurately identified the faces of all 18 participants. They were aged 14 to 18. They came from Việt Trì, Vân Phú and Nông Trang wards and Phù Ninh and Bình Phú communes (Tuổi Trẻ, VietNamNet). Tiền Phong says the whole case was clarified in just over two hours. It says 17 of the 18 were pupils of schools including Vũ Thê Lang High School and Dữu Lâu Middle School. One had dropped out. It says the provincial police summoned all 18, and that at the police station they admitted the violations. No report says whether a fight took place." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Phú Thọ provincial police AI camera system with facial recognition (provincial command and information center)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Phú Thọ provincial police AI cameras put faces to all 18 teenagers found gathering with weapons to fight in Việt Trì within about 30 minutes; all were summoned and confessed", "headline": "AI cameras name 18 armed teenagers in Việt Trì within half an hour" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cbc3b4ff7f19e78060c6ad0dfbf0d0de7daffde4e0020f6cba8a81fa6f651c51" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On the night of Saturday 13 June 2026, Phú Thọ provincial police detected a group of teenagers gathering in Việt Trì ward. Officers were monitoring and mining data from the camera system. The teenagers were preparing weapons and vehicles to fight and disturb public order, Tuổi Trẻ reported on 14 June. Within about 30 minutes the AI camera system of the provincial command center had accurately identified the faces of all 18 participants. They were aged 14 to 18. They came from Việt Trì, Vân Phú and Nông Trang wards and Phù Ninh and Bình Phú communes (Tuổi Trẻ, VietNamNet). Tiền Phong says the whole case was clarified in just over two hours. It says 17 of the 18 were pupils of schools including Vũ Thê Lang High School and Dữu Lâu Middle School. One had dropped out. It says the provincial police summoned all 18, and that at the police station they admitted the violations. No report says whether a fight took place.", "replication": { "produced_by": [ "A provincial camera network with facial recognition feeding the police command center", "Officers watching camera data at night who noticed the gathering", "Reference images that let the system put names to 14-to-18-year-olds", "Police able to summon the 18 and their families within hours" ], "must_hold": [ "Camera coverage of the gathering point with usable faces", "The subjects are enrolled in the reference database", "Police verification of each match before action" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0210", "title": "TIAA’s AI flags a suspected scam involving a 76-year-old’s retirement savings, and staff stop the money from moving", "summary": "TIAA’s CEO said that an AI flag, staff intervention, and contact with a participant’s daughter protected retirement savings of more than $3 million.", "date_observed": "2026-06-17", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "TIAA CEO Thasunda Brown Duckett told Fortune that an AI alert helped staff stop a scam involving a 76-year-old participant’s retirement savings. A portfolio manager referred the concern to the fraud team, which spent hours with the participant and contacted his daughter. Duckett said that the money did not move. The interview describes retirement holdings above $3 million, but does not itemize an attempted transfer. The original episode was released on June 17, 2026, with its transcript published five days later. No participant statement, transaction record, or separate investigation is supplied.", "category": "harm prevented", "unexpected": false, "purpose": "The unnamed AI tool flagged suspected fraud for human review. Staff investigation and contact with the participant’s family were necessary to stop the money from moving.", "system": "Unnamed TIAA AI tool used to flag suspected fraud for human review", "model_version": null, "developer": null, "deployer": "TIAA (Teachers Insurance and Annuity Association of America)", "location": null, "domain": "Financial services / retirement accounts / fraud prevention", "segment": "Retirement savings provider for educators, healthcare workers and public servants", "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-06-17-b80b" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The CEO describes a 76-year-old retaining retirement savings of more than $3 million after a suspected scam was interrupted. 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The complete written transcript and episode metadata were read.", "There is no independent participant-level verification.", "Fructus should distinguish the reported retirement holdings from a verified attempted transfer or net benefit." ], "access_audit": [ { "url": "https://fortune.com/2026/06/22/tiaa-ceo-thasunda-brown-duckett-retirement-crisis-annuity-income-america/", "access": "complete lightly edited transcript read", "version": "June 22, 2026" }, { "url": "https://video.fortune.com/media/452d84c7-1fe6-41aa-9716-89bb11886530?activePlaylistName=Fortune+500+Titans+and+Disruptors+of+Industry", "access": "publication metadata read; video not watched", "version": "June 17, 2026; page updated August 13" } ], "related_material": [], "scope": "Complete review of retained-source lineage and access status. This does not mean that inaccessible upstream documents were inspected, that every required case field is complete, or that the original claims were independently verified.", "chronology_source": { "url": "https://video.fortune.com/media/452d84c7-1fe6-41aa-9716-89bb11886530?activePlaylistName=Fortune+500+Titans+and+Disruptors+of+Industry", "title": "Original Fortune interview episode", "date": "2026-06-17" } } }, "provenance": { "kind": "source_review", "basis": "Replaced two news retellings and podcast metadata with the original interview transcript. Distinguished the participant’s retirement holdings from an itemized attempted transfer or independently measured avoided loss. Access limits are enumerated in the review.", "record_fields": [ "evidence", "account", "ai_role" ], "source_refs": [ "AIBD-0210-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "TIAA’s CEO gives the account in an interview with a complete transcript. No participant account or transaction record independently verifies the savings at risk or the amount of any attempted transfer.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "TIAA’s CEO said that an AI flag, staff intervention, and contact with a participant’s daughter protected retirement savings of more than $3 million.", "account": "TIAA CEO Thasunda Brown Duckett told Fortune that an AI alert helped staff stop a scam involving a 76-year-old participant’s retirement savings. A portfolio manager referred the concern to the fraud team, which spent hours with the participant and contacted his daughter. Duckett said that the money did not move. The interview describes retirement holdings above $3 million, but does not itemize an attempted transfer. The original episode was released on June 17, 2026, with its transcript published five days later. No participant statement, transaction record, or separate investigation is supplied." } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two news retellings and podcast metadata with the original interview transcript. Distinguished the participant’s retirement holdings from an itemized attempted transfer or independently measured avoided loss.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0210-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Unnamed TIAA AI tool used to flag suspected fraud for human review" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two news retellings and podcast metadata with the original interview transcript. Distinguished the participant’s retirement holdings from an itemized attempted transfer or independently measured avoided loss.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0210-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "TIAA’s unnamed system for detecting suspected fraud.", "editor_note": "" } }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "TIAA’s AI flags a suspected scam involving a 76-year-old’s retirement savings, and staff stop the money from moving", "headline": "TIAA’s AI may have helped stop a scam involving retirement savings" } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two news retellings and podcast metadata with the original interview transcript. Distinguished the participant’s retirement holdings from an itemized attempted transfer or independently measured avoided loss.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0210-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "7740ef13b31747812ace838f969427f4de13b1270cb566200e7b1d319b6ec852" ], "role": "SHA-256 of normalized current case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version of the updated case record.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "TIAA CEO Thasunda Brown Duckett told Fortune that an AI alert helped staff stop a scam involving a 76-year-old participant’s retirement savings. A portfolio manager referred the concern to the fraud team, which spent hours with the participant and contacted his daughter. Duckett said that the money did not move. The interview describes retirement holdings above $3 million, but does not itemize an attempted transfer. The original episode was released on June 17, 2026, with its transcript published five days later. No participant statement, transaction record, or separate investigation is supplied.", "replication": { "produced_by": [ "An AI alert that a portfolio manager reviewed and referred to the fraud team", "Staff who spent hours discussing the suspected scam with the participant", "Contact with a family member who could help stop the money from moving" ], "must_hold": [ "The flagged request must actually be fraud. Duckett gives no false-positive rate, and the scam itself is not described", "The firm must be able to hold a transfer while it persuades the customer. Duckett says AI by itself would not necessarily have protected him", "The customer or a relative must be reachable and open to persuasion before the funds move" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped fields during the source review. Replaced two news retellings and podcast metadata with the original interview transcript. Distinguished the participant’s retirement holdings from an itemized attempted transfer or independently measured avoided loss.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0210-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A portfolio manager referred an AI alert to the fraud team. Staff spoke with the participant for hours and contacted his daughter before the money moved.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 24, "record_mapped": 8, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0211", "title": "o3 Deep Research reanalysis at Boston Children's Hospital yields 18 confirmed local diagnoses, including 11 new diagnoses and seven rediscoveries", "summary": "AI-assisted reanalysis of 376 locally unresolved cases yielded 18 confirmed diagnoses. Eleven were new, while seven had already been established elsewhere.", "date_observed": "2026-06-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Boston Children’s Hospital and OpenAI researchers used o3 Deep Research to reassess 376 rare-disease cases that remained unresolved in their local research records. They reported 18 confirmed local diagnoses, or 4.8%: 11 newly identified diagnoses and seven rediscoveries of diagnoses already made elsewhere. Clinicians reviewed candidates, arranged laboratory confirmation, and returned results to families. The paper’s discussion explains that some findings depended on later gene discoveries, revised classifications, previously uncalled variants, or information that was unavailable to earlier analyses. The researchers did not compare the model with a simultaneous expert reanalysis using the same current evidence. They also did not measure improvements in treatment, cost, or clinician time. NBC News separately interviewed Kyra Benton about receiving a diagnosis and sought comment from outside clinicians. The study was retrospective and involved OpenAI employees and funding, so it does not establish an independent estimate of the model’s added benefit.", "category": "benefit created", "unexpected": false, "purpose": "OpenAI o3 Deep Research is a general-purpose reasoning and research model, not a diagnostic device. The Manton Center team built an explanation-first reanalysis workflow around it to propose candidate molecular diagnoses for unsolved cases. These diagnoses were the workflow's intended output. OpenAI states that the study does not describe or endorse a customer use of o3 for diagnosis. Brownstein said that she was shocked that a commercial system could find new diagnoses in genomes analyzed many times.", "system": "OpenAI o3 Deep Research, used as the reasoning layer of an LLM-assisted genome reanalysis workflow (Human Phenotype Ontology terms, clinician notes and a filtered variant table in; explanation-linked candidate diagnoses out)", "model_version": "o3 Deep Research", "developer": "OpenAI", "deployer": "Boston Children's Hospital, The Manton Center for Orphan Disease Research (with Harvard Medical School and OpenAI co-authors)", "location": "Boston, United States", "domain": "Clinical genomics / rare disease diagnosis", "segment": "Hospital rare-disease research center; retrospective reanalysis study", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-06-20-3da6" }, "ratings": [ { "group": "personal", "depth": 2, "reason": "Investigators returned 18 confirmed local diagnoses to families, including 11 new diagnoses and seven rediscoveries. NBC’s direct patient interview describes the value of receiving an explanation after years of uncertainty. Changes to treatment or health outcomes were not measured." }, { "group": "organizational", "depth": 1, "reason": "The team resolved 18 cases in its local research records, including seven diagnoses already established elsewhere. No contemporaneous human-reanalysis comparison or measured savings in time, cost, or clinician effort establish the additional organizational benefit of AI." } ], "ai_role": { "status": "assessed", "statement": "o3 Deep Research read each de-identified case packet and proposed the most plausible molecular explanation with its supporting evidence. It diagnosed no one. Humans did the rest. At least two reviewers adjudicated each candidate under ACMG/AMP criteria, a CLIA-certified laboratory confirmed each variant, and the clinical team returned results to families. Its distinct contribution was surfacing candidates in cases that commercial and institutional analyses and multidisciplinary teams had already reviewed. In one early-psychosis case it inferred a 22q11.2 deletion absent from the input data, which genome sequencing then confirmed. Seven of the 18 were rediscoveries already established externally. The study was retrospective, and reviewers were not blinded to model confidence. The authors call for prospective evaluation with comparator baselines, so the gain over renewed human reanalysis is unmeasured." }, "evidence": [ { "kind": "peer-reviewed study", "citation": "Jaech A, Cheatham M, Shringarpure SS, Genetti CA, Pradhan P, Bagul A, Panch T, Rader B, Sewalk K, Distler R, Anderson KN, Stewart M, Lejfer S, Glahn DC, Goldstein RD, Wojcik M, Beggs AH, Brownstein JS, Brownstein CA (2026). LLM-Assisted Reanalysis of Unsolved Rare Disease Genomes Increases Diagnostic Yield. NEJM AI 3(7); doi:10.1056/AIcs2501343; PMID 42529462. Four of the nineteen authors, including the first, are OpenAI employees; the senior author is at Boston Children's Hospital and Harvard Medical School.", "title": "LLM-Assisted Reanalysis of Unsolved Rare Disease Genomes Increases Diagnostic Yield", "url": "https://doi.org/10.1056/AIcs2501343", "date": "2026-06-25", "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Jared Perlo. “AI helped diagnose 18 children whose rare diseases had stumped doctors.” NBC News, June 18, 2026. Original interviews with patient Kyra Benton, study investigators, and outside clinicians.", "title": "AI helped diagnose 18 children whose rare diseases had stumped doctors", "url": "https://www.nbcnews.com/tech/innovation/ai-boston-childrens-hospital-diagnose-rare-diseases-kids-openai-rcna350387", "date": "2026-06-18", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Already-sequenced unsolved cases, mostly child-parent trios, assembled into a de-identified packet. Each packet held Human Phenotype Ontology terms, any clinician notes, age and sex. It also held a filtered variant table with rarity, predicted effect, ClinVar class and family signal quality", "A general-purpose reasoning model asked for the single most plausible molecular explanation and its evidence, not just a ranked gene. The prompt was refined first on cases of known diagnosis", "Time elapsed since the original analysis, so that newly published gene-disease links and reclassified variants existed to be found", "Expert adjudication under ACMG/AMP criteria by at least two reviewers, CLIA-laboratory confirmation, and return of results by the clinical team" ], "must_hold": [ "Human geneticists review every candidate and a model output is never treated as a diagnosis", "Confirmatory testing in a certified laboratory before any result reaches a family", "De-identified data handled inside approved environments", "Yield expectations calibrated to the cohort: single-digit gains in heavily reviewed cases, and seven of the 18 here were rediscoveries" ], "echoes": [] }, "paired_incident": null, "headline": "o3-assisted reanalysis yields 11 new diagnoses and seven rediscoveries", "metric": "gave 18 families confirmed rare-disease diagnoses", "comparator": { "against": "prior local research records; no contemporaneous expert-reanalysis control", "before": "376 cases unresolved in the local research record, including some diagnosed elsewhere", "after": "18 confirmed local diagnoses: 11 new and seven rediscoveries; 4.8% overall", "basis": "measured", "quote": "We identified seven rediscoveries", "url": "https://doi.org/10.1056/AIcs2501343" }, "later": { "status": "unknown", "date": null, "note": "The paper calls for prospective multicenter evaluation, but no later development after the June 2026 publication was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-06-20-3da6", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://europepmc.org/abstract/MED/42529462", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Boston_Children%27s_Hospital", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Read the full paper, corrected 18 wholly new diagnoses to 11 new plus seven rediscoveries, and retained NBC for original patient and outside-expert interviews.", "source": "https://doi.org/10.1056/AIcs2501343", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' peer-reviewed study. 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No new source review is claimed.", "record_fields": [ "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "text", "text": "Researchers used o3 Deep Research to analyze de-identified clinical information and genetic variants." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "model_version", "system", "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "value_present", "value": { "kind": "text", "text": "The model received clinical notes, phenotype terms, and filtered genetic variants. It proposed a molecular diagnosis with supporting evidence." }, "provenance": { "kind": "legacy_record", "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.", "record_fields": [ "system", "ai_role", "replication", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "model_version": "o3 Deep Research" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "model_version" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Exact release not established.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "OpenAI o3 Deep Research, used as the reasoning layer of an LLM-assisted genome reanalysis workflow (Human Phenotype Ontology terms, clinician notes and a filtered variant table in; explanation-linked candidate diagnoses out)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "o3 Deep Research reanalysis at Boston Children's Hospital yields 18 confirmed local diagnoses, including 11 new diagnoses and seven rediscoveries", "headline": "o3-assisted reanalysis yields 11 new diagnoses and seven rediscoveries" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0211-source-0001", "AIBD-0211-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "62db4c890827eaf5d1a8644a78979a919343bda8e166a386481a64749fd0aa91" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Boston Children’s Hospital and OpenAI researchers used o3 Deep Research to reassess 376 rare-disease cases that remained unresolved in their local research records. They reported 18 confirmed local diagnoses, or 4.8%: 11 newly identified diagnoses and seven rediscoveries of diagnoses already made elsewhere. Clinicians reviewed candidates, arranged laboratory confirmation, and returned results to families. The paper’s discussion explains that some findings depended on later gene discoveries, revised classifications, previously uncalled variants, or information that was unavailable to earlier analyses. The researchers did not compare the model with a simultaneous expert reanalysis using the same current evidence. They also did not measure improvements in treatment, cost, or clinician time. NBC News separately interviewed Kyra Benton about receiving a diagnosis and sought comment from outside clinicians. The study was retrospective and involved OpenAI employees and funding, so it does not establish an independent estimate of the model’s added benefit.", "replication": { "produced_by": [ "Already-sequenced unsolved cases, mostly child-parent trios, assembled into a de-identified packet. Each packet held Human Phenotype Ontology terms, any clinician notes, age and sex. It also held a filtered variant table with rarity, predicted effect, ClinVar class and family signal quality", "A general-purpose reasoning model asked for the single most plausible molecular explanation and its evidence, not just a ranked gene. The prompt was refined first on cases of known diagnosis", "Time elapsed since the original analysis, so that newly published gene-disease links and reclassified variants existed to be found", "Expert adjudication under ACMG/AMP criteria by at least two reviewers, CLIA-laboratory confirmation, and return of results by the clinical team" ], "must_hold": [ "Human geneticists review every candidate and a model output is never treated as a diagnosis", "Confirmatory testing in a certified laboratory before any result reaches a family", "De-identified data handled inside approved environments", "Yield expectations calibrated to the cohort: single-digit gains in heavily reviewed cases, and seven of the 18 here were rediscoveries" ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0211-source-0001", "AIBD-0211-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Researchers gave the model de-identified symptoms, clinical notes, and genetic variants that earlier analyses had not resolved. They refined the prompt on known diagnoses, then asked for explanations of unresolved cases. At least two experts reviewed each candidate, and a certified laboratory confirmed diagnoses before clinicians returned results to families." } } }, "summary": { "total": 91, "addressed": 91, "known": 36, "reviewed": 4, "record_mapped": 32, "not_assessed": 55, "complete": false, "by_state": { "value_present": 36, "not_reported": 0, "unresolved": 0, "not_assessed": 55, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0239", "title": "OpenAI alert relayed through the FBI leads Espírito Santo police to detain a father a day before his stated date to kill his son", "summary": "OpenAI flagged a user's plan to kill his 8-year-old son; relayed via the FBI, Brazilian police held him a day before his stated date.", "date_observed": "2026-06-19", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "In 2026 a 36-year-old farmer in São Gabriel da Palha, Espírito Santo, Brazil, told ChatGPT about a plan to kill his 8-year-old son. He said he had offered R$50,000 to a hitman and set 20 June as the date. OpenAI's safety systems flagged the account, and the company referred it to the FBI. The FBI passed it to the Ministry of Justice's CyberLab. The Polícia Civil received it on 16 June and, under warrants, arrested him on 19 June. Officers seized his phone, four bottles of an unidentified substance and a knotted rope. He admitted the searches but denied intent. He was freed on habeas corpus on 13 August 2026 after 54 days, under an ankle monitor and a no-contact order. The inquiry continues.", "category": "protective response", "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant. OpenAI's moderation layer is built to route conversations that indicate plans to harm others to human reviewers. Those reviewers may refer an imminent threat to law enforcement, under a policy published 26 August 2025. The referral that triggered the arrest was that layer doing what it was built to do, not an emergent use of the assistant.", "system": "ChatGPT with OpenAI's safety-monitoring pipeline (automated classifiers plus human review and law-enforcement referral)", "model_version": null, "developer": "OpenAI", "deployer": "OpenAI", "location": "São Gabriel da Palha, Brazil", "domain": "Public safety", "segment": "Law enforcement and child protection", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-09-16-2a33" }, "ratings": [ { "group": "personal", "depth": 3, "reason": "The 8-year-old, and his mother who was placed under a no-contact order, were shielded from a plan the father had dated to 20 June. Police say the platform's information was corroborated when they arrived. He denies intent and no charge has been filed, so a life-saving effect is not established." }, { "group": "organizational", "depth": 2, "reason": "The Polícia Civil do Espírito Santo obtained a lead through the FBI and the Ministry of Justice CyberLab. It says it had no other way to get it. Its cybercrime chief called the alert another path for police work. The Ministry rated it the gravest of three such alerts in Brazil." } ], "ai_role": { "status": "assessed", "statement": "OpenAI's automated classifiers and human reviewers flagged the user's messages, and the company chose to refer the account to the FBI. The system did not predict a crime or act on its own. The warrants, the arrest and the evidence-gathering were police and court actions. OpenAI sent only the user's prompts, not ChatGPT's replies. What the assistant said to the user, and whether it helped or hindered him, is unknown." }, "evidence": [ { "kind": "report", "citation": "Polícia Civil do Espírito Santo (2026). Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial. pc.es.gov.br.", "title": "Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial", "url": "https://pc.es.gov.br/Not%C3%ADcia/alerta-do-fbi-e-do-ministerio-da-justica-auxiliam-pces-na-prisao-de-investigado-por-ameacas-contra-o-proprio-filho-em-inteligencia-artificial", "date": "2026-06-26", "written_by": "beneficiary", "quote": "Recebemos a denúncia no dia 16 de junho. Nas conversas analisadas, ele mencionava que os atos ocorreriam no dia 20." }, { "kind": "news report", "citation": "g1 Espírito Santo (2026). Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT. g1.globo.com.", "title": "Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT", "url": "https://g1.globo.com/es/espirito-santo/norte-noroeste-es/noticia/2026/06/25/pai-e-preso-por-planejar-a-morte-do-filho-para-nao-pagar-pensao-e-confessar-crime-ao-chatgpt.ghtml", "date": "2026-06-25", "written_by": "independent", "quote": "no último dia 19, um dia antes da data em que o crime aconteceria, segundo o delegado adjunto" }, { "kind": "news report", "citation": "Freitas, C. / A Gazeta (2026). Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES. agazeta.com.br.", "title": "Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES", "url": "https://www.agazeta.com.br/es/policia/conversa-com-ia-ajuda-policia-a-prender-pai-por-planejar-morte-de-filho-no-es-0626", "date": "2026-06-25", "written_by": "independent", "quote": "Os elementos foram fornecidos pela própria empresa responsável por essa inteligência artificial." }, { "kind": "news report", "citation": "Folha de S.Paulo (2026). Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta. folha.uol.com.br.", "title": "Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta", "url": "https://www1.folha.uol.com.br/cotidiano/2026/06/homem-e-preso-sob-suspeita-de-usar-ia-para-planejar-morte-de-filho-de-8-anos-plataforma-emitiu-alerta.shtml", "date": "2026-06-26", "written_by": "independent", "quote": "a OpenAI, desenvolvedora do ChatGPT, foi quem reportou ao FBI que um usuário realizava pesquisas frequentes relacionadas à intenção de matar o próprio filho" }, { "kind": "news report", "citation": "g1 Tecnologia (2026). Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades. g1.globo.com.", "title": "Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades", "url": "https://g1.globo.com/tecnologia/noticia/2026/06/27/como-chatgpt-identificou-plano-de-pai-para-matar-o-filho-e-levou-alerta-para-autoridades.ghtml", "date": "2026-06-27", "written_by": "independent", "quote": "Quando identificamos conversas que indicam um risco iminente e crível de dano a outras pessoas, podemos notificar as autoridades competentes" }, { "kind": "news report", "citation": "BBC News Brasil (2026). Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil? bbc.com/portuguese.", "title": "Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil?", "url": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "date": "2026-08-14", "written_by": "independent", "quote": "Na quinta-feira (13/8), ele foi solto após a Justiça conceder um habeas corpus apresentado pela defesa" }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. openai.com.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "date": "2025-08-26", "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ], "replication": { "produced_by": [ "The user typed explicit, dated threats against an identifiable child into ChatGPT over about two months, naming means and a hired killer", "OpenAI's moderation process, automated classifiers plus human review, flagged the account. The company chose to refer it to the FBI under its policy on imminent threats to others", "A standing FBI-to-Brazil channel through the Ministry of Justice CyberLab relayed the file to the state police within days", "The Polícia Civil do Espírito Santo prioritized the case, identified the user, confirmed the child existed and obtained warrants before the stated date" ], "must_hold": [ "The user discloses the plan to the assistant rather than keeping it offline", "The vendor's reviewers judge the threat credible and imminent and choose referral rather than only an account ban", "A cross-border law-enforcement channel exists and acts within days", "Local police can identify the user from the vendor's data and secure judicial warrants before the stated date" ], "echoes": [] }, "paired_incident": null, "headline": "OpenAI flag leads Brazilian police to hold a father a day early", "metric": "held him a day before his stated date", "comparator": null, "later": { "status": "litigated", "date": "2026-08-13", "note": "He was released on 13 August 2026 after a court granted habeas corpus, under an ankle monitor and a no-contact order, with the inquiry continuing.", "quote": "Na quinta-feira (13/8), ele foi solto após a Justiça conceder um habeas corpus apresentado pela defesa", "url": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-09-16-2a33", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports, the makers' press release and the beneficiary's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0239", "catalog_version": "1.0.0", "source_fingerprint": "40a6b91f6da11e7b61e17b845b9c4d3689ceaeaf7a17db97c70ddc003eb24a85", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0239-source-0001", "AIBD-0239-source-0002", "AIBD-0239-source-0003", "AIBD-0239-source-0004", "AIBD-0239-source-0005", "AIBD-0239-source-0006", "AIBD-0239-source-0007" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "OpenAI", "deployer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "OpenAI's automated classifiers and human reviewers flagged the user's messages, and the company chose to refer the account to the FBI. The system did not predict a crime or act on its own. The warrants, the arrest and the evidence-gathering were police and court actions. OpenAI sent only the user's prompts, not ChatGPT's replies. What the assistant said to the user, and whether it helped or hindered him, is unknown." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "OpenAI's automated classifiers and human reviewers flagged the user's messages, and the company chose to refer the account to the FBI. The system did not predict a crime or act on its own. The warrants, the arrest and the evidence-gathering were police and court actions. OpenAI sent only the user's prompts, not ChatGPT's replies. What the assistant said to the user, and whether it helped or hindered him, is unknown." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The 8-year-old, and his mother who was placed under a no-contact order, were shielded from a plan the father had dated to 20 June. Police say the platform's information was corroborated when they arrived. He denies intent and no charge has been filed, so a life-saving effect is not established." }, { "group": "organizational", "depth": 2, "reason": "The Polícia Civil do Espírito Santo obtained a lead through the FBI and the Ministry of Justice CyberLab. It says it had no other way to get it. Its cybercrime chief called the alert another path for police work. The Ministry rated it the gravest of three such alerts in Brazil." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: five independent news reports, the makers' press release and the beneficiary's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The 8-year-old, and his mother who was placed under a no-contact order, were shielded from a plan the father had dated to 20 June. Police say the platform's information was corroborated when they arrived. He denies intent and no charge has been filed, so a life-saving effect is not established." }, { "group": "organizational", "depth": 2, "reason": "The Polícia Civil do Espírito Santo obtained a lead through the FBI and the Ministry of Justice CyberLab. It says it had no other way to get it. Its cybercrime chief called the alert another path for police work. The Ministry rated it the gravest of three such alerts in Brazil." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "The 8-year-old, and his mother who was placed under a no-contact order, were shielded from a plan the father had dated to 20 June. Police say the platform's information was corroborated when they arrived. He denies intent and no charge has been filed, so a life-saving effect is not established." }, { "group": "organizational", "depth": 2, "reason": "The Polícia Civil do Espírito Santo obtained a lead through the FBI and the Ministry of Justice CyberLab. It says it had no other way to get it. Its cybercrime chief called the alert another path for police work. The Ministry rated it the gravest of three such alerts in Brazil." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": 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He said he had offered R$50,000 to a hitman and set 20 June as the date. OpenAI's safety systems flagged the account, and the company referred it to the FBI. The FBI passed it to the Ministry of Justice's CyberLab. The Polícia Civil received it on 16 June and, under warrants, arrested him on 19 June. Officers seized his phone, four bottles of an unidentified substance and a knotted rope. He admitted the searches but denied intent. He was freed on habeas corpus on 13 August 2026 after 54 days, under an ankle monitor and a no-contact order. 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Police say the platform's information was corroborated when they arrived. He denies intent and no charge has been filed, so a life-saving effect is not established." }, { "group": "organizational", "depth": 2, "reason": "The Polícia Civil do Espírito Santo obtained a lead through the FBI and the Ministry of Justice CyberLab. It says it had no other way to get it. Its cybercrime chief called the alert another path for police work. The Ministry rated it the gravest of three such alerts in Brazil." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "ChatGPT is a general-purpose conversational assistant. OpenAI's moderation layer is built to route conversations that indicate plans to harm others to human reviewers. Those reviewers may refer an imminent threat to law enforcement, under a policy published 26 August 2025. The referral that triggered the arrest was that layer doing what it was built to do, not an emergent use of the assistant." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "São Gabriel da Palha, Brazil", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "ChatGPT is a general-purpose conversational assistant. OpenAI's moderation layer is built to route conversations that indicate plans to harm others to human reviewers. Those reviewers may refer an imminent threat to law enforcement, under a policy published 26 August 2025. The referral that triggered the arrest was that layer doing what it was built to do, not an emergent use of the assistant." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-06-19", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-09-16-2a33", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "The user typed explicit, dated threats against an identifiable child into ChatGPT over about two months, naming means and a hired killer", "OpenAI's moderation process, automated classifiers plus human review, flagged the account. The company chose to refer it to the FBI under its policy on imminent threats to others", "A standing FBI-to-Brazil channel through the Ministry of Justice CyberLab relayed the file to the state police within days", "The Polícia Civil do Espírito Santo prioritized the case, identified the user, confirmed the child existed and obtained warrants before the stated date" ], "must_hold": [ "The user discloses the plan to the assistant rather than keeping it offline", "The vendor's reviewers judge the threat credible and imminent and choose referral rather than only an account ban", "A cross-border law-enforcement channel exists and acts within days", "Local police can identify the user from the vendor's data and secure judicial warrants before the stated date" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-09-16-2a33", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/OpenAI; https://en.wikipedia.org/wiki/OpenAI", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Public safety", "segment": "Law enforcement and child protection" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Polícia Civil do Espírito Santo (2026). Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial. pc.es.gov.br.", "title": "Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial", "url": "https://pc.es.gov.br/Not%C3%ADcia/alerta-do-fbi-e-do-ministerio-da-justica-auxiliam-pces-na-prisao-de-investigado-por-ameacas-contra-o-proprio-filho-em-inteligencia-artificial", "date": "2026-06-26", "written_by": "beneficiary", "quote": "Recebemos a denúncia no dia 16 de junho. Nas conversas analisadas, ele mencionava que os atos ocorreriam no dia 20." }, { "kind": "news report", "citation": "g1 Espírito Santo (2026). Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT. g1.globo.com.", "title": "Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT", "url": "https://g1.globo.com/es/espirito-santo/norte-noroeste-es/noticia/2026/06/25/pai-e-preso-por-planejar-a-morte-do-filho-para-nao-pagar-pensao-e-confessar-crime-ao-chatgpt.ghtml", "date": "2026-06-25", "written_by": "independent", "quote": "no último dia 19, um dia antes da data em que o crime aconteceria, segundo o delegado adjunto" }, { "kind": "news report", "citation": "Freitas, C. / A Gazeta (2026). Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES. agazeta.com.br.", "title": "Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES", "url": "https://www.agazeta.com.br/es/policia/conversa-com-ia-ajuda-policia-a-prender-pai-por-planejar-morte-de-filho-no-es-0626", "date": "2026-06-25", "written_by": "independent", "quote": "Os elementos foram fornecidos pela própria empresa responsável por essa inteligência artificial." }, { "kind": "news report", "citation": "Folha de S.Paulo (2026). Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta. folha.uol.com.br.", "title": "Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta", "url": "https://www1.folha.uol.com.br/cotidiano/2026/06/homem-e-preso-sob-suspeita-de-usar-ia-para-planejar-morte-de-filho-de-8-anos-plataforma-emitiu-alerta.shtml", "date": "2026-06-26", "written_by": "independent", "quote": "a OpenAI, desenvolvedora do ChatGPT, foi quem reportou ao FBI que um usuário realizava pesquisas frequentes relacionadas à intenção de matar o próprio filho" }, { "kind": "news report", "citation": "g1 Tecnologia (2026). Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades. g1.globo.com.", "title": "Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades", "url": "https://g1.globo.com/tecnologia/noticia/2026/06/27/como-chatgpt-identificou-plano-de-pai-para-matar-o-filho-e-levou-alerta-para-autoridades.ghtml", "date": "2026-06-27", "written_by": "independent", "quote": "Quando identificamos conversas que indicam um risco iminente e crível de dano a outras pessoas, podemos notificar as autoridades competentes" }, { "kind": "news report", "citation": "BBC News Brasil (2026). Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil? bbc.com/portuguese.", "title": "Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil?", "url": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "date": "2026-08-14", "written_by": "independent", "quote": "Na quinta-feira (13/8), ele foi solto após a Justiça conceder um habeas corpus apresentado pela defesa" }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. openai.com.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "date": "2025-08-26", "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0239-source-0001", "AIBD-0239-source-0002", "AIBD-0239-source-0003", "AIBD-0239-source-0004", "AIBD-0239-source-0005", "AIBD-0239-source-0006", "AIBD-0239-source-0007" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "report", "citation": "Polícia Civil do Espírito Santo (2026). Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial. pc.es.gov.br.", "title": "Alerta do FBI e do Ministério da Justiça auxiliam PCES na prisão de investigado por ameaças contra o próprio filho em Inteligência Artificial", "url": "https://pc.es.gov.br/Not%C3%ADcia/alerta-do-fbi-e-do-ministerio-da-justica-auxiliam-pces-na-prisao-de-investigado-por-ameacas-contra-o-proprio-filho-em-inteligencia-artificial", "date": "2026-06-26", "written_by": "beneficiary", "quote": "Recebemos a denúncia no dia 16 de junho. Nas conversas analisadas, ele mencionava que os atos ocorreriam no dia 20." }, { "kind": "news report", "citation": "g1 Espírito Santo (2026). Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT. g1.globo.com.", "title": "Pai é preso por planejar a morte do filho para não pagar pensão e confessar crime ao ChatGPT", "url": "https://g1.globo.com/es/espirito-santo/norte-noroeste-es/noticia/2026/06/25/pai-e-preso-por-planejar-a-morte-do-filho-para-nao-pagar-pensao-e-confessar-crime-ao-chatgpt.ghtml", "date": "2026-06-25", "written_by": "independent", "quote": "no último dia 19, um dia antes da data em que o crime aconteceria, segundo o delegado adjunto" }, { "kind": "news report", "citation": "Freitas, C. / A Gazeta (2026). Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES. agazeta.com.br.", "title": "Conversa com IA ajuda polícia a prender pai por planejar morte de filho no ES", "url": "https://www.agazeta.com.br/es/policia/conversa-com-ia-ajuda-policia-a-prender-pai-por-planejar-morte-de-filho-no-es-0626", "date": "2026-06-25", "written_by": "independent", "quote": "Os elementos foram fornecidos pela própria empresa responsável por essa inteligência artificial." }, { "kind": "news report", "citation": "Folha de S.Paulo (2026). Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta. folha.uol.com.br.", "title": "Homem é preso sob suspeita de usar IA para planejar morte de filho de 8 anos; plataforma emitiu alerta", "url": "https://www1.folha.uol.com.br/cotidiano/2026/06/homem-e-preso-sob-suspeita-de-usar-ia-para-planejar-morte-de-filho-de-8-anos-plataforma-emitiu-alerta.shtml", "date": "2026-06-26", "written_by": "independent", "quote": "a OpenAI, desenvolvedora do ChatGPT, foi quem reportou ao FBI que um usuário realizava pesquisas frequentes relacionadas à intenção de matar o próprio filho" }, { "kind": "news report", "citation": "g1 Tecnologia (2026). Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades. g1.globo.com.", "title": "Como ChatGPT identificou plano de pai para matar o filho e levou alerta para autoridades", "url": "https://g1.globo.com/tecnologia/noticia/2026/06/27/como-chatgpt-identificou-plano-de-pai-para-matar-o-filho-e-levou-alerta-para-autoridades.ghtml", "date": "2026-06-27", "written_by": "independent", "quote": "Quando identificamos conversas que indicam um risco iminente e crível de dano a outras pessoas, podemos notificar as autoridades competentes" }, { "kind": "news report", "citation": "BBC News Brasil (2026). Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil? bbc.com/portuguese.", "title": "Ele contou ao ChatGPT que queria matar o filho e foi preso — conversas com IA podem ser prova de crime no Brasil?", "url": "https://www.bbc.com/portuguese/articles/c8dn1l7vr6ro", "date": "2026-08-14", "written_by": "independent", "quote": "Na quinta-feira (13/8), ele foi solto após a Justiça conceder um habeas corpus apresentado pela defesa" }, { "kind": "press release", "citation": "OpenAI (2025). Helping people when they need it most. openai.com.", "title": "Helping people when they need it most", "url": "https://openai.com/index/helping-people-when-they-need-it-most/", "date": "2025-08-26", "written_by": "makers", "quote": "If human reviewers determine that a case involves an imminent threat of serious physical harm to others, we may refer it to law enforcement." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "OpenAI flagged a user's plan to kill his 8-year-old son; relayed via the FBI, Brazilian police held him a day before his stated date.", "account": "In 2026 a 36-year-old farmer in São Gabriel da Palha, Espírito Santo, Brazil, told ChatGPT about a plan to kill his 8-year-old son. He said he had offered R$50,000 to a hitman and set 20 June as the date. OpenAI's safety systems flagged the account, and the company referred it to the FBI. The FBI passed it to the Ministry of Justice's CyberLab. The Polícia Civil received it on 16 June and, under warrants, arrested him on 19 June. Officers seized his phone, four bottles of an unidentified substance and a knotted rope. He admitted the searches but denied intent. He was freed on habeas corpus on 13 August 2026 after 54 days, under an ankle monitor and a no-contact order. The inquiry continues." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "ChatGPT with OpenAI's safety-monitoring pipeline (automated classifiers plus human review and law-enforcement referral)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "OpenAI" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "OpenAI alert relayed through the FBI leads Espírito Santo police to detain a father a day before his stated date to kill his son", "headline": "OpenAI flag leads Brazilian police to hold a father a day early" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "40a6b91f6da11e7b61e17b845b9c4d3689ceaeaf7a17db97c70ddc003eb24a85" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "In 2026 a 36-year-old farmer in São Gabriel da Palha, Espírito Santo, Brazil, told ChatGPT about a plan to kill his 8-year-old son. He said he had offered R$50,000 to a hitman and set 20 June as the date. OpenAI's safety systems flagged the account, and the company referred it to the FBI. The FBI passed it to the Ministry of Justice's CyberLab. The Polícia Civil received it on 16 June and, under warrants, arrested him on 19 June. Officers seized his phone, four bottles of an unidentified substance and a knotted rope. He admitted the searches but denied intent. He was freed on habeas corpus on 13 August 2026 after 54 days, under an ankle monitor and a no-contact order. The inquiry continues.", "replication": { "produced_by": [ "The user typed explicit, dated threats against an identifiable child into ChatGPT over about two months, naming means and a hired killer", "OpenAI's moderation process, automated classifiers plus human review, flagged the account. The company chose to refer it to the FBI under its policy on imminent threats to others", "A standing FBI-to-Brazil channel through the Ministry of Justice CyberLab relayed the file to the state police within days", "The Polícia Civil do Espírito Santo prioritized the case, identified the user, confirmed the child existed and obtained warrants before the stated date" ], "must_hold": [ "The user discloses the plan to the assistant rather than keeping it offline", "The vendor's reviewers judge the threat credible and imminent and choose referral rather than only an account ban", "A cross-border law-enforcement channel exists and acts within days", "Local police can identify the user from the vendor's data and secure judicial warrants before the stated date" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 0, "record_mapped": 29, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0012", "title": "Fire and Rescue NSW drone with AI person detection finds two lost hikers off the Dead Horse Gap track within five hours", "summary": "23 June 2026: FRNSW drone AI flagged two lost hikers 500 m off track in Kosciuszko NP; found in under five hours, mild exposure", "date_observed": "2026-06-23", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "On Tuesday 23 June 2026 two men in their early 20s failed to reach a rendezvous on the Dead Horse Gap walking track. The track is in Kosciuszko National Park, about 35 km south-west of Jindabyne. They were reported overdue at about 7 pm. NSW Police formed an alpine search team with the State Emergency Service and asked Fire and Rescue NSW for drone support. FRNSW launched a remotely piloted aircraft with thermal imaging and AI detection software. The software flagged the pair in bushland about 500 m off the track, and the thermal camera confirmed the find. The drone's spotlight directed ground crews to them. They were located less than five hours after the report, had mild effects of exposure and declined treatment. FRNSW Inspector Phillip Eberle said the technology turned a potential long-term incident into a short-term one.", "category": "harm prevented", "unexpected": false, "purpose": "Built to detect people, vehicles and vessels in drone imagery for search and rescue; this benefit is that purpose.", "system": "Fire and Rescue NSW remotely piloted aircraft system with thermal imaging and AI person-detection software (software vendor not named in the sources)", "model_version": null, "developer": null, "deployer": "Fire and Rescue NSW", "location": "Dead Horse Gap track, Kosciuszko National Park, New South Wales, Australia (about 35 km south-west of Jindabyne)", "domain": "Search and rescue", "segment": "Fire and rescue services", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Two young men on a winter night in alpine bushland were found with mild exposure within five hours. The inspector overseeing the search says it could otherwise have become a long-term incident." }, { "group": "organizational", "depth": 2, "reason": "FRNSW, police and SES avoided an overnight multi-agency search and the risk to rescuers that Inspector Eberle described." } ], "ai_role": { "status": "assessed", "statement": "The AI flagged the hikers in the drone feed, and the thermal camera confirmed the find. The inspector overseeing the search credits it with cutting the search short. The hikers also signaled with a phone light, and the software vendor is not named. FRNSW's own media release was not available and is not cited. No cited source dates it." }, "evidence": [ { "kind": "news report", "citation": "McGuirk-Scolaro, M. (2026). Hikers lost in Kosciuszko National Park rescued by drones powered by AI. ABC News (Australia).", "title": "Hikers lost in Kosciuszko National Park rescued by drones powered by AI", "url": "https://www.abc.net.au/news/2026-06-27/lost-hikers-found-by-ai-drone-in-kosciuszko-national-park/106846712", "date": "2026-06-27", "written_by": "independent", "quote": "It's definitely helped make what could have been a long-term incident into a very short-term incident." }, { "kind": "news report", "citation": "Sams, C. (2026). How AI saved two hikers lost in the unforgiving alpine wilderness. About Regional.", "title": "How AI saved two hikers lost in the unforgiving alpine wilderness", "url": "https://aboutregional.com.au/how-ai-saved-two-hikers-lost-in-the-unforgiving-alpine-wilderness/509715/", "date": "2026-06-29", "written_by": "independent", "quote": "The AI scans the area and scans the information that it can see on its camera and says, 'OK, this item that I'm looking at has a 35 per cent chance of being human'." }, { "kind": "news report", "citation": "Matler, A. (2026). AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first. iTWire.", "title": "AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first", "url": "https://itwire.com/business-it-news/business-technology/ai-assisted-drone-helps-rescue-lost-kosciuszko-hikers-in-nsw-first", "date": "2026-06-30", "written_by": "independent", "quote": "a first-of-its-kind mission" } ], "replication": { "produced_by": [ "Thermal-capable drone with onboard AI person detection launched at night from the search command post", "Subjects within drone range whose detection can be confirmed by thermal camera" ], "must_hold": [ "Weather permits flight", "Detections are verified by the pilot before ground teams are directed" ], "echoes": [] }, "paired_incident": null, "headline": "FRNSW drone AI finds two lost hikers in under five hours", "metric": "located less than five hours after the report", "comparator": { "against": "a conventional search without the AI drone", "before": "several days (the inspector's estimate of the search time avoided)", "after": "less than five hours after they were reported missing", "basis": "assumed", "quote": "FRNSW Inspector and regional duty commander for the NSW Alpine area, Phillip Eberle, said the technology probably reduced the search by several days.", "url": "https://www.abc.net.au/news/2026-06-27/lost-hikers-found-by-ai-drone-in-kosciuszko-national-park/106846712" }, "later": { "status": "unknown", "date": null, "note": "No development dated after the 23 June 2026 rescue was found in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Restored the dropped middle clause of Inspector Eberle's sentence so that the About Regional quote is verbatim, moved the location from Jindabyne to the Dead Horse Gap track in Kosciuszko National Park where the sources place the hikers, and removed the 25 June 2026 date for FRNSW's media release because no cited source gives it.", "source": "https://aboutregional.com.au/how-ai-saved-two-hikers-lost-in-the-unforgiving-alpine-wilderness/509715/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.abc.net.au/news/2026-06-27/lost-hikers-found-by-ai-drone-in-kosciuszko-national-park/106846712", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Fire_and_Rescue_NSW", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0012", "catalog_version": "1.0.0", "source_fingerprint": "8c39dd93c59267c78bef620f5881fce0946039ab4712bd0a41925d9c0536c17e", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0012-source-0001", "AIBD-0012-source-0002", "AIBD-0012-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "deployer": "Fire and Rescue NSW" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The AI flagged the hikers in the drone feed, and the thermal camera confirmed the find. The inspector overseeing the search credits it with cutting the search short. The hikers also signaled with a phone light, and the software vendor is not named. FRNSW's own media release was not available and is not cited. No cited source dates it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "harm prevented", "ai_role": { "status": "assessed", "statement": "The AI flagged the hikers in the drone feed, and the thermal camera confirmed the find. The inspector overseeing the search credits it with cutting the search short. The hikers also signaled with a phone light, and the software vendor is not named. FRNSW's own media release was not available and is not cited. No cited source dates it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two young men on a winter night in alpine bushland were found with mild exposure within five hours. The inspector overseeing the search says it could otherwise have become a long-term incident." }, { "group": "organizational", "depth": 2, "reason": "FRNSW, police and SES avoided an overnight multi-agency search and the risk to rescuers that Inspector Eberle described." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: three independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two young men on a winter night in alpine bushland were found with mild exposure within five hours. The inspector overseeing the search says it could otherwise have become a long-term incident." }, { "group": "organizational", "depth": 2, "reason": "FRNSW, police and SES avoided an overnight multi-agency search and the risk to rescuers that Inspector Eberle described." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 3, "reason": "Two young men on a winter night in alpine bushland were found with mild exposure within five hours. The inspector overseeing the search says it could otherwise have become a long-term incident." }, { "group": "organizational", "depth": 2, "reason": "FRNSW, police and SES avoided an overnight multi-agency search and the risk to rescuers that Inspector Eberle described." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", 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(2026). Hikers lost in Kosciuszko National Park rescued by drones powered by AI. ABC News (Australia).", "title": "Hikers lost in Kosciuszko National Park rescued by drones powered by AI", "url": "https://www.abc.net.au/news/2026-06-27/lost-hikers-found-by-ai-drone-in-kosciuszko-national-park/106846712", "date": "2026-06-27", "written_by": "independent", "quote": "It's definitely helped make what could have been a long-term incident into a very short-term incident." }, { "kind": "news report", "citation": "Sams, C. (2026). How AI saved two hikers lost in the unforgiving alpine wilderness. About Regional.", "title": "How AI saved two hikers lost in the unforgiving alpine wilderness", "url": "https://aboutregional.com.au/how-ai-saved-two-hikers-lost-in-the-unforgiving-alpine-wilderness/509715/", "date": "2026-06-29", "written_by": "independent", "quote": "The AI scans the area and scans the information that it can see on its camera and says, 'OK, this item that I'm looking at has a 35 per cent chance of being human'." }, { "kind": "news report", "citation": "Matler, A. (2026). AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first. iTWire.", "title": "AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first", "url": "https://itwire.com/business-it-news/business-technology/ai-assisted-drone-helps-rescue-lost-kosciuszko-hikers-in-nsw-first", "date": "2026-06-30", "written_by": "independent", "quote": "a first-of-its-kind mission" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0012-source-0001", "AIBD-0012-source-0002", "AIBD-0012-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "McGuirk-Scolaro, M. (2026). Hikers lost in Kosciuszko National Park rescued by drones powered by AI. ABC News (Australia).", "title": "Hikers lost in Kosciuszko National Park rescued by drones powered by AI", "url": "https://www.abc.net.au/news/2026-06-27/lost-hikers-found-by-ai-drone-in-kosciuszko-national-park/106846712", "date": "2026-06-27", "written_by": "independent", "quote": "It's definitely helped make what could have been a long-term incident into a very short-term incident." }, { "kind": "news report", "citation": "Sams, C. (2026). How AI saved two hikers lost in the unforgiving alpine wilderness. 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AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first. iTWire.", "title": "AI-assisted drone helps rescue lost Kosciuszko hikers in NSW first", "url": "https://itwire.com/business-it-news/business-technology/ai-assisted-drone-helps-rescue-lost-kosciuszko-hikers-in-nsw-first", "date": "2026-06-30", "written_by": "independent", "quote": "a first-of-its-kind mission" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "23 June 2026: FRNSW drone AI flagged two lost hikers 500 m off track in Kosciuszko NP; found in under five hours, mild exposure", "account": "On Tuesday 23 June 2026 two men in their early 20s failed to reach a rendezvous on the Dead Horse Gap walking track. The track is in Kosciuszko National Park, about 35 km south-west of Jindabyne. They were reported overdue at about 7 pm. NSW Police formed an alpine search team with the State Emergency Service and asked Fire and Rescue NSW for drone support. FRNSW launched a remotely piloted aircraft with thermal imaging and AI detection software. The software flagged the pair in bushland about 500 m off the track, and the thermal camera confirmed the find. The drone's spotlight directed ground crews to them. They were located less than five hours after the report, had mild effects of exposure and declined treatment. FRNSW Inspector Phillip Eberle said the technology turned a potential long-term incident into a short-term one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Fire and Rescue NSW remotely piloted aircraft system with thermal imaging and AI person-detection software (software vendor not named in the sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Fire and Rescue NSW drone with AI person detection finds two lost hikers off the Dead Horse Gap track within five hours", "headline": "FRNSW drone AI finds two lost hikers in under five hours" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "8c39dd93c59267c78bef620f5881fce0946039ab4712bd0a41925d9c0536c17e" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "On Tuesday 23 June 2026 two men in their early 20s failed to reach a rendezvous on the Dead Horse Gap walking track. The track is in Kosciuszko National Park, about 35 km south-west of Jindabyne. They were reported overdue at about 7 pm. NSW Police formed an alpine search team with the State Emergency Service and asked Fire and Rescue NSW for drone support. FRNSW launched a remotely piloted aircraft with thermal imaging and AI detection software. The software flagged the pair in bushland about 500 m off the track, and the thermal camera confirmed the find. The drone's spotlight directed ground crews to them. They were located less than five hours after the report, had mild effects of exposure and declined treatment. FRNSW Inspector Phillip Eberle said the technology turned a potential long-term incident into a short-term one.", "replication": { "produced_by": [ "Thermal-capable drone with onboard AI person detection launched at night from the search command post", "Subjects within drone range whose detection can be confirmed by thermal camera" ], "must_hold": [ "Weather permits flight", "Detections are verified by the pilot before ground teams are directed" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0246", "title": "Odakyu Electric Railway starts an AI crossing image-analysis system at four Odawara Line crossings that signals approaching trains to stop when people are left inside", "summary": "ITmedia (22 Jun 2026): from 24 Jun 2026 AI analyzes existing crossing cameras, tracks pedestrians, wheelchair users, cyclists and motorcyclists and sends a brake signal to approaching trains; devel...", "date_observed": "2026-06-24", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "ITmedia's 岡田有花 reported on 22 Jun 2026 that Odakyu Electric Railway would introduce an “AI踏切画像解析システム” from 24 June 2026. It covers four crossings on its Odawara Line. They are Minami-Shinjuku Nos. 2, 4 and 5 between Minami-Shinjuku and Sangubashi stations, and Mukogaoka-Yuen No. 9 between Mukogaoka-Yuen and Ikuta stations. The AI analyzes footage from the existing safety-confirmation cameras in real time. It identifies and tracks pedestrians, wheelchair users, bicycles and motorcycles. When it detects someone left inside after the barriers come down, it sends a signal through the signaling equipment. That applies the brakes of approaching trains and lights the crossing's special signal lamps to alert crews. Both are released automatically once the crossing is clear. Images are used only for hazard detection, not to identify individuals, and analysis data are destroyed within a year. The system was developed by Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries. It was trialed from January 2023, with work on detection accuracy at night and in rain. railf.jp carried the same announcement on 25 Jun 2026. No detection events or outcomes are reported.", "category": "general benefit", "unexpected": false, "purpose": "The system is built to detect people left inside a closed crossing and stop approaching trains automatically.", "system": "AI踏切画像解析システム (AI crossing image-analysis system) using existing crossing cameras linked to signaling equipment", "model_version": null, "developer": "Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries", "deployer": "Odakyu Electric Railway", "location": null, "domain": "Railway safety", "segment": "Level-crossing obstacle detection", "benefit_type": "Increased Product Safety", "taxonomy_note": "Launch only; the automatic brake signal is a failsafe with no stop event documented.", "registry_ids": {}, "ratings": [ { "group": "societal", "depth": null, "reason": "No outcome is documented; the sources describe the start of operation." }, { "group": "organizational", "depth": null, "reason": "No operational outcome is documented." }, { "group": "personal", "depth": null, "reason": "No individual outcome is documented." } ], "ai_role": { "status": "unassessed", "statement": "The sources describe the intended detection-to-brake chain and the trial period; no detections, false alarms or accuracy figures are reported." }, "evidence": [ { "kind": "news report", "citation": "岡田有花 (22 Jun 2026). 踏切に取り残された人をAIで検知→列車を自動停止 小田急が実運用. ITmedia NEWS.", "title": "踏切に取り残された人をAIで検知→列車を自動停止 小田急が実運用", "url": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html", "date": "2026-06-22", "written_by": "independent", "quote": "名鉄EIエンジニア、トヨタシステムズ、東邦電機工業が開発し、2023年1月からの実証を行ってきた。" }, { "kind": "news report", "citation": "railf.jp (25 Jun 2026). 小田急，AIを活用した踏切画像解析システムを導入.", "title": "小田急，AIを活用した踏切画像解析システムを導入", "url": "https://railf.jp/news/2026/06/25/041500.html", "date": "2026-06-25", "written_by": "independent", "quote": "踏切内の取り残しが解消された場合は、これらの措置は自動で解除される" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-06-22-b4f8: AI System Deployed to Prevent Railway Crossing Accidents in Japan.", "title": "AI System Deployed to Prevent Railway Crossing Accidents in Japan", "url": "https://oecd.ai/en/incidents/2026-06-22-b4f8", "date": "2026-06-22", "written_by": "independent", "quote": "The system analyzes real-time camera footage to detect pedestrians, cyclists, and others left inside crossings, automatically triggering train stops to prevent accidents." } ], "replication": { "produced_by": [ "Existing crossing cameras with sufficient coverage of the enclosed area", "Integration with signaling equipment able to command train braking", "Three years of trials covering night and rain" ], "must_hold": [ "Detection accuracy holds in poor weather and lighting", "False detections do not stop trains so often that the function is disabled", "Signaling interlocks remain in place" ], "echoes": [ { "date": "2022-11-14", "setting": "Seibu Railway's AI and 3D-image crossing anomaly detection in full operation at three crossings, alerting drivers by special signal lamps (Response.jp)", "model_version": null, "outcome": "recurred", "source": "https://response.jp/article/2022/11/11/363968.html" }, { "date": "2020-08-12", "setting": "Optage and Sanyo Electric Railway trial of AI crossing-camera analysis at three crossings (Mynavi News)", "model_version": null, "outcome": "unknown", "source": "https://news.mynavi.jp/article/20200812-1216717" } ] }, "paired_incident": null, "headline": "Odakyu to brake trains when cameras see someone inside a crossing", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No development after the 24 June 2026 start was found; railf.jp says only that wider operation will be considered.", "quote": null, "url": null }, "value": null, "developer_country": "Japan", "deployer_country": "Japan", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://ja.wikipedia.org/wiki/%E5%90%8D%E9%89%84EI%E3%82%A8%E3%83%B3%E3%82%B8%E3%83%8B%E3%82%A2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Odakyu_Electric_Railway", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0246", "catalog_version": "1.0.0", "source_fingerprint": "cb230cae9b818512df19a1fff82ec3f6fd48700e059c91150c001b519ac9f745", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0246-source-0001", "AIBD-0246-source-0002", "AIBD-0246-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries", "deployer": "Odakyu Electric Railway" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The sources describe the intended detection-to-brake chain and the trial period; no detections, false alarms or accuracy figures are reported." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: two independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No outcome is documented; the sources describe the start of operation." }, { "group": "organizational", "reason": "No operational outcome is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ 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"family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": 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development after the 24 June 2026 start was found; railf.jp says only that wider operation will be considered." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0246" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "Launch only; the automatic brake signal is a failsafe with no stop event documented." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ITmedia's 岡田有花 reported on 22 Jun 2026 that Odakyu Electric Railway would introduce an “AI踏切画像解析システム” from 24 June 2026. It covers four crossings on its Odawara Line. They are Minami-Shinjuku Nos. 2, 4 and 5 between Minami-Shinjuku and Sangubashi stations, and Mukogaoka-Yuen No. 9 between Mukogaoka-Yuen and Ikuta stations. The AI analyzes footage from the existing safety-confirmation cameras in real time. It identifies and tracks pedestrians, wheelchair users, bicycles and motorcycles. When it detects someone left inside after the barriers come down, it sends a signal through the signaling equipment. That applies the brakes of approaching trains and lights the crossing's special signal lamps to alert crews. Both are released automatically once the crossing is clear. Images are used only for hazard detection, not to identify individuals, and analysis data are destroyed within a year. The system was developed by Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries. It was trialed from January 2023, with work on detection accuracy at night and in rain. railf.jp carried the same announcement on 25 Jun 2026. No detection events or outcomes are reported.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "societal", "reason": "No outcome is documented; the sources describe the start of operation." }, { "group": "organizational", "reason": "No operational outcome is documented." }, { "group": "personal", "reason": "No individual outcome is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "The system is built to detect people left inside a closed crossing and stop approaching trains automatically." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer_country": "Japan", "deployer_country": "Japan" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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ITmedia NEWS.", "title": "踏切に取り残された人をAIで検知→列車を自動停止 小田急が実運用", "url": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html", "date": "2026-06-22", "written_by": "independent", "quote": "名鉄EIエンジニア、トヨタシステムズ、東邦電機工業が開発し、2023年1月からの実証を行ってきた。" }, { "kind": "news report", "citation": "railf.jp (25 Jun 2026). 小田急，AIを活用した踏切画像解析システムを導入.", "title": "小田急，AIを活用した踏切画像解析システムを導入", "url": "https://railf.jp/news/2026/06/25/041500.html", "date": "2026-06-25", "written_by": "independent", "quote": "踏切内の取り残しが解消された場合は、これらの措置は自動で解除される" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-06-22-b4f8: AI System Deployed to Prevent Railway Crossing Accidents in Japan.", "title": "AI System Deployed to Prevent Railway Crossing Accidents in Japan", "url": "https://oecd.ai/en/incidents/2026-06-22-b4f8", "date": "2026-06-22", "written_by": "independent", "quote": "The system analyzes real-time camera footage to detect pedestrians, cyclists, and others left inside crossings, automatically triggering train stops to prevent accidents." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0246-source-0001", "AIBD-0246-source-0002", "AIBD-0246-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "岡田有花 (22 Jun 2026). 踏切に取り残された人をAIで検知→列車を自動停止 小田急が実運用. ITmedia NEWS.", "title": "踏切に取り残された人をAIで検知→列車を自動停止 小田急が実運用", "url": "https://www.itmedia.co.jp/news/articles/2606/22/news125.html", "date": "2026-06-22", "written_by": "independent", "quote": "名鉄EIエンジニア、トヨタシステムズ、東邦電機工業が開発し、2023年1月からの実証を行ってきた。" }, { "kind": "news report", "citation": "railf.jp (25 Jun 2026). 小田急，AIを活用した踏切画像解析システムを導入.", "title": "小田急，AIを活用した踏切画像解析システムを導入", "url": "https://railf.jp/news/2026/06/25/041500.html", "date": "2026-06-25", "written_by": "independent", "quote": "踏切内の取り残しが解消された場合は、これらの措置は自動で解除される" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor, incident 2026-06-22-b4f8: AI System Deployed to Prevent Railway Crossing Accidents in Japan.", "title": "AI System Deployed to Prevent Railway Crossing Accidents in Japan", "url": "https://oecd.ai/en/incidents/2026-06-22-b4f8", "date": "2026-06-22", "written_by": "independent", "quote": "The system analyzes real-time camera footage to detect pedestrians, cyclists, and others left inside crossings, automatically triggering train stops to prevent accidents." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "ITmedia (22 Jun 2026): from 24 Jun 2026 AI analyzes existing crossing cameras, tracks pedestrians, wheelchair users, cyclists and motorcyclists and sends a brake signal to approaching trains; devel...", "account": "ITmedia's 岡田有花 reported on 22 Jun 2026 that Odakyu Electric Railway would introduce an “AI踏切画像解析システム” from 24 June 2026. It covers four crossings on its Odawara Line. They are Minami-Shinjuku Nos. 2, 4 and 5 between Minami-Shinjuku and Sangubashi stations, and Mukogaoka-Yuen No. 9 between Mukogaoka-Yuen and Ikuta stations. The AI analyzes footage from the existing safety-confirmation cameras in real time. It identifies and tracks pedestrians, wheelchair users, bicycles and motorcycles. When it detects someone left inside after the barriers come down, it sends a signal through the signaling equipment. That applies the brakes of approaching trains and lights the crossing's special signal lamps to alert crews. Both are released automatically once the crossing is clear. Images are used only for hazard detection, not to identify individuals, and analysis data are destroyed within a year. The system was developed by Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries. It was trialed from January 2023, with work on detection accuracy at night and in rain. railf.jp carried the same announcement on 25 Jun 2026. No detection events or outcomes are reported." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AI踏切画像解析システム (AI crossing image-analysis system) using existing crossing cameras linked to signaling equipment" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Odakyu Electric Railway starts an AI crossing image-analysis system at four Odawara Line crossings that signals approaching trains to stop when people are left inside", "headline": "Odakyu to brake trains when cameras see someone inside a crossing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "cb230cae9b818512df19a1fff82ec3f6fd48700e059c91150c001b519ac9f745" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "ITmedia's 岡田有花 reported on 22 Jun 2026 that Odakyu Electric Railway would introduce an “AI踏切画像解析システム” from 24 June 2026. It covers four crossings on its Odawara Line. They are Minami-Shinjuku Nos. 2, 4 and 5 between Minami-Shinjuku and Sangubashi stations, and Mukogaoka-Yuen No. 9 between Mukogaoka-Yuen and Ikuta stations. The AI analyzes footage from the existing safety-confirmation cameras in real time. It identifies and tracks pedestrians, wheelchair users, bicycles and motorcycles. When it detects someone left inside after the barriers come down, it sends a signal through the signaling equipment. That applies the brakes of approaching trains and lights the crossing's special signal lamps to alert crews. Both are released automatically once the crossing is clear. Images are used only for hazard detection, not to identify individuals, and analysis data are destroyed within a year. The system was developed by Meitetsu EI Engineer, Toyota Systems and Toho Electric Industries. It was trialed from January 2023, with work on detection accuracy at night and in rain. railf.jp carried the same announcement on 25 Jun 2026. No detection events or outcomes are reported.", "replication": { "produced_by": [ "Existing crossing cameras with sufficient coverage of the enclosed area", "Integration with signaling equipment able to command train braking", "Three years of trials covering night and rain" ], "must_hold": [ "Detection accuracy holds in poor weather and lighting", "False detections do not stop trains so often that the function is disabled", "Signaling interlocks remain in place" ], "echoes": [ { "date": "2022-11-14", "setting": "Seibu Railway's AI and 3D-image crossing anomaly detection in full operation at three crossings, alerting drivers by special signal lamps (Response.jp)", "outcome": "recurred", "source": "https://response.jp/article/2022/11/11/363968.html" }, { "date": "2020-08-12", "setting": "Optage and Sanyo Electric Railway trial of AI crossing-camera analysis at three crossings (Mynavi News)", "outcome": "unknown", "source": "https://news.mynavi.jp/article/20200812-1216717" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0360", "title": "Transport for NSW launches the PAWS AI animal-detection and smart-signage trial on the Monaro Highway between Bredbo and Williamsdale; no outcome yet", "summary": "Transport for NSW's Protective Animal Warning System: two AI-enabled roadside cameras on a 13 km Monaro Highway stretch trigger driver warnings; trial announced 18 July 2026, no results yet.", "date_observed": "2026-07-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The NSW Government announced its Protective Animal Warning System trial on July 18, 2026. Transport for NSW developed the system, which uses thermal and optical cameras with AI to recognize wildlife and trigger roadside warnings. The announcement describes training at Yennora and Symbio Wildlife Park before a live trial on the Monaro Highway. About Regional’s separate interviews add the planned two-camera layout on a 13 km stretch between Bredbo and Williamsdale and the role of local wildlife carers. The intended benefit is fewer collisions after drivers receive warnings. Neither source reports a measured change in detection accuracy, driver behavior, or collisions.", "category": "general benefit", "unexpected": false, "purpose": "Detect wildlife near the road and warn drivers dynamically to limit wildlife-vehicle strikes; no benefit has yet been observed.", "system": "PAWS (Protective Animal Warning System): heat-sensing and optical roadside cameras with a species-trained AI model triggering warning signs", "model_version": null, "developer": "Transport for NSW", "deployer": "Transport for NSW", "location": "Monaro Highway between Bredbo and Williamsdale, New South Wales, Australia", "domain": "Road safety and wildlife-vehicle collision prevention", "segment": "State transport agency trial", "benefit_type": "Increased Product Safety", "taxonomy_note": "Trial launch only; the type names the driver-warning feature, with wildlife as co-beneficiary.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "The trial had not started at the time of the report." }, { "group": "organizational", "depth": null, "reason": "No detections or sign activations reported." }, { "group": "societal", "depth": null, "reason": "No collision data." } ], "ai_role": { "status": "unassessed", "statement": "The original government announcement describes AI recognition of animals on thermal and optical images, followed by dynamic driver warnings. The intended contribution is identifiable, but the reviewed sources contain no measured trial outcomes." }, "evidence": [ { "kind": "press release", "citation": "NSW Government. New AI animal detection and smart signage trial working to limit wildlife-vehicle strikes. 2026-07-18.", "title": "New AI animal detection and smart signage trial working to limit wildlife-vehicle strikes", "url": "https://www.nsw.gov.au/ministerial-releases/new-ai-animal-detection-and-smart-signage-trial-working-to-limit-wildlife-vehicle-strikes", "date": "2026-07-18", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Sams, C. (2026). AI cameras to be extra set of eyes on roadside wildlife in Monaro Highway trial. About Regional, 18 Jul 2026.", "title": "AI cameras to be extra set of eyes on roadside wildlife in Monaro Highway trial", "url": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/", "date": "2026-07-18", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "Roadside thermal and optical cameras with an on-site AI species model", "Dynamic warning signs linked to detections", "Solar power at remote sites", "State agency funding for a multi-year trial" ], "must_hold": [ "Trial start and continued operation to 2027/2028", "Detection accuracy across target species", "Driver compliance with dynamic warnings", "Collision monitoring to measure effect" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot: 3 mph slowdown measured, collisions prevented not established", "model_version": null, "outcome": "unknown", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html" } ] }, "paired_incident": null, "headline": "Transport for NSW trials PAWS wildlife cameras; no results yet", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "The trial was due to start in August 2026 and run until 2027/2028; no result has been reported in the cited sources.", "quote": null, "url": null }, "value": null, "developer_country": "Australia", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Transport_for_NSW; https://en.wikipedia.org/wiki/Transport_for_NSW", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Added the government’s original announcement and retained local reporting because it adds direct interviews and deployment details.", "source": "https://www.nsw.gov.au/ministerial-releases/new-ai-animal-detection-and-smart-signage-trial-working-to-limit-wildlife-vehicle-strikes", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0360", "catalog_version": "1.0.0", "source_fingerprint": "67b5b9574f1a0f6c7935bea3c45c4df7b4e10f0a210931adeaccea621a403545", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0360-source-0001", "AIBD-0360-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Transport for NSW", "deployer": "Transport for NSW" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. 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New AI animal detection and smart signage trial working to limit wildlife-vehicle strikes. 2026-07-18." }, { "source_refs": [ "AIBD-0360-source-0002" ], "url": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/", "title": "AI cameras to be extra set of eyes on roadside wildlife in Monaro Highway trial", "published_on": "2026-07-18", "relationship": "independent", "citation": "Sams, C. (2026). AI cameras to be extra set of eyes on roadside wildlife in Monaro Highway trial. About Regional, 18 Jul 2026." } ], "excluded_republications": [ { "url": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/", "title": "AI cameras to be extra set of eyes on roadside wildlife (deployment)", "published_on": "2026-07-18", "relationship": "Repeated quotation or alternate version of a retained original work", "previous_source_ref": "AIBD-0360-source-0002" } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0360-source-0001", "retained_source_order": [ "AIBD-0360-source-0001", "AIBD-0360-source-0002" ], "ordering_basis": "The source that directly supports the central case leads. Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "System development, species detection, and trial intent", "source_chain": [ { "url": "https://www.nsw.gov.au/ministerial-releases/new-ai-animal-detection-and-smart-signage-trial-working-to-limit-wildlife-vehicle-strikes", "locator": "Development, training, and Monaro trial description", "role": "Original government announcement", "access_status": "Full relevant text reviewed", "published_on": "2026-07-18" } ], "limitations": [ "No measured collision reduction or driver response reported" ], "source_ref": "AIBD-0360-source-0001" }, { "claim": "Local deployment and wildlife-carer contribution", "source_chain": [ { "url": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/", "locator": "Interviews with LAOKO’s Peter Gibson and Transport for NSW", "role": "Original local interviews and reporting", "access_status": "Full relevant text reviewed", "published_on": "2026-07-18" } ], "limitations": [ "Site selection and intended operations do not establish outcomes" ], "source_ref": "AIBD-0360-source-0002" } ], "limitations": [] } }, "provenance": { "kind": "source_review", "basis": "Added the government’s original announcement and retained local reporting because it adds direct interviews and deployment details.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0360-source-0001", "AIBD-0360-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Transport for NSW's Protective Animal Warning System: two AI-enabled roadside cameras on a 13 km Monaro Highway stretch trigger driver warnings; trial announced 18 July 2026, no results yet.", "account": "The NSW Government announced its Protective Animal Warning System trial on July 18, 2026. Transport for NSW developed the system, which uses thermal and optical cameras with AI to recognize wildlife and trigger roadside warnings. The announcement describes training at Yennora and Symbio Wildlife Park before a live trial on the Monaro Highway. About Regional’s separate interviews add the planned two-camera layout on a 13 km stretch between Bredbo and Williamsdale and the role of local wildlife carers. The intended benefit is fewer collisions after drivers receive warnings. Neither source reports a measured change in detection accuracy, driver behavior, or collisions." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0360-source-0001", "AIBD-0360-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "PAWS (Protective Animal Warning System): heat-sensing and optical roadside cameras with a species-trained AI model triggering warning signs" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Transport for NSW" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Transport for NSW launches the PAWS AI animal-detection and smart-signage trial on the Monaro Highway between Bredbo and Williamsdale; no outcome yet", "headline": "Transport for NSW trials PAWS wildlife cameras; no results yet" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "67b5b9574f1a0f6c7935bea3c45c4df7b4e10f0a210931adeaccea621a403545" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The NSW Government announced its Protective Animal Warning System trial on July 18, 2026. Transport for NSW developed the system, which uses thermal and optical cameras with AI to recognize wildlife and trigger roadside warnings. The announcement describes training at Yennora and Symbio Wildlife Park before a live trial on the Monaro Highway. About Regional’s separate interviews add the planned two-camera layout on a 13 km stretch between Bredbo and Williamsdale and the role of local wildlife carers. The intended benefit is fewer collisions after drivers receive warnings. Neither source reports a measured change in detection accuracy, driver behavior, or collisions.", "replication": { "produced_by": [ "Roadside thermal and optical cameras with an on-site AI species model", "Dynamic warning signs linked to detections", "Solar power at remote sites", "State agency funding for a multi-year trial" ], "must_hold": [ "Trial start and continued operation to 2027/2028", "Detection accuracy across target species", "Driver compliance with dynamic warnings", "Collision monitoring to measure effect" ], "echoes": [ { "date": "2026-10-20", "setting": "Virginia Route 460 thermal-camera AI pilot: 3 mph slowdown measured, collisions prevented not established", "outcome": "unknown", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html" } ] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0360-source-0001", "AIBD-0360-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 4, "record_mapped": 24, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0292", "title": "Consumer wearable rhythm strips let a 59-year-old man skip repeat 30-day monitoring and go straight to pulmonary vein isolation for paroxysmal atrial fibrillation", "summary": "Virginia family physicians report that AF episodes a 59-year-old recorded on a consumer wearable, confirmed by a cardiologist, expedited referral and ablation; AF-free off drugs at follow-up.", "date_observed": "2026-07-24", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Joy S. Elliott of Riverside Family Medicine Medical Center, Newport News, Virginia, and Andrew H. Hagen of Edward Via College of Osteopathic Medicine, Blacksburg, Virginia, reported a case. It appeared in Osteopathic Family Physician (volume 18, number 3, Summer 2026, pages 56–59), published 24 July 2026. The event dates are not given. The patient is a 59-year-old man with two years of weekly episodes of fast heart rate, palpitations and fatigue, lasting up to 24 hours. He had documented several episodes through his smartphone using a consumer wearable device. A cardiologist friend had judged them paroxysmal atrial fibrillation (AF), but he had not sought formal evaluation. At the family medicine clinic his examination and bloods were normal. Initial management used the wearable for ambulatory rhythm monitoring to separate AF from premature beats. A confirmed episode lasting several hours prompted laboratory work-up and cardiology referral. Echocardiography showed a 4.1 cm aortic root and ascending aorta with normal ventricular function. Thirty-day monitoring was recommended. Because the wearable's rhythm strips already documented paroxysmal AF, his care went straight to treatment options. He chose pulmonary vein isolation ablation and reported dramatic improvement. He had one recurrence while skiing that responded to flecainide. At follow-up he was asymptomatic and AF-free without antiarrhythmic drugs, declining anticoagulation at a CHA2DS2-VASc score of 1. The device's brand is not named. The PDF was downloadable from the ACOFP site, although the article page says membership is required.", "category": "benefit created", "unexpected": false, "purpose": "Consumer wearables with electrocardiogram (ECG) recording are built to let wearers capture their rhythm during symptoms. Using those strips to document paroxysmal AF and shorten the path to ablation was that purpose.", "system": "Consumer wearable device with smartphone-linked rhythm-strip recording (brand and model not stated)", "model_version": null, "developer": "Not stated (the report does not name the device's maker)", "deployer": null, "location": "Newport News, Virginia, United States (corresponding author's clinic; the case text does not name the clinic)", "domain": "Healthcare (cardiology; primary care)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 2, "reason": "The patient's own recordings replaced repeat 30-day monitoring and took him directly to ablation. After it he was asymptomatic and AF-free off antiarrhythmics. That is material relief of a two-year symptom burden, with the authors' note that ablation is not curative." }, { "group": "organizational", "depth": 1, "reason": "The authors say the approach minimized the burden and costs of redundant diagnostic processes by avoiding repeat ambulatory monitoring. No figure is given." } ], "ai_role": { "status": "assessed", "statement": "The device recorded rhythm strips during symptomatic episodes. The AF determination is attributed to a cardiologist friend and later to clinical confirmation. The report does not say whether the device's own algorithm classified any episode. The device's contribution was therefore the documentation that let clinicians forgo further monitoring, not an automated diagnosis. The brand is unknown. Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care." }, "evidence": [ { "kind": "case report", "citation": "Elliott JS, Hagen AH (2026). Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation. Osteopathic Family Physician 18(3):56-59. doi:10.33181/18308. Case presentation, p. 57; discussion and limitations, pp. 58–59.", "title": "Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation", "url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "date": "2026-07-24", "written_by": "independent", "quote": null } ], "replication": { "produced_by": [ "A wearer who records rhythm strips on a consumer wearable during symptomatic episodes over an extended period", "A clinician (here a cardiologist friend, then the clinic) willing to accept those strips as documentation of paroxysmal AF", "A referral pathway that treats the documentation as sufficient to proceed to ablation without repeat 30-day monitoring" ], "must_hold": [ "The episodes are frequent and long enough to be captured on a user-triggered device", "The wearer has the device, the smartphone and the skills to record and share the strips (the authors list these as barriers for other patients)" ], "echoes": [ { "date": null, "setting": "Apple Heart Study and Fitbit Heart Study, cited in the report's introduction: 34% of Apple irregular-pulse notifications and about one-third of Fitbit irregular-rhythm detections were confirmed as AF on ECG patch", "model_version": null, "outcome": "recurred", "source": "Elliott JS, Hagen AH (2026), Osteopathic Family Physician 18(3):56-59, introduction, citing Perez et al. 2019 and Lubitz et al. 2022" } ] }, "paired_incident": null, "headline": "Wearable rhythm strips let a 59-year-old go straight to ablation", "metric": null, "comparator": { "against": "repeat 30-day ambulatory cardiac monitoring", "before": "it was recommended that the patient undergo continued cardiac monitoring for 30 days to attempt to document the arrhythmia", "after": "his care was able to be expedited straight to discussing treatment options", "basis": "assumed", "quote": "Given continued symptomatic episodes, it was recommended that the patient undergo continued cardiac monitoring for 30 days to attempt to document the arrhythmia. However, given the patient had documented paroxysmal AF from the rhythm strips produced by his consumer-wearable device, his care was able to be expedited straight to discussing treatment options.", "url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf" }, "later": { "status": "unknown", "date": null, "note": "The July 2026 report is the only account; its follow-up (asymptomatic and AF-free without antiarrhythmic therapy) is undated and nothing published later was found.", "quote": null, "url": null }, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf?sfvrsn=913e1e01_1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated four excerpts and formats into one original clinical case report. Read the full four-page PDF, its tables and references. The case attributes AF identification to clinicians and never identifies the wearable's brand or an algorithmic contribution. Preserved the documented clinical benefit and flagged the unresolved AI qualification for review.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Clarified that an AI contribution is unconfirmed. Retained the case and its depth assessment, but withheld it from homepage highlights.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" } ], "confidence": "studied", "shade": "high", "claim_status": "Independently studied", "claim_basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "profile": { "case_id": "AIBD-0292", "catalog_version": "1.0.0", "source_fingerprint": "f89aa5f70b0c588b2cc259050fae432822cc1fdf3cbf60d8a0c25eaae1079a51", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0292-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The device recorded rhythm strips during symptomatic episodes. The AF determination is attributed to a cardiologist friend and later to clinical confirmation. The report does not say whether the device's own algorithm classified any episode. The device's contribution was therefore the documentation that let clinicians forgo further monitoring, not an automated diagnosis. The brand is unknown. Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care." } } }, "provenance": { "kind": "source_review", "basis": "Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The wearable recorded heart rhythms that clinicians interpreted as atrial fibrillation. Those recordings let them proceed without further monitoring. The report does not establish that an automated classifier contributed.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "The device recorded rhythm strips during symptomatic episodes. The AF determination is attributed to a cardiologist friend and later to clinical confirmation. The report does not say whether the device's own algorithm classified any episode. The device's contribution was therefore the documentation that let clinicians forgo further monitoring, not an automated diagnosis. The brand is unknown. Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care." } } }, "provenance": { "kind": "source_review", "basis": "Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The documented benefit came from wearable recordings and clinical interpretation. An AI contribution is unconfirmed.", "editor_note": "" } }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The patient's own recordings replaced repeat 30-day monitoring and took him directly to ablation. After it he was asymptomatic and AF-free off antiarrhythmics. That is material relief of a two-year symptom burden, with the authors' note that ablation is not curative." }, { "group": "organizational", "depth": 1, "reason": "The authors say the approach minimized the burden and costs of redundant diagnostic processes by avoiding repeat ambulatory monitoring. No figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "high", "evidence_word": "studied", "claim_status": "Independently studied", "basis": "Sources: one independent case report. The cited evidence includes no finding by a regulator or court.", "interpretation": "Existing display rule retained. Originality, authorship, and independence are assessed separately in the source lineage. Repeated formats, quotations, and versions are not independent confirmations." } }, "provenance": { "kind": "source_review", "basis": "Rechecked source authorship and independence without changing benefit-depth ratings.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The patient's own recordings replaced repeat 30-day monitoring and took him directly to ablation. After it he was asymptomatic and AF-free off antiarrhythmics. That is material relief of a two-year symptom burden, with the authors' note that ablation is not curative." }, { "group": "organizational", "depth": 1, "reason": "The authors say the approach minimized the burden and costs of redundant diagnostic processes by avoiding repeat ambulatory monitoring. No figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The patient's own recordings replaced repeat 30-day monitoring and took him directly to ablation. After it he was asymptomatic and AF-free off antiarrhythmics. That is material relief of a two-year symptom burden, with the authors' note that ablation is not curative." }, { "group": "organizational", "depth": 1, "reason": "The authors say the approach minimized the burden and costs of redundant diagnostic processes by avoiding repeat ambulatory monitoring. No figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"record_fields", "fields": { "account": "Joy S. Elliott of Riverside Family Medicine Medical Center, Newport News, Virginia, and Andrew H. Hagen of Edward Via College of Osteopathic Medicine, Blacksburg, Virginia, reported a case. It appeared in Osteopathic Family Physician (volume 18, number 3, Summer 2026, pages 56–59), published 24 July 2026. The event dates are not given. The patient is a 59-year-old man with two years of weekly episodes of fast heart rate, palpitations and fatigue, lasting up to 24 hours. He had documented several episodes through his smartphone using a consumer wearable device. A cardiologist friend had judged them paroxysmal atrial fibrillation (AF), but he had not sought formal evaluation. At the family medicine clinic his examination and bloods were normal. Initial management used the wearable for ambulatory rhythm monitoring to separate AF from premature beats. A confirmed episode lasting several hours prompted laboratory work-up and cardiology referral. Echocardiography showed a 4.1 cm aortic root and ascending aorta with normal ventricular function. Thirty-day monitoring was recommended. Because the wearable's rhythm strips already documented paroxysmal AF, his care went straight to treatment options. He chose pulmonary vein isolation ablation and reported dramatic improvement. He had one recurrence while skiing that responded to flecainide. At follow-up he was asymptomatic and AF-free without antiarrhythmic drugs, declining anticoagulation at a CHA2DS2-VASc score of 1. The device's brand is not named. The PDF was downloadable from the ACOFP site, although the article page says membership is required.", "benefit_type": "Improved Physical Health" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 2, "reason": "The patient's own recordings replaced repeat 30-day monitoring and took him directly to ablation. After it he was asymptomatic and AF-free off antiarrhythmics. That is material relief of a two-year symptom burden, with the authors' note that ablation is not curative." }, { "group": "organizational", "depth": 1, "reason": "The authors say the approach minimized the burden and costs of redundant diagnostic processes by avoiding repeat ambulatory monitoring. No figure is given." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Consumer wearables with electrocardiogram (ECG) recording are built to let wearers capture their rhythm during symptoms. Using those strips to document paroxysmal AF and shorten the path to ablation was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Newport News, Virginia, United States (corresponding author's clinic; the case text does not name the clinic)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Consumer wearables with electrocardiogram (ECG) recording are built to let wearers capture their rhythm during symptoms. Using those strips to document paroxysmal AF and shorten the path to ablation was that purpose." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-07-24", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf?sfvrsn=913e1e01_1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated four excerpts and formats into one original clinical case report. Read the full four-page PDF, its tables and references. The case attributes AF identification to clinicians and never identifies the wearable's brand or an algorithmic contribution. Preserved the documented clinical benefit and flagged the unresolved AI qualification for review.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Clarified that an AI contribution is unconfirmed. Retained the case and its depth assessment, but withheld it from homepage highlights.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A wearer who records rhythm strips on a consumer wearable during symptomatic episodes over an extended period", "A clinician (here a cardiologist friend, then the clinic) willing to accept those strips as documentation of paroxysmal AF", "A referral pathway that treats the documentation as sufficient to proceed to ablation without repeat 30-day monitoring" ], "must_hold": [ "The episodes are frequent and long enough to be captured on a user-triggered device", "The wearer has the device, the smartphone and the skills to record and share the strips (the authors list these as barriers for other patients)" ], "echoes": [ { "setting": "Apple Heart Study and Fitbit Heart Study, cited in the report's introduction: 34% of Apple irregular-pulse notifications and about one-third of Fitbit irregular-rhythm detections were confirmed as AF on ECG patch", "outcome": "recurred", "source": "Elliott JS, Hagen AH (2026), Osteopathic Family Physician 18(3):56-59, introduction, citing Perez et al. 2019 and Lubitz et al. 2022" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A wearer who records rhythm strips on a consumer wearable during symptomatic episodes over an extended period", "A clinician (here a cardiologist friend, then the clinic) willing to accept those strips as documentation of paroxysmal AF", "A referral pathway that treats the documentation as sufficient to proceed to ablation without repeat 30-day monitoring" ], "must_hold": [ "The episodes are frequent and long enough to be captured on a user-triggered device", "The wearer has the device, the smartphone and the skills to record and share the strips (the authors list these as barriers for other patients)" ], "echoes": [ { "setting": "Apple Heart Study and Fitbit Heart Study, cited in the report's introduction: 34% of Apple irregular-pulse notifications and about one-third of Fitbit irregular-rhythm detections were confirmed as AF on ECG patch", "outcome": "recurred", "source": "Elliott JS, Hagen AH (2026), Osteopathic Family Physician 18(3):56-59, introduction, citing Perez et al. 2019 and Lubitz et al. 2022" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf?sfvrsn=913e1e01_1", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated four excerpts and formats into one original clinical case report. Read the full four-page PDF, its tables and references. The case attributes AF identification to clinicians and never identifies the wearable's brand or an algorithmic contribution. Preserved the documented clinical benefit and flagged the unresolved AI qualification for review.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Clarified that an AI contribution is unconfirmed. Retained the case and its depth assessment, but withheld it from homepage highlights.", "source": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Clinicians interpreted the wearable’s recordings. The report does not establish that AI contributed to the patient’s care.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology; primary care)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "versions_and_access": [ { "source_url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "status": "Publisher-hosted four-page PDF read in full, including both tables and references." }, { "source_url": "https://acofp.org/news-and-publications/journal/article-detail/vol.-18-no.-3-(2026)--summer-2026/consumer-wearable-device-leads-to-expedited-diagnosis-andtreatment-of-paroxysmal-atrial-fibrillation", "status": "Article landing page gives the abstract and a membership notice. The linked publisher PDF was accessible." }, { "source_url": "https://acofp.org/news-and-publications/journal?publicationId=178&submissionId=286", "finding": "The publisher's issue listing explicitly gives July 24, 2026 as this case report's publication date." } ], "limitations": [ "The wearable brand, model, classification output and event date are unspecified.", "The report documents clinician interpretation, not a demonstrated AI contribution.", "The case has no controlled comparison and does not quantify the time or cost that was saved." ] } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The clinical report describes physicians interpreting wearable recordings. It does not identify the device, report an algorithm’s classification, or quantify the time and cost saved.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Elliott JS, Hagen AH (2026). Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation. Osteopathic Family Physician 18(3):56-59. doi:10.33181/18308. Case presentation, p. 57; discussion and limitations, pp. 58–59.", "title": "Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation", "url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "date": "2026-07-24", "written_by": "independent" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0292-source-0001" ], "role": "Retained evidence sources in reviewed order" }, "provenance": { "kind": "curatorial", "basis": "Updated identifiers after consolidating duplicate excerpts and reviewing original sources.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "case report", "citation": "Elliott JS, Hagen AH (2026). Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation. Osteopathic Family Physician 18(3):56-59. doi:10.33181/18308. Case presentation, p. 57; discussion and limitations, pp. 58–59.", "title": "Consumer Wearable Device Leads to Expedited Diagnosis and Treatment of Paroxysmal Atrial Fibrillation", "url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "date": "2026-07-24", "written_by": "independent" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated only the mapped fields affected by this source review. Other mapped content and review decisions are preserved.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "lead_source_ref": "AIBD-0292-source-0001", "retained_source_order": [ "AIBD-0292-source-0001" ], "origins": [ { "url": "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "contribution": "Original clinical account documents rhythm capture, expedited referral, ablation, recurrence and later symptom resolution.", "locator": "Printed p. 57, Case Presentation; pp. 58–59, Discussion, Tables 1–2 and references.", "relationship": "Clinical authors report their own case, independently of any named manufacturer. No AI classifier is identified.", "source_refs": [ "AIBD-0292-source-0001" ] } ], "claim_chains": [ { "claim": "Clinical benefit", "path": [ "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "Case Presentation, p. 57" ], "finding": "A cardiologist friend interpreted the recordings. The evidence supports wearable-assisted documentation and expedited care." }, { "claim": "AI contribution", "path": [ "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "Discussion and references 10–14" ], "finding": "General Apple/Fitbit studies and a review concern other devices and populations. They do not establish which device or algorithm, if any, contributed to this patient's care." }, { "claim": "Money or resource savings", "path": [ "https://www.acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf", "Table 2, p. 59; reference 14" ], "finding": "Table 2 contains general device-price comparisons, not measured expenditures or savings for this patient. Those figures are not imported as case benefits." } ], "limitations": [ "The wearable brand, model, classification output and event date are unspecified.", "The report documents clinician interpretation, not a demonstrated AI contribution.", "The case has no controlled comparison and does not quantify the time or cost that was saved." ], "excluded_or_consolidated_sources": [ { "url": "https://acofp.org/news-and-publications/journal/article-detail/vol.-18-no.-3-(2026)--summer-2026/consumer-wearable-device-leads-to-expedited-diagnosis-andtreatment-of-paroxysmal-atrial-fibrillation", "reason": "Another excerpt or format of the same Elliott and Hagen clinical report." }, { "url": "https://acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf?sfvrsn=913e1e01_1", "reason": "Another excerpt or format of the same Elliott and Hagen clinical report." }, { "url": "https://acofp.org/docs/default-source/ofp/vol-18-no-3-summer-2026/11_consumer-wearable-device-leads-to-expedited-diagnosis-and-treatment-of-paroxysmal-atrial-fibrillation.pdf?sfvrsn=913e1e01_1", "reason": "Another excerpt or format of the same Elliott and Hagen clinical report." } ], "review_scope": "Traced the claims in this case through accessible original publications and relevant embedded references, tables, appendices, corrections, and supplements. The stated access limits remain unresolved." } }, "provenance": { "kind": "source_review", "basis": "Read the available originals and relevant source chains, with unresolved access and evidentiary limits recorded explicitly.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0292-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The treating authors describe the wearable recordings, referral, ablation, recurrence, and later symptom resolution. Their clinical account is independent of any named manufacturer, but it does not establish an AI contribution.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Virginia family physicians report that AF episodes a 59-year-old recorded on a consumer wearable, confirmed by a cardiologist, expedited referral and ablation; AF-free off drugs at follow-up.", "account": "Joy S. Elliott of Riverside Family Medicine Medical Center, Newport News, Virginia, and Andrew H. Hagen of Edward Via College of Osteopathic Medicine, Blacksburg, Virginia, reported a case. It appeared in Osteopathic Family Physician (volume 18, number 3, Summer 2026, pages 56–59), published 24 July 2026. The event dates are not given. The patient is a 59-year-old man with two years of weekly episodes of fast heart rate, palpitations and fatigue, lasting up to 24 hours. He had documented several episodes through his smartphone using a consumer wearable device. A cardiologist friend had judged them paroxysmal atrial fibrillation (AF), but he had not sought formal evaluation. At the family medicine clinic his examination and bloods were normal. Initial management used the wearable for ambulatory rhythm monitoring to separate AF from premature beats. A confirmed episode lasting several hours prompted laboratory work-up and cardiology referral. Echocardiography showed a 4.1 cm aortic root and ascending aorta with normal ventricular function. Thirty-day monitoring was recommended. Because the wearable's rhythm strips already documented paroxysmal AF, his care went straight to treatment options. He chose pulmonary vein isolation ablation and reported dramatic improvement. He had one recurrence while skiing that responded to flecainide. At follow-up he was asymptomatic and AF-free without antiarrhythmic drugs, declining anticoagulation at a CHA2DS2-VASc score of 1. The device's brand is not named. The PDF was downloadable from the ACOFP site, although the article page says membership is required." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Consumer wearable device with smartphone-linked rhythm-strip recording (brand and model not stated)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Not stated (the report does not name the device's maker)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Consumer wearable rhythm strips let a 59-year-old man skip repeat 30-day monitoring and go straight to pulmonary vein isolation for paroxysmal atrial fibrillation", "headline": "Wearable rhythm strips let a 59-year-old go straight to ablation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "f89aa5f70b0c588b2cc259050fae432822cc1fdf3cbf60d8a0c25eaae1079a51" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Updated the fingerprint after this targeted source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Joy S. Elliott of Riverside Family Medicine Medical Center, Newport News, Virginia, and Andrew H. Hagen of Edward Via College of Osteopathic Medicine, Blacksburg, Virginia, reported a case. It appeared in Osteopathic Family Physician (volume 18, number 3, Summer 2026, pages 56–59), published 24 July 2026. The event dates are not given. The patient is a 59-year-old man with two years of weekly episodes of fast heart rate, palpitations and fatigue, lasting up to 24 hours. He had documented several episodes through his smartphone using a consumer wearable device. A cardiologist friend had judged them paroxysmal atrial fibrillation (AF), but he had not sought formal evaluation. At the family medicine clinic his examination and bloods were normal. Initial management used the wearable for ambulatory rhythm monitoring to separate AF from premature beats. A confirmed episode lasting several hours prompted laboratory work-up and cardiology referral. Echocardiography showed a 4.1 cm aortic root and ascending aorta with normal ventricular function. Thirty-day monitoring was recommended. Because the wearable's rhythm strips already documented paroxysmal AF, his care went straight to treatment options. He chose pulmonary vein isolation ablation and reported dramatic improvement. He had one recurrence while skiing that responded to flecainide. At follow-up he was asymptomatic and AF-free without antiarrhythmic drugs, declining anticoagulation at a CHA2DS2-VASc score of 1. The device's brand is not named. The PDF was downloadable from the ACOFP site, although the article page says membership is required.", "replication": { "produced_by": [ "A wearer who records rhythm strips on a consumer wearable during symptomatic episodes over an extended period", "A clinician (here a cardiologist friend, then the clinic) willing to accept those strips as documentation of paroxysmal AF", "A referral pathway that treats the documentation as sufficient to proceed to ablation without repeat 30-day monitoring" ], "must_hold": [ "The episodes are frequent and long enough to be captured on a user-triggered device", "The wearer has the device, the smartphone and the skills to record and share the strips (the authors list these as barriers for other patients)" ], "echoes": [ { "setting": "Apple Heart Study and Fitbit Heart Study, cited in the report's introduction: 34% of Apple irregular-pulse notifications and about one-third of Fitbit irregular-rhythm detections were confirmed as AF on ECG patch", "outcome": "recurred", "source": "Elliott JS, Hagen AH (2026), Osteopathic Family Physician 18(3):56-59, introduction, citing Perez et al. 2019 and Lubitz et al. 2022" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 10, "record_mapped": 21, "not_assessed": 60, "complete": false, "by_state": { "value_present": 31, "not_reported": 0, "unresolved": 0, "not_assessed": 60, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0376", "title": "West Yorkshire Police's first live facial recognition deployment in Huddersfield: three arrests, including a domestic stalking suspect, and six Sexual Harm Prevention Order checks over three days", "summary": "West Yorkshire Police reported three arrests and six Sexual Harm Prevention Order checks in Huddersfield on August 12–14, 2026. Its register records nine alerts and an estimated 12,875 faces seen.", "date_observed": "2026-08-17", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "West Yorkshire Police used live facial recognition in Huddersfield on August 12–14, 2026. The force reported three arrests, involving a domestic stalking suspect, a person wanted on a warrant, and a shoplifting suspect, along with six Sexual Harm Prevention Order checks. Its deployment register records five alerts on August 12 and two on each subsequent day. All nine were recorded as confirmed true alerts. The estimated numbers of faces seen were 5,824, 2,951, and 4,100, totaling 12,875. These are the force’s operational records, not an independent accuracy study. Zero recorded false alerts does not establish that there were no missed matches. The force identifies NEC NeoFace as the matching system and states that trained officers review alerts before intervention. The reported arrests and checks do not establish a conviction or a specific harm that was prevented.", "category": "benefit created", "unexpected": false, "purpose": "LFR vans are deployed to match passers-by against a watchlist of wanted people and suspects so that officers can arrest or check them. The arrests and order checks are that purpose. The Examiner adds that the cameras also serve to find missing people, witnesses and victims.", "system": "NEC NeoFace live facial recognition used in West Yorkshire Police camera vans", "model_version": null, "developer": "NEC (NeoFace)", "deployer": "West Yorkshire Police (Kirklees district)", "location": "Huddersfield, United Kingdom", "domain": "Policing / wanted-person identification", "segment": "Live facial recognition in a town center", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-08-17-4e1c" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "The force’s own release and deployment register report three arrests and six other interventions over three days. They establish a reported operational result, without independent verification of accuracy or later case outcomes." }, { "group": "societal", "depth": 1, "reason": "The force reported detention of three suspects and six checks of order subjects. No specific prevented harm or subsequent conviction is established." } ], "ai_role": { "status": "assessed", "statement": "NEC NeoFace compares camera images with a police watchlist and generates possible matches. Trained officers review the alerts and decide whether to act. The nine recorded alerts and resulting interventions are reported by the deployer; no independent evaluation of these deployments was found." }, "evidence": [ { "kind": "press release", "citation": "West Yorkshire Police. Cutting Edge Facial Recognition Cameras Used for First Time in Kirklees. 2026-08-17.", "title": "Cutting Edge Facial Recognition Cameras Used for First Time in Kirklees", "url": "https://www.westyorkshire.police.uk/news-appeals/cutting-edge-facial-recognition-cameras-used-first-time-kirklees", "date": "2026-08-17", "written_by": "deployer", "quote": null }, { "kind": "dataset", "citation": "West Yorkshire Police. Live facial recognition deployment register 2026. n.d. Version identified by filename 19102026. Huddersfield rows dated August 12–14, 2026.", "title": "Live facial recognition deployment register 2026", "url": "https://www.westyorkshire.police.uk/sites/default/files/2026-10/live-facial-recognition-deployment-register-2026-19102026.docx", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "West Yorkshire Police. Live Facial Recognition. n.d. Operational description, NEC NeoFace identification, human review, and data retention.", "title": "Live Facial Recognition", "url": "https://www.westyorkshire.police.uk/about-us/how-we-work/facial-recognition/live-facial-recognition", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Two vans on the first deployment day and one on each subsequent day, with trained officers available to review alerts", "A watchlist of wanted people, suspects and order subjects built from intelligence", "Officers on hand to review alerts and act on them" ], "must_hold": [ "Watchlist entries are current and lawful", "Officers verify each alert before a stop", "Non-matching faces are deleted as the force states" ], "echoes": [] }, "paired_incident": null, "headline": "Huddersfield's first facial recognition vans: three arrests, six checks", "metric": "three arrests and six Sexual Harm Prevention Order stops", "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": "United Kingdom", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-08-17-4e1c", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/West_Yorkshire_Police", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced repeated news coverage with police originals and added the deployment register’s counts and limits.", "source": "https://www.westyorkshire.police.uk/news-appeals/cutting-edge-facial-recognition-cameras-used-first-time-kirklees", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report, the deployer's dataset and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0376", "catalog_version": "1.0.0", "source_fingerprint": "231a8badedc852ef4b62e408af0651fbd1eb5d885134590727f4cc90b476b0c1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "NEC (NeoFace)", "deployer": "West Yorkshire Police (Kirklees district)" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "deployer", "developer" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "NEC NeoFace compares camera images with a police watchlist and generates possible matches. Trained officers review the alerts and decide whether to act. The nine recorded alerts and resulting interventions are reported by the deployer; no independent evaluation of these deployments was found." } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "benefit created", "ai_role": { "status": "assessed", "statement": "NEC NeoFace compares camera images with a police watchlist and generates possible matches. Trained officers review the alerts and decide whether to act. The nine recorded alerts and resulting interventions are reported by the deployer; no independent evaluation of these deployments was found." } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The force’s own release and deployment register report three arrests and six other interventions over three days. They establish a reported operational result, without independent verification of accuracy or later case outcomes." }, { "group": "societal", "depth": 1, "reason": "The force reported detention of three suspects and six checks of order subjects. No specific prevented harm or subsequent conviction is established." } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report, the deployer's dataset and the deployer's press release. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The force’s own release and deployment register report three arrests and six other interventions over three days. They establish a reported operational result, without independent verification of accuracy or later case outcomes." }, { "group": "societal", "depth": 1, "reason": "The force reported detention of three suspects and six checks of order subjects. No specific prevented harm or subsequent conviction is established." } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "The force’s own release and deployment register report three arrests and six other interventions over three days. They establish a reported operational result, without independent verification of accuracy or later case outcomes." }, { "group": "societal", "depth": 1, "reason": "The force reported detention of three suspects and six checks of order subjects. No specific prevented harm or subsequent conviction is established." } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": 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Operational description, NEC NeoFace identification, human review, and data retention.", "title": "Live Facial Recognition", "url": "https://www.westyorkshire.police.uk/about-us/how-we-work/facial-recognition/live-facial-recognition", "written_by": "deployer" } ] } }, "provenance": { "kind": "source_review", "basis": "Replaced repeated news coverage with police originals and added the deployment register’s counts and limits.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0376-source-0001" ], "url": "https://www.westyorkshire.police.uk/news-appeals/cutting-edge-facial-recognition-cameras-used-first-time-kirklees", "title": "Cutting Edge Facial Recognition Cameras Used for First Time in Kirklees", "published_on": "2026-08-17", "relationship": "deployer", "citation": "West Yorkshire Police. Cutting Edge Facial Recognition Cameras Used for First Time in Kirklees. 2026-08-17." }, { "source_refs": [ "AIBD-0376-source-0002" ], "url": "https://www.westyorkshire.police.uk/sites/default/files/2026-10/live-facial-recognition-deployment-register-2026-19102026.docx", "title": "Live facial recognition deployment register 2026", "relationship": "deployer", "citation": "West Yorkshire Police. Live facial recognition deployment register 2026. n.d. Version identified by filename 19102026. Huddersfield rows dated August 12–14, 2026." }, { "source_refs": [ "AIBD-0376-source-0003" ], "url": "https://www.westyorkshire.police.uk/about-us/how-we-work/facial-recognition/live-facial-recognition", "title": "Live Facial Recognition", "relationship": "deployer", "citation": "West Yorkshire Police. Live Facial Recognition. n.d. Operational description, NEC NeoFace identification, human review, and data retention." } ], "excluded_republications": [ { "url": "https://www.examinerlive.co.uk/news/local-news/nine-including-stalker-wanted-shoplifter-34472938", "title": "Nine including stalker and wanted shoplifter caught out in Huddersfield with live facial recognition cameras", "published_on": "2026-08-17", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0376-source-0001" }, { "url": "https://www.bbc.co.uk/news/articles/c70gl5rp19yo", "title": "Arrests after facial recognition tool used in Huddersfield", "published_on": "2026-08-17", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0376-source-0002" }, { "url": "https://www.examinerlive.co.uk/news/local-news/nine-including-stalker-wanted-shoplifter-34472938", "title": "Nine including stalker and wanted shoplifter caught out in Huddersfield with live facial recognition cameras", "published_on": "2026-08-17", "relationship": "Repeated quotation or alternate version of a retained original work", "previous_source_ref": "AIBD-0376-source-0003" }, { "url": "https://oecd.ai/en/incidents/2026-08-17-4e1c", "title": "Live Facial Recognition Leads to Multiple Arrests in Huddersfield", "published_on": "2026-08-17", "relationship": "Retained as source history; replaced by the original evidence or omitted because no distinct evidence is used for the revised claims", "previous_source_ref": "AIBD-0376-source-0004" } ], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0376-source-0001", "retained_source_order": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "ordering_basis": "The source that directly supports the central case leads. Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Arrests and order checks", "source_chain": [ { "url": "https://www.westyorkshire.police.uk/news-appeals/cutting-edge-facial-recognition-cameras-used-first-time-kirklees", "locator": "August 12–14 operation and intervention descriptions", "role": "Original police announcement", "access_status": "Full relevant text reviewed", "published_on": "2026-08-17" } ], "limitations": [ "All outcome claims originate with the deployer; arrests are not convictions" ], "source_ref": "AIBD-0376-source-0001" }, { "claim": "Nine alerts, three arrests, six other interventions, and estimated 12,875 faces", "source_chain": [ { "url": "https://www.westyorkshire.police.uk/sites/default/files/2026-10/live-facial-recognition-deployment-register-2026-19102026.docx", "locator": "Table rows 12/08/2026, 13/08/2026, and 14/08/2026; columns for confirmed alerts, arrests, other interventions, and estimated faces", "role": "Original operational register; DOCX table reviewed", "access_status": "Full relevant text reviewed" } ], "limitations": [ "Sums: alerts 5+2+2, faces 5824+2951+4100", "All nine alerts are recorded as true confirmed; the register does not measure missed matches", "Filename indicates the October 19 version, not a verified publication date" ], "source_ref": "AIBD-0376-source-0002" }, { "claim": "System identity and review procedure", "source_chain": [ { "url": "https://www.westyorkshire.police.uk/about-us/how-we-work/facial-recognition/live-facial-recognition", "locator": "NEC NeoFace, trained-officer review, and retention sections", "role": "Original deployment-policy account", "access_status": "Full relevant text reviewed" } ], "limitations": [ "A police policy description is not independent assurance that every deployment complied" ], "source_ref": "AIBD-0376-source-0003" } ], "limitations": [ "No independent evaluation of the three deployments; BBC full text could not be re-opened and is not used for retained claims" ] } }, "provenance": { "kind": "source_review", "basis": "Replaced repeated news coverage with police originals and added the deployment register’s counts and limits.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The retained accounts describe three deployments without an independent evaluation. The BBC article’s full text was inaccessible.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "West Yorkshire Police reported three arrests and six Sexual Harm Prevention Order checks in Huddersfield on August 12–14, 2026. Its register records nine alerts and an estimated 12,875 faces seen.", "account": "West Yorkshire Police used live facial recognition in Huddersfield on August 12–14, 2026. The force reported three arrests, involving a domestic stalking suspect, a person wanted on a warrant, and a shoplifting suspect, along with six Sexual Harm Prevention Order checks. Its deployment register records five alerts on August 12 and two on each subsequent day. All nine were recorded as confirmed true alerts. The estimated numbers of faces seen were 5,824, 2,951, and 4,100, totaling 12,875. These are the force’s operational records, not an independent accuracy study. Zero recorded false alerts does not establish that there were no missed matches. The force identifies NEC NeoFace as the matching system and states that trained officers review alerts before intervention. The reported arrests and checks do not establish a conviction or a specific harm that was prevented." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. 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The reported arrests and checks do not establish a conviction or a specific harm that was prevented.", "replication": { "produced_by": [ "Two vans on the first deployment day and one on each subsequent day, with trained officers available to review alerts", "A watchlist of wanted people, suspects and order subjects built from intelligence", "Officers on hand to review alerts and act on them" ], "must_hold": [ "Watchlist entries are current and lawful", "Officers verify each alert before a stop", "Non-matching faces are deleted as the force states" ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0376-source-0001", "AIBD-0376-source-0002", "AIBD-0376-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 4, "record_mapped": 25, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0345", "title": "UNEP records eight methane mitigations in Turkmenistan after MARS notifications", "summary": "UNEP lists eight mitigation cases, with site identifiers and dates from November 2024 to March 2026. The contribution of AI is described at system level, rather than isolated for each repair.", "date_observed": "2026-08-31", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "UNEP’s MARS mitigation index lists eight Turkmenistan cases: two in Yelguyi in November 2024, Babarap in June 2025, Gugurtli field in July 2025, Balguyy in August 2025, two in Dauletabad in February 2026, and Lebap Province in March 2026. Each entry has a source identifier and a link to an individual case document. UNEP describes these as mitigations that its notification and monitoring system helped prompt and verify. UNEP states that MARS combines satellite observations, scientific review, and AI to identify emissions for government and company action. The available aggregate evidence does not isolate AI’s contribution from analysts, notifications, and physical repairs or quantify their combined benefit.", "category": "general benefit", "unexpected": false, "purpose": "Satellite-based detection and notification of large methane plumes so that governments and operators mitigate them. The reported repairs are that purpose.", "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation", "model_version": null, "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); Government of Turkmenistan and its oil and gas operators (repairs; entities not named in cited sources)", "location": "Turkmenistan: Yelguyi, Babarap, Gugurtli field, Balguyy, Dauletabad, and Lebap Province", "domain": "Climate change mitigation / methane emissions monitoring", "segment": "Oil and gas sector; intergovernmental observatory", "benefit_type": "Reduced Carbon Emissions", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual benefit is established." }, { "group": "organizational", "depth": null, "reason": "UNEP identifies the mitigation sites, but the contribution to a named operator’s capability or finances has not been assessed." }, { "group": "societal", "depth": null, "reason": "UNEP reports eight mitigations. This record does not establish their combined avoided emissions or assess the depth of the societal benefit." } ], "ai_role": { "status": "assessed", "statement": "UNEP identifies AI as part of the satellite-analysis system that generates notifications and supports subsequent monitoring. Its public index names eight Turkmenistan mitigation cases. It does not isolate the AI contribution to each repair." }, "evidence": [ { "kind": "report", "citation": "UNEP International Methane Emissions Observatory. MARS Mitigation Cases. n.d. Central Asia section lists eight Turkmenistan mitigation cases dated November 2024–March 2026, with individual case links.", "title": "MARS Mitigation Cases", "url": "https://www.unep.org/en/what-we-do/energy/methane/mars-case-studies", "date": null, "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Damian Carrington, The Guardian. ‘Breakthrough’ as Turkmenistan starts fixing ‘mindboggling’ methane mega-leaks. 2026-08-31. Original interviews and contemporaneous alert-response totals.", "title": "‘Breakthrough’ as Turkmenistan starts fixing ‘mindboggling’ methane mega-leaks", "url": "https://www.theguardian.com/environment/2026/aug/31/turkmenistan-methane-leaks-un-alerts-mars", "date": "2026-08-31", "written_by": "independent", "quote": null }, { "kind": "report", "citation": "UNEP International Methane Emissions Observatory. Methane Alert and Response System (MARS). n.d. Original description of satellite analysis, AI, and notifications.", "title": "Methane Alert and Response System (MARS)", "url": "https://www.unep.org/en/what-we-do/energy/methane/methane-alert-and-response-system-mars", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Satellite detection and analysis, notification to government or operators, and physical mitigation that UNEP reports as verified" ], "must_hold": [ "Operators can identify and address the notified emissions source", "Continued monitoring distinguishes durable mitigation from temporary non-detection", "Site-level evidence is needed to establish each repair and its effects" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: a single documented MARS-enabled pipeline mitigation in a neighboring country (UNEP case document)", "model_version": null, "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" } ] }, "paired_incident": null, "headline": "UNEP records eight methane mitigations in Turkmenistan", "metric": "eight listed mitigation cases; 192 alerts and about 20% answered in the August 2026 report", "comparator": null, "later": { "status": "unknown", "date": null, "note": "The UNEP index names and dates eight mitigation cases. Their continued performance is not established by the aggregate account.", "quote": null, "url": "https://www.unep.org/en/what-we-do/energy/methane/mars-case-studies" }, "value": null, "developer_country": "France", "deployer_country": "France", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Carbon Emissions under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory; https://en.wikipedia.org/wiki/International_Methane_Emissions_Observatory", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to UNEP International Methane Emissions Observatory.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced derivative summaries with UNEP’s original case index and the original Guardian reporting. Corrected the assertion that site-level documents do not exist.", "source": "https://www.unep.org/en/what-we-do/energy/methane/mars-case-studies", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, the makers' report and the deployer's report. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0345", "catalog_version": "1.0.0", "source_fingerprint": "99d559a555e9dd72aff880cf95666fa1cd18d56f5ab7dc5148de450fe943f190", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "viator", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0345-source-0001", "AIBD-0345-source-0002", "AIBD-0345-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "UNEP International Methane Emissions Observatory (IMEO)", "deployer": "UNEP International Methane Emissions Observatory (notification); Government of Turkmenistan and its oil and gas operators (repairs; entities not named in cited sources)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "UNEP identifies AI as part of the satellite-analysis system that generates notifications and supports subsequent monitoring. 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This record does not establish their combined avoided emissions or assess the depth of the societal benefit." } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. 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Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Eight named mitigation cases and dates", "source_chain": [ { "url": "https://www.unep.org/en/what-we-do/energy/methane/mars-case-studies", "locator": "Central Asia, Turkmenistan entries TKM_S_406, 451, 452, 118, 053, 071, 080, and 081", "role": "Original UNEP mitigation index", "access_status": "Full relevant text reviewed" }, { "url": "https://wedocs.unep.org/items/5c86c2bd-db0e-49ab-98ed-f9d4730b1af4", "locator": "TKM_S_406, Lebap Province, March 2026", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/ab7219e7-8192-4ad3-91f5-1c93b440ec48", "locator": "TKM_S_451, Dauletabad, February 2026", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/24553364-60bb-4cd9-841f-3e8ca35dfc3a", "locator": "TKM_S_452, Dauletabad, February 2026", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/fa3e52ea-97bd-4009-b5f2-7dafb2a5a4e9", "locator": "TKM_S_118, Balguyy, August 2025", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/1bc9fee8-eb37-4f2a-b690-0f7ee470c8c5", "locator": "TKM_S_053, Gugurtli field, July 2025", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/490eba84-19e5-41eb-93fe-e885f74cb68e", "locator": "TKM_S_071, Babarap, June 2025", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/12065ac0-2bee-4097-a140-7c94924603af", "locator": "TKM_S_080, Yelguyi, November 2024", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" }, { "url": "https://wedocs.unep.org/items/ba302a6c-8b00-404e-9e5a-ec6912f65250", "locator": "TKM_S_081, Yelguyi, November 2024", "role": "Linked original mitigation case document", "access_status": "Link identified in original index; document request timed out or failed" } ], "limitations": [ "The index supports named cases and dates; underlying sheets were inaccessible, so repair procedures and emissions quantities were not independently checked" ], "source_ref": "AIBD-0345-source-0001" }, { "claim": "192 alerts and roughly 20% response rate", "source_chain": [ { "url": "https://www.theguardian.com/environment/2026/aug/31/turkmenistan-methane-leaks-un-alerts-mars", "locator": "Contemporaneous MARS totals and direct interview", "role": "Original reporting", "access_status": "Full relevant text reviewed", "published_on": "2026-08-31" }, { "url": "https://methanedata.unep.org/", "locator": "August 2026 MARS snapshot underlying the reported totals", "role": "UNEP original data platform", "access_status": "Exact archived August snapshot not retrieved" } ], "limitations": [ "Historical totals could not be recomputed from the underlying snapshot" ], "source_ref": "AIBD-0345-source-0002" }, { "claim": "AI contribution to MARS", "source_chain": [ { "url": "https://www.unep.org/en/what-we-do/energy/methane/methane-alert-and-response-system-mars", "locator": "What is MARS?", "role": "Original system description", "access_status": "Full relevant text reviewed" } ], "limitations": [ "System-level AI contribution is not an isolated per-repair causal estimate" ], "source_ref": "AIBD-0345-source-0003" } ], "limitations": [ "Eight linked case sheets and the historical snapshot remain uninspected" ], "chronology_source": { "url": "https://www.theguardian.com/environment/2026/aug/31/turkmenistan-methane-leaks-un-alerts-mars", "locator": "Original aggregate report predating Eurasianet and The Chemical Engineer", "role": "First verified publication of the aggregate case", "access_status": "Full relevant text reviewed", "published_on": "2026-08-31", "date": "2026-08-31", "title": "‘Breakthrough’ as Turkmenistan starts fixing ‘mindboggling’ methane mega-leaks" } } }, "provenance": { "kind": "source_review", "basis": "Replaced derivative summaries with UNEP’s original case index and the original Guardian reporting. Corrected the assertion that site-level documents do not exist.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0345-source-0001", "AIBD-0345-source-0002", "AIBD-0345-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Eight linked case sheets and the historical website snapshot remain uninspected.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "UNEP lists eight mitigation cases, with site identifiers and dates from November 2024 to March 2026. The contribution of AI is described at system level, rather than isolated for each repair.", "account": "UNEP’s MARS mitigation index lists eight Turkmenistan cases: two in Yelguyi in November 2024, Babarap in June 2025, Gugurtli field in July 2025, Balguyy in August 2025, two in Dauletabad in February 2026, and Lebap Province in March 2026. Each entry has a source identifier and a link to an individual case document. UNEP describes these as mitigations that its notification and monitoring system helped prompt and verify. UNEP states that MARS combines satellite observations, scientific review, and AI to identify emissions for government and company action. The available aggregate evidence does not isolate AI’s contribution from analysts, notifications, and physical repairs or quantify their combined benefit." } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0345-source-0001", "AIBD-0345-source-0002", "AIBD-0345-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "UNEP IMEO Methane Alert and Response System (MARS): satellite plume detection and analysis with AI models, notification and satellite confirmation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "UNEP International Methane Emissions Observatory (IMEO)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "UNEP records eight methane mitigations in Turkmenistan after MARS notifications", "headline": "UNEP records eight methane mitigations in Turkmenistan" } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "title", "headline" ], "source_refs": [ "AIBD-0345-source-0001", "AIBD-0345-source-0002", "AIBD-0345-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "99d559a555e9dd72aff880cf95666fa1cd18d56f5ab7dc5148de450fe943f190" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "UNEP’s MARS mitigation index lists eight Turkmenistan cases: two in Yelguyi in November 2024, Babarap in June 2025, Gugurtli field in July 2025, Balguyy in August 2025, two in Dauletabad in February 2026, and Lebap Province in March 2026. Each entry has a source identifier and a link to an individual case document. UNEP describes these as mitigations that its notification and monitoring system helped prompt and verify. UNEP states that MARS combines satellite observations, scientific review, and AI to identify emissions for government and company action. The available aggregate evidence does not isolate AI’s contribution from analysts, notifications, and physical repairs or quantify their combined benefit.", "replication": { "produced_by": [ "Satellite detection and analysis, notification to government or operators, and physical mitigation that UNEP reports as verified" ], "must_hold": [ "Operators can identify and address the notified emissions source", "Continued monitoring distinguishes durable mitigation from temporary non-detection", "Site-level evidence is needed to establish each repair and its effects" ], "echoes": [ { "date": "2025-11-26", "setting": "Kazakhstan KAZ_S_136: a single documented MARS-enabled pipeline mitigation in a neighboring country (UNEP case document)", "outcome": "recurred", "source": "https://wedocs.unep.org/bitstreams/558dda69-c8e5-42c2-b10a-7b9c3dcc3e79/download" } ] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0345-source-0001", "AIBD-0345-source-0002", "AIBD-0345-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 4, "record_mapped": 25, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0575", "title": "Manchester People’s Panel shapes a proposed public-facing Caddy AI advice service", "summary": "Manchester residents proposed safeguards for a public-facing Caddy service. Wider access to understandable advice remains intended; the panel’s design recommendations are reported.", "date_observed": "2026-09-02", "date_basis": "source publication", "date_precision": "day", "benefit_status": "intended", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-015", "account": "In a September 2026 post, Citizens Advice SORT’s Stuart Pearson describes a January panel that considered three proposals for public-facing Caddy and proposed a fourth. Residents called for client choice, human escalation for red flags, and transparency. They also noted that members of the public would lack trained advisers’ prompting skills. A separate Open University interview describes an earlier presentation in July 2024. The council’s LGA account reports learning and confidence changes from its wider participation program, not improved outcomes from Caddy. None of these accounts establishes deployment of the proposed public service or a benefit to its clients.", "category": "general benefit", "unexpected": false, "purpose": "Extend access to understandable advice through a proposed public-facing AI service with human escalation and user choice.", "system": "Proposed public-facing Caddy AI advice service", "model_version": null, "developer": "Citizens Advice Stockport, Oldham, Rochdale and Trafford", "deployer": "Citizens Advice Stockport, Oldham, Rochdale and Trafford (proposed public-facing service)", "location": "Manchester, United Kingdom", "domain": "Public advice and community participation", "segment": null, "benefit_type": "Improved Accessibility", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Advice recipients are intended beneficiaries. The proposed design has no established client outcome." }, { "group": "organizational", "depth": null, "reason": "Citizens Advice received specific design input. Its contribution to service capability and performance remains unassessed." } ], "ai_role": { "status": "unassessed", "statement": "Caddy would support public-facing advice. The panel generated the design recommendations; the intended AI contribution to advice outcomes has not been evaluated." }, "evidence": [ { "kind": "other", "citation": "Stuart Pearson, Citizens Advice SORT, LinkedIn, September 2, 2026. First-person account of proposed service design and panel feedback.", "title": "Citizens Advice Should Be the Trusted AI Advice Service", "url": "https://www.linkedin.com/posts/stoopearson_designing-the-future-of-trusted-advice-recruiting-activity-7500816766869127168-sbBE", "date": "2026-09-02", "written_by": "deployer", "quote": null }, { "kind": "other", "citation": "Stuart Pearson interview in the Open University course Use cases for Generative AI, section People’s Panel for Artificial Intelligence. Describes Citizens Advice SORT’s July 2024 presentation to the council-funded panel. Publication date unspecified.", "title": "People’s Panel for Artificial Intelligence - Stuart Pearson interview", "url": "https://www.open.edu/openlearncreate/mod/oucontent/view.php?id=234605§ion=3.1.4", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Manchester City Council account published by the Local Government Association, January 28, 2025. Describes the council-funded People’s Panel and its educational survey results. The proposed Caddy service was not evaluated.", "title": "Manchester City Council: People’s Panel for AI: Building skills, confidence and residents’ voices", "url": "https://www.local.gov.uk/case-studies/manchester-city-council-peoples-panel-ai-building-skills-confidence-and-residents", "date": "2025-01-28", "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Residents supplied design recommendations for a proposed AI advice service. Improvements from the resulting service remain unverified." ], "must_hold": [ "Implementation and evaluation would be needed to determine whether the proposed service improves access. Conditions sufficient for a beneficial outcome remain unknown." ], "echoes": [] }, "paired_incident": null, "headline": "Manchester residents shape a proposed AI advice service", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.linkedin.com/posts/stoopearson_designing-the-future-of-trusted-advice-recruiting-activity-7500816766869127168-sbBE", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Retained three firsthand accounts with distinct contributions and separated the January design discussion from the July 2024 presentation.", "source": "https://www.linkedin.com/posts/stoopearson_designing-the-future-of-trusted-advice-recruiting-activity-7500816766869127168-sbBE", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report and two other sources from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0575", "catalog_version": "1.0.0", "source_fingerprint": "777f01cda89e5997d15f6164ad23db5e37873d188343a0110ad4b9ec6d2064d2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0575-source-0001", "AIBD-0575-source-0002", "AIBD-0575-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Citizens Advice Stockport, Oldham, Rochdale and Trafford", "deployer": "Citizens Advice Stockport, Oldham, Rochdale and Trafford (proposed public-facing service)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "Caddy would support public-facing advice. The panel generated the design recommendations; the intended AI contribution to advice outcomes has not been evaluated." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report and two other sources from the deployer. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Advice recipients are intended beneficiaries. The proposed design has no established client outcome." }, { "group": "organizational", "reason": "Citizens Advice received specific design input. Its contribution to service capability and performance remains unassessed." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Intended benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "Advice recipients are intended beneficiaries. 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Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Public-facing Caddy proposal and residents’ recommendations", "source_chain": [ { "url": "https://www.linkedin.com/posts/stoopearson_designing-the-future-of-trusted-advice-recruiting-activity-7500816766869127168-sbBE", "locator": "Post body describing January panel, three options, and fourth proposal", "role": "First-person account by Citizens Advice SORT’s Stuart Pearson", "access_status": "Full relevant text reviewed", "published_on": "2026-09-02" } ], "limitations": [ "Publication date is consistent with the LinkedIn activity timestamp; the exact January meeting date is not supplied", "Intended service benefits are not evaluated" ], "source_ref": "AIBD-0575-source-0001" }, { "claim": "Earlier panel participation", "source_chain": [ { "url": "https://www.open.edu/openlearncreate/mod/oucontent/view.php?id=234605§ion=3.1.4", "locator": "Section 3.1.4, Stuart Pearson video transcript", "role": "Original interview; transcript reviewed", "access_status": "Full relevant text reviewed" } ], "limitations": [ "July 2024 presentation is an earlier event, not necessarily the January meeting in the later post" ], "source_ref": "AIBD-0575-source-0002" }, { "claim": "Wider participation-program context", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/manchester-city-council-peoples-panel-ai-building-skills-confidence-and-residents", "locator": "Approach and impact sections", "role": "Original Manchester City Council account", "access_status": "Full relevant text reviewed", "published_on": "2025-01-28" } ], "limitations": [ "Council survey gains concern education and participation; they do not measure Caddy’s service benefit" ], "source_ref": "AIBD-0575-source-0003" } ], "limitations": [] } }, "provenance": { "kind": "source_review", "basis": "Retained three firsthand accounts with distinct contributions and separated the January design discussion from the July 2024 presentation.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0575-source-0001", "AIBD-0575-source-0002", "AIBD-0575-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Manchester residents proposed safeguards for a public-facing Caddy service. 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Residents called for client choice, human escalation for red flags, and transparency. They also noted that members of the public would lack trained advisers’ prompting skills. A separate Open University interview describes an earlier presentation in July 2024. The council’s LGA account reports learning and confidence changes from its wider participation program, not improved outcomes from Caddy. None of these accounts establishes deployment of the proposed public service or a benefit to its clients.", "replication": { "produced_by": [ "Residents supplied design recommendations for a proposed AI advice service. Improvements from the resulting service remain unverified." ], "must_hold": [ "Implementation and evaluation would be needed to determine whether the proposed service improves access. Conditions sufficient for a beneficial outcome remain unknown." ], "echoes": [] } } }, "provenance": { "kind": "curatorial", "basis": "Updated affected case fields after the dated primary-source review. Unrelated requirement assessments retain their existing status.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0575-source-0001", "AIBD-0575-source-0002", "AIBD-0575-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 4, "record_mapped": 25, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0377", "title": "A Waymo robotaxi is pulled over in San Francisco's Richmond District after the company detects a firearm violation; police find a loaded AR-style “ghost gun” and book two juveniles", "summary": "LA Times (12 September 2026): before 4 a.m. on 3 Sep Waymo pulled a robotaxi over in the Richmond District after detecting a firearm violation; SFPD found a loaded ghost gun and booked two minors.", "date_observed": "2026-09-03", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Shortly before 4 a.m. on Thursday 3 September 2026, Waymo pulled one of its driverless cars over in San Francisco's Richmond District. It had detected “a violation of our terms of service involving a firearm”. Waymo alerted emergency services and “cooperated fully” with police, a Waymo spokesperson told the Los Angeles Times (12 September). The San Francisco Police Department said officers made a “high-risk vehicle stop” and detained the two juvenile passengers. They found a loaded AR-style assault rifle, suspected marijuana and mace spray, and the two were taken to juvenile hall. The Independent, citing SFGATE, quotes SFPD spokesperson Allison Maxie calling the weapon an “AR-styled assault rifle also known as a ghost gun”. It says the boy and girl were booked into the Juvenile Justice Center on firearm-possession charges. The California Post puts the stop at 40th Avenue and Cabrillo Street. No source says how the firearm was detected; The Independent and Xataka both say this is unclear.", "category": "protective response", "unexpected": false, "purpose": "The Waymo Driver is built to provide driverless rides. The service's rider rules prohibit weapons, and Xataka says interior cameras record rides so that the company can check compliance and respond to emergencies. Pulling over and calling police on a firearm violation is that safeguard working, not a driving function.", "system": "Waymo driverless ride-hail vehicle (Waymo Driver) with the company's in-ride monitoring and terms-of-service enforcement", "model_version": null, "developer": "Waymo LLC", "deployer": "Waymo LLC", "location": "San Francisco, United States", "domain": "Mobility / rider safety", "segment": "Robotaxi in-ride monitoring", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-09-10-4b01" }, "ratings": [ { "group": "organizational", "depth": 2, "reason": "SFPD took a loaded AR-style ghost gun, suspected marijuana and mace from two juveniles. It booked both on firearm-possession charges after the company's alert, per the Los Angeles Times and The Independent." }, { "group": "societal", "depth": 1, "reason": "A loaded unserialized rifle was taken out of circulation, and two minors were charged. No report shows a harm that was about to occur, so the public benefit is the seizure itself." } ], "ai_role": { "status": "assessed", "statement": "What the system did is established only at the level of the company. Waymo says it detected a terms-of-service violation involving a firearm, pulled the driverless car over and alerted emergency services. The Independent says it is not clear how the firearm was detected. Xataka says Waymo has not explained whether detection was automatic or human. The Monitor's statement that the vehicle's AI detected the gun is not supported by any cited source. The driverless car's ability to stop on command is the only system function the accounts describe." }, "evidence": [ { "kind": "news report", "citation": "Kwok I (2026). Waymo pulls over, calls police on juvenile riders who had 'ghost gun,' authorities say. Los Angeles Times, 12 September 2026, syndicated by The Spokesman-Review.", "title": "Waymo pulls over, calls police on juvenile riders who had 'ghost gun,' authorities say", "url": "https://www.spokesman.com/stories/2026/sep/12/waymo-pulls-over-calls-police-on-juvenile-riders-w/", "date": "2026-09-12", "written_by": "independent", "quote": "The company pulled the car over after detecting a \"violation of our terms of service involving a firearm,\" the spokesperson said." }, { "kind": "news report", "citation": "The Independent (2026). Waymo pulls over robotaxi after detecting riders were carrying assault rifle. The Independent, 12 September 2026.", "title": "Waymo pulls over robotaxi after detecting riders were carrying assault rifle", "url": "https://www.independent.co.uk/news/world/americas/crime/waymo-assault-rifle-passengers-b3049133.html", "date": "2026-09-12", "written_by": "independent", "quote": "It's not clear exactly how the Waymo detected the firearm, especially one described as a \"ghost gun\" by the SFPD." }, { "kind": "news report", "citation": "Peña M (2026). Waymo calls cops on teen riders after detecting loaded AR-style 'ghost gun'. The California Post, via Yahoo News, 13 September 2026.", "title": "Waymo calls cops on teen riders after detecting loaded AR-style 'ghost gun'", "url": "https://www.yahoo.com/news/us/articles/waymo-calls-cops-teen-riders-001306046.html", "date": "2026-09-13", "written_by": "independent", "quote": "Both juveniles were arrested on charges related to illegal firearm possession. They were taken into custody and booked into San Francisco's Juvenile Justice Center." }, { "kind": "news report", "citation": "Marquez J (2026). Subirse armado a un robotaxi puede acabar mal: dos menores lo comprobaron cuando apareció la policía. Xataka, 14 September 2026.", "title": "Subirse armado a un robotaxi puede acabar mal: dos menores lo comprobaron cuando apareció la policía", "url": "https://www.xataka.com/movilidad/subirse-armado-a-robotaxi-puede-acabar-mal-dos-menores-comprobaron-cuando-aparecio-policia", "date": "2026-09-14", "written_by": "independent", "quote": "no sabemos si hubo detección automática, revisión humana o algún otro mecanismo que desencadenara la alerta" }, { "kind": "registry label", "citation": "OECD AI Incidents and Hazards Monitor (2026). Waymo Robotaxi AI Detects Firearm, Alerts Police Leading to Juvenile Arrests in San Francisco. OECD.AI, 10 September 2026.", "title": "Waymo Robotaxi AI Detects Firearm, Alerts Police Leading to Juvenile Arrests in San Francisco", "url": "https://oecd.ai/en/incidents/2026-09-10-4b01", "date": "2026-09-10", "written_by": "independent", "quote": "Waymo's autonomous vehicle AI detected a firearm violation involving two minors in San Francisco, pulled over, and alerted police." } ], "replication": { "produced_by": [ "Interior cameras recording the ride, which Waymo says it may review to check rule compliance and respond to emergencies (Xataka)", "A company process that pulls the car over and calls emergency services on a firearm violation", "Police able to reach the stopped car quickly before 4 a.m." ], "must_hold": [ "The weapon is visible or otherwise detectable inside the cabin", "Waymo staff or systems act on the detection in time", "Riders stay in the car until police arrive. The Independent notes the doors were not locked in the July San Mateo case" ], "echoes": [] }, "paired_incident": null, "headline": "Waymo pulls a car over; police find a loaded ghost gun with two minors", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-21", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-09-10-4b01", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Waymo; https://en.wikipedia.org/wiki/Waymo", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: four independent news reports and a registry entry. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0377", "catalog_version": "1.0.0", "source_fingerprint": "7f2a79c8b929f473a713655466f3ce80d16f4090bad88be71a75ef0b00da5a91", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0377-source-0001", "AIBD-0377-source-0002", "AIBD-0377-source-0003", "AIBD-0377-source-0004", "AIBD-0377-source-0005" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Waymo LLC", "deployer": "Waymo LLC" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "What the system did is established only at the level of the company. Waymo says it detected a terms-of-service violation involving a firearm, pulled the driverless car over and alerted emergency services. The Independent says it is not clear how the firearm was detected. Xataka says Waymo has not explained whether detection was automatic or human. The Monitor's statement that the vehicle's AI detected the gun is not supported by any cited source. The driverless car's ability to stop on command is the only system function the accounts describe." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "What the system did is established only at the level of the company. Waymo says it detected a terms-of-service violation involving a firearm, pulled the driverless car over and alerted emergency services. The Independent says it is not clear how the firearm was detected. Xataka says Waymo has not explained whether detection was automatic or human. The Monitor's statement that the vehicle's AI detected the gun is not supported by any cited source. The driverless car's ability to stop on command is the only system function the accounts describe." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "SFPD took a loaded AR-style ghost gun, suspected marijuana and mace from two juveniles. 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The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 2, "reason": "SFPD took a loaded AR-style ghost gun, suspected marijuana and mace from two juveniles. It booked both on firearm-possession charges after the company's alert, per the Los Angeles Times and The Independent." }, { "group": "societal", "depth": 1, "reason": "A loaded unserialized rifle was taken out of circulation, and two minors were charged. 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It had detected “a violation of our terms of service involving a firearm”. Waymo alerted emergency services and “cooperated fully” with police, a Waymo spokesperson told the Los Angeles Times (12 September). The San Francisco Police Department said officers made a “high-risk vehicle stop” and detained the two juvenile passengers. They found a loaded AR-style assault rifle, suspected marijuana and mace spray, and the two were taken to juvenile hall. The Independent, citing SFGATE, quotes SFPD spokesperson Allison Maxie calling the weapon an “AR-styled assault rifle also known as a ghost gun”. It says the boy and girl were booked into the Juvenile Justice Center on firearm-possession charges. The California Post puts the stop at 40th Avenue and Cabrillo Street. No source says how the firearm was detected; The Independent and Xataka both say this is unclear.", "replication": { "produced_by": [ "Interior cameras recording the ride, which Waymo says it may review to check rule compliance and respond to emergencies (Xataka)", "A company process that pulls the car over and calls emergency services on a firearm violation", "Police able to reach the stopped car quickly before 4 a.m." ], "must_hold": [ "The weapon is visible or otherwise detectable inside the cabin", "Waymo staff or systems act on the detection in time", "Riders stay in the car until police arrive. The Independent notes the doors were not locked in the July San Mateo case" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0556", "title": "North East Derbyshire District Council: using Copilot to support better decisions and organisational change", "summary": "North East Derbyshire uses Copilot for drafting, summaries, and analysis. 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Original council account.", "title": "North East Derbyshire District Council: using Copilot to support better decisions and organisational change", "url": "https://www.local.gov.uk/case-studies/north-east-derbyshire-district-council-using-copilot-support-better-decisions-and", "date": "2026-09-14", "written_by": "deployer" } ] } }, "provenance": { "kind": "source_review", "basis": "Confirmed that the LGA page is the council’s original account, not an independent evaluation.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0556-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0556-source-0001" ], "url": "https://www.local.gov.uk/case-studies/north-east-derbyshire-district-council-using-copilot-support-better-decisions-and", "title": "North East Derbyshire District Council: using Copilot to support better decisions and organisational change", "published_on": "2026-09-14", "relationship": "deployer", "citation": "North East Derbyshire District Council. “North East Derbyshire District Council: using Copilot to support better decisions and organisational change.” Local Government Association, September 14, 2026. Original council account." } ], "excluded_republications": [], "independent_evaluations_of_reported_results": 0, "lead_source_ref": "AIBD-0556-source-0001", "retained_source_order": [ "AIBD-0556-source-0001" ], "ordering_basis": "The source that directly supports the central case leads. Additional sources contribute the specific evidence or limitations described in claim_lineage.", "claim_lineage": [ { "claim": "Copilot trial, wider organizational program, and intended benefits", "source_chain": [ { "url": "https://www.local.gov.uk/case-studies/north-east-derbyshire-district-council-using-copilot-support-better-decisions-and", "locator": "Challenge, approach, outcomes, and lessons sections", "role": "Original council account published by LGA", "access_status": "Full relevant text reviewed", "published_on": "2026-09-14" } ], "limitations": [ "Copilot was introduced alongside governance, training, and data initiatives", "The account does not isolate AI’s effect or quantify realized time savings", "No linked outcome study or supplementary evaluation accompanies the case" ], "source_ref": "AIBD-0556-source-0001" } ], "limitations": [] } }, "provenance": { "kind": "source_review", "basis": "Confirmed that the LGA page is the council’s original account, not an independent evaluation.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0556-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "North East Derbyshire uses Copilot for drafting, summaries, and analysis. Reduced repetitive work remains intended; the source does not establish an AI-produced cultural benefit.", "account": "North East Derbyshire introduced Copilot alongside governance, data, and skills programs to improve decisions and service design. The council describes more evidence-seeking staff discussions and changes in decision practice. It does not isolate Copilot’s contribution from the wider program. Reductions in repetitive work and better resident outcomes remain expected." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Microsoft Copilot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Microsoft" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "North East Derbyshire District Council: using Copilot to support better decisions and organisational change", "headline": "North East Derbyshire explores Copilot for routine work" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "2e4445f7995e4d2063cd72965fd8432a191f114a2b7420c59053baae7b1f61d5" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version after the October 24, 2026 primary-source review.", "record_fields": [], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "North East Derbyshire introduced Copilot alongside governance, data, and skills programs to improve decisions and service design. The council describes more evidence-seeking staff discussions and changes in decision practice. It does not isolate Copilot’s contribution from the wider program. Reductions in repetitive work and better resident outcomes remain expected.", "replication": { "produced_by": [ "The council introduced Copilot and supported staff to explore drafting, summarization, and analysis.", "The wider adoption program included data preparation, governance, training, and human review of outputs." ], "must_hold": [ "The conditions needed to reproduce a benefit from AI are unknown." ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 29, "reviewed": 4, "record_mapped": 25, "not_assessed": 62, "complete": false, "by_state": { "value_present": 29, "not_reported": 0, "unresolved": 0, "not_assessed": 62, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0240", "title": "Anthropic's threat monitoring flags a Bonita Springs woman's messages about shooting up the Lee County Sheriff's Office; human reviewers tip police, who detain her without incident and find no gun", "summary": "Anthropic safeguards flagged a threat to shoot up a Florida sheriff's office; reviewers tipped police, who arrested the user; no gun found.", "date_observed": "2026-09-29", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A user of Anthropic's AI chat service wrote at about 05:10 on 26 September 2026. She said she was going to “shoot up” the Lee County Sheriff's Office in Florida. At 01:07 on 27 September she wrote that she had got a new gun. Anthropic's safety monitoring flagged the messages, and because of their severity a human review team reported them to law enforcement. The sheriff's office logged the tip on 29 September and identified the user as Carli Michelle Heller, 30, of Bonita Springs. Deputies detained her at home without incident at 00:51 on 30 September. A detective charged her under Florida Statute 836.10, written threats of violence. No weapon was seized, and she described the AI as a personal diary.", "category": "protective response", "unexpected": false, "purpose": "Anthropic's consumer terms (effective 8 October 2025) reserve the right “at our sole discretion” to report Inputs to law enforcement. Its privacy policy (effective 10 September 2026) allows disclosure the company believes “reasonably necessary” to “prevent serious harm to any person or to property”. The arrest report says the platform's safety measures are “designed to monitor for key phrases and potentially threatening content”. Flagging a stated shooting threat, reviewing it by hand and referring it to police was that purpose. Of an August 2026 referral Anthropic said “This is our safeguards process working as intended”.", "system": "Anthropic Claude consumer-chat safety monitoring: automated flagging of threatening content, escalation to a human review team, referral to law enforcement", "model_version": null, "developer": "Anthropic", "deployer": "Anthropic", "location": "Bonita Springs, United States", "domain": "Online safety and threat referral to law enforcement", "segment": "Media, social platforms, and marketing", "benefit_type": "Reduced Violence", "taxonomy_note": null, "registry_ids": { "oecd_aim": "2026-10-04-dced" }, "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Lee County Sheriff's Office, the threatened party, received a tip quoting a stated plan to shoot up its building and a claimed new gun. It identified the user and resolved the matter at her home within about three days without incident. No weapon was seized, so no averted attack is shown." }, { "group": "societal", "depth": 1, "reason": "A written threat of a mass shooting at a public building was examined within days rather than left unread. It was at least the third Anthropic referral to police since August 2026. The benefit is bounded by the absence of a weapon, the user's diary account, and expert doubt that the words were a true threat." } ], "ai_role": { "status": "assessed", "statement": "The arrest report says the platform “utilizes safety and security measures designed to monitor for key phrases and potentially threatening content”. It says the messages were “escalated to a human review team”. An automated layer therefore surfaced the two messages, and people judged their severity and made the referral. The sources do not say whether the flag came from a classifier or a keyword rule. Straight Arrow News, citing court records, says the review team escalated to the FBI, which notified the sheriff's office. Identifying the user, the home visit, the Miranda interview and the charging decision were the work of Lee County deputies and Intelligence Detective Thomas Alejo. The arrest report calls the platform “Anthropic Artificial Intelligence”. Press reports name Claude, and court records note the user told the detective she used Perplexity." }, "evidence": [ { "kind": "court document", "citation": "Lee County Sheriff's Office, Alejo, T. S. (2026). Arrest / Notice to Appear and Probable Cause Statement, agency report 26-530248, clerk case 26CF017549, Heller, Carli Michelle. Redacted copy hosted by the Daily Caller.", "title": "Arrest report and probable cause statement, LCSO report 26-530248 (Heller, Carli Michelle)", "url": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "date": "2026-09-30", "written_by": "beneficiary", "quote": "Due to the severity of the aforementioned statements, the information was escalated to a human review team, which subsequently reported the statements to law enforcement." }, { "kind": "news report", "citation": "WINK News, Alvarado, D. (2026). Woman arrested after AI threat against Lee County Sheriff's Office: Investigators. WINK News.", "title": "Woman arrested after AI threat against Lee County Sheriff's Office: Investigators", "url": "https://www.winknews.com/news/woman-arrested-after-ai-threat-against-lee-county-sheriffs-office-investigators/article_3d4c5915-7015-43c0-b86a-d7fa5eadf958.html", "date": "2026-09-30", "written_by": "independent", "quote": "Deputies identified Heller and went to her Bonita Springs home and she was detained without incident before an LCSO intelligence detective took over the investigation." }, { "kind": "news report", "citation": "The Daily Caller, Kresak, D. (2026). Florida Woman Nabbed After Chatbot Maker Flags Alleged Threat to 'Shoot Up' Sheriff's Office. The Daily Caller.", "title": "Florida Woman Nabbed After Chatbot Maker Flags Alleged Threat to 'Shoot Up' Sheriff's Office", "url": "https://dailycaller.com/2026/10/05/chatbot-maker-tips-off-cops-florida-woman-allegedly-threatens-sheriffs-office/", "date": "2026-10-05", "written_by": "independent", "quote": "When someone uses AI to make or facilitate a threat, we have to take that threat seriously." }, { "kind": "news report", "citation": "Straight Arrow News, Pavlou, D. (2026). A chatbot message led to a felony charge. Experts say it may not hold up. Straight Arrow News.", "title": "A chatbot message led to a felony charge. Experts say it may not hold up", "url": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/", "date": "2026-10-08", "written_by": "independent", "quote": "She denied owning any firearms, and the arrest form indicates authorities didn’t seize a weapon." }, { "kind": "news report", "citation": "Tom's Hardware, Downing, S. (2026). Anthropic reports Florida woman’s Claude ‘diary’ threat to shoot up sheriff’s office, felony charge follows — it’s at least the third such conversation to reach police since August. Tom's Hardware.", "title": "Anthropic reports Florida woman’s Claude ‘diary’ threat to shoot up sheriff’s office, felony charge follows — it’s at least the third such conversation to reach police since August", "url": "https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-reports-florida-womans-claude-diary-threat-to-shoot-up-sheriffs-office-felony-charge-follows-its-at-least-the-third-such-conversation-to-reach-police-since-august", "date": "2026-10-05", "written_by": "independent", "quote": "court records listing the Sept. 30 felony charge under Florida Statute 836.10: written or electronic threat of a mass shooting or act of terrorism" }, { "kind": "other", "citation": "Volokh, E. (2026). Can a Chatbot Prompt Be a Punishable Threat? Reason, The Volokh Conspiracy.", "title": "Can a Chatbot Prompt Be a Punishable Threat?", "url": "https://reason.com/volokh/2026/10/08/can-a-chatbot-prompt-be-a-punishable-threat/", "date": "2026-10-08", "written_by": "independent", "quote": "Simply typing a prompt into a chatbot, expecting it to be viewed only by the software, wouldn't qualify." }, { "kind": "news report", "citation": "The San Francisco Standard, Jones, R. (2026). Anthropic called SFPD over threat against CEO. Claude user says it was a misunderstanding. The San Francisco Standard.", "title": "Anthropic called SFPD over threat against CEO. Claude user says it was a misunderstanding", "url": "https://sfstandard.com/2026/09/04/anthropic-threat-claude-sfpd/", "date": "2026-09-04", "written_by": "independent", "quote": "We banned this account, consistent with our standard practice, and referred the case to law enforcement. This is our safeguards process working as intended." }, { "kind": "other", "citation": "Anthropic (2026). Privacy Policy, effective 10 September 2026. Anthropic.", "title": "Privacy Policy", "url": "https://www.anthropic.com/legal/privacy", "date": "2026-09-10", "written_by": "makers", "quote": "(ii) prevent serious harm to any person or to property; (iii) detect, prevent, or otherwise address fraud or other illegal activity" }, { "kind": "other", "citation": "Anthropic (2025). Consumer Terms of Service, effective 8 October 2025. Anthropic.", "title": "Consumer Terms of Service", "url": "https://www.anthropic.com/legal/consumer-terms", "date": "2025-10-08", "written_by": "makers", "quote": "We reserve the right, at our sole discretion, to report information from or about you, including but not limited to Inputs, Outputs, or Actions to law enforcement." } ], "replication": { "produced_by": [ "A vendor practice of screening consumer chats for threatening content and escalating severe cases to a human review team. That team can refer them to law enforcement, which Anthropic's consumer terms and privacy policy permit", "A tip carrying enough account information for the sheriff's office to identify a named resident within days", "A local agency that treated a stated threat against its own building as credible enough to send deputies the same night" ], "must_hold": [ "The referral must identify a real person and a real risk. The Lee County Sheriff's Office told reporters it does not count tips from Anthropic. No public figures exist on how often such referrals are made or prove unfounded", "The disclosure must stay within the emergency exception of the Stored Communications Act. An EFF attorney told Straight Arrow News “there is always the risk of over-reporting”, and the Monitor logs reputational and psychological harm to the user", "The response must remain proportionate. Here no weapon was found, and the user described a personal diary. Whether a chatbot prompt is a punishable threat under Florida Statute 836.10 is contested by the defense and by Eugene Volokh", "The attribution to Claude rests on press reports and the arrest report's phrase “Anthropic Artificial Intelligence”. Court records also note the user told the detective she used Perplexity, and her attorney declined to say which" ], "echoes": [] }, "paired_incident": null, "headline": "Anthropic flag on a shooting threat leads to a Florida arrest", "metric": null, "comparator": null, "later": { "status": "litigated", "date": "2026-10-08", "note": "Heller pleaded not guilty and her arraignment was set for 2 November 2026 while prosecutors had not yet filed a formal charge; the arrest form sets a $10,000 bond and a 20 October 2026 appearance date, and First Amendment scholar Eugene Volokh doubts the charge will hold.", "quote": "Heller's arraignment is scheduled for Nov. 2", "url": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/" }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-10-04-dced", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Anthropic", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: five independent news reports, one other independent source, two other sources from the makers and the beneficiary's court document. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0240", "catalog_version": "1.0.0", "source_fingerprint": "c87231c7cd74f35a314296f55b276a55c0341260a19641f61d8c311faf2b20c2", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "querist", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0240-source-0001", "AIBD-0240-source-0002", "AIBD-0240-source-0003", "AIBD-0240-source-0004", "AIBD-0240-source-0005", "AIBD-0240-source-0006", "AIBD-0240-source-0007", "AIBD-0240-source-0008", "AIBD-0240-source-0009" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Anthropic", "deployer": "Anthropic" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The arrest report says the platform “utilizes safety and security measures designed to monitor for key phrases and potentially threatening content”. It says the messages were “escalated to a human review team”. An automated layer therefore surfaced the two messages, and people judged their severity and made the referral. The sources do not say whether the flag came from a classifier or a keyword rule. Straight Arrow News, citing court records, says the review team escalated to the FBI, which notified the sheriff's office. Identifying the user, the home visit, the Miranda interview and the charging decision were the work of Lee County deputies and Intelligence Detective Thomas Alejo. The arrest report calls the platform “Anthropic Artificial Intelligence”. Press reports name Claude, and court records note the user told the detective she used Perplexity." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The platform automatically flagged threatening messages for human review. Reviewers referred the messages to law enforcement.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "The arrest report says the platform “utilizes safety and security measures designed to monitor for key phrases and potentially threatening content”. It says the messages were “escalated to a human review team”. An automated layer therefore surfaced the two messages, and people judged their severity and made the referral. The sources do not say whether the flag came from a classifier or a keyword rule. Straight Arrow News, citing court records, says the review team escalated to the FBI, which notified the sheriff's office. Identifying the user, the home visit, the Miranda interview and the charging decision were the work of Lee County deputies and Intelligence Detective Thomas Alejo. The arrest report calls the platform “Anthropic Artificial Intelligence”. Press reports name Claude, and court records note the user told the detective she used Perplexity." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Lee County Sheriff's Office, the threatened party, received a tip quoting a stated plan to shoot up its building and a claimed new gun. It identified the user and resolved the matter at her home within about three days without incident. No weapon was seized, so no averted attack is shown." }, { "group": "societal", "depth": 1, "reason": "A written threat of a mass shooting at a public building was examined within days rather than left unread. It was at least the third Anthropic referral to police since August 2026. 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It was at least the third Anthropic referral to police since August 2026. The benefit is bounded by the absence of a weapon, the user's diary account, and expert doubt that the words were a true threat." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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"not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "No public figures establish how often Anthropic’s referrals are substantiated. The arrest report names Anthropic but does not identify the detection method. Coverage names Claude, while court records also report that the user mentioned Perplexity. No weapon or averted attack is established." } }, "external_references[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "registry_ids": { "oecd_aim": "2026-10-04-dced" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "registry_ids" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "litigated", "date": "2026-10-08", "note": "Heller pleaded not guilty and her arraignment was set for 2 November 2026 while prosecutors had not yet filed a formal charge; the arrest form sets a $10,000 bond and a 20 October 2026 appearance date, and First Amendment scholar Eugene Volokh doubts the charge will hold.", "quote": "Heller's arraignment is scheduled for Nov. 2", "url": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "value_present", "value": { "kind": "text", "text": "Reviewers assessed the messages before making the referral. Deputies identified and interviewed the user and made the charging decision." }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "ai_role", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0240" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "value_present", "value": { "kind": "text", "text": "The Lee County Sheriff’s Office was the threatened institution and recipient of the tip. A wider safety benefit is unproved." }, "provenance": { "kind": "legacy_record", "basis": "Moved the specific information already present in the entry into its applicable question. No new source review is implied.", "record_fields": [ "account", "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "The Lee County Sheriff’s Office was the threatened institution and recipient of the tip. A wider safety benefit is unproved." } }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A user of Anthropic's AI chat service wrote at about 05:10 on 26 September 2026. She said she was going to “shoot up” the Lee County Sheriff's Office in Florida. At 01:07 on 27 September she wrote that she had got a new gun. Anthropic's safety monitoring flagged the messages, and because of their severity a human review team reported them to law enforcement. The sheriff's office logged the tip on 29 September and identified the user as Carli Michelle Heller, 30, of Bonita Springs. Deputies detained her at home without incident at 00:51 on 30 September. A detective charged her under Florida Statute 836.10, written threats of violence. No weapon was seized, and she described the AI as a personal diary.", "benefit_type": "Reduced Violence" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Anthropic’s reviewers reported threatening messages to police, who identified and detained the user without incident. No weapon was found." } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "depth": 1, "reason": "The Lee County Sheriff's Office, the threatened party, received a tip quoting a stated plan to shoot up its building and a claimed new gun. It identified the user and resolved the matter at her home within about three days without incident. No weapon was seized, so no averted attack is shown." }, { "group": "societal", "depth": 1, "reason": "A written threat of a mass shooting at a public building was examined within days rather than left unread. It was at least the third Anthropic referral to police since August 2026. The benefit is bounded by the absence of a weapon, the user's diary account, and expert doubt that the words were a true threat." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Anthropic's consumer terms (effective 8 October 2025) reserve the right “at our sole discretion” to report Inputs to law enforcement. Its privacy policy (effective 10 September 2026) allows disclosure the company believes “reasonably necessary” to “prevent serious harm to any person or to property”. The arrest report says the platform's safety measures are “designed to monitor for key phrases and potentially threatening content”. Flagging a stated shooting threat, reviewing it by hand and referring it to police was that purpose. Of an August 2026 referral Anthropic said “This is our safeguards process working as intended”." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Bonita Springs, United States", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Anthropic's consumer terms (effective 8 October 2025) reserve the right “at our sole discretion” to report Inputs to law enforcement. Its privacy policy (effective 10 September 2026) allows disclosure the company believes “reasonably necessary” to “prevent serious harm to any person or to property”. The arrest report says the platform's safety measures are “designed to monitor for key phrases and potentially threatening content”. Flagging a stated shooting threat, reviewing it by hand and referring it to police was that purpose. Of an August 2026 referral Anthropic said “This is our safeguards process working as intended”." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-09-29", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-10-04-dced", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Anthropic", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A vendor practice of screening consumer chats for threatening content and escalating severe cases to a human review team. That team can refer them to law enforcement, which Anthropic's consumer terms and privacy policy permit", "A tip carrying enough account information for the sheriff's office to identify a named resident within days", "A local agency that treated a stated threat against its own building as credible enough to send deputies the same night" ], "must_hold": [ "The referral must identify a real person and a real risk. The Lee County Sheriff's Office told reporters it does not count tips from Anthropic. No public figures exist on how often such referrals are made or prove unfounded", "The disclosure must stay within the emergency exception of the Stored Communications Act. An EFF attorney told Straight Arrow News “there is always the risk of over-reporting”, and the Monitor logs reputational and psychological harm to the user", "The response must remain proportionate. Here no weapon was found, and the user described a personal diary. Whether a chatbot prompt is a punishable threat under Florida Statute 836.10 is contested by the defense and by Eugene Volokh", "The attribution to Claude rests on press reports and the arrest report's phrase “Anthropic Artificial Intelligence”. Court records also note the user told the detective she used Perplexity, and her attorney declined to say which" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "display": { "answer": "Reviewers need enough information to identify the person and assess a credible risk. Disclosure and police action need a lawful basis and a proportionate response." } }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the OECD Monitor entry and the cited sources.", "source": "https://oecd.ai/en/incidents/2026-10-04-dced", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Reduced Violence under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Anthropic; https://en.wikipedia.org/wiki/Anthropic", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Clarified the displayed field answers and placed measurements and limitations in their respective fields.", "editor": "AIBD" }, { "date": "2026-10-25", "change": "Reviewed the specified original sources; corrected their authorship, document types, and support for the reported benefit.", "source": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Online safety and threat referral to law enforcement", "segment": "Media, social platforms, and marketing" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "court document", "citation": "Lee County Sheriff's Office, Alejo, T. S. (2026). Arrest / Notice to Appear and Probable Cause Statement, agency report 26-530248, clerk case 26CF017549, Heller, Carli Michelle. Redacted copy hosted by the Daily Caller.", "title": "Arrest report and probable cause statement, LCSO report 26-530248 (Heller, Carli Michelle)", "url": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "date": "2026-09-30", "written_by": "beneficiary", "quote": "Due to the severity of the aforementioned statements, the information was escalated to a human review team, which subsequently reported the statements to law enforcement." }, { "kind": "news report", "citation": "WINK News, Alvarado, D. (2026). Woman arrested after AI threat against Lee County Sheriff's Office: Investigators. WINK News.", "title": "Woman arrested after AI threat against Lee County Sheriff's Office: Investigators", "url": "https://www.winknews.com/news/woman-arrested-after-ai-threat-against-lee-county-sheriffs-office-investigators/article_3d4c5915-7015-43c0-b86a-d7fa5eadf958.html", "date": "2026-09-30", "written_by": "independent", "quote": "Deputies identified Heller and went to her Bonita Springs home and she was detained without incident before an LCSO intelligence detective took over the investigation." }, { "kind": "news report", "citation": "The Daily Caller, Kresak, D. (2026). Florida Woman Nabbed After Chatbot Maker Flags Alleged Threat to 'Shoot Up' Sheriff's Office. The Daily Caller.", "title": "Florida Woman Nabbed After Chatbot Maker Flags Alleged Threat to 'Shoot Up' Sheriff's Office", "url": "https://dailycaller.com/2026/10/05/chatbot-maker-tips-off-cops-florida-woman-allegedly-threatens-sheriffs-office/", "date": "2026-10-05", "written_by": "independent", "quote": "When someone uses AI to make or facilitate a threat, we have to take that threat seriously." }, { "kind": "news report", "citation": "Straight Arrow News, Pavlou, D. (2026). A chatbot message led to a felony charge. Experts say it may not hold up. Straight Arrow News.", "title": "A chatbot message led to a felony charge. Experts say it may not hold up", "url": "https://san.com/cc/a-chatbot-message-led-to-a-felony-charge-experts-say-it-may-not-hold-up/", "date": "2026-10-08", "written_by": "independent", "quote": "She denied owning any firearms, and the arrest form indicates authorities didn’t seize a weapon." }, { "kind": "news report", "citation": "Tom's Hardware, Downing, S. (2026). Anthropic reports Florida woman’s Claude ‘diary’ threat to shoot up sheriff’s office, felony charge follows — it’s at least the third such conversation to reach police since August. Tom's Hardware.", "title": "Anthropic reports Florida woman’s Claude ‘diary’ threat to shoot up sheriff’s office, felony charge follows — it’s at least the third such conversation to reach police since August", "url": "https://www.tomshardware.com/tech-industry/artificial-intelligence/anthropic-reports-florida-womans-claude-diary-threat-to-shoot-up-sheriffs-office-felony-charge-follows-its-at-least-the-third-such-conversation-to-reach-police-since-august", "date": "2026-10-05", "written_by": "independent", "quote": "court records listing the Sept. 30 felony charge under Florida Statute 836.10: written or electronic threat of a mass shooting or act of terrorism" }, { "kind": "other", "citation": "Volokh, E. (2026). Can a Chatbot Prompt Be a Punishable Threat? Reason, The Volokh Conspiracy.", "title": "Can a Chatbot Prompt Be a Punishable Threat?", "url": "https://reason.com/volokh/2026/10/08/can-a-chatbot-prompt-be-a-punishable-threat/", "date": "2026-10-08", "written_by": "independent", "quote": "Simply typing a prompt into a chatbot, expecting it to be viewed only by the software, wouldn't qualify." }, { "kind": "news report", "citation": "The San Francisco Standard, Jones, R. (2026). Anthropic called SFPD over threat against CEO. Claude user says it was a misunderstanding. The San Francisco Standard.", "title": "Anthropic called SFPD over threat against CEO. Claude user says it was a misunderstanding", "url": "https://sfstandard.com/2026/09/04/anthropic-threat-claude-sfpd/", "date": "2026-09-04", "written_by": "independent", "quote": "We banned this account, consistent with our standard practice, and referred the case to law enforcement. This is our safeguards process working as intended." }, { "kind": "other", "citation": "Anthropic (2026). Privacy Policy, effective 10 September 2026. Anthropic.", "title": "Privacy Policy", "url": "https://www.anthropic.com/legal/privacy", "date": "2026-09-10", "written_by": "makers", "quote": "(ii) prevent serious harm to any person or to property; (iii) detect, prevent, or otherwise address fraud or other illegal activity" }, { "kind": "other", "citation": "Anthropic (2025). Consumer Terms of Service, effective 8 October 2025. Anthropic.", "title": "Consumer Terms of Service", "url": "https://www.anthropic.com/legal/consumer-terms", "date": "2025-10-08", "written_by": "makers", "quote": "We reserve the right, at our sole discretion, to report information from or about you, including but not limited to Inputs, Outputs, or Actions to law enforcement." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0240-source-0001", "AIBD-0240-source-0002", "AIBD-0240-source-0003", "AIBD-0240-source-0004", "AIBD-0240-source-0005", "AIBD-0240-source-0006", "AIBD-0240-source-0007", "AIBD-0240-source-0008", "AIBD-0240-source-0009" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "text", "text": "A sheriff’s detective wrote the arrest statement. It documents the referral and police response. It does not establish that an attack was averted, and no weapon was seized." }, "provenance": { "kind": "source_review", "basis": "The identified originals and their locators are listed in the source assessment.", "record_fields": [], "source_refs": [ "AIBD-0240-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A sheriff’s detective wrote the arrest statement. It documents the referral and police response. It does not establish that an attack was averted, and no weapon was seized." } }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-25", "lead_source_ref": "AIBD-0240-source-0001", "retained_source_order": [ "AIBD-0240-source-0001", "AIBD-0240-source-0002", "AIBD-0240-source-0003", "AIBD-0240-source-0004", "AIBD-0240-source-0005", "AIBD-0240-source-0006", "AIBD-0240-source-0007", "AIBD-0240-source-0008", "AIBD-0240-source-0009" ], "origins": [ { "url": "https://cdn01.dailycaller.com/wp-content/uploads/2026/10/26-530248_Heller__Carli_Redacted.pdf", "locator": "Arrest/probable-cause form, pp. 1–2; author signature, referral narrative, and weapons-seized field.", "contribution": "Firsthand account of the tip, review, detention, and absence of a seized weapon.", "relationship": "The claimed beneficiary’s police statement filed with the clerk, not a judicial determination.", "source_refs": [ "AIBD-0240-source-0001" ] } ], "excluded_or_consolidated_sources": [], "review_scope": "Whether the specified sources establish the reported benefit, their document types, and their authorship relationships. Other fields and sources were not comprehensively reassessed." } }, "provenance": { "kind": "source_review", "basis": "A limited source-role review; each inspected source and its contribution is identified.", "record_fields": [], "source_refs": [ "AIBD-0240-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "A sheriff’s detective wrote the arrest statement. It documents the referral and police response. It does not establish that an attack was averted, and no weapon was seized." } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Anthropic safeguards flagged a threat to shoot up a Florida sheriff's office; reviewers tipped police, who arrested the user; no gun found.", "account": "A user of Anthropic's AI chat service wrote at about 05:10 on 26 September 2026. She said she was going to “shoot up” the Lee County Sheriff's Office in Florida. At 01:07 on 27 September she wrote that she had got a new gun. Anthropic's safety monitoring flagged the messages, and because of their severity a human review team reported them to law enforcement. The sheriff's office logged the tip on 29 September and identified the user as Carli Michelle Heller, 30, of Bonita Springs. Deputies detained her at home without incident at 00:51 on 30 September. A detective charged her under Florida Statute 836.10, written threats of violence. No weapon was seized, and she described the AI as a personal diary." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Anthropic Claude consumer-chat safety monitoring: automated flagging of threatening content, escalation to a human review team, referral to law enforcement" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Anthropic" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Anthropic's threat monitoring flags a Bonita Springs woman's messages about shooting up the Lee County Sheriff's Office; human reviewers tip police, who detain her without incident and find no gun", "headline": "Anthropic flag on a shooting threat leads to a Florida arrest" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "c87231c7cd74f35a314296f55b276a55c0341260a19641f61d8c311faf2b20c2" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A user of Anthropic's AI chat service wrote at about 05:10 on 26 September 2026. She said she was going to “shoot up” the Lee County Sheriff's Office in Florida. At 01:07 on 27 September she wrote that she had got a new gun. Anthropic's safety monitoring flagged the messages, and because of their severity a human review team reported them to law enforcement. The sheriff's office logged the tip on 29 September and identified the user as Carli Michelle Heller, 30, of Bonita Springs. Deputies detained her at home without incident at 00:51 on 30 September. A detective charged her under Florida Statute 836.10, written threats of violence. No weapon was seized, and she described the AI as a personal diary.", "replication": { "produced_by": [ "A vendor practice of screening consumer chats for threatening content and escalating severe cases to a human review team. That team can refer them to law enforcement, which Anthropic's consumer terms and privacy policy permit", "A tip carrying enough account information for the sheriff's office to identify a named resident within days", "A local agency that treated a stated threat against its own building as credible enough to send deputies the same night" ], "must_hold": [ "The referral must identify a real person and a real risk. The Lee County Sheriff's Office told reporters it does not count tips from Anthropic. No public figures exist on how often such referrals are made or prove unfounded", "The disclosure must stay within the emergency exception of the Stored Communications Act. An EFF attorney told Straight Arrow News “there is always the risk of over-reporting”, and the Monitor logs reputational and psychological harm to the user", "The response must remain proportionate. Here no weapon was found, and the user described a personal diary. Whether a chatbot prompt is a punishable threat under Florida Statute 836.10 is contested by the defense and by Eugene Volokh", "The attribution to Claude rests on press reports and the arrest report's phrase “Anthropic Artificial Intelligence”. Court records also note the user told the detective she used Perplexity, and her attorney declined to say which" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 32, "reviewed": 2, "record_mapped": 30, "not_assessed": 59, "complete": false, "by_state": { "value_present": 32, "not_reported": 0, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0262", "title": "Zasocitinib, computationally designed by Nimbus with Schrodinger's platform, beats deucravacitinib in phase 3; FDA priority review", "summary": "Takeda reports 36.5% complete skin clearance with zasocitinib versus 13.9% with deucravacitinib at week 16. The contribution of AI to discovery is not separately measured.", "date_observed": "2026-09-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Takeda reported that zasocitinib produced complete skin clearance in 36.5% of its LATITUDE Atlas group, versus 13.9% with deucravacitinib, at week 16. The September 30, 2026 announcement gives analysis groups of 301 and 303 participants. The sponsor’s registration lists 606 enrolled participants and has no posted results. The earlier Nimbus-funded phase 2b trial treated 259 participants and found a dose response against placebo, including complete clearance in 33% at the 30 mg dose. Nimbus and Schrödinger developed the molecule with computational structure-based design. Schrödinger describes free-energy calculations and virtual screening, while a Takeda scientist separately describes the approach as AI-assisted. These accounts do not isolate the effect of AI from the wider discovery process. Takeda reported that the FDA granted priority review and that the EMA accepted its application in September 2026. These were application milestones, not approvals. Takeda’s February 2023 closing announcement states an approximately $4 billion upfront acquisition payment, with additional contingent milestones. That transaction is not a valuation of the benefit attributable to AI.", "category": "benefit created", "unexpected": false, "purpose": "Design a selective oral allosteric TYK2 inhibitor for plaque psoriasis and other immune-mediated diseases", "system": "Schrodinger physics-based computational drug-design platform with machine learning, used by Nimbus Therapeutics to discover NDI-034858 (TAK-279, zasocitinib)", "model_version": "FEP+", "developer": "Schrodinger (platform); Nimbus Therapeutics (compound)", "deployer": "Takeda (clinical development, LATITUDE phase 3 program)", "location": "United States (Nimbus, Boston; Takeda Development Center Americas, Cambridge, MA); phase 2b at 55 sites in the US and Canada; phase 3 sites unverified", "domain": "Health; drug discovery", "segment": "Adults with moderate-to-severe plaque psoriasis", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "Trial participants achieved complete skin clearance at higher rates. PASI 100 was 36.5% vs 13.9% at week 16 in LATITUDE Atlas, and 33% at 30 mg in phase 2b." }, { "group": "organizational", "depth": 2, "reason": "Takeda reported acceptance of its application for FDA priority review in September 2026 after acquiring the program for approximately $4 billion upfront. Application acceptance is not regulatory confirmation of efficacy or an estimate of AI-created value." }, { "group": "societal", "depth": null, "reason": "No approval or population-level outcome as of 20 October 2026." } ], "ai_role": { "status": "assessed", "statement": "The original developer accounts describe computational structure-based design, free-energy calculations, and virtual screening. Takeda’s Warren Winkelman calls the approach AI-assisted. Physics-based computation alone does not establish an AI contribution. The discovery paper and developer accounts do not provide a controlled estimate of AI’s contribution to clinical efficacy, discovery speed, or the acquisition price." }, "evidence": [ { "kind": "press release", "citation": "Takeda. Zasocitinib demonstrates superior efficacy to deucravacitinib in LATITUDE Atlas. 2026-09-30. Original sponsor announcement of EADV 2026 late-breaking results, citing Stein Gold et al., LB-312, session D3T01.3.", "title": "Zasocitinib demonstrates superior efficacy to deucravacitinib in LATITUDE Atlas", "url": "https://www.takeda.com/newsroom/newsreleases/2026/zasocitinib-superior-efficacy/", "date": "2026-09-30", "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Armstrong AW, Gooderham M, Lynde C, et al.. Tyrosine Kinase 2 Inhibition With Zasocitinib (TAK-279) in Psoriasis: A Randomized Clinical Trial. 2024-08-21. JAMA Dermatology 160(10). doi:10.1001/jamadermatol.2024.2701. Nimbus funded the trial and participated in design, analysis, and interpretation.", "title": "Tyrosine Kinase 2 Inhibition With Zasocitinib (TAK-279) in Psoriasis: A Randomized Clinical Trial", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11339701/", "date": "2024-08-21", "written_by": "makers", "quote": null }, { "kind": "dataset", "citation": "Takeda; ClinicalTrials.gov. NCT06973291: LATITUDE Atlas. 2025-05-15. Sponsor-submitted registration; first posted May 15, 2025, updated May 1, 2026. No posted results.", "title": "NCT06973291: LATITUDE Atlas", "url": "https://clinicaltrials.gov/study/NCT06973291", "date": "2025-05-15", "written_by": "makers", "quote": null }, { "kind": "report", "citation": "Schrödinger. Design of a highly selective, allosteric, picomolar TYK2 inhibitor using novel FEP+ strategies. n.d. Original developer account; JH2 program section concerns TAK-279.", "title": "Design of a highly selective, allosteric, picomolar TYK2 inhibitor using novel FEP+ strategies", "url": "https://www.schrodinger.com/design-of-a-highly-selective-allosteric-picomolar-tyk2-inhibitor-using-novel-fep-strategies/", "date": null, "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Drug Target Review, interview with Takeda’s Warren Winkelman. Inside Zasocitinib: A New Model for TYK2 Inhibition in Immune-Mediated Diseases. 2025-09-26. A firsthand sponsor account of the AI-assisted design claim, rather than independent verification.", "title": "Inside Zasocitinib: A New Model for TYK2 Inhibition in Immune-Mediated Diseases", "url": "https://www.drugtargetreview.com/inside-zasocitinib-a-new-model-for-tyk2-inhibition-in-immune-mediated-diseases/677029.article", "date": "2025-09-26", "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "Takeda. FDA Grants Priority Review to Zasocitinib for Moderate-to-Severe Plaque Psoriasis. 2026-09-14. Sponsor reports FDA priority review and EMA application acceptance; no approval reported.", "title": "FDA Grants Priority Review to Zasocitinib for Moderate-to-Severe Plaque Psoriasis", "url": "https://www.takeda.com/newsroom/newsreleases/2026/fda-priority-review-zasocitinib-psoriasis/", "date": "2026-09-14", "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "Takeda. Takeda Completes Acquisition of Nimbus Therapeutics’ TYK2 Program Subsidiary. 2023-02-08. Closing announcement. Approximately $4 billion upfront, subject to closing adjustments, with contingent milestones.", "title": "Takeda Completes Acquisition of Nimbus Therapeutics’ TYK2 Program Subsidiary", "url": "https://www.takeda.com/newsroom/newsreleases/2023/takeda-completes-acquisition-of-nimbus-therapeutics-tyk2-program-subsidiary/", "date": "2023-02-08", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Computational structure-based design and laboratory testing of a selective allosteric TYK2 inhibitor", "Sponsor-led randomized clinical trials against placebo and deucravacitinib" ], "must_hold": [ "Phase 3 efficacy and safety confirmed in regulatory review", "Independent documentation of the computational platform's contribution to the molecule" ], "echoes": [ { "date": "2024-08-21", "setting": "Phase 2b RCT, 47 US and 8 Canadian centers, 259 treated patients", "model_version": null, "outcome": "recurred", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11339701/" }, { "date": "2026-09-14", "setting": "FDA acceptance of the NDA under priority review", "model_version": null, "outcome": "unknown", "source": "https://www.takeda.com/newsroom/newsreleases/2026/fda-priority-review-zasocitinib-psoriasis/" } ] }, "paired_incident": null, "headline": "Nimbus's zasocitinib beats deucravacitinib in phase 3 trial", "metric": "PASI 100 36.5% vs 13.9% for deucravacitinib at week 16", "comparator": { "against": "deucravacitinib (Sotyktu), the active comparator in the LATITUDE Atlas phase 3 trial", "before": "13.9% of those receiving deucravacitinib (n = 303)", "after": "36.5% of patients (n = 301) achieving PASI 100 at week 16", "basis": "measured", "quote": "36.5% of patients treated with zasocitinib (n=301) achieved complete skin clearance … versus 13.9% in the deucravacitinib group", "url": "https://www.takeda.com/newsroom/newsreleases/2026/zasocitinib-superior-efficacy/" }, "later": { "status": "unknown", "date": "2026-09-14", "note": "Takeda reported FDA priority review with a decision expected in the first quarter of 2027 and EMA acceptance of the application. 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Corrected the phase 2b trial’s interested authorship and online publication date.", "source": "https://www.takeda.com/newsroom/newsreleases/2026/zasocitinib-superior-efficacy/", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study, the makers' report, the makers' news report, the makers' dataset and three press releases from the makers. 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The September 30, 2026 announcement gives analysis groups of 301 and 303 participants. The sponsor’s registration lists 606 enrolled participants and has no posted results. The earlier Nimbus-funded phase 2b trial treated 259 participants and found a dose response against placebo, including complete clearance in 33% at the 30 mg dose. Nimbus and Schrödinger developed the molecule with computational structure-based design. Schrödinger describes free-energy calculations and virtual screening, while a Takeda scientist separately describes the approach as AI-assisted. These accounts do not isolate the effect of AI from the wider discovery process. Takeda reported that the FDA granted priority review and that the EMA accepted its application in September 2026. These were application milestones, not approvals. Takeda’s February 2023 closing announcement states an approximately $4 billion upfront acquisition payment, with additional contingent milestones. 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They are at the Marietta Blau Institute for Particle Physics (Austrian Academy of Sciences, Vienna). Alessandro Longo (University of Urbino and INFN Florence) is a co-author. It is titled “MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data” (version 2, 19 October 2026; submitted to the European Physical Journal C). The pipeline is “a series of sequential convolutional neural networks that perform anomaly detection, glitch classification, coherence testing, and signal ranking”. It is applied to one-second Q-transform windows of Hanford and Livingston data from O3a, O3b, O4a and O4b. That is 442.9 days of coincident livetime in total. The abstract reports 47 detections with a false alarm rate below one per year and p_astro above 0.9. Of those, “44 are shared with the minimally modeled coherent WaveBurst search”. The three others are cataloged events, and the paper states that “no candidate without a catalog counterpart survives the analysis”. Recovery rises with mass. It reaches 8.1% of confident catalog events below 30 solar masses and 39.8% between 30 and 100. It reaches 53.3% above 100 for network SNR above 10. The authors conclude that anomaly-detection pipelines “can serve as an independent detection channel complementary to matched filtering in the high-mass high-SNR regime”. The paper confirms no new event independently. The authors identify the two-detector configuration as MADGRAV-2D in their code repository. Its changelog dates the final pipeline configuration to 14 September 2026, and its README states that this configuration produced the reported 47 detections. The repository provides the trained weights and frozen calibration.", "category": "general benefit", "unexpected": false, "purpose": "MADGRAV was built to search LIGO data for high-mass compact binary coalescences by anomaly detection. Recovering cataloged events was that purpose.", "system": "MADGRAV-2D (two-detector cascade of convolutional neural networks)", "model_version": null, "developer": "Marietta Blau Institute for Particle Physics, Austrian Academy of Sciences, with the University of Urbino and INFN Florence", "deployer": "The same authors, on public LIGO O3 and O4 data", "location": "Vienna, Austria", "domain": "Astrophysics / gravitational-wave astronomy", "segment": "Academic research on public detector data", "benefit_type": "Improved Task Accuracy", "taxonomy_note": "Re-detection of cataloged events is read as task performance; no discovery is claimed.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "Recovery of 47 known events, 44 of them shared with coherent WaveBurst, demonstrates the method. No new event, catalog adoption or operational use is documented." }, { "group": "societal", "depth": null, "reason": "A complementary search channel is proposed; no scientific result beyond re-detection is claimed." } ], "ai_role": { "status": "assessed", "statement": "The convolutional networks performed the whole detection chain, from anomaly detection to ranking, and the authors are the developers. Every detection matches a published catalog event. The authors state that no candidate without a catalog counterpart survives, so the search added no new discovery in this analysis." }, "evidence": [ { "kind": "preprint", "citation": "Inguglia G, Haigh H, Dupletsa U, Longo A (2026). MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data. arXiv:2609.39583v1, 30 September 2026, abstract and sections 3–5. Revised as v2 on 19 October 2026. Authored by the pipeline's developers.", "title": "MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data", "url": "https://arxiv.org/abs/2609.39583v1", "date": "2026-09-30", "written_by": "makers", "quote": "Of the 47 detections, 44 are shared with the minimally modelled coherent WaveBurst search." }, { "kind": "other", "citation": "Inguglia, Gianluca, and collaborators. MADGRAV code repository, snapshot acb66841f9408939c1ca17bff90360214c4ea2c9, 19 September 2026. README opening and sections 3–6; CHANGELOG entry for 14 September 2026; spectrogram_cascade/massive_calibration_BA.json; environment.yml.", "title": "MADGRAV: Multilevel Anomaly Detection for GRAVitational-wave science", "url": "https://github.com/ginguglia/MADGRAV/tree/acb66841f9408939c1ca17bff90360214c4ea2c9", "date": "2026-09-19", "written_by": "makers", "quote": "This is the final version of the pipeline" } ], "replication": { "produced_by": [ "Sequential CNNs for anomaly detection, glitch classification, coherence testing and signal ranking on one-second Q-transform windows of Hanford and Livingston data", "442.9 days of coincident livetime across O3a, O3b, O4a and O4b" ], "must_hold": [ "High-mass, high-SNR sources: the recovered fraction rises from 8.1% below 30 solar masses to 53.3% above 100", "Two-detector coherence between Hanford and Livingston" ], "echoes": [] }, "paired_incident": null, "headline": "Researchers found 47 known gravitational-wave signals", "metric": "47 detections with a false alarm rate below one per year and p_astro above 0.9", "comparator": { "against": "the coherent WaveBurst (cWB) search and the published catalogs on the same LIGO data", "before": null, "after": "47 detections, 17% of the catalog population and 39% of the cWB count", "basis": "measured", "quote": "MADGRAV 47 detections correspond to 17% of the catalog population and 39% of the cWB count. 44 of the 47 are shared with cWB: the MADGRAV detection set is a subset of cWB, with the exclusion of 3 events.", "url": "https://arxiv.org/html/2609.39583v2" }, "later": { "status": "unknown", "date": null, "note": "The authors revised the preprint on 19 October 2026. No independent follow-up result is cited.", "quote": null, "url": null }, "value": null, "developer_country": "Austria", "deployer_country": "Austria", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Title reworded to state the event without naming who claims it.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/html/2609.39583v2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Task Accuracy under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://inspirehep.net/api/institutions?q=Marietta%20Blau&size=3; https://inspirehep.net/api/institutions?q=Marietta%20Blau&size=3", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Consolidated the abstract and HTML citations into one primary preprint. Read version 1 and verified that the 47 detections, 44 shared detections, 442.9 days of data, recovery rates, comparison percentages, and absence of a new candidate were already reported on 30 September 2026. Preserved the 19 October 2026 version 2 link and the submission history in source provenance. Versions of the same work are not independent corroboration.", "source": "https://arxiv.org/html/2609.39583v1", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://arxiv.org/abs/2609.39583v1", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://arxiv.org/abs/2609.39583v1", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://arxiv.org/abs/2609.39583v1", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://arxiv.org/abs/2609.39583v1", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified MADGRAV-2D and recorded the authors' final pipeline configuration dated 14 September 2026. Removed the paper revision from the AI model-version field. Added a fixed repository snapshot, checkpoint identifier, and calibration environment to the configuration metadata; preserved the arXiv versions as publication metadata. No separately labeled model release or exact runtime commit is established.", "source": "https://github.com/ginguglia/MADGRAV/tree/acb66841f9408939c1ca17bff90360214c4ea2c9", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Added both Austrian and Italian developer affiliations and identified Austria as the documented research-computing location. Distinguished the U.S. LIGO data sources from the research location. 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They are at the Marietta Blau Institute for Particle Physics (Austrian Academy of Sciences, Vienna). Alessandro Longo (University of Urbino and INFN Florence) is a co-author. It is titled “MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data” (version 2, 19 October 2026; submitted to the European Physical Journal C). The pipeline is “a series of sequential convolutional neural networks that perform anomaly detection, glitch classification, coherence testing, and signal ranking”. It is applied to one-second Q-transform windows of Hanford and Livingston data from O3a, O3b, O4a and O4b. That is 442.9 days of coincident livetime in total. The abstract reports 47 detections with a false alarm rate below one per year and p_astro above 0.9. Of those, “44 are shared with the minimally modeled coherent WaveBurst search”. The three others are cataloged events, and the paper states that “no candidate without a catalog counterpart survives the analysis”. Recovery rises with mass. It reaches 8.1% of confident catalog events below 30 solar masses and 39.8% between 30 and 100. It reaches 53.3% above 100 for network SNR above 10. The authors conclude that anomaly-detection pipelines “can serve as an independent detection channel complementary to matched filtering in the high-mass high-SNR regime”. The paper confirms no new event independently. The authors identify the two-detector configuration as MADGRAV-2D in their code repository. Its changelog dates the final pipeline configuration to 14 September 2026, and its README states that this configuration produced the reported 47 detections. The repository provides the trained weights and frozen calibration.", "benefit_type": "Improved Task Accuracy" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "Recovery of 47 known events, 44 of them shared with coherent WaveBurst, demonstrates the method. 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The acknowledgments state that computational results used Austrian Scientific Computing infrastructure, including VSC-5 and MUSICA. Austria is the documented research-computing location, not the location of the celestial events. Hanford and Livingston LIGO supplied U.S. observational data. This review adds geographic roles from version 2 without treating it as an independent work or changing the version 1 publication chronology.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [ "AIBD-0283-source-0001" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "The research team had Austrian and Italian affiliations and used computing facilities in Austria. 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(2026a)", "snapshot_commit": "acb66841f9408939c1ca17bff90360214c4ea2c9", "configuration_date": "2026-09-14", "files": [ { "url": "https://github.com/ginguglia/MADGRAV/blob/acb66841f9408939c1ca17bff90360214c4ea2c9/README.md", "locator": "Opening paragraphs, Important note, and sections 3–6", "supports": "MADGRAV-2D identity and the connection between the final configuration and the reported 47 detections." }, { "url": "https://github.com/ginguglia/MADGRAV/blob/acb66841f9408939c1ca17bff90360214c4ea2c9/CHANGELOG.md", "locator": "Entry for 14 September 2026", "supports": "The dated final configuration, including the injection-set glitch-arm gate." }, { "url": "https://github.com/ginguglia/MADGRAV/blob/acb66841f9408939c1ca17bff90360214c4ea2c9/spectrogram_cascade/massive_calibration_BA.json", "locator": "model_path", "supports": "The deployed autoencoder checkpoint path." }, { "url": "https://github.com/ginguglia/MADGRAV/blob/acb66841f9408939c1ca17bff90360214c4ea2c9/environment.yml", "locator": "Frozen-weights training/calibration comments", "supports": "PyTorch, CUDA, and cuDNN versions for calibration of the frozen weights." } ], "limitations": [ "The authors do not identify the exact runtime commit.", "The code repository and paper have the same authorship and are not independent confirmations.", "There is no numbered software release or Git tag." ] }, "reviewed_on": "2026-10-25", "claim_chains": [ { "claim": "Developer affiliations and research location", "path": [ "https://arxiv.org/html/2609.39583v2" ], "finding": "The original paper’s author affiliations identify the Marietta Blau Institute in Vienna, Austria, and the University of Urbino and INFN Florence in Italy. The acknowledgments state that computational results used Austrian Scientific Computing infrastructure, including VSC-5 and MUSICA. Austria is the documented research-computing location, not the location of the celestial events. Hanford and Livingston LIGO supplied U.S. observational data. This review adds geographic roles from version 2 without treating it as an independent work or changing the version 1 publication chronology." } ], "review_scope": " Additional geographic review on October 25, 2026, distinguishes author affiliations, research computing, and the observational-data source without adding another independent work." } }, "provenance": { "kind": "source_review", "basis": "Added geographic roles from the original paper’s affiliations and acknowledgments, preserving the existing version chronology and source identity.", "record_fields": [ "evidence", "developer_country", "location" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-25" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The developers’ preprint reports the detections. Their repository supplies the code, trained weights, and configuration. The paper’s revisions and code are supporting material from the same team.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Researchers used MADGRAV-2D to recover 47 cataloged gravitational-wave signals from LIGO data.", "account": "A paper was posted on arXiv on 30 September 2026 by Gianluca Inguglia, Huw Haigh and Ulyana Dupletsa. They are at the Marietta Blau Institute for Particle Physics (Austrian Academy of Sciences, Vienna). Alessandro Longo (University of Urbino and INFN Florence) is a co-author. It is titled “MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data” (version 2, 19 October 2026; submitted to the European Physical Journal C). The pipeline is “a series of sequential convolutional neural networks that perform anomaly detection, glitch classification, coherence testing, and signal ranking”. It is applied to one-second Q-transform windows of Hanford and Livingston data from O3a, O3b, O4a and O4b. That is 442.9 days of coincident livetime in total. The abstract reports 47 detections with a false alarm rate below one per year and p_astro above 0.9. Of those, “44 are shared with the minimally modeled coherent WaveBurst search”. The three others are cataloged events, and the paper states that “no candidate without a catalog counterpart survives the analysis”. Recovery rises with mass. It reaches 8.1% of confident catalog events below 30 solar masses and 39.8% between 30 and 100. It reaches 53.3% above 100 for network SNR above 10. The authors conclude that anomaly-detection pipelines “can serve as an independent detection channel complementary to matched filtering in the high-mass high-SNR regime”. The paper confirms no new event independently. The authors identify the two-detector configuration as MADGRAV-2D in their code repository. Its changelog dates the final pipeline configuration to 14 September 2026, and its README states that this configuration produced the reported 47 detections. 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The Git blob identifies the checkpoint file; it is not a model release number. The arXiv revisions belong to the paper." } }, "provenance": { "kind": "source_review", "basis": "Traced the paper's repository citation to the authors' README, dated changelog, frozen model configuration, checkpoint listing, and calibration environment.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "MADGRAV-2D combined anomaly detection with classifiers for glitches and low- and high-frequency signals. It analyzed observations from the Hanford and Livingston detectors during LIGO’s O3 and O4 runs.", "editor_note": "" } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "value_present", "value": { "kind": "structured", "data": { "named_component": "BaselineCAE", "component_role": "Convolutional autoencoder for anomaly detection in the MADGRAV-2D cascade.", "scope": "An implementation name in the authors’ published code. The full cascade includes other convolutional networks, and this name does not identify a release." } }, "provenance": { "kind": "source_review", "basis": "The authors’ configuration and code identify BaselineCAE and its checkpoint as a component of the published MADGRAV-2D pipeline.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "BaselineCAE, a convolutional autoencoder, together with convolutional networks that classify glitches and signals.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the paper and the authors' repository, including its README, changelog, frozen calibration configuration, checkpoint listing, and release history.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-24" }, "reason": "The authors publish trained weights and a dated pipeline configuration, but no separately labeled model release for the reported analysis. The configuration date, checkpoint file, and reviewed repository snapshot are recorded separately; none is substituted for an undisclosed model release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The authors publish trained weights and a configuration dated 14 September 2026, without a separate model release number.", "editor_note": "The dated configuration comes from the authors’ repository changelog (reference 2). Their published checkpoint and code snapshot identify available files but do not establish the exact code commit used for every reported run." } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "MADGRAV-2D (two-detector cascade of convolutional neural networks)" } }, "provenance": { "kind": "source_review", "basis": "Identified the reported product or pipeline from its original case and technical sources; kept hardware, underlying model, and software release distinct.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "MADGRAV-2D", "editor_note": "" } }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Gianluca Inguglia and the MADGRAV research team" }, "provenance": { "kind": "source_review", "basis": "The developers authored the paper and provide the public code and trained weights through Gianluca Inguglia's repository.", "record_fields": [ "developer" ], "source_refs": [ "AIBD-0283-source-0001", "AIBD-0283-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "MADGRAV anomaly-detection pipeline recovers 47 gravitational-wave detections in LIGO O3 and O4 data, 44 shared with coherent WaveBurst and none new", "headline": "Researchers found 47 known gravitational-wave signals" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "9a239a727d550cd771e1f73eca2daaf960cfa4c0c3a9881269f88fa1e5a365a0" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after the homepage copy revision.", "record_fields": [ "summary", "revisions" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "A paper was posted on arXiv on 30 September 2026 by Gianluca Inguglia, Huw Haigh and Ulyana Dupletsa. They are at the Marietta Blau Institute for Particle Physics (Austrian Academy of Sciences, Vienna). Alessandro Longo (University of Urbino and INFN Florence) is a co-author. It is titled “MADGRAV: a multilevel anomaly-detection pipeline for gravitational-wave searches applied to LIGO data” (version 2, 19 October 2026; submitted to the European Physical Journal C). The pipeline is “a series of sequential convolutional neural networks that perform anomaly detection, glitch classification, coherence testing, and signal ranking”. It is applied to one-second Q-transform windows of Hanford and Livingston data from O3a, O3b, O4a and O4b. That is 442.9 days of coincident livetime in total. The abstract reports 47 detections with a false alarm rate below one per year and p_astro above 0.9. Of those, “44 are shared with the minimally modeled coherent WaveBurst search”. The three others are cataloged events, and the paper states that “no candidate without a catalog counterpart survives the analysis”. Recovery rises with mass. It reaches 8.1% of confident catalog events below 30 solar masses and 39.8% between 30 and 100. It reaches 53.3% above 100 for network SNR above 10. The authors conclude that anomaly-detection pipelines “can serve as an independent detection channel complementary to matched filtering in the high-mass high-SNR regime”. The paper confirms no new event independently. The authors identify the two-detector configuration as MADGRAV-2D in their code repository. Its changelog dates the final pipeline configuration to 14 September 2026, and its README states that this configuration produced the reported 47 detections. The repository provides the trained weights and frozen calibration.", "replication": { "produced_by": [ "Sequential CNNs for anomaly detection, glitch classification, coherence testing and signal ranking on one-second Q-transform windows of Hanford and Livingston data", "442.9 days of coincident livetime across O3a, O3b, O4a and O4b" ], "must_hold": [ "High-mass, high-SNR sources: the recovered fraction rises from 8.1% below 30 solar masses to 53.3% above 100", "Two-detector coherence between Hanford and Livingston" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 15, "record_mapped": 17, "not_assessed": 59, "complete": false, "by_state": { "value_present": 31, "not_reported": 1, "unresolved": 0, "not_assessed": 59, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0303", "title": "Galaxy Watch4 Classic ECG returns “atrial fibrillation” for Joseph Holycross, 39; ER confirms AFib, a week in hospital and open-heart surgery follow", "summary": "Mr. Joseph Holycross reported that doctors confirmed the atrial fibrillation that Samsung Health Monitor detected on his Galaxy Watch4 Classic.", "date_observed": "2026-10-01", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "CyberGuy published Kurt Knutsson's interview with Joseph and Jamie Holycross on 1 October 2026. Joseph, 39, is a father of four. The event date and place are not given. He had attributed a racing heart to caffeine for one and a half to two years. His wife Jamie, a respiratory therapist, noticed that he was short of breath. She urged him to run the electrocardiogram (ECG) feature on his Samsung Galaxy Watch4 Classic. He says that the result read “atrial fibrillation” in bold. He repeated the recording several times, then went to the emergency room (ER), where a doctor reviewed the watch tracing and confirmed AFib. He stayed about a week in hospital. About ten days later he returned for open-heart surgery to repair “several things on my heart”. Asked whether he would have gone to the ER without the watch, he said “Nope”. The family says that doctors warned that he “probably would have had a stroke, heart attack, or both” and recommended screening for his siblings and children.", "category": "benefit created", "unexpected": false, "purpose": "The Samsung Health Monitor ECG feature is built to record a 30-second single-lead ECG and classify it. It flags a possible AFib result so the user contacts a doctor. This result was that purpose.", "system": "Samsung Health Monitor ECG Monitor app", "model_version": null, "developer": "Samsung Electronics", "deployer": null, "location": "Not stated in the read reports", "domain": "Healthcare (cardiology)", "segment": "Consumer wearables", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "ER confirmation of AFib, a week of inpatient work-up and open-heart surgery followed the result. The stroke-or-heart-attack counterfactual is the family's report of doctors' warnings in a single news feature." } ], "ai_role": { "status": "assessed", "statement": "The watch classified a user-initiated 30-second ECG as atrial fibrillation. Holycross says that he would not have gone to the ER without that result and that an ER doctor confirmed the rhythm. The recording was prompted by his wife's observation, not by a passive irregular-rhythm notification. CyberGuy's original interview records the couple's account. No clinical document or independent clinical verification is cited. Samsung's instructions distinguish the ECG app from its compatible watch hardware. The interview does not disclose the installed app, operating-system, or classifier version." }, "evidence": [ { "kind": "news report", "citation": "Knutsson K (2026). Smartwatch AFib alert sends dad to ER before heart surgery. CyberGuy, 1 October 2026.", "title": "Smartwatch AFib alert sends dad to ER before heart surgery", "url": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "date": "2026-10-01", "written_by": "independent", "quote": "It came up and told me immediately at the top in bold letters, atrial fibrillation" }, { "kind": "other", "citation": "Samsung Electronics. Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use. June 2023, document revision 4.0, pp. 2, 4–5. Page 4 distinguishes ECG app versions 1.1 and 1.2 from compatible Galaxy Watch4 hardware.", "title": "Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use", "url": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "date": null, "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "A Galaxy Watch with the ECG feature enabled through Samsung Health Monitor on a paired Galaxy phone", "A symptomatic user prompted to record an ECG", "An ER able to confirm the rhythm on a 12-lead ECG" ], "must_hold": [ "The single-lead classifier returns AFib rather than inconclusive or poor recording", "The user acts on the result instead of dismissing it" ], "echoes": [] }, "paired_incident": null, "headline": "A father went to the ER after checking his heart with a smartwatch", "metric": "open-heart surgery followed ten days later", "comparator": { "against": "no watch ECG reading (Joseph's and his doctors' counterfactual)", "before": "He probably would have had a stroke, heart attack, or both", "after": "He says an ER doctor reviewed the tracing and confirmed that he was in AFib.", "basis": "assumed", "quote": "When I asked Joseph whether he would have gone to the emergency room that day without the watch, he did not hesitate. \"Nope,\" he said.", "url": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/" }, "later": { "status": "unknown", "date": null, "note": "The original interview says that Holycross uses the watch to track walking during recovery. No separately reported later outcome is cited.", "quote": null, "url": null }, "value": null, "developer_country": "South Korea", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.foxnews.com/tech/smartwatch-afib-alert-sends-dad-er-before-heart-surgery", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Samsung_Electronics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Samsung Electronics.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the account to Kurt Knutsson's original CyberGuy interview, published on 1 October 2026. Replaced the two Fox excerpts with one original source and removed the BGR retelling from active evidence. Fox's 4 October republication and BGR's 6 October retelling add no independent case evidence. Preserved the couple's testimony and the absence of clinical verification. Excluded source URLs: https://www.foxnews.com/tech/smartwatch-afib-alert-sends-dad-er-before-heart-surgery; https://www.bgr.com/2279265/samsung-galaxy-watch-detects-afib-before-heart-surgery/.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Separated the Galaxy Watch4 Classic hardware from the Samsung Health Monitor ECG Monitor app. Cleared the unsupported AI model version and added Samsung's original instructions, whose compatibility table shows that the hardware alone cannot establish the installed app version.", "source": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' other. 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Preserved the reported benefit and material qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Separated the Galaxy Watch4 Classic hardware from the Samsung Health Monitor ECG Monitor app. Cleared the unsupported AI model version and added Samsung's original instructions, whose compatibility table shows that the hardware alone cannot establish the installed app version.", "source": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "date_observed", "revisions", "date_basis", "date_precision" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "A Galaxy Watch with the ECG feature enabled through Samsung Health Monitor on a paired Galaxy phone", "A symptomatic user prompted to record an ECG", "An ER able to confirm the rhythm on a 12-lead ECG" ], "must_hold": [ "The single-lead classifier returns AFib rather than inconclusive or poor recording", "The user acts on the result instead of dismissing it" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Accessibility among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://www.foxnews.com/tech/smartwatch-afib-alert-sends-dad-er-before-heart-surgery", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Samsung_Electronics", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Samsung Electronics.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the account to Kurt Knutsson's original CyberGuy interview, published on 1 October 2026. Replaced the two Fox excerpts with one original source and removed the BGR retelling from active evidence. Fox's 4 October republication and BGR's 6 October retelling add no independent case evidence. Preserved the couple's testimony and the absence of clinical verification. Excluded source URLs: https://www.foxnews.com/tech/smartwatch-afib-alert-sends-dad-er-before-heart-surgery; https://www.bgr.com/2279265/samsung-galaxy-watch-detects-afib-before-heart-surgery/.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Placed the beneficiary’s personal name in the subtitle and kept the display headline focused on the reported benefit.", "source": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Separated the Galaxy Watch4 Classic hardware from the Samsung Health Monitor ECG Monitor app. Cleared the unsupported AI model version and added Samsung's original instructions, whose compatibility table shows that the hardware alone cannot establish the installed app version.", "source": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the homepage subtitle for concise database prose, with courtesy titles for named beneficiaries and numbered clauses for the Coates drug-selection account. Preserved the reported evidence and material uncertainty.", "editor": "AIBD" } ] } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Healthcare (cardiology)", "segment": "Consumer wearables" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "sources": [ { "source_ref": "AIBD-0303-source-0002", "url": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "title": "Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use", "published_month": "2023-06", "document_revision": "4.0", "accessed_on": "2026-10-24", "locator": "p. 4, Getting started table", "qualification": "Document revision 4.0 is not the ECG app version; the table separately identifies ECG v1.1 and v1.2." } ] } }, "provenance": { "kind": "source_review", "basis": "Read Samsung's original U.S. instructions and distinguished the document revision from the app releases.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Samsung’s June 2023 instructions are available. Revision 4.0 identifies the document. The compatibility table on page 4 lists ECG app versions 1.1 and 1.2, without establishing which version Holycross used.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Knutsson K (2026). Smartwatch AFib alert sends dad to ER before heart surgery. CyberGuy, 1 October 2026.", "title": "Smartwatch AFib alert sends dad to ER before heart surgery", "url": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "date": "2026-10-01", "written_by": "independent", "quote": "It came up and told me immediately at the top in bold letters, atrial fibrillation" }, { "kind": "other", "citation": "Samsung Electronics. Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use. June 2023, document revision 4.0, pp. 2, 4–5. Page 4 distinguishes ECG app versions 1.1 and 1.2 from compatible Galaxy Watch4 hardware.", "title": "Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use", "url": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "role": "Active evidence sources in record order" }, "provenance": { "kind": "curatorial", "basis": "Preserved existing source identifiers and appended the material technical source where applicable.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "news report", "citation": "Knutsson K (2026). Smartwatch AFib alert sends dad to ER before heart surgery. CyberGuy, 1 October 2026.", "title": "Smartwatch AFib alert sends dad to ER before heart surgery", "url": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "date": "2026-10-01", "written_by": "independent", "quote": "It came up and told me immediately at the top in bold letters, atrial fibrillation" }, { "kind": "other", "citation": "Samsung Electronics. Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use. June 2023, document revision 4.0, pp. 2, 4–5. Page 4 distinguishes ECG app versions 1.1 and 1.2 from compatible Galaxy Watch4 hardware.", "title": "Samsung ECG Monitor App with Irregular Heart Rhythm Notification: US Instructions for Use", "url": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "written_by": "makers" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sources[].upstream_sources": { "state": "value_present", "value": { "kind": "structured", "data": { "origins": [ { "source_refs": [ "AIBD-0303-source-0001" ], "url": "https://cyberguy.com/future-tech/galaxy-watch-afib-alert-dad-heart-surgery/", "publisher": "CyberGuy", "author": "Kurt Knutsson", "published_on": "2026-10-01", "relationship": "Original interview with Joseph and Jamie Holycross. Their account is not clinical verification.", "display_name": "CyberGuy" }, { "source_refs": [ "AIBD-0303-source-0002" ], "url": "https://image-us.samsung.com/SamsungUS/home/apps/samsung-health-monitor/IFU_IHRN_US_202306.pdf", "publisher": "Samsung Electronics", "published_month": "2023-06", "relationship": "Original manufacturer instructions establish the app identity, recording mode, and multiple compatible software versions. They do not verify Holycross's health outcome or installed release.", "display_name": "Samsung Electronics", "locator": "pp. 2, 4–5; especially the Getting started table on p. 4" } ], "excluded_republications": [ { "url": "https://www.foxnews.com/tech/smartwatch-afib-alert-sends-dad-er-before-heart-surgery", "published_on": "2026-10-04", "relationship": "Same reporting republished by Fox; no additional case evidence." }, { "url": "https://www.bgr.com/2279265/samsung-galaxy-watch-detects-afib-before-heart-surgery/", "published_on": "2026-10-06", "relationship": "Retelling with no additional independently obtained case evidence." } ], "independent_reporting_origins": 1, "lead_source_ref": "AIBD-0303-source-0001", "retained_source_order": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "ordering_basis": "The first retained source is the original publication that supports the main reported benefit. Any additional retained source follows it and supplies the separate evidence described in its relationship.", "system_identity_review": { "reviewed_on": "2026-10-24", "finding": "The original interview establishes Galaxy Watch4 Classic. The original manufacturer instructions establish the Samsung Health Monitor ECG Monitor app, but neither identifies the installed software or classifier release.", "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "technical_locator": "Samsung instructions, p. 4, Getting started table" }, "excluded_technical_attributions": [ { "url": "https://www.youtube.com/watch?v=rU6KyIZ2RpY", "title": "Galaxy Watch6 | Watch6 Classic: How to monitor your heart rate & heart rhythm | Samsung", "published_on": "2023-09-12", "relationship": "Samsung's general tutorial embedded in the CyberGuy article; it is not a recording of Holycross's device and cannot identify his installed software." } ] } }, "provenance": { "kind": "source_review", "basis": "Read the original publications and distinguished original reporting from republication and retelling. Multiple excerpts or copies do not provide independent corroboration.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "CyberGuy interviewed Holycross and his wife. Samsung’s instructions explain the ECG app and compatible watches. Neither supplies a clinical record for Holycross or identifies his installed software release.", "editor_note": "" } }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Mr. Joseph Holycross reported that doctors confirmed the atrial fibrillation that Samsung Health Monitor detected on his Galaxy Watch4 Classic.", "account": "CyberGuy published Kurt Knutsson's interview with Joseph and Jamie Holycross on 1 October 2026. Joseph, 39, is a father of four. The event date and place are not given. He had attributed a racing heart to caffeine for one and a half to two years. His wife Jamie, a respiratory therapist, noticed that he was short of breath. She urged him to run the electrocardiogram (ECG) feature on his Samsung Galaxy Watch4 Classic. He says that the result read “atrial fibrillation” in bold. He repeated the recording several times, then went to the emergency room (ER), where a doctor reviewed the watch tracing and confirmed AFib. He stayed about a week in hospital. About ten days later he returned for open-heart surgery to repair “several things on my heart”. Asked whether he would have gone to the ER without the watch, he said “Nope”. The family says that doctors warned that he “probably would have had a stroke, heart attack, or both” and recommended screening for his siblings and children." } }, "provenance": { "kind": "curatorial", "basis": "Updated the displayed wording and revision history without changing the reviewed facts, sources, or assessments.", "record_fields": [ "summary", "account" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "value_present", "value": { "kind": "structured", "data": { "hardware": { "manufacturer": "Samsung Electronics", "model": "Galaxy Watch4 Classic", "source_ref": "AIBD-0303-source-0001", "locator": "His Galaxy Watch showed AFib" }, "software": { "product": "Samsung Health Monitor ECG Monitor app", "version_status": "not reported for this case" }, "operating_system": { "name": "Wear OS", "version_status": "not reported for this case" }, "classifier_version": { "status": "not reported for this case" }, "mode": "User-initiated 30-second ECG recording, prompted by his wife; the case does not establish an irregular-heart-rhythm notification.", "compatible_versions_in_documentation": [ { "ecg_app_version": "1.1", "hardware": "Galaxy Watch4 or later", "minimum_watch_os": "WearOS 3.5", "source_ref": "AIBD-0303-source-0002", "locator": "p. 4, Getting started table" }, { "ecg_app_version": "1.2", "hardware": "Galaxy Watch4 or later", "minimum_watch_os": "WearOS 4.0", "feature": "Irregular Heart Rhythm Notification", "source_ref": "AIBD-0303-source-0002", "locator": "p. 4, Getting started table" } ], "qualification": "Compatibility does not establish which app or operating-system release Holycross had installed. The instructions' v4.0 is a document revision." } }, "provenance": { "kind": "source_review", "basis": "Read the original interview and Samsung's instructions. Kept device, software, and document versions distinct.", "record_fields": [ "system", "model_version" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Samsung Health Monitor ran on a Galaxy Watch4 Classic. Holycross took an ECG after his wife noticed a possible problem.", "editor_note": "" } }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the case evidence and the relevant original technical documentation; no case-specific model identity or release was disclosed.", "record_fields": [], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "reason": "Samsung names its ECG Monitor app within Samsung Health Monitor. Neither the interview nor the instructions identify a separately named underlying classification model used in this case.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "Samsung’s ECG classifier for atrial fibrillation. Samsung does not give a separate model name.", "editor_note": "" } }, "systems[].model_version": { "state": "not_reported", "provenance": { "kind": "source_review", "basis": "Read the case evidence and the relevant original technical documentation; no case-specific model identity or release was disclosed.", "record_fields": [ "model_version" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "reason": "The original interview does not state the installed ECG app or classifier version. Samsung lists both ECG v1.1 and v1.2 as compatible with Galaxy Watch4 hardware, so Galaxy Watch4 Classic does not identify the software release.", "review_state": "reviewed", "coverage": "complete", "display": { "answer": "The interview does not identify the installed app or classifier release.", "editor_note": "" } }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Samsung Health Monitor ECG Monitor app" } }, "provenance": { "kind": "source_review", "basis": "Identified the reported product or pipeline from its original case and technical sources; kept hardware, underlying model, and software release distinct.", "record_fields": [ "system" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "systems[].provider": { "state": "value_present", "value": { "kind": "text", "text": "Samsung Electronics" }, "provenance": { "kind": "source_review", "basis": "Samsung Electronics identifies itself as the manufacturer of the ECG Monitor app in the original instructions.", "record_fields": [ "developer" ], "source_refs": [ "AIBD-0303-source-0001", "AIBD-0303-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "complete" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Galaxy Watch4 Classic ECG returns “atrial fibrillation” for Joseph Holycross, 39; ER confirms AFib, a week in hospital and open-heart surgery follow", "headline": "A father went to the ER after checking his heart with a smartwatch" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "ca726c54b3937fe2ad593b6030126fd50dd11c30308c8349e4cfd806f0752c2a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Recomputed the fingerprint after the homepage copy revision.", "record_fields": [ "summary", "revisions" ], "source_refs": [], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "CyberGuy published Kurt Knutsson's interview with Joseph and Jamie Holycross on 1 October 2026. Joseph, 39, is a father of four. The event date and place are not given. He had attributed a racing heart to caffeine for one and a half to two years. His wife Jamie, a respiratory therapist, noticed that he was short of breath. She urged him to run the electrocardiogram (ECG) feature on his Samsung Galaxy Watch4 Classic. He says that the result read “atrial fibrillation” in bold. He repeated the recording several times, then went to the emergency room (ER), where a doctor reviewed the watch tracing and confirmed AFib. He stayed about a week in hospital. About ten days later he returned for open-heart surgery to repair “several things on my heart”. Asked whether he would have gone to the ER without the watch, he said “Nope”. The family says that doctors warned that he “probably would have had a stroke, heart attack, or both” and recommended screening for his siblings and children.", "replication": { "produced_by": [ "A Galaxy Watch with the ECG feature enabled through Samsung Health Monitor on a paired Galaxy phone", "A symptomatic user prompted to record an ECG", "An ER able to confirm the rhythm on a 12-lead ECG" ], "must_hold": [ "The single-lead classifier returns AFib rather than inconclusive or poor recording", "The user acts on the result instead of dismissing it" ], "echoes": [] } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0303-source-0001" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 31, "reviewed": 17, "record_mapped": 16, "not_assessed": 58, "complete": false, "by_state": { "value_present": 31, "not_reported": 2, "unresolved": 0, "not_assessed": 58, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0359", "title": "VTTI/VDOT thermal-camera AI wildlife detection pilot on Route 460 near Grundy, Virginia: 97% detection accuracy and a 3 mph average speed drop at activated signs", "summary": "Drivers slowed by an average of 3 mph near warning signs linked to Crosstek’s AI in Virginia’s ADDWS pilot.", "date_observed": "2026-10-20", "date_basis": "source publication", "date_precision": "day", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Gwen Sheldon reported for Virginia Tech on 20 October 2026 on a one-year Virginia Tech Transportation Institute (VTTI) pilot that ended in September 2026. It ran on Route 460 near Grundy in Southwest Virginia, sponsored by the Virginia Department of Transportation (VDOT) as part of the Corridor Q expansion. Eight portable solar-powered trailers with thermal cameras were installed on a 750-meter section of a 14-mile corridor that is home to about 100 elk. AI software from Crosstek analyzed the camera feeds. When wildlife was detected, dynamic message signs told motorists that wildlife had been detected ahead and to slow down. T-Mobile provided 5G and satellite links. The system achieved 97 percent overall accuracy in identifying medium and large wildlife. The initial analysis found an average speed reduction of 3 mph as vehicles approached activated signs. The report gives detection accuracy and driver speeds but no result on collisions or fatalities prevented. WCYB had reported the test on 19 November 2025. Its separate interview with Michelle Earl of VDOT describes animal detection and communication with the message boards. The measured results come from VTTI's own report. WCYB's earlier interview establishes deployment context, not independent verification of those results. VDOT names the pilot the Animal Detection and Driver Warning System (ADDWS). Its project page identifies VTTI as the research partner. Virginia Tech’s results report identifies Crosstek as the camera and AI-software supplier.", "category": "protective response", "unexpected": false, "purpose": "Detect large wildlife near the roadway and warn approaching drivers in real time to reduce wildlife-vehicle collisions. The measured driver slowdown was the intended response.", "system": "Animal Detection and Driver Warning System (ADDWS), using Crosstek thermal-camera AI detection", "model_version": null, "developer": "Crosstek (cameras and detection software); system integration and evaluation by Virginia Tech Transportation Institute", "deployer": "Virginia Department of Transportation with Virginia Tech Transportation Institute", "location": "Route 460 (Corridor Q) near Grundy, Buchanan County, Virginia, USA", "domain": "Road safety and wildlife-vehicle collision prevention", "segment": "State transportation agency research pilot", "benefit_type": "Increased Product Safety", "taxonomy_note": "The documented effect is slower driving at warning signs; collisions avoided are not established.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual driver or crash outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "VDOT obtained a measured driver response (3 mph average slowdown) and 97 percent detection accuracy from a pilot, but no crash reduction." }, { "group": "societal", "depth": 1, "reason": "One 750-meter test section. The institutional report gives no result on collisions or fatalities prevented." } ], "ai_role": { "status": "assessed", "statement": "AI analysis of thermal camera feeds triggered the warning signs. Virginia Tech reports a 3 mph average slowdown as drivers approached activated signs, but it gives no result on collisions prevented. The results come from the evaluating institution's own report. WCYB's separate interview with VDOT describes deployment and adds no independent test of the measured results." }, "evidence": [ { "kind": "press release", "citation": "Sheldon, G. (2026). Elk crossing: Real-time driver warning system helps prevent animal collisions. Virginia Tech, 20 October 2026.", "title": "Elk crossing: Real-time driver warning system helps prevent animal collisions", "url": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "date": "2026-10-20", "written_by": "deployer", "quote": null }, { "kind": "news report", "citation": "Allen, S. (2025). VDOT tests elk-detection system to prevent collisions in Southwest Virginia. WCYB, 19 November 2025.", "title": "VDOT tests elk-detection system to prevent collisions in Southwest Virginia", "url": "https://wcyb.com/news/local/vdot-tests-elk-detection-system-to-prevent-collisions-in-southwest-virginia", "date": "2025-11-19", "written_by": "independent", "quote": "It identifies a large animal on the road — an elk, a bear, or even a large deer — it will communicate with our message boards." }, { "kind": "report", "citation": "Donaldson, Bridget M., Elizabeth M. Hillard, Jacalyn P. Rosenberger, and Renee Callahan. An Evaluation of Wildlife Crossing Design, Placement, Costs, and Funding Opportunities for Corridor Q. VTRC 24-R8. Virginia Transportation Research Council, September 2023, 20–21, 41–42, table 12 and footnotes a and c.", "title": "An Evaluation of Wildlife Crossing Design, Placement, Costs, and Funding Opportunities for Corridor Q", "url": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf", "date": null, "written_by": "deployer", "quote": null }, { "kind": "report", "citation": "Virginia Department of Transportation. “Corridor Q driver safety and maintaining habitat connectivity,” § “Current Research - Pilot Project.”", "title": "Corridor Q driver safety and maintaining habitat connectivity", "url": "https://www.vdot.virginia.gov/projects/bristol-district/corridor-q-driver-safety-and-maintaining-habitat-connectivity/", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Portable solar trailers with thermal cameras on a known elk corridor", "AI detection software linked to dynamic message signs", "5G and satellite connectivity", "State DOT sponsorship within a highway expansion project" ], "must_hold": [ "Detection accuracy high enough to keep driver trust in the signs", "Sign placement giving drivers time to slow", "Power and connectivity at remote sites", "Crash data collection to test the unproven safety effect" ], "echoes": [ { "date": "2026-02-09", "setting": "LAARMA AI roadside alerts in the Kuranda cassowary trial, Queensland (AIBD-0104): fatal-crash reduction reported", "model_version": null, "outcome": "recurred", "source": "AIBD-0104" }, { "date": "2026-07-18", "setting": "NSW Monaro Highway PAWS trial launched with the same detect-and-warn design; no results yet", "model_version": null, "outcome": "unknown", "source": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/" } ] }, "paired_incident": null, "headline": "Drivers slowed down when signs warned of wildlife ahead", "metric": "an average speed reduction of 3 mph as vehicles approached activated signs", "comparator": { "against": "comparison baseline not specified in the institutional report", "before": null, "after": "an average speed reduction of 3 mph as vehicles approached signs that had been activated by wildlife detections", "basis": "measured", "quote": "reducing their speeds by an average of 3 mph when approaching activated signs.", "url": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html" }, "later": { "status": "unknown", "date": null, "note": "The institutional report states that the pilot ended in September 2026 and that data analysis was continuing. No later result is cited.", "quote": null, "url": null }, "value": { "amount": "$80,771.49 per elk crash", "what": "Estimated comprehensive societal cost of an elk-vehicle crash in 2020 U.S. dollars, including economic loss and monetized pain and suffering. Context only: no AI-attributed savings or crashes prevented are established.", "who": "Road users and wider society", "estimate": true, "quote": "the calculated costs for an elk crash and a deer crash were $80,771.49 and $41,338.28, respectively.", "url": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf" }, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/; https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.crosstekco.com/contact-us; https://en.wikipedia.org/wiki/Virginia_Department_of_Transportation", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced three excerpts from the Bioengineer.org reproduction with Virginia Tech's original 20 October 2026 report by Gwen Sheldon. The reproduction adds no original reporting. Retained Samantha Allen's 19 November 2025 WCYB interview with VDOT for separate deployment evidence, not corroboration of the measured results. The original report gives no collision-prevention result or explicit comparison baseline. Removed the reproduced limitation wording as a quotation and retained that evidentiary limit in the account. Excluded reproduction: https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the elk-crash cost through the 2026 Virginia Tech article and its cited 2024 feasibility study to Donaldson et al. (2023), pages 41–42, table 12. Replaced the rounded amount with $80,771.49 per elk crash. The estimate includes economic costs and monetized pain and suffering, so it is contextual societal valuation rather than an AI saving or cash loss. Recorded the input references, California severity assumption, and unresolved price year.", "source": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Recovered the cited VDOT crash-cost memorandum in a preserved copy. Its tables 1–2 and page 3 establish the 2020 price basis. The elk estimate reproduces as 0.862 × $13,743 + 0.136 × $308,895 + 0.002 × $13,457,654 = $80,771.494, rounded to $80,771.49. This is a contextual societal valuation, not an AI saving.", "source": "https://loudouncoalition.org/wp-content/uploads/2022/06/37-VDOT-Crash-Costs-Memo_acc050222-1.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.vdot.virginia.gov/projects/bristol-district/corridor-q-driver-safety-and-maintaining-habitat-connectivity/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report, two reports from the deployer and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0359", "catalog_version": "1.0.0", "source_fingerprint": "1b5658b0b4e4d534db95642c8c0b4ab3bec761d8b7e2156861af3d0ec07dffbe", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "adyt", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "value_present", "value": { "kind": "text", "text": "An existing source-stated monetary observation is present in the original value object." }, "provenance": { "kind": "legacy_record", "basis": "Existing value object only; its financial interpretation has not been reverified.", "record_fields": [ "value" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial", "record_ids": [ "AIBD-0359-legacy-value" ] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Crosstek (cameras and detection software); system integration and evaluation by Virginia Tech Transportation Institute", "deployer": "Virginia Department of Transportation with Virginia Tech Transportation Institute" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "AI analysis of thermal camera feeds triggered the warning signs. Virginia Tech reports a 3 mph average slowdown as drivers approached activated signs, but it gives no result on collisions prevented. The results come from the evaluating institution's own report. WCYB's separate interview with VDOT describes deployment and adds no independent test of the measured results." } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "ai_role" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "AI detected animals in thermal images and activated roadside warning signs. Virginia Tech reports that approaching drivers slowed by an average of 3 mph. It reports no measured reduction in collisions.", "editor_note": "" } }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "protective response", "ai_role": { "status": "assessed", "statement": "AI analysis of thermal camera feeds triggered the warning signs. Virginia Tech reports a 3 mph average slowdown as drivers approached activated signs, but it gives no result on collisions prevented. The results come from the evaluating institution's own report. WCYB's separate interview with VDOT describes deployment and adds no independent test of the measured results." } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "category", "ai_role" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual driver or crash outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "VDOT obtained a measured driver response (3 mph average slowdown) and 97 percent detection accuracy from a pilot, but no crash reduction." }, { "group": "societal", "depth": 1, "reason": "One 750-meter test section. The institutional report gives no result on collisions or fatalities prevented." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report, two reports from the deployer and the deployer's press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "The display category follows the existing rule. Source lineage and claim-specific limitations are stated here; a publication count is not a count of independent confirmations." } }, "provenance": { "kind": "source_review", "basis": "Recomputed the existing display rule after adding the reviewed sources. Source independence remains claim-specific.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual driver or crash outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "VDOT obtained a measured driver response (3 mph average slowdown) and 97 percent detection accuracy from a pilot, but no crash reduction." }, { "group": "societal", "depth": 1, "reason": "One 750-meter test section. The institutional report gives no result on collisions or fatalities prevented." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual driver or crash outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "VDOT obtained a measured driver response (3 mph average slowdown) and 97 percent detection accuracy from a pilot, but no crash reduction." }, { "group": "societal", "depth": 1, "reason": "One 750-meter test section. The institutional report gives no result on collisions or fatalities prevented." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$80,771.49 per elk crash", "what": "Estimated comprehensive societal cost of an elk-vehicle crash in 2020 U.S. dollars, including economic loss and monetized pain and suffering. Context only: no AI-attributed savings or crashes prevented are established.", "who": "Road users and wider society", "estimate": true, "quote": "the calculated costs for an elk crash and a deer crash were $80,771.49 and $41,338.28, respectively.", "url": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf" } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source or monetary context after tracing the cited cost estimate to the original analysis, its table and footnotes. Other mapped content and review states remain unchanged.", "record_fields": [ "value" ], "source_refs": [ "AIBD-0359-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].measure_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$80,771.49 per elk crash", "what": "Estimated comprehensive societal cost of an elk-vehicle crash in 2020 U.S. dollars, including economic loss and monetized pain and suffering. Context only: no AI-attributed savings or crashes prevented are established.", "who": "Road users and wider society", "estimate": true, "quote": "the calculated costs for an elk crash and a deer crash were $80,771.49 and $41,338.28, respectively.", "url": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf" } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source or monetary context after tracing the cited cost estimate to the original analysis, its table and footnotes. Other mapped content and review states remain unchanged.", "record_fields": [ "value" ], "source_refs": [ "AIBD-0359-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].recipient_payer": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "value": { "amount": "$80,771.49 per elk crash", "what": "Estimated comprehensive societal cost of an elk-vehicle crash in 2020 U.S. dollars, including economic loss and monetized pain and suffering. Context only: no AI-attributed savings or crashes prevented are established.", "who": "Road users and wider society", "estimate": true, "quote": "the calculated costs for an elk crash and a deer crash were $80,771.49 and $41,338.28, respectively.", "url": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf" } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source or monetary context after tracing the cited cost estimate to the original analysis, its table and footnotes. Other mapped content and review states remain unchanged.", "record_fields": [ "value" ], "source_refs": [ "AIBD-0359-source-0003" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].measurement_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].metric": { "state": "not_assessed", "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "metric" ], "source_refs": [] }, "review_state": "not_assessed", "coverage": "partial", "family": "evaluations", "display": { "answer": "an average speed reduction of 3 mph as vehicles approached activated signs", "editor_note": "" } }, "evaluations[].reproduction_materials": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].setting_sample": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].uncertainty_limitations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "external_references[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "follow_up[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "later": { "status": "unknown", "note": "The institutional report states that the pilot ended in September 2026 and that data analysis was continuing. No later result is cited." } } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "later" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0359" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Increased Product Safety", "taxonomy_note": "The documented effect is slower driving at warning signs; collisions avoided are not established." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Gwen Sheldon reported for Virginia Tech on 20 October 2026 on a one-year Virginia Tech Transportation Institute (VTTI) pilot that ended in September 2026. It ran on Route 460 near Grundy in Southwest Virginia, sponsored by the Virginia Department of Transportation (VDOT) as part of the Corridor Q expansion. Eight portable solar-powered trailers with thermal cameras were installed on a 750-meter section of a 14-mile corridor that is home to about 100 elk. AI software from Crosstek analyzed the camera feeds. When wildlife was detected, dynamic message signs told motorists that wildlife had been detected ahead and to slow down. T-Mobile provided 5G and satellite links. The system achieved 97 percent overall accuracy in identifying medium and large wildlife. The initial analysis found an average speed reduction of 3 mph as vehicles approached activated signs. The report gives detection accuracy and driver speeds but no result on collisions or fatalities prevented. WCYB had reported the test on 19 November 2025. Its separate interview with Michelle Earl of VDOT describes animal detection and communication with the message boards. The measured results come from VTTI's own report. WCYB's earlier interview establishes deployment context, not independent verification of those results. VDOT names the pilot the Animal Detection and Driver Warning System (ADDWS). Its project page identifies VTTI as the research partner. Virginia Tech’s results report identifies Crosstek as the camera and AI-software supplier.", "benefit_type": "Increased Product Safety" } }, "provenance": { "kind": "source_review", "basis": "Updated the fields affected by the system-identification review. Existing benefit-depth ratings and unrelated assessments are preserved.", "record_fields": [ "account", "benefit_type" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Drivers slowed by an average of 3 mph as they approached activated warning signs.", "editor_note": "" } }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual driver or crash outcome is documented." }, { "group": "organizational", "depth": 1, "reason": "VDOT obtained a measured driver response (3 mph average slowdown) and 97 percent detection accuracy from a pilot, but no crash reduction." }, { "group": "societal", "depth": 1, "reason": "One 750-meter test section. The institutional report gives no result on collisions or fatalities prevented." } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the affected source references, dates, or account after reading the original sources. Other mapped content and its review status remain unchanged.", "record_fields": [ "ratings" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002" ], "reviewed_on": "2026-10-24" }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Detect large wildlife near the roadway and warn approaching drivers in real time to reduce wildlife-vehicle collisions. The measured driver slowdown was the intended response." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Route 460 (Corridor Q) near Grundy, Buchanan County, Virginia, USA", "developer_country": "United States", "deployer_country": "United States" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Detect large wildlife near the roadway and warn approaching drivers in real time to reduce wildlife-vehicle collisions. The measured driver slowdown was the intended response." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-10-20", "date_basis": "source publication", "date_precision": "day", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/; https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.crosstekco.com/contact-us; https://en.wikipedia.org/wiki/Virginia_Department_of_Transportation", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced three excerpts from the Bioengineer.org reproduction with Virginia Tech's original 20 October 2026 report by Gwen Sheldon. The reproduction adds no original reporting. Retained Samantha Allen's 19 November 2025 WCYB interview with VDOT for separate deployment evidence, not corroboration of the measured results. The original report gives no collision-prevention result or explicit comparison baseline. Removed the reproduced limitation wording as a quotation and retained that evidentiary limit in the account. Excluded reproduction: https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the elk-crash cost through the 2026 Virginia Tech article and its cited 2024 feasibility study to Donaldson et al. (2023), pages 41–42, table 12. Replaced the rounded amount with $80,771.49 per elk crash. The estimate includes economic costs and monetized pain and suffering, so it is contextual societal valuation rather than an AI saving or cash loss. Recorded the input references, California severity assumption, and unresolved price year.", "source": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Recovered the cited VDOT crash-cost memorandum in a preserved copy. Its tables 1–2 and page 3 establish the 2020 price basis. The elk estimate reproduces as 0.862 × $13,743 + 0.136 × $308,895 + 0.002 × $13,457,654 = $80,771.494, rounded to $80,771.49. This is a contextual societal valuation, not an AI saving.", "source": "https://loudouncoalition.org/wp-content/uploads/2022/06/37-VDOT-Crash-Costs-Memo_acc050222-1.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.vdot.virginia.gov/projects/bristol-district/corridor-q-driver-safety-and-maintaining-habitat-connectivity/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "date_observed", "revisions", "date_basis", "date_precision" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Portable solar trailers with thermal cameras on a known elk corridor", "AI detection software linked to dynamic message signs", "5G and satellite connectivity", "State DOT sponsorship within a highway expansion project" ], "must_hold": [ "Detection accuracy high enough to keep driver trust in the signs", "Sign placement giving drivers time to slow", "Power and connectivity at remote sites", "Crash data collection to test the unproven safety effect" ], "echoes": [ { "date": "2026-02-09", "setting": "LAARMA AI roadside alerts in the Kuranda cassowary trial, Queensland (AIBD-0104): fatal-crash reduction reported", "outcome": "recurred", "source": "AIBD-0104" }, { "date": "2026-07-18", "setting": "NSW Monaro Highway PAWS trial launched with the same detect-and-warn design; no results yet", "outcome": "unknown", "source": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Portable solar trailers with thermal cameras on a known elk corridor", "AI detection software linked to dynamic message signs", "5G and satellite connectivity", "State DOT sponsorship within a highway expansion project" ], "must_hold": [ "Detection accuracy high enough to keep driver trust in the signs", "Sign placement giving drivers time to slow", "Power and connectivity at remote sites", "Crash data collection to test the unproven safety effect" ], "echoes": [ { "date": "2026-02-09", "setting": "LAARMA AI roadside alerts in the Kuranda cassowary trial, Queensland (AIBD-0104): fatal-crash reduction reported", "outcome": "recurred", "source": "AIBD-0104" }, { "date": "2026-07-18", "setting": "NSW Monaro Highway PAWS trial launched with the same detect-and-warn design; no results yet", "outcome": "unknown", "source": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against, the value as stated from the cited sources.", "source": "https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/; https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Increased Product Safety under Trustible's full taxonomy of 23 types; it was Improved Environmental Sustainability among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.crosstekco.com/contact-us; https://en.wikipedia.org/wiki/Virginia_Department_of_Transportation", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Replaced three excerpts from the Bioengineer.org reproduction with Virginia Tech's original 20 October 2026 report by Gwen Sheldon. The reproduction adds no original reporting. Retained Samantha Allen's 19 November 2025 WCYB interview with VDOT for separate deployment evidence, not corroboration of the measured results. The original report gives no collision-prevention result or explicit comparison baseline. Removed the reproduced limitation wording as a quotation and retained that evidentiary limit in the account. Excluded reproduction: https://bioengineer.org/virginia-pilot-links-wildlife-alerts-to-3-mph-speed-reduction/", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the elk-crash cost through the 2026 Virginia Tech article and its cited 2024 feasibility study to Donaldson et al. (2023), pages 41–42, table 12. Replaced the rounded amount with $80,771.49 per elk crash. The estimate includes economic costs and monetized pain and suffering, so it is contextual societal valuation rather than an AI saving or cash loss. Recorded the input references, California severity assumption, and unresolved price year.", "source": "https://www.vdot.virginia.gov/media/vdotvirginiagov/projects/bristol/corridor-q-driver-safety-and-maintaining-habitat/VTRC-Evaluation-of-Wildlife-Crossing-Design-for-Corridor-Q-Final-Report_acc09032025_PM.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Recovered the cited VDOT crash-cost memorandum in a preserved copy. Its tables 1–2 and page 3 establish the 2020 price basis. The elk estimate reproduces as 0.862 × $13,743 + 0.136 × $308,895 + 0.002 × $13,457,654 = $80,771.494, rounded to $80,771.49. This is a contextual societal valuation, not an AI saving.", "source": "https://loudouncoalition.org/wp-content/uploads/2022/06/37-VDOT-Crash-Costs-Memo_acc050222-1.pdf", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Rewrote the short title and summary in plain language, preserving the reported benefit and material limits. Added the named publication or institution to the reviewed lead source for homepage display.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Identified the AI system or feature in the supporting summary, or stated that the source does not name the software. Preserved the reported benefit and material qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Traced the system identity beyond the original case report. Added product names and supporting original sources, preserving historical-version limits and any inference in the source notes.", "source": "https://www.vdot.virginia.gov/projects/bristol-district/corridor-q-driver-safety-and-maintaining-habitat-connectivity/", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Shortened the homepage supporting statement to one sentence naming the system and its contribution; retained detailed outcomes and qualifications in the case account and source notes.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Revised the title and subtitle for natural phrasing, with named researchers, shorter dependencies, and less compressed terminology; preserved the system identities and evidence qualifications.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" }, { "date": "2026-10-24", "change": "Assessed model identity, provider, and deployment configuration from the original case sources. Distinguished the named product and known hardware roles from the unreported model and release.", "source": "https://news.vt.edu/articles/2026/10/vtti-elk-live-driver-warning-detection-virginia.html", "editor": "AIBD" } ] } }, "provenance": { "kind": "source_review", "basis": "Updated the mapped values after reviewing system identity and distinguishing product, hardware, and model versions.", "record_fields": [ "revisions" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Road safety and wildlife-vehicle collision prevention", "segment": "State transportation agency research pilot" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "value_present", "value": { "kind": "structured", "data": { "reviewed_on": "2026-10-24", "versions_and_access": [ { "source_url": "https://www.vdot.virginia.gov/projects/bristol-district/corridor-q-driver-safety-and-maintaining-habitat-connectivity/", "status": "Original source inspected.", "locator": "Current Research - Pilot Project.", "reviewed_on": "2026-10-24" } ], "limitations": [ "This access review covers the newly added source. Earlier source-access details remain in the source lineage." ] } }, "provenance": { "kind": "source_review", "basis": "Inspected the added originals and retained prior access limitations for other sources.", "record_fields": [ "evidence" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Virginia Tech reports its own pilot results. WCYB’s interview with VDOT describes the deployment but provides no separate test of the measured slowdown.", "editor_note": "" } }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Sheldon, G. (2026). Elk crossing: Real-time driver warning system helps prevent animal collisions. 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It ran on Route 460 near Grundy in Southwest Virginia, sponsored by the Virginia Department of Transportation (VDOT) as part of the Corridor Q expansion. Eight portable solar-powered trailers with thermal cameras were installed on a 750-meter section of a 14-mile corridor that is home to about 100 elk. AI software from Crosstek analyzed the camera feeds. When wildlife was detected, dynamic message signs told motorists that wildlife had been detected ahead and to slow down. T-Mobile provided 5G and satellite links. The system achieved 97 percent overall accuracy in identifying medium and large wildlife. The initial analysis found an average speed reduction of 3 mph as vehicles approached activated signs. The report gives detection accuracy and driver speeds but no result on collisions or fatalities prevented. WCYB had reported the test on 19 November 2025. Its separate interview with Michelle Earl of VDOT describes animal detection and communication with the message boards. 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Virginia Tech’s results report identifies Crosstek as the camera and AI-software supplier.", "replication": { "produced_by": [ "Portable solar trailers with thermal cameras on a known elk corridor", "AI detection software linked to dynamic message signs", "5G and satellite connectivity", "State DOT sponsorship within a highway expansion project" ], "must_hold": [ "Detection accuracy high enough to keep driver trust in the signs", "Sign placement giving drivers time to slow", "Power and connectivity at remote sites", "Crash data collection to test the unproven safety effect" ], "echoes": [ { "date": "2026-02-09", "setting": "LAARMA AI roadside alerts in the Kuranda cassowary trial, Queensland (AIBD-0104): fatal-crash reduction reported", "outcome": "recurred", "source": "AIBD-0104" }, { "date": "2026-07-18", "setting": "NSW Monaro Highway PAWS trial launched with the same detect-and-warn design; no results yet", "outcome": "unknown", "source": "https://aboutregional.com.au/ai-cameras-to-be-extra-set-of-eyes-on-roadside-wildlife-in-monaro-highway-trial/510964/" } ] } } }, "provenance": { "kind": "source_review", "basis": "Updated the fields affected by the system-identification review. Existing benefit-depth ratings and unrelated assessments are preserved.", "record_fields": [ "account", "replication" ], "source_refs": [ "AIBD-0359-source-0001", "AIBD-0359-source-0002", "AIBD-0359-source-0003", "AIBD-0359-source-0004" ], "reviewed_on": "2026-10-24" }, "review_state": "reviewed", "coverage": "partial", "display": { "answer": "Solar-powered trailers carried thermal cameras beside an elk corridor. Crosstek’s software detected animals and activated warning signs. VDOT and Virginia Tech monitored the pilot through 5G and satellite connections.", "editor_note": "" } } }, "summary": { "total": 91, "addressed": 91, "known": 35, "reviewed": 19, "record_mapped": 18, "not_assessed": 54, "complete": false, "by_state": { "value_present": 35, "not_reported": 2, "unresolved": 0, "not_assessed": 54, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0361", "title": "AIMS's ReefScan and ReefCloud apply machine learning to coral reef imagery for automated classification and monitoring; no AI-driven management action documented", "summary": "AIMS states ReefScan uses machine learning for real-time object classification and ReefCloud automates benthic image analysis; no reef management decision attributed to the AI was found.", "date_observed": "2026-10-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "The Australian Institute of Marine Science (AIMS) describes ReefScan as a modular suite of automated marine monitoring systems. It integrates machine learning, imaging sensors and robotics and “uses machine learning for real-time object identification and classification, freeing human effort from routine tasks”. AIMS describes ReefCloud as a platform on which users upload survey images, apply automated benthic analysis and generate consistent outputs. It “reduces manual processing time” and lets teams focus on interpretation and management actions. The ReefCloud.ai site claims accelerated image processing with AI giving results “that would take weeks in hours, with up to 90% accuracy”. AIMS lists a 2022 Asia-Pacific Spatial Excellence Award and a Fast Company honorable mention in the AI and Data category. It lists in-kind support from Accenture and the Allen Coral Atlas. No cited study links AI detection of crown-of-thorns starfish to a Reef Authority control action. AIMS's crown-of-thorns pages describe eDNA detection and chemical-cue control research, not AI. Only the maker's own pages are among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Automate classification of reef imagery so that monitoring programs report faster and at larger scale. The claimed benefit is the intended one.", "system": "AIMS ReefScan (machine-learning object identification on imaging and robotic platforms) and ReefCloud (automated benthic image analysis platform)", "model_version": null, "developer": "Australian Institute of Marine Science, with in-kind support from Accenture and the Allen Coral Atlas (ReefCloud)", "deployer": "AIMS and reef monitoring programs, research institutions and conservation partners using ReefCloud", "location": "Great Barrier Reef and other reefs, Australia; ReefCloud users worldwide", "domain": "Coral reef monitoring", "segment": "Government marine research agency", "benefit_type": "Repetitive Task Automation", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome." }, { "group": "organizational", "depth": null, "reason": "Time savings are asserted by AIMS without a quantified case." }, { "group": "societal", "depth": null, "reason": "No reef management action or ecological outcome attributed to the AI." } ], "ai_role": { "status": "unassessed", "statement": "AIMS's pages state that machine learning performs the image classification in ReefScan and the automated benthic analysis in ReefCloud. That is the claimed source of efficiency. No independent evaluation, named monitoring result or management decision attributable to these systems is among the sources, and only the maker's own account is cited." }, "evidence": [ { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefScan. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefScan", "url": "https://www.aims.gov.au/research/technology/reefscan", "date": null, "written_by": "makers", "quote": "ReefScan™ uses machine learning for real-time object identification and classification, freeing human effort from routine tasks and providing more time for knowledge building and decision support." }, { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefCloud. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefCloud", "url": "https://www.aims.gov.au/research/technology/reefcloud", "date": null, "written_by": "makers", "quote": "This reduces manual processing time and enables teams to focus on interpretation, decision‑making, and management actions rather than data handling." }, { "kind": "press release", "citation": "ReefCloud.ai (2026). Protecting the future of coral reefs. reefcloud.ai, fetched 20 Oct 2026.", "title": "ReefCloud.ai — Protecting the Future of Coral Reefs", "url": "https://reefcloud.ai/", "date": null, "written_by": "makers", "quote": "Accelerated image processing with advanced AI. Get results that would take weeks in hours, with up to 90% accuracy." } ], "replication": { "produced_by": [ "Large volumes of standardized reef survey imagery", "Machine-learning classifiers for benthic cover and objects", "Cloud platform shared by multiple monitoring programs", "Institutional partners (Accenture, Allen Coral Atlas)" ], "must_hold": [ "Classifier accuracy across reef types and image methods", "Continued uploads from monitoring programs", "Validation against expert annotation", "Links from outputs to management decisions, not yet documented" ], "echoes": [] }, "paired_incident": null, "headline": "AIMS's ReefScan and ReefCloud automate reef image analysis", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later outcome is established as of 20 October 2026.", "quote": null, "url": null }, "value": null, "developer_country": "Australia", "deployer_country": "Australia", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Repetitive Task Automation under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science; https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: three press releases from the makers. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0361", "catalog_version": "1.0.0", "source_fingerprint": "101f3b4438f7f120c379995fca777b773003cbad16eccbc1f1fc8c562220211a", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0361-source-0001", "AIBD-0361-source-0002", "AIBD-0361-source-0003" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Australian Institute of Marine Science, with in-kind support from Accenture and the Allen Coral Atlas (ReefCloud)", "deployer": "AIMS and reef monitoring programs, research institutions and conservation partners using ReefCloud" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "AIMS's pages state that machine learning performs the image classification in ReefScan and the automated benthic analysis in ReefCloud. 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No independent evaluation, named monitoring result or management decision attributable to these systems is among the sources, and only the maker's own account is cited." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The makers' claim", "basis": "Sources: three press releases from the makers. 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"family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].effect": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].exposure": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": 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later outcome is established as of 20 October 2026." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0361" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Repetitive Task Automation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Australian Institute of Marine Science (AIMS) describes ReefScan as a modular suite of automated marine monitoring systems. It integrates machine learning, imaging sensors and robotics and “uses machine learning for real-time object identification and classification, freeing human effort from routine tasks”. AIMS describes ReefCloud as a platform on which users upload survey images, apply automated benthic analysis and generate consistent outputs. It “reduces manual processing time” and lets teams focus on interpretation and management actions. The ReefCloud.ai site claims accelerated image processing with AI giving results “that would take weeks in hours, with up to 90% accuracy”. AIMS lists a 2022 Asia-Pacific Spatial Excellence Award and a Fast Company honorable mention in the AI and Data category. It lists in-kind support from Accenture and the Allen Coral Atlas. No cited study links AI detection of crown-of-thorns starfish to a Reef Authority control action. AIMS's crown-of-thorns pages describe eDNA detection and chemical-cue control research, not AI. Only the maker's own pages are among the sources.", "benefit_type": "Repetitive Task Automation" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual outcome." }, { "group": "organizational", "reason": "Time savings are asserted by AIMS without a quantified case." }, { "group": "societal", "reason": "No reef management action or ecological outcome attributed to the AI." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].status": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].tradeoffs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].unexpected": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "unexpected": false, "purpose": "Automate classification of reef imagery so that monitoring programs report faster and at larger scale. The claimed benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "unexpected", "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "places[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "location": "Great Barrier Reef and other reefs, Australia; ReefCloud users worldwide", "developer_country": "Australia", "deployer_country": "Australia" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "location", "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Automate classification of reef imagery so that monitoring programs report faster and at larger scale. The claimed benefit is the intended one." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "purpose" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "record_dates": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "date_observed": "2026-10-20", "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Repetitive Task Automation under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science; https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "replication.conditions": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Large volumes of standardized reef survey imagery", "Machine-learning classifiers for benthic cover and objects", "Cloud platform shared by multiple monitoring programs", "Institutional partners (Accenture, Allen Coral Atlas)" ], "must_hold": [ "Classifier accuracy across reef types and image methods", "Continued uploads from monitoring programs", "Validation against expert annotation", "Links from outputs to management decisions, not yet documented" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "revision_history[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Repetitive Task Automation under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science; https://en.wikipedia.org/wiki/Australian_Institute_of_Marine_Science", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sector": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "domain": "Coral reef monitoring", "segment": "Government marine research agency" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "domain", "segment" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].access_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].citation_locator": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefScan. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefScan", "url": "https://www.aims.gov.au/research/technology/reefscan", "written_by": "makers", "quote": "ReefScan™ uses machine learning for real-time object identification and classification, freeing human effort from routine tasks and providing more time for knowledge building and decision support." }, { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefCloud. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefCloud", "url": "https://www.aims.gov.au/research/technology/reefcloud", "written_by": "makers", "quote": "This reduces manual processing time and enables teams to focus on interpretation, decision‑making, and management actions rather than data handling." }, { "kind": "press release", "citation": "ReefCloud.ai (2026). Protecting the future of coral reefs. reefcloud.ai, fetched 20 Oct 2026.", "title": "ReefCloud.ai — Protecting the Future of Coral Reefs", "url": "https://reefcloud.ai/", "written_by": "makers", "quote": "Accelerated image processing with advanced AI. Get results that would take weeks in hours, with up to 90% accuracy." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0361-source-0001", "AIBD-0361-source-0002", "AIBD-0361-source-0003" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefScan. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefScan", "url": "https://www.aims.gov.au/research/technology/reefscan", "written_by": "makers", "quote": "ReefScan™ uses machine learning for real-time object identification and classification, freeing human effort from routine tasks and providing more time for knowledge building and decision support." }, { "kind": "press release", "citation": "Australian Institute of Marine Science (n.d.). ReefCloud. aims.gov.au, fetched 20 Oct 2026.", "title": "ReefCloud", "url": "https://www.aims.gov.au/research/technology/reefcloud", "written_by": "makers", "quote": "This reduces manual processing time and enables teams to focus on interpretation, decision‑making, and management actions rather than data handling." }, { "kind": "press release", "citation": "ReefCloud.ai (2026). Protecting the future of coral reefs. reefcloud.ai, fetched 20 Oct 2026.", "title": "ReefCloud.ai — Protecting the Future of Coral Reefs", "url": "https://reefcloud.ai/", "written_by": "makers", "quote": "Accelerated image processing with advanced AI. Get results that would take weeks in hours, with up to 90% accuracy." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "AIMS states ReefScan uses machine learning for real-time object classification and ReefCloud automates benthic image analysis; no reef management decision attributed to the AI was found.", "account": "The Australian Institute of Marine Science (AIMS) describes ReefScan as a modular suite of automated marine monitoring systems. It integrates machine learning, imaging sensors and robotics and “uses machine learning for real-time object identification and classification, freeing human effort from routine tasks”. AIMS describes ReefCloud as a platform on which users upload survey images, apply automated benthic analysis and generate consistent outputs. It “reduces manual processing time” and lets teams focus on interpretation and management actions. The ReefCloud.ai site claims accelerated image processing with AI giving results “that would take weeks in hours, with up to 90% accuracy”. AIMS lists a 2022 Asia-Pacific Spatial Excellence Award and a Fast Company honorable mention in the AI and Data category. It lists in-kind support from Accenture and the Allen Coral Atlas. No cited study links AI detection of crown-of-thorns starfish to a Reef Authority control action. AIMS's crown-of-thorns pages describe eDNA detection and chemical-cue control research, not AI. Only the maker's own pages are among the sources." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "AIMS ReefScan (machine-learning object identification on imaging and robotic platforms) and ReefCloud (automated benthic image analysis platform)" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Australian Institute of Marine Science, with in-kind support from Accenture and the Allen Coral Atlas (ReefCloud)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "AIMS's ReefScan and ReefCloud apply machine learning to coral reef imagery for automated classification and monitoring; no AI-driven management action documented", "headline": "AIMS's ReefScan and ReefCloud automate reef image analysis" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "101f3b4438f7f120c379995fca777b773003cbad16eccbc1f1fc8c562220211a" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "The Australian Institute of Marine Science (AIMS) describes ReefScan as a modular suite of automated marine monitoring systems. It integrates machine learning, imaging sensors and robotics and “uses machine learning for real-time object identification and classification, freeing human effort from routine tasks”. AIMS describes ReefCloud as a platform on which users upload survey images, apply automated benthic analysis and generate consistent outputs. It “reduces manual processing time” and lets teams focus on interpretation and management actions. The ReefCloud.ai site claims accelerated image processing with AI giving results “that would take weeks in hours, with up to 90% accuracy”. AIMS lists a 2022 Asia-Pacific Spatial Excellence Award and a Fast Company honorable mention in the AI and Data category. It lists in-kind support from Accenture and the Allen Coral Atlas. No cited study links AI detection of crown-of-thorns starfish to a Reef Authority control action. AIMS's crown-of-thorns pages describe eDNA detection and chemical-cue control research, not AI. Only the maker's own pages are among the sources.", "replication": { "produced_by": [ "Large volumes of standardized reef survey imagery", "Machine-learning classifiers for benthic cover and objects", "Cloud platform shared by multiple monitoring programs", "Institutional partners (Accenture, Allen Coral Atlas)" ], "must_hold": [ "Classifier accuracy across reef types and image methods", "Continued uploads from monitoring programs", "Validation against expert annotation", "Links from outputs to management decisions, not yet documented" ], "echoes": [] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 26, "reviewed": 0, "record_mapped": 26, "not_assessed": 65, "complete": false, "by_state": { "value_present": 26, "not_reported": 0, "unresolved": 0, "not_assessed": 65, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0363", "title": "Whale Safe (Benioff Ocean Science Laboratory) combines buoy acoustic detection, sightings and habitat models into whale presence ratings and grades ship cooperation with 10-knot slowdowns", "summary": "Whale Safe rates whale presence from acoustic buoys, sightings and a habitat model and grades ship cooperation with California's voluntary 10-knot zones; no avoided strike is documented.", "date_observed": "2026-10-20", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Whale Safe is run by the Benioff Ocean Science Laboratory at UC Santa Barbara's Marine Science Institute. Its site describes it as a technology-based mapping and analysis tool. It displays whale and ship data for the Santa Barbara Channel and the San Francisco Bay region. Its methodology page cites Baumgartner et al. 2019. It says the acoustic buoy “uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water”. After that, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. Acoustic, sighting and Blue Whale Habitat Model streams are combined over a five-day window into a Whale Presence Rating. AIS data are used to compute each vessel's cooperation rate with NOAA's voluntary 10-knot recommendation, graded A+ to F. The homepage states that “Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales”. The operator score-card page on record lists 2026-season cooperation rates by shipping company with letter grades. Partners named on the about page include Woods Hole Oceanographic Institution, NOAA's Southwest Fisheries Science Center, The Marine Mammal Center and others. The buoy system's peer-reviewed description (Baumgartner et al. 2019, Methods in Ecology and Evolution) reports false detection rates of 0% to nearly 0%. It reports daily missed detection rates of 12% to 42% for a Massachusetts buoy. No cited source gives a dated ship slowdown, cooperation change or avoided strike attributable to Whale Safe detections.", "category": "general benefit", "unexpected": false, "purpose": "Provide near-real-time whale presence information and public cooperation grades so that ships slow in whale habitat; no attributable outcome is documented.", "system": "Whale Safe: moored acoustic buoy with onboard call detection and classification (Baumgartner et al. 2019 system) plus sightings and habitat model, with AIS-based ship cooperation grading", "model_version": null, "developer": "Benioff Ocean Science Laboratory, UC Santa Barbara (platform); Woods Hole Oceanographic Institution (buoy detection system)", "deployer": "Benioff Ocean Science Laboratory with The Marine Mammal Center (San Francisco) and NOAA partners", "location": "Santa Barbara Channel and San Francisco Bay region, California, USA", "domain": "Marine mammal protection from ship strikes", "segment": "University ocean science laboratory with federal and NGO partners", "benefit_type": "Improved Environmental Sustainability", "taxonomy_note": "No avoided strike is documented; whale conservation is read as “improved environment”.", "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "No individual outcome." }, { "group": "organizational", "depth": null, "reason": "Shipping companies' cooperation grades are published but no change attributable to Whale Safe is documented." }, { "group": "societal", "depth": null, "reason": "No avoided strike or population effect is documented." } ], "ai_role": { "status": "assessed", "statement": "The automated component is the buoy's onboard detection and classification of whale calls, the Baumgartner et al. 2019 system. Whale Safe's own methodology page says a human analyst then reviews it before it contributes to the Whale Presence Rating. Cooperation grades are computed from AIS data, not AI. Only the maker's pages and the developers' buoy paper are among the sources, and none records a dated outcome attributable to the detections." }, "evidence": [ { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe methodology. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe methodology", "url": "https://whalesafe.com/methodology/", "date": null, "written_by": "makers", "quote": "The acoustic buoy uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe methodology, analyst review.", "title": "Whale Safe methodology (analyst review)", "url": "https://whalesafe.com/methodology/", "date": null, "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe homepage. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe", "url": "https://whalesafe.com/", "date": null, "written_by": "makers", "quote": "Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales." }, { "kind": "other", "citation": "Benioff Ocean Science Laboratory (2026). Whale Safe operator score cards (2026 season). whalesafe.com, accessed 20 Oct 2026.", "title": "Whale Safe tool: operator score cards", "url": "https://whalesafe.com/whale-safe-tool/", "date": null, "written_by": "makers", "quote": null }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). About us. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe: about us", "url": "https://whalesafe.com/about-us/", "date": null, "written_by": "makers", "quote": null }, { "kind": "peer-reviewed study", "citation": "Baumgartner, M. F., Bonnell, J., Van Parijs, S. M., Corkeron, P. J., Hotchkin, C., Ball, K., et al. (2019). Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation. Methods in Ecology and Evolution, 16 Jul 2019. doi:10.1111/2041-210X.13244", "title": "Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation", "url": "https://doi.org/10.1111/2041-210X.13244", "date": "2019-07-16", "written_by": "makers", "quote": "The moored buoy has been used to reduce the risk of ship strikes for right whales in a U.S. Coast Guard gunnery range" } ], "replication": { "produced_by": [ "Moored acoustic buoy with onboard call detection and classification", "Human analyst review of detections", "Sightings and habitat-model data streams", "AIS vessel tracking and public cooperation grading", "NOAA voluntary speed reduction zones" ], "must_hold": [ "Buoy operation (both regional buoys were listed offline when the pages were consulted)", "Analyst capacity for review", "Shipping company attention to public grades", "Evaluation linking ratings to speed changes and strikes, not yet documented" ], "echoes": [ { "date": null, "setting": "Massachusetts buoy used to reduce ship-strike risk for right whales in a US Coast Guard gunnery range (Baumgartner et al. 2019)", "model_version": null, "outcome": "unknown", "source": "https://doi.org/10.1111/2041-210X.13244" } ] }, "paired_incident": null, "headline": "Whale Safe grades ship cooperation with 10-knot slowdowns", "metric": null, "comparator": null, "later": { "status": "unknown", "date": null, "note": "No later outcome is established as of 20 October 2026. The statewide zone expansion occurred earlier in the 2026 season.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara; https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The makers' claim", "claim_basis": "Sources: the makers' peer-reviewed study, three press releases from the makers and the makers' other. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0363", "catalog_version": "1.0.0", "source_fingerprint": "bef437f3e20ceec57cd481f5f750c5fdc9d98909d6ec24d523b1865c6e49fb67", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0363-source-0001", "AIBD-0363-source-0002", "AIBD-0363-source-0003", "AIBD-0363-source-0004", "AIBD-0363-source-0005", "AIBD-0363-source-0006" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Benioff Ocean Science Laboratory, UC Santa Barbara (platform); Woods Hole Oceanographic Institution (buoy detection system)", "deployer": "Benioff Ocean Science Laboratory with The Marine Mammal Center (San Francisco) and NOAA partners" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ai_role": { "status": "assessed", "statement": "The automated component is the buoy's onboard detection and classification of whale calls, the Baumgartner et al. 2019 system. 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Its site describes it as a technology-based mapping and analysis tool. It displays whale and ship data for the Santa Barbara Channel and the San Francisco Bay region. Its methodology page cites Baumgartner et al. 2019. It says the acoustic buoy “uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water”. After that, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. Acoustic, sighting and Blue Whale Habitat Model streams are combined over a five-day window into a Whale Presence Rating. AIS data are used to compute each vessel's cooperation rate with NOAA's voluntary 10-knot recommendation, graded A+ to F. The homepage states that “Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales”. The operator score-card page on record lists 2026-season cooperation rates by shipping company with letter grades. Partners named on the about page include Woods Hole Oceanographic Institution, NOAA's Southwest Fisheries Science Center, The Marine Mammal Center and others. The buoy system's peer-reviewed description (Baumgartner et al. 2019, Methods in Ecology and Evolution) reports false detection rates of 0% to nearly 0%. It reports daily missed detection rates of 12% to 42% for a Massachusetts buoy. No cited source gives a dated ship slowdown, cooperation change or avoided strike attributable to Whale Safe detections.", "benefit_type": "Improved Environmental Sustainability" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].distribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].duration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].id": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].stakeholder_group": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "reason": "No individual outcome." }, { "group": "organizational", "reason": "Shipping companies' cooperation grades are published but no change attributable to Whale Safe is documented." }, { "group": "societal", "reason": "No avoided strike or population effect is documented." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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https://en.wikipedia.org/wiki/University_of_California,_Santa_Barbara", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: account, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "editor": "AIBD" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "date_observed", "revisions" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "replication.attempts[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Moored acoustic buoy with onboard call detection and classification", "Human analyst review of detections", "Sightings and habitat-model data streams", "AIS vessel tracking and public cooperation grading", "NOAA voluntary speed reduction zones" ], "must_hold": [ "Buoy operation (both regional buoys were listed offline when the pages were consulted)", "Analyst capacity for review", "Shipping company attention to public grades", "Evaluation linking ratings to speed changes and strikes, not yet documented" ], "echoes": [ { "setting": "Massachusetts buoy used to reduce ship-strike risk for right whales in a US Coast Guard gunnery range (Baumgartner et al. 2019)", "outcome": "unknown", "source": "https://doi.org/10.1111/2041-210X.13244" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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Whale Safe methodology. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe methodology", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "The acoustic buoy uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe methodology, analyst review.", "title": "Whale Safe methodology (analyst review)", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe homepage. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe", "url": "https://whalesafe.com/", "written_by": "makers", "quote": "Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales." }, { "kind": "other", "citation": "Benioff Ocean Science Laboratory (2026). Whale Safe operator score cards (2026 season). whalesafe.com, accessed 20 Oct 2026.", "title": "Whale Safe tool: operator score cards", "url": "https://whalesafe.com/whale-safe-tool/", "written_by": "makers" }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). About us. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe: about us", "url": "https://whalesafe.com/about-us/", "written_by": "makers" }, { "kind": "peer-reviewed study", "citation": "Baumgartner, M. F., Bonnell, J., Van Parijs, S. M., Corkeron, P. J., Hotchkin, C., Ball, K., et al. (2019). Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation. Methods in Ecology and Evolution, 16 Jul 2019. doi:10.1111/2041-210X.13244", "title": "Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation", "url": "https://doi.org/10.1111/2041-210X.13244", "date": "2019-07-16", "written_by": "makers", "quote": "The moored buoy has been used to reduce the risk of ship strikes for right whales in a U.S. Coast Guard gunnery range" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].id": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "AIBD-0363-source-0001", "AIBD-0363-source-0002", "AIBD-0363-source-0003", "AIBD-0363-source-0004", "AIBD-0363-source-0005", "AIBD-0363-source-0006" ], "role": "Existing evidence items, in their original order" }, "provenance": { "kind": "curatorial", "basis": "Stable within the fingerprinted record version; no source content or source review has been added.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "sources[].language": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "sources[].relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "evidence": [ { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe methodology. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe methodology", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "The acoustic buoy uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe methodology, analyst review.", "title": "Whale Safe methodology (analyst review)", "url": "https://whalesafe.com/methodology/", "written_by": "makers", "quote": "An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected." }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). Whale Safe homepage. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe", "url": "https://whalesafe.com/", "written_by": "makers", "quote": "Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales." }, { "kind": "other", "citation": "Benioff Ocean Science Laboratory (2026). Whale Safe operator score cards (2026 season). whalesafe.com, accessed 20 Oct 2026.", "title": "Whale Safe tool: operator score cards", "url": "https://whalesafe.com/whale-safe-tool/", "written_by": "makers" }, { "kind": "press release", "citation": "Benioff Ocean Science Laboratory (n.d.). About us. whalesafe.com, fetched 20 Oct 2026.", "title": "Whale Safe: about us", "url": "https://whalesafe.com/about-us/", "written_by": "makers" }, { "kind": "peer-reviewed study", "citation": "Baumgartner, M. F., Bonnell, J., Van Parijs, S. M., Corkeron, P. J., Hotchkin, C., Ball, K., et al. (2019). Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation. Methods in Ecology and Evolution, 16 Jul 2019. doi:10.1111/2041-210X.13244", "title": "Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: System description and evaluation", "url": "https://doi.org/10.1111/2041-210X.13244", "date": "2019-07-16", "written_by": "makers", "quote": "The moored buoy has been used to reduce the risk of ship strikes for right whales in a U.S. Coast Guard gunnery range" } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "evidence" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "sources[].upstream_sources": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "strategic_assessments[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "strategic assessments" }, "summary": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "summary": "Whale Safe rates whale presence from acoustic buoys, sightings and a habitat model and grades ship cooperation with California's voluntary 10-knot zones; no avoided strike is documented.", "account": "Whale Safe is run by the Benioff Ocean Science Laboratory at UC Santa Barbara's Marine Science Institute. Its site describes it as a technology-based mapping and analysis tool. It displays whale and ship data for the Santa Barbara Channel and the San Francisco Bay region. Its methodology page cites Baumgartner et al. 2019. It says the acoustic buoy “uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water”. After that, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. Acoustic, sighting and Blue Whale Habitat Model streams are combined over a five-day window into a Whale Presence Rating. AIS data are used to compute each vessel's cooperation rate with NOAA's voluntary 10-knot recommendation, graded A+ to F. The homepage states that “Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales”. The operator score-card page on record lists 2026-season cooperation rates by shipping company with letter grades. Partners named on the about page include Woods Hole Oceanographic Institution, NOAA's Southwest Fisheries Science Center, The Marine Mammal Center and others. The buoy system's peer-reviewed description (Baumgartner et al. 2019, Methods in Ecology and Evolution) reports false detection rates of 0% to nearly 0%. It reports daily missed detection rates of 12% to 42% for a Massachusetts buoy. No cited source gives a dated ship slowdown, cooperation change or avoided strike attributable to Whale Safe detections." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "summary", "account" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].autonomy_permissions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].component_role": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].deployment_configuration": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].inputs_outputs": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_name": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].model_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "systems[].product_name": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "system": "Whale Safe: moored acoustic buoy with onboard call detection and classification (Baumgartner et al. 2019 system) plus sightings and habitat model, with AIS-based ship cooperation grading" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "system" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "systems[].provider": { "state": "value_present", "value": { "kind": "structured", "data": { "application_developer": "Benioff Ocean Science Laboratory, UC Santa Barbara (platform); Woods Hole Oceanographic Institution (buoy detection system)" } }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "developer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "taxonomy_crosswalks[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "title": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "title": "Whale Safe (Benioff Ocean Science Laboratory) combines buoy acoustic detection, sightings and habitat models into whale presence ratings and grades ship cooperation with 10-knot slowdowns", "headline": "Whale Safe grades ship cooperation with 10-knot slowdowns" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "title", "headline" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "version": { "state": "value_present", "value": { "kind": "identifiers", "identifiers": [ "bef437f3e20ceec57cd481f5f750c5fdc9d98909d6ec24d523b1865c6e49fb67" ], "role": "SHA-256 of normalized original case data" }, "provenance": { "kind": "curatorial", "basis": "Deterministic content version assigned by the local migration.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "complete" }, "workflow": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "Whale Safe is run by the Benioff Ocean Science Laboratory at UC Santa Barbara's Marine Science Institute. Its site describes it as a technology-based mapping and analysis tool. It displays whale and ship data for the Santa Barbara Channel and the San Francisco Bay region. Its methodology page cites Baumgartner et al. 2019. It says the acoustic buoy “uses a hydrophone (underwater microphone) and a tiny computer to detect and identify sounds in the water”. After that, “An analyst then reviews these data and indicates for each 15-minute period whether each of the monitored species was detected”. Acoustic, sighting and Blue Whale Habitat Model streams are combined over a five-day window into a Whale Presence Rating. AIS data are used to compute each vessel's cooperation rate with NOAA's voluntary 10-knot recommendation, graded A+ to F. The homepage states that “Research demonstrates ships that slow to 10 knots in areas with high whale presence significantly reduce the danger to whales”. The operator score-card page on record lists 2026-season cooperation rates by shipping company with letter grades. Partners named on the about page include Woods Hole Oceanographic Institution, NOAA's Southwest Fisheries Science Center, The Marine Mammal Center and others. The buoy system's peer-reviewed description (Baumgartner et al. 2019, Methods in Ecology and Evolution) reports false detection rates of 0% to nearly 0%. It reports daily missed detection rates of 12% to 42% for a Massachusetts buoy. No cited source gives a dated ship slowdown, cooperation change or avoided strike attributable to Whale Safe detections.", "replication": { "produced_by": [ "Moored acoustic buoy with onboard call detection and classification", "Human analyst review of detections", "Sightings and habitat-model data streams", "AIS vessel tracking and public cooperation grading", "NOAA voluntary speed reduction zones" ], "must_hold": [ "Buoy operation (both regional buoys were listed offline when the pages were consulted)", "Analyst capacity for review", "Shipping company attention to public grades", "Evaluation linking ratings to speed changes and strikes, not yet documented" ], "echoes": [ { "setting": "Massachusetts buoy used to reduce ship-strike risk for right whales in a US Coast Guard gunnery range (Baumgartner et al. 2019)", "outcome": "unknown", "source": "https://doi.org/10.1111/2041-210X.13244" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "replication" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" } }, "summary": { "total": 91, "addressed": 91, "known": 28, "reviewed": 0, "record_mapped": 28, "not_assessed": 63, "complete": false, "by_state": { "value_present": 28, "not_reported": 0, "unresolved": 0, "not_assessed": 63, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }, { "id": "AIBD-0550", "title": "Kent County Council: Using predictive analytics to prevent homelessness in Maidstone and Kent", "summary": "Kent reports under 1% homelessness among proactively supported households versus 40% in an unsupported comparator. The groups were not randomized.", "date_observed": "2026-10-22", "date_basis": "source access", "date_precision": "day", "benefit_status": "reported", "source_collection": "LGA AI case-study bank", "source_entry": "LGA-010", "account": "Kent describes Maidstone’s use of an AI-enabled Xantura platform to flag households for proactive homelessness support and a wider county pilot. The council presenter reports that fewer than 1% of supported alerted households became homeless, compared with 40% of a group that lacked support because of limited capacity. The comparison was not randomized and does not separate AI’s effect from the support intervention. Outcome dates are unspecified.", "category": "general benefit", "unexpected": false, "purpose": "Identify households at risk of homelessness so that councils can offer proactive support.", "system": "Xantura AI-enabled predictive-analytics platform used for homelessness prevention", "model_version": null, "developer": "Xantura", "deployer": "Maidstone Borough Council and Kent County Council with participating district and borough councils", "location": "United Kingdom", "domain": "Housing and homelessness prevention", "segment": null, "benefit_type": "Reduced Risk", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 4, "reason": "The council reports that proactive support prevented homelessness in a high-risk cohort. The groups were not randomized, and AI’s separate effect is unknown." }, { "group": "organizational", "depth": 2, "reason": "The reported prevention program improves targeting and preventive results for councils. The source does not supply sample sizes or an independent evaluation." } ], "ai_role": { "status": "unassessed", "statement": "The presenter describes an AI-enabled platform that combines council data and flags households for human support. The prevention comparison concerns the combined targeting-and-support program. Because support was capacity-constrained and not randomized, AI’s separate contribution to the difference is not established." }, "evidence": [ { "kind": "report", "citation": "Kent County Council video presentation published by the Local Government Association, with an automated transcript. Outcomes are reported by the council and have not been independently evaluated.", "title": "Kent County Council: Using predictive analytics to prevent homelessness in Maidstone and Kent", "url": "https://www.youtube.com/watch?v=Nz5fzLtzO_Q", "date": null, "written_by": "deployer", "quote": null } ], "replication": { "produced_by": [ "Maidstone combined local data with data shared by Kent County Council, including social-care information.", "The comparison group did not receive proactive support because the housing team lacked capacity." ], "must_hold": [ "The presenter states that protected characteristics are not included in the live prediction model.", "The source does not establish causal conditions for reproducing the prevention result." ], "echoes": [] }, "paired_incident": null, "headline": "Kent reports fewer homeless households after targeted support", "metric": null, "comparator": null, "later": null, "value": null, "developer_country": null, "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-22", "change": "Added the case.", "source": "https://www.youtube.com/watch?v=Nz5fzLtzO_Q", "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0550", "catalog_version": "1.0.0", "source_fingerprint": "ee4a7830fdaf03869acf69ca708f39ebd27ab4056307efe6325d74879cafbbe4", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0550-source-0001" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Xantura", "deployer": "Maidstone Borough Council and Kent County Council with participating district and borough councils" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The presenter describes an AI-enabled platform that combines council data and flags households for human support. The prevention comparison concerns the combined targeting-and-support program. Because support was capacity-constrained and not randomized, AI’s separate contribution to the difference is not established." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "The council reports that proactive support prevented homelessness in a high-risk cohort. The groups were not randomized, and AI’s separate effect is unknown." }, { "group": "organizational", "depth": 2, "reason": "The reported prevention program improves targeting and preventive results for councils. The source does not supply sample sizes or an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "low", "evidence_word": "claimed", "claim_status": "The deployer's account", "basis": "Sources: the deployer's report. The cited evidence includes no independent source and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "The council reports that proactive support prevented homelessness in a high-risk cohort. The groups were not randomized, and AI’s separate effect is unknown." }, { "group": "organizational", "depth": 2, "reason": "The reported prevention program improves targeting and preventive results for councils. The source does not supply sample sizes or an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "value_present", "value": { "kind": "text", "text": "Reported benefit" }, "provenance": { "kind": "legacy_record", "basis": "Mapped from the existing case description without a new external source review.", "record_fields": [ "benefit_status" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "personal", "depth": 4, "reason": "The council reports that proactive support prevented homelessness in a high-risk cohort. The groups were not randomized, and AI’s separate effect is unknown." }, { "group": "organizational", "depth": 2, "reason": "The reported prevention program improves targeting and preventive results for councils. The source does not supply sample sizes or an independent evaluation." } ] } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ratings" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].missingness": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].proposition": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "cross_border_flows[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "decisions[].action_outcome": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].grounds": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].institution_task": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "decisions[].success_criterion": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "institutional decisions" }, "deployment_stage": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "economics[].amount": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].costs[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].counterfactual": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].currency_price_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].gross_net": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].measure_type": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].period_unit": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].realization": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].recipient_payer": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].return_payback": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "economics[].valuation_method": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "monetary observations" }, "evaluations[].ai_uplift": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].comparator": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": "evaluations" }, "evaluations[].design": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "family": 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